pursuing the good life: engagement, and …cb008zb6473/... · investigation had two overarching...

PURSUING THE GOOD LIFE:

AN EXAMINATION OF PURPOSE, MEANINGFUL

ENGAGEMENT, AND PSYCHOLOGICAL WELL-BEING

IN EMERGING ADULTHOOD

A DISSERTATION

SUBMITTED TO THE SCHOOL OF

EDUCATION AND THE COMMITTEE ON

GRADUATE STUDIES

OF STANFORD UNIVERSITY

IN PARTIAL FULFILLMENT OF THE

REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

Matthew Joseph Bundick

December 2009

http://creativecommons.org/licenses/by-nc/3.0/us/

This dissertation is online at: http://purl.stanford.edu/cb008zb6473

© 2010 by Matthew Joseph Bundick. All Rights Reserved.

Re-distributed by Stanford University under license with the author.

This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.

ii



http://purl.stanford.edu/cb008zb6473

I certify that I have read this dissertation and that, in my opinion, it is fully adequatein scope and quality as a dissertation for the degree of Doctor of Philosophy.

William Damon, Primary Adviser


Richard Shavelson, Co-Adviser


John Krumboltz


Shirley Feldman

Approved for the Stanford University Committee on Graduate Studies.

Patricia J. Gumport, Vice Provost Graduate Education

This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file inUniversity Archives.

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iv

ABSTRACT

Emerging adulthood represents a critical phase for the development of purpose in

life, yet little is known about the process through which young people become

purposeful, or what the lasting benefits of such purposefulness might be. The present

investigation had two overarching goals: 1) to advance the notion of meaningful

engagement as important toward purpose development, and 2) to test multiple

components of a process model through which meaningful engagement and purpose lead

to psychological well-being.

Specifically, four hypotheses were put to the test though three interconnec ted

studies. The first hypothesis, addressed in Study 1 using cross-sectional data, posited that

purpose and meaningful engagement would be associated with psychological well-being.

The second hypothesis proposed a mediational model, wherein the relationship between

meaningful engagement and psychological well-being would be mediated by purpose;

this hypothesis was tested first with cross-sectional data in Study 1 and again using

longitudinal data in Study 2. Third, a moderation hypothesis was tested on the temporal

relationship between purpose and psychological well-being, specifically that the

relationship would be stronger for those high in self-transcendent life goals. Finally,

Study 3 tested an intervention hypothesis to see whether engaging in deep reflection on

and discussion about one’s life goals can increase both purpose and, consequently,

psychological well-being.

The results showed partial confirmation of the hypotheses. The cross-sectional

analyses showed strong relations among meaningful engagement, purpose, and

psychological well-being, and provided support for the proposed mediational model.

v

However, the longitudinal analyses did not show significant relations among the

constructs. The moderation hypothesis did provide evidence that the path from purpose to

well-being was stronger for those high on self- transcendent life goals, suggesting

psychological benefits of pursuing purposes beyond oneself (but not self-oriented life

goals). Finally, there was a significant positive effect of engaging in deep discussion and

reflection on one’s life goals, toward both increased purpose and increased psychological

well-being. Implications of these findings for higher education in particular are discussed,

and directions for future research are presented.

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ACKNOWLEDGEMENTS

For the many gifts of knowledge, guidance, and support that have been bestowed

upon me along this long and winding road—by friends, family, mentors and colleagues

alike—I can only begin here to express my deepest gratitude.

First, I would like to acknowledge my professional indebtedness to the present

and past scholars in the Stanford Center on Adolescence with whom I have worked on

the Youth Purpose Project, most importantly my advisor, Bill Damon, on whose

incredibly broad intellectual shoulders I have attempted to stand (and to whom I will be

forever grateful for the opportunity). I will refrain from individually naming the rest of

my colleagues on this project who have not only influenced me and my thinking, but who

also laid the theoretical and empirical groundwork upon which my present framework

and studies were founded. Though my current work does not completely reflect the

theory advanced and research questions taken on by the Youth Purpose Project, much of

my thinking and the majority of my data originated in this project, and I am tremendously

appreciative for the experience and the access.

My further professional thanks go out to Rich Shavelson, Shirley Feldman, and

John Krumboltz, for their investments in me through the dissertation process (and

throughout my graduate career) as members of my various committees including reading

and oral committees, as well as Sheri Sheppard for her willingness to fill the role of my

committee University Chair. In particular, Shirley has served as a wonderful academic in-

house counsel since the beginning, and Rich has provided me not only invaluable advice

but opportunities to broaden my scholarly horizons in ways that will no doubt serve me

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well long into my professional future. Additionally, I would like to thank the John

Templeton Foundation and the Thrive Foundation for Youth for their support of the

Youth Purpose Project and the present research, in particular the Thrive crew for the

amazing relationships I have built with them and their close-knit affiliates.

For all the friends and family who have supported me along the way, I cannot

offer enough thanks. My life has been enriched more than I could have imagined by the

friendships I have built during my time in graduate school, in ways that will no doubt last

long into the future. My parents, Joe and Paulette, are and will always be the rocks upon

which my life and whatever successes it might bring have been built. And finally, to my

wife, Jackie, I owe absolutely everything.

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TABLE OF CONTENTS

Page

ABSTRACT iv

ACKNOWLEDGEMENTS vi

LIST OF TABLES xii

LIST OF FIGURES xiv

CHAPTER 1: INTRODUCTION 1

Introduction 1

Definition and Measurement Issues 4

Definitional Issues 5

Purpose 5

Meaningful engagement 12

Psychological well-being 17

Measurement Issues 21

Purpose 21

Meaningful engagement 24


Review of the Empirical Literature 30

Purpose and its Relations with Well-Being and Engagement 31

Meaningful Engagement and its Relations with Purpose

and Well-Being 38

Summary 41

CHAPTER 2: CONCEPTUAL FRAMEWORK 43

Definitions of the Constructs 43

Purpose 43

Meaningful Engagement 48

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Psychological Well-Being 49

Conceptual Model 51

Research Questions and Hypotheses 58

CHAPTER 3: EMPIRICAL APPROACH AND MEASUREMENT

ISSUES 62

Overview 62

Measurement Issues 63

Method 64

Participants and Procedure 64

Missing Data 66

Measures 68

Meaningful Engagement 68

Purpose and Psychological Well-Being 77

Purpose 79


Measurement Model 84

CHAPTER 4: STUDY 1 – A CROSS-SECTIONAL TEST OF THE MEDIATIONAL MODEL 96

Overview and Predictions for Study 1 96

Method 96


Measures 97

Analytic Procedures 97

Results 97

Relations among Purpose, Meaningful Engagement, and


Testing the Mediational Model 99

Study 1 Discussion 101

x

CHAPTER 5: STUDY 2 – LONGITUDINAL RELATIONS AMONG MEANINGFUL ENGAGEMENT, PURPOSE, AND

PSYCHOLOGICAL WELL-BEING 106


Overview of Data and Measurement Approach 111

Method 112


Attrition 113

Measures 114

Mediation Measurement Model 119

Measurement Invariance 124

Results 127

Mean Differences 127

Testing the Longitudinal Mediational Model 129

Testing the Longitudinal Moderation Hypothesis 132

BTS-orientation of life goals as moderator 133

Self-orientation of life goals as moderator 137

Study 2 Discussion 139

CHAPTER 6: STUDY 3 – EXPLORATION OF A ―PURPOSE INTERVENTION‖ 143


The Purpose Interview 146

Purpose Interview as Purpose Intervention 147

Method 151


Attrition 153

Measures 154

Analytic Plan 156

Study 3 Results and Discussion 158

Purpose 158

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CHAPTER 7: GENERAL DISCUSSION 166

Summary of Conceptual Framework 166

Summary of the Main Findings 168

Implications 174

Limitations 176

Future Directions 178

APPENDICES 181

Appendix A. Relevant Youth Purpose Project Survey Materials and Sample Page from Online Survey 181

Appendix B. Results of Exploratory Factor Analyses from Chapter Three 187

Appendix C. Youth Purpose Project Interview protocol 195

REFERENCES 197

xii

LIST OF TABLES

Page

Table 1 Exploratory Factor Analysis of Meaningful Engagement Items

with Oblique Rotation 71

Table 2 Descriptive Statistics for Meaningful Engagement Activity

Domain Subscales 72

Table 3 Descriptive Statistics for Purpose Parcels 82

Table 4 Descriptive Statistics for Psychological Well-Being Parcels 83

Table 5 Summary Statistics of the Competing Confirmatory Factor

Analysis Models 94

Table 6 Correlations among Purpose, Meaningful Engagement, and


Table 7 Descriptive Statistics for Categories of Purpose Items 116

Table 8 Final Results of Exploratory Factor Analysis of Categories of

Purpose Items 118

Table 9 Results of Longitudinal Confirmatory Factor Analysis for

Meaningful Engagement, Purpose, and Psychological Well-Being

– Factor Loadings 122

Table 10 Results of Longitudinal Confirmatory Factor Analysis for

Meaningful Engagement, Purpose, and Psychological Well-Being

– Factor Intercorrelations 123

Table 11 Mean Differences in Meaningful Engagement Domains from

Time 1 to Time 2 128

Table 12 Latent Mean Differences in Purpose, Meaningful Engagement,

and Psychological Well-Being from Time 1 to Time 2 129

Table 13 Descriptive Statistics for Study 3 Purpose and Psychological Well

Being Measures Across Interviewee/Non-Interviewee Groups 155

Table 14 First Run of Exploratory Factor Analysis of Meaningful

Engagement Items with Oblique Rotation – Five Factor Solution 187

xiii

Table 15 First Run of Exploratory Factor Analysis of Meaningful

Engagement Items with Oblique Rotation – Three Factor Solution 188

Table 16 Exploratory Factor Analysis of Purpose-Related Items with

Oblique Rotation – One Factor Solution 190

Table 17 Exploratory Factor Analysis of Purpose-Related Items with

Oblique Rotation – Two Factor Solution 191

Table 18 Exploratory Factor Analysis of Psychological-Well-Being

Related Items with Oblique Rotation – One Factor Solution 193

xiv

LIST OF FIGURES

Page

Figure 1 Schematic representation of mediational model 53

Figure 2 Schematic representation of mediational model with moderation 58

Figure 3 Means of meaningful engagement domain subscale scores 75

Figure 4 Measurement model for meaningful engagement, purpose, and

psychological well-being 88

Figure 5 Confirmatory factor analysis of meaningful engagement,

purpose, and psychological well-being results 91

Figure 6 Mediational model of purpose, meaningful engagement, and

psychological well-being 100

Figure 7 Hypothesized two-wave longitudinal mediational model 107

Figure 8 Moderation model of BTS-orientation of life goals moderating

the relationship between purpose and psychological well-being 111

Figure 9 Longitudinal measurement model for meaningful engagement,

purpose, and psychological well-being 120

Figure 10 Results of longitudinal cross-lagged structural model of purpose,

meaningful engagement, and psychological well-being 131

Figure 11 Results of moderation model of BTS-orientation of life goals

moderating the relationship between purpose and psychological

well-being 135

Figure 12 Results of moderation model of self-orientation of life goals

moderating the relationship between purpose and psychological

well-being 138

Figure 13 Adjusted means of purpose scores at pre-test and post-test 159

Figure 14 Adjusted means of psychological well-being scores at pre-test

and post-test 163

Figure 15. First run of exploratory factor analysis of meaningful 189

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engagement items – scree plot

Figure 16. First run of exploratory factor analysis of purpose items – scree

plot 192

Figure 17. First run of exploratory factor analysis of psychological well

being items – scree plot 194

1

CHAPTER 1: INTRODUCTION

Introduction

One of the most fundamental of human endeavors is the quest to understand why

we are here, what our purpose in life is. The Japanese call it ikigai, or ―the thing for

which one lives;‖ the French, raison d'être, or ―reason for being.‖ Philosophers from

Plato and Aristotle to Jeremy Bentham and Friedrich Nietzsche have contemplated why

we exist, what makes life most worth living. Religions offer their own answers to the

―ultimate question,‖ from serving and glorifying a divine power (a common notion in

monotheistic Western religions such as Christianity, Judaism, and Islam) to living in

harmony with nature and/or one’s true self (characteristic of many Eastern schools of

thought like Hinduism and Taoism). More recently, psychology has taken on the task of

investigating from a more scientific perspective how we make sense of our own lives,

from what sources we derive meaning, what role purpose has in the broader context of

our being. From this psychological perspective, the question has little to do with what the

purpose of all life is; instead, the focus is more on what each person understands the

purpose (or purposes) of his or her life to be, and how this understanding and the pursuit

of such purposes affect and are affected by other psychological and behavioral constructs.

Though the field has been slow to incorporate such higher- level belief systems into

models of human understanding, motivation, well-being, and action (Damon, Menon, &

Bronk, 2003), in recent years there has been a surge of interest, as well as many

theoretical and empirical advances, in understanding the role of purpose in human

thought and behavior (e.g., Baumeister, 1991; Damon, 2008; Ryff, 1989a).

2

The current investigation aims to further our understanding of the role that

purpose in life might play in psychological well-being (PWB) during emerging

adulthood. My two overarching objectives are to advance the underappreciated construct

of meaningful engagement as an important component of living the good life, and to

establish whether purpose and meaningful engagement are causally related 1 to PWB in

the emerging adult years. Toward those ends, this dissertation is broken into seven

chapters that fall into four general sections. The first section (comprising Chapters 1 and

2) focuses on theory. I review the literature on purpose, meaningful engagement, and

PWB, and offer an integrative conceptual framework for my empirical investigation. I

pay special attention to the distinction between purpose and meaning, as some conceptual

confusion has plagued the literature in this area. And I advance the concept of

―meaningful engagement,‖ which I argue has been large ly overlooked in the literature. In

the second section (including Chapter 3), I cover some of the measurement-related issues

germane to operationalizing my definitions of the constructs, and put forth a

measurement model.

The third section (covering Chapters 4, 5, and 6) comprises my empirical

arguments. Through three studies, I address my four research questions: 1) Are purpose

and meaningful engagement associated with PWB in emerging adulthood? 2) If so, does

purpose mediate the relationship between meaningful engagement and PWB? 3) Is the

relationship between purpose and PWB moderated by the presence of an orientation

toward self-transcendent life goals? 4) Can engaging in deep reflection and discussion

1 I use the phrase ―causally related‖ intentionally—though very cautiously—as the problems with inferring

causation from observational data are well-known (e.g., Rubin, 1991). I believe the phrase is appropriate

because my analyses involve testing a temporal causal hypothesis, and employ an experimental

intervention design from which, under the proper circumstances, causation may be inferred.

3

about purpose function as a ―purpose intervention,‖ increasing purpose and,

consequently, PWB? In the final section (including Chapter 7), I summarize and discuss

the implications and limitations of the results of these analyses, and address how might

they advance practice in educational settings, in particular, institutions of higher

education.

Purpose in life has been studied at various developmental stages across the life

span, from early adolescence (e.g., Bronk, 2008; Damon, 2008) through old age (e.g.,

Pinquart, 2002; Ryff, 1989b). Emerging adulthood refers to the years between late

adolescence and early adulthood (roughly, ages 18-25) which are typically marked by

identity explorations, instability, self- focus, revision of life priorities and goals, and

possibilities (Arnett, 2004), and thus represents a particularly important life phase in the

development of purpose. Identity development—which is an integral aspect of

establishing a life purpose (Damon, 2008)—is ongoing and potentially formative in these

years (see also Erikson, 1968; Luyckx, Goossens, & Soenens, 2006). What and who one

wants to be is particularly salient as young people commence through the normative

transition from bearing few significant life commitments and responsibilities in high

school or college to the shouldering of many (e.g., starting a career, getting married,

having children; Settersten, Furstenberg, & Rumbaut, 2000). Moreover, the identity-

relevant notion of generativity, or one’s ―concern for and commitment to promoting the

well-being of future generations‖ (McAdams, 2006, p. 82), while typically considered a

manifestly adult developmental issue, is thought to have its developmental roots in

emerging adulthood (Frensch, Pratt, & Norris, 2007) and may be strongly related to

purpose (Damon et al., 2003).

4

Additionally, the college student development literature has acknowledged the

central role of purpose in the college years, which typically overlap with emerging

adulthood.2 For example, Chickering’s (1969, Chickering & Reisser, 1993) ―Seven

Vectors of College Student Development‖ theory identifies purpose development as a

core developmental task. Astin (2004) suggests that cultivating purpose and meaning

ought to constitute ―one of the central purposes of higher education‖ (p. 34). College and

university student affairs practitioners have acknowledged the centrality of purpose in the

lives of their students and its relevance to their practice, and have joined the call for a

more deliberate and concentrated effort to develop college students’ senses of purpose

and meaning in life (e.g., Moran, 2001; Robinson, Sterner, & Johnson, 2006). Braskamp,

Trautvetter, and Ward (2006) describe efforts to address the development of purpose and

meaning in college students (along with the rest of the ―whole student‖) through joint

efforts by all members of a campus community, calling in particular for faculty and

student affairs professionals to work together toward this important end. The degree to

which these emerging adults engage in activities they find meaningful and begin directing

themselves—and receive guidance from others—toward a set of coherent life goals

stands to have significant consequences for their successful transition to adulthood and

overall well-being.

Definitional and Measurement Issues

The constructs of purpose, meaningful engagement, and psychological well-being

have each been conceptualized in a variety of different ways in the psychological

2 However, this is changing; non-traditional students (including adults older than 25 years) increasing

constitute undergraduate enrollments in institutions of higher education in the United States (National

Center for Education Statistics, 2002).

5

literature. As such, in the current section I address these constructs one at a time and for

each present an overview of the assortment of theoretical frameworks and definitions that

have been proposed and investigated, as well as a range of instruments used for their

assessment. I then provide a brief review of the literature which addresses the relations

among these constructs, which guides my conceptual framework, research questions, and

hypotheses (as presented in Chapter Two).

Definitional issues

Purpose. The psychological study of purpose and meaning in life has its roots in the

philosophical writings of Frankl (1963), who focused on the importance of sensing

meaning toward psychological health (i.e., absence of mental illness, such as depression)

and the protective role of having a purpose with regard to enduring significant life

hardships.3 One of the central tenets of Frankl’s work on purpose in life was the idea of

―noogenic neurosis‖ (from Greek nous, referring to the human spirit; and ―neurosis,‖ or

mental disorder), which is the consequence of what he called ―existential frustration‖

culminating in an ―existential vacuum,‖ or lack of meaning in life. Inspired by Frankl’s

writings, Crumbaugh and Maholick (1964; 1969; Crumbaugh, 1968) took up the

scientific study of purpose and meaning. These authors extended the notion of noogenic

neurosis to studies of clinical populations, defining it as ―the ontological significance of

life from the point of view of the experiencing individual‖ (Crumbaugh & Maholick,

1964, p. 201) and operationalizing it through their Purpose in Life Test (see below for a

review of purpose measures).

3 Frankl was a survivor of the Holocaust, and drew often on his experience in h is writings.

6

Many theorists and researchers have since offered their own conceptualizations

and operationalizations of purpose and meaning in life, most of whom have notably used

the terms interchangeably. Some have focused on the degree to which one sees one’s life

as coherent and understandable (e.g., Battista & Almond, 1973; Reker & Wong, 1988);

others have focused more on a global sense that one’s life is generally significant (e.g.,

Baumeister, 1991; Yalom, 1980) or that one is broadly oriented toward the future and

directed toward one’s goals (e.g., Ryff, 1989a). However, not until Damon et al. (2003)

had anyone tackled the distinction between purpose and meaning. According to these

authors, purpose refers to ―a stable and generalized intention to accomplish something

that is at once meaningful to the self and of consequence to the world beyond the self‖ (p.

121). The stability component reflects that one’s purpose is deeply rooted in one’s

identity and has a life- long time horizon. The generalized notion suggests that it operates

across multiple life domains; in other words, one’s decisions and actions in all areas of

one’s life are affected by one’s purpose, and not isolated to a single domain such as

family or career. This definition centrally highlights the far-reaching, abstract life goal

aspect of purpose (i.e., the intention to accomplish something), which has as ―its

necessary characteristic… not its concreteness but the sense of direction that it provides

in creating an objective‖ to be pursued, which in turn organizes one’s lower- level goals,

decisions, and actions (Damon et al., 2003, p. 121; see also Damon, 2008).

In presenting the contrast between purpose and meaning, Damon et al. (2003)

assert that meaning is more akin to a global (and perhaps more affective) sense which

need not be tied to a particular life goal: ―Unlike meaning alone (which may or may not

be oriented towards a defined end), purpose is always directed at an accomplishment

7

towards which one can make progress‖ (p. 121). In this way, purpose is similar to

Emmons’ (1999) notion of ―ultimate concerns‖ in life, which he defines as ―the multiple

personal goals that a person might possess in striving toward the sacred‖4 (p. 6). Damon

et al.’s conceptualization is also akin to Roberts and Robins’s (2000) formulation of

―major life goals,‖ which ―involve a person’s aspirations to shape their life context and

establish general life structures such as having a career, a family, a certain kind of

lifestyle, and so on‖ (p. 1285). These authors drew upon not only previous goal theories

but also the values literature, reflecting their belief that values ―represent a basic level in

the motive domain… that could be used to organize major life goals‖ (p. 1286). In this

way, a major life goal, like a purpose, ought to be congruent with and intimately tied to

one’s value system and personal identity; indeed, a purpose might be thought of as a

cognitive manifestation of one or more of one’s deepest-held values.

Similar notions of relatively higher-order goal structures have been advanced and

studied in the psychological literature, though they are generally more contextualized and

largely lack the long-term time horizon characteristic of a life purpose. Some examples of

these more mid-level goal units include ―personal strivings‖ (Emmons, 1986) defined as

―what a person is characteristically trying to do‖ in accordance with one’s ―characteristic

goal-directed trends‖ in life (p. 1059); ―personal projects‖ (McGregor & Little, 1998),

which are ―self-generated accounts of what a person is doing or is planning to do‖ and

4 This use of the word ―sacred‖ may be seen to imply spirituality. To be clear, purpose does not necessarily

(though certainly may) have a spiritual component. In the popular literature, the term ―purpose‖ has in

recent years often been associated with Rick War ren’s (2002) best-selling book, A Purpose-Driven Life:

What On Earth Am I Here For? which defines purpose in decidedly religious terms (i.e ., in the Judeo-

Christian sense). This is a perfect ly valid understanding of purpose—indeed, Klinger (1977) suggested that

―people’s purposes can be either the things they intend to do or the things they are put on earth for… the

second of these meanings poses a theological question, rather than a psychological or social-scientific one,

that we shall [therefore] not cons ider further‖ (p. 5). I, and (I think it is safe to say) the majority of my

colleagues who take an academic approach to studying purpose, concur.

8

can range from daily tasks to larger life goals (p. 495; see also Little, 1983); ―life tasks‖

(Cantor, Norem, Niedenthal, Langston, & Brower, 1987), defined as ―the set of tasks that

the person sees himself or herself working on and devoting energy to solving during a

specified period in life‖ (p. 1179); and ―current concerns‖ (Klinger, 1977), which are

valued goals around which one’s current thoughts, plans, and actions are organized.

Though not the same as purpose, these types of goals are likely relevant to purpose in that

they occupy one level down in one’s goal complex (Elliot & Thrash, 2002) and may be

directed toward the accomplishment of one’s purpose.

In recent years the field has begun to recognize and adopt Damon et al.’s (2003)

distinction between purpose and meaning, and coalesce around the conceptualization of

purpose as an overarching life goal with a long-term time horizon. Kashdan and

McKnight (in press) have suggested purpose is ―a central, self-organizing life aim‖ (p. 3)

that is a predominant component of one’s identity, provides a framework for one’s goals

and actions, and motivates one to allocate personal resources toward its actualization.

These authors further posit that ―as a life aim, a purpose cannot be achieved…‖ and

instead functions as a ―continual target for efforts to be devoted‖ (p. 4). Similarly, Steger

(2009) integrates a purpose component into his conceptual framework of meaning in life,

and refers to purposes as ―highly motivating, long-term goals about which people are

passionate and highly committed‖ (p. 679). In Steger’s model, having a global sense of

meaning in life emerges from the combination of purpose and what he called ―life

comprehension,‖ the latter integrating an understanding of 1) onese lf, 2) the surrounding

world, and 3) the interaction of the two, wherein one can find one’s ―particular niches,

roles, and degree of fit people perceive for themselves in the world‖ (p. 681).

9

However, Kashdan and McKnight’s (in press) and Steger’s (2009)

conceptualizations (along with those that concern mid- level goals) differ from Damon et

al.’s (2003) in that the latter authors’ notion directly addresses life goal content.

Specifically, they propound that purpose has a necessarily externa l, ―beyond-the-self‖

(BTS) aim, whereas a general sense of meaning may be derived from either self- or BTS-

oriented goal pursuits (see also Baird, 1985). Put another way, in these authors’

framework there are two types of major life goals, one that has as its primary intent the

benefit of the world beyond oneself (a purpose), and another that has as its primary intent

the benefit of the self (a self-oriented life goal). Indeed, this conceptualization of purpose

extends Frankl’s (1988) notions of responsibility and ―giving to the world,‖ which

emphasize the essential nature of self-transcendent goals toward experiencing purpose in

its deepest sense (see also Reker & Wong, 1998). To this end, a purpose may function not

only as a life aim, but as a ―moral beacon‖ which motivates one to commit to and engage

in prosocial, generative behaviors in adolescence and the years to follow (Damon, 2008;

Moran, in press).

Damon et al.’s (2003) self- vs. BTS-orientation distinction regarding the content

of one’s purpose represented a new way of categorizing types of purposes, but the idea

that meaning may be derived from different types or sources of goal pursuits has been

around for some time. DeVogler and Ebersole (1980) explored sources of meaning

among college students via an idiographic essay documentation technique, and

categorized what they found to be the most common sources into eight groups: beliefs,

existential-hedonism, expression, growth, obtaining, relationships, service, and

understanding. O’Connor and Chamberlain (2000) took a similar idiographic approach,

10

and found the sources of meaning generated by their participants grouped into six

categories: relationships with others, creativity, personal development,

religion/spirituality, and relationships with nature.

Some scholars have taken the exploration of sources a step further, and employed

both qualitative and statistical techniques to reduce the number of categories into more

fundamental clusters. Prager, Savaka, and Bar-Tur (2000) investigated a variety of

sources of meaning in a sample of Jewish and Arab adults ages 20-40 and 60-97, and

used exploratory factor analysis to cluster them into eleven factors: family/communal

values, materialistic concerns, life satisfaction/autonomy, sense of connectedness,

communal awareness/national pride, attainment of tranquility, self-development/aesthetic

pursuits, family relationships, leisure activities away from home, love for animals, and

relationships with one’s partner. Guided discussions with focus groups led the authors to

propose four basic dimensions of meaning: 1) material comforts, 2) self-realization, 3)

―areas of meaning lying beyond the realm of self- interest‖ (i.e., other-oriented), and 4)

sources of meaning that transcend self and others, or ―cosmic meaning‖ (p. 134). As

reported by Van Ranst and Marcoen (2000), Reker (1991) also applied exploratory factor

analysis to reduce a larger list of categories of sources of meaning to three ―levels of life

goal orientations:‖ self-preoccupation (which included sources such as financia l security,

seeking pleasure), individualism (engaging in leisure and creative activities, having high

achievement), and self-transcendence (comprising personal relationships, societal causes,

religious activities, and altruism).

Reker’s (1991) factors of self-preoccupation and individualism, along with Prager

et al.’s (2000) groupings of material comforts and self-realization, correspond to Damon

11

et al.’s (2003) self-orientation of life goals. Though these types of goals may have

(perhaps inadvertent) beyond-the-self consequences, the primary intention behind them is

to advance one’s self- interests. For example, one may have as her most important goal in

life to invent new technologies for speeding up computer processors—while such an

invention would likely benefit many other people, if the inventor’s primary intentions

were to meet a challenge in her professional area of interest and gain recognition for her

work, this would constitute a self-oriented life goal. In contrast, Prager et al.’s groupings

of ―other-oriented‖ and ―cosmic‖ and Reker’s ―self- transcendence‖ would reflect Damon

et al.’s BTS-orientation. Though this body of research on sources of meaning may not

fully encapsulate the notion of life goals (i.e., some of the sources, such as personal

relationships and engaging in leisure, may lead to a sense of meaning without having any

particular goals associated with them), these studies offer preliminary insights into the

kinds of purposes to which people may aspire. Importantly, they also reveal that different

people derive meaning from different kinds of sources, which in turn may influence one’s

life goals (Reker, 2000).

The motivation literature has likewise addressed the content of one’s goals, and

the adaptiveness of certain goals with regard to well-being (e.g., Brandstädter & Renner,

1990; Emmons, 1986; Little, 1983). However, these studies typically focus on the

aforementioned mid- level goal units such as personal strivings and life tasks, which may

be less informative for the investigation of a higher- level construct like purpose.

Moreover, the frameworks and dichotomies typically found in these literatures, such as

approach vs. avoidance (Elliot & Harackiewicz, 1996), intrinsic vs. extrinsic (deCharms,

1968; Deci & Ryan, 1985), and agency vs. communion (Bakan, 1966) are less applicable

12

to purpose. In accordance with the Damon et al. (2003) definition, purposes are almost

always approached rather than avoided, intrinsic rather than extrinsic, and ought to

incorporate both agentic and communal components. Moreover, this literature typically

does not address the distinction between self- vs. BTS-orientation at the level of

abstraction of higher- level life goals. Emmons (1999) does address the idea of level of

abstraction of goal content in general, suggesting that there are important motivational

consequences to holding more abstract and expansive higher- level goals (e.g., ―Deepen

my relationship with God‖ and ―Improve the lives of others‖) compared to more concrete

and actionable lower- level goals (e.g., ―Make others laugh‖ and ―Keep good posture‖).

His findings suggest that ―higher- level goals are rated as more important and more self-

defining that low-level goals [and] carry vital information about what a person finds

valuable, meaningful, and purposeful‖ (p. 54). However, he makes no distinction between

self- and BTS-orientation of these higher- level goals.

Though the goals and motivation literatures may not speak directly to higher- level

life goals, the research on the content of mid- level goals may offer insights into how

purpose operates with regard to meaningful engagement and PWB, and thus will be given

further treatment in the ―Review of the Empirical Literature‖ section later in this chapter.

Meaningful engagement. Among the many theoretical models of meaning and

purpose in life, there has been a surprising lack of focus on ―meaningful engagement.‖

Meaningful engagement refers to the degree to which one finds the activities in which

one is involved across the domains of one’s life to be worthwhile, important, and in

accordance with one’s values and sense of self (hence, meaningful). For example, as a

13

young adult, I am engaged in a variety of activities related to family, work/school,

community, leisure/aesthetic pleasures, and other life domains. The more I find the

activities in which I regularly engage across these domains to be personally significant

and consequential, the more meaningfully engaged I am in my life overall. Looking at it

another way, the more I find time to engage in the activities most important to me, the

more meaningfully engaged in my life I am likely to feel.

Many scholars in the field have acknowledged the importance of activity

engagement broadly, in the sense that meaning can be and often is derived from the daily

experiences of our lives (King, L.A., Hicks, Krull, & Del Gaiso, 2006). The literature on

sources of meaning has established that the degree to which activities confer meaning is

not universal (Baumeister, 1991; DeVogler & Ebersole, 1980; Reker & Wong, 1988).

According to the relativistic perspective on meaning in life there are no given activities in

which engagement is inherently meaningful (Battista & Almond, 1973). For example, on

average, engaging in religious activities has been found to be one of the most meaningful

human endeavors (Hill & Pargament, 2003); however, while devoutly religious people

generally derive deep meaning from attending worship services, atheists likely do not.

Similarly, people in general feel a great sense of purpose when volunteering in their

communities (Benson et al., 1980; Thoits & Hewitt, 2001), yet there are undoubtedly a

number of college-bound high school seniors who experience such engagement only as a

laborious chore necessary for college admission. Indeed, some graduate students interpret

writing a dissertation as the most meaningful activity in which they will engage in the

whole of their professional lives, while others decidedly do not. 5

5 Unlike the other examples, I can only cite anecdotal evidence for this latter point.

14

That said, the frequency of engagement in particular kinds of activities, especially

self-transcendent ones (e.g., volunteering, attending religious services), has been

associated on average with greater meaning in life (e.g., Reker & Wong, 1988; Steger,

Kashdan, & Oishi, 2008). According to Steger (2009), ―there is concordance around the

idea that meaning is most fully achieved when people actively engage in pursuits that

transcend their own immediate interests‖ (p. 683). Importantly, however, these studies

rarely if ever address the combination of the meaningfulness and frequency of

engagement in activities across life domains as a singular construct, as I am proposing in

my conceptualization of meaningful engagement.

Of the major theoretical frameworks reviewed herein, the only one that directly

addresses some formulation of engagement as an integral component of purpose is that of

Damon et al. (2003). Though not explicit in the wording of their original definition, these

authors later incorporated the notion of ―productive engagement,‖ which suggests one

must not only have beyond-the-self life aims to be fully purposeful, but must also be

actively working toward accomplishing these goals (see Bronk, 2006). In his formulation

of positive development, or ―thriving,‖ in youth, Damon (2008) emphasized the

importance of not only the beyond-the-self orientation and future direction of one’s life

goals, but also the meaningfulness of a young person's purposeful efforts toward those

goals. Notably, this notion of productive engagement in the Damon et al. (2003) model is

tied specifically to the purposeful intention (i.e., productive engagement in activities or

planning in service of that particular life goal); the conceptualization of meaningful

engagement espoused in this current investigation may, but need not be linked to any one

(or more) life goal(s). It is possible that a person who does not meet the criteria for

15

purpose is nonetheless meaningfully engaged in a variety of activities; or, that one who

has identified a life purpose may be engaged in a number of meaningful activities that are

entirely unrelated to one’s major life goal(s). For example, some might extract meaning

from engagement in activities like hiking or sailing or golfing, 6 perhaps from the

opportunity they present for some people to feel at peace with themselves and with

nature, even though such engagement may have nothing to do with their purpose in life.

There are other formulations in the psychological literature of constructs similar

to, yet notably different from, meaningful engagement. Csikszentmihalyi’s (1990) notion

of flow may be thought of as the deepest form of meaningful engagement. Flow is

characterized by full immersion in an activity that is intrinsically rewarding and

invigorating, provides a challenge level which fits one’s skill level, and draws one’s

complete attention. However, unlike meaningful engagement which has a wider scope of

the meaning one derives from an array of activities across all of life’s domains, flow

typically refers to an ephemeral (albeit very motivating) experience. Peterson, Park, and

Seligman (2005) extended Csikszentmihalyi’s (1990) flow in their conceptualization of

an ―engagement orientation to happiness,‖ which is perhaps more similar to meaningful

engagement in that it attempts to address the degree to which flow experiences are

characteristic of one’s life (i.e., it is viewed as a personality variable rather than an

experiential one). Still, the idea of engagement in their model remains focused on a

particular kind of meaningful experience—one in which the person is fully absorbed and

time passes quickly—while the current approach to meaningful engagement need not

involve such focused attention and engrossment.

6 For a contrasting viewpoint with regard to the latter of these engagements, see Feinstein (1995).

16

Beyond the positive psychology literature, there are several constructs akin to the

current conceptualization of meaningful engagement. One recent perspective, stemming

from the self-regulation literature (e.g., Carver & Scheier, 1998) and expectancy-value

models of motivation (e.g., Vroom, 1964), conceptualizes purpose in life as meaningful

engagement, or ―life engagement,‖ which refers to the ―the extent to which a person

engages in activities that are personally valued‖ (Scheier et al., 2006). This approach

suggests when one cannot find new meaningful activities in which to engage following a

necessary shift away from one’s usual repertoire of meaningful activities (such as is

common among athletes in post-retirement; see Gorbett, 1985), one is likely to feel one’s

life is without purpose. Scheier et al. (2006) suggest that lack of engagement and the

consequent lack of purpose puts at risk psychological as well as physical well-being (see

also Wrosch, Scheier, Miller, Schulz, & Carver, 2003).

The occupational science and social gerontology literatures provide a

complementary perspective to Scheier et al.’s (2006) notion of life engagement. Clark et

al. (1991) suggest that engagement in activities (especially those related to one’s

occupation) that are personally valued and meaningful will contribute to an individual’s

global sense purpose in life, which will in turn lead to enhanced overall well-being. This

claim has been substantiated in both qualitative (Jackson, 1996) and quantitative (Prager,

1996) studies of older adults, many who faced various declines in functioning. Two

prominent models of meaning in the context of the occupational and rehabilitation

sciences (Hammell, 2004a; King, G. A., 2004) incorporate among of their core

components the notion of ―doing,‖ which in both models refers to engagement in

purposeful goal-directed actions. Hammell (2004b) found that the dimensions most

17

important among people with physical impairments for ―experiencing and expressing

meaning through doing‖ included exploring new opportunities, engaging in prosocial

activities that contribute to others, and ―having something to wake up for‖ (i.e., a

purpose; p. 301).

Additionally, life-span developmental theories have acknowledged the centrality

of engagement in meaningful activities to positive development in old age. Rowe and

Kahn’s (1987) model of ―successful aging‖ holds as one of its four tenets ―active

engagement with life‖ (p. 433). Baltes and Baltes’s (1990) selection, optimization, and

compensation model of successful development and aging suggests engaging

meaningfully in the daily activities of one’s life contributes to the optimization process

(see also Schulz & Heckhausen, 1996). In his exploration of the use of leisure time and

well-being in aging populations, Kleemeier (1961) espoused ―the significance for older

persons of time usage and the meaning of activity‖ (p. 8). Herzog, Franks, Markus, and

Holmberg (1998) found in their study of older adults (65 and over) that engagement in

meaningful social activities (such as doing volunteer work) that reinforce one’s sense of

agency leads to better developmental outcomes.

Psychological Well-Being. The turn of the 21st century witnessed a sea change in the

way psychologists have come to understand mental health, ushered in largely by the

positive psychology (Seligman & Csikszentmihalyi, 2000), positive youth development

(Benson, 1990; Damon, 2004, Lerner, 2004), and successful aging (Baltes & Baltes,

1990; Rowe & Kahn, 1987) movements.7 These approaches advance a strengths-based

7 While the sea change may not have begun until late in the 20

th century, the groundwork for the positive

perspective on mental health was laid much earlier by the humanistic psychologists, most notably Abraham

18

rather than deficits-centered focus, suggesting psychological well-being constitutes not

only the absence of mental illness but also the presence of a wide array of positive

indicators of mental health. These positive psychological approaches are replete with

models of well-being, and the field has yet to galvanize around one framework for a

broad understanding of optimal mental health. It is likely the case that there is no one

such model that can be applied universally across life span; instead, the applicability of a

model of well-being may be contingent upon one’s developmental stage in life (see

Bundick, Yeager, King, P. E., & Damon, in press). From this perspective, the positive

youth developmental notion of ―thriving‖—which is distinct in its emphasis on future

direction and its integration of relational developmental systems theory—is most

appropriate for understanding adolescents who are passing through a formative phase in

development, while some of the positive psychological notions of well-being which focus

less on development and more on individual characteristics may be more applicable to

adults whose personalities are more likely to be stable (Roberts, Caspi, & Moffitt, 2001).

As the current investigation is geared primarily toward understanding emerging

adulthood, I will focus on the positive psychological (more adult-oriented) conceptions of

mental health. Some of the prominent frameworks in the positive psychological literature

include subjective well-being (Diener, 1984), psychological well-being (Ryff, 1989a),

flourishing (Keyes, 2002), self-determination theory (Ryan & Deci, 2000), and character

strengths (Peterson & Seligman, 2004). Though it is beyond the scope of the present

work to review each of these theoretical perspectives in depth, it is important to my

Maslow and Carl Rogers. Maslow’s (1970) formulation of self-actualizat ion, which he defined as the

―desire to become more and more what one id iosyncratically is, to become everything that one is capable of

becoming‖ (p. 22), advocated the maximization of one’s full potential as the highest human striving.

Rogers (1961) likewise sought to understand the pursuit of human potential and optimal functioning in his

notion of the ―fully-functioning person.‖

19

conceptual framework and operational definition of PWB that I address one thread of

debate which pervades each of them regarding the distinction between hedonistic and

eudaimonic well-being.

The positive psychology movement in social and personality psychology found

many of its roots in the work of Diener (1984, 2000) on subjective well-being, which

refers to ―people's cognitive and affective evaluations of their lives‖ (Diener, 2000, p.

34), or more colloquially, happiness. Subjective well-being comprises three essential

elements across two dimensions: 1) affective, or high positive affect and low negative

affect; and 2) cognitive, or life satisfaction (Andrews, 1974; Diener & Emmons, 1984).

According to Lucas, Diener, and Suh (1996), the affective components ―represent two

broad, underlying dimensions of basic emotions that consistently emerge‖ across various

situations and cultures, while the cognitive component refers to one’s global evaluation

of one’s life through which one ―examines the tangible aspects of his or her life, weighs

the good against the bad, and arrives at a judgment of overall satisfaction‖ (p. 616). These

two dimensions of subjective well-being are thought to be related yet distinct. Life

satisfaction is somewhat more stable and partially independent from one’s affective state

at the time of judgment (Schwarz & Strack, 1991).

Hedonism—the notion that humans should maximize pleasure and minimize

pain—has (for better or worse) been embraced in the new psychological subfield of

―hedonic psychology‖ (Kahneman, Diener & Schwarz, 1999). Being happy has been

consistently found to rank among the most important goals or desired states in people’s

lives (Suh, Diener, Oishi, & Triandis, 1998; Veenhoven, 1994), especially in Westernized

countries where basic needs are more likely to be met and higher order desires more

20

likely to be salient (Inglehart, 1990; Maslow, 1970). Indeed, it is the rare person who

does not strive to be happy—though what makes people happy may be highly

individualized (Diener & Fujita, 1995; Emmons, 1986).

However, subjective well-being, while an essential piece of the larger well-being

puzzle (Diener, Sapyta, & Suh, 1998), is limited in its ability to capture the full breadth of

positive mental health (Keyes, 1998; Ryan & Deci, 2001; Waterman, 1993). The pursuit

of ―the good life‖ involves much more than just the pursuit of happiness (Ryff, 1989a).

As noted by Waterman (1993), there can (and should) be made an important distinction

between hedonic enjoyment (or hedonia) and what Aristotle (350 B.C./1985) called in his

Nicomachean Ethics ―eudaimonia.‖ Hedonia refers to a certain kind of happiness

characterized by pleasure-seeking pursuits; in contrast, eudaimonia, though often also

translated to mean ―happiness,‖ focuses on our internal daimon or ―true self,‖ and refers

to the ―potentialities of each person, the realization of which represents the greatest

fulfillment in living of which each is capable‖ (Waterman, 1993, p. 678). Waterman

labeled the state of living in which one feels most authentic and alive, i.e., living in

accordance with one’s daimon, as ―personal expressiveness,‖ and suggested that this state

is most likely to occur when one is engaged in activities congruent with one’s deepest

held values and life goals. In this view, following from the humanistic theories of

Maslow (1970) and Rogers (1961), it is from the well of the pursuit of self- realization

and the fulfillment of one’s unique potential that the good life most fruitfully springs.

Many of the prominent theories of PWB are grounded primarily in this

eudaimonic perspective (Peterson & Seligman, 2004; Ryff, 1989a; Ryan & Deci, 2000),

while others incorporate a balance of hedonic and eudaimonic components (Keyes, 2002;

21

Peterson et al., 2005). Each of these theories, either implicitly or explicitly, acknowledges

the importance of purpose to both eudaimonic and hedonic well-being, as my review of

the literature which relates purpose to PWB in the sections to follow will show.

Measurement issues

Purpose. Given the multitude of definitions of purpose that have been proposed in

the psychological literature, it should be unsurprising that there are a multitude of

assessment tools to accompany them. Though some scholars have very effectively

employed qualitative approaches, such as interview and essay methodologies (e.g.,

Damon, 2008; DeVogler & Ebersole, 1980), the preponderance of research on purpose in

life has measured purpose and meaning via self-report survey instruments. The most

commonly used has been Crumbaugh and Maholick’s (1969) Purpose in Life test, which

is a 20- item Likert personality questionnaire designed to operationalize Frankl’s concept

of the existential vacuum. It has been tested in diverse populations and a variety of

settings, and has demonstrated favorable internal consistency and temporal stability

across a number of studies (Crumbaugh & Maholick, 1969; Zika & Chamberlain, 1992).

At the same time, the Purpose in Life test has been criticized on primarily conceptual

grounds, namely for conflating aspects of purpose and meaning (Damon et al., 2003) and

being confounded on an item level with many of the constructs to which its creators

sought to establish relationships, such as depression, affect, and general well-being

(Dyck, 1987; Steger et al., 2006). Indeed, this flaw significantly handicaps the Purpose in

Life test in investigations of the relations among purpose and other well-being constructs.

22

Another frequently-used questionnaire measuring purpose, the Life Regard Index

(28 items, Likert scale; Battista & Almond, 1973) also demonstrates strong psychometric

properties (Debats, 1990), but has been similarly criticized. As a case in point, both of

these measures include an item which assesses the degree to which one ―feels really good

about [one’s] life,‖ which may be more likely to tap a broader well-being construct such

as life satisfaction than it does purpose. Other lesser-used measures of purpose, such as

the Life Attitude Profile (Reker & Peacock, 1981) and Life Attitude Profile-Revised

(Reker, 1992), the Sense of Coherence scale (Antonovsky, 1987), and the Seeking Noetic

Goals Scale (Crumbaugh, 1977), have also suffered from validity issues (Dyck, 1987)

and a ―muddling of the nomological network‖ (Steger et al., 2006, p. 81).

Two other measures, Ryff’s (1989) Purpose in Life subscale of her Scales of

Psychological Well-Being (PWB-P) and Steger et al.’s (2006) Meaning in Life

Questionnaire-Presence subscale (MLQ-P), show more promise as reliable and valid

measures of purpose and have been widely used. The PWB-P is a 20-item Likert scale

designed to assess the degree to which one ―has goals, intentions, and a sense of

direction‖ in life (Ryff, 1989a, p. 1071). It has been shown to be psychometrically sound

and has demonstrated strong convergent and discriminant validity (Morgan & Farsides,

2008; Ryff, 1989a; Ryff & Keyes, 1995), and is increasingly commonly used to assess

purpose and goal-directedness (van Dierendonck, 2005). Though the items of this scale

do not specifically address whether one has identified and is pursuing a specific life aim

per the definitions of purpose offered by Damon et al. (2003), Kashdan and McKnight (in

press), and Steger (2009), they do tap generally into the degree to which one is oriented

23

toward pursuing and accomplishing one’s life goals (sample item: ―Some people wander

aimlessly through life, but I am not one of them‖).

The MLQ-P, a short (five- item) Likert scale, has likewise demonstrated strong

psychometric properties and in a short amount of time has become a popular measure in

the meaning literature (likely due as much to its brevity as its strong conceptual worth).

Despite its title, it can be argued based on item content that the Meaning in Life

Questionnaire – Presence subscale is much more a measure of purpose than meaning.8

Three of the five items use the word ―purpose‖ to directly inquire about the degree to

which one has found a purpose in one’s life (e.g., ―I have found a satisfying life

purpose‖); the two remaining items that do not use the word ―purpose‖ ask whether

respondents have identified what in their lives accords them meaning (e.g., ―I have a

good sense of what makes my life meaningful‖). Though these two items use the word

―meaning‖ rather than ―purpose,‖ they nonetheless seem to address whether respondents

understand their source(s) of meaning (like a purposeful life goal) more than they do the

extent to which respondents are more globally sensing or experiencing their lives to be

meaningful. Notably, neither the PWB-P nor the MLQ-P address the content of one’s

purpose (i.e., whether the life goals toward which one strives are self- or beyond-the-self-

oriented), and thus fail to provide a full assessment of purpose as defined by Damon et al.

(2003).

8 Steger et al. (2006) would likely defend their stance that the MLQ-P is a measure of meaning in life

because having a sense of meaning ought to be the direct consequence of having identified a purpose.

Though reasonable, this would be an incomplete position; merely identifying a life purpose may in itself

universally confer some meaning, but the degree to which one’s purpose is actively pursued and engaged

may be just as important toward actually p roducing a global sense of meaning (Emmons, 1999). Moreover,

people derive meaning from many sources other than their life goals (see Baumeister, 1991).

24

Meaningful engagement. As noted earlier, though many scholars of purpose and

meaning have separately assessed life meaningfulness and frequency of activity

involvement, few have directly addressed the notion of meaningful engagement as a

unitary construct. Flow (Csikszentmihalyi, 1990) and engagement orientation to

happiness (Peterson et al., 2005), though measured in reliable and valid ways, do not

fully capture the essence of meaningful engagement. Scheier et al.’s (2006) six- item Life

Engagement Test partially taps into meaningful engagement, and has been shown to

exhibit internal consistency and construct validity across diverse populations (see also

Pressman et al., 2009). However, it muddles constructs—namely, purpose and

meaningful engagement—and thus does not provide a solid assessment of the current

conceptualization of meaningful engagement.

In the social gerontology literature, despite its much-acknowledged importance in

old age, there are few established measures of meaningful engagement. The modus

operandi for most scholars in this area has been to devise their own assessments.

Unfortunately, as in the positive psychological literature, most of these studies seem to

consider the impact of frequency and meaningfulness of engagement separately. For

example, in his investigation of life satisfaction and aging, Gregory (1983) constructed

his own assessment of the meaningfulness of 23 activities common among older adults,

on which participants rated both the frequency of participation in and meaningfulness of

each activity. However, he failed to combine frequency and meaningfulness in his

analyses, thus missing an opportunity to understand how the interaction of the two

contributes to well-being in old age. Similarly, Lawton, Winter, Kleban, and Ruckdeschel

(1999) assessed multiple dimensions on a number of common activities among an elderly

25

population, including both frequency and ―perceived quality‖ (which could be considered

a proxy for meaningfulness). These authors likewise failed to combine their measures of

frequency and quality in their analyses, thus rendering their results interpretable only

with regard to their roles separately.

The Engagement in Meaningful Activities Survey (12- item, Likert scale;

Goldberg, Brintnell, & Goldberg, 2002) purports to measure the extent to which one

ascribes meaningfulness to one’s activity routines, and has been used to assess

meaningful engagement in older adult populations (Edwards, Hahn, Baum & Dromerick,

2006). A sample item is ―The activities I do help me express my personal values.‖

Though it has been shown to be psychometrically sound (Eakman, Carlson, & Clark,

2009), it has not been widely adopted, perhaps because it was developed for use with the

mentally ill and because it (arguably erroneously; see Battista & Almond, 1973) assumes

that certain qualities of activities—such as whether they provide opportunities for

creativity, achievement, or challenge—reflect inherent meaningfulness, rather than

actually directly asking whether particular activities are experienced as meaningful.

Psychological Well-Being. As was the case in the purpose literature, the abundant

conceptualizations of psychological well-being have spawned almost as many assessment

tools. Most of the major theories of PWB have their own accompanying measurement

instrument. For example, Seligman and Peterson’s (2004) notion of character strengths

can be measured via their Values in Action Classification of Strengths questionnaire.

Other conceptualizations of PWB combine already established scales which together

operationalize the primary components of their models, such as Keyes’s (2002)

26

conceptualization of flourishing. Typically, the hedonic vs. eudaimonic distinction is not

intentionally operationalized—instead, the merits of the hedonic and eudaimonic

approaches are argued for and against in the conceptualization of the models, and their

measures reflect the scholars’ broader theories of well-being which usually privileges one

approach over the other. Given that most well-being researchers agree that PWB at least

partly reflects both hedonic and eudaimonic aspects, it is surprising (and unfortunate) that

most of the prominent models fail to actually adequately represent both (Peterson et al.,

2005; Ryan & Deci, 2001). The only one of these frameworks which does deliberately

incorporate both approaches, Keyes’s (2002) flourishing, is so inclusive of a broad array

of aspects of mental health that it is at the same time laudably comprehensive and

regrettably impractical, especially for smaller-scale studies.

Perhaps the most reasonable approach to assessing psychological well-being is to

incorporate shorter yet still reliable and valid independent self-report measures that focus

specifically on hedonic or eudaimonic well-being. The subfield of hedonic psychology

offers a number of scales which address subjective well-being, including those which

measure positive and negative affect (e.g., the Positive and Negative Affect Schedule, or

PANAS; Watson, Clark & Tellegen, 1988) and those which measure life satisfaction

(e.g., the Satisfaction with Life Scale, or SWLS; Diener, Emmons, Larsen, & Griffin,

1985). Since positive and negative affect have been found to be largely independent

constructs (Diener & Emmons, 1984; Zevon & Tellegen, 1982), the PANAS is bifurcated

into two ten- item subscales: one that measures positive affect and another that measures

negative affect. The PANAS has been shown to demonstrate high reliability and validity

across a variety of populations and cultures (Crawford & Henry, 2004; Watson, Clark &

27

Tellegen, 1988). This affective component of happiness is thought to reflect moods

(which may fluctuate) as well as traits (sometimes referred to as ―trait affectivity‖), which

suggests that people typically exhibit a good deal of stability in the degree to which they

feel and express positive and negative affect (Watson & Walker, 1996). The SWLS is a

short (five- item) questionnaire designed to measure peoples’ cognitive judgments of their

global life satisfaction. Its psychometric properties are well-documented (see Pavot &

Diener, 1993), and it has been validated in a wide variety of populations (Diener, 2000;

Diener & Suh, 1997, 1999). A number of other measures of life satisfaction (e.g., Life-3

Delighted-Terrible Scale, Andrews & Withey, 1976; Life Satisfaction Index, Neugarten,

Havighurst, & Tobin, 1961) and positive and negative affect (e.g., Affect Balance Scale;

Bradburn, 1969), as well as indices of general happiness (e.g., Oxford Happiness

Inventory, Argyle, Martin, & Lu, 1995; Happiness Measures, Fordyce, 1988; Subjective

Happiness Scale, Lyubomirsky & Lepper, 1999) have been developed, though the

PANAS and SWLS have been the most commonly used and have garnered the most

empirical support (Arthaud-Day, Rode, Mooney, & Near, 2005).

Measures of eudaimonic well-being have proliferated with psychology’s

newfound attention to better understanding the good life. Most of these measures

represent attempts to operationalize one of the prominent multidimensional theories of

positive mental health, which purport to address the multiple (and distinct) aspects of

eudaimonic well-being. For example, the Values in Action Strengths of Character survey

(Seligman & Peterson, 2004) comprises 6 dimensions (e.g., Courage, Transcendence) and

24 personality elements (e.g., honesty, gratitude), and covers 240 questions. Thus, these

assessments typically do not directly address (in a unified way) the degree to which

28

people feel they are fulfilling their potential, which Waterman (1993) and others have

presented as being at the heart of eudaimonic well-being.

A few measures have been introduced which attempt to more d irectly tap into the

core of this construct. Waterman (1993) accompanied his theoretical argument in favor of

a eudaimonic approach to well-being with the presentation of a new scale to assess it,

which he called the ―Personally Expressive Activities Questionnaire‖ or PEAQ. The

PEAQ asks respondents to list five activities that are important to them, following which

they rate (on a 7-point Likert scale) the degree to which six statements reflective of

eudaimonic happiness apply to each activity. Examples of these statements include ―This

activity gives me the greatest feeling of really being alive,‖ and ―When I engage in this

activity I feel more intensely involved than I do in most other activities‖ (Waterman,

1993, p. 682).9 Scores across the six statements are then summed for each activity. This

approach to assessing eudaimonic happiness differs from those taken by Ryff (1989a),

Keyes (2002), Seligman and Peterson (2004), and other well-being scholars whose

models are multidimensional, in that instead of viewing well-being as a global or

individual difference variable Waterman (1993) assesses eudaimonia more narrowly in

relation to particular activities. Additionally, the multidimensional models typically

specify a group of constructs theorized to comprise eudaimonic living (via their

dimensions, such as autonomy, courage, etc.), whereas Waterman’s approach is content-

free; he makes no judgment about the activities themselves, only the extent to which

engagement in them leaves one feeling alive and expressing one’s true selves. The PEAQ

9 Respondents are additionally asked, for each activ ity, six questions designed to measure hedonic

enjoyment, as well as a number of other items intended to tap different constructs such as emotion , sense of

control, happiness, etc., which are kept separate from the eudaimonic happiness assessment.

29

has demonstrated strong reliability and validity (Waterman, 1993, 2004), though it has

not been widely used.

Notably, researchers (including Waterman) have consistently found high levels of

statistical covariance between hedonic and eudaimonic well-being; for example,

Waterman, Schwartz and Conti (2006) reported very high correlations between measures

of the two (rs=.83-.87, ps<.001; see also Bauer, McAdams, & Pals, 2006; Waterman,

2004). Such high correlations should bring into question the constructs’ distinctiveness

(Kenny, 1979), and the absence of any studies which have rigorously explored the

construct validity of hedonic and eudaimonic well-being (such as via a multi-trait

multimethod matrix; Campbell & Fiske, 1959) renders the discriminant validity of the

constructs suspect. However, Waterman et al. (2006) do provide both theoretical and

empirical arguments for their separation. These authors posit that people who live

eudaimonic lives (i.e., in accordance with their true selves) will necessarily also

experience hedonic enjoyment, but that not all hedonic enjoyment is derived from

eudaimonic living. They also empirically demonstrate that hedonic and eudaimonic well-

being exhibit asymmetric relations in people who score very high and very low, and the

patterns of relations among the two constructs and other personality variables are distinct

(e.g., they found eudaimonic well-being to be significantly related to perceived

competence, but hedonic well-being was not).

Other measures stemming from the humanistic tradition have been proposed to

measure self-actualization and fulfillment of potential, notions which as noted earlier are

conceptually very much in line with Waterman’s (1993) conceptualization of eudaimonic

well-being. Shostrom’s (1964) Personal Orientation Inventory was among the most

30

commonly used in the years of the original humanistic movement of the 1960s, though it

has been considered prohibitively long (150 items) and has failed to demonstrate strong

psychometric properties (see Ray, 1984). Jones and Crandall’s (1986) Short Index of

Self-Actualization offered a modified and shortened (to 15-items) version of the Personal

Orientation Inventory which they showed did demonstrate better reliability and validity

(see also Richard & Jex, 1991); however, later studies have also brought into question its

test-retest reliability and internal consistency (Chan & Joseph, 2000; Compton, Smith,

Cornish, & Qualls, 1996).

With these commonly-used measures largely failing to hold up psychometrically,

Shultz, King, P. E., and Wagener (2006) devised their own fairly straightforward 3- item

measure of fulfillment of potential to address this component of their conceptualization of

youth thriving. These items directly asked respondents to what degree they believe they

are living up to their potential (e.g., ―On the whole, I think that I am living up to the best

of my abilities.‖). Though the measure has not gained widespread popularity, the authors

demonstrated that it does have good internal consistency and is appropriate for use in

adolescent samples.

Review of the Empirical Literature

Before proceeding to my conceptual framework, it is important to lay out what

has already been unearthed regarding the relations among purpose, meaningful

engagement, and psychological well-being. The primary goal of the present work is to

make a unique contribution to the field, not simply replicate or rehash an old finding. In

general, the research literature suggests moderate-to-strong, positive interrelations among

31

the different conceptualizations of purpose, aspects of well-being, and to a lesser degree,

meaningful engagement. My review of these findings in the current section will be

organized around the primary independent variables in the studies, start ing with those

which focus on purpose and its relations with well-being and engagement, followed by

meaningful engagement as a predictor (and indicator) of meaning/purpose and well-

being.

Purpose and its Relations with Well-Being and Engagement. It is important to

point out that some of the multidimensional models of PWB directly incorporate purpose

and aspects of meaningful engagement. Ryff’s Six Dimensions of Psychological Well-

Being (1989a) and Keyes’s (2002) model of flourishing both advance purpose in life to

be one of a number of core components of well-being. They also recognize the

contributions to well-being of what they call ―personal growth,‖ which to a certain degree

reflects Waterman’s (1993) conception of eudaimonia in that it incorporates the ―need to

actualize oneself and realize one's potentialities‖ (Ryff, 1989a, p. 1071; it also

incorporates the degree to which people are open to experience and have a growth

mindset). Typically, research which incorporates Ryff’s and Keyes’s models o f PWB

assesses their dimensions independently and often reports their intercorrelations. Ryff

(1989a) found her dimensions of purpose in life and personal growth to be strongly

correlated with each other (r=.72, p<.001), as well as moderately correlated with

measures of life satisfaction (rs=.59 and .38, respectively; both ps<.001) and affect

balance (rs=.42 and .25, respectively; p<.001 and p<.01, respectively). To address the

issue of discriminant validity, she also demonstrated differentiation among the purpose

32

and personal growth components and these measures of subjective well-being through

exploratory factor analysis. Ryff and Keyes (1995), using a larger and more diverse

sample, found a smaller (yet still statistically significant) zero-order correlation between

purpose and personal growth (r=.31, p<.001), though the effect size was much higher

(r=.68, p<.001) in a second sample in which they used structural equation modeling for

their analyses. They also found significant (albeit weaker) relations among purpose and

personal growth, and one- item measures10 of life satisfaction (rs=.10 and .18,

respectively, both ps<.05) and happiness (rs=.13 and .15, respectively; both ps<.05).

These authors further demonstrated via confirmatory factor analysis the empir ical

distinctiveness of their six components, suggesting that even though the purpose and

personal growth components are highly related, they are not one and the same.

Other approaches that do not necessarily subscribe to (or at least do not focus on)

the multidimensional models of well-being have uncovered similar relations among

purpose and both the hedonic and eudaimonic aspects of PWB. In their investigation of

young adult women and older adults, Zika and Chamberlain (1992) operationally defined

purpose and meaning in life via a number of measures—Crumbaugh and Maholick’s

(1969) Purpose in Life Test, Battista and Almond’s (1973) Life Regard Index, and the

meaningfulness subscale of Antonovsky’s (1983) Sense of Coherence measure—which

they found to be highly intercorrelated (rs=.62-.84, ps<.001). The results for both the

younger and older samples showed strong positive correlations between all three

measures of purpose and life satisfaction (average r=.66), positive affect (average r=.59),

and an omnibus measure of PWB (comprising positive and negative indicators of

10

One-item measures have been criticized on the grounds that they often do not demonstrate test -retest

reliability (Nunnally, 1994) and are generally not conducive to testing psychometric properties

(Lyubomirsky & Lepper, 1999).

33

emotional and cognitive components; average r=.70; all ps<.001). Similarly, Reker,

Peacock, and Wong (1987) found in their exploration of purpose (measured via the Life

Purpose subscale of the Life Attitude Profile; Reker & Peacock, 1981) and PWB

(measured by the Perceived Well-Being Scale; Reker & Wong, 1984) across the life span

(their sample ranged from ages 16-93) that the two constructs were significantly

positively correlated in every age group (rs=.47-.59; all ps<.001), with no significant

differences in effect sizes by age. Compton et al. (1996), who also included participants

from late adolescence through old age, used Antonovsky’s (1987) Sense of Coherence

measure to operationalize purpose in life; these authors found strong relations among

purpose and life satisfaction (r=.65, measured by Diener et al.’s (1985) SWLS),

happiness (r=.58, measured by Fordyce’s (1988) Happiness Measure), self-actualization

(r=.52; measured by Jones & Crandall’s (1986) Short Index of Self-Actualization), affect

balance (r=.69; measured by the Affect Balance Scale; Bradburn, 1969), and general

PWB (r=.77, measured by a full-scale total of Ryff’s (1989) Scales of Psychological

Well-Being; all p-values across analyses were reported as significant at the p<.05 level).

However, we should interpret these findings with caution. Given the

aforementioned criticisms of the measures of purpose and meaning the majority of

previous research has used, it is likely that the strengths of the relationships uncovered

across most of these studies were inflated due to the measures’ conflation of purpose and

well-being at the item level. Nonetheless, the findings are quite robust, so it is likely that

the positive relations cannot be entirely attributed to measurement issues. Of greater

relevance is the concern that in none of the studies did the authors acknowledge the

distinction between purpose and meaning, and since their measures likely tapped into

34

both we cannot know whether the results reflect associations primarily based on the

global sense that one’s life is meaningful, or on the understanding and pursuit of one’s

purposeful life goal(s). Along these same lines, none of these studies consider the content

of one’s purposeful pursuits, so the Damon et al. (2003) definition has yet to be fully

empirically tested.

Steger et al. (2006) employed their MLQ-P—which as suggested earlier

represents a more sound (and more in line with the current conceptualization) measure of

the degree to which respondents believe they have identified a purpose for their lives—to

investigate relations among purpose and a variety of well-being instruments. They found

strong positive relations among purpose and life satisfaction (r=.46, p<.001; measured by

the Satisfaction with Life Scale; Diener et al., 1985) as well as other indicators of well-

being such as joy and love (r=.49, p<.001 and r=.40, p<.001, respectively; both are

thought to be indicators of long-term positive affectivity, see Diener, Smith, & Fujita,

1995), and self-esteem (r=.37, p<.001); they also found strong negative relations among

purpose and depression (r=-.48, p<.001) and neuroticism (r=-.23, p<.01). The above

represents but a few of the growing body of studies that have uncovered pos itive relations

among purpose as life goal and aspects of PWB (e.g., Steger, Kashdan, Sullivan, &

Lorentz, 2008; Tiliouine & Belgoumidi, 2009).

Inversely, it seems to be the case that the absence of having identified a purpose

may have negative psychological consequences. Steger et al. (2006) found that people

searching for a purpose (which implies the absence of one)11 are on average more likely

11

However, Steger et al. (2006) note that the correlation between searching for purpose and the presence of

purpose is non-significant (r=-.09), indicating that many respondents may believe they have identified a life

purpose while at the same time are open to the possibility that there are other (or more) purposes out there

for which they should continue to search.

35

than those not searching to be depressed, neurotic, and low in self-esteem (the

relationship between searching and life satisfaction was non-significant in the negative

direction, r=-.12). Similarly, Reker et al. (1987) found a significant negative relationship

between goal seeking—which was designed to measure the degree to which one desires a

new set of goals in life (Reker & Peacock, 1981)—and PWB in their young adult (16-29

years old) and early middle-age (30-49 years old) samples (r=-.39, p<.01 and r=-.30,

p<.05, respectively). These results led the authors to conclude that high goal seeking

could ―reflect unfulfilled needs which reduce PWB‖ (p. 48), which may be the

consequence of a lack of purposeful life goals.

A smaller literature has explored relations among types/categories of purpose and

PWB. Lapierre, Bouffard, and Bastin (1997), who took an idiographic approach to

measuring life goals in older adults, found that those who aspired to self-development

goals (such as personal growth) and other-oriented goals (such as helping others) were

more likely to sense high meaning and life satisfaction, while those who focused on self-

preservation goals (e.g., maintaining good physical health) were more likely to

experience less meaning and life satisfaction. Research on mid- level goals has

consistently shown that aspiring to materialistic and/or extrinsic goals (such as to make

money, look good, and be popular) is associated with reduced well-being and a lesser

degree of self-perceived self-actualization (Cohen & Cohen, 2001; Kasser, 2002;

Salmela-Aro, Pennanen, & Nurmi, 2001). Additionally, Reker (2000) reported findings

showing that those who endorsed a greater diversity of life goals also rated themselves

higher on global life meaningfulness as well as general PWB.

36

While most of this literature has focused on adults, Massey, Gebhardt &

Garnefski (2008) explored relations among types of goals and well-being in adolescents

(ages 12-19). In their study, these authors took an idiographic approach in which life

goals were self-generated by the participants and then coded into the following groups by

the authors: school goals, future trajectory goals, material goals, free-time goals, self-

oriented goals, relationship goals, health goals, and body goals. Most germane to the

current investigation, they found that endorsement of self-oriented goals (such as ―always

be yourself‖) was related to lower PWB, but they did not find any evidence of a

relationship between materialistic goals and well-being. It is worth noting that the goals

the authors coded into the ―self-oriented‖ grouping may have reflected a desire to

improve upon an existing deficiency (e.g., one might set the goal to ―always be oneself‖

because he feels like he does not have many opportunities to be authentic, which is

frustrating). It is also notable that these authors did not believe their data warranted a

code that approximated a self-transcendent category, a point on which they did not

elaborate.

One recent study integrated all dimensions of Damon et al.’s (2003)

conceptualization of purpose, including a measure of beyond-the-self orientation of life

goals. In their investigation of adolescents aged 12-22, Moran, Bundick, Malin and Reilly

(2009) operationally defined beyond-the-self-orientation of life goals by first assessing on

a Likert scale the degree to which participants felt each of 17 general categories of

purpose (e.g., ―Serve God‖ or ―Have fun,‖ derived from the sources of meaning found by

DeVogler & Ebersole, 1980; Reker & Wong, 1988) reflected their life goals, fo llowed by

creating a subscale via summing together ratings for the nine beyond-the-self-oriented

37

life goals (e.g., ―Help others,‖ ―Make the world a better place‖) that comprised the first

factor of the two-factor structure that emerged from exploratory factor analyses (the other

factor represented a set of self-oriented life goals, such as ―Have a good career‖ and

―Make money‖). They found that scores on both Steger et al.’s (2006) MLQ-P and Ryff’s

(1989a) PWB-P measures of purpose were significantly related to having a beyond-the-

self-orientation in one’s life goals (r=.40 and r=.24, respectively; both ps<.001).12

Importantly, not all research on levels and types of purpose and purpose- like

constructs suggest purpose and PWB are positively related. In a study investigating

personal strivings and well-being in college students and adults (Emmons, 1992),

participants were grouped into two categories, those reporting primarily higher- level life

strivings (like purposes) and those with primarily lower- level strivings, and compared on

a variety of well-being measures. Results revealed that those who aspired to primarily

higher- level goals were more likely to score higher on anxiety and depression, compared

to those who held primarily low-level goals who on average where higher on PWB

(though lower on physical health). According to the author, higher- level goals may be

more meaningful, but are fuzzier and potentially harder to accomplish (or at least harder

to see the fruits of one’s labors), as indicated by participant ratings. He concluded that the

most adaptive form of self- regulatory goal-striving behavior may be to select lower- level

(more concrete and behaviorally-oriented) goals which are directly linked to one’s

higher-order life goals, and that the presence of such higher-order strivings in the absence

of concrete and actionable goals (which may function as means toward carrying them

out) may have negative well-being consequences.

12

These authors did not explore relat ions among aspects of purpose and self-oriented life goals, as these

types of goals are not part of the Damon et al. (2003) definit ion they adopted.

38

Notably, very few investigations of relations among purpose and well-being

indicators have incorporated longitudinal data. Feist, Bodner, Jacobs, Miles, and Tan

(1995) found a moderately strong correlation (r=.56, p<.001) between purpose (as

measured by the PWB-P) and satisfaction with self (as measured via the Self-as-Worthy

subscale of the World Assumptions Scale; Janoff-Bulman, 1989) at assessments

separated by one month; however, they did not control for levels at the first assessment

period so directionality of effects could not be inferred. 13 Steger and Kashdan (2007)

found in a sample of college students that purpose (measured by the MLQ-P) and life

satisfaction (measured by the SWLS) were relatively stable over one year, and

significantly correlated from the first year to the second (r=.30, p<.01). They also found

that purpose at the time of the second assessment was not significantly predicted by life

satisfaction at the time of the first assessment, controlling for time 1 purpose (β=0.05,

p>.05); nor was life satisfaction at the time of the second assessment significantly

predicted by purpose at the time of the first assessment, controlling for time 1 life

satisfaction (β=0.15, p>.05). However, the sample was small (N=82), and in their

analyses the authors included as a covariate (for reasons pertinent to their investigation) a

measure of searching for meaning in life. For these reasons, Steger and Kashdan’s (2007)

results may not fully reflect the temporal relations between purpose and life satisfaction.

Meaningful Engagement and its Relations with Purpose and Well-Being. As

noted earlier, as a unified construct meaningful engagement has attracted surprisingly

13

Feist et al. (1995) did exp lore longitudinal relat ions among other constructs (including satisfaction with

self) and their own conception of well-being, of which purpose in life was considered a part (specifically,

well-being was a latent variab le comprising purpose, environmental mastery, and self-acceptance). As

such, any unique contributions of purpose to well-being could not be inferred from these longitudinal

analyses.

39

little empirical attention in the purpose and meaning literature, especially given that some

of the early theoretical models in the meaning and purpose literature incorporated a

behavioral component (Maddi, 1967; Reker & Wong, 1988). Most of the empirical

studies in this field which have explored engagement have conceptualized meaning in life

and frequency of activity engagement as separate constructs. Indeed, engagement in

certain activities has been found to be associated with a higher sense of global meaning in

life, such as volunteering and community service activities (Benson et a l., 1980; Keyes &

Waterman, 2003), especially in older populations (Pinquart, 2002; Thoits & Hewitt,

2001); religious and spiritual activities (Chamberlain & Zika, 1992; Hill & Pargament,

2003) and spending time with family (Ebersole, 1998; Wong, 1998). Others have

demonstrated that engaging in helping behaviors leads to increased PWB in college

students (Konow & Earley, 2008)

Few empirical studies exist that directly investigate relationships between having

a life purpose and the degree to which one engages in personally meaningful activities.

Steger, Oishi and Kashdan (2009) explored relations between having a life purpose

(measured by the MLQ-P) and Peterson et al.’s (2005) notion of engagement orientation

to happiness, and found significant, albeit small- to-moderate-sized correlations across the

life span (rs=.34-.45, all ps<.01). Other investigations have sought to determine whether

engagement in activities specifically thought to be tied to personal meaning structures are

associated with a greater sense of meaning and higher subjective well-being. Steger et al.

(2008) explored whether engagement in ―daily eudaimonic activities,‖ which refer to

activities in which one feels most deeply engaged and at peace with one’s self (a notion

conceptually similar to meaningful engagement) was associated with higher purpose and

40

PWB. These authors used a daily diary method over the course of three weeks to assess

engagement in eudaimonic activities (which included a predetermined set, such as

―volunteered my time‖ and ―persevered at a valued goal even in the face of obstacles‖),

and found that higher engagement predicted higher scores on purpose (measured by the

MLQ-P; r=.21, p<.05) and positive affect (measured by the PANAS; r=.25, p<.05), and

a trend toward higher life satisfaction (measured by the SWLS; r=.18, p<.10). They also

found that engaging in eudaimonic behaviors on one day predicted a greater sense of

meaning the following day. The authors concluded that ―eudaimonic activities [may]

assist people in endowing their experiences with coherence, meaning, and purpose‖ (p.

38). While this study does provide some insights into the experience of meaningful

activity engagement, participants were not asked to what degree they found meaningful

each of the activities to which they responded in the predetermined list; without this

knowledge, one cannot infer from their findings that participants actually would be fully

invested in or derived meaning from the so-called eudaimonic behaviors. As suggested

earlier, engagement in activities such as ―volunteering one’s time,‖ though socially

valued and a common source of meaning (Thoits & Hewitt, 2001), may accord different

levels of meaning to different people.

Scheier et al. (2006) framed their notion of life engagement—which as noted

earlier is conceptually akin to meaningful engagement—as an indicator of purpose in life,

and did not recognize the life-goal- like nature of purpose as portrayed by Damon et al.

(2003), Kashdan and McKnight (in press), and Steger (2009). Therefore, they and others

who have investigated the construct (e.g., Cohen & Lemay, 2007; Pressman et al., 2009)

have typically not explored relationships between life engagement and purpose as defined

41

herein. However, Scheier et al. (2006) did demonstrate across a number of diverse

samples that life engagement was moderately-to-strongly positively correlated with life

satisfaction (rs=.34-.58, all ps<.01; measured by the SWLS), as well as other indicators

of PWB such as optimism (rs=.39-.61, all ps<.01) and self-esteem (rs=.43-.61, all

ps<.01), and was moderately negatively correlated with depression across the samples

(rs=-.33 to -.49, all ps<.01). Pressman et al. (2009) further showed that in middle-aged to

older adults, life engagement was significantly related to frequency of engagement in

enjoyable leisure activities (r=.31, all p<.001), even when controlling for subjective well-

being.

Summary

The extant literature provides some insights into the relations we might expect to

find among the core constructs of interest in the current investigation: purpose,

meaningful engagement, and psychological well-being. By and large, the previous

empirical research points to moderately strong relations among a variety of conceptions

of purpose and PWB, and the limited research on meaningful engagement and constructs

similar suggest it is likely related to both purpose and well-being. However, much of the

research on purpose has either suffered from dubious measurement, or failed to consider

the content of one’s purpose; and meaningful engagement, as a unified construct as

conceived herein, has garnered little attention in populations outside of older adults.

Moreover, the directionality of the relations that have been uncovered remains in

question, due in large part to the paucity of longitudinal and experimental studies.

Perhaps most importantly, in my review I could not find any studies which have at the

42

same time investigated purpose, meaningful engagement, and PWB as they are currently

defined, despite the theoretical importance of their interrelations.

43

CHAPTER 2: CONCEPTUAL FRAMEWORK

Chapter One addressed a number of the conceptual and measurement-related

issues surrounding the study of purpose, meaningful engagement, and psychological

well-being. Each of these constructs have been multifariously conceptualized and

operationalized in their respective literatures, rendering much of the research on the

topics difficult to interpret at best, and possibly misleading at worst. In the current

chapter, I will 1) distill from my review in Chapter One the most important aspects of the

existing conceptualizations of these three constructs and from them provide my own

definitions, 2) integrate relevant perspectives from the literature to inform a concep tual

model of how the three are interrelated, and 3) formulate a set of hypotheses regarding

my four primary research questions, which will guide my empirical investigation.

Definitions of the Constructs

Purpose

In the present investigation, I define a purpose as a stable and generalized higher-

order life goal which organizes and motivates one’s current actions, decisions, and

lower-level aspirations. In this conceptualization, purpose may have any content—self-

oriented or beyond-the-self-oriented—provided it meets the definitional criteria of

stability (i.e., it is not fleeting), generalizability (i.e., it is not confined to one life

domain), is of a higher order (i.e., it has a long-term time horizon, and operates across

one’s life span and subsumes multiple and diverse concrete goals), and has organizational

and motivational properties with regard to one’s current life (i.e., the purpose leads one to

44

make decisions, form lower- level/short-term goals, and engage in current activities in

pursuit of its realization). I consider purpose at the person- level (i.e., as a personality

variable); in other words, I am interested in the degree to which one is purposeful in the

way he lives, not just whether he believes he has and understands his purpose. This thus

entails both the identification of one or more life purposes, and an orientation toward

pursuing it/them (i.e., life-goal-directedness). For simplicity, I refer to this personality

variable as ―purpose,‖ though it might be better articulated as purposefulness. Thus, my

operational definition of purpose will consider the degree to which one believes she has

established a purpose for her life (per the definitional criteria), as well as the degree to

which she is oriented toward accomplishing and driven by having such life goals.

This approach to purpose is intended to be integrative, drawing on components of

multiple definitions to provide a focused yet inclusive conceptualization. Damon et al.

(2003) clearly distinguished purpose from meaning in their assertion that purpose is not

merely a general (largely affective) sense one has about one’s life on the whole, but

instead is a specific (though abstract) life goal which is stable (i.e., rooted deeply in one’s

identity), generalized (i.e., it operates across multiple life domains) and influences one’s

lower- level goals, decisions, and actions (see also Damon, 2008). Kashdan and McKnight

(in press) and Steger (2009) likewise acknowledged the abstract life-goal- like nature of

purpose, and further advanced its motivational and behavioral properties. Each of these

scholars assert that meaning is derived from the identification and pursuit of a purpose in

life, though meaning may also be found in sources outside of one’s life goals (Reker,

2000). Following these authors’ lead, the current definition embraces as one of its core

aspects the abstract, motivating life-goal nature of purpose.

45

Others have put forth definitions of purpose which may not emphasize its higher-

order goal- like nature, but do focus on the idea of being goal-directed and future-oriented

(which implies goal pursuit; see Nurmi, 1991). In particular, Ryff (1989a) described

those who have purpose as being directed toward finding and accomplishing their most

important life goals, and integrated into her definition of purpose in life the notions of

planfulness and future orientation (see also Keyes, 2002). While goal-directedness is

implied in the life-goal models of purpose, it is not always included in the definitions and

is absent from the only measurement tool of purpose-as-life-goal in regular use (the

MLQ-P). I would agree with Damon (2008) who suggested that one who has identified a

stable and generalized life goal but is not at all oriented toward making it happen, is

really just an idealist or ―dreamer‖—the label ―purposeful‖ ought not apply in this

scenario. For people to be truly purposeful, they must not only understand what their

most important goal(s) in life are, but they must also be committed to realizing those

goals.

Damon et al. (2003; Damon, 2008) included one component they assert is an

essential criterion of purpose which is not reflected in the present definition. They

stipulated that a purpose must have content that is motivated by ―beyond-the-self-

oriented‖ concerns; self-oriented life goals are not purposes, in their estimation. While

this is a perfectly valid way of defining purpose—indeed, a number of other scholars also

endorse the self-transcendent nature of purpose (e.g., Frankl, 1963; Reker & Wong,

1988)—I have not adopted it in the current definition, for a couple of reasons worth

illuminating. For one, it runs somewhat counter to the common nomenclature: when

people are asked what their purpose in life is, they commonly respond with life goals that

46

are clearly self-oriented (see Moran, 2008).14 People are often said to be quite purposeful

when in committed pursuit of their most deeply held life goals, even when those goals are

entirely driven by self- interest. Damon (2008) offered the following observations: ―A

purpose is an ultimate concern. It is the final answer to the question Why? Why are you

doing this? Why does it matter to you? Why is it important? A purpose is a deeper reason

for the immediate goals and motives that drive most daily behavior‖ (p. 22; italics in

original). One’s ultimate concern, and her answers to the ―why‖ questions for her actions,

goals, and motives (and importance of each, at least in her mind) may well be centered in

her desire to be famous, or the best in the world at a given task, or simply to survive. In

my view, how one might chose to categorize these life goals—such as, oriented toward

the self vs. oriented beyond-the-self (or for that matter, as liberal vs. conservative,

attainable vs. unattainable, noble vs. ignoble)—may, but by no objective standard must,

warrant the ―purpose‖ label. In other words, I see this issue as a primarily semantic one—

I am comfortable labeling a self-oriented life goal a ―purpose‖ provided it meets my

definitional criteria, while Damon et al. (2003) are not. Thus, in the current formulation,

self-oriented life goals and beyond-the-self-oriented life goals are simply two different

types of purposes. Indeed, the extent to which these different types of purpose function

differently in one’s life (e.g., whether one is more likely to lead to well-being than the

other) is an interesting research question—interesting enough to me that I have elected to

investigate it (see Research Questions section below).

14

To their credit, Damon et al. (2003) and others are helping to raise awareness of this important

distinction; indeed, I agree that we (as scholars and more broadly as humans) would be better served if the

common understanding and usage of the word ―purpose‖ was reserved for only the life goals that are

intended to affect someone or something beyond oneself.

47

Though largely semantic, this issue is particularly important from a measurement

perspective. Researchers who define purpose strictly as beyond-the-self-oriented and are

interested in quantitatively assessing the degree to which one has purpose seem to have

two options. They may either use scales that include items which directly ask whether a

respondent has identified one or more purposes or life goals (such as is the case on the

MLQ-P), which then must be qualified with follow-up questions about the content of

one’s purpose(s) (as understood from an emic—the respondent’s—perspective) before it

can be determined whether they warrant the label ―purpose‖ (as understood from an

etic—the researcher’s—perspective; see Moran, 2008). Alternatively, the items must

simultaneously ask respondents whether they feel they have one or more life goals and

whether those life goals are beyond-the-self-oriented (e.g., ―To what degree do you feel

you are pursuing life goals that are intended to benefit the world beyond you?‖). In the

latter case, it is impossible to know whether the answer is influenced more by the degree

to which one has a life goal, or the degree to which one’s life goals are BTS-oriented (this

is known in the scale construction literature as ―double-barreling;‖ see DeVellis, 1991).

Of course, one response to this issue is that purpose should not (and perhaps cannot) be

assessed quantitatively, which is a reasonable point. An alternative response, the one I

have adopted, is to relax the criterion that purposes can only be BTS-oriented, freeing one

up to quantitatively assess purpose in the former of the two manners suggested—i.e., to

ask people whether they have a purpose (with the freedom to use the word ―purpose‖ in

the items, so participants’ responses reflect their common understanding of the term),

then ask separately what the content of that purpose is. This approach allows the

researcher to account for the degree to which a respondent feels he has a purpose (from

48

an emic perspective), and then separately compare whether these purposes function

differently dependent upon whether their content is self- or BTS-oriented.

Meaningful Engagement

As introduced in Chapter One, meaningful engagement refers to the degree to

which one finds the activities in which one is involved across the domains of one’s life to

be significant and worthwhile. Outside of situations in which one suffers from some kind

of debilitating condition, all humans engage to varying degrees in a wide range of

activities over a given time frame (from hours to days, weeks, months, or years). One of

the things that differentiates one human from another is the degree to which one is

meaningfully engaged across the activities of one’s life. In this way, meaningful

engagement might be seen as an individual difference variable,15 on which people may be

relatively high or low. Scheier et al.’s (2006) notion of life engagement taps into this

human characteristic, and implies that the degree to which one values the activities in

which one is engaged is itself a measure of how much meaning one is experiencing in

one’s life. Waterman (1993) and Steger et al. (2008) espoused similar perspectives in

their approaches to eudaimonic activity engagement. Support for this notion can even be

found in the cognitive science literature—the ―enactive approach,‖ which explores the

mutual dependence between cognitive agents and the world around them, asserts that

―everything that is meaningful to us is produced by the array of actions in which we are

engaged at any given time‖ (McGann, 2007, p. 467).16

15

Individual difference variables ought to be relatively stable over time; though this has not yet been

demonstrated for the current conceptualizat ion of meaningful engagement, the present work will address it. 16

Indeed, this enactive approach to cognitive science has much to add to the current conversation on

purpose in life. Though it is not the intent of the current paper to highlight connections between cognitive

49

Psychological Well-Being

Chapter One reviewed some of the major theoretical frameworks of psychological

well-being in the positive psychology literature, focusing on the hedonic vs. eudaimonic

distinction. One of the important claims I made in that review was that amidst the arguing

over which is the ―better‖ way of conceptualizating PWB, many of the scholars in this

field have failed to recognize (or, have recognized and still failed to incorporate into their

models) the value of considering both hedonic and eudaimonic well-being (Peterson et

al., 2005). At the same time, the singular prominent framework which does incorporate

both, Keyes’s (2002) notion of flourishing, is so comprehensive as to be arguably

impractical.

One emerging framework, Peterson et al.’s (2005) Orientations to Happiness,

provides a more manageable conceptualization of PWB, focusing on three ―ways to be

happy‖: pleasure, meaning, and engagement. Though these authors do not portray their

model as a framework of PWB, it seems to function as one: they incorporate both

hedonic (pleasure orientation) and eudaimonic (meaning and engagement orientations)

components as coexistent routes to the good life, and argue (as well as demonstrate

empirically) that a life marked by meaning and engagement is likely to result in

happiness. Unlike the present work, Peterson et al. look separately at global meaning and

life engagement, though they acknowledge that meaning may come from such

science and psychology, it is worth noting another relevant observation from McGann (2007) on the

layering of goals and actions that emanate from purposeful pursuits: ―Every moment we are act ive in our

environment, our layered goals—interests, reasons, strategies, purposes—enact a world of rich, complex

and entangled meanings…. Our purposes constrain the strategies that might be deployed over a period of

time [toward achieving those goals], which in turn affect our reasons for acting in particu lar situations

which finally affect the kinds of individual behaviours that are produced in a given context. There is a

hierarchical structure of intentions which lay multip le strata of implications into the interaction between

agent and world‖ (p. 481).

50

engagement. Though their measures may not be suitable for the current study, their

framework helps inform the current conceptualization of PWB in that they acknowledge

both hedonia and eudaimonia as essential to overall well-being. Other approaches in the

positive psychological literature likewise advocate combining hedonic and eudaimonic

elements to operationalize PWB (Chirkov, Ryan, Kim & Kaplan, 2003; Ryan & Deci,

2001).

Following the lead of these scholars, my conceptualization of well-being

integrates both hedonic and eudaimonic approaches. I define PWB as people’s self-

evaluations of the degree to which they are both satisfied with their lives on the whole

and believe they are fulfilling their potentials. This definition asserts that both hedonic

and eudaimonic components must be present to gain a full understanding of PWB. Their

combination represents one way of operationalizing ―the good life‖ (see King, L. A. et

al., 2006). This combination also implies a singularity of the construct—this is

appropriate not just theoretically, but empirically: research which has compared the two

different types of well-being has demonstrated very strong relationships between them

(e.g., Waterman (1993) reported correlations of r>.80), to the point that they may be

convergent.17 This definition is not intended to comprehensive—other psychological

constructs such as optimism, self-esteem, sociability, self-regulation, etc., that are present

in the multidimensional models certainly make integral contributions to mental health—it

is instead intended to be elemental, in that it represents at a basic (and straightforward)

level the two components that undergird most frameworks of PWB. In this way, it also

17

To be sure, I will empirically address in my analyses in the following chapters whether this is the case in

my samples before proceeding with this unitary operationalization of the construct.

51

lends itself to a more practical operational definition than most of the multidimensio nal

models.

Conceptual Model

As outlined in Chapter One, research on purpose in life (and constructs similar),

meaningful engagement (and constructs similar), and PWB (in its variety of

conceptualizations) strongly suggests positive relations among the three constructs.

However, as noted, much of this research muddles the measurement of these constructs

leading to difficult-to- interpret results. To date, no investigation of the three constructs as

defined herein has been presented, and no conceptual model of directional relations

among the three has been proposed. In the current section, I will lay out my hypothesized

model of the relations among purpose, meaningful engagement, and PWB, with reference

to the literature upon which the thinking behind this model was based.

Though theory suggests that purpose and meaningful engagement influence PWB

(e.g., Crumbaugh & Maholick, 1964; Yalom, 1980), most empirical studies have been

cross-sectional and correlational. Further, few have addressed relations among these

constructs as conceptualized in the present work, and no empirical studies have sought to

directly investigate causal relations among them.18 To date, we only have correlational

research to go on. Indeed, at least one study has found that aspects of meaning may in

fact be the consequence, rather than the cause, of current well-being; specifically, King,

L. A. et al. (2006) argued that feeling happy makes people more likely to believe their

18

Steger and Kashdan’s (2007) longitudinal study of purpose and life satisfaction was framed as an

investigation of the stability of the constructs, and did not seek to establish causal relat ions. Nonetheless, as

reported in Chapter One, they did report analyses which provided some insights into directionality,

comparing the effects of Time 1 purpose on Time 2 residual life satisfaction, and vice versa.

52

lives in general are meaningful, leading them to find greater meaning in their daily

activities.19 As noted in Chapter One, very few longitudinal studies which might help

establish directionality have been performed, and those that have have suffered from low

power and failed to produce conclusive results (e.g., Steger & Kashdan, 2007). Moreover,

purpose and meaningful engagement have yet to be investigated using experimental (or

even quasi-experimental) designs (Steger, 2009), likely because they do not lend

themselves easily to manipulation in a laboratory or otherwise controlled setting. Indeed,

we still know very little about how to increase one’s sense of purpose (cf., Moran et al.,

2009).20

With theory and empirical research suggesting relations among purpose,

meaningful engagement, and well-being, the primary condition for a mediational

hypothesis of interrelatedness among all three constructs is in place (Baron & Kenny,

1986). The conditions for mediation hold that the two predictor constructs of interest

(meaningful engagement and purpose) must: 1) both be significantly related to the

outcome construct of interest (PWB), and 2) be significantly related to each other. Strong

theory then should inform the mediational/directional paths. I propose a model in which

the relationship between meaningful engagement and PWB is mediated by purpose. In

other words, engaging meaningfully in the activities of one’s life (especially in the

adolescent/late adolescent years) increases the likelihood that she will find and commit

19

In King, L. A. et al.’s (2006) investigation, they found that being high in positive emotions increased the

likelihood that people would rate their daily act ivit ies as having a sense of meaning. While this may suggest

it is possible that people high in more general PWB might be more likely to report that they have purpose,

as laid out earlier the current conceptualizations of purpose and well -being differ from the sense of

meaning and feelings of positive affect exp lored in the King, L. A. et al. study. Thus, it is difficult to tell to

what extent their work has bearing on the current investigation. 20

Some clin ical investigations of the efficacy of logotherapy, as formulated by Frankl (1963; a.k.a.

―meaning-centered counseling,‖ which focuses largely on helping people find and foster what gives them

meaning in life), have been performed, though these studies by and large have met with mixed results (se e

Wong, 1998, for a rev iew).

53

herself to a life purpose (in emerging adulthood), and that the presence of purpose then

leads her to feel both more satisfied with her life and that she is fulfilling her potential. I

offer a schematic representation of this model in Figure 1.

Note. The dotted line represents the hypothesized mediated path.

Figure 1. Schematic representation of mediational model.

This hypothesized model is informed by much of the theory reviewed in Chapter

One. Clark et al. (1991) believed that engagement in personally meaningful activities

leads to the sense that one has a purpose in the world, and that this purpose can enhance

one’s overall well-being. Waterman (1993) posited that when people are engaged in

activities that reflect their deepest held values, they find the sources of meaning that are

most important to them. Nakamura and Csikszentmihalyi (2003) suggested that

involvement in daily activities in which one feels ―vitally engaged‖ can lead to a greater

understanding of the larger goals to which one might commit. Scheier et al. (2006) and

Wrosch et al. (2003) asserted that the lack of meaningful engagement in one’s life breeds

54

a decline in purpose, which in turn breeds a decline in PWB. And Steger et al. (2008)

emphasized the role of engaging in eudaimonic activities toward endowing one’s

experiences with purpose, which increases the likelihood of greater PWB.

Considering that humans are not passive reactors to external influences but

instead active constructors of their own worlds (Brandstädter, 2006) and that we have a

fundamental need to find and make meaning in our lives (Frankl, 1963; Debats, 2000),

we can surmise that as people come to understand what is meaningful to them through

their actions, they are inclined to form goals (including higher- level life goals) based

upon these understandings (Emmons, 1986). Even when higher- level goals do not evolve

directly from meaningful engagements, these experiences may still contribute to the

formation of coherent goal hierarchies which provide mechanisms for implementing

longer term goals (Gollwitzer & Brandstädter, 1997), which in turn offer ―a practical

means–end structure for one’s major life goals‖ (Bauer & McAdams, 2004, p. 124). And

as suggested in Chapter One, once these larger life goals are in place and are being

pursued, they can function as a source of well-being (Emmons, 1999; Steger et al., 2006).

This mediational model also finds support in self-concordance theory, which

considers the degree to which one’s broad personal goals reflect stable interests and

values (Sheldon & Elliot, 1999). Self-concordant goals are intrinsically motivating and

reflective of one’s identity (Sheldon & Houser-Marko, 2001), linked to long-term values

and enjoyment of goal pursuit (Sheldon & Kasser, 1998), and predictive of greater effort

and progress toward those goals which in turn lead to higher well-being (Sheldon &

Elliot, 1999). Since in the current model meaningful engagement is thought to help

people better understand their interests and values, the link between meaningful

55

engagement and purpose (and ultimately PWB) may be reflected in the self-concordance

model. Though levels of self-concordance are not specifically addressed in the present

work, these potential connections are ripe for future investigation.

Furthermore, I propose that this meaningful engagement purpose PWB

process is most likely to bear out in the years of emerging adulthood. From a

developmental perspective, adolescence may first serve to lay the foundation of purpose

(Damon, 2008; Steger, 2009), in that this developmental phase provides opportunities to

explore different identities (Erikson, 1968; Marcia, 1966), develop self-understanding

(Damon & Hart, 1988) and a more differentiated self-concept (Dusek & Flaherty, 1981;

Shavelson, Hubner, & Stanton, 1976), get involved in an assortment of different activities

and organizations (Eccles & Barber, 1999), and become exposed to a variety of potential

sources of meaning (Fry, 1998). In these and a number of other developmentally

appropriate ways, adolescence is marked by exploration, growth and change; the

burgeoning literature on the transition from adolescence to adulthood puts front and

center the progression from relative instability to relative stability in one’s life

commitments (Settersten et al., 2000). Emerging adulthood is thought to be a critical

stage for the selection of life goals (Arnett, 2000; Freund & Baltes, 2002), and it is in this

stage when both major life goals and personality appear to settle into stable patterns

(Roberts et al., 2001; Roberts, O’Donnell, & Robins, 2004). It therefore seems

appropriate to explore the current hypothesized causal process model21 in the stage of life

when it may be most likely to be occurring.

21

By definit ion, all mediational models are process models (see Cole & Maxwell, 2003).

56

An alternative process among these constructs might be posited. It might instead

be argued that purpose leads to meaningful engagement, which then leads to PWB; some

theories of mid- level goals suggest such a model (e.g., Klinger, 1977; Little, 1983).

Indeed, it would also be logical that once people identify and are oriented toward

pursuing higher-order goals such as purposes, they would be more likely to be higher on

meaningful engagement (e.g., Steger, 2009). It is from a developmental perspective that I

believe the meaningful engagement purpose PWB path is more likely in the age

range on which I am focusing, given the aforementioned theory which suggests: 1)

opportunities to become more meaningfully engaged across a variety of new activities are

likely to emerge as one has greater independence in the years of late adolescence and

emerging adulthood, and 2) emerging adulthood is the developmental phase in which life

goals are most likely to take root, once the ―building blocks‖ of purpose (e.g., identity,

self-understanding) are more likely to have been laid (Arnett, 2000; Erikson, 1968).

Indeed, I believe meaningful engagement is likely to increase as people come to

understand and become oriented toward pursuing their purposes; however, this process

can only play out after people establish and orient themselves toward their purposes,

which I posit occurs in emerging adulthood. Perhaps a purpose meaningful

engagement PWB model might be well-suited for investigation in the transition from

emerging adulthood into young adulthood (i.e., the late 20’s into the early 30’s), but that

is beyond the scope of the present investigation (albeit ripe for future investigation)

To summarize, I believe the above mediational process as it applies to emerging

adulthood implies two steps. First, meaningful engagement (which occurs during and

perhaps increases over the course of adolescence as young people explore and commit to

57

different activity involvements) leads to the formation of and commitment to purposeful

life goals (that presuppose a certain degree of self-understanding and identity

development, both of which also develop through adolescence). This process of

meaningful engagement purpose most likely occurs in late adolescence and into the

emerging adult years. Second, after young people identify, and begin planning toward

and pursuing their stable and purposeful life goals in emerging adulthood, they begin to

reap the psychological benefits. For primarily these reasons, I ground my current

investigation in the heart of emerging adulthood, in the early- to mid-20’s.

This mediational hypothesis is primary in the present work. Additionally, I am

interested in testing a secondary (though no- less-important) hypothesis which stems from

the work of Damon et al. (2003) and their focus on the role of content of one’s life goals.

To date, no studies have directly addressed whether the presence of beyond-the-self-

oriented life goals might function as a moderator of the relationship between purpose and

PWB, as currently defined. Chapter One revealed that mid- level goals oriented toward

helping others and otherwise transcending the self were more likely to be associated with

higher life satisfaction and meaning than self-oriented goals. It would be reasonable to

extrapolate from these findings that the relationship between purpose and PWB may be

stronger for those who have beyond-the-self-oriented life goals, and weaker for those

who do not.

Taking these perspectives together, I propose a conceptual model of the relations

among purpose, meaningful engagement, and psychological well-being, in which 1) the

relationship between meaningful engagement and PWB is mediated by purpose, and 2)

the path from purpose to PWB is moderated by the content of one’s life goal(s), namely

58

the degree to which one’s life goals are self-transcendent.22 Figure 2 offers a pictorial

representation.

Note. The dotted line represents the hypothesized mediated path.

Figure 2. Schematic representation of mediational model with moderation

Research Questions and Hypotheses

The current investigation seeks to address four primary research questions in the

context of emerging adulthood:

1) Are purpose and meaningful engagement associated with psychological well-

being?

2) Does purpose mediate the relationship between meaningful engagement and

PWB?

22

Some might refer to this model as one of ―moderated mediation‖ (e.g., MacKinnon, Fairchild, & Fritz,

2007). I am not investigating it as a pure moderated mediational model, as my theory does not stipulate any

moderating effect of BTS-orientation of life goals on the relationship between meaningful engagement and

purpose.

59

3) Is the relationship between purpose and PWB moderated by the presence of an

orientation toward beyond-the-self life goals?

4) Can purpose, and consequently well-being, be enhanced via an intervention

consisting of an in-depth interview in which one deeply reflects upon and

discusses one’s life goals?

Each of these research questions addresses some aspect of the conceptual model

shown in Figure 2. The first research question addresses the individual (though non-

directional) paths among the three primary variables (i.e., not controlling for the other

primary variables). The second research question addresses whether the path from

meaningful engagement to PWB (i.e., the dotted line) is mediated by purpose. In other

words, when controlling for the paths from meaningful engagement to purpose and

purpose to PWB, is the significant relationship between meaningful engagement and

well-being no longer significant (or at least significantly reduced; see Baron & Kenny,

1986)? The third question focuses specifically on the path from purpose to well-being,

where moderation is depicted by the arrow pointing from BTS-orientation of life goals to

the path between purpose and PWB. It addresses whether purpose is more likely to lead

to psychological well-being for those who have BTS-oriented life goals compared to

those who do not. Finally, the fourth research question addresses whether further

credence can be accorded this directionality, suggesting that if purpose is enhanced

through an intervention- like process, well-being may consequently also be enhanced via

the increased purpose.

60

Regarding this final research question, perhaps ideally I would have designed an

intervention for increasing meaningful engagement. However, such an approach would

have been difficult if not impossible, since it would entail either making people derive

more meaning from the activities in which they regularly engage or engaging more often

in the activities they find meaningful across many life domains. While perhaps future

research can address such manipulations, I have instead elected to explore an intervention

designed to trigger what I believe is the mechanism linking meaningful engagement to

purpose—connecting one’s current meaningful goals and activities to one’s larger life

concerns and values. I hypothesized that deep discussion and reflection on these

meaningful goals and activities, as might occur through engagement in an in-depth

interview, may function as this trigger.

Though they are implied by the hypothesized models, let me be clear in my

hypotheses regarding each research question. My four primary hypotheses in the present

investigation are:

1) Purpose, meaningful engagement, and psychological well-being are predicted to

be significantly associated with each other, as required by my theory. However,

these constructs are predicted to have discriminant validity in that the associations

between them are not overly large (i.e., correlations greater than .85; see Kline,

2005), thus providing evidence that they are conceptually distinct.

2) It is predicted that the relations among purpose, meaningful engagement, and

PWB will meet the requirements of a mediated model, where purpose is predicted

to mediate the association between meaningful engagement and psychological

well-being. Specifically, the mediated model requires that: (a) Purpose and

61

meaningful engagement are correlated with PWB; (b) Meaningful engagement is

correlated with purpose; and (c) When purpose is included in the model, the paths

from meaningful engagement to purpose, and purpose to PWB remain significant,

but the path from meaningful engagement to PWB is attenuated (in a fully

mediated model, this path is reduced to non-significant).

3) The relationship between purpose and PWB is moderated by an orientation

toward beyond-the-self life goals. Specifially, I hypothesize that the association

between purpose and PWB will be stronger for those who are high in this type of

goal orientation, compared to those who are lower. Additionally, I hypothesize

that this relationship is not moderated by the presence of an orientation toward

self- focused life goals (which would provide evidence that the hypothesized BTS-

orientation moderation is attributable to the content of these life goals, and not

merely the greater degree of life goals in general).

4) Engaging in deep reflection and discussion about one’s life goals and pursuits can

function as a ―purpose intervention,‖ leading to both increased levels of purpose

and PWB.

Before tackling these research questions and testing these hypotheses, I will

devote the next chapter to providing an overview of the general empirical approach,

methodologies and characteristics of the samples employed in the studies, as well as

some measurement-related issues including the construction of my scale for assessing

meaningful engagement and measurement model building in the structural equation

modeling framework.

62

CHAPTER 3: EMPIRICAL APPROACH AND MEASUREMENT ISSUES

Overview

The empirical component of the present work brings together various groups of

data from more than one primary source—specifically, I employed a combination of data

collected for the purposes of a larger research project, along with a set of supplemental

data I collected for the purposes of addressing a research question (Research Question

#4) that was not addressable through the data collected for that larger project. Moreover, I

used different subsets of data from this larger project for different purposes (i.e., to

address different research questions). To reduce the potential for confusion, I will start

this chapter with a broad overview of my empirical approach and these sources of data.

The present work incorporated data that was collected23 as part of the Youth

Purpose Project (YPP) in the Stanford Center on Adolescence under the direction of

principal investigator William Damon. The project on the whole employed a two-wave

longitudinal, multi-method design (interviews and surveys) with adolescents age 12-22 at

the first wave of data collection. The current investigation only employed the survey data

collected from the oldest cohort in the YPP sample, comprising students who were 21-22

years old at the first wave of data collection (in the spring of 2007). For the purposes of

the larger YPP project, as many Wave 1 participants as possible were followed up

approximately eighteen months later (summer/early fall of 2008). For the purposes of my

dissertation, I (with support from the larger YPP project) collected additional survey data

on as many Wave 1 participants as possible at a point roughly midway between the two

23

As the survey/quantitative methodology specialist on the YPP, I was primarily responsible for the

collection of the majority of the data that were used in the present work.

63

waves of the YPP (in the winter of 2007). The details regarding the participants,

materials, procedures, attrition, etc., will be provided below and in the following

chapters.

My four primary research questions were addressed through three studies. Study 1

addressed the first and second research questions using the full sample of college

participants from Wave 1 of the YPP. Study 2 sought to both further substantiate the

findings from Study 1 regarding the second research question using longitudinal data, as

well as address the third research question; both of these studies employed the subsample

of the Wave 1 participants who also completed surveys during the second wave of the

YPP in the summer/early fall of 2008. Study 3 addressed the final research question using

the subsample of the Wave 1 YPP participants who also participated in my supplemental

mid-point survey assessment in the winter of 2007, and capitalized on a design

component of the YPP to test my intervention hypothesis (described in detail below).

Note that the Study 2 and Study 3 samples are not entirely independent (i.e., many of the

participants from the mid-point assessment also participated in the second wave of the

YPP data collection); despite the overlap in samples, I view the studies as separate as

they address different research questions via a completely different analytical approach.

Measurement Issues

In Chapter One, I outlined the various measurement tools used in the research

literature on purpose, meaningful engagement, and psychological well-being. In Chapter

Two, I laid out my conceptualizations of each of these constructs. Because they are

integrative definitions, advancing previous thinking, none of them are easily

64

operationalized by any one measurement tool. Instead, purpose and PWB may be

(separately) properly measured by way of a combination of established measures. It is

also the case that there are no existing measures (or combination of measures) that

properly permit the measurement of meaningful engagement as conceived herein—I thus

have constructed my own approach to measuring this construct. Because of the depth and

breadth of these measurement issues, I am devoting much of the current chapter (as

opposed to parts of the Method sections in the upcoming chapters covering the studies) to

scale construction and the measurement model I will employ in Study 1. 24 These will

then form the basis for components of the Study 2 and, to a less degree, Study 3 Method

sections and measurement approaches. I will first explicate the scale construction process

for the meaningful engagement variable, after which I will lay out how I approached the

measurement of purpose and PWB via a combination of existing instruments.

However, before I can detail these measurement issues, because scale

construction and measurement models require data I must first describe the participants

and procedures used in addressing them (these will be the same as those used for Study 1,

covered in Chapter Four). I will additionally explain how I addressed missing data in this

current sample.

Method

Participants and Procedure

In Wave 1 of the Youth Purpose Project, approximately four thousand

undergraduates were contacted via e-mail to be recruited to participate in the current

24

The measurement model in Study 2 will have similar components, but as I will be incorporating

longitudinal data in Study 2 a new measurement model will need to be tested. I will present these methods

and model in Chapter Five.

65

study from two different institutions of higher education in Northern California, one large

state university and one mid-sized community college.25 Specifically, only students who

were born in the year 1985 were contacted, to ensure they were approximately 21 years

old at the time of their participation. Of those contacted, four-hundred and twenty-seven

agreed to participate (mean age = 21.2 years, SD = 0.5 years). Though this is a relatively

low response rate (approximately 11%), it is not uncommonly low given the norm for

response rates to web-based survey administrations in college samples (see Sax,

Gilmartin, & Bryant, 2003).26 Participants were 61% female, and were mostly Caucasian

(41%), followed by Asian American (28%), Latino (14%), Pacific Islander (10%),

African-American (4%), and Native American (2%); approximately 5% of the sample

self- identified as multi-ethnic. Participants provided their consent on and completed an

online survey which included a battery of questionnaires and demographic items (median

completion time: 28 min.), in exchange for being entered into a lottery in which, if

selected, they received a $50 gift certificate to a popular online retailer.

The present study only used selected measures from among the battery of

questionnaires included on the larger YPP survey. For the purposes of the present sca le

construction and measurement models, I drew on the data collected for two measures

related to purpose in life, two measures of PWB, and all of the survey items designed

specifically to be included in the construction of my meaningful engagement assessment.

25

The exact number of people contacted is unknown, as the distribution of invitation e-mails was handled

by representatives at the two institutions of higher education from where we collected the data. The

numbers provided by the representatives were indicated as ―approximately 2000‖ e-mail contacts at each

school. We are fu rther unaware of how many of the e-mails were sent to invalid or unchecked e-mail

accounts (all e-mails were sent to students’ school ―.edu‖ accounts); it is often the case in college samples

that students do not use their school account (see Sax et al., 2003). 26

Though we have no data on nonresponse bias for the current sample, Sax et al. (2003) found that web -

based surveys typically draw more females, status-seekers, and people high in leadership traits , and fewer

―partiers .‖ It is unlikely that, if any of these nonresponse biases exist in the current sample, they would

significantly alter or g rossly reduce the generalizability of the results of the analyses.

66

Additionally, I also drew on two other variables measured in the YPP survey for the

purposes of controlling for demographic and other influences that have been found in the

literature to be related to my primary constructs of interest (e.g., Massey et al., 2008;

Steger et al., 2006). Specifically, I incorporated the survey questions which established

the participant’s gender (0=male, 1=female) and a measure of social desirability. 27 This

latter measure, a short (10-item) version of the Marlowe-Crowne Social Desirability

Scale (Reynolds, 1982; adapted from Crowne & Marlowe, 1960; items are available in

Appendix A) exhibited relatively low internal consistency (α=.54); nonetheless,

controlling for this measure has been shown to be effective in reducing the social

desirability bias (Ballard, 1992).

Missing Data

Missing data is a common problem in empirical research, in particular when

sample sizes are small and the data are longitudinal (as will be the case in Studies 2 and

3). It is not my intention to review the burgeoning literature on missing data and the

variety of methods to address them.28 I will simply provide some basic information

regarding how many of my data were missing, and how and why I addressed them the

way I did.

First, I determined that across the 75 variables on which data were collected and

used for the current investigation and the 427 participants (totaling 32,025 data points),

27

The survey also included items that assessed race/ethnicity, though these were not included in my

analyses as covariates. As a preliminary step to running my analyses with each of my samples, I checked

for associations among gender, race, social desirability, and the latent constructs. The race variable

(dichotomous, white/non-white) was not significantly associated with any of the latent constructs at any of

the time points. 28

Thorough reviews on missing data are presented by Little and Rubin (2002) and, more accessibly for the

non-statistician, by Acock (2005).

67

only 330 (or 1%) of these data were missing. Next, I explored the patterns of missingness

across the items; by far the most common pattern was no missingness, followed by

patterns of apparently random combinations of single items being skipped. There was no

evidence of consistent patterns of particular types or groupings of variables having

especially high missingness. This scan of the data led me to a determination that the

missingness of data in my dataset could be categorized as ―Missing at Random‖ (MAR;

Little & Rubin, 2002). MAR suggests that the likelihood of having missing data on a

given variable is not related to the participants’ scores on that variable after controlling

for other variables in the study. Thus, these other variables may provide insights into the

mechanism for explaining the missingness of values. According to Acock (2005),

common variables associated with missingness found in social science research include

level of education, race/ethnicity, age, gender, and indicators of PWB; fortunately, most

of these are among the variables the YPP survey assessed.

Instead of employing one of the traditional approaches to working with missing

values, such as listwise/pairwise deletion or mean substitution (which typically yield

biased estimates; Little & Rubin, 2002), I used a modern missing values single

imputation method known as ―expectation maximization‖ or EM, run using the LISREL

8.80 software package (Jöreskog & Sörbom, 1996). EM uses information about observed

relationships among all measured variables (and injects a degree of random error to

reflect uncertainty of imputation) to produce a new dataset in which all missing values are

imputed with maximum likelihood values (Acock, 2005; for a detailed explanation of

EM, see Dempster, Laird, & Rubin, 1977). The EM approach is appropriate for use when

68

the MAR assumption holds, and the number of data missing is relatively small (Little &

Rubin, 2002).

Measures

Meaningful Engagement. As noted in my literature review of the construct, most

scholars have devised their own approaches to assessing activity engagement and the

degree to which people find the activities in which they engage meaningful. Due to the

lack of reliable and valid measures of meaningful engagement in the literature, I have

constructed my own scale and approach to operationalizing the construct.

In the process of designing the larger YPP survey, a group of three scholars in the

Stanford Center on Adolescence (including me) put together a list of 34 activities from

five primary domains of adolescent life based on a thorough review of the youth

engagement literature (e.g., Eccles & Barber, 1999; Larson, 2000). These five activity

domains included aesthetic/leisure (e.g., dancing, sports), family (e.g., talking with

relatives), religion/spirituality (e.g., praying, attending religious services), school/career

(e.g., studying, working for pay), and community/volunteer (e.g., volunteering with those

in need, working on an environmental cause; see Appendix A for a full list of activity-

related survey items), and were meant to represent the most common kinds of activities

engaged in by the typical adolescent. Because this process was designed for use in the

larger YPP sample which cut across all of adolescence, some of the activities included

were not expected to be representative of all phases of adolescence (e.g., engagement in

the domain of family may involve different activities for younger adolescents living at

home—such as family dinners—compared to college students living away from home—

69

such as talking to relatives over the phone). Additionally, some items were determined to

be multiply interpretable or too vague (e.g., involvement with computers/technology).

For these reasons, before proceeding I sorted through the 34 activities to determine which

might not be appropriate for a college-aged sample and which were vague—fourteen

were removed from the list, leaving 20 activities for consideration in constructing the

larger meaningful engagement variable (a list of all of the activities included on the

survey is available in Appendix A).

Participants were asked to respond to two questions about each of these

activities: ―How often are you engaged in this activity?‖ indicating frequency of

engagement (nine-point Likert scale; 1 = never, 9 = every day) and ―How meaningful is

this activity to you?‖ indicating meaningfulness of engagement (five-point Likert scale; 1

= strongly disagree, 5 = strongly agree). The frequency item scores were rescaled to a 1-

5 scale to match the scale of the meaningfulness items; following this, for each activity,

the frequency item score was multiplied by the meaningfulness item score to create a

single meaningful engagement item score for each activity. The scores were again

rescaled, this time to a 1-7 scale, for more direct comparability with the other measures

included in the study. This process resulted in 20 total meaningful engagement items (one

per activity) with possible score ranges of 1-7.

Exploratory factor analysis (EFA) using principal axis factoring was then

performed (using the Stata/SE 10.0 statistical software; StataCorp, 2007) on these 20

meaningful engagement items, using an oblique (direct oblimin) rotation technique to

uncover latent factors.29 Determination of the number of factors to keep was guided by

29

Since the meaningful engagement construct was hypothesized to occur across life domains, the factors

were expected to be non-orthogonal (i.e., correlated). Direct oblimin rotation is generally considered the

70

three considerations, including two traditional cut-off guidelines for EFA (eigenvalues

greater than 1, a.k.a., the Kaiser or Kaiser-Guttman test, and an inspection of the scree

plot), along with an emphasis on a priori theory (Hoyle & Duvall, 2004). Additionally,

the Kaiser-Meyer-Olkin measure of sampling adequacy was implemented to test the

degree of relations among the items in the current sample.

Using these guidelines, the first round of factor analysis produced an unclear

solution—the eigenvalue≥1 cutoff suggested a three-factor solution, while theory and

(less determinatively) the scree plot suggested a five factor solution (a table and scree

plot of these results are available in Appendix B). Given the compelling nature of the

theory behind the groupings of activities (i.e., from the literature review which served as

the basis for the original construction of the survey), I determined the five factor solution

to be more appropriate. However, in this first-run solution two of the items (meaningful

engagement in sports and writing) did not load on any of the factors above the traditional

item loading cut-off of .30 (Tabachnick & Fidell, 2006); they were thus dropped and the

analysis rerun. This second run including the remaining eighteen items produced a

similar solution as the first run, again suggesting either a three-factor or five-factor

solution—for the same reasons, I considered the latter more appropriate and determined

this to be the final EFA results for the meaningful engagement items (see Table 1). These

results also demonstrated acceptable sampling adequacy (Kaiser-Meyer-Olkin overall

statistic = 0.76; values over 0.70 are considered ―middling‖ or acceptable; Kaiser, 1974).

standard rotation method when one wishes to obtain a non-orthogonal (oblique) solution (Tabachnick &

Fidell, 2006).

71

Table 1

Exploratory Factor Analysis of Meaningful Engagement Items with Oblique Rotation

Factor structure coefficients

Meaningful Engagement --------------------------------------------------------

Activity, by domain Factor1 Factor2 Factor3 Factor4 Factor5

Family: Family celebrations 0.66 0.03 0.14 -0.10 0.21

Talking with relatives 0.79 0.03 0.02 0.09 -0.07

Family vacations 0.39 0.10 0.21 -0.03 0.18

Visiting with relatives 0.86 -0.02 -0.07 0.03 -0.04

Religion/Spirituality: Praying 0.06 0.87 -0.02 -0.04 0.00

Attending religious services -0.02 0.85 0.01 -0.01 -0.02

Thinking about faith -0.07 0.77 0.01 0.10 0.04

School/Career: Participating in class -0.04 -0.05 0.58 0.13 0.04

Studying -0.02 0.07 0.60 0.07 -0.13

Working for pay 0.17 -0.07 0.45 -0.09 0.06

Volunteering/Community: Environmental cause 0.00 -0.11 0.07 0.44 0.20

Neighborhood 0.04 0.03 0.05 0.66 -0.02

Helping those in need 0.13 0.11 0.02 0.57 0.03

Political cause -0.05 -0.03 0.08 0.43 0.08

Aesthetic/Leisure: Creating art -0.13 -0.02 -0.08 0.12 0.52

Dancing 0.19 0.06 0.06 0.03 0.52

Drama/Theatre/Stage -0.03 0.01 -0.07 0.05 0.55

Music 0.01 0.08 0.24 -0.15 0.33

Eigenvalue 3.68 1.72 1.14 0.84 0.61 % variance 51.89 24.29 16.17 11.92 8.56

Note: N=427. The present structure matrix was produced via principal axis factoring with oblique (d irect

oblimin) rotation. Loadings greater than .30 appear in boldface.

Respondents’ scores on the items loading onto each factor above .30 were then

averaged together to create a subscale for each meaningful engagement activity domain.

72

Table 2 shows these domains’ descriptive statistics (the possible range for each domain

was 1-7)

Table 2

Descriptive Statistics for Meaningful Engagement Activity Domain Subscales

Meaningful Engagement Activity Domain

Number of items Mean SD Range

Cronbach's alpha

Family 4 3.36 1.19 1.00-7.00 0.81

Religion/Spirituality 3 2.74 1.96 1.00-7.00 0.88

School/Career 3 4.32 1.36 1.45-7.00 0.60

Volunteering/Community 4 1.72 0.96 1.00-7.00 0.65

Aesthetic/Leisure 4 2.57 1.17 1.00-7.00 0.55

Note: N=427.

Some of the Cronbach’s alphas were relatively low (coefficients of 0.70 and

above are traditionally considered to be acceptable; Nunnally, 1994), though this test of

internal consistency is sensitive to the number of items of the scale. For the three domains

with αs<.70—School/Career, Volunteering/Community, and Aesthetic/Leisure—the

average inter- item correlations were, respectively, .42, .44, and .35, with none of the

individual item-to- item correlations within scale less than .30. However, the internal

consistency of these scales was not of primary concern, as the main objective of creating

the subscales was not that they be used as stand-alone variables for my primary analyses.

Instead, they were meant to comprise the indicators or ―manifest variables‖ of a

measurement model in a structural equation modeling, or SEM, framework, which map

onto a latent variable signifying overall meaningful engagement across these domains (I

73

will provide a brief description of SEM and the role of the measurement model in the

SEM framework in the Measurement Model section at the end of this chapter).

To check whether the domain subscale scores met the univariate normality

assumption, a requirement in both the traditional OLS as well as the SEM frameworks, I

ran D'Agostino & Pearson’s (1973) omnibus test for univariate normality. This test

revealed that the Aesthetic, Religion, and Volunteering domains may be non-normally

distributed (ps<.01); however, this test (along with most other tests of normality) is

sensitive to large sample size, so I proceeded to visually inspect the histograms and

diagnostic plots directly. This visual inspection indicated that the Religion and

Volunteering domain scores appeared to deviate from the normal curve (specifically, the

Religion domain scores were relatively rectangularly distributed, and the Volunteering

domain scores were positively skewed). However, the use of SEM has been shown to be

quite robust to such violations (McDonald & Ho, 2002), so these normality violations

should not significantly affect the results of the analyses including meaningful

engagement, all of which will be performed in the SEM framework. I also checked each

of the domain scores for univariate outliers, and found none. Following these assumption

checks, I determined the meaningful engagement domain scale scores were suitable for

use in building an overall meaningful engagement latent construct in the SEM

framework. The details of the process for how this meaningful engagement latent

variable was created from these five domain scores will be described and depicted (along

with that of the purpose and PWB constructs) in the Measurement Model section at the

end of this chapter.

74

Though some of the domain subscale scores demonstrated only modest

Cronbach’s alphas, since their inter- item correlations showed reasonable internal

consistency we can use these scales to provide some preliminary insights into meaningful

engagement in emerging adulthood.30 Though not among the primary research questions

in the present work, it is worth noting that emerging adults appeared to on average

engage more meaningfully in some domains of activities compared to others.

Specifically, the school/career domain was most meaningfully engaged in, followed by

family, religion/spirituality and aesthetic/leisure, and volunteering/community (see

Figure 3).

30

However, because the psychometric propert ies were not strong, any findings using these scales should be

interpreted conservatively.

75

Note. N=427. Error bars represent 95% confidence intervals . Activ ity domains are listed in descending

order of mean scores.

Figure 3. Means of meaningful engagement domain subscale scores

It is not surprising that school/career is the highest meaningful engagement

domain in a sample of 21-year-old college students, since for most of them the bulk of

their time is spent in and their primary focus is on school and preparing for the world of

work. However, at first glance it may be surprising that the volunteering/community

domain has the lowest scores, given that research has found this domain to be one from

which people generally derive much meaning (Keyes & Waterman, 2003; Thoits &

Hewitt, 2001). Herein we see a good example of how the present meaningful engagement

construct is different from previous approaches to understanding meaningful activity

engagement. Emerging adults may on average find volunteering relatively meaningful,

76

but they are likely rather infrequently engaged in such activities.31 Thus, even though the

current sample may have exhibited relatively high mean scores on meaningfulness across

the volunteer activities assessed, typically lower mean frequency scores on these

volunteer activities would have restricted the combined meaningfulness X frequency

scores (which constitute the meaningful engagement variables). In other words, unless

the activities one finds most meaningful in life are actually engaged in with some degree

of frequency, their meaningful engagement scores in those domains (and likely overall)

will be limited.

There is another result worth pointing out in the meaningful engagement domain

subscale mean scores. Though the scores themselves have no absolute meaning (since

each is a product of two items measured on agree-disagree scales), we can infer from

where they are along the created scale something about how much, on average, people

are meaningfully engaged in these domains relative to what is possible. In none of these

domains do emerging adults engage very frequently and derive lots of meaning (if that

were the case, we would see mean scores at the high end of the range). Indeed, only the

school/career domain is even above the mid-point.32 Overall, these statistics might

suggest that emerging adults are more meaningfully engaged on average in some domains

compared to others, but likely not very meaningfully engaged in their lives in general.

31

To help make this point more concrete, I can report that the original YPP data which kept

meaningfulness and frequency of activity involvement separate seems to confirm this. The average

meaningfulness score of the activities which comprise the volunteering/community domain was 3.85 (on a

1-7 scale; roughly equivalent to a mid-point response of ―moderately meaningful‖), while the average

frequency was only 2.26 (on a 1-7 scale, which is roughly equivalent in absolute terms to ―once a year‖).

While separate analyses of frequency of activity engagement and meaningfu lness of activity engagement

would be ripe for investigation, I did not want to introduce an additional level of complexity to the current

work and thus have not exp lored such analyses. 32

Mid-point scores for a given activity/domain may imply 1) high meaningfu lness and low frequency, 2)

low meaningfulness and high frequency, or 3) middling scores on both ratings. Again, while it may be

interesting to further explore the variations in the constituent parts of each meaningful engagement domain

score, it is beyond the scope of the current investigation (for reasons provided in the previous footnote).

77

Purpose and Psychological Well-Being. I have grouped my description of the

measurement of the purpose and psychological well-being constructs together because

my general approach to assessing them is roughly the same. I will start by describing this

general approach, after which I will address the instruments used to assess each.

As explicated in Chapter Two, my conceptualizations of both purpose and PWB

incorporated two primary components: for purpose, both identification of a life purpose

and goal-directedness toward accomplishing it; for PWB, both life satisfaction and self-

perceived fulfillment of potential. As there are no measurement tools available which

fully and properly operationalize each of these conceptualizations (i.e., that combine the

measurement of the two components per construct into a single instrument), both require

more than one measurement tool for their assessment (i.e., two measures per component).

For each of the two constructs, I have made an argument for their conceptual

homogeneity in Chapter Two. The current approach to their assessment involved a two-

step process. First, the items of scales used to measure each of the components (for each

construct) were subjected to an EFA, to ensure not just conceptual but also statistical

homogeneity. Second, the results of the EFA for each construct were used to inform a

process for combining items of a scale known as ―parceling,‖ which is an increasingly

popular psychometric technique in multivariate statistical approaches, especially as a

precursor to SEM (Kline, 2005).

A parcel can be defined as ―an aggregate- level indicator comprised of the sum (or

average) of two or more items, responses, or behaviors‖ (Little, Cunningham, Shahar, &

Widaman, 2002, p. 152). The traditional approach to creating scale scores involves

78

simply summing (or averaging) the response scores of the individual items which

comprise the scale; in contrast, parceling first entails summing (or averaging) the

response scores of a select number of items into one parcel score, and repeating this

process until one has collected the desired number of parcels (usually three). 33 To make

this process more concrete via example, suppose a researcher is using a homogeneous,

unidimensional fifteen- item rating scale. The traditional approach would simply entail

adding or averaging the fifteen items together for a total scale score. In contrast, using the

parceling approach the researcher would group together the items into three sets of five

items per set (i.e., parcel), and for each set/parcel would sum or average the five item

response scores to create a parcel score.34 The researcher thus has three parcels, which

may then be used as the indicators of a latent construct in an SEM framework. I will

explain the process I employed to create the parcels for each of the purpose and PWB

constructs below.

Parceling has a number of psychometric advantages—it is beyond the scope of the

current paper to review all of the pros and cons (see Little et al., 2002, for an excellent

summary), I will simply note that I felt parceling was particularly beneficial to the current

investigation for two primary reasons beyond those typically considered in the SEM

literature (e.g., higher reliability, parsimony, etc.). First, assessments of purpose and

PWB notoriously produce scales with non-normal (skewed) measurement properties

(Cummins, 2003; Steger & Frazier, 2005), and parceling can reduce the likelihood of

distributional violations (Little et al., 2002). Second, the sample sizes for the longitudinal

33

The use of three parcels as indicators of a latent variable is most common because in SEM, three

indicators per construct means that a measurement model is ―just identified‖ (meaning that there are the

same number of free parameters as there are known values), which is optimal for CFAs (Kline, 2005; Little

et al., 2002). 34

Processes for determin ing how items might be parceled together will be described below.

79

analyses in Study 2 of the present work were relatively small for SEM (i.e., less than 200;

see Kline, 2005), which can be at least partially offset by the use of parcels because fewer

parameters are then needed to define a construct. Though the sample size for Study 1 was

relatively large, I wished to employ the same psychometric approach in Study 1 as in

Study 2 so the same inferences across the studies could be made.

Purpose.35 The Meaning in Life Questionnaire-Presence subscale (MLQ-P;

Steger et al., 2006) and Ryff’s (1989a) Purpose in Life subscale of her PWB Scales

(PWB-P) were included on the YPP survey as measures relevant to purpose. Overviews

of these measures were provided in Chapter One. In the present study, the five- item

MLQ-P and nine- item PWB-P were assessed on seven-point, Likert scales (1 = strongly

disagree, 7 = strongly agree; scale items and instructions can be found in Appendix A).

Both scales included negatively-worded items, which were reverse-coded.

As noted earlier, the definition of purpose employed in the present work required

that attributes of both the MLQ-P and PWB-P scales be considered in concert; to refresh

the reader, the MLQ-P taps into the degree to which respondents understand and have

identified their life purpose(s), and the PWB-P taps into the degree to which respondents

are planful about and oriented toward accomplishing their life goals. These scales have

been found to be moderately strongly correlated in previous research (e.g., Moran et al.

(2009) reported a zero-order correlation of r=.52, p<.001), and share largely overlapping

conceptual space.

35

In addition to the measurement of the purpose construct described in this section, in Study 2 (covered in

Chapter Five) I incorporated a self-constructed measure of categories of purpose (i.e., self- and BTS-

oriented life goals). Since this measure was not employed in Study 1, I will not describe it here; a detailed

description will be provided in Chapter Five.

80

Before parceling the items of the MLQ-P and PWB-P scales, I performed an EFA

on the fourteen items which comprise them to test whether they loaded onto one factor, as

hypothesized. Principal axis factoring with oblique (direct oblimin) rotation was

implemented using Stata/SE 10.0 statistical software, and the Kaiser-Meyer-Olkin

measure of sampling adequacy was used to test the degree of relations among the items.

The factor solution produced from this analysis was not clear cut; it could have been

interpreted as either one or two factors, depending on the criteria used (Tabachnick &

Fidell, 2006). The traditional eigenvalue cut-off of 1.00 would suggest two factors (the

first factor eigenvalue=5.86; the second factor was barely above the 1.00 cut-off;

eigenvalue=1.07), while the scree plot was difficult to interpret, though appearing to start

to level off after the first factor (the one-factor and two-factor EFAs, as well as the scree

plot results are presented in Appendix B). For both conceptual reasons and statistical

reasons, I determined the one-factor solution was preferable. The first factor accounted

for 86% of the variance and all of the items loaded at least .30 onto the first unrotated

factor. Additionally, in the rotated two-factor solution, four of the nine items (all from the

PWB-P) double- loaded (i.e., had loadings above .30) on both factors. I believe the best

explanation for this has less to do with discriminant item content, and instead points to

two possible sources of method variance. First, the MLQ-P items were clustered together

at the beginning of the survey and the PWB-P items were clustered at the end, so

respondent fatigue could have been a source of method variance (since the survey took on

average nearly 30 minutes). Second, and I believe more compelling, the two-factor

solution may have been driven by what psychometric research has identified as a

negative-wording method factor (see Marsh, 1996). All of the positive-worded items

81

loaded at least .30 onto the first factor, while only one of the negatively-worded items did

(which also double- loaded on the second factor); all of the negatively-worded items

loaded at least .25 onto the second factor, along with three of the positively-worded items

(all of which also double- loaded on the first factor). Importantly, when items are

combined into one scale, parceling can help distribute and attenuate these method effects

(Little et al., 2002). The Kaiser-Meyer-Olkin overall statistic for the EFA demonstrated

high sampling adequacy at 0.91.

Upon establishing this one-factor solution for the items across the MLQ-P and

PWB-P scales, I proceeded to create three parcels which together incorporated all

fourteen items. Parcels can be created by either combining items randomly, or by

deliberate (and well-considered) grouping—I took the latter approach. Following the

guidelines of Little et al. (2002), I considered three factors in constructing the parcels.

First, I evenly distributed the negatively-worded items across the parcels, to attenuate the

negative-wording method effect that appeared to have come into play in the EFA.

Second, I evenly distributed the items from the two scales across the parcels, for equal

representation and to attenuate any possible fatigue method effects. Third, where possible

I paired the items that loaded highest onto the one-factor solution with the items that

loaded the lowest, so as to balance the representativeness of the construct via the items

across the parcels. This process produced two parcels with the average scores of five

items and one parcel with the average scores of four items, which then could function as

the indicator variables of the purpose latent construct in the measurement model (see the

Measurement Model section at the end of this chapter). Table 3 shows the descriptive

statistics for the purpose construct parcels.

82

Table 3

Descriptive Statistics for Purpose Parcels

Purpose Parcel Number of

items Mean SD Range

Parcel 1 5 5.42 1.05 1.00-7.00

Parcel 2 5 4.99 1.11 1.40-7.00

Parcel 3 4 5.03 1.05 1.60-7.00

Note: N=427.

Notably, a check of D'Agostino & Pearson’s (1973) test of normality showed that

despite the espoused benefits of the parceling process, two of the three parcels

significantly deviated from normality (ps<.01); however, a visual inspection of the

histograms and diagnostic plots showed that neither of these appeared to grossly violate

the normality assumption, to which (as noted earlier) SEM is quite robust.

Psychological Well-Being. The Satisfaction with Life Scale subscale (SWLS;

Diener et al., 1985) and the Fulfillment of Potential subscale (FOP) of Shultz et al.’s

(2006) Thriving Measure were included on the YPP survey as measures relevant to PWB.

Overviews of these measures were provided in Chapter One. In the present study, the

five- item SWLS and three- item FOP were assessed on seven-point, Likert scales (1 =

strongly disagree, 7 = strongly agree; scale items and instructions can be found in

Appendix A). Unlike the purpose measures, neither of these scales included any

negatively-worded items.

83

As was the case for the purpose construct, the current definition of PWB

integrates two closely-related conceptual notions, life satisfaction and fulfillment of

potential, which were operationalized on the YPP survey via the SWLS and FOP,

respectively. The same procedure for building parcels that was described above for the

purpose construct was applied here, starting with an EFA. This time, the results clearly

produced a one-factor solution (only one eigenvalue≥1, and a leveling of the scree plot

after one factor; see Appendix B), with all items loading onto this single factor at levels

above .45 and a strong Kaiser-Meyer-Olkin overall statistic of .89. Again, I took an

intentional approach to parcel construction, following the same guidelines as I did in my

approach to parceling the purpose items (with the exception of distributing based on item

wording, as all of the items were positively-worded). This process produced two parcels

with three items and one parcel with two items, which could then function as the

indicator variables of the PWB latent construct (as covered in the Measurement Model

section below). Table 4 shows the descriptive statistics for the PWB construct parcels.

Table 4

Descriptive Statistics for Psychological Well-Being Parcels

PWB Parcel

Number of

items Mean SD Range

Parcel 1 3 4.59 1.24 1.00-7.00

Parcel 2 3 5.04 1.26 1.00-7.00

Parcel 3 2 4.30 1.23 1.00-7.00

Note: N=427. PW B = Psychological Well-Being.

84

As before, a check of D'Agostino & Pearson’s (1973) test of normality showed

that two of the three parcels significantly deviated from normality (ps<.01); however,

once again a visual inspection of the histograms and diagnostic plots showed that neither

of these appeared to grossly violate the normality assumption. So, as was the case with

the previous variables which showed possible signs of non-normality, I felt comfortable

proceeding with these variables unaltered (i.e., not transforming them)36 and continuing

with the planned analyses using maximum likelihood SEM that as noted is relatively

robust to normality violations.37

Measurement Model

Before describing the current measurement model, it is important to provide some

brief background on structural equation modeling in general, and how measurement

models work within an SEM framework. SEM might be thought of as a complex and

more powerful alternative to multiple regression as a means toward understanding

relations among a set of constructs. Compared to multiple regression, it allows more

flexible assumptions and reduces measurement error, and arguably more intuitively

allows for the construction and testing of theoretical models via graphical depictions of

these models and simultaneous analysis of all of the variables in the models (Kline,

2005). The mechanics of SEM involve matrix algebra performed on the variance-

covariance matrix of a set of measured variables. Most SEM approaches, including the

36

Though a viable option, transforming variables can render them difficult to interpret. 37

Suggested approaches to performing SEM with non-normal data, such as using generalized or weighted

least squares estimators, have been found to underperform compared to the maximum likelihood approach

(Olsson, Foss, Troye, & Howell, 2000). Other approaches, such as asymptotic distribution free estimators

and bootstrapping, require very large sample sizes, which would be problemat ic for some of my analyses.

Given that maximum likelihood SEM is robust to normality violat ions, I felt the trade-off of the benefits

using that approach outweighed the potential complications of adopting one of the approaches for non -

normal data.

85

one I employed, use maximum likelihood estimation, which means that ―the estimates

maximize the likelihood (the continuous generalization) that the data (the observed

covariances) were drawn from [a given] population‖ (Kline, 2005, p. 112).

The SEM approach also permits statistical testing of the degree to which a model

reproduces the data (i.e., the variance-covariance matrix), or what is known in the SEM

literature as ―model fit.‖ There are a number of different model fit indices, and no clear

conventions (though plenty of ongoing debate) regarding which are the best to use.38 For

all of my analyses which employ structural equation modeling techniques, I will report

the following fit statistics as recommended by Kline (2005) and Little (personal

communication, June 3, 2009): 1) the model chi-square (χ2), 2) the Root Mean Squared

Error of Approximation (RMSEA; Browne & Cudeck, 1993) along with its 90%

confidence interval, 3) the Bentler Comparative Fit Index (CFI; Bentler, 1990), and 4) the

Non-Normed Fit Index (NNFI; also known as the Tucker-Lewis fit index; Bentler &

Bonnett, 1980). The conventions regarding acceptable fit cut-offs on these indices are as

follows (see Hu & Bentler, 1999): 1) the model chi-square is a Pearson chi-square

statistic which has a p-value; ideally, this p-value is non-significant when the fit is good39

(the model chi-square is actually a test of ―badness-of- fit‖—the higher its value, the

worse the fit); 2) the RMSEA is also a ―badness-of- fit‖ test; values of .06 and below

represent good fit, and for smaller samples values between .06 and .08 are thought to be

acceptable; 3) the CFI should be close to .95 or higher, and likewise 4) the NNFI should

38

A review of these indices and the pros and cons of each goes beyond the scope of the present work. For a

thorough review, I refer the reader to Barrett (2007) and Hu and Bentler (1999). 39

However, because the model chi-square is sensitive to the sample size, many have observed that when

the sample size is large (i.e., N>200) it is unrealistic to expect the p-value to be non-significant. As such,

this fit index is typically paid little attention with large samples.

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be close to .95 or higher. When all of these criteria are met, one may conclude that there

is a good fit between the hypothesized model and the observed data.

The process of structural equation modeling involves two primary steps:

validating the measurement model and fitting the structural model. A measurement model

demonstrates how the measures of interest in a study map onto a researcher’s latent

theoretical constructs, typically by way of confirmatory factor analysis, or CFA. In the

present case, the latent constructs are purpose, meaningful engagement, and PWB; and

the measures (or indicators, a.k.a. ―manifest variables‖) are the five domains of

meaningful engagement (which are theorized to map onto the meaningful engagement

latent construct), the three parcels created by combining the items of the MLQ-P and the

PWB-P (which are theorized to map onto the purpose latent construct), and the three

parcels created by combining the items of the SWLS and the FOP (which are theorized to

map onto the PWB latent construct). Establishing that a measurement model fits one’s

sample data is a prerequisite step to fitting a structural model (i.e., the correlational and

theoretically causal links between the latent constructs), which were analyzed in Studies

1 and 2 and will be presented in Chapters Four and Five.

Before validating the measurement model, I ran checks for multivariate normality

and outliers on the eleven manifest variables to be included in the model. To check for

multivariate normality, I ran an omnibus test for multivariate normality prescribed by

Doornik and Hansen (2008) via the ―omninorm‖ command in Stata/SE 10.0 (see Baum &

Cox, 2007); this test confirmed, as anticipated (given the previously uncovered issues

with univariate normality), that the multivariate normality assumption was not met with

the current data (D-H statistic = 303.94, p<.001). I defer the reader to my earlier

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discussion for why I determined the violation of normality assumptions would not be

problematic for my current investigation. To check for multivariate outliers, I used the

Mahalanobis distance statistic and followed Kline’s (2005) suggestion to use a

conservative level of significance (p<.001); at this level, none of the observations were

multivariate outliers.

The measurement model (which presents the structure to be tested via the CFA)

for the three latent constructs and eleven total manifest variables is shown in Figure 4.

The rectangles denote manifest variables, the ovals represent latent constructs, and the

circles represent error terms. The model depicts paths (arrows) from each latent construct

to the other latent constructs, which indicate the relations among the constructs to be

freely estimated (I will address these paths in greater depth in Study 1 in the next

chapter). The model also shows paths from the latent constructs to the manifest variables;

these suggest that a specific set of manifest variables function as indicators of the

particular latent construct (which, as a hypothetical construct, cannot be directly observed

or measured) from which their arrows point. These paths from the latent constructs to the

manifest variables denote the hypothesized factor structure determined a priori by theory.

In other words, the arguments I made earlier in this chapter for the appropriateness of the

mapping of these particular measures (i.e., domain scores and parcels) onto their latent

factors provide the theoretical rationale for these paths. It also follows from theory that

these manifest variables only map onto the one latent factor they are hypothesized to

indicate (i.e., they do not double- load onto other latent constructs). The estimates for

these paths produced by running the CFA will tell us the extent to which the latent

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construct is reflected by each indicator, which reflects the equivalent of a factor loading

in traditional factor analysis.

Note: ME-F=Meaningfu l Engagement-Family domain subscale

ME-R=Meaningful Engagement-Religion/Spirituality domain subscale

ME-S=Meaningfu l Engagement- School/Career domain subscale

ME-V=Meaningful Engagement-Volunteering/Community domain subscale

ME-A=Meaningful Engagement-Aesthetic/Leisure domain subscale

Purp1, Purp 2, and Purp3 represent the parcel scores for Purpose

PWB1, PWB2, and PWB3 represent the parcel scores for Psychological Well-Being

EMEf-EMEa represent the error terms of the Meaningful Engagement domain scores

EPu1-EPu3 represent the error terms of the Purpose parcel scores

EPW1-EPW3 represent the error terms of the Psychological Well-Being parcel scores

Figure 4. Measurement model for meaningful engagement, purpose, and psychological

well-being

The model also shows arrows pointing from the error terms to the indicators—this

is standard way in SEM of acknowledging that with all assessment instruments there will

be some degree of measurement error, which here represents the variance not explained

by the factors (i.e., unique variance). In other words, the error terms represent all sources

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of residual variation in the domain subscale and parcel scores that is not explained by the

factors.40 Standard CFA models typically assume the measurement errors are independent

of each other and of the factors (Kline, 2005).41 These error terms, along with the latent

constructs (in ovals), thus have a double-headed arrow pointing to themselves to indicate

variance. The variances of the error terms incorporate both the unreliability of the

measurement (i.e., random error), and other sources of systematic variance not due to the

factors (e.g., method effects).

Before running a confirmatory factor analysis, one must make sure the model is

properly identified. This involves two steps: 1) making sure the number of free

parameters is equal to or less than the number of observations, 42 and 2) performing what

in the SEM framework is known as scale setting. In the current model, the number of free

parameters is 25 and the number of observations is 66; thus, the first criterion is met (it is

also how we know how many degrees of freedom we have to work with—i.e., the

number of observations minus the number of free parameters—in this case, df=41).

Regarding the second criterion, there are a number of d ifferent (and under most

circumstances equally valid) ways to approach scale setting (Kline, 2005). I elec ted to

impose what is known as the ―unit loading identification constraint,‖ which fixes the

unstandardized coefficient (i.e., loading) for the direct effect of one of each factor’s

indicators to 1.0 (which becomes known as the ―reference variable‖). This is the most

common approach to scale setting in CFA models (Byrne, 1998).

40

SEM is said to measure latent constructs without measurement error because these error terms essentially

function to hold the error separate. Put another way, the latent variab le only pulls in the varian ce

attributable to the construct, and leaves the measurement error behind. As noted earlier, th is constitutes one

of the considerable appeals of the SEM approach. 41

One exception to the assumption of uncorrelated errors occurs when dealing with longitudina l data, as we

will see in Study 2. 42

The number o f observations is equal to the number of variances and covariances among observed

variables (Kline, 2005).

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An additional function of this CFA will be to provide information regarding the

discriminant validity among the three latent constructs. In this framework, a correlation

coefficient nearing 1.00 (guidelines often suggest .85 or larger; see Kline, 2005) is

generally considered to indicate poor discriminant validity (Kenny, 1979). As noted

before, the paths among the factors indicate their relations with each other. Though the

strength of these relations will help address Research Question #1 (covered in Study 1 in

the next chapter), I will make note in the results of the current CFA of whether the factors

exhibit discriminant validity, as this is a key prerequisite to considering relations among

variables (Campbell & Fiske, 1959).

With these necessary conditions in place, a CFA of the above model was

estimated using the LISREL 8.80 software package to perform maximum likelihood

estimation. Results of this CFA are shown in Figure 5 below.

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Model Fit : χ2 (41, N=427) = 86.31, p<.001; RMSEA = 0.051 (0.036-0.066); CFI = 0.99; NNFI = 0.98

Note. N=427. All coefficients are standardized. Asterisks indicate reference variables. All other parameters

are statistically significant at the p<.05 level. In the Model Fit statistics, χ2 refers to the model ch i-square,

followed parenthetically by the model degrees of freedom and sample size. RMSEA = Root Mean Square

Error o f Approximation, followed by the 90% confidence interval of RMSEA. CFI = Comparative Fit

Index. NNFI = Non-Normed Fit Index.

Figure 5. Confirmatory factor analysis of meaningful engagement, purpose, and

psychological well-being results

There are a number of noteworthy results of this CFA. It is important to first

orient the reader to the model fit statistics reported at the bottom of the model (per SEM

convention). The first set of numbers refers to the model chi-square, with the model

degrees of freedom and sample size subscripted and in parentheses. Though the model

chi-square was statistically significant (i.e., p<.05), as noted earlier it should not be

viewed as problematic given the large sample size. The RMSEA of .051 was below the

conventional cut-off of .06; this statistic is followed by a reporting of the 90% confidence

interval for the RMSEA. The CFI and NNFI were well above the suggested cut-offs of

.95. Taken together, the fit statistics indicated an adequate model fit for the current CFA.

92

Upon having established the degree to which a model fits the data, it is relatively

common practice to then investigate any possible areas of misspecification in the model.

The two types of information which help identify misspecification include residuals and

modification indices. Should either of these sources indicate problem areas, the

researcher then has the option to use this information to respecify and reestimate the

model. However, doing so then reframes the investigation within an exploratory, rather

than confirmatory framework (Byrne, 1998). Given that the primary intent of the current

CFA was confirmatory (as a precursor to using SEM to establish relationships among the

latent constructs), and the model fit indices suggested a strong fit of the hypothesized

model to the sample data, it was unnecessary to proceed with misspecification checks and

possible post hoc analyses to improve the model.43

There are two other important sets of results in this CFA to point out. First, the

loadings were all above .30, indicating that the manifest variables each provided

important information about the latent variable it was hypothesized to indicate.

Additionally, we see that the paths between the purpose and PWB latent constructs and

their respective parceled indicators demonstrated very high factor loadings (all above

.80); this was not the case for the meaningful engagement latent construct, where the

loadings ranged between .32 and .64. Additionally, the error variances were higher for

these indicators than for those of the purpose and PWB parcels. These results suggest that

the meaningful engagement construct, while acceptably measured by the domain scores

which comprised its measurement and completely valid for use in the current

43

This same logic regarding model modification will apply throughout all of my SEM analyses across

studies—only if/when there is poor model fit will I consider making adjustments.

93

investigation, may not be fully encapsulated by the assessment approach advanced

herein, at least not in the years of emerging adulthood.

Second, the strengths of the relations among the latent constructs indicate they are

moderately-to-strongly associated with each other, though not so much so that they do

not exhibit discriminant validity (i.e., the standardized coefficients of the paths are well

under .85). In particular, this alleviates any concerns that meaningful engagement and

purpose might not discriminate (as might be suggested by Scheier et al., 2006). The

importance of these relationships to the current investigation will be further addressed in

the next chapter.

Before moving on to Study 1, it was important to establish that the model not only

fit the data well, but that the model fit the data better than plausible competing models.

Four competing models were thus tested: 1) a single- factor solution, wherein all manifest

variables loaded onto one general well-being factor (as might be suggested by the

multidimensional models of PWB); 2) a two-factor solution (to which I will refer as ―two

factor – version 1‖), in which the meaningful engagement domain scores loaded onto

their own meaningful engagement factor, and the purpose and PWB parcel scores loaded

onto a single general well-being factor; 3) a second two- factor solution (―two factor –

version 2‖), in which the purpose parcel scores loaded onto their own purpose factor, and

the meaningful engagement domain scores and the PWB parcel scores loaded onto a

single general well-being factor; and 4) a final two- factor solution (―two factor – version

3‖), in which the meaningful engagement domain scores and purpose parcel scores

loaded onto a single general purpose factor and the PWB parcel scores loaded onto a

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PWB factor.44 Table 5 shows the chi-square statistics and goodness-of- fit statistics for

each model, including my hypothesized three-factor model as presented above.

Table 5

Summary Statistics of the Competing Confirmatory Factor Analysis Models

Model χ2(427) df RMSEA CFI NNFI

Single-factor 682.96*** 44 0.18 0.83 0.78

Two-factor V1 576.38*** 43 0.17 0.85 0.81

Two-factor V2 291.15*** 43 0.12 0.94 0.92

Two-factor V3 197.44*** 43 0.09 0.96 0.95

Three-factor 86.31*** 41 0.05 0.99 0.98

Note. ***p<.001. V=version. df = degrees of freedom. RMSEA = Root Mean Square Error of

Approximation. CFI = Comparative Fit Index. NNFI = Non-Normed Fit Index.

To test whether the fit of the three-factor model proposed earlier was significantly

superior to the single- and two-factor models, I used three difference tests suggested in

the SEM literature (Kline, 2005): 1) the chi-square difference for nested comparisons

(Δχ2), which compares the chi-square values and degrees of freedom of two nested (or

hierarchical) models estimated with the same data to determine whether they provide the

same fit of the two models in the population; 2) the difference in CFI values (ΔCFI); and

3) the difference in NNFI values (ΔNNFI). Vandenberg and Lance (2000) suggest that if

each of the following three criteria is satisfied, a null hypothesis of equivalent model fit

could be rejected: 1) Δχ2 is significant at p< .05, 2) ΔCFI≥.01, and 3) ΔNNFI ≥ .02. In

each case, the model with the statistically significantly lower chi-square value and higher

44

Of the two-factor solutions, this final one seemed most plausible, as the meaningful engagement and

purpose constructs are conceptually closely related and therefore might be least likely to discriminate.

95

CFI and NNFI values should be considered the superior model. My hypothesis was that

the three-factor model used in the CFA presented above would fit the data better than the

four competing models.

The results of these chi-square, CFI, and NNFI difference tests indicated that the

three- factor model did indeed provide a significantly better fit to the data than each of the

competing models, including comparisons with: 1) the single- factor model, Δχ2(3) =

596.65, p< .001; ΔCFI = .16; ΔNNFI = .20; 2) two-factor model version 1, Δχ2(2) =

490.07, p< .001; ΔCFI = .14; ΔNNFI = .17; 3) two-factor model version 2, Δχ2(2) =

204.84, p< .001; ΔCFI = .07; ΔNNFI = .06; and 4) two-factor model version 3, Δχ2(2) =

111.13, p< .001; ΔCFI = .03; ΔNNFI = .03. Therefore, I was able to retain the three-

factor model for subsequent analyses, and proceeded to my SEM analyses in Study 1.

In summary, these results provide evidence of discriminant validity among the

constructs, as well as content validity of the constructs by way of the patterns and

acceptable strengths of factor loadings in the measurement model. Additionally, the

measurement model demonstrated adequate model fit, and was shown to be a stronger

model than a set of plausible competing models. Thus, the necessary conditions for

exploring relations about the constructs and my hypothesized mediational model are in

place, and are addressed in Chapter Four.

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CHAPTER 4: STUDY 1 – A CROSS-SECTIONAL TEST

OF THE MEDIATIONAL MODEL

Overview and Predictions for Study 1

In Study 1, I employed cross-sectional data to examine how meaningful

engagement and purpose related to PWB (Research Question #1), and tested the

mediational model presented in Chapter Two wherein purpose was hypothesized to

mediate the relationship between meaningful engagement and PWB (Research Question

#2). My review of the literature suggested purpose and PWB would be strongly related

(e.g., Steger et al., 2006; Steger & Kashdan, 2007); and though there is a relatively small

literature on meaningful engagement, that which does exist also suggests significant

relations with PWB (e.g., Peterson et al., 2005; Scheier et al., 2006). Since these three

constructs have not been investigated in concert, and since the relationship between

meaningful engagement and PWB has not been well-established, it is important that

relations among the constructs are established before testing a mediational model (i.e.,

that the conditions for a mediational process and analysis are met; Baron & Kenny,

1986).

Method


The participants and procedures for Study 1 were exactly the same as those used

for scale construction and building the measurement model in Chapter Three.

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Measures

The present study employed the measures (i.e., parcels and domain scores) of

purpose, meaningful engagement, and PWB, and well as the covariates (gender and

social desirability) described in Chapter Three.

Analytic Procedures

The current study employed structural equation modeling using the LISREL 8.80

statistical package for all analyses. The first step in SEM, validating the measurement

model, was performed in Chapter Three—the results of this step indicated the three latent

constructs of interest were validly measured by the eleven manifest variables via a three-

factor model. Thus, in the current chapter, I will focus on 1) the results of the

measurement model which indicate the relations among the latent constructs, and 2)

fitting my hypothesized mediational structural model. For the sake of clarity, in the

analyses and models I will present here I will focus on the latent variables and not the

manifest variables or the error terms indicated in the measurement model, since these

were addressed in the previous chapter and do not have direct bearing on the results for

the structural model.45

Results

The results for the current study are presented in two main sections: 1) tests of

relations among purpose, meaningful engagement, and PWB; and 2) tests of my

mediational hypothesis.

45

It is common practice in presentations of structural models to focus only on the latent variables and the

relations among them (Byrne, 1998).

98

Relations among Purpose, Meaningful Engagement, and Psychological Well-Being

The standardized coefficients of the relations among purpose, meaningful

engagement, and PWB, as first shown in the paths among the latent constructs in Figure 5

in the previous chapter, are summarized in Table 6.

Table 6

Correlations among Purpose, Meaningful Engagement, and Psychological Well-Being

Variable 1 2 3

1. Purpose - 2. Meaningful Engagement 0.59*** -

3. Psychological Well-Being 0.63*** 0.46*** -

Note. N=427. ***p<.001

These results suggested that 1) purpose and meaningful engagement were strongly

related (r=.59, p<.001), and that both were moderately-to-strongly related to PWB (r=.63,

p<.001 and r=.46, p<.001, respectively). Additionally, I wanted to address whether these

relationships were significantly attenuated by controlling for gender and social

desirability. I re-ran the measurement model with both of these variables included as

covariates of the three latent constructs (i.e., I introduced paths from the covariates to all

three latent constructs). The results showed that gender (female=1, male=0) and social

desirability were both significantly related to purpose (r=.11, p<.05 and r=.23, p<.001,

respectively), meaningful engagement (r=.31, p<.001 and r=.20, p<.001, respectively),

and PWB (r=.10, p<.05 and r=.25, p<.001, respectively). However, controlling for these

99

variables did not significantly attenuate the relations among the latent constructs (all

remained significant at p<.001).

Testing the Mediational Model

With the moderate-to-strong relations among purpose, meaningful engagement,

and PWB having been established, the necessary preconditions were in place to test my

mediational hypothesis, that purpose mediates the relationship between meaningful

engagement and PWB. To test this model, I introduced the three hypothesized paths

among the latent constructs (meaningful engagement PWB, meaningful engagement

PWB, purpose PWB) into my measurement model to create a structural model.

This hypothesized model was depicted in Figure 1 in Chapter Two. The results of the test

of my mediational model are presented in Figure 6.

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Model Fit : χ2 (41, N=427) = 86.31, p<.001; RMSEA = 0.051 (0.036-0.066); CFI = 0.99; NNFI = 0.98

Note. N=427. ***p<.001, ns

p>.05. The dotted line represents the mediated path. Italicized effect sizes

below lines represent zero-order correlations among variab les ; non-italicized effect sizes above lines

represent mediation model results . All coefficients are standardized.

Figure 6. Mediational model of purpose, meaningful engagement, and psychological

well-being

These results showed that while the relationship between purpose and meaningful

engagement was unchanged from the measurement model to the structural model, and the

relationship between purpose and PWB only dropped slightly (from a standardized

coefficient of .63 to .54; both significant at p<.001), the relationship between meaningful

engagement and PWB dropped considerably (from a standardized coefficient of .46,

p<.001, to a standardized coefficient of .14, p>.05). These results met the relatively

informal criteria suggested by Baron and Kenny (1986) to judge whether mediation has

occurred, namely that the effect size for the path from meaningful engagement to PWB

clearly dropped; however, there are statistical methods for more formally testing whether

mediation has occurred (Baron & Kenny, 1986; MacKinnon & Dwyer, 1993). The most

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prominent of these tests is known as the Sobel test (Sobel, 1982), which statistically

determines whether a mediator (purpose) carries the influence of an independent variable

(meaningful engagement) to a dependent variable (PWB). The results of the Sobel test

showed that purpose did in fact statistically mediate the relationship between meaningful

engagement and PWB in the present sample (Sobel test statistic: 5.41, p<.001). 46

I also tested again whether gender and social desirability had any effect on the

mediational model. As before, the impact of including these covariates was minimal; the

standardized coefficients only changed by .01-.02, and the significance levels were not

notably impacted. Thus, my mediational hypothesis was supported by my Study 1

analyses, even after controlling for gender and social desirability.

Study 1 Discussion

I presented data in Study 1 which addressed my first two research questions: 1)

Are purpose and meaningful engagement related to psychological well-being? and 2)

Does purpose mediate the relationship between meaningful engagement and PWB? The

results suggested that purpose and meaningful engagement are indeed related to PWB, as

well as each other. This provides support for the idea that purpose, when conceived of as

the presence and pursuit of higher-order life goals, does in fact predict PWB. This in

itself is an important finding, as few studies which have similarly considered purpose to

be a higher-order life goal have provided empirical findings relating it to well-being

(Steger et al., 2008), and none of these studies of purpose-as-life-goal have integrated

into their operational definitions the notions of goal-directedness and future-orientation.

46

To run this analysis, I used Preacher and Leonardelli’s ―Calculat ion for the Sobel Test: An interactive

calculation tool for mediation tests‖ found at http://people.ku.edu/~preacher/sobel/sobel.htm.

http://people.ku.edu/~preacher/sobel/sobel.htm

102

At the same time, these results are not surprising, given the conceptual overlap between

the current conceptualization and others’ notions of purpose (as explicated in Chapter

One), which the broader literature has addressed and shown relations with PWB. Still,

given that there has been some indication in the literature that the presence of higher-

level strivings—compared to having lower- level, more concrete goals—may lead to

reduced well-being (Emmons, 1999), the strong correlation between purpose and PWB

was not a foregone conclusion. It may be the case that goal-directedness, integral to the

current conceptualization of purpose but not to Emmons’s exploration of higher-order

strivings, helps to mitigate the problems of having overly abstract goals which may not

easily lend themselves to a plan of action. As Emmons suggested, well-being may be

enhanced when one uses her higher- level goals as a framework within which she

constructs a complex of lower- level, more concrete goals (see also Elliot & Thrash,

2002); the goal-directedness component of the current conception of purpose may thus

help to facilitate this process.

Perhaps the more significant finding regarding the first research question is that

meaningful engagement, which has received little attention in the purpose literature, was

shown to be highly related to both purpose and PWB. The strong relationship between

meaningful engagement and purpose may actually be viewed as an indication of

concurrent validity, given the conceptual similarity of the two constructs which have

meaning at their core (one more in the behavioral realm, the other in the cognitive realm).

It is noteworthy, however, that despite their conceptual similarity these two constructs

demonstrated sufficient discriminant validity. The moderately strong correlation between

meaningful engagement and PWB may be viewed as a substantial indicator of the

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importance of living one’s life in a meaningful way toward being psychologically

healthy.

The mediational model tested in Study 1 addressed the second research question,

and provided support for the hypothesis that the relationship between meaningful

engagement and PWB is mediated by purpose. However, the directionality of these

effects requires special attention. As noted in Chapter 2, the directional relationship from

meaningful engagement to purpose makes strong theoretical sense, especially in the years

of late adolescence and emerging adulthood. This represents a point in young people’s

lives when they have likely already had many opportunities to try out different activities

and figure out which they find most meaningful, and also have the autonomy (which they

may not have had as children or early adolescents) to make decisions that lead to

continued engagement in those activities (Brandstädter, 2006; Debats, 2000; Waterman,

1993). It is additionally around this time when young people are crystallizing various

aspects of their identities, which have been developing throughout the formative years of

adolescence (Erikson, 1968; Marcia, 1966). Since emerging adulthood is a critical phase

of development when life goals are thought to be established (Arnett, 2000; Roberts et

al., 2004), it is logical that being meaningfully engaged in the activities of one’s life (and

making choices to get and stay involved in activities from which one has determined one

derives the most meaning) in the adolescent years, combined with the greater likelihood

of a well-developed identity toward the end of adolescence (which lays the groundwork

for establishing and committing to purposeful life goals; Damon, 2008), leads to an

increased likelihood that one finds purpose in emerging adulthood.

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It is noteworthy that these results do not provide support for the alternative

hypothesis that meaningful engagement mediates the relationship between purpose and

PWB. This alternative hypothesis would suggest that the effect size for the purpose

PWB link would be attenuated when meaningful engagement is added to the model.

Though there was slight attenuation of the purpose-PWB link (i.e., the effect size dropped

from .63 to .54), the Sobel test of this mediational path was not statistically significant at

the p<.05 level (Sobel test statistic: 1.87).

The directional path from purpose to PWB suggested by the current mediational

model is based in strong theory (Damon, 2008; Reker & Wong, 1988), though this theory

does not necessarily tie the directional relationship specifically to one developmental

phase in life (e.g., Reker et al., 1987). At the same time, there has been empirical work

which suggests the possibility of this directional relationship flowing opposite; in

particular, as noted in Chapter Two, King, L.A. et al. (2006) found that high levels of

positive affect (which is thought to be one of the emotional components of psychological

well-being) may lead people to feel their lives are more meaningful. Though positive

affect does not map directly onto my conceptualization of PWB, and a general sense of

meaning does not imply having purpose, King, L.A. et al.’s work at least suggests the

possibility that the directional path of my hypothesized model could be reversed (or

perhaps bi-directional).

This is where the theoretical rubber hits the empirical road. It is particularly

important here to point out that the hypothesized model I have presented above is

statistically exactly equivalent to a model in which purpose mediates a directional

relationship from psychological well-being to meaningful engagement; put another way,

105

given that I have employed cross-sectional data, the statistics do not support the

directionality of the paths, only my theory does. Indeed, as MacKinnon et al. (2007)

stress in their excellent review of mediation analysis, cross-sectional data may be used to

establish preliminary insights into mediational processes, but they cannot determine the

direction of the effects (i.e., causation). To more fully justify my hypothesized directional

paths, it is insufficient to simply provide strong theory to accompany empirical evidence

from cross-sectional data that meaningful engagement leads to purpose and purpose leads

to PWB; it is also necessary to establish that PWB does not lead to purpose which in turn

does not lead to meaningful engagement. One way of demonstrating this and providing

more justification for the hypothesized directionality is to test this mediationa l model

using longitudinal data. With longitudinal data directionality can be inferred, since—at

least outside of the realm of science fiction—time does not move backwards. Study 2 was

designed specifically to address this issue.

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CHAPTER 5: STUDY 2 – LONGITUDINAL RELATIONS AMONG

MEANINGFUL ENGAGEMENT, PURPOSE, AND

PSYCHOLOGICAL WELL-BEING


In Study 1, I established that purpose, meaningful engagement, and psychological

well-being were significantly related to each other, and tested my hypothesized

mediational model in which purpose mediates the relationship between meaningful

engagement and PWB. The results of this test of mediation supported my hypothesis, but

should be viewed as preliminary as the analyses were performed using cross-sectional

data which are insufficient to establish true directionality of effects (MacKinnon et al.,

2007).

In Study 2, I set out to address this limitation by testing a fully cross- lagged

autoregressive model (MacKinnon et al., 2007) of the three latent constructs using

longitudinal data, in which a two-wave mediational model might be embedded (Cole &

Maxwell, 2003; Little, Preacher, Selig & Card, 2007). Following Cole and Maxwell’s

(2003) guidelines, for my mediational hypothesis to be fully supported using these two-

wave longitudinal panel data the following relationships must bear out: 1) meaningful

engagement at Time 1 (T1) positively predicts purpose at Time 2 (T2) but not PWB at

T2; 2) T1 purpose positively predicts T2 PWB but not T2 meaningful engagement; and 3)

T1 PWB does not predict either T2 purpose or T2 meaningful engagement. Figure 7

represents a schematic representation of this cross- lagged two-wave longitudinal model

and my Study 2 hypotheses.

107

Note. T1 = Time 1, T2 = Time 2. Solid lines represent paths between latent constructs hypothesized to be

significant. Long-dashed lines represent paths between latent constructs included in the model but

hypothesized to be non-significant. Short-dashed lines represent autocorrelations between the same

constructs at T1 and T2 (hypothesized to be significant). The shadowed solid lines connecting the T2 latent

constructs represent residual covariances.

Figure 7. Hypothesized two-wave longitudinal mediational model

Additionally, according to Little et al. (2007a) a two-wave panel approach to

testing a mediational hypothesis must make the assumptions that the ―optimal‖ time lags

between the measurements have been identified and used, and that the optimal lag

between the measurement of the predictor variable and mediator variable is the same as

the optimal lag between the mediator variable and outcome variable. As described in

Chapter 3, the time lag between the wave 1 and wave 2 YPP survey data collections was

approximately 18 months, which ought to be sufficient time for the processes under

investigation to play out (i.e., for meaningful engagement to lead to purpose, and for the

108

psychological benefits of understanding and pursuing one’s purpose to set in). It is

difficult to say whether the optimal time lag for both processes is the same, but for the

purposes of the current investigation I believe it is a reasonable assumption. 47

Again, one of my two primary hypotheses in Study 2 was that purpose mediates

the relationship between meaningful engagement and PWB; however, relative to the

results of cross-sectional mediational analysis in Study 1, I would expect the effect sizes

to be lower in the longitudinal mediational analysis since previous levels of the

endogenous (i.e., dependent) variables were controlled. In addition to further testing this

primary mediational hypothesis, Study 2 also allowed me to explore a number of

secondary hypotheses. First, the incorporation of longitudinal data allowed for tests of

temporal stability of the three constructs across 18 months of emerging adulthood, as

indicated by the autocorrelation of each construct at T1 with the same construct at T2. I

hypothesized that all three constructs would demonstrate high stability over time. Second,

these longitudinal data also provided some preliminary insights into changes in levels of

these constructs in emerging adulthood, specifically through exploring differences in

mean levels of meaningful engagement (along with each of its domain subscales),

purpose, and psychological well-being from T1 to T2.

Finally, I was additionally interested in testing my second primary hypothesis of

Study 2, as articulated in Research Question #3, that the relationship between purpose

and PWB is moderated by the presence of an orientation toward self- transcendent life

goals. This hypothesis directly addresses the beyond-the-self component of Damon et

al.’s (2003) definition of purpose. As noted in Chapter 2, the goals literature suggests that

people who have self-transcendent mid-level goals or personal strivings (Emmons, 1999)

47

Future research on these constructs should address how long these ―optimal‖ t ime lags might be.

109

are more likely to be higher in life satisfaction; however, this hypothesis have never been

addressed with regard to the content of higher- level life goals such as purposes. The

longitudinal data employed in Study 2 were well-suited to address this moderation

hypothesis, so directionality could be inferred.48

To be clear, this moderation hypothesis does not directly address the presence of

self-oriented life goals—these two orientations of life goals are thought to operate largely

independent of each other (Moran et al., 2009). Put another way, people may be high (or

low) on both orientations at the same time; many people indicate they strive toward both

self- and other-serving higher-order goals (DeVogler & Ebersole, 1980; Reker & Wong,

1988). Following from Damon’s (2008, Damon et al., 2003) theory of purpose, the

current moderation hypothesis suggests it is from the presence and pursuit of specifically

BTS-oriented life goals that PWB is more likely to spring (regardless of whether self-

oriented life goals are at the same time being pursued).

Though my theory does not directly address whether the presence of a self-

orientation of life goals also serves as a moderator of the purpose-PWB relationship, I felt

it was important to nonetheless also test whether this is the case. A limitation of testing

the BTS-orientation-as-moderator hypothesis is that it may instead be seen as a test of

whether simply having more life goals compared to fewer life goals is beneficial, which

has been found to be the case (see Reker, 2000). One way to counter this argument would

48

I felt it was important to test this moderation hypothesis using these longitudinal data instead of the

cross-sectional data in Study 1. With longitudinal data, a positive test of this hypo thesis permits the

inference that purpose is more likely to lead to PWB for those who have self-transcendent life goals

compared to those who do not, as opposed to vice-versa. Were I to have used the cross-sectional data, I

would have had to have been equally prepared to accept the inference that PWB is more likely to lead to

purpose for those who have self-transcendent life goals. Indeed, one could make a reasonable argument for

this opposite moderated directionality—as noted earlier, King, L.A. et al. (2006) demonstrated that positive

affect can lead to an enhanced sense of meaning, and meaning has been shown to be more highly associated

with self-transcendent goals than self-oriented goals (see Steger, 2009).

110

be to test whether self-orientation of life goals also moderates the purpose-PWB

relationship; if it does not, but the BTS-orientation does, we could infer from these

findings that it is the content of the life goals (and not the mere presence of more rather

than fewer life goals) that functions as a moderator. Since I do believe that it is the

content of one’s life goals and not the mere presence of more versus fewer life goals

which carries the benefit, I thus hypothesized that BTS-orientation of life goals

moderates the relationship between purpose and PWB, but self-orientation of life goals

does not.

To test this moderation hypothesis, I focused on the segment of the longitudinal

cross- lagged model shown in Figure 7 which addressed the relations among T1 Purpose,

T1 PWB, and T2 PWB, specifically the path from T1 Purpose to T2 PWB. Adapting the

model I presented in Chapter Two to the present longitudinal data, Figure 8 depicts the

primary moderation model I tested in the current study (the same model applies to the

self-orientation of life goals moderation test, replacing BTS-orientation with self-

orientation).

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Note. T1 = Time 1, T2 = Time 2. Dotted line represents autocorrelation between constructs measured at

Time 1 and Time 2.

Figure 8. Moderation model of BTS-orientation of life goals moderating the relationship

between purpose and psychological well-being

Overview of Data and Measurement Approach

For Study 2, I combined the data collected in Study 1 (from Wave 1 of the Youth

Purpose Project) with data from participants in the larger YPP who also completed the

YPP survey in Wave 2. With the incorporation of these new longitudinal data, the method

and analytical approaches of Study 2 expanded on those of Study 1. In the Method

section below, I will describe the attributes of and procedure for collecting only these

new data (since the Study 1 Method, described in Chapter 3, already covered the Wave 1

data), and will discuss attrition between the two data collections. Additionally, with the

introduction of the longitudinal data, the measurement model presented in Chapter Three

needed to be respecified to incorporate these new data; on top of that, a new statistical

process needed to be run, to establish what is known as measurement invariance.

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Establishing measurement invariance (a.k.a., factorial invariance, measurement

equivalence) is a prerequisite to comparing data collected on multiple occasions for the

same individuals, to ensure that the way in which the constructs of interest are

operationalized functions equivalently at each measurement occasion (Byrne, Shavelson,

& Muthen, 1989; Little & Slegers, 2005; Meredith, 1993). In other words, demonstrating

measurement invariance allows a researcher to determine that any changes in the way a

construct operates are due to substantive changes in the construct itself, and not artifacts

of the measurement instrument(s).

Method


In Wave 2 of the Youth Purpose Project, all participants in the college cohort

from Wave 1 were contacted via e-mail and asked to take the Wave 2 YPP survey.49 The

survey was again administered online, and a link to the survey website was included in

the invitation e-mail. Up to three e-mails were sent to the primary and secondary e-mail

addresses each participant provided when they completed the Wave 1 survey. 50 Of those

with whom contact was actually made, one-hundred eighty-nine agreed to participate

49

In the time period between Wave 1 and Wave 2, part icipants were sent postcards in the month of their

birthdays wishing them well and asking them to update their contact informat ion if it had changed since our

last correspondence. These efforts were made to decrease the likelihood of attrition. Addit ionally, all

participants were sent at least one e-mail in December 2007 (approximately midway between Wave 1 and

Wave 2) inviting them to participate in a mid-pro ject survey admin istration—this contact is germane to

Study 3 and will be described in Chapter 6. 50

In the cases of no email response, a subgroup of participants was additionally attempted to be contacted

by phone (provided they offered their phone numbers in Wave 1). This subgroup comp rised all participants

who were interviewed as well as surveyed during Wave 1, in an attempt to arrange another interview as

well (for purposes of the larger YPP not relevant to the current investigation). Presumably because extra

effort was made to contact the interviewee subsample, there were a d isproportionate number of

interviewees represented in the Wave 2 sample (18% compared to 11% at Wave 1), as discussed in the

attrition section of the current study below.

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(response rate = 44%).51 The mean age of these participants at the time of this second

data collection was 22.8 years (SD = 0.6 years). Participants were 62% female, and were

mostly Caucasian (42%), followed by Asian American (30%), Latino (19%), Pacific

Islander (10%), African-American (3%) and Native American (2%); approximately 6%

of the sample self- identified as multi-ethnic. Participants provided their consent on and

completed the same online survey as in YPP Wave 1. All participants were offered a $10

gift certificate for their participation. The same measures of the constructs employed in

Study 1 were again selected for use in Study 2, and the same approach to missing values

employed in Study 1 was again used for this longitudinal sample. 52

Attrition

To determine whether the participants who participated in both administrations of

the survey (―stayers‖) differed substantially from the participants who only participated

in the first administration (―attritors‖), I ran a series of Pearson chi-square and paired t-

tests on all of the variables of interest in the current study, as well as other demographic

variables including gender, race, self-reported grade point average, and whether

participants were interviewed in Wave 1. These attrition analyses revealed only two

statistically significant differences in the subsamples: Hispanics/Latinos comprised 19%

of the stayers, but only 10% of attritors (χ2=7.01, p<.01), and interviewees comprised

18% of stayers, but only 7% of attritors (χ2=11.78, p<.001). Though these is no apparent

51

It is impossible to know how many e -mails were actually received, for the reasons described in Chapter 3

regarding e-mail use among college students. Moreover, it is likely that a number o f participants changed e -

mail addresses and/or phone numbers, and some may have transferred institutions and were unreachable.

As such, the response rate reflects only the percentage of participants from Wave 1 who participated at

Wave 2, not necessarily the proportion of participants who received our invitation and accepted. 52

Approximately the same degree of missingness was found in the longitudinal sample (1.2%) as in the

Wave 1 sample (1.0%).

114

reason for the disproportionate representation of Hispanics/Latinos in the stayer sample,

the disproportionate number of interviewees can likely be attributed to the extra effort

made by the YPP researchers to track them down at Wave 2 for not only a follow-up

survey but also a follow-up interview. Though it is unlikely that these differences in the

stayer and attritor samples constituted significant attrition biases, I included both in an

initial run of all Study 2 analyses as covariates to make sure they did not significantly

alter the results. In none of the analyses were either being Hispanic/Latino or an

interviewee at Wave 1 significantly related to any of the other variables nor did their

inclusion in the models have any noteworthy affect on the results, so they were removed

from all final models (as reported below).53

Measures

The same measures of and measurement approach to the constructs of interest in

Study 1 were used in Study 2 (see Chapter Three). It was unnecessary to rerun the EFAs

as preliminary steps to building the domains of meaningful engagement and the parce ls

for the purpose and PWB measures as they were sufficiently established in Chapter

Three. The measures included to address the three primary constructs of interest again

included the five domain subscale scores of the meaningful engagement construct from

both Time 1 and Time 2 administrations of the YPP survey, the three parcels that

comprised the purpose construct measurement at T1 and T2, and the three parcels that

comprised the PWB construct measurement at T1 and T2. The two covariates used in

53

As will be examined in Study 3, it was also possible that being interviewed in Wave 1 may have actually

affected these participants’ levels of purpose and PWB at Wave 2. For this reason, the fact that interviewed

status did not function as a significant covariate was important beyond just alleviating concerns about

attrition bias.

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Study 1 (gender and social desirability) were not included in Study 2, since they did not

significantly affect the results in Study 1.

Additionally, to test the moderation hypothesis I incorporated a number of new

items from two measures intended to operationalize life goal orientations, collected at

Time 1: beyond-the-self-orientation of life goals and self-orientation of life goals.54 The

procedure for constructing these life goal orientation scales was the same as in Moran et

al. (2009).55 As described in Chapter One, these authors assessed the degree to which

participants felt each of seventeen general categories of purpose (e.g., ―Serve God/a

Higher Power‖ or ―Have fun,‖ derived from the sources of meaning found by DeVogler

& Ebersole, 1980; Reker & Wong, 1988) reflected their life goals, and performed an EFA

on these seventeen items. This EFA produced a two-factor solution, which they labeled

―beyond-the-self-orientation of life goals‖ (including items such as ―Make the world a

better place‖) and ―self-orientation of life goals‖ (including items such as ―Make

money‖). They then constructed two subscales by summing together the item scores for

each factor.

I selected ten of the seventeen categories of purpose used by Moran et al.

(2009)—I elected not to include the remaining seven items for both theoretical and

empirical reasons. Conceptually, some items were more appropriate (and specifically

included on the YPP survey) for younger adolescents (e.g., ―Fulfill my duties‖);

empirically, Moran et al. (2009) showed that many of the items did not load onto either

factor in their two-factor solution and it seemed unlikely they would contribute to the

54

I only included the T1 measures of life goal orientations because the content of one’s life goals in

emerging adulthood are thought to be relatively stable (Roberts et al., 2004). 55

Moran et al. (2009) pulled data from the same YPP dataset as I employed for my current analyses;

however, those authors included all Time 1 part icipants from across all ado lescent cohorts, meaning that

only about one-eighth of their participants overlapped with those in the present work.

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factor solution in the current sample (e.g., ―Serve my country,‖ ―Change the way people

think‖). A list of these ten categories of purpose items with their raw means, standard

deviations, and range of score responses can be found in Table 7. All items followed the

stem ―The purpose of my life is to‖ and were rated on a 1-7 Likert scale (1=strongly

disagree, 7=strongly agree). It is worth noting that all of these items demonstrated

significant negative skew—therefore, before running an EFA on the items I transformed

each of them using a Box-Cox power transformation (via the Stata/SE 10.0 ―bcskew0‖

command) which determined the optimal transformation for univariate non-normal data

and produced a new variable with a skewness of approximately zero.

Table 7

Descriptive Statistics for Categories of Purpose Items

Category of Purpose Mean SD Range

Do the right thing 6.31 0.95 1.00-7.00

Help others 6.19 0.96 1.00-7.00

Have fun 6.18 1.04 1.00-7.00

Be successful 6.14 1.07 2.00-7.00

Have a good career 6.01 1.27 1.00-7.00

Support my family and friends 6.01 1.27 1.00-7.00

Make the world a better place 5.88 1.22 1.00-7.00

Earn the respect of others 5.78 1.20 1.00-7.00

Make money 5.21 1.61 1.00-7.00

Serve God/a Higher Power 3.73 2.19 1.00-7.00

Note. N=189. Items are listed in descending order of mean scores. Means represent item means prior to

transformation.

I then ran an EFA on these 10 categories of purpose items using principal axis

factoring (using the Stata/SE 10.0 statistical software) and oblique (direct oblimin)

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rotation following the same steps and cut-off guidelines (eigenvalues ≥ 1, scree plot, and

theory) as in the EFAs I performed in Chapter Three. It is important to note here that my

choice of the use of an oblique rotation underlies a significant conceptual point. These

self- and BTS-orientation of life goals factors were thought a priori to be non-orthogonal,

based on both theory and the empirical results of Moran et al.’s (2009) similar analyses.

Theory suggests that it is very common for people to simultaneously be oriented toward

self-serving as well as self- transcendent life goals (e.g., one may desire to both be

successful one’s career for personal achievement as well as support one’s family; see e.g.,

Reker & Wong, 1988). This logic was prevailing in the construction of separate

measures of self- and BTS-orientations of life goals (as opposed to one continuous

bipolar measure of life goal orientation with only self-orientation and only BTS-

orientation at the extremes).56

The first run of this EFA produced a clean two-factor solution on all

aforementioned criteria (see Appendix B). However, one of the items (―Serve God/a

Higher Power‖) did not load above .25 on either factor; so another run of the EFA was

performed with this item dropped. This second run produced a clean two-factor solution,

with all nine items loading at least .27 on one or the other factor.57 Though ―Support my

friends and family‖ item loaded above .27 on both factors, the loading was clearly higher

on the second factor; for this reason along with its greater conceptual similarity to the

56

Indeed, one might surmise that, with regard to the current hypothesis that BTS-oriented life goals

moderate the relationship between purpose and PWB, one who has only BTS-oriented life goals may be

less likely to experience high psychological health since she may disproportionately attend to others’ needs

over her own (and perhaps even suffer from a ―martyr complex‖; see Yeager & Bundick, 2 009, for a

similar perspective). 57

Though ―Have fun‖ loaded slightly below the traditional loading cut -off of .30, I deemed it appropriate to

keep on this factor since theory strongly suggests the item represents a self-oriented, hedonic approach to

life (Roberts & Robins, 2000) which comports with the theme of the rest of the items on the first factor.

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other items on this factor, it was determined for analytical purposes to single- load on the

second factor. The results of this EFA are shown in Table 8.

Table 8

Final Results of Exploratory Factor Analysis of Categories of Purpose Items

Factor Structure Coefficients

Categories of Purpose Items Factor 1 Factor 2

Have a good career 0.76 0.05

Be successful 0.75 0.05

Make money 0.75 -0.16

Earn the respect of others 0.55 0.15

Have fun 0.27 0.20

Help others -0.07 0.77

Make the world a better place 0.01 0.66

Do the right thing 0.16 0.52

Support my friends and family 0.28 0.41

Eigenvalue 2.47 1.01 % variance 79.43 32.46

Note. N=189. The present structure matrix was produced via principal axis factoring with oblique (d irect


The results of this EFA suggested that the first factor, on which five items loaded,

represented a grouping of self-oriented life goals, and the second factor, on which four

items loaded, represented a grouping of BTS-oriented life goals. The primary intent of

this EFA was to determine whether the current data replicated the Moran et al. (2009)

results of a two-factor solution representing the hypothesized groupings, which was in

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fact the case.58 As such, these factors can be used to represent the constructs of self-

oriented and BTS-oriented life goals to test the moderation hypothesis.

Mediation Measurement Model

Measurement models of longitudinal panel data must incorporate all measures of

the latent constructs at each time of measurement. Thus, the measurement model for

Study 2 can be represented by a combination the measurement model from Study 1 with

a replication of that model including the same Study 2 measures. Figure 9 provides a

pictorial representation.

58

It is important to note that, were these subscales to be created using traditional methods (i.e., averag ing)

rather than the SEM approach, the summary statistics (before transformat ion) would be as fo llows: BTS-

Orientation of Life Goals – Mean = 6.21, SD = 0.75, Range = 1.00-7.00, α=.76; Self-Orientation of Life

Goals: Mean = 5.86, SD = 0.89, Range = 2.80-7.00, α=.78. The high means, especially for BTS-orientation,

suggest these scales may show a ceiling effect and have limited variance.

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Note: Dotted lines denote correlated errors. Error terms of the manifest variables are not shown.

ME-F1 = Time 1 Meaningful Engagement-Family domain subscale

ME-R1= Time 1 Meaningfu l Engagement-Relig ion/Spirituality domain subscale

ME-S1= Time 1 Meaningful Engagement-School/Career domain subscale

ME-V1= Time 1 Meaningful Engagement-Volunteering/Community domain subscale

ME-A1= Time 1 Meaningful Engagement-Aesthetic/Leisure domain subscale

ME-F2 = Time 2 Meaningful Engagement-Family domain subscale

ME-R2 = Time 2 Meaningful Engagement-Religion/Spirituality domain subscale

ME-S2 = Time 2 Meaningful Engagement-School/Career domain subscale

ME-V2 = Time 2 Meaningful Engagement-Volunteering/Community domain subscale

ME-A2 = Time 2 Meaningful Engagement-Aesthetic/Leisure domain subscale

Pur11, Pur 21, and Pur31 represent the parcel scores for Time 1 Purpose

PWB11, PW B21, and PWB31 represent the parcel scores for Time 1 Psychological Well-Being

Pur12, Pur 22, and Pur32 represent the parcel scores for Time 2 Purpose

PWB12, PW B22, and PWB32 represent the parcel scores for Time 2 Psychological Well-Being

Figure 9. Longitudinal measurement model for meaningful engagement, purpose, and

psychological well-being

This visually complex model is actually quite similar to the measurement model

presented in Chapter Three; the manifest variables each load on their respective

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constructs (within time), and all of the latent constructs covary with all other latent

constructs in the model (both within time and across time). The primary difference in this

model is that the residual variances of the manifest variables are assumed to be correlated

(as denoted by the dotted lines). According to Little et al. (2007a), this is an important

specification because, as noted in Chapter Three, the residual variance of any given

measure has a unique variance component that can be expected to reliably show up each

time it is administered to the same subject; thus the measures which constitute the

manifest variables are expected to be correlated over time. Setting this specification

therefore reduces this source of variance not attributable to the factors, thus improving

the model.

Before running the CFA on this measurement model, as noted in Chapter Three it

was necessary to 1) verify there are enough degrees of freedom to work with, and 2) set

the scales. In the current model, the number of free parameters was 70 and the number of

observations was 253, leaving 183 degrees of freedom. As before, I set the scales for each

latent construct by fixing the loading of one of its manifest variables to 1.0. With these

conditions in place, I ran the CFA using the LISREL 8.80 software package to perform

maximum likelihood estimation. The results of this CFA will not be presented pictorially,

as the model is too visually complex to be labeled with the parameter estimates. Instead,

the principle results are summarized in Table 9 (which shows the loadings of the

indicators on the factors) and Table 10 (which shows the latent factor intercorrelations).

The model fit statistics were as follows: χ2 (199, N=189) = 232.89, p=.05; RMSEA = 0.030

(0.000-0.045); CFI = 0.99; NNFI = 0.99. These results indicated a very strong fit of the model

to the data.

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Table 9

Results of Longitudinal Confirmatory Factor Analysis for Meaningful Engagement, Purpose, and Psychological Well-Being – Factor Loadings

Note. N=189. Purp = Purpose, ME = Meaningful Engagement, PW B = Psychological Well -Being. T1 =

Time 1, T2 = Time 2. All factor loadings were significant at the p<.05 level.

These factor loadings are very similar to those seen in Chapter Three with the full

Time 1 sample, with very high loadings of the purpose and PWB parcels onto their latent


Manifest Variable T1 Purp T1 ME T1 PWB T2 Purp T2 ME T2 PWB

Time 1 Measures:

Purpose Parcel 1 T1 0.89 - - - - -



ME-Family Domain T1 - 0.44 - - - -

ME-Religion Domain T1 - 0.24 - - - -

ME-School/Career Domain T1 - 0.55 - - - -

ME-Volunteering Domain T1 - 0.44 - - - -

ME-Aesthetic Domain T1 - 0.26 - - - -

PWB Parcel 1 T1 - - 0.86 - - -

PWB Parcel 2 T1 - - 0.87 - - -

PWB Parcel 3 T1 - - 0.85 - - -

Time 2 Measures:

Purpose Parcel 1 T2 - - - 0.89 - -



ME-Family Domain T2 - - - - 0.49 -

ME-Religion Domain T2 - - - - 0.25 -

ME-School/Career Domain T2 - - - - 0.62 -

ME-Volunteering Domain T2 - - - - 0.43 -

ME-Aesthetic Domain T2 - - - - 0.30 -

PWB Parcel 1 T2 - - - - - 0.86

PWB Parcel 2 T2 - - - - - 0.87

PWB Parcel 3 T2 - - - - - 0.85

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factors and lower (though still statistically significant) loadings of the meaningful

engagement domains onto the meaningful engagement latent factor. Also, the patterns of

factor loadings of the T1 manifest variables onto their respective latent factors are very

similar to the factor loadings of the T2 manifest variables onto their respec tive latent

factors. This provides evidence of configural invariance, which I will discuss in the

Measurement Invariance section later in this chapter.

Table 10 Results of Longitudinal Confirmatory Factor Analysis for Meaningful Engagement,

Purpose, and Psychological Well-Being – Factor Intercorrelations

Latent Factor 1 2 3 4 5 6

1. T1 Purpose -

2. T1 Meaningful Engagement 0.74*** -

3. T1 Psychological Well-Being 0.66*** 0.67*** -

4. T2 Purpose 0.67*** 0.53*** 0.45*** -

5. T2 Meaningful Engagement 0.53*** 0.80*** 0.49*** 0.66*** -

6. T2 Psychological Well-Being 0.54*** 0.50*** 0.73*** 0.66*** 0.64*** -

Note. N=189. T1 = Time 1, T2 = Time 2. ***p<.001.

The intercorrelations among the latent factors also provide valuable information

about our constructs. First, the intercorrelations among the T1 factors were very similar

to those shown in Study 1, which is to be expected since the Study 2 sample was a

subsample of the Study 1. Put another way, the fact that this set of correlations closely

mimics the set found in Study 1 provides further evidence that there was little if any

attrition bias. Second, the intercorrelations among the T2 factors also reflected similarly

strong effect sizes (rs=.64-.66), which suggests that there was high stability in the

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strengths of relations among purpose, meaningful engagement, and PWB over 18 months

(i.e., the constructs are about as highly related among each other in 21-year-olds as they

are among 23-year-olds). Third, the strong correlations of each construct at T1 with the

same construct at T2 (i.e., the autocorrelations) demonstrated that there was very high

stability of the constructs themselves (rs=.67-.80). These results replicated Steger and

Kashdan’s (2007) findings of strong one-year stabilities of purpose (r=.41, p<.001) and

life satisfaction (r=.40, p<.001), though the standardized coefficients were even stronger

in the current study. Fourth, each construct at T1 was moderately-to-highly correlated

with the other two constructs at T2 (rs=.45-.54, all ps<.001). These results provide

evidence of the conditions necessary for a mediational hypothesis to be tested

longitudinally, as described in Study 1 (Baron & Kenny, 1986; MacKinnon et al., 2007).

Measurement Invariance

Before proceeding to look at mean differences in the constructs over time and

testing the primary mediational hypothesis, it was necessary to demonstrate what is

known as measurement invariance, or that the constructs’ measurement properties across

the two administrations of the survey were the same (Byrne et al., 1989; Little & Slegers,

2005; Meredith, 1993; for a thorough review, see Vandenberg & Lance, 2000).59

Establishing measurement invariance with longitudinal panel data involves multiple steps

that simultaneously test the model fit of the data across two or more time points. These

steps might be thought of as a ―taxonomy of invariance‖ (Little & Slegers, 2005), or a

hierarchical sequence starting with the least strict form of invariance and working up to

59

The process of establishing measurement invariance across time points of longitudinal panel data is the

functional equivalent of establishing measurement invariance across two groups/samples (Little & Slegers,

2005).

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the strictest form. Though the labels researchers apply to the levels of this taxonomy are

often varied (Vandenberg & Lance, 2000), the primary levels are: 1) configural

invariance, 2) weak factorial invariance, 3) strong factorial invariance, and 4) strict

factorial invariance.60 Configural invariance is the most basic form, typically evident in

the measurement model; this level is met when the models at both time points have the

same number of latent constructs and manifest variables, as well as the same pattern of

estimated parameters. The demonstration of the next highest level of invariance, weak

factorial invariance (which, despite its name, is stronger than configural invariance; it is

also known as ―metric invariance‖ and ―pattern invariance‖), requires all of the

conditions of configural invariance be met plus that the relative factor loadings across

time points are equivalent. This level holds when the means of the manifest variances and

their residual variances are allowed to vary; since the factor variances are free to vary

across groups, the factor loadings are considered proportionally equivalent (Little &

Slegers, 2005). Strong factorial invariance (a.k.a., ―scalar invariance‖) suggests that the

conditions of the previous two levels are met, and that the relative manifest variable

means are equal across groups. This type of invariance is necessary to demonstrate that

participants who have the same levels of a construct (as measured by a manifest variable)

at both time points actually exhibit the same scores on those instruments which measure

that construct; in other words, that ―the constructs are defined in precisely the same

operational manner [and] can be compared meaningfully and with quantitative precision‖

(Little & Slegers, 2005, p. 618). According to these authors, strong factorial invariance

represents the required level to establish measurement equivalence. Finally, strict

60

A comparison of models might also demonstrate partial invariance—which happens when there is

equivalence across only some of the loading parameters but not others (see Byrne et al., 1989)—which was

not necessary to be explored in the current study.

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factorial invariance (a.k.a., residual invariance) means that on top of the conditions of

strong factorial invariance, the residual variances are also equal across assessments;

however, this level is generally considered too strict (since it rarely holds in practice) and

is therefore unnecessary for comparisons of measurements across time points (see Little

et al., 2007a). Thus, strict invariance was not addressed in the current investigation.

To examine the current measurement model for measurement invariance, tests of

model fit were performed which successively constrained (in a stepwise fashion) the

necessary parameters (e.g., factor loadings, indicator means) across the models

representing the two time points until the level of strong factorial invariance was

supported (or refuted). The criterion used to check whether the successive models were

sufficiently equivalent was that the decrease in the CFI model fit statistic was no greater

than 0.01 (Cheung & Rensvold, 2002). Configural invariance was evident via a visual

inspection of the CFA results pertaining to the model shown in Figure 9, which as noted

earlier showed a strong overall fit; it was also confirmed by comparing the model fit

statistics for T1 and T2 models (with the same structure) run separately, both of which

had CFIs=.99. Second, I tested for weak factorial invariance by constraining the factor

loadings of each manifest variable on its latent construct to be equal across assessments;

this resulted in no decrease in fit. Third, I tested for strong factorial invariance by

constraining the means of the indicators to be equal across time points; this resulted in a

minimal decrease in CFI (ΔCFI=0.002), and provided evidence for overall measurement

invariance. Thus, we can be confident that any covariance or mean differences observed

using my measurement approach are due to actual differences in levels of purpose,

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meaningful engagement, and PWB, and not artifacts of differential measurement

properties of the instruments over time.

Results

There were three main sets of results of interest in the present study, 1) the mean

differences in the constructs (as well as in the domains of meaningful engagement) across

the two measurement points, 2) the test of the hypothesized longitudinal mediational

model, and 3) the test of the hypothesized longitudinal moderation model.

Mean differences

I made no formal hypotheses about the mean differences in the measures over

time, as they were not a primary focus of the present investigation. Nonetheless, they still

are of potential interest given the dearth of longitudinal studies in this field. Since I

constructed the meaningful engagement scale by creating domain subscales, I was also

able to compare whether any of the individual domains of meaningful engagement

demonstrated changes from the T1 assessment to the T2 assessment. These results are

shown in Table 11.

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Table 11

Mean Differences in Meaningful Engagement Domains from Time 1 to Time 2

Domain Time 1 Mean Time 2 Mean Mean Change

Family 3.95 3.98 +0.03

Religion/Spirituality 2.90 2.93 +0.03

School/Career 4.56 4.43 -0.13†

Volunteering/Community 2.09 2.19 +0.09†

Aesthetic/Leisure 2.99 2.92 -0.07

Note. N=189. † p<.10

Overall, there was little change across the meaningful engagement domains,

though two domains showed marginally significant differences. Paired t-tests61 showed

that average meaningful engagement in the school/career domain dropped slightly

(t=1.92, p<.10), while average meaningful engagement in the volunteering/community

domain increased slightly (t=1.87, p<.10). Both results are relatively unsurprising. The

school/career domain subscale comprised items which measured school-specific activities

(i.e., studying and participating in class), and many of the participants in the current

sample may have graduated between the T1 and T2 assessments and were thus unlikely

to be in classes anymore.62 At the same time, the career-related item in this subscale was

unlikely to increase enough to offset the drop on the school-specific items, since students

commonly see their schoolwork as connected to their careers while in college.

The mean differences in the constructs, which were constructed in the SEM

framework and thus do not have measured means, can be demonstrated as latent mean

61

These analyses were also run using repeated-measures ANOVA, and the same results regarding

statistical significance for the within -subjects (time) terms were obtained. 62

The Wave 2 YPP survey did not directly ask whether participants had graduated or were still enrolled in

their institution of higher education, thus precise data to determine this were unavailab le.

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differences. SEM involves the analysis of variance-covariance matrices, wherein the

observed variables are mean-centered; thus, the latent variables means are set to zero.

This is not a problem in the current investigation, as the absolute values of the latent

construct means were not of primary interest; instead, the differences in the latent means

(i.e., differences in the T2 constructs’ latent means from the zero means of the T1 latent

constructs) provided the information of interest here, i.e., the changes in levels of these

constructs. These latent mean changes are reported in Table 12.

Table 12

Latent Mean Differences in Purpose, Meaningful Engagement, and Psychological Well-

Being from Time 1 to Time 2

Latent Construct Latent Mean Change

Purpose +0.07

Meaningful Engagement -0.08

Psychological Well-Being -0.03

Note. N=189.

These results show that there was no significant change in the latent mean levels

of any of the constructs from Time 1 to Time 2.

Testing the Longitudinal Mediational Model

As suggested by the model I presented in Figure 7, the longitudinal structural

mediational model was specified by including paths that fully cross-lagged the T1 latent

constructs with the T2 latent constructs. In other words, all of the T1 latent variables were

set as predictors of all three T2 latent variables, controlling for each other. This allowed

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me to explore all of the possible directional paths, and establish whether the two paths

which would denote mediation (T1 meaningful engagement T2 purpose, T1 purpose

T2 PWB) were significant. As noted earlier, all of the residual variances of the T1

manifest variables were allowed to correlate with their T2 counterparts. Additionally, the

factor loadings and mean estimates of each construct’s corresponding indicators were

constrained to be equal at each time point (i.e., the constraints of measurement invariance

were held in place), which allowed the possible sources of cross-wave differences to

emerge at the construct level (see Lopez & Little, 1996). The results of this cross- lagged

analysis are shown in Figure 10.

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Model Fit : χ2 (199, N=189) = 232.89, p=.05; RMSEA = 0.030 (0.000-0.045); CFI = 0.99; NNFI = 0.99

Note. ***p<.001, † p<.10, ns

p>.10. T1 = Time 1, T2 = Time 2. All values are standardized. Solid lines

represent paths between latent constructs that were expected to be significant given the mediational

hypothesis. Long-dashed lines represent paths between latent constructs included in the model but expected

to be significant given the mediational hypothesis. Short-dashed lines represent autocorrelations between

the same constructs at T1 and T2. The shadowed solid lines connecting the T2 latent constructs represent

residual covariances. Error terms and correlated errors of the manifest variables are not shown to reduce

complexity.

Figure 10. Results of longitudinal cross- lagged structural model of purpose, meaningful

engagement, and psychological well-being

As I previously discussed the autocorrelations and relations among the T1 latent

constructs earlier in this chapter (which remain highly significant and strong here), I will

focus my attention on the results regarding the cross- lagged paths which were specified

to test the temporal relations among the constructs, controlling for the other constructs.

Specifically, these paths were investigated to determine whether the model provided

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support for my mediational hypothesis; again, for this hypothesis to have been confirmed,

the paths from T1 meaningful engagement T2 purpose and T1 purpose T2 PWB

should have been significant. The results showed that, while both paths were positive,

neither was significant (standardized β=.09, p=.30 and standardized β=.12, p=.15,

respectively). Thus, these results did not support the mediational hypothesis. In other

words, in the current sample T1 meaningful engagement did not significantly lead to T2

purpose, and T1 purpose did not significantly lead to T2 PWB. In fact, none of the cross-

lagged relationships reached even the p<.10 level of marginal statistical significance.

Taken together, the results of this model suggest that only the temporal predictors of the

levels of the constructs at Time 2 are the levels of the same constructs at Time 1.

Testing the Longitudinal Moderation Hypothesis

The moderation hypothesis posited that the relationship between purpose and

PWB was moderated by the degree of orientation toward BTS life goals, specifically that

the relationship would be significantly more positive for those who have more BTS-

oriented life goals compared to those who have fewer such life goals. To provide

evidence that this moderation effect was attributable to the BTS-oriented content of life

goals and not the mere degree of life goals in general, I also separately tested whether

self-orientation of life goals moderated this relationship.63 Before running any

63

Theoretically, I could have also tested this hypothesis via a three-way interaction of T1 Purpose X BTS-

Orientation X Self-Orientation. I d id not do so for two reasons. First, statistically speaking three-way

interactions are notoriously difficu lt to interpret, prone to error, and in an SEM framework typically require

exceedingly complex interaction structures (see Dawson & Richter, 2006). Second, and more importantly, a

three-way interaction of the current hypothesis of BTS-orientation as moderator would prov ide insights into

whether the simple slopes of the T1 Purpose T2 PW B path are different across four groupings on the

BTS-Orientation and Self-Orientation dimensions: High BTS/High Self, High BTS/Low Self, Low

BTS/High Self, Low BTS/Low Self. While this might make for an interesting exploration, to address the

present issue of whether it is the content of one’s life goals purpose or the total number of them which

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moderation analyses, I mean-centered all variables (Little, Card, Bovaird, Preacher &

Crandall, 2007).

BTS-Orientation of Life Goals as Moderator. To test this hypothesis, I followed

Baron and Kenny’s (1986) general guidelines for moderation and Little et al.’s (2007b)

procedure for conducting moderation analyses using SEM. Because this hypothesis

concerned only the subsection of the above longitudinal cross- lagged model which

comprised the T1 Purpose, T1 PWB, and T2 PWB latent variables and the relations

among them (which essentially represents the relationship between T1 Purpose and T2

PWB controlling for T1 PWB), none of the other latent variables (T1 or T2 Meaningful

Engagement, or T2 Purpose) were included in these analyses (see Figure 8 for a pictorial

representation). In addition to these three latent constructs, this moderation model

included a BTS-Orientation of Life Goals latent variable as well as a latent variable

representing the interaction of the T1 Purpose and BTS-Orientation of Life Goals latent

variables. Because this was a new measurement model, it required a CFA before the

moderation analyses could be run. This CFA demonstrated strong model fit: χ2 (56, N=189) =

79.90, p=.02; RMSEA = 0.048 (0.020-0.070); CFI = 0.99; NNFI = 0.99. Additionally, all

paths from the BTS-orientation of life goals items to the BTS-orientation latent construct

represented significant factor loadings (all over .35), and this construct correlated

significantly (though relatively weakly) with T1 Purpose (standardized β=.36, p<.001),

T1 PWB (standardized β=.24, p<.01), and T2 PWB (standardized β=.25, p<.01).

contributes to PWB, we would need to compare those in the High BTS/Low Self group with those in the

Low BTS/High Self group. This, however, might reveal less about the issue of content vs. number of life

goals, and more about whether the purpose-PWB like is stronger for martyrs vs. pure hedonists; while

interesting, is beyond the scope of the present investigation.

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Following Little et al.’s (2007b) guidelines, I then built a latent variable to

represent the T1 Purpose X BTS-Orientation of Life Goals interaction composed of the

products of the indicators of T1 Purpose (i.e., three purpose parcels) and the indicators of

BTS-Orientation of Life Goals (i.e., the four BTS-orientation items); this resulted in 12

indicator variables for this interaction latent construct. I then introduced this latent

variable into the aforementioned moderation model and 1) allowed it to covary freely

with the T1 Purpose, T1 PWB, and BTS-Orientation of Life Goals constructs, as well as

2) introduced a path from the interaction term to the T2 PWB construct. According to

Little et al. (2007b), in this approach to testing interactions in an SEM framework a

significant path from the interaction term to the dependent variable represents a

significant moderation effect; in the current model, this would be translated to mean that

the moderation hypothesis (i.e., the relationship between purpose and PWB is stronger

for those with more BTS-oriented life goals than for those with fewer BTS-oriented life

goals) would be supported if the path from the interaction term to T2 PWB was

significant. The results of this moderation test are presented graphically in Figure 11.

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Note. N=189. ***p<.001, *p<.05, ns

p>.10. T1 = Time 1, T2 = Time 2. BTS = Beyond-the-Self. Dotted line

represents the autocorrelation between the psychological well-being construct measured at Time 1 and

Time 2. Model fit statistics do not apply to moderation models with interactions (Little et al., 2007b)

Figure 11. Results of moderation model of BTS-orientation of life goals moderating the

relationship between purpose and psychological well-being

These results provide support for the moderation hypothesis—the positive effect

of the interaction term (standardized β=.14, p<.05) suggests that the relationship between

T1 Purpose and T2 PWB was stronger for those high in BTS-orientation of life goals

compared to those low in BTS-orientation of life goals in the current sample. To further

demonstrate this effect, I performed a median split 64 of the sample into those high on

BTS-Orientation of Life Goals and those low in BTS-Orientation of Life Goals (median

= 6.25) and separately in each sample tested for significant relations in the paths of T1

64

Ten participants had scores at the median; I randomly sorted half o f them into the high BTS -orientation

group and the other half into the low BTS-orientation group.

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Purpose to T2 PWB (controlling for T1 PWB).65 The results of these tests showed that for

the High BTS-Orientation of Life Goals subsample, the standardized coefficient for the

T1 Purpose to T2 PWB path was .18 (p=.11) with an acceptable model fit (χ2 (21, N=95)

= 35.52, p=.02; RMSEA = 0.082 (0.023-0.130); CFI = 0.99; NNFI = 0.98), while for the

Low BTS-Orientation of Life Goals subsample, the standardized coefficient for the T1

Purpose to T2 PWB path was -.08 (p=.53) with a strong model fit (χ2 (21, N=94) = 20.42,

p=.49; RMSEA = 0.000 (0.000-0.080); CFI = 1.00; NNFI = 1.00). The results of these

subsample models should be interpreted with caution, since the sample sizes were below

what is typically considered acceptable for SEM (Kline, 2005) and the BTS-orientation

subscale had limited variance; nonetheless, they provide some evidence of a disparity in

the strength of relationships between purpose and PWB for those high and low on BTS-

orientation of life goals. For those relatively low in BTS-orientation, there was no

relationship between T1 purpose and T2 PWB; however, for those high in BTS-

orientation, there was a modest (though non-significant) positive association between T1

purpose and T2 PWB.

However, as I pointed out earlier it is possible that the moderation uncovered by

these analyses was attributable to simply having more life goals compared to having

fewer life goals, independent of goal content. Therefore, I ran the same test for

moderation as above substituting the Self-Orientation of Life Goals construct for the

BTS-Orientation of Life Goals construct.

65

Though there are other ways to demonstrate differences between high and low subsamples on a

moderating variable (e.g., trisecting the sample; looking at only those at least one standard deviation above

the mean vs. those at least one standard deviation below the mean), I was constrained by sample size (g iven

the limitations of SEM) and wanted to use all participants in this analysis.

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Self-Orientation of Life Goals as Moderator. To test whether the Self-Orientation

of Life Goals construct also functioned as a moderator of the T1 Purpose T2 PWB

path, I followed the same steps substituting the self-orientation of life goals measures for

the BTS-orientation of life goals measures. Because this also constituted a new

measurement model (with T1 Purpose, T1 and T2 PWB, and now Self-Orientation of

Life Goals as the latent constructs), I ran a new CFA. The results of this CFA also

demonstrated strong model fit: χ2 (68, N=189) = 89.52, p=.04; RMSEA = 0.041 (0.001-

0.060); CFI = 0.99; NNFI = 0.99. Additionally, all paths from the five self-orientation of

life goals items to the Self-Orientation of Life Goals latent construct represented

significant factor loadings (all over .44). Self-Orientation of Life Goals correlated

significantly (though relatively weakly) with T1 Purpose (standardized β=.27, p<.01),

though it did not correlate significantly with T1 PWB (standardized β=.09, p>.10) or T2

PWB (standardized β=.08, p>.10).

As before, I then built a latent variable to represent the T1 Purpose X Self-

Orientation of Life Goals interaction composed of the products of the indicators of T1

Purpose (i.e., three purpose parcels) and the indicators of Self-Orientation of Life Goals

(i.e., the five self-orientation of life goals items); this resulted in fifteen indicator

variables for this interaction latent construct. Following the same procedure as in the

BTS-orientation moderation analyses, I constructed and ran the model for Self-

Orientation of Life Goals as moderator—the results are shown in Figure 12.

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Note. N=189. ***p<.001, ns

p>.10. T1 = Time 1, T2 = Time 2. Dotted line represents the autocorrelation

between psychological well-being measured at Time 1 and Time 2. Model fit statistics do not apply to

moderation models with interactions.

Figure 12. Results of moderation model of self-orientation of life goals moderating the

relationship between purpose and psychological well-being

The non-significant path (standardized β=.06, p>.10) from the Self-Orientation of

Life Goals latent construct to the path between T1 Purpose and T2 PWB suggests there

was no evidence of moderation. Given that the moderation analysis for BTS-Orientation

of Life Goals was significant, but Self-Orientation of Life Goals was not, it is unlikely

that the effect of the former is primarily attributable to the presence of simply any kind of

life goals. Together, these results suggest that it is the actual content of the BTS-

orientation of purpose which promotes PWB.

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Study 2 Discussion

To summarize the three primary sets of results in Study 2, I found that: 1) there

was very little evidence of change in levels of meaningful engagement, purpose, and

psychological well-being across the approximately eighteen months of emerging

adulthood investigated in the current sample; 2) there was no clear evidence for the

longitudinal mediational hypothesis that meaningful engagement temporally predicts

purpose and purpose temporally predicts PWB; and 3) there was evidence for the

longitudinal moderation hypothesis that the strength of orientation toward BTS life goals

moderates the temporal relationship between purpose and PWB, such that the purpose

PWB relationship is on average stronger for those who have a higher BTS-orientation of

their life goals compared to those who have a (relatively) lower BTS-orientation of their

life goals. That the source of this moderation lay in the BTS content of these life goals

rather than the presence of more rather than fewer life goals was supported by the finding

that self-orientation of life goals did not function as a moderator of the purpose PWB

relationship.

Regarding these moderation findings, it is important to note that the mean for the

BTS-orientation of life goals measure for the low BTS-orientation of life goals subsample

was still quite high (M=5.61); thus, it would be incorrect to conclude from these results

that the presence of BTS-orientation fosters well-being. This observation invites the

question: Why is there a difference in psychological well-being for people who say they

on average ―moderately agree‖ to ―agree‖ with statements which indicate they are

oriented toward self- transcendent life goals and those who say they on average ―agree‖ to

―strongly agree‖ with such statements? One possibility is that the latter group is more

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likely to have a tendency to provide socially desirable answers to these kinds of

questions; however, as I noted earlier in an initial run of the data I controlled for social

desirability and it did not play a significant role (however, there is some debate over the

effectiveness of controlling for social desirability using scales such as the one I

employed; see Krosnick, 1999). Perhaps the responses of those in the high BTS-

orientation group reflect not only a stronger orientation toward BTS goals but also a

greater commitment to those kinds of goals; this high goal commitment in turn may

contribute to the strength of the purpose PWB path (Emmons, 1986; Klinger, 1977).

Though goal commitment was not assessed in the present work, its role in the

relationship between purpose and well-being may be fruitfully investigated in future

research.

There are a number of possible reasons why the effects were not stronger for the

hypothesized mediational paths. From a purely statistical standpoint, it may be the case

that the somewhat restricted variance within the constructs themselves (especially

purpose and PWB, both of which had negatively skewed distributions which exhibited

some signs of ceiling effects) made it more difficult to detect effects in the cross- lag

paths. From a methodological standpoint, it is possible that the effects were reduced

because the lag time between survey administrations was poorly determined. According

to Kenny (1975), when a researcher uses longitudinal data to explore hypothesized causal

effects but performs her assessments with too short or too long a time lag, the effects may

be underestimated. As I noted earlier, there has been very little longitudinal research on

purpose in life that might speak to optimal lags; the process through which engaging

meaningfully in the activities of one’s life leads to purpose, and the process through

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which purpose leads to greater well-being may simply happen on a shorter, or longer,

time scale than the 18-month lag investigated in the current study.

Alternatively, it may be the case that the lives of emerging adults, particularly

those in the final months of their college careers (as was the case for many in the present

sample), are so affected by transition, identity reevaluation, and goal refinement (Arnett,

2000) that any effects of meaningful engagement and purpose on well-being in these

years are muddled, inconsistent, and/or short- lived. Perhaps the present study would bear

more fruits in the subsequent years of early adulthood, a time of greater stability with

regard to larger life commitments.

There is another possible explanation for these null results which I had not

previously considered, but comports with another heretofore unexplored developmental

literature. It may be the case that emerging adults typically do not make cognitive

connections between the activities they find meaningful and the long-term goals to which

they aspire through a gradual developmental process. Instead, it may be more common

that these connections are made in sporadic episodes, perhaps set off by ―triggering

events‖66 they experience while engaged in meaningful activities which instigate deep

reflection on what is most important to them in life (see McAdams & Bowman, 2001).

For example, Gottlieb, Still, and Newby-Clark (2007) found that the majority of

emerging adults who report the development of new interests and life paths in the college

years attribute their beginnings to a specific event. The discovery of these new paths may

66

I have borrowed the phrase ―triggering event‖ from the psychopathology literature, in which it refers to

an incident or stimulus leading to some kind of significant cognitive or affect ive reaction (e.g., triggered

displaced aggression, see Pedersen, Gonzales, and Miller, 2000; or cognitive dysfunction, see Garety,

Kuipers, Fowler, Freeman & Bebbington, 2001). The connotation of my usage is not intended to be

negative—the phrase is simply meant to convey a sense of immediacy of concern and (potentially)

subsequent action.

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lead to a greater understanding of and orientation toward one’s purpose in life, which

then leads to increased PWB. If this ―triggering event‖ phenomenon is a more powerful

(and possibly more common) path from meaningful engagement to purpose (and

ultimately to PWB), then an 18-month longitudinal study may not be well-suited to

capture such as process.

Though this possibility reflects a potential limitation of the current study, it may

lend itself to an opportunity to explore at least part of this hypothesized causal chain,

namely the purpose PWB link, through a different empirical approach. If a triggering

event could be created or manipulated in a controlled setting, one in which a young

person who is in the midst of such identity reevaluation is induced to think deeply about

and reflect on his or her life goals, meaningful activities, values, and long-term plans, it

might be possible to set in motion a process which actually increases one’s purposeful

orientation, and consequently one’s more general well-being. It was this possibility that

led me to explore the ―purpose intervention‖ hypothesis I proposed in Study 3.

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CHAPTER 6: STUDY 3 – EXPLORATION OF A “PURPOSE INTERVENTION”


The primary results of Study 1 suggested that the presence of purpose in emerging

adulthood is associated with positive mental health, and may function as a pathway from

being meaningfully engaged in one’s life as an adolescent to incurring the psycholo gical

benefits of that engagement while in the transition to adulthood. The results of Study 2

did not lend broad support to this purpose-as-pathway hypothesis, though they did

suggest that when people have life goals that are strongly oriented beyond themselves,

purpose may serve to increase well-being. Taken together, with regard to the primary

outcome of interest in the present investigation (psychological well-being) in the

developmental phase of interest (emerging adulthood) these results provided inconclusive

support for a causal (indirect) relationship from meaningful engagement to PWB, and

under certain circumstances some preliminary support for the causal (direct) relationship

from purpose (especially self-transcendent purpose) to PWB.67

One mechanism precipitating this purpose PWB link was proposed in the

Discussion section of Study 2, namely that of a ―triggering event‖ which may function as

an important life turning point to spark serious consideration of and deep reflection about

one’s most important life goals and plans, which in turn may (eventually) lead to greater

well-being (McAdams & Bowman, 2001; McLean & Pratt, 2006). The idea of turning

points has been proposed as part of life course theory (Elder, 1998) and narrative identity

67

While leading a life of meaningful engagement was of central interest in the other chapters of the p resent

work, and is certainly a desirable end in itself (Peterson et al., 2005; Waterman, 1993), Studies 1 and 2

suggested the causal link, if one exists, from meaningful engagement to PW B is indirect. As such, and

because I have proposed a mechanism for the link between purpose and PWB that warrants further

exploration, I will not focus in Study 3 on meaningfu l engagement.

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(McAdams, 1993) to refer to episodes that serve as catalysts for long-term behavioral

change through a restructuring of one’s identity and longer-term goals, and the short-term

plans and daily activities in which one engages in pursuit of them. McLean and Pratt

(2006) note that turning points ―are usually events in which one understands something

new about oneself or faces decisions about different paths to take in life, the emphasis on

self-reflection [is] particularly well suited to examine in relation to identity development‖

(p. 715).Turning points can either be specific and short- lived (such as a near-death

experience) or generalized and longer-term (such as engaging in military service). Graber

and Brooks-Gunn (1996) suggested that life transitional periods, such as the transition

from adolescence into adulthood, are times of ―heightened sensitivity‖ for what they

referred to as ―transition- linked turning points‖ (p. 772).

One type of triggering event for such turning points may come in the form of

meaningful engagement in an activity through which one’s eyes are opened to

possibilities previously unseen or an occurrence which has an unusually profound

impact—for example, engaging in a service learning project may lead a college student to

take on a particular cause, or a young couple may have a child together which leads them

to devote their lives to family (Gottlieb et al., 2007). It is possible that another type of

triggering event may occur through the intentional induction of deep thought and

reflection about what is most important in one’s life, what one finds purposeful, and an

self-evaluation of whether one is moving toward (or away from) one’s purpose. This

second type provides the basis for the current exploration.

The investigations in Study 1 and Study 2 used an advanced statistical approach

(structural equation modeling) to model ―causal‖ relations among these constructs using

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descriptive, self-report survey data; however, even with the inclusion of longitudinal data

(which can help establish directionality), causal claims are dubious (Kline, 2005). In fact,

as suggested in the previous chapter, the use of longitudinal data to investigate causality

may under some circumstances be misleading (Kenny, 1975). Another avenue toward

exploring the purpose-PWB link would be to employ an experimental approach. While

conceptually appealing, practically speaking this is a somewhat daunting prospect—

indeed, in my review of the purpose literature I found no experimental studies of the

construct (though plenty of standard calls for it ―in future research on the topic‖ among

the waning comments of journal articles; for a similar perspective, see Steger, 2009). The

reason is rather obvious—purpose is a difficult construct to manipulate, especially in a

psychological laboratory setting.

In the current study, I have taken a somewhat unorthodox, yet potentially fruitful

approach toward melding the notion that a triggering event may act as a turning point in

life goal construction and pursuit, with the need for experimental research on the

purpose-PWB link. The present investigation capitalized on a design component of the

larger Youth Purpose Project (described in Chapter Two) wherein a subsample of Wave 1

participants was randomly selected to be asked to participate in a purpose interview

shortly following their completion of the YPP survey. It was my hypothesis that this

purpose interview, which was designed to induce deep reflection on one’s most

meaningful and important life goals, may have functioned as a triggering event and thus a

purpose intervention, serving to enhance one’s purpose and, consequently (if my

hypothesized purpose PWB causal path is indeed correct), one’s overall psychological

well-being. The fact that all participants in the present study were first surveyed (which

146

in the present study might be thought of as a ―pre-test‖), then a group of these survey

participants was randomly ―assigned‖ to participate in the interview (the ―intervention‖

condition), allowed me to explore whether these interviewees—relative to those in the

―comparison‖ group who were not interviewed—experienced enhanced purpose and

PWB as measured by a survey (i.e., the ―post-test‖) which I specially administered

approximately nine months later.68 These components thus allowed me to address, in a

preliminary fashion,69 my fourth and final research question: Can purpose, and

consequently well-being, be enhanced via a ―purpose intervention‖ in which one deeply

reflects upon and discusses their life goals?70

The Purpose Interview

Before describing my justification for believing the purpose interview may have

functioned as a triggering event which enhanced the interviewees’ levels of purpose and

(consequently) PWB, it is important to briefly describe the interview itself. The purpose

interview was designed as a data collection tool—the primary objective was to elicit

information from the interviewees about their most important life goals, why they have

selected these particular goals, what they are doing in pursuit of these goals, what future

68

I chose to admin ister the ―post-test‖ survey nine months later because I felt that if there was to be an

intervention effect, participants would need sufficient time for it to set in (indeed, purpose takes time to

develop; see Damon, 2008). As I d iscuss below, this intervention effect was hypothesized to stem from

increased reflection upon, orientation toward, and pursuit of one’s life goals (which may have even been

newly formed via the reflection process triggered by the interview); th is process would be unlikely to occur

over just a few weeks or even months. 69

Clearly, this does not represent an intentional, well-controlled, a priori-designed experimental study.

Since the components of an experimental design happened to be in place, I was opportunistic in working

with them to test a hypothesis. The post-hoc nature of the design notwithstanding, I do believe any

significant results of this study may serve as something of an existence proof of the potential for purpose

interventions, both in psychological research and more importantly in practice. 70

Ideally, I would have also been able to exp lore whether any effects in the present study were moderated

by BTS-orientation of life goals, as we saw in Study 2; however, no measure of this variab le was able to be

administered on the post-test, and pre-test scores on that variable would not provide any informat ion

regarding whether the interview served to reinforce o r completely change the orientation of one’s life goals.

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plans they have for these goals, what supports they have and obstacles that inhibit the

pursuit of these goals. Toward the end of each interview, all participants were asked to

describe how these goals, plans, and actions were integrated (or not integrated) with each

other, and how they were related to other aspects of their lives. The interview was semi-

structured, in that the responses provided by the interviewee may have prompted the

interviewer to probe more deeply, typically by asking a series of ―why‖ questions to

ensure that the interviewee was genuinely considering the questions and putting deep

thought into the responses. In this way, in each interview it was the interviewer’s

responsibility to induce reflection to the extent that the interviewee was willing to engage

in it; the vast majority of the interviewees were fully cooperative and genuinely

engaged.71 The back-and-forth question-and-answer dialogue typically lasted in the

college sample approximately 45 minutes, though some of the interviews lasted over an

hour (typically due to the interest and eagerness of the interviewees to share their

thoughts on their purposes). The full YPP interview protocol can be found in Appendix

C.

Purpose Interview as Purpose Intervention

Given the somewhat non-traditional, post-hoc approach of the current intervention

study, I will first elaborate on my justification for hypothesizing that engaging in this

purpose interview might constitute a triggering event for (at least some of) the

interviewees, and why this effect may have lead to longer-term psychological benefits.

71

In my experience as an interviewer on the YPP, of the approximately 20 co llege students I personally

interviewed I can only remember one who I felt was not fully engaged in the interview. Even in that

interview, I felt I induced at least some degree of reflect ion. Anecdotal reports from the other interv iewers

in the YPP have corroborated my typical experience of fu lly engaged interviewees in the college sample.

148

My rationale is rooted in three sources. First, the discussion about and reflection on one’s

most meaningful life goals that occurred in these purpose interviews approximates

Frankl’s (1988) existential psychotherapy or ―logotherapy,‖ in which a therapist attempts

to bring into awareness a client’s meanings and meaning potentials (Lantz, 1993). The

effectiveness of logotherapy in clinical populations has been documented (e.g., Coward,

1994; De La Flor, 1997; Kass, 1996), though these studies were typically not well-

controlled and sometimes produced inconclusive results (see Wong, 1998). Similarly, the

early character education work of Rath, Harmin, and Simon (1966) advocated what they

called ―values clarification‖—which may have also been induced in the interview

process—which they believed helped young people align their values with their actions

(see also Lickona, 1991).

Second, some researchers have observed that the process of engaging in

interviews for psychological research sometimes confers psychological (albeit usually

unintended) benefits on the interviewees. For example, Sanford (1982) asserted that the

research interviews he conducted had positive consequences for the students in his

studies. He further suggested that through engagement in the interview process, they

―have a chance to reflect on their lives, to take stock, to think out loud about alternatives .

. . [and] often gain some self- insight and become more open to the psychological needs of

students. We have known people who took the occasion to make important changes in

their lives‖ (Sanford, 1982, p. 897). Sanford’s description is akin to the notion of turning

points previously described (Elder, 1998). Similar interview-as-intervention effects have

also been documented in clinical populations (e.g., Keaney, Wanigaratne, & Pullin, 1995)

as well as in the organizational development literature (e.g., Boss, 1983).

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Third, small interventions (such as a one-time interview) can have substantial,

lasting psychological effects. Cohen, Garcia, Apfel, and Master (2006) demons trated that

the administration of a short, 15-minute questionnaire to seventh-graders early in a school

year aimed at inducing reflection on and increasing the salience of their values (and thus

reaffirming their self- integrity) reduced a significant portion of the racial achievement

gap in science education by the end of the academic term, five months later. Sheldon,

Kasser, Smith, and Share (2002) showed how two brief counseling sessions intended ―to

enhance participants’ sense of ownership of their listed goals‖ (p. 8) through reflection

resulted in greater progression toward those goals (though this effect was moderated by

personality integration). Koestner, Lekes, Powers, and Chicoine (2002) found that

participants who engaged in a brief self-reflection exercise in which they considered their

most personally meaningful reasons for pursuing a set of goals were more likely to feel

autonomous about these goals; this goal autonomy, in turn, was associated with goal

progress.

Importantly, each of these sets of authors highlighted the benefits of reflection

leading from their interventions to the desired ends. I believe reflection is at the heart of

the current hypothesized process, which was initially triggered by engagement in the

purpose interview, perhaps leading to further reflection and self-(re-)evaluation in the

weeks and months to follow, eventually leading to the construction of or a strong

(perhaps newfound) dedication to one’s life goals. The benefits of reflection in general

have been well-documented in the psychological literature (e.g., Hixon & Swann, 1993;

Trapnell & Campbell, 1999). For example, Hixon and Swann (1993) found that self-

reflection leads to greater self- insight and self-knowledge, which is particularly germane

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to the current study as self-knowledge constitutes one of the essential elements necessary

for the formation of identity-relevant life goals (Damon, 2008; Arnett, 2004). Indeed,

McLean and Pratt (2006) suggested that ―a key component to healthy identity

development is thinking about and reflecting on one’s experiences and options in life‖ (p.

715) and espoused the benefits of self-reflection toward the meaning-making process.

Similarly, Marcia (1966) theorized that self-reflection can function as a means of identity

exploration, which can then lead to identity commitment (a component of purpose

development; Damon, 2008). Moreover, the reflection process I believe was induced by

participating in the purpose interviews may have served to help the interviewees integrate

and assimilate their goals, values, plans, and behaviors; such integration and assimilation

has been shown to be associated with greater psychological well-being and interpersonal

functioning (Deci & Ryan, 2000; Sheldon et al., 2004)

Taken together, I felt these examples from the literature along with a strong

theoretical basis for a process mechanism provided sufficient justification for the

hypothesis that engaging in an in-depth discussion about one’s purposeful life goals as

facilitated by the YPP purpose interview may serve as an intervention which could lead

to increased reflection upon, formation of, orientation toward, and pursuit of one’s life

goals in emerging adulthood. Given the theoretical rationale for the causal link between

purpose and PWB, and the suggestive evidence for this possibility provided by Studies 1

and 2 of the present work, I felt it further justified to hypothesize that the purpose

interview would serve as not only an intervention to enhance purpose, but also to enhance

well-being.

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Method


The present study employed a subsample of the original Youth Purpose Project

subject pool (described in Chapter Three), comprising those who completed the YPP

survey in Wave 1 (hereafter referred to as the ―pre-test‖ survey) and who also

participated in the follow-up survey (hereafter referred to as the ―post-test‖ survey)

approximately nine months later. The procedures for contacting participants to take the

post-test survey were largely the same as in Study 2; up to three e-mails were sent to the

primary and secondary e-mail addresses each participant provided when they completed

the Wave 1 survey. Of the 427 Wave 1 participants, 102 agreed to participate (response

rate = 24%).72 Like the pre-test survey, the post-test was again administered online, and a

link to the survey website was included in the invitation e-mail. The mean age of these

participants at the time of this post-test survey collection was 22.0 years (SD = 0.5 years).

The ethnic breakdown of the participants was nearly the same as that in Study 1: 64%

female, and were mostly Caucasian (39%), followed by Asian American (26%),

Hispanic/Latino (16%), Pacific Islander (9%), African-American (3%), and Native

American (2%); approximately 4% of the sample self- identified as multi-ethnic.

Participants provided their consent on and completed the post-test survey online, which

had roughly the same number of items and took approximately the same amount of time

on average as the pre-test survey. All participants who took the post-test survey were

entered into a lottery in which ten $50 gift certificates to a popular online retailer were

72

For the same reasons described in Study 2, it is difficult to know how many of these participants actually

received the follow-up e-mail request; as such the response rate reflects only the percentage of participants

who responded out of those attempted to be contacted, not the percentage of those who received the request

and declined.

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distributed to randomly-selected participants. The same measures of the constructs of

interest in the current study (purpose and PWB) that were used in Study 1 were again

assessed on the post-test survey, including gender and social desirability as possible

covariates (along with a number of other measures not germane to the current study). The

same approach to missing values employed in Studies 1 and 2 were again used for the

follow-up survey data.73

As noted in Chapter Three, during Wave 1 of the YPP a subsample of 52

participants (of the 427 total participants) was randomly selected (via a random number

generator)74 to be contacted following completion of the survey to see if they would be

interested in participating in the purpose interview. All participants who were contacted

indicated on the Wave 1 survey that they would be willing to be contacted about the

interview, if selected. Of the 52 contacted, 51 agreed to participate.75 The purpose

interview was then conducted one-on-one and in-person with a trained researcher from

the Stanford Center on Adolescence between two days and two weeks after completing

the survey (interview consent forms were collected immediately preceding the beginning

of the interview, and gift certificates were handed to the interviewee immediately upon

73

Though there was slightly more missingness in the follow-up sample (1.8%) compared to the Wave 1

sample (1.0%), the overall level of missingness was still quite low and amenable to EM imputation as

described in Chapter Three. 74

To be check whether randomness was achieved, I compared the interv iewee group with the non -

interviewee group on all demographic and study variables on the pre-test, using Pearson chi-square and t-

test analyses. These tests showed no significant differences, suggesting that the process of randomly

selecting Wave 1 survey participants to be invited to be interviewed resulted in relatively equivalent groups

on demographic and study characteristics. 75

It is important to note that the mere act of asking some part icipants (and not others) to participate may

have introduced a source of bias. Though all part icipants were made aware on the original survey t hat the

selection process for interviewees would be random, it is possible that being selected and asked to

participate in the interview nonetheless induced a sense of being wanted and that one’s opinion is highly

valued (and not being asked may have left some part icipants feeling unwanted). Though there is no way of

knowing the extent to which this unintended consequence occurred, it is unlikely to have been so strong as

to have a significant effect on the results.

153

completion of the interview). As pointed out earlier, the average time of the interviews

was approximately 45 minutes.

Of the 102 participants who completed both the pre-test and post-test survey

measures, 38 were interviewed as part of the YPP Wave 1 data collection (the

―intervention‖ group) and 64 were neither invited to be interviewed nor participated in

the interview (the ―comparison‖ group). Thus, 13 participants who were interviewed at

Wave 1 and 311 of the participants who were not interviewed at Wave 1 did not take the

post-test survey. With the exception of their participation in the interview and the contact

between the interviewee and interviewer that was necessary to set it up, the YPP and its

researchers had no systematically different interactions with these two groups. Thus, any

differences between the groups on the post-test measures should be primarily attributable

to their participation/non-participation in the interview.

Attrition

I ran the same attrition analyses as in Study 2, which revealed only one

statistically significant difference between the stayers and the attritors: interviewees from

Wave 1 were more likely to participate in the post-test survey than were the non-

interviewees. Specifically, interviewees comprised 37% of stayers, but only 4% of

attritors (χ2=81.63, p<.001). There are a number of possible reasons for this. It may have

been the case that since the interviewees (compared to the non- interviewees) at Wave 1

both received a greater monetary (gift certificate) incentive for their participation and

engaged more deeply in the research process through the interview, they had more

positive feelings about their first experience with the research team and were thus more

154

willing to participate again. It is also possible that they felt more of a connection to the

project by way of the exchange of relatively personal information that took place in the

interview, and thus felt more invested in the success of the project. Whatever the reasons,

it is unlikely that this disproportionate representation of interviewees in the post-test

assessment signals a problematic source of bias.

The primary outcomes of interest, purpose and PWB, showed no differences

between stayers and attritors on the pre-test survey; more importantly, there were no

significant differences in levels of either T1 Purpose or T1 PWB between stayer

interviewees and attritor interviewees. I also ran a logistic regression with stayer status

(i.e., stayer=1, attritor=0) as the dichotomous dependent variable and pre-test values for

purpose and PWB, as well as gender and race/ethnicity, as independent variables; none

were statistically significant. Additionally, I compared the pre-test correlation matrices of

these variables in the overall pre-test sample with the stayer sample. To do this, I

compared each correlation coefficient using Fisher's z; none of these correlations were

statistically significantly different. Taking these checks together, I concluded that any

differences uncovered in the analyses between the interviewee ―intervention‖ group and

the non-interviewee ―comparison‖ group would not be due to attrition bias.

Measures

The only two constructs of interest in Study 3 were purpose and PWB. As noted

earlier, the same measurement tools related to these constructs were used on the post-test

survey as were used on the pre-test survey. However, the present analytical approach

could not employ SEM—this is because SEMs require large sample sizes (N≈200) lest

155

they suffer from a variety of issues which may render them uninterpretable (e.g., unstable

estimates, inaccurate fit statistics; see Kline, 2005); therefore, the scales needed to be

constructed via an approach different from the measurement model and CFA approach

employed in Studies 1 and 2. At the same time, I felt it was important to replicate the

measurement of these latent constructs in the previous studies as closely as possible

within the traditional framework; therefore, in the current study I again employed the

parceling technique, and built the two scales from their respective parcels. Specifically, I

constructed three parcel scores for each construct in the same manner (i.e., comprising

the same items per parcel) as described in Chapter Three, and then simply took the

average of these parcel scores to create a scale score for each construct for both the pre-

test and post-test administrations of the survey. The descriptive statistics for each of these

scales across administrations of the survey are presented in Table 13.

Table 13

Descriptive Statistics for Study 3 Purpose and Psychological Well-Being Measures

Across Interviewee/Non-Interviewee Groups

Measure Mean SD Range

Pre-test Purpose 5.16 1.08 1.85-7.00

Psychological Well-Being 4.50 1.20 1.50-6.89

Post-test

Purpose 4.97 0.94 2.85-6.53

Psychological Well-Being 4.47 1.16 2.00-6.72

Note. N=102.

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Tests of univariate normality showed that in the current sample, none of the

measures at either pre-test or post-test were significantly skewed; only PWB at the pre-

test measurement demonstrated significant kurtotis (kurtosis = 2.26, p=.04). There was

also no evidence of outliers. Since there were no serious violations of these assumptions,

these analyses did not present compelling cause for considering transformations or the

use of non-parametric analyses.

Analytic Plan

There are a variety of possible analytic approaches in randomized experimental

designs, some the most common of which are Student’s t-tests and analyses of variance

run on the outcome variable following the treatment/intervention (Bonate, 2000).

However, these approaches implicitly assume the randomization process resulted in an

experimental group and control group with equal baseline levels of the variable of

interest, which is not always the case even when the subject allocation randomization

process is properly implemented (Altman & Dore, 1990). Moreover, these t-test and

ANOVA approaches ignore within-subject variability, which if accounted for may

increase one’s ability to detect significant differences between experimental and control

groups. For these reasons among others, Bonate (2000) advocates the use of pre-test data

in analyses of experimental designs when possible.

There are three primary approaches to analyzing pre-test/post-test experimental

designs: t-test analysis of difference scores (a.k.a., change scores or gain scores), repeated

measures/split-plot analysis of variance, and analysis of covariance (controlling for pre-

test scores). There has been much debate over the advantages and disadvantages of these

157

approaches (Brogan & Kutner, 1980; Cronbach & Furby, 1970; Lord, 1963; Porter &

Raudenbush, 1987). Because my sample size was relatively low, I felt one of the more

compelling criteria for deciding which approach to employ was statistical power.

Additionally, an inspection of the pre-test scores on both outcome variables showed

modest differences. Since ANCOVA has been shown to improve the precision of

estimates in randomized designs (Porter & Raudenbush, 1987) and is recommended in

situations when baseline scores are not equivalent (Bonate, 2000), I selected this analytic

approach.

For each analysis I checked for multivariate outliers,76 violations of the

multivariate normality77 and heteroscedasticity78 assumptions, as well as the homogeneity

of regression slopes assumption.79 For the purpose ANCOVA, the heteroscedasticity

assumption was violated (χ2(1)=4.29, p<.05); so I transformed the pre-test and post-test

purpose scores using the Box-Cox transformation approach (as described in Chapter

Five) and reran the ANCOVA, which this time met the heteroscedasticity and all other

assumptions. The ANCOVA on PWB did not violate any assumptions, so these scales

were not transformed.

Additionally, for all analyses I performed a first run to check whether gender or

social desirability functioned as covariates, as well as checked for interactions between

these variables and the experimental group. In none of these analyses were the covariates

76

To check for multivariate outliers, I evaluated the Cook’s D, leverage and Studentized residuals statistics. 77

To check for vio lations of multivariate normality, I checked skew and kurtosis statistics, and ran Doornik

and Hansen’s (2008) test described in Chapter Three. 78

To check for heteroskedasticity, I ran the Breusch-Pagan/Cook-Weisberg test for heteroskedasticity using

the ―hettest‖ command in Stata/SE 10.0 statistical package. 79

To check the homogeneity of regression slopes assumption, I entered an interaction term of the

independent variable (interviewed/not interviewed) and the covariate (pre-test score) into the ANCOVA

equation—when the interaction term is significant, this indicates the assumption has been violated.

158

or interactions statistically significant, so I did not include them in the final analyses and

inferred that neither gender nor social desirability played a significant role in the results.

Study 3 Results and Discussion

The primary hypothesis of the present study was that, for emerging adults,

engaging in a purpose interview would function as an intervention to increase future

levels of purpose and, consequently, psychological well-being. Thus, there were two

primary tests to be described in these results: 1) an ANCOVA of post-test levels of

purpose by interview/non-interview (―intervention‖) group, controlling for pre-test levels

of purpose; and 2) an ANCOVA of post-test levels of PWB by interview/non- interview

group, controlling for pre-test levels of PWB. I will present each set of results followed

by a brief discussion for each, and then move to a broader discussion of the results of all

three studies in Chapter Seven.

Purpose

The results of the ANCOVA test for the purpose scale showed that there was a

significant effect of participating in the interview on levels of purpose after controll ing

for baseline purpose levels, F(2, 99)=6.21, p<.05. These results are shown in the graph in

Figure 13.

159

Figure 13. Adjusted means of purpose scores at pre-test and post-test

These results suggest that the purpose interview, on average across the

interviewed group, acted as a purpose intervention, serving as a buffer against a decline80

in purpose for those who engaged in the interview compared to those who did not.

Though these results do not speak directly to the mechanism by which discussing and

thinking deeply about one’s purpose in a one-time interview is related to purpose nine

months later, I have hypothesized that the interview functioned as a trigger for a

reflection process that helped people become more self-aware, which in turn lead them to

more deeply consider what is most important to them in life and formulate goals and

plans in accordance with those things. 80

A t-test to check whether the decline from pre-test and post-test scores for the non-interviewed group was

not statistically significant (t=1.65, p=.10).

Comparison group (N=64)

0

Intervention group (N=38)

7.0

160

It is worth noting that this intervention effect may have disproportionately

affected some interviewees; in other words, the hypothesized triggering effect may not

have fired in every interviewee. I can say from my experience as an interviewer, for

many participants the process of engaging in the interview—of being forced to consider

what is important to them, ask themselves the ―why‖ question, and take stock of what

they are doing about it—appeared to dislodge them from a complacency of not asking

these larger questions of themselves. Following the completion of the interviews, some

participants shared that they had not considered these things before, and appreciated the

opportunity to do so. Certainly this was not the case with most interviewees, but it could

be that these particular interviewees and a small number of others were so affected by the

interview that they engaged in a larger reevaluation process, leading them to over time

change their goals, thoughts, and behaviors in a large-scale systematic way—i.e., the

interview functioned as a turning point—and thus these few interviewees exhibited

especially large effects on the post-test measures. In other words, it may be that for the

average interviewee, the process of reflection conferred some relatively small effects of

perhaps being more aware of their life goals and reorienting them toward new ones, but

did not instigate a significant change in their approach to life; however, those for whom

the interview functioned as a significant turning point may have made wholesale changes

in their lives, with the purpose interview setting those wheels in motion. In this way, a

small number of participants could have potentially driven the intervention effect overall.

Unfortunately, data were not collected by the YPP interviewers on their perceived

impact of the interview on the interviewee, which may have allowed a direct test of this

hypothesis; however, a closer look at the distribution of the T1-T2 difference scores in

161

purpose revealed some potential evidence for this hypothesis. For the non-interviewee

group, the distribution curve was smooth with short, asymptotic tails; for the interviewee

group, the low end of the distribution looked like that of the non- interviewee group, but

the high-end tail looked somewhat different. The curve up to about one standard

deviation above the mean was asymptotic, and no interviewees’ scores fell between there

and about one and two-thirds above the mean; however, between one and two-thirds SDs

and two and one-quarter SDs above the mean there were four cases, and another at three

and three-quarters SDs above the mean.81 Thus, a total of five of the 38 interviewees

(13%) clustered disproportionately over one and two-thirds SDs above the mean.

It is impossible to know whether these substantial increases in purpose were

triggered by the interview, or instead that happenstance or some other unknown cause(s)

may have differentiated them from the pack of other interviewees in a way that was both

objectively not normal and was not present in the non-interviewed group. With that in

mind, given their magnitude of change I felt they warrant special attention. I found that

all five were at or below average on the pre-test purpose measure, and three of them had

scores below the scale mid-point (suggesting they felt they did not have a purpose at that

time). Thus, they may have been primed for a triggering effect given their relatively low

levels of purpose before the interview. Though there was no statistical basis for

considering them outliers, if we were to classify them as such given that they underwent

marked purpose change from pre- to post-test (possibly due to the interview) and drop

them from the ANCOVA analysis, the effect would have no longer been significant (F (2,

99)=1.85, p=.18).

81

Though this ext reme case may have exhib ited some qualit ies of an outlier, the combination of leverage,

Studentized residuals, and Cook’s D statistics did not suggest it warranted being dropped from the analysis.

162

While these results are only suggestive of a triggering effect of the interview—

namely for a select few interviewees, who were perhaps more susceptible to the effect

given their relatively low levels of purpose—the hypothesis may be worthy of future

empirical study.

Psychological Well-Being

It was hypothesized that an increase in purpose caused by engaging in the

reflection process induced by the interview may have led to a subsequent increase in

psychological well-being, given the research literature and some of the results in Studies

1 and 2 which suggest this link. Since the previous analyses supported the view that the

purpose interview functioned as an intervention, it was warranted to test whether the

purpose interview further had the effect of increasing interviewees’ PWB. The results of

the ANCOVA test for the PWB scale showed that, on average, there was in fact a

significant effect of participating in the interview on levels of PWB after controlling for

baseline PWB levels, F(2, 99)=4.17, p<.05. These results are depicted in the graph in

Figure 14.

163

Figure 14. Adjusted means of psychological well-being scores at pre-test and post-test

These results suggest that the purpose interview, which appears to have

functioned as a purpose intervention, may have not only led to relatively higher levels of

purpose, but also led to relatively higher levels of PWB. It is important to note that the

interview was not geared toward making people feel better about themselves, affirming

their accomplishments, or otherwise increasing their happiness (hedonic or

eudaimonic)—it was simply intended to make people reflect on their life goals, values,

behaviors, and the reasons behind them, which I would argue are typically mood-neutral

topics. Moreover, even if participants were likely to enjoy the discussion and more often

than not left the interview feeling greater positive affect, there is no reason to believe that

this transitory mood state would carry across a time span as long as nine months. Indeed,

as explained earlier it was intentional that the post-test survey occurred many months

0

7.0

Intervention group (N=38)

Comparison group (N=64)

164

after the interview; not only did I want to allow time for the reflection process (and any

consequences of that, such as goal formation or change in behavior) to engage, but I did

not want the potential afterglow of a potentially interesting conversation to contaminate

the interviewees ratings of PWB.82

That said, the most plausible theoretical explanation for these results was that

engaging in the interview conferred benefits regarding purpose, and that these

psychological benefits then accrued as a secondary effect of having more purpose.

However, what insight we can gain from further inspection of the data provides only

partial support for this theory. If engaging in the interview led to increased purpose in

emerging adults (at least relative to the decline in purpose over this span for the average

emerging adult) which in turn lead to (relative) increased well-being, then the effect of

the interview on PWB should be fully mediated by the effect of the interview on levels of

purpose. Following the same guidelines for mediation I applied via the SEM frameworks

in Chapters Three and Four, I ran a series of OLS regressions using the difference scores

of purpose and PWB to test this mediational model. The results of this mediation test

showed that the relationship between interview group and PWB marginally significantly

dropped from a standardized β of .19 to a standardized β of .11 when purpose was

included in the model (Sobel test = 1.70, p=.09).

This suggests that a significant portion of the effect of the interview on change in

PWB was carried through change in purpose, but not all of it. Thus, it is possible the

purpose interview also affected interviewees in ways that went beyond its benefits to

purpose, which then separately led to later PWB. Perhaps engaging in purposeful

82

Though the PWB construct as operationalized herein focused on the more stable components of well -

being, measures of well-being have been shown to be subject to the transitory influences of mood (see

Schwarz & Clore, 1983; Yardley & Rice, 1990).

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discussion and reflection helped some interviewees connect their self-worth to a set of

core values and unique features of the self, which conferred lasting psychological

benefits independent of one’s purposeful pursuits (Pyszczynski, Greenberg, &

Goldenberg, 2003). Or maybe the interview increased self-awareness and/or self-

knowledge, which helped interviewees make smarter decisions about their academic,

career, or social pursuits increasing the likelihood of future person-environment fit which

in turn benefited their overall well-being (Roberts et al., 2004). In the absence of data

which might speak to these alternative hypotheses, the mechanism(s) for non-purpose-

related PWB increases resulting from the purpose interview remains open for further

investigation.

The purpose results discussed earlier suggested the possibility that a small group

of interviewees carried the majority of the intervention effect (perhaps because of a

triggering effect of the interview). Though this group is too small to include in a

statistical analysis, it is worth exploring whether these five interviewees who showed

notable increases in purpose from the pre-test to the post-test also showed increases in

PWB. All five did in fact show increases in PWB, averaging 1.15 standard deviations

above the mean (four of whom were at or above one standard deviation above the mean,

one of whom was at 1/3 of a standard deviation above the mean). Though little in the way

of strong insight might be gained from this inspection, it at least does not detract from the

hypothesis that those who incurred purpose-related benefits may have also incurred

PWB-related benefits.

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CHAPTER 7: GENERAL DISCUSSION

The present investigation addressed multiple research questions with the

overarching goal of better understanding how purpose, meaningful engagement, and

psychological well-being are interrelated in the years of emerging adulthood. In the

current section, I will review my conceptual framework, summarize the main findings,

discuss how they work (and to a degree fail to work) together. In addition, I will address

a few limitations of the studies, and offer my insights on their broader implications for

education (especially higher education).

Summary of Conceptual Framework

Since my conceptualizations of the constructs of interest represent recent

advances in theory, it is worth restating some important arguments of the conceptual

framework described in detail in Chapter Two. First, I advanced a definition of purpose

based on the work of Damon et al. (2003), Steger (2009), and Kashdan and McKnight (in

press), which fashions the construct as a higher-order life goal which operates in one’s

life so as to organize and motivate current actions, decisions, and lower- level aspirations.

Thus, purpose is composed of both people’s understanding of their most important and

driving life goals, and an orientation toward realizing those life goals. By its nature,

purpose is central to one’s identity, relatively stable over time, generalized across the

domains of one’s life, and serves as a motivational force behind some degree of one’s

present behavior and short-term goals.

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Although psychological well-being has been conceptualized in myriad ways, my

approach integrates two primary elements which underlie the prominent theories in the

field, namely hedonic well-being and eudaimonic well-being. Hedonic well-being refers

primarily to happiness and one’s avowed satisfaction with one’s life, while eudaimonic

well-being focuses on the humanistic notions of self-actualization and the fulfillment of

one’s potential. The integration of these components of well-being was intended to more

fully represent what Aristotle referred to as ―the good life‖ (King, L. A., et al., 2006;

Ryan & Deci, 2001). My operational definitions of PWB as well as purpose were shown

in the SEM framework to be psychometrically viable and factorially invariant over time.

Of the three constructs I explored in the present investigation, meaningful

engagement has drawn the least attention in the literature. Though some formulations

similar to mine have been advanced (e.g., Scheier et al., 2006; Waterman, 1993),

surprisingly little research has examined meaningful engagement as a unitary construct,

the degree to which people find the activities in which they engage across life domains to

be meaningful on the whole. In this way, meaningful engagement goes beyond the

research which has explored what types of activities people find meaningful (e.g..,

DeVogler & Ebersole, 1980; Reker & Wong, 1988), and separately that which has

investigated the frequency with which people involved themselves in activities presumed

to be meaningful (e.g. Steger et al., 2008). Put another way, meaningful engagement was

presented as a way of understanding the extent to which people derive meaning in life

from the breadth of the things they actually do.

Based on theory derived from the extant literature of the relevant constructs (e.g.,

global sense of meaning in life, flow, the varied conceptions of positive mental health), I

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presented a process model in which purpose was hypothesized to mediate the relationship

between meaningful engagement and PWB. I suggested that in adolescence (particularly

late adolescence), young people typically have growing opportunities and increasing

independence to explore different kinds of activity involvements through which they

become more meaningfully involved in their lives. According to my conceptual model,

through this meaningful engagement in late adolescence young people develop their

identities and construct purposeful life goals, and from the establishment and pursuit of

these purposes people are more likely to experience greater PWB. The empirical

component of the present work was designed to address this conceptual model, on the

whole as well as with a focus on some of its constituent parts.

Summary of the Main Findings

The main findings of the present investigation are presented in terms of the

research questions I set out to address. I addressed the first research question in Study 1;

the second I addressed in Study 1 using cross-sectional data and again in Study 2 using

longitudinal data; the third I tested in Study 2 using longitudinal data, and the fourth I

tackled via an opportunistic experimental approach in Study 4.

Research Question #1: Are purpose and meaningful engagement associated with

psychological well-being?

In a sample of 427 undergraduate students investigated via a cross-sectional study

using survey data and structural equation modeling, I demonstrated that both meaningful

engagement and purpose were strongly related to PWB. Additionally, the results showed

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that purpose and meaningful engagement were strongly related to each other, which is

both substantively interesting and serves as evidence of concurrent validity for this new

operationalization of meaningful engagement. Though these relatively strong relations

among the constructs are not surprising, not all of the links were foregone conclusions.

The link between purpose, conceived as a higher-order life goal, and PWB may have

instead functioned more like the higher-order personal strivings Emmons (1999) found to

be predictors of reduced mental health. The current findings may have differed from

Emmons’s findings because the current conceptualization of purpose integrated a goal-

directedness and planfulness component, whereas Emmons’s higher-order personal

strivings did not; indeed, Emmons theorized that higher-order strivings are likely to be

adaptive rather than maladaptive when they are paired with lower- level plans and

concrete actionable goals. The findings that purpose, meaningful engagement, and PWB

were highly significantly related provided the necessary conditions for testing the

hypothesized mediational model.

Research Question #2: Does purpose mediate the relationship between meaningful

engagement and PWB?

This research question was addressed in two different ways, the first using cross-

sectional data to fit a structural equation model with hypothesized paths based on my

theory, and the second using longitudinal data with a full cross- lagging of paths relating

the three constructs at one time point with their reassessment at a point approximately 18

months later. The former approach was designed to uncover preliminary evidence for the

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validity of the model, and the latter approach was designed to determine the directionality

of effects.

The results regarding this research question were mixed. The cross-sectional data

provided strong support for the model, exhibiting an excellent model fit and a mediation

effect in which the relationship between meaningful engagement and PWB dropped from

being highly significant to no longer statistically significant once the mediational path

through purpose was specified. Thus, these results suggested full mediation. However,

the longitudinal cross- lagged model, in which the mediational model is embedded via the

T1 meaningful engagement to T2 purpose and T1 purpose and T2 PWB paths (see

MacKinnon et al., 2007), failed to support the mediational hypothesis.

There are many possible explanations for the failure of purpose to mediate to the

meaningful engagement-PWB link in the longitudinal study. First, it may be that the

hypothesized mediational process plays out over a shorter or longer time frame than 18

months, or is more likely to occur over an age span outside of the one I investigated (21-

23 years old). Alternatively, the process by which emerging adults connect their

meaningful engagements to larger life goals (i.e., the meaningful engagement purpose

path), which then leads to higher PWB (i.e., the purpose PWB path), may be more

episodic, occurring through turning points (Elder, 1998; McAdams, 1993). Or, it may

simply be that the mediated pathways identified in the current model are associated but

not causally related.

Research Question #3: Is the relationship between purpose and PWB moderated by the

presence of an orientation toward beyond-the-self life goals?

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As demonstrated in Study 2, the relationship between purpose and PWB was on

average stronger for emerging adults who were high on BTS-orientation of life goals

compared to those who were not high on BTS-orientation of life goals. A close inspection

of these results suggested that this BTS-orientation must be very strong in order for one

to incur the benefits of purpose on PWB; those who had a moderately-strong orientation

toward BTS life goals were on average not likely to derive these benefits. Additionally,

the findings held only for BTS-orientation, and not self- focused orientation, of life goals.

Research Question #4: Can purpose, and consequently well-being, be enhanced via an

intervention consisting of an in-depth interview in which one deeply reflects upon and

discusses one’s life goals?

Capitalizing on a design component of the larger Youth Purpose Project from

which most of the current data were taken, I explored whether engaging in a 45-minute

purpose interview designed to induce deep reflection upon one’s purposeful goals an

pursuits functioned as a purpose intervention to enhance emerging adults’ levels of

purpose and, consequently, PWB. The results of comparisons of those interviewed with

those not interviewed revealed that the interviewees, on average, did in fact have higher

levels of both purpose and PWB nine months later. However, the greatest benefits of

engaging in the purpose interview may have only been enjoyed by a relatively small

percentage of the interviewees, for whom the interview might have functioned to trigger a

turning point in their lives leading to a larger reevaluation of their life goals and

identities. Additionally, I conducted a mediational test of the pre-test/post-test differences

in purpose and PWB to see whether the relative increases in PWB for the interviewed

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group (compared to the non- interviewed group) were accounted for primary by the

increases in purpose, as I hypothesized that PWB was increased as the direct result of the

increase in purpose. This analysis provided partial support of my hypothesis—increases

in purpose were responsible for some, but not all, of the increases in PWB.

Overall, these results suggest links between meaningful engagement, purpose, and

PWB in emerging adulthood. The cross-sectional data provided evidence for relations

among the constructs, and the intervention study supported the contention that purpose

can be enhanced, which in turn may lead to greater well-being. Though the longitudinal

data did not support the mediational hypothesis in the present sample, they did provide

support for the notion that the purpose-PWB link is stronger for those who are very high

in BTS-orientation compared to those who are not very high in BTS-orientation

(independent of self-orientation of life goals).

This conception of BTS-orientation differs from previous goals literature (e.g.,

Emmons, 1986; Little, 1983) in that it is both focused on higher-order goals, and

functions as an individual difference variable intended to capture the kind of person one

is. In this way, the orientation of one’s life goals reflects not only an answer to the classic

identity question, ―Who am I?‖ but also addresses the question ―Why am I?‖ (Yeager &

Bundick, 2009). For emerging adults for whom the answer to this why question is

―because I want my life to be about something greater than myself,‖ the present data

suggest a greater likelihood of happiness and self-actualization compared to those who

are less interested in beyond-the-self life aims. Whether these young people also have

self-oriented life goals seems to be of little consequence to their overall well-being. What

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proportion of presence of BTS- and self-oriented life goals is most likely to lead to well-

being is topic ripe for future investigation.83

The present work provides the first known experimental test of whether a

―manipulation‖ of purpose can produce lasting effects related to relative increases in

psychological well-being. When framed as an intervention study, the results showing that

purpose was higher for those who engaged in the purpose interview compared to those

who did not provides evidence that the ―intervention‖ worked. The results showing

relative increases in PWB which were (partially) attributable to increases in purpose

suggest an experimental effect wherein increases in purpose produce increases in PWB.

As noted earlier, I view these results and this purpose intervention study on the whole as

preliminary, as it was clearly not designed to be an experimental study and therefore not

as well controlled as it otherwise could have been (e.g., a comparison group in which

participants talked for 45 minutes with an interviewer about non-purpose-related topics

would have helped to address any concerns that the intervention effect might be an

artifact of the perception of being wanted or merely having a discussion with a anyone,

let alone a researcher at a highly regarded university). That said, this study demonstrated

that purpose can in fact be enhanced, which is good both for the potential experimental

study of purpose as well as, more importantly, its broader implications for practice and

helping people live their lives more purposefully.

83

Perhaps Fredrickson and Losada’s (2005) notion of the ―positivity ratio,‖ which posits an optimal

balance of positive and negative affect (ranging from roughly 3:1 to 11:1, respectively), might serve as a

guide for such an exp loration.

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Implications

There are a range of potential implications of the present work, which

conceivably could stretch into a variety of domains such as clinical psychological

practice, youth development work (in community programs and families), and behavioral

medicine. Instead of presenting an exhaustive list of these potential implications, I will

restrict my focus here to those which are most relevant to education, in particular higher

education (given my focus on college students). As noted in Chapter One, increasingly

scholars of college student development and student services practitioners in colleges and

universities alike are calling for a greater emphasis on purpose and meaning in the

academy (Astin, 2004; Braskamp et al., 2006; Moran, 2001; Robinson et al., 2006).

Though there may be curricular options for introducing discussions of purpose into the

classroom (see Dalton, Eberhardt, Bracken, & Echols, 2006), perhaps a more fruitful

approach would be in co-curricular options and student affairs settings. Much of the self-

discovery and personal development that occurs in the college years occurs outside of the

classroom, often through engagement in institutionally organized opportunities and

school-sponsored organizations (Astin, 1993; Kuh, 1993; Pascarella & Terenzini, 2005).

The present analyses suggest an association between purpose and engagement in

meaningful activities; colleges and universities may foster purpose development by

offering a wide range of options for engagement in potentially meaningful activities

outside the classroom (such as school-community partnerships for social justice

initiatives and service learning programs, or collaborations with local businesses to offer

internships). Such meaningful engagement may not only foster purpose development but

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also to increase student persistence (e.g., Tinto, 1993) and academic performance (e.g.,

Astin, 1993; Pascarella & Terenzini, 2005).

Student affairs/services professionals, especially career counselors and academic

advisors, and in some cases faculty members (especially those in smaller schools or in

departments that pair students with faculty advisors/mentors) are among the

college/university representatives who are perhaps most likely to get to know students on

a more personal basis, and thus are in unique positions to build relationships with them in

ways which permits guidance of these students toward involvement in activities in which

they are likely to be meaningful engaged. Since different activities hold different levels of

meaning for different people, individual students would be best served by the school not

just by having many potentially meaningful engagement options, but by having someone

who knows and understands their interests and goals steer them toward the best fitting

ones.

Perhaps even more importantly, when student affairs professionals and faculty

members develop connections with students, they become potential vehicles for a

purpose discussion very much like that which occurred in the purpose interviews in Study

3. In many institutions of higher education, it is a requirement that students meet with an

advisor and/or career counselor at least once a year (if not once every term) to discuss

their academic and career plans—these meetings present excellent opportunities for a

purpose discussion. Not only might the benefits of engaging in such a discussion include

an increased likelihood that students become more purposeful and even more

psychologically healthy (clearly desirable ends in themselves), they might also equip the

student affairs professionals with new and vital insights about the students’ longer-term

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life goals, which in turn help them provide better guidance regarding both their curricular

and co-curricular options. In the present study, the average positive effects o f the purpose

interview last at least nine months; I would suspect that these benefits fade over time, 84

especially for the participants for whom the interview did not trigger a turning point

event. If this is the case, it would seem to me that at least one purpose discussion per year

(preferably once per term) with a faculty member or student service professional would

provided a necessary ―booster shot‖ effect to help carry this purpose intervention effect

through the end of one’s college career. To the extent that these years of emerging

adulthood constitute a critical life stage in the development of purposeful life goals

(Arnett, 2000), I would argue that the most lasting, efficacious (and low cost) change we

can make to our educational system in this country with regards to increasing people’s

individual (and perhaps the country’s collective) levels of purpose would be to integrate

the purpose discussion into the structure of the academic advising and career counseling

systems (as well as perhaps residential life, school orientations, judicial affairs, and other

venues in which student contact is high).

Limitations

All research has limitations and the current studies are no exception. For example,

in previous chapters I noted the inability to make casual inferences from the cross-

sectional analyses presented in Study 1, and the potential problems of the cross- lag

design for addressing the mediational hypothesis in Study 2. Beyond these, perhaps the

biggest limitation of the current investigation is that it only included data from college

84

Though beyond the scope of the present study, I have explored some data on the Study 3 participants

who also participated in Wave 2 of the larger YPP which suggests this is indeed the case.

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students, namely in one area of the country. It is entirely possible that the degree to which

non-college-going emerging adults experience meaningful engagement, purpose, and

PWB, and the ways in which these constructs are related, look different. For example, the

college years may afford a ―psychosocial moratorium‖ during which greater identity

exploration can take place (Schwartz, Cote, & Arnett, 2005). For young adults who do

not go to college, career options are relatively restricted, adult guidance through the

transition to adulthood is scant, and family responsibilities are often central in ways that

they are not for college students (Halparin, 1998; Settersten et al., 2000); each of these

suggest potential differences in levels of and relations among meaningful engagement

and purpose (and perhaps psychological well-being) for non-college-going emerging

adults. It is also possible that types of life goals and activities differ by region or

culture.85 It would be important for future studies on these topics to integrate non-college-

going and more geographically diverse emerging adults.

The present work focused on four major constructs, but there are other variables

which might have played important roles in the relations among these constructs. For

example, goal efficacy (McGregor & Little, 1998) and autonomy (Ryan & Deci, 2000)

might be important moderators of the relationship between purpose and PWB; openness

to experience (Schnell & Becker, 2005) might moderate the relationship between

meaningful engagement and purpose. Moreover, having a global sense of life meaning

was not strictly operationalized, though it is likely to have arisen from both meaningful

engagement and purpose (Steger, 2009) and may play an integral mediational role in the

paths from these constructs to PWB.

85

The fact that the present investigation included racially d iverse participants from across two different

kinds of institutions of higher education may have attenuated the possibility of some of these differences.

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An exclusive reliance on quantitative data to explore the relations among the

complex psychological constructs of this research ought to be supplemented by

qualitative data such as interviews or open-ended/essay-style survey responses. In

particular, qualitative data would have been very helpful toward understanding how

exactly the purpose interview impacted the participants in Study 3. Furthermore, the

present operationalizations of BTS- and self-orientations of life goals took a nomothetic

approach, which did not permit consideration of the different reasons people have for

these life goals (Carver & Baird, 1998; Deci & Ryan, 2000). An interview or set of open-

ended response survey items may have helped elucidate these reasons and thus provided

a deeper understanding of whether young adults aspired to particular life goals because

they were ultimately intended to benefit themselves or were instead aimed beyond-the-

self (Damon, 2008; Yeager & Bundick, 2009).86

Finally, I relied solely on self-report survey data, which are prone to a variety of

response style and response set biases such as acquiescence (the tendency to always

provide positive responses; see Schriesheim & Hill, 1981) and the social desirability bias

(see Paulhaus, 1991). Attempts were made to reduce these biases, such as integrating

both negatively- and positively-worded items and measuring (and checking/controlling

for the influence of) social desirability. Nonetheless, these biases can be hard to mitigate

(Krosnick, 1999) and ideally are checked against sources of data other than self- report

(such as, where possible, behavioral data and observer reports).

86

For example, one might rate oneself high on the category of purpose item ―Have a good career‖ because

she aspires to a career which will allow her to help others. The fact that these categories of purpose

statistically clustered together into self- and BTS-oriented ones suggests that, on average, people held,

respectively, self- and BTS-focused reasons for the categories which comprised the clusters; however, there

was likely individual variation in reasons unaccounted for by this approach.

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Future Directions

The results of the present investigation point to a number of possible future

directions for research in this field. First, the current conception and operationalization of

meaningful engagement represents a step forward in understanding not just how people

think about purpose, but how they live it. Purposeful living requires not only the presence

of life goals but planful action in the pursuit of them (Damon, 2008). While I have argued

and provided some empirical evidence to suggest that meaningful engagement is a

precursor to purpose in the years of emerging adulthood, it is possible that the presence of

purpose—perhaps more likely in the early adult years—contributes reciprocally to

meaningful engagement. In other words, while one route to developing purpose may

proceed through being meaningfully engaged in life, once purpose is well-developed it is

likely to lead to greater engagement in meaningful activities in pursuit of one’s purpose.

SEM designs with non-recursive models may be well-suited to detect such effects.

Specifically regarding Study 2, as noted earlier the time lag of 18 months between

assessments may have been poorly identified, and only two time-points of data were

collected. Of course, longitudinal models are essential for better understanding causal

processes, though more than two assessments are recommended to permit both a better

understanding of growth patterns as well as the integration of multi- level and mixed

linear models which can better account for both group-level change and individual- level

variations in that change (Singer & Willet, 2003). Indeed, if my hypothesis of differential

effects of turning point experiences with regard to purpose development is correct, such

designs and analytical approaches would be much better suited for their investigation.

Moreover, integrating a mixed-methods design, wherein multiple (three or more) surveys

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are administered to the same participants over time combined with one or more

interviews of at least a subset of those participants, would allow for a deeper

understanding of these processes. Thus, future research designs would benefit from

multiple survey administrations, ideally at intervals shorter than 18 months, and the

integration of interviews in one or more of these waves of data collection.

With regard to Study 3, as noted the design was post-hoc and opportunistic;

indeed, the intent of this study was to provide preliminary evidence for (i.e., a small-scale

―existence proof‖ of) the potential impact of engaging in deep discussion about and

reflection on one’s purposeful life goals. The significant results o f this exploration

provides license (or at least a learner’s permit) for further study of whether purposeful

discussion and reflection might serve to enhance young people’s purpose in life, and

perhaps lead to greater psychological well-being as well. If these results were to be

replicated in a highly controlled, well-designed study, the implications for practice—

especially, in my opinion, that of student affairs professionals and in many cases, faculty

in higher education—could be most auspicious.

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APPENDICES

Appendix A. Relevant Youth Purpose Project Survey Materials and Sample Page

from Online Survey

Purpose-related survey assessments

All items responses were on 7-point scale ranging from 1 (strongly disagree) to 7

(strongly agree); all items were randomly arranged within scales. (Note: the MLQ-P scale items were near the beginning of the survey, and the PWB-P scale items were near the end).

Instructions: ―How much do you agree or disagree with the following statements?‖

Meaning in Life Questionnaire-Presence subscale (Steger et al., 2006):

1. My life has a clear sense of purpose. 2. I have a good sense of what makes my life meaningful.

3. I have discovered a satisfying life purpose. 4. My life has no clear purpose. (R) 5. I understand my life’s meaning.

Ryff’s Purpose in Life Subscale of the Scales of Psychological Well-Being (Ryff, 1989a):

1. I don't have a good sense of what it is I'm trying to accomplish in life. (R) 2. I am an active person in carrying out the plans I set for myself.

3. I used to set goals for myself, but that now seems like a waste of time. (R) 4. Some people wander aimlessly through life, but I am not one of them.

5. I enjoy making plans for the future and working to make them a reality. 6. My daily activities often seem trivial and unimportant to me. (R) 7. I sometimes feel as if I've done all there is to do in life. (R)

8. I tend to focus on the present, because the future nearly always brings me problems. (R)

9. I live life one day at a time and don't really think about the future. (R) Note. (R) = Reverse-scored

Categories of Purpose (for measurement of BTS- and Self-Orientation of Life Goals)

All items responses were on 7-point scale ranging from 1 (strongly disagree) to 7

(strongly agree); all items were randomly arranged.


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―Note: In the following section, "purpose" refers to the MOST IMPORTANT overall goal or goals for your life.‖

Stem: ―The purpose of my life is to . . .‖

1. Help others. 2. Serve God/a Higher Power.

3. Make the world a better place. 4. Change the way people think.

5. Create something new. 6. Make things more beautiful. 7. Fulfill my obligations.

8. Do the right thing. 9. Live life to the fullest.

10. Make money. 11. Discover new things about the world. 12. Earn the respect of others.

13. Support my family and friends. 14. Serve my country.

15. Have fun. 16. Be successful. 17. Have a good career.

Meaningful engagement-related survey assessments (arranged by domain)

Two questions per activity (activities were randomly ordered across this section), each

with the following instructions: 1) ―How often are you engaged in this activity?‖

- Response options: 9 point scale ranging from 1 (never) to 9 (every day) 2) ―How meaningful is it to you?‖

- Response options: 5 point scale ranging from 1 (not at all) to 5

(extremely)

Family: 1. Family celebrations (birthdays, holidays, etc.)

2. Spending time with sibling(s)

3. Family vacations

4. Talking with relatives

5. Visiting with relatives

6. Family dinners

Volunteering/Community: 7. Volunteering with children

8. Volunteering with those in need

9. Volunteering with the elderly

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10. Working on your neighborhood

11. Working on a political cause/campaign

12. Working on an environmental cause

13. Military service or ROTC/JROTC

Religion/Spirituality: 14. Praying

15. Meditating 16. Attending religious or spiritual service

17. Reading or Studying religious or spiritual texts 18. Listening to religious or spiritual music 19. Attending a religious or spiritual camp

20. Thinking about faith or spiritual beliefs

School/Career: 21. Actively participating in class

22. Studying/doing homework for class

23. Participating in an academic club 24. Student leadership

25. Meeting with a tutor/mentor 26. Job training 27. Working for pay

Aesthetic/Leisure/Extracurricular:

28. Sports

29. Dancing

30. Music

31. Drama/Theater/Stage

32. Creating art

33. Writing

34. Involvement with computers/technology

(Note: The items in bold represent those retained for the present work.)

Psychological well-being-related survey assessments

All items responses were on 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree); all items were randomly arranged across scales.


Life Satisfaction (Diener et al., 1985) 1. In most ways my life is close to my ideal.

2. The conditions of my life are excellent. 3. I am satisfied with my life.

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4. So far I have gotten the important things I want in life. 5. If I could live my life over, I would change almost nothing.

Fulfillment of Potential (Shultz et al., 2006)

1. Most people think that I am living up to my potential. 2. On the whole, I think that I am living up to the best of my abilities. 3. I have a lot of potential that I don’t normally use. (R)

Note. (R) = Reverse-scored

Covariates

Social Desirability (Short version of the Marlowe-Crowne Social Desirability Scale; Reynolds, 1982)

Instructions: ―Listed below are a number of statements concerning personal attitudes and traits. Read each item and decide whether the statement is TRUE or FALSE for you.‖

1. I never hesitate to go out of my way to help someone in trouble. T or F 2. I have never intensely disliked anyone. T or F 3. There have been times when I was quite jealous of the good fortune of others. T or F

4. I would never think of letting someone else be punished for my wrong doings. T or F 5. I sometimes feel resentful when I don’t get my way. T or F

6. There have been times when I felt like rebelling against people in authority even though I knew they were right. T or F 7. I am always courteous, even to people who are disagreeable. T or F

8. When I don’t know something I don’t at all mind admitting it. T or F 9. I can remember ―playing sick‖ to get out of something. T or F

10. I am sometimes irritated by people who ask favors of me. T or F

Demographic information

What is your gender?

1. Male

2. Female

How would you identify your race/ethnicity? Check all that apply.

□ African American

□ Asian/Asian American □ Hispanic/Latino

□ Native American/Alaskan Native □ Pacific Islander

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□ White (Non-Hispanic) □ Other (please specify)

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Sample page of Youth Purpose Survey in online formatting (includes some items not

used in the present work:

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Appendix B. Results of Exploratory Factor Analyses from Chapter Three


Table 14

First Run of Exploratory Factor Analysis of Meaningful Engagement Items with Oblique Rotation – Five Factor Solution


Meaningful Engagement --------------------------------------------------------

Activity, by domain Factor1 Factor2 Factor3 Factor4 Factor5

Family: Family celebrations 0.67 0.03 0.12 -0.09 0.20

Talking with relatives 0.78 0.03 0.03 0.09 -0.08

Family vacations 0.42 0.08 0.20 -0.02 0.17

Visiting with relatives 0.85 -0.02 -0.07 0.03 -0.04

Religion/Spirituality: Praying 0.05 0.87 -0.01 -0.04 0.00

Attending religious services -0.01 0.85 0.00 0.00 -0.03

Thinking about faith -0.06 0.77 0.00 0.09 0.04

School/Career: Participating in class 0.00 -0.06 0.57 0.12 0.04

Studying -0.01 0.06 0.64 0.05 -0.12

Working for pay 0.17 -0.07 0.44 -0.09 0.05

Volunteering/Community: Environmental cause 0.01 -0.12 0.08 0.44 0.20

Neighborhood 0.03 0.03 0.05 0.66 -0.01

Helping those in need 0.13 0.11 0.01 0.56 0.03

Political cause -0.04 -0.04 0.07 0.43 0.04

Aesthetic/Leisure: Creating art -0.13 -0.02 -0.07 0.11 0.56

Dancing 0.20 0.07 0.03 0.02 0.52

Drama/Theatre/Stage 0.01 -0.01 -0.10 0.06 0.51

Music 0.02 0.07 0.23 -0.18 0.36

Sports 0.07 -0.07 0.21 0.06 0.10

Writing -0.13 0.11 0.24 0.12 0.26

Eigenvalue 3.83 1.75 1.23 0.87 0.65 % variance 50.15 22.91 16.19 11.52 8.47



188

Table 15

First Run of Exploratory Factor Analysis of Meaningful Engagement Items with Oblique Rotation – Three Factor Solution



Activity, by domain Factor1 Factor2 Factor3

Family: Family celebrations 0.76 0.08 0.00

Talking with relatives 0.77 -0.01 0.04

Family vacations 0.52 0.17 0.05

Visiting with relatives 0.81 -0.10 -0.01

Religion/Spirituality: Praying 0.06 -0.04 0.87

Attending religious services 0.00 -0.02 0.85

Thinking about faith -0.06 0.09 0.77

School/Career: Participating in class 0.21 0.42 -0.08

Studying 0.22 0.31 0.03

Working for pay 0.36 0.18 -0.11

Volunteering/Community: Environmental cause 0.00 0.52 -0.10

Neighborhood -0.05 0.55 0.10

Helping those in need 0.06 0.46 0.17

Political cause -0.07 0.41 0.00

Aesthetic/Leisure: Creating art -0.10 0.41 -0.05

Dancing 0.27 0.34 0.03

Drama/Theatre/Stage 0.02 0.31 -0.04

Music 0.18 0.20 0.01

Sports 0.15 0.21 -0.08

Writing -0.02 0.40 0.09

Eigenvalue 3.83 1.75 1.23 % variance 50.15 22.91 16.19



189

01

23

45

Eig

enva

lues

0 5 10 15 20Number

Scree plot of eigenvalues after factor

Figure 15. First run of exploratory factor analysis of meaningful engagement items –

scree plot

190

Purpose:

Table 16

Exploratory Factor Analysis of Purpose-Related Items with Oblique Rotation – One

Factor Solution

Factor structure

coefficients

Purpose Items, by scale

Factor1

Meaning in Life Questionnaire - Presence subscale

My life has no clear purpose. (R) 0.74

I have discovered a satisfying life purpose. 0.74

I have a good sense of what makes my life meaningful. 0.70

My life has a clear sense of purpose. 0.76

I understand my life's meaning. 0.65

Ryff’s Purpose in Life Subscale I live life one day at a time and don't really think about the

future. (R) 0.36

I tend to focus on the present, because the future nearly always brings me problems. (R) 0.49

My daily activities often seem trivial and unimportant to me. (R) 0.64

I don't have a good sense of what it is I'm trying to accomplish in life. (R) 0.69

I used to set goals for myself, but that now seems like a

waste of time. (R) 0.68

I enjoy making plans for the future and working to make

them a reality. 0.69

I am an active person in carrying out the plans I set for myself. 0.73

Some people wander aimlessly through life, but I am not one of them. 0.68

I sometimes feel as if I've done all there is to do in life. (R) 0.30

Eigenvalue 5.86 % variance 85.51


oblimin) rotation. Loadings greater than .30 appear in boldface. (R) denotes items that were reverse-

scored.

191

Table 17

Exploratory Factor Analysis of Purpose-Related Items with Oblique Rotation – Two

Factor Solution

Factor structure

coefficients

Purpose Items, by scale

Factor1 Factor2

Meaning in Life Questionnaire - Presence subscale

My life has no clear purpose. (R) 0.54 0.26

I have discovered a satisfying life purpose. 0.83 -0.02

I have a good sense of what makes my life meaningful. 0.77 0.01

My life has a clear sense of purpose. 0.81 0.01

I understand my life's meaning. 0.82 -0.11

Ryff’s Purpose in Life Subscale I live life one day at a time and don't really think about the

future. (R) -0.12 0.59

I tend to focus on the present, because the future nearly always brings me problems. (R) -0.12 0.74

My daily activities often seem trivial and unimportant to me. (R) 0.25 0.49

I don't have a good sense of what it is I'm trying to

accomplish in life. (R) 0.41 0.39

I used to set goals for myself, but that now seems like a

waste of time. (R) 0.16 0.65

I enjoy making plans for the future and working to make them a reality. 0.35 0.46

I am an active person in carrying out the plans I set for myself. 0.39 0.45

Some people wander aimlessly through life, but I am not one of them. 0.49 0.29

I sometimes feel as if I've done all there is to do in life. (R) -0.15 0.51

Eigenvalue 5.86 1.07 % variance 85.51 15.61


oblimin) rotation. Loadings greater than .30 appear in boldface. (R) denotes items that were reverse-scored.

192

02

46

Eig

enva

lues

0 5 10 15Number


Figure 16. First run of exploratory factor analysis of purpose items – scree plot

193

Psychological Well-Being:

Table 18

Exploratory Factor Analysis of Psychological-Well-Being-Related Items with Oblique

Rotation – One Factor Solution

Factor structure

coefficients

Psychological Well-Being Items, by scale Factor1

Satisfaction with Life Scale

I am satisfied with my life. 0.76

If I could live my life over, I would change almost nothing. 0.59

The conditions of my life are excellent. 0.65

In most ways my life is close to exactly how I want it to be. 0.76

So far I have gotten the important things I want in life. 0.69

Fulfillment of Potential subscale

Most people think that I am living up to my potential. 0.65

On the whole, I think that I am living up to the best of my abilities. 0.74

I have a lot of potential that I don't normally use. (R) 0.45

Eigenvalue 3.59

% variance 1.03


oblimin) rotation. Loadings greater than .30 appear in boldface. (R) denotes items that were reverse-scored.

194

01

23

4

Eig

enva

lues

0 2 4 6 8Number


Figure 17. First run of exploratory factor analysis of psychological well-being items –

scree plot

195

Appendix C. Youth Purpose Project Interview protocol

Note: The interview was semi-structured – the following represents the questions provided to the interviewers to guide the discussion, though not all questions were asked

in every interview. The Stages were generally followed sequentially, though the Probes were brought in and out at the discretion of the interviewer. Checks were performed at various points to ensure the interviewee was deeply thinking about and reflecting on the

questions.

STAGES 1 & 2:

Stage 1: Describe self and most important things/goals in life

What matters to you? What are some of the things that you care about?

What is really important to you? How do you spend your time? What do you do well?

What kind of person are you?

Stage 2: Beyond-the-self interests What would you want to be different in the world? Describe your perfect place/world?

Are you doing anything in progressing towards this? How could you work towards making some of these changes?

Check 1: You’ve mentioned several things that matter to you, which are most important?

Why is X more important than Y or Z?

Is there anything else more important?

PROBES:

Centrality of life goals/most important things in life:

How does X influence your life? You have also mentioned Y and Z, how do they relate to X?

Rationale for life goals/most important things in life:

How does your participation in X affect others?

How does X relate to the ―ideal world‖ you described earlier? How do you feel when you are engaging in X?

Stability of life goals/most important things in life:

How long have you cared about X?

What do you do that shows X is important to you? Do you see your participation in X ending at some point?

Challenges and maintenance of life goals/most important things in life:

196

Why are you excited about this? How do you keep yourself excited? What were the obstacles?

How did you overcome them? What will you need to do to maintain your involvement in this?

Inspiration and formative experiences regarding life goals/most important things in life:

How did X become important to you?

When did it become important to you? Why do you think you care about/got involved in this particular cause rather than

a different one? Future:

Picture yourself at say, 40 years of age. What will you be doing? Who’ll be in your life? What will be important to you? What are your plans in the immediate future,

say the next few years? Check 2: Is there anything else we have missed that you think is important?

STAGE 3 AND FINAL CHECK:

Stage 3: Integrated life goal narrative

You have mentioned, _, _, _, how do these fit together?

Why is IP/EP more important than X, Y and Z? What part does IP play in your life?

How does IP influence your goals? How do you deal with conflicts within IP? How do your friends and/or family feel about IP?

Do you see IP as being part of your life forever? Explain.

Final Check: Throughout the interview you have talked about how __ is the reason you ___, ___, and __. Is this correct?

Do you have a purpose? What does purpose (the concept) mean to you?

Do you think you’ll have it for the rest of your life?/ Do you think you will have one?

Is there anything else I have missed that you think is important in your life?

197

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