Psychometric performance of the Mental Health Implementation Science Tools (mhIST) across six low- and middle-income countries.

Implementation measurement Low- and middle-income countries Mental health Psychometrics

Journal

Implementation science communications
ISSN: 2662-2211
Titre abrégé: Implement Sci Commun
Pays: England
ID NLM: 101764360

Informations de publication

Date de publication:
19 May 2022
Historique:
received: 21 12 2021
accepted: 26 04 2022
entrez: 19 5 2022
pubmed: 20 5 2022
medline: 20 5 2022
Statut: epublish

Résumé

Existing implementation measures developed in high-income countries may have limited appropriateness for use within low- and middle-income countries (LMIC). In response, researchers at Johns Hopkins University began developing the Mental Health Implementation Science Tools (mhIST) in 2013 to assess priority implementation determinants and outcomes across four key stakeholder groups-consumers, providers, organization leaders, and policy makers-with dedicated versions of scales for each group. These were field tested and refined in several contexts, and criterion validity was established in Ukraine. The Consumer and Provider mhIST have since grown in popularity in mental health research, outpacing psychometric evaluation. Our objective was to establish the cross-context psychometric properties of these versions and inform future revisions. We compiled secondary data from seven studies across six LMIC-Colombia, Myanmar, Pakistan, Thailand, Ukraine, and Zambia-to evaluate the psychometric performance of the Consumer and Provider mhIST. We used exploratory factor analysis to identify dimensionality, factor structure, and item loadings for each scale within each stakeholder version. We also used alignment analysis (i.e., multi-group confirmatory factor analysis) to estimate measurement invariance and differential item functioning of the Consumer scales across the six countries. All but one scale within the Provider and Consumer versions had Cronbach's alpha greater than 0.8. Exploratory factor analysis indicated most scales were multidimensional, with factors generally aligning with a priori subscales for the Provider version; the Consumer version has no predefined subscales. Alignment analysis of the Consumer mhIST indicated a range of measurement invariance for scales across settings (R We provide evidence that the Consumer and Provider versions of the mhIST are internally valid and reliable across diverse contexts and stakeholder groups for mental health research in LMIC. We recommend the instrument be revised based on these analyses and future research examine instrument utility by linking measurement to other outcomes of interest.

Sections du résumé

BACKGROUND BACKGROUND
Existing implementation measures developed in high-income countries may have limited appropriateness for use within low- and middle-income countries (LMIC). In response, researchers at Johns Hopkins University began developing the Mental Health Implementation Science Tools (mhIST) in 2013 to assess priority implementation determinants and outcomes across four key stakeholder groups-consumers, providers, organization leaders, and policy makers-with dedicated versions of scales for each group. These were field tested and refined in several contexts, and criterion validity was established in Ukraine. The Consumer and Provider mhIST have since grown in popularity in mental health research, outpacing psychometric evaluation. Our objective was to establish the cross-context psychometric properties of these versions and inform future revisions.
METHODS METHODS
We compiled secondary data from seven studies across six LMIC-Colombia, Myanmar, Pakistan, Thailand, Ukraine, and Zambia-to evaluate the psychometric performance of the Consumer and Provider mhIST. We used exploratory factor analysis to identify dimensionality, factor structure, and item loadings for each scale within each stakeholder version. We also used alignment analysis (i.e., multi-group confirmatory factor analysis) to estimate measurement invariance and differential item functioning of the Consumer scales across the six countries.
RESULTS RESULTS
All but one scale within the Provider and Consumer versions had Cronbach's alpha greater than 0.8. Exploratory factor analysis indicated most scales were multidimensional, with factors generally aligning with a priori subscales for the Provider version; the Consumer version has no predefined subscales. Alignment analysis of the Consumer mhIST indicated a range of measurement invariance for scales across settings (R
CONCLUSION CONCLUSIONS
We provide evidence that the Consumer and Provider versions of the mhIST are internally valid and reliable across diverse contexts and stakeholder groups for mental health research in LMIC. We recommend the instrument be revised based on these analyses and future research examine instrument utility by linking measurement to other outcomes of interest.

Identifiants

pubmed: 35590428
doi: 10.1186/s43058-022-00301-6
pii: 10.1186/s43058-022-00301-6
pmc: PMC9118868
doi:

Types de publication

Journal Article

Langues

eng

Pagination

54

Subventions

Organisme : NIMH NIH HHS
ID : T32 MH109436
Pays : United States
Organisme : NIMH NIH HHS
ID : K01MH116335
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR003015
Pays : United States
Organisme : NCATS NIH HHS
ID : KL2 TR003016
Pays : United States
Organisme : NIMH NIH HHS
ID : T32 MH103210
Pays : United States
Organisme : NCATS NIH HHS
ID : KL2TR003016
Pays : United States
Organisme : NIDA NIH HHS
ID : P30 DA029926
Pays : United States
Organisme : NIMH NIH HHS
ID : T32MH109436
Pays : United States
Organisme : NIAAA NIH HHS
ID : K01 AA026523
Pays : United States
Organisme : NIAAA NIH HHS
ID : K01AA026523
Pays : United States
Organisme : NIMH NIH HHS
ID : U19MH109988
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1TR003015
Pays : United States
Organisme : NIMH NIH HHS
ID : R01MH115495-02S1
Pays : United States
Organisme : NIMH NIH HHS
ID : U19 MH109988
Pays : United States

Informations de copyright

© 2022. The Author(s).

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Auteurs

Luke R Aldridge (LR)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA. laldrid3@jhu.edu.

Christopher G Kemp (CG)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA.

Judith K Bass (JK)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA.

Kristen Danforth (K)

University of Washington Department of Global Health, Seattle, USA.

Jeremy C Kane (JC)

Columbia University Mailman School of Public Health, New York, USA.

Syed U Hamdani (SU)

University of Liverpool Institute of Population Health, Liverpool, UK.

Lisa A Marsch (LA)

Dartmouth Center for Technology & Behavioral Health, Lebanon, USA.

José M Uribe-Restrepo (JM)

Pontificia Universidad Javeriana Department of Psychiatry and Mental Health, Bogota, Colombia.

Amanda J Nguyen (AJ)

University of Virginia School of Education and Human Development, Charlottesville, USA.

Paul A Bolton (PA)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA.

Laura K Murray (LK)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA.

Emily E Haroz (EE)

Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA.

Classifications MeSH