predictors of positive development in emerging adulthood

EMPIRICAL RESEARCH

Predictors of Positive Development in Emerging Adulthood

Meredith O’Connor • Ann Sanson • Mary T. Hawkins •

Primrose Letcher • John W. Toumbourou • Diana Smart •

Suzanne Vassallo • Craig A. Olsson

Received: 3 February 2010 / Accepted: 22 September 2010 / Published online: 9 October 2010

� Springer Science+Business Media, LLC 2010

Abstract This article responds to recent calls for a focus

on successful development in young people and examina-

tion of its developmental precursors, in order to identify

potentially modifiable targets for interventions. The current

study examined child and adolescent precursors of positive

functioning in emerging adulthood, including individual

characteristics, relationship factors, and connections to the

community, using a multidimensional positive develop-

ment measure at 19–20 years. The sample consisted of 511

males and 647 females who were participants in the

Australian Temperament Project, a population based lon-

gitudinal study that has followed young people’s psycho-

social adjustment from infancy to early adulthood. Higher

levels of positive development in emerging adulthood were

associated with stronger family and peer relationships,

better adjustment to the school setting, higher family

socioeconomic status, and better emotional control. Some

significant gender differences were observed, with emo-

tional control, family relationships, and community orien-

tation all being stronger predictors of males’ than of

females’ positive development. The findings provide pos-

sible targets for child and adolescent interventions to pro-

mote positive development in early adulthood.

Keywords Positive development � Emerging adulthood �Longitudinal analysis � Community engagement � Gender

Introduction

Understanding the characteristics of healthy psychosocial

growth is a fundamental task for the science of human

development, and is a particularly salient issue during the

transition to adulthood. Emerging adulthood extends from

the late teens to the early twenties and is defined by exten-

sive variability and role exploration, without clear norma-

tive expectations (Arnett 2000). It has been described as a

window of opportunity for positive change in life course

trajectories (Masten et al. 2006), as well as a period in which

the incidence of risk behaviors and mental health problems

is relatively high (Kessler and Walters 1998; National

Health and Medical Research Council 2001). The capacity

of young people to successfully take up adult roles as they

transition to adulthood is of great social and economic

M. O’Connor (&) � A. Sanson � M. T. Hawkins � P. Letcher

Department of Paediatrics, The University of Melbourne,

Royal Children’s Hospital, Flemington Road, Parkville,

VIC 3052, Australia

e-mail: [email protected]

A. Sanson


M. T. Hawkins


P. Letcher


J. W. Toumbourou

School of Psychology, Deakin University, Deakin, Australia


D. Smart � S. Vassallo

Australian Institute of Family Studies, Melbourne, Australia


S. Vassallo


C. A. Olsson

Psychological Sciences & Department of Paediatrics, Murdoch

Children’s Research Institute, Royal Children’s Hospital

and the University of Melbourne, Flemington Rd,

Parkville 3052, VIC, Australia


123

J Youth Adolescence (2011) 40:860–874

DOI 10.1007/s10964-010-9593-7

importance to individuals, communities, and societies. Yet, as

noted by Masten et al. (2004), ‘‘intervening to foster the condi-

tions for positive change during the transition to adulthood

requires a more solid base of knowledge than presently

exists’’ (Masten et al. 2004, p. 1092). It is therefore

important to identify the antecedent factors that promote

successful development during this transition period, and

which may provide targets for intervention (Tanner 2006).

While positive development is acknowledged to be a

multidimensional construct, few studies have examined

factors that contribute to overall positive development

during this period. Furthermore, most studies have exam-

ined the contributions of only a small number of predictors.

Gender differences in predictors of positive development

have been largely unexamined, and although most studies

have been longitudinal, they are typically short-term with

few waves of data. There is an important need for further

research on the developmental antecedents of positive

development during the transition to adulthood; in partic-

ular, research based in established longitudinal studies of

social and emotional development spanning childhood

through young adulthood.

Defining Positive Development

Positive development has been conceptualized in many

different ways by different theorists and researchers, but

the term generally refers to functional aspects of human

behavior (such as ‘‘assets’’ or ‘‘strengths’’) and successful

developmental outcomes (such as being in employment).

There are few examples of multidimensional models of

positive development in the literature. Our group has

recently proposed a multidimensional model using data

collected from a population based longitudinal study

(Hawkins et al. 2009), which incorporates perspectives

from developmental psychopathology (Cicchetti 1984;

Masten and Curtis 2000), life course and life span psy-

chology (Lerner 2006), and social capital theory (Whitley

and McKenzie 2005). The model identifies five important

domains of positive psychosocial development at

19–20 years (see the ‘‘Methods’’ section for further details

on model development). The first domain, social compe-

tence, underpins successful social relationships, helping

individuals to meet everyday functional demands, partici-

pate socially, and be responsible for themselves and others

(Gresham et al. 2001). The second domain, life satisfac-

tion, reflects a sense of contentment and feelings of con-

gruency between wants or needs and accomplishments or

resources (Keyes and Waterman 2003), and can be taken as

a measure of quality of life (Huebner 2004; Park 2004).

The third and fourth domains, trust and tolerance of others

and trust in authorities and institutions, are important

aspects of social capital that reflect an individual’s

attachment to the community and society and their capacity

to work harmoniously with people from different back-

grounds and cultures (Putnam 1995). The fifth domain,

civic engagement, refers to the willingness of an individual

to take up the role of being a citizen, and is central to

political socialization and a successful democratic society

(Flanagan and Sherrod 1998; Winter 2000). Our multidi-

mensional model provides a robust measure of positive

development during emerging adulthood.

Investigating Predictors of Positive Development

Across Domains

Most studies investigating antecedents of positive devel-

opment have examined only a limited number of predictors.

Yet, the multidimensional nature of positive development

most likely reflects multiple influences from multiple

domains across the life course. Hence, thorough assessment

of the developmental origin of positive development in early

adulthood will require systematic multivariate modeling of

child and adolescent exposures across multiple domains

(individual, relational, and community). In what follows we

review what is known of the predictors of positive young

adult development.

Individual Characteristics

Personal and academic characteristics, such as gender,

temperament, emotional self-control and academic ability,

are likely to make significant contributions to positive

adaptation over the transition to adulthood. For example,

looking at the role of temperament and personality, longi-

tudinal data from the Australian Temperament Project

suggests that dimensions of temperament, including reac-

tivity and persistence, are reliable predictors of social

competence at 19–20 years (Smart and Sanson 2003).

Similarly, Shiner (2000) drew on data from Project Com-

petence—a US sample of 205 children recruited from two

elementary schools in lower to middle-class neighbor-

hoods—and found that personality traits at 8–12 years,

including academic conscientiousness, agreeableness, and

surgent engagement (higher extraversion, expressiveness,

and attention), were predictive of adaptive functioning

(defined as academic achievement, rule-abiding behavior,

and peer social competence) both concurrently and 10 years

later. Hence, dimensions of temperament and personality

are likely to be relevant to later positive adaptation.

The ability to self-regulate behaviors and emotions has

also been found to predict positive development. Drawing

on data from a small US longitudinal sample (N = 185),

Shoda et al. (1990) found that preschoolers’ (mean age

4 years) ability to delay gratification was related to their

Scholastic Aptitude Test scores, taken to be an indicator of

J Youth Adolescence (2011) 40:860–874 861

123

positive development, 14 years later (mean age 18 years).

This finding suggests that the ability to regulate emotional

states in childhood continues to have implications for

positive adaptation well beyond this period.

Masten et al. (1995), utilizing data from Project Com-

petence, identified academic achievement during childhood

(ages 8–12 years) as a powerful precursor of a construct

labeled ‘‘competence’’ in early adulthood, which included

competence in the academic, social, behavioral, romantic,

and employment domains. Furthermore, using the same

sample, Obradovic and Masten (2007) found that adoles-

cent academic competence and social competence were

unique predictors of citizenship in emerging adulthood.

Citizenship was operationalized as involvement in activi-

ties such as voting in elections, upholding the responsi-

bilities of citizenship, and contributing to society at large.

Academic competence therefore appears to be related to

both multidimensional positive development and core

dimensions of this construct.

Gender may also influence emergent positive develop-

mental pathways in young people. For example, Phelps

et al. (2007) examined trajectories of positive youth

development over grades 5–7 and found that girls were

more likely to be in the high or medium trajectories. There

is also some evidence that gender may moderate the rela-

tionship between positive development and assets or

resources that contribute to positive development (Benson

et al. 2006). For example, Huebner and Betts (2002) have

shown that, for female youth, attachment with parents and

peers was more strongly associated with positive devel-

opmental outcomes (low delinquency and higher academic

achievement) whereas, for males, involvement bonds

(operationalised as time spent in school and non-school

based activities) were more protective. This is consistent

with a large body of research suggesting that the quality of

close relationships are particularly relevant to females’

psychological wellbeing (Cyranowski et al. 2000).

Relational Factors

Social relationships, particularly those with parents and

peers, are also likely to play an influential role in predicting

positive development through young adulthood. Studies

drawing on life course theories emphasize the importance of

interactions between the individual and their social context,

highlighting the relevance of strong relationships with others

for successful development. These studies look particularly

at well-being as an indicator of positive development and

reveal young peoples’ relationships with their parents and

peers as important contributors to their later well-being.

Schulenberg et al.’s (2004) examination of trajectories of

well-being (as measured by self-esteem, self-efficacy, and

social support) using data from a large US cohort-sequential

longitudinal study found that peer relationships play an

important role in the maintenance of well-being, with peer

involvement predicting a ‘‘steady-high’’ versus ‘‘decreas-

ing’’ trajectory of well-being. Using path analysis with

longitudinal data from a large national study of Dutch young

people, van Wel et al. (2002) found that the parental bond

was important for well-being in emerging adulthood and was

at least as important as peer and romantic connections. Thus,

there is also evidence that relational factors during adoles-

cence may promote successful adaptation in young people.

Community-Level Factors

The importance of the broader social context, including

perceptions of connectedness with the community, con-

tinue to be emphasized in life span, developmental psy-

chopathology and social capital frameworks. For example,

Scales et al. (2006) have shown that, after controlling for

initial academic levels, students who were higher in con-

nection to the community (a factor that included partici-

pation in youth programs, religious involvement, service to

others, creative activities, and reading for pleasure) in early

adolescence were more likely to have positive academic

outcomes 3 years later. Scales et al. (2006) also found that

adherence to the social norms of responsibility (including

school bonding) was predictive of better academic out-

comes. Using well-being as an outcome, McGraw et al.

(2008) drew on an Australian school based sample and

found that school connectedness was moderately associated

with well-being during the final year of high school (mean

age 17 years), and continued to predict well-being 1 year

after leaving high school. Community-level factors have

received relatively little empirical attention, yet these

studies suggest that this domain may also play a key role in

facilitating positive adaptation.

Distal and Proximal Influences on Positive

Development

In examining antecedents of positive development, both

earlier and later experiences in these domains need to be

considered. Early experiences neither ensure future positive

functioning or inoculate against problems in later adaptation

(Curtis and Cicchetti 2003). While early experiences may be

critical, their influences on later functioning are likely to be

mediated by later experiences (Schulenberg et al. 2004).

Hence, the influence of early antecedents of adaptation may

be mediated by later measures of these factors. This is

particularly clear when positive adaptation is viewed as a

function of strong person–context interactions (Larson

2000), that can shift over time according to changes in the

individual, the context, and their interaction (Cicchetti and

Rogosch 2002; Sameroff 2000; Schulenberg et al. 2004).

862 J Youth Adolescence (2011) 40:860–874

123

The Current Study

The purpose of the current study is to conduct a compre-

hensive examination of the developmental origins of a

multidimensional model of positive development in

emerging adulthood (Hawkins et al. 2009). Specifically, we

aim to estimate the unique contribution of individual,

social or relational, and community level factors to the

prediction of positive development in controlled multi-

variate models. Data are drawn from the Australian Tem-

perament Project (ATP), a large scale longitudinal

community based study, which has followed the develop-

ment of a cohort of Australian children from infancy to

young adulthood. The ATP has collected a wealth of data

across 14 waves from multiple informants, including par-

ents, teachers, and the children themselves.

Based on a broad lifespan/ecological developmental

approach and findings of previous research, we sought to

test three general hypotheses. Firstly, we hypothesized

that positive development in emerging adulthood would

be best explained by multiple influences from individual,

interpersonal, and community domains. Secondly, we

hypothesized that the influence of child and early ado-

lescent predictors on positive development would be lar-

gely mediated by later measures of these factors. Finally,

we expected that the relative importance of predictors of

positive development would differ for males and females.

Expected relationships are illustrated in a hypothesized

model shown in Fig. 1. In developing this model, we were

mindful that a number of predictors were likely to be

interrelated. For example, self control and the temperament

dimension of persistence both have a relatively strong

influence on school adjustment (Bramlett et al. 2000;

Miech et al. 2001). The temperament dimension of nega-

tive reactivity is also related to emotional control (Fox and

Calkins 2003), and to the quality of attachments with

others (Cassidy 1994). Similarly, relationships with peers

and parents also share a relatively strong association with

one another (Raja et al. 1992). Hence, the hypothesized

model incorporates both relationships of antecedents to

positive development, and interrelations between the

antecedent constructs.

Positivedevelopment

SES

Self control

Schooladjustment

Relationship withpeers

Relationship withparents

Late childhood Early adolescence Mid/late adolescence Emerging adulthood

Emotional control

Schooladjustment


Relationship withParents

Emotional control

Schooladjustment



Communityorientation

Reactivity

Persistence PersistencePersistence

Reactivity Reactivity

Extraversion

Agreeableness

Conscientiousness

Fig. 1 Hypothesized model presenting relationships between child, early adolescent, and mid/late adolescent factors and positive development

in emerging adulthood


123

Method

Participants and Procedure

Participants were young people enrolled in the ATP, a

longitudinal study following the psychosocial development

of a community sample from infancy to adulthood. A

representative sample of 2,443 infants was recruited

through selected Maternal and Child Health Centres across

both urban and rural areas in the State of Victoria,

Australia, during a specified 2 week period in 1983.

Fourteen waves of data have been collected over the past

27 years from parents (with an average response rate of

83%), primary school teachers (average response rate

73%), maternal and child health nurses (in infancy only;

response rate 100%), and from the age of 11 onwards, the

young people themselves (with an average response rate of

83%). The study has used a mail survey methodology in

which questionnaires were mailed to participants [for fur-

ther information, see Prior et al. (2000)].

Participants in the current study were the 1,158 partici-

pants (647 females and 511 males) who completed the

thirteenth survey at age 19–20 years, and thus had data on

positive development in emerging adulthood. This sample

represented 77% of the young people who were still enrolled

in the ATP at 19–20 years (Wave 13). Questionnaire

booklets were mailed to participants, together with reply-

paid, addressed envelopes in which to return them. One

round of postal reminders was undertaken and was followed

by a second mail-out of questionnaires to non-respondents.

Finally, a round of telephone reminders was undertaken.

Approximately two-thirds of the cohort were still enrol-

led in the study at Wave 13. Attrition has been slightly

higher in families experiencing socio-economic disadvan-

tage or among families with parents not born in Australia.

However, there are no substantial differences between the

retained and non-retained sub-groups on child characteris-

tics assessed in infancy, such as temperament style or behav-

ior problems (Ruschena et al. 2005). Hence, although

attrition has led to a slight under-representation of young

people from families living in socio-economically disadvan-

taged circumstances, the study continues to include children

with a wide range of capacities and characteristics, and

attrition is unlikely to be a significant influence on the results.

Materials

The measure used to assess positive development in

emerging adulthood was developed by Hawkins et al.

(2009) using AMOS 7.0 SEM confirmatory factor analysis

(SPSS Inc., Chicago, IL; Arbuckle and Wothke 2006). This

construct incorporates the five domains of social compe-

tence, life satisfaction, trust and tolerance of others, trust in

authorities and organizations and civic action and

engagement, all assessed by self report at 19–20 years.

Rates of missing data were very low (average of 0.7%), and

were estimated using the Expectation–Maximization (EM)

algorithm. All first order constructs loaded meaningfully on

the second order latent positive development construct

(from .30 to .68), and all second-order loadings were

gender invariant. The second order construct accounted for

nearly half of the variance in the five-first order constructs

and the model provided a good fit for the data

(RMSEA = .05, CFI = .94). Using model-based imputa-

tion in AMOS on the final positive development model, a

latent factor score was computed and used as the positive

development outcome measure. The components of this

score are described below.

Social Competence

Social competence was assessed with three subscales

derived from Smart and Sanson (2003), including empathy

(5 items, a = .78, e.g., ‘‘I show my concern for others when

they experience difficulties’’), responsibility (4 items,

a = .72, e.g., ‘‘I can be relied on to do things right’’), and

self control (3 items, a = .60, e.g., ‘‘I can assert my opinion

without arguing or fighting’’). Items were rated on a five-

point Likert scale ranging from ‘‘never’’ to ‘‘always’’.

Life Satisfaction

Life satisfaction was measured by two subscales adapted

from the National Survey of Families and Households

(Sweet and Bumpass 2002), including (1) satisfaction with

achievement and life directions (3 items, a = .83, e.g.,

‘‘How satisfied are you with what you are accomplish-

ing?’’), and (2) satisfaction with personal and social life (5

items, a = .75, e.g., ‘‘How satisfied are you with your

social life?’’). Items were rated on a four point scale from

‘‘very satisfied’’ to ‘‘not at all satisfied’’.

Trust and Tolerance of Others

Trust and tolerance of others was measured using 3 single

items derived from Stone and Hughes (2002) relating to

trust in people in the neighborhood, trust in Australians,

and tolerance of different ethnic groups (e.g., ‘‘Most people

in your neighborhood can be trusted’’). Ratings were made

on a five point scale from ‘‘disagree completely’’ to ‘‘agree

completely’’ (a = .55).

Trust in Authorities and Organizations

Trust in authorities and organizations was measured by

three scales, two derived from Flanagan and Longmire


123

(1995) measuring trust in authorities, and one from Stone

and Hughes (2002) measuring trust in organizations. The

scales comprised (a) confidence in police (5 items, a = .83,

e.g., ‘‘How much confidence do you have in the police to

treat everyone fairly’’ rated on a 4 point scale from ‘‘a great

deal’’ to ‘‘none at all’’), (b) confidence in the courts (5

items, a = .87, e.g., ‘‘How much confidence do you have

in the ability of the courts to impose fair sentences’’ rated

on the same scale), and (c) trust in organizations (8 items,

a = .83), reflecting confidence that various organizations/

institutions can be relied on to act in a fair or reasonable

manner (e.g., government, the media), using a four point

scale from ‘‘not at all confident’’ to ‘‘very confident’’.

Civic action and Engagement

Civic action and engagement was measured by three scales

derived from Stone (2001) and Stone and Hughes (2002)

tapping (a) participation in community activities over the

past year (10 items, a = .58, e.g., ‘‘In the past 12 months

how often have you attended a public meeting’’ rated from

‘‘not at all’’ to ‘‘5 times or more’’), (b) participation in

groups (9 items, a = .65, e.g., ‘‘sporting, recreation, or

hobby groups’’ rated as ‘‘yes’’ or ‘‘no’’ to participation in

the last year), and (c) donations to groups (9 items,

a = .60, e.g., ‘‘church groups’’ rated as ‘‘yes’’ or ‘‘no’’ to

donations made in the past year).

Predictor Variables

A wealth of data on potential predictors of positive

development was available across the 13 waves of data

collected from infancy to 19–20 years. To simplify anal-

yses and reduce multicollinearity, the data were divided

into three age categories: childhood (4–8 months to

11–12 years, waves 1–8), early adolescence (12–13 and

13–14 years, waves 9 and 10), and mid/late adolescence

(15–16 and 17–18 years, waves 11 and 12). Where iden-

tical measures were available at adjacent time points within

an age category, previous literature was used to guide the

selection of the most salient time point. If the literature did

not provide a means of differentiating between time points,

variable selection was based on the psychometric proper-

ties of the measures, including their internal reliability

(Osborne and Waters 2002). Where data was available

from multiple informants, parent and teacher reports were

used in preference to self-reports to reduce the effects of

shared method variance (Podsakoff et al. 2003). Measures

are summarized in Table 1. Further details are available

from the authors upon request or can be viewed at

www.aifs.gov.au/atp. See Prior et al. (2000) for an

overview.

Data Analysis

The path analysis in the current study was performed using

AMOS 16.0.1 software (Arbuckle 2007). Model estima-

tions were based on a covariance matrix and used maxi-

mum likelihood estimates, which work well with large

sample sizes (Tabachnick and Fidell 2001). The model

was identified and the estimation process converged. All

parameter estimates were within the range of permissible

values. The model diagram shows standardized parameter

estimates, b, which represent the effect of a given predictor

variable on the dependant variable after accounting for the

remaining relationships in the model.

A number of fit statistics were examined (Schermelleh-

Engel et al. 2003). We used chi-square as an indicator of fit

problems. Significant values suggest that the sample cor-

relation matrix and the model correlated matrix are sig-

nificantly different. However, chi-square is known to be

affected by large sample size (Schermelleh-Engel et al.

2003). We also examined the Adjusted Goodness of Fit

Index (AGFI), which is the GFI adjusted for the degrees of

freedom. AGFI values greater than .80 are taken to reflect

acceptable fit (Hair et al. 1998; Schermelleh-Engel et al.

2003). The Root Mean Square Error of Approximation

(RMSEA) is based on the non-centrality parameter, and

takes particular account of the error of approximation

(Zubrick and Lawrence 2006), with values below .08 taken

to indicate a good fit in this study (Brown and Cudeck

1993; Hair et al. 1998). The normed fit index (NFI) com-

pares the v2 of the model to the v2 value of the indepen-

dence model, with values greater than .95 indicating a good

fit (Tabachnick and Fidell 2001). The chi-square difference

test is a popular means of comparing model fit that was

used to examine whether changes in chi-square were sta-

tistically significant (Byrne 2001). These fit measures were

used in the current study to provide a comprehensive

evaluation of the goodness of fit of the model, and to

examine differences in model fit across male and female

participants.

Results

Descriptive statistics and inter-correlations between vari-

ables are included in Table 2. SES was included in the

model to control for its effects, as socioeconomic effects

have been identified in previous literature as potential

confounds (e.g., Obradovic and Masten 2007). Missing

data in the predictor variables averaged 8.8% and was

handled using the Expectation–Maximization (EM) Algo-

rithm method (Raghunathan 2004).


123

http://www.aifs.gov.au/atp

Table 1 Summary of child, early adolescent and mid/late adolescent predictor measures used in the analyses

Domain Instrument Source Age

(years)

Internal

reliability

Example item Scale

Late childhood

Temperament Negative Reactivity and Persistence

subscales of the School Age

Temperament Inventory

(McClowry 1995)

P 11–12 a = .91;

a = .91

‘Gets upset when he/she can’t find

something’ ‘returns to

responsibilities (homework,

chores) after friends phone or

visit’

6-point scale from

‘almost never’ to

‘almost always’

Self control Self control subscale of the

Gresham and Elliot (1990) Social

Skills Rating System

P 11–12 a = .83 ‘Speaks in an appropriate tone of

voice at home’

3-point scale from

‘rarely or never’ to

‘very often’

Relationship

with

parents

Parents scale of the Self

Description Questionnaire

(Marsh et al. 1984)

C 11–12 a = .82 ‘My parents and I have fun

together’

5-point scale from

‘true’ to ‘false’

Relationship

with peers

Peer scale from the Self

Description Questionnaire

(Marsh et al. 1984)

C 11–12 a = .87 ‘I have lots of friends’ As above

School

adjustment

Academic Competence subscale of

the Gresham and Elliot’s (1990)

Social Skills Rating System

T 11–12 a = .94 Asks teachers to rate the student on

9 academic skills (e.g., ‘Reading

skills’)

5-point scale from

‘lowest 10%’ to

‘highest 10%’

SES Composite of both parents

occupational level and

educational levels (Broom et al.

1974; Brotherton et al. 1979).

P 11–12 a = .72 ‘Upper professional’ to

‘unemployed or

student’; ‘post

graduate degree’ to

‘primary schooling’

Early adolescence

Temperament As in late childhood P 12–13 a = .92;

a = .92

5-point Likert scale

from ‘almost never’

to ‘almost always’

Emotional

control

ATP devised scale C 13–14 a = .60 ‘Know how to relax when I feel

tense’


from strongly

disagree to strongly

agree

Relationship

with

parents

Family attachment scale adapted

from the Inventory of Parent and

Peer Attachment (Armsden and

Greenberg 1987)

T 13–14 a = .85 ‘My parents respect my feelings’ 5-point scale from

always/almost always

true to almost never/

never

Relationship

with peers

ATP devised peer involvement

scale

P 13–14 a = .83 ‘Plays/talks with peers for long

periods’


from rarely/never to

very often

School

adjustment

ATP devised scale P 13–14 a = 76 ‘Understanding the work in class’ 4-point Likert scale

from no problem to

big problem

Mid/late adolescence

Temperament As in early adolescence P 15–16 a = .84;

a = .79

Personality Extraversion, Agreeableness, and

Conscientiousness subscales of

the Five Factor Personality

Questionnaire (Lanthier and

Bates 1995)

P 15–16 a = .70;

a = .78;

a = .80

‘How talkative do you think he/she

is?’; ‘How bossy do you think he/

she is?’; ‘How organised do you

think he/she is?’

5-point scale from

‘hardly at all’ to

‘extremely’

Emotional

control

As in early adolescence C 15–16 a = .70

Relationship

with

parents

Mean of the Warmth, Trust, and

Alienation subscales of the

Inventory of Parent and Peer

Attachment (Armsden and

Greenberg 1987)

C 17–18 a = .83 ‘Senses when I’m upset about

something’; ‘Considers my point

of view when we discuss things’;

‘Doesn’t understand me’

4-point scale ranging

from ‘always/almost

always’ to ‘never/

almost never’


123

Full Model

The hypothesized model (see Fig. 1) was estimated and

found to be a poor fit for the data (v2 = 3,297.61,

p = \.001; RMSEA = .11; AGFI = .74; NFI = .66).

Hence, we performed model-trimming, removing non-sig-

nificant paths one at a time starting from the smallest

loading path. Following this procedure, the personality

dimensions of extraversion, agreeableness, and conscien-

tiousness at mid/late adolescence, and reactivity and per-

sistence during both adolescent time points, as well as a

number of the paths and covariances hypothesized between

predictors, were removed from the model. This improved

model fit (Dv(63) = 702.4, p \ .001), although fit was still

judged to be relatively poor (v2 = 2,000.83, p = \.001;

RMSEA = .09; AGFI = .80; NFI = .75). Next, we per-

formed model building. The Modification Indices indicated

a number of changes to improve model fit that were judged

to be conceptually coherent. Specifically, three paths were

added (see discussion for conceptual explanation), includ-

ing paths: (1) from relationships with parents to emotional

control within the early adolescent and mid/late adolescent

periods, (2) from relationships with parents to relationships

with peers during mid/late adolescence, and (3) from per-

sistence in childhood to school adjustment in mid/late

adolescence. Following these modifications, the model was

substantially improved (Dv(70) = 1,366.13, p \ .001), and

was judged a good fit for the data (v2 = 634.71,

p = \.001; RMSEA = .07; AGFI = .91; NFI = .87). The

final model is presented in Fig. 2, and reveals that greater

positive development in emerging adulthood was related to

higher family SES, self control, school adjustment, rela-

tionships with parents and peers, and lower reactivity. The

model also demonstrates that the effects of persistence

were totally mediated by its relationship to school

adjustment. Overall, these factors accounted for 26% of the

variance in positive development.

Gender Invariance

We next examined the gender invariance of the final model

using Byrne’s (2001) method to test whether the relation-

ships between the predictors and positive development

were similar for young men and women. It should be noted

that the chi-square difference test is known to be overly

sensitive to small differences when sample size is large

(Schumacker and Lomax 2004).

Initially, the model was examined separately for each

group simultaneously providing the baseline chi-square

value of 765 (df = 216), against which subsequent tests for

invariance were compared. Model comparison showed

that the constraints did not hold for the two genders

(Dv(23) = 67, p \ .001). The quality of relationships with

parents over childhood and early adolescence showed

greater continuity for females (b = .44 for females,

b = .39 for males; Dv(1) = 8, p = .005). In contrast, the

relationships between a number of antecedents and positive

development were stronger for males than for females,

with relationships with parents (b = .21 males, b = .12

females; Dv(1) = 7, p = .01), emotional control (b = .29

males, b = .19 females; Dv(1) = 8, p = .01), and com-

munity orientation (b = .30 males, b = .20 females;

Dv(1) = 8, p = .01) at mid/late adolescence all showing

stronger associations with positive development for males.

Discussion

Healthy adaptation over the transition to adulthood has a

range of implications for young peoples’ life course

Table 1 continued

Domain Instrument Source Age

(years)

Internal

reliability

Example item Scale

Relationship

with peers

Mean of the Communication, Trust,

and Alienation subscales of the

Inventory of Parent and Peer

Attachment (Armsden and

Greenberg 1987)

C 17–18 a = .62 ‘My friends accept me as I am’;

‘My friends sense when I’m upset

about something’; ‘My friends

don’t understand what I’m going

through these days’

4-point scale from

‘always/almost

always’ to ‘never/

almost never’

School

adjustment

ATP devised scale P 15–16 a = .84 ‘Managing school rules and

routines’

3-point scale from ‘no

problem’ to ‘a big

problem’

Community

orientation

ATP devised scale C 17–18 a = .61 Asked participants to rate the

likelihood of their involvement in

different activities in the future,

such as ‘Work to improve

conditions in your local

community’

4-point scale ranging

from ‘not likely’ to

‘extremely likely’

P parent informant, C child/teenager informant, T teacher informant


123

Table 2 Intercorrelations between variables and descriptive statistics

1 2 3 4 5 6 7 8 9 10 11 12

1. Positive development 1 .16** .25** -.22** .27** .17** .21** .11** .26** -.23** .20** .26**

Childhood predictors

2. SES .16** 1 .09** -.11** .16** .15** -.01 .01 .08** -.14** .05 .09**

3. Persistence .25** .09** 1 -.42** .41** .42** .24** .21** .73** -.36** .19** .44**

4. Reactivity -.22** -.11** -.42** 1 -.73** -.15** -.24** -.18** -.33** .72** -.19** -.25**

5. Self control .27** .16** .41** -.73** 1 .20** .28** .20** .36** -.58** .24** .28**

6. School adjustment .17** .15** .42** -.15** .20** 1 .06 .08** .35** -.13** .10** .35**

7. Relationship with peers .21** -.01 .24** -.24** .28** .06 1 .42** .19** -.22** .24** .20**

8. Relationship with parents .11** .01 .21** -.18** .20** .08** .42** 1 .17** -.15** .21** .13**

Early adolescent predictors

9. Persistence .26** .08** .76** -.33** .36** .35** .19** .17** 1 -.43** .19** .54**

10. Reactivity -.23** -.14** -.36** .72** -.58** -.13** -.22** -.15** -.43** 1 -.21** -.28**

11. Emotional control .20** .05 .19** -.19** .24** .10** .24** .21** .19** -.21** 1 .18**

12. School adjustment .26** .09** .44** -.25** .28** .35** .20** .13** .54** -.28** .18** 1

13. Relationship with peers .15** .09** .20** -.16** .20** .09** .16** .31** .17** -.16** .12** .09**

14. Relationship with parents .23** .04 .24** -.20** .27** .11** .43** .26** .25** -.23** .43** .25**

Mid/late adolescent predictors

15. Extraversion .12** -.06* .16** -.08** .08** .07* .10** .21** .05 -.01 .06* .00

16. Agreeableness .20** .05 .26** -.44** .43** .08* .18** .09** .29** -.46** .09** .28**

17. Conscientiousness .23** .02 .50** -.23** .25** .21** .14** .12** .55** -.23** .14** .38**

18. Persistence .20** .10** .45** -.22** .27** .27** .09** .12** .44** -.21** .11** .36**

19. Reactivity -.20** -.09** -.22** .53** -.44** -.08** -.08** -.04 -.23** .57** -.11** -.20**

20. Emotional control .32** .03 .13** -.20** .21** .07* .18** .18** .11** -.24** .34** .13**

21. School adjustment .29** .06* .44** -.24** .28** .36** .18** .13** .48** -.25** .18** .65**

22. Relationship with peers .28** -.05 .20** -.14** .14** .05 .25** .23** .12** -.10** .20** .09**

23. Relationship with parents .29** -.02 .18** -.09** .15** .04 .29** .23** .14** -.11** .19** .09**

24. Community orientation .31** .07* .07* -.04 .06* .09** -.02 -.03 .09** -.03 .06* .06*

Mean .00 4.08 2.37 2.95 12.71 35.33 1.55 1.87 2.31 2.90 3.48 1.42

Standard deviation .75 1.40 .73 .70 3.53 6.30 .50 .65 .70 .69 .58 .48

Min -3.22 1.00 1.00 1.00 1.00 10 1.00 1.00 1.00 1.08 1.40 -4.00

Max 2.65 8.00 5.00 4.92 20.00 45.00 4.25 4.88 4.91 5.00 5.00 1.00

13 14 15 16 17 18 19 20 21 22 23 24

1. Positive development .15** .23** .12** .20** .23** .20** -.20** .32** .29** .28** .29** .31**

Childhood predictors

2. SES .09** .04 -.06* .05 .02 .10** -.09** .03 .06* -.05 -.02 .07*

3. Persistence .20** .24** .16** .26** .50** .45** -.22** .13** .44** .20** .18** .07*

4. Reactivity -.16** -.20** -.08** -.44** -.23** -.22** .53** -.20** -.24** -.14** -.09** -.04

5. Self control .20** .27** .08** .43** .25** .27** -.44** .21** .28** .14** .15** .06*

6. School adjustment .09** .11** .07* .08* .21** .27** -.08** .07* .36** .05 .04 .09**

7. Relationship with peers .16** .43** .10** .18** .14** .09** -.08** .18** .18** .25** .29** -.02

8. Relationship with parents .31** .26** .21** .09** .12** .12** -.04 .18** .13** .23** .23** -.03

Early adolescent predictors

9. Persistence .17** .25** .05 .29** .55** .44** -.23** .11** .48** .12** .14** .09**

10. Reactivity -.16** -.23** -.01 -.46** -.23** -.21** .57** -.24** -.25** -.10** -.11** -.03

11. Emotional control .12** .43** .06* .09** .14** .11** -.11** .34** .18** .20** .19** .06*

12. School adjustment .09** .25** .00 .28** .38** .36** -.20** .13** .65** .09** .09** .06*

13. Relationship with peers 1 .14** .33** .04 .08** .08** -.09** .11** .07* .18** .11** .01

14. Relationship with parents .14** 1 .07* .29** .23** .18** -.17** .33** .23** .22** .46** .04


123

trajectories. Identifying the factors that facilitate healthy

adaptation during this time remains an important challenge

for developmental science. Due in large part to a paucity

of multidimensional models of positive development in

emerging adulthood, few studies has examined this issue.

Hence, the current study examined the longitudinal ante-

cedents of a multidimensional index of positive deve-

lopment in emerging adulthood, including individual,

relational, and community level predictors from childhood

to late adolescence. Higher positive development in

emerging adulthood was predicted by higher socioeco-

nomic status, having better control of emotions, better

adjustment to the school setting, having stronger relation-

ships with parents and peers, and greater community

engagement. There were some indications of gender dif-

ferences in the strength of predictors of positive

.26

Positivedevelopment

SES

Self control

Schooladjustment



Late childhood Early adolescence Mid/late adolescence Emerging adulthood

Emotional control

Schooladjustment


Relationship withParents

Emotional control

Schooladjustment



Communityorientation

Reactivity

Persistence

.41

.15

.19 .56

.30.36

.42

.13

.19

.19

.16

.27

.14.30

.19

.13

.46

.40.19

.12

.35

-.73

-.38

.29

-.08

-.10

-.10

.31

Fig. 2 Final model of the relationships between child, early adolescent, and mid/late adolescent factors and positive development in emerging

adulthood

Table 2 continued

13 14 15 16 17 18 19 20 21 22 23 24

Mid/late adolescent predictors

15. Extraversion .33** .07* 1 -.07* .12** .06* .03 .14** .07* .18** .19** .03

16. Agreeableness .04 .29** -.07* 1 .40** .28** -.53** .23** .33** .10** .19** -.01

17. Conscientiousness .08** .23** .12** .40** 1 .52** -.24** .10** .49** .12** .21** .06*

18. Persistence .08** .18** .06* .28** .52** 1 -.35** .15** .41** .11** .19** .08**

19. Reactivity -.09** -.17** .03 -.53** -.24** -.35** 1 -.24** -.23** -.03 -.15** -.02

20. Emotional control .11** .33** .14** .23** .097** .15** -.24** 1 .17** .24** .25** .03

21. School adjustment .07* .23** .07* .33** .492** .41** -.23** .17** 1 .09** .14** .04

22. Relationship with peers .18** .22** .18** .10** .116** .11** -.03 .24** .09** 1 .31** .06*

23. Relationship with parents .11** .46** .19** .19** .212** .19** -.15** .25** .14** .31** 1 .11**

24. Community orientation .01 .04 .03 -.01 .059* .08** -.02 .03 .04 .06* .11** 1

Mean 1.56 3.96 3.33 3.46 3.45 2.41 2.85 3.76 1.43 3.05 3.09 1.91

Standard deviation .36 .69 .61 .65 .67 .63 .849 .61 .48 .37 .48 .59

Min .13 1.13 1.17 1.00 1.17 1.00 1.00 1.60 .00 1.67 1.13 1.00

Max 2.00 5.00 5.00 5.00 5.00 4.50 5.00 5.70 3.80 3.75 4.00 4.00

* p \ .01; ** p \ .01


123

development for males and females. These findings indi-

cate a number of potential domains that may foster positive

development during this transition period.

Self regulatory characteristics across childhood and

adolescence predicted later positive development, reveal-

ing the importance of self control and control over emo-

tions, particularly for young men. Others have also

observed the relationship between self regulation and

positive development (e.g., Shoda et al. 1990). Shonkoff

and Phillips (2000) have described the development of the

ability to self regulate as ‘‘a cornerstone of early childhood

development that cuts across all domains of behavior’’

(p. 26). For example, emotional control is essential for the

development of social competence. The ability to self

regulate allows the unfolding of appropriate social behav-

ior (Eisenberg et al. 1995), is related to the ability to focus

on the needs of others, and is an important determinant of

prosocial behavior (Fabes et al. 1993, 1994). Self control in

late childhood predicted pathways to both emotional con-

trol and school adjustment and in this way represented an

early influence on positive development.

At the relational level, strong relationships with parents

and peers also significantly predicted positive develop-

ment. This is consistent with previous research such as

Schulenberg et al.’s (2004) finding that peer relationships

play an important role in the maintenance of well-being,

and Van Wel et al.’s (2002) finding that strong relation-

ships with parents continue to have implications for posi-

tive functioning in emerging adulthood. Attachment theory

(Bowlby 1971) suggests that positive relationships with

parents and peers may facilitate the development of young

peoples’ identity and trust in others, making it possible for

them to explore their environment and adapt well to change

(Sroufe et al. 1999). Strong relationships with parents may

also facilitate positive development through their contri-

bution to the development of emotional control (Cassidy

1994), with the relationship between these two antecedent

domains also observed in the current study. Somewhat

surprisingly, the association between relationships with

parents in mid/late adolescence and positive development

in emerging adulthood was stronger for males than

females. One possible explanation for this finding is that

the quality of relationships with parents was more stable

over time for females, and hence changes to the quality of

relationships with parents in mid/late adolescence may be

particularly relevant to young men’s healthy development.

Adjustment to the school setting was also related to later

positive development. Academic skills may be particularly

important for healthy development in the context of a

knowledge economy, where important outcomes, such as

employment, require increasing levels of competency

(Lewis et al. 2009). Feelings of connectedness to teachers

and to the school as an institution may also facilitate

wellbeing (Griffiths et al. 2009), a proposition supported by

a strong body of empirical evidence, such as McGraw

et al.’s (2008) recent Australian study. According to con-

trol theory, young people who feel connected to school are

also more likely to adopt prosocial norms about appropriate

behaviour, which can help them to avoid risky behaviours

like substance misuse (Maddox and Prinz 2003). Hence,

adjustment to the school setting may facilitate positive

development through a number of avenues.

Results also indicate the importance of community

engagement during mid to late adolescence for positive

development in emerging adulthood. This supports theo-

retical propositions that adolescents need to develop an

understanding of their roles and connections to the broader

society for healthy psychosocial development and identity

formation (e.g., Erikson 1965). Civic mindedness has

also been theorized to reflect an individual’s developing

capacity for empathy and responsibility (e.g., Maslow

1972), which are important elements of social competence,

a dimension of our positive development model. The

results further suggest that an orientation towards the

community may have particular relevance for males’

healthy development, perhaps as a result of their generally

lower levels of this aspect of connectedness.

Family socioeconomic status in late childhood emerged

as a significant predictor of positive development in

emerging adulthood. This finding is consistent with previ-

ous research suggesting that children who live in poorly

resourced environments experience substantial develop-

mental deficits (Korenman et al. 1995). It is also consistent

with a previous study of the ATP sample at 15–16 years,

which found that family socioeconomic status played a

significant role in the development of civic engagement, a

dimension of positive development in emerging adulthood

(Smart et al. 2000). Children growing up in higher socio-

economic status families are likely to have a greater

capacity to take advantage of neighborhood resources such

as social cohesion (Benson et al. 1998), and opportunities

for relationships and activities that support their needs

(Kagitcibasi 2007; Lerner and Overton 2008). Parents’

ability to invest in their children’s development and par-

ents’ emotional wellbeing may also mediate the effects of

socioeconomic status on children’s capacity to develop

successfully (Yeung et al. 2002). Parents’ ability to act as

successful role models might also account for observed

socioeconomic effects (Smart et al. 2000).

Findings also reveal that the impact of earlier experi-

ences appeared to be mediated by later experiences, sup-

porting Schulenberg et al.’s (2004) proposition of the

salience of proximal influences. There was one exception,

however, with the temperament dimension of reactivity in

late childhood demonstrating direct effects with positive

development that were not mediated by later measures of


123

reactivity. It is possible that negative reactivity at

11–12 years, which coincides with significant pubertal

changes, may represent a particularly salient risk factor for

poor outcomes such as depression (Cyranowski et al.

2000).

Whereas Shiner (2000) observed a relationship between

a number of personality traits and later positive function-

ing, personality traits did not emerge as significant pre-

dictors in the current study. This divergence in findings is

likely to reflect the current study’s use of a comprehensive

multivariate model, which allowed the unique contribu-

tions of predictors to positive development to be examined.

Temperament is typically seen as the ‘‘core’’ of aspects of

developing personality, including affective, activational,

and attentional dimensions (Sanson et al. 2002). Person-

ality encompasses a broader range of factors, including

thought content, skills, habits, values, beliefs, and social

cognitions (Shiner and Caspi 2003). Personality traits may

not make a significant unique contribution to positive

development after underlying temperament dimensions are

taken into account.

Certain limitations of the present research merit con-

sideration. Given the large scale and breadth of this study,

it cannot reveal the mechanisms through which the vari-

ables identified as important for positive development exert

their influence. Rather, the current article provides a basis

for further research to explore these relationships in greater

depth. Negative aspects of development such as indicators

of psychopathology were not included as predictors in the

present study because the relationship between positive and

negative developmental outcomes, and the way that they

should be conceptualized in a single model, remains con-

troversial (Silbereisen and Lerner 2007). Since the rela-

tionship between negative indicators and positive

development is of both theoretical and empirical interest,

further research is needed to examine how best to con-

ceptualize negative outcomes in a model of positive

development and its antecedents. It may also be of interest

in future research to separately examine predictors of the

five facets of positive development that make up our model

of positive development, to examine whether common

attributes and experiences underlie each of them.

Nevertheless, the current study provided a rare oppor-

tunity to examine the contributions of individual, rela-

tionship and community factors from infancy to late

adolescence to positive development in emerging adult-

hood. It employed an empirically tested, multi-dimensional

construct of positive development in emerging adulthood,

rather than a single facet of this construct as in most pre-

vious research. The multi-wave longitudinal data

set allowed this question to be investigated over a 20 year

period of time using data from multiple informants,

including parents, primary school teachers, and the

children/adolescents themselves, reducing the effects of

shared method variance. The study also provided indica-

tions of gender differences in predictors of positive

development that have not previously been described. By

utilizing multivariate analyses, the study was able to pro-

vide an indication of the relative contributions of the many

previously identified predictors of positive development or

its dimensions.

The findings have a number of implications for policy

and future research. Interventions that promote strong

family and peer relationships, the ability to self regulate,

and that facilitate school adjustment, are likely to benefit

young people’s positive development. The results also

suggest the need for early, multifaceted interventions to

reduce the effects of socioeconomic disadvantage on

positive development (Kagitcibasi 2007; Kagitcibasi et al.

2001), although further research is needed to provide

insight into the mechanisms through which socio-economic

status exerts its effects.

We examined predictors of a multi-component index of

positive development in emerging adulthood that includes

a wide set of predictors from infancy to late adolescence

spanning individual, relational and broader community

characteristics. This study demonstrates that there are a

number of domains of influence that contribute to positive

development, reflecting a wide range of both individual and

contextual factors. These findings suggest a number of

potential avenues for intervention to promote positive

development in emerging adulthood.

Acknowledgments The ATP study is led and managed by the

Australian Institute of Family Studies, and further information is

available from the ATP website (www.aifs.gov.au/atp). Funding for

this analysis was supported through grants from the Australian

Research Council. Professor Toumbourou is supported by a Victorian

Health Promotion Foundation Senior Research Fellowship. We wish

to acknowledge the work of Professors Margot Prior and Frank

Oberklaid, along with other collaborators who have contributed to the

Australian Temperament Project. We would also like to sincerely

thank the participating families for their loyal support of the study.

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Author Biographies

Meredith O’Connor is based at the Department of Paediatrics and

Melbourne Graduate School of Education at The University of

Melbourne. Her areas of interest include the transition to adulthood,

and the interrelationships between well-being, mental illness, and

education.

Ann Sanson is a Professor in Paediatrics at the University of

Melbourne and the Network Coordinator for the Australian Research

Alliance for Children and Youth (ARACY). She is a developmental

psychologist whose main research interests revolve around the

interplay of intrinsic child characteristics and family and contextual

factors in the development of good and poor psychosocial adjustment.

Mary Hawkins is a Research Officer working in the Department of

Paediatrics, The University of Melbourne, located in the Royal

Children’s Hospital. Mary has a background in psychology and has a

particular interest in the development and validation of outcome

measures for use in research.

Primrose Letcher is a research analyst in the Department of

Paediatrics at The University of Melbourne, based in the Royal

Children’s Hospital. Her areas of interest are adolescent mental health

and well being.

John Winston Toumbourou is Professor and Chair in Health

Psychology at Deakin University and a Senior Research Fellow

within the Murdoch Children’s Research Institute at the Centre for

Adolescent Health. John is a founding member and the current Chair

of the College of Health Psychologists within the Australian

Psychological Society. John’s interests include evaluation, drug

abuse prevention and treatment, and the role of community, family

and peer groups in adolescent health promotion.

Diana Smart is a Senior Research Fellow at the Australian Institute

of Family Studies and works primarily on the Australian Tempera-

ment Project and Growing Up in Australia: The Longitudinal Study of

Australian Children. She joined the Growing Up in Australia study in

2007 after a long association with the Australian Temperament

Project as the Project Manager. Her research interests include child

and youth adjustment, developmental transitions and pathways, and

the fostering of social competence and social responsibility.

Suzanne Vassallo is a Research Fellow at the Australian Institute of

Family Studies and the Project Manager of the study. Suzanne

interests include parenting, family relationships, and child

development.

Craig A. Olsson is based at the Centre for Adolescent Health. His

work addresses the many and varied processes in child and adolescent

psychological development—from genes, to individuals, to families,

to school environments, communities and cultures.


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predictors of positive development in emerging adulthood

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