1 class 7 measurement issues in research with diverse populations including health disparities...

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Class 7

Measurement Issues in Research with Diverse Populations Including Health Disparities

Research

November 5, 2009

Anita L. Stewart Institute for Health & Aging

University of California, San Francisco

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Overview of Class 7

Background: culture-specific versus generic measures

Conceptual and psychometric adequacy and equivalence– Adequacy in one group

– Equivalence across groups

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Background

U.S. population becoming more diverse Minority groups are being included in

research due to:– NIH mandate (1993 – women and

minorities)

– Health disparities initiatives

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Types of Diverse Groups

Health disparities research focuses on differences in health between …– Minority vs. non-minority

– Lower income vs. others

– Lower education vs. others

– Limited English Proficiency (LEP) vs. others

– …. and many others

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Measurement Implications of Research in Diverse Groups

Most self-reported measures were developed and tested in mainstream, well-educated groups

Little information is available on appropriateness, reliability, validity, and responsiveness in diverse groups– Although this is changing rapidly

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Measurement Adequacy vs. Measurement Equivalence

Adequacy - within a “diverse” group– concepts are appropriate and relevant– psychometric properties meet minimal criteria

» Good variability » Reliable and valid» Sensitive to change over time

Equivalence - between “diverse” groups– conceptual and psychometric properties are

comparable

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Why Not Use Culture-Specific Measures?

Measurement goal is to identify measures that can be used across all groups in one study, yet maintain sensitivity to diversity and have minimal bias

Most health disparities studies compare mean scores across diverse groups

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Generic/Universal vs Group-Specific(Etic versus Emic)

Concepts unlikely to be defined exactly the same way across diverse ethnic groups

Generic/universal (etic)– features of a concept that are appropriate across

groups Group-Specific (emic)

– idiosyncratic or culture-specific portions of a concept

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Etic versus Emic (cont.)

Goal in health disparities research with more than one group:– identify generic/universal portion of a concept that are

applicable across all groups For within-group studies:

– the culture-specific portion is also relevant

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Overview of Class 7




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Conceptual and Psychometric Adequacy and Equivalence

Conceptual

Psychometric

Adequacyin 1 Group

EquivalenceAcross Groups

Concept equivalentacross groups

Psychometric propertiesmeet minimal standards

within one group

Psychometric propertiesinvariant (equivalent)

across groups

Concept meaningfulwithin one group

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Left Side of Matrix: Adequacy in a Single Group

Conceptual

Psychometric

Adequacyin 1 Group




within one group


across groups


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Ride Side of Matrix: Equivalence in More Than One Group

Conceptual

Psychometric

Adequacyin 1 Group




within one group


across groups


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Overview of Class 7




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Approaches to Explore Conceptual Adequacy in Diverse Groups

Literature reviews of concepts and measures

In-depth interviews and focus groups – discuss concepts, obtain their views

Expert consultation from diverse groups– review concept definitions– rate relevance of items

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Basis: Published Review - Physical Activity Measures for Minority Women

WHI convened experts to identify issues in measuring PA in minority and older women

Some conclusions:– Add culturally sensitive activities (e.g., walking for

transportation and errands)– Measure intermittent activities – Phrases “leisure time, free time, spare time” (used to denote

non-occupational activities) not understood Review can help select appropriate measures and adapt

as needed

LC Masse et al., J Women’s Health, 1998;7:57-67.

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Basis: Published Review - Measures of Dietary Intake in Minority Populations

Reviewed food frequency questionnaires for appropriateness for minority populations– method of development, minority-group specific

features, reliability, validity, and systematic bias Group differences that could affect scores:

– Portion sizes differ– Missing common foods of minority groups/cultures

Would underestimate total intake and nutrients

RJ Coates et al. Am J Clin Nutr; 1997;65(suppl):1108S-15S.

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A Structured Method for Examining Conceptual Relevance

Compiled set of 33 HRQL items Assessed relevance to older African Americans After each question, asked “how relevant is this

question to the way you think about your health?”– Response scale: 0-10 scale with endpoints labeled– 0=not at all relevant, 10=extremely relevant

Cunningham WE et al., Qual Life Res, 1999;8:749-768.

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HRQL Relevance Results

Most relevant items:– Spirituality, weight-related health,

hopefulness

– Spirituality items Least relevant items:

– Physical functioning, role limitations due to emotional problems

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Qualitative Research: Expert Panel Reviewed Spanish FACT-G

Functional Assessment of Cancer Therapy – General (FACT-G)

Bilingual/bicultural panel reviewed items for conceptual relevance to Hispanics– One item had low relevance (I worry about dying)

» Added new item "I worry my condition will get worse" – One domain missing – spirituality

» Developed new spirituality scale (FACIT-Sp) with input from cancer patients, psychotherapists, and religious experts

D Cella et al. Med Care 1998: 36;1407

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Example of Inadequate Concept

Patient satisfaction typically conceptualized in mainstream populations in terms of, e.g.,– access, technical care, communication,

continuity, interpersonal style In minority and low income groups,

additional relevant domains include, e.g., – discrimination by health professionals– sensitivity to language barriers

MN Fongwa et al., Ethnicity Dis, 2006;16(3):948-955.

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Measuring Park/Recreation Environments in Low-Income Communities

New policy focus on how environments promote physical activity– Many good new measures

None considered concerns or environments of lower-income minority communities

MF Floyd et al. Am J Prev Med, 2009;36:S156-S160.

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Measuring Park/Recreation Environments in Low-Income Communities (cont)

Recommendations: In low-income communities of color:– Identify and address most salient

environmental needs– Incorporate research on preferred

recreational activities– Ensure representation of perceptions of

residents

MF Floyd et al. Am J Prev Med, 2009;36:S156-S160.

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Psychometric Adequacy in any Group

Minimal standards:– Sufficient variability

– Minimal missing data

– Adequate reliability/reproducibility

– Evidence of construct validity

– Evidence of sensitivity to change

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Overview of Class 7


Conceptual and psychometric adequacy and equivalence

– Adequacy in one group– Equivalence across groups

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Conceptual Equivalence Across Groups

Conceptual

Psychometric

Adequacyin 1 Group




within one group


across groups


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Conceptual Equivalence

Is the concept relevant, familiar, acceptable to all diverse groups being studied?

Is the concept defined the same way in all groups? – all relevant “domains” included (none missing)

– interpreted similarly

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Obtain Perspective of All Diverse Groups on Concept

Develop concept

Create item pool

Pretest/revise

Field survey

Psychometric analyses

Final measures

Obtain perspectives of diverse groups

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Example: Developing Concept of Interpersonal Processes of Care

IPC IIconceptualframework

IPC Version I frameworkin Milbank Quarterly

19 new focus groups -African American, Latino,and White adults

Literature review of quality

of care in diverse groups

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IPC-II Conceptual Framework: 91 items

I. COMMUNICATION III. INTERPERSONAL STYLE General clarity Respectfulness Elicitation/responsiveness Courteousness Explanations of Perceived discrimination --processes, condition, Emotional support self-care, meds Cultural sensitivity Empowerment II. DECISION MAKING Responsive to patient preferences Consider ability to comply

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IPC-II Conceptual Framework (cont)

IV. OFFICE STAFF Respectfulness Discrimination V. FOR LIMITED ENGLISH PROFICIENCY PATIENTS MD’s and office staff’s sensitivity to language

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Psychometric Equivalence

Conceptual

Psychometric

Adequacyin 1 Group




within one group


across groups


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Psychometric or Measurement Equivalence

When comparing groups (as in health disparities research):– Measures should have similar or equivalent

measurement properties in all diverse groups of interest in your study» e.g., English and Spanish, African Americans

and Caucasians

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Psychometric Equivalence Across Groups

Psychometric characteristics should be “equivalent” across all groups:– Sufficient variability– Minimal missing data– Reliability/reproducibility– Construct validity– Sensitivity to change

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Bias (Systematic Error) - A Special Concern

Observed group mean differences in a measure can be due to:– Culturally- or group-mediated differences in

true score (true differences) -- OR --

– Bias - systematic differences between observed scores not attributable to true scores

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Random versus Systematic Error

Observed true item score score

= + error random

systematic

Relevant to reliability

Relevant to validity

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Bias (Systematic Error) - A Special Concern (cont)

Measurement bias may make group comparisons invalid

Bias can be due to group differences in:– the meaning of concepts or items – the extent to which measures represent a concept – cognitive processes of responding– use of response scales– appropriateness of data collection methods

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Bias or “Systematic Difference”?

Bias refers to “deviation from true score” Cannot speak of a measure being “biased” in

one group compared to another w/o knowing true score

Preferred term: differential “item” functioning (DIF)– Item (or measure) that has a different meaning

in one group than another

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Item Equivalence

Differential Item Functioning (DIF)– Items are non-equivalent if they are

differentially related to the underlying trait Meaning of response categories is

similar across groups Distance between response categories is

similar across groups

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Methods for Identifying Differential Item Functioning (DIF)

Item Response Theory (IRT) Examines each item in relation to underlying

latent trait Tests if responses to one item predict the

underlying latent “score” similarly in two groups– if not, items have “differential item functioning”

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Example of Effect of Biased Items

5 CES-D items administered to Black and White men– 1 item subject to differential item functioning (bias)

5-item scale including item suggested that Black men had more somatic symptoms than White men (p < .01)

4-item scale excluding biased item showed no differences

S Gregorich, Med Care, 2006;44:S78-S94.

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Equivalence of Response Choices: Spanish and English Self-rated Health

Excellent Very good Good Fair Poor

Excelente Muy buena Buena Regular Mala

“Regular” in Spanish may be closer to “good” in English, thus is not comparable to the meaning of “fair”

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Equivalence of Response Choices: Spanish and English Self-rated Health

Excellent Very good Good Fair Poor

Excelente Muy buena Buena Regular (pasable?) Mala

“Regular” in Spanish may be closer to “good” in English, thus is not comparable to the meaning of “fair”

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Equivalence of Reliability?? No!

Difficult to compare reliability because it depends on the distribution of the construct in a sample– Thus lower reliability in one group may simply

reflect poorer variability More important is the adequacy of the

reliability in both groups– Reliability meets minimal criteria within each group

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Example: Adequacy of Reliability of Spanish SF-36 in Argentinean Sample

SF-36 scale Coefficient alpha

Physical functioning .85

Role limitations - physical .84

Bodily pain .80

General health perceptions .69

Vitality .82

Social functioning .76

Role limitations - emotional .75

Mental health .84

F Augustovski et al, J Clin Epid, 2008, in press;

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Equivalence of Criterion Validity

Determine if hypothesized patterns of associations with specified criteria are confirmed in both groups, e.g.– a measure predicts utilization in both groups

– a cutpoint on a screening measure has the same specificity and sensitivity in identifying a condition in both groups

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Equivalence of Construct Validity

Are hypothesized patterns of associations confirmed in both groups?– Example: Scores on the Spanish version of the

FACT-G had similar relationships with other health measures as scores on the English version

Primarily tested through subjectively examining pattern of correlations

Can also test using confirmatory factor analysis (CFA)

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Equivalence of Construct Validity of Spanish SF-36 in Argentinean Sample

Compared Spanish SF-36 construct validity test results to U.S. English SF-36 results

Tested several previously tested hypotheses (which were confirmed):– PCS decreases with age and # of diseases– Relationship of PCS and MCS with utilization– Known groups validity (scores lower for those with

various diseases)

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Equivalence of Factor Structure

Factor structure is similar in new group to structure in original groups in which measure was tested– measurement model is the same across

groups Methods

– Specify the number of factors you are looking for

– Determine if the hypothesized model fits the data

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How Evidence for Equivalence of Factor Structure is Obtained

Subjectively– visually compare factor pattern matrixes across

“group-specific” exploratory factor analysis solutions

Empirically– confirmatory factor analysis of data that

includes multiple groups– studies of psychometric invariance

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Empirical Examination of Equivalence of Factor Structure

Psychometric invariance (equivalence) Important properties of theoretically-based

factor structure (measurement model) do not vary across groups (are invariant)– measurement model is the same across groups

Empirical comparison across groups using confirmatory factor analysis – Not simply by examination

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Confirmatory Factor Analysis Hierarchical Tests of Equivalence

Across all groups – a sequential process: Same number of factors or dimensions Same items on same factors Same factor loadings No bias on any item across groups Same residuals on items No item or scale bias AND same residuals

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Measurement or Psychometric Invariance

Gregorich, S.E. Do self-report instruments allow meaningful comparisons across population groups? Testing measurement invariance using the confirmatory factor analysis framework. Med Care, 2006;44 (11, supp 3):S78-S94.

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Dimensional Invariance: Same number of factors

Configural Invariance: Same items load on same factors

Metric or Factor Pattern Invariance:Items have same loadings on same factors

Scalar or Strong Factorial Invariance:

Observed scores are unbiased

Residual Invariance:Observed item and factor

variances are unbiased

Strict Factorial InvarianceBoth scalar and residual criteria are met

Criteria for Evaluating Invariance AcrossGroups: Technical Terms

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Dimensional Invariance of CES-D Definition: same number of factors observed in

all groups Original 4 CES-D factors

– Somatic symptoms– Depressive affect– Interpersonal behavior– Positive affect

LS Radloff, The CES-D scale: A self-report depression scale for research in the general population, Applied Psychol Measurement, 1977;1:385-401.

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No Evidence of Dimensional Invariance Hispanic EPESE (n=2,536) and a study of older Mexican

Americans (n=330) 2 factors in both studies

– Depression (somatic symptoms, depressive affect, and interpersonal behavior)

– Well-being

American Indian adolescents (n=179) 3 factors

– Depressed affect– Somatic symptoms and reduced activity– Positive affect

TQ Miller et al., J Gerontol: Soc Sci 1997;520:S259

SM Manson et al., Psychol Assessment 1990;2:231-237

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Configural Invariance

Assumes: dimensional invariance is found (same number of factors)

Definition: Item-factor patterns are the same, i.e., the same items load on the same factors in both groups

CES-D example– 4 factors found in Anglos, Blacks, and Chicanos– Same items loaded on each factor in all groups

RE Roberts et al., Psychiatry Research, 1980;2:125-134

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Strong Factorial or ScalarInvariance:


Residual Invariance:Observed item and factor variances

can be compared across groups

Strict Factorial InvarianceBoth scalar invariance and residual invariance criteria are met

Configural Invariance

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Metric Invariance or Factor Pattern Invariance

Assumes: dimensional and configural invariance are found

Definition: Item loadings are the same across groups– i.e., the correlation of each item with its factor is

the same in all groups

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Metric Invariance

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Metric Invariance Example from Interpersonal Processes of Care

Out of 91 items – factor structure of 29 items met criteria of dimensional, configural, and metric invariance across 4 groups– Spanish-speaking Latinos, English speaking Latinos,

African Americans, Whites Dimensional

– Similar factor structure across all 4 groups Configural

– Same items loaded on each factor in all 4 groups Metric

– Same item loadings in all 4 groups

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Seven “Metric Invariant” Scales:Same Item Loadings Across Groups

I. COMMUNICATION Hurried communication Elicited concerns, responded Explained results, medications

II. DECISION MAKING Patient-centered decision-making

III. INTERPERSONAL STYLE Compassionate, respectful Discriminated Disrespectful office staff

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Strong Factorial Invariance or Scalar Invariance

Assumes: dimensional, configural, and metric invariance are found

Definition: Observed scores are unbiased, i.e., means can be compared across groups

Requires test of equivalence of mean scores across groups using confirmatory factor analysis

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Strong Factorial Invariance

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Seven “Scalar Invariant” (Unbiased) IPC Scales (18 items)

I. COMMUNICATION Hurried communication – lack of clarity Elicited concerns, responded Explained results, medications – explained results

II. DECISION MAKING Patient-centered decision-making – decided together

III. INTERPERSONAL STYLE Compassionate, respectful–(subset) compassionate, respectful Discriminated – discriminated due to race/ethnicity Disrespectful office staff

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Equivalence of Spanish and English Hospital Quality of Care Survey (H-CAHPS®)

Tested 7 subscales– Nurse communication, MD communication, communication

about meds, nursing services, discharge information, pain control, and physical environment

Report on translation/adaptation, pretesting, item-scale correlations, internal consistency reliability, and construct validity

CFA methods compared factor structure between Spanish and English groups

MP Hurtado et al. Health Serv Res, 2005;40-6, Part II:2140-2161

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Psychometric or Measurement Equivalence: Second Meaning

Measurement properties of a measure in your diverse group are similar to original (mainstream) groups on which the measures were developed

Subjective comparison and evaluation

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Mixed Methods for Assessing Equivalence

Use qualitative and quantitative methods in tandem to address issues of cultural equivalence

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Mixed Methods: Developing IPC Measure of “Cultural Sensitivity”

Initial concept and items from qualitative work 1st survey: In psychometric analyses, did not meet

minimal criteria Second version of concept and items

– new qualitative work, results of first study 2nd survey: In psychometric analyses, measure again

did not meet minimal criteria Analyzed focus group data in more depth

– cultural sensitivity is multidimensional 3rd survey: testing multidimensional measures of

cultural sensitivity

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Conclusions Measurement in health disparities and

minority health research is a relatively new field

Encourage testing and reporting on adequacy and equivalence of measures tested in any diverse population

As evidence grows, concepts and measures that work better across diverse groups will be identified

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Resource: Reviews of Measures for Diverse Populations

Multicultural measurement in older populations, JH Skinner et al (eds), Springer Publishing Co: NY, 2002– ALSO published as: Measurement in older ethnically diverse

populations, J Mental Health Aging, Vol 7, Spring 2001

Reviews measures that have been used cross-culturally in: acculturation, socio-economic status, social supports, cognition, health and functionalcapacity, depression, health locus of control, health-related quality of life,and religiosity

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Resource: Special Journal Issue

Measurement in a multi-ethnic society– Med Care, Vol 44, November 2006

– Qualitative and quantitative methods in addressing measurement in diverse populations

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Resource: Clinical Research with Diverse Communities

Epi 222, Spring Course Director: Eliseo Pérez-Stable, MD Thursdays 2:45-4:15

– China Basin Summary and syllabus for 2008:

http://www.epibiostat.ucsf.edu/courses/schedule/diverse_pops.html

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Epi 222 Provides Overview Of….

Meaning of race, ethnicity, social class and culture Multi-level factors that are mechanisms of health

disparities Methodological and measurement considerations in

research in ethnically diverse populations Qualitative methods in developing and pre-testing

instruments Strategies for recruiting ethnically diverse populations

and for expanding the role of communities

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Homework for Next Week

For those interested in studying any diverse population group:– Finish matrix: complete rows 27-34

» Translations, equivalence across diverse groups, acceptability for your population

For everyone:– Complete row 34: can measure be modified

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Next Week (Class 8)

Pretesting measures and creating a questionnaire

1 class 7 measurement issues in research with diverse populations including health disparities...

Documents

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