Approaches for creating comparable measures of alcohol use symptoms: Harmonization with eight studies of criminal justice populations

Andrea M. Hussong, Nisha C. Gottfredson, Dan J. Bauer, Patrick J. Curran, Maleeha Haroon, Redonna Chandler, Shoshana Y. Kahana, Joseph A.C. Delaney, Frederick L. Altice, Curt G. Beckwith, Daniel J. Feaster, Patrick M. Flynn, Michael S. Gordon, Kevin Knight, Irene Kuo, Lawrence J. Ouellet, Vu M. Quan, David W. Seal, Sandra A. Springer

Research output: Contribution to journalArticle

Abstract

Background: With increasing data archives comprised of studies with similar measurement, optimal methods for data harmonization and measurement scoring are a pressing need. We compare three methods for harmonizing and scoring the AUDIT as administered with minimal variation across 11 samples from eight study sites within the STTR (Seek-Test-Treat-Retain) Research Harmonization Initiative. Descriptive statistics and predictive validity results for cut-scores, sum scores, and Moderated Nonlinear Factor Analysis scores (MNLFA; a psychometric harmonization method) are presented. Methods: Across the eight study sites, sample sizes ranged from 50 to 2405 and target populations varied based on sampling frame, location, and inclusion/exclusion criteria. The pooled sample included 4667 participants (82% male, 52% Black, 24% White, 13% Hispanic, and 8% Asian/ Pacific Islander; mean age of 38.9 years). Participants completed the AUDIT at baseline in all studies. Results: After logical harmonization of items, we scored the AUDIT using three methods: published cut-scores, sum scores, and MNLFA. We found greater variation, fewer floor effects, and the ability to directly address missing data in MNLFA scores as compared to cut-scores and sum scores. MNLFA scores showed stronger associations with binge drinking and clearer study differences than did other scores. Conclusions: MNLFA scores are a promising tool for data harmonization and scoring in pooled data analysis. Model complexity with large multi-study applications, however, may require new statistical advances to fully realize the benefits of this approach.

LanguageEnglish (US)
Pages59-68
Number of pages10
JournalDrug and Alcohol Dependence
Volume194
DOIs
StatePublished - Jan 1 2019

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Criminal Law
Meta-Analysis
Alcohols
Factor analysis
Population
Statistics
Sampling
Binge Drinking
Aptitude
Health Services Needs and Demand
Hispanic Americans
Psychometrics
Reproducibility of Results
Sample Size
Statistical Factor Analysis
Research Design
Research

Keywords

  • Data harmonization
  • Data pooling
  • Drinking severity
  • Integrative data analysis

ASJC Scopus subject areas

  • Toxicology
  • Pharmacology
  • Psychiatry and Mental health
  • Pharmacology (medical)

Cite this

Approaches for creating comparable measures of alcohol use symptoms : Harmonization with eight studies of criminal justice populations. / Hussong, Andrea M.; Gottfredson, Nisha C.; Bauer, Dan J.; Curran, Patrick J.; Haroon, Maleeha; Chandler, Redonna; Kahana, Shoshana Y.; Delaney, Joseph A.C.; Altice, Frederick L.; Beckwith, Curt G.; Feaster, Daniel J.; Flynn, Patrick M.; Gordon, Michael S.; Knight, Kevin; Kuo, Irene; Ouellet, Lawrence J.; Quan, Vu M.; Seal, David W.; Springer, Sandra A.

In: Drug and Alcohol Dependence, Vol. 194, 01.01.2019, p. 59-68.

Research output: Contribution to journalArticle

Hussong, AM, Gottfredson, NC, Bauer, DJ, Curran, PJ, Haroon, M, Chandler, R, Kahana, SY, Delaney, JAC, Altice, FL, Beckwith, CG, Feaster, DJ, Flynn, PM, Gordon, MS, Knight, K, Kuo, I, Ouellet, LJ, Quan, VM, Seal, DW & Springer, SA 2019, 'Approaches for creating comparable measures of alcohol use symptoms: Harmonization with eight studies of criminal justice populations' Drug and Alcohol Dependence, vol. 194, pp. 59-68. https://doi.org/10.1016/j.drugalcdep.2018.10.003
Hussong, Andrea M. ; Gottfredson, Nisha C. ; Bauer, Dan J. ; Curran, Patrick J. ; Haroon, Maleeha ; Chandler, Redonna ; Kahana, Shoshana Y. ; Delaney, Joseph A.C. ; Altice, Frederick L. ; Beckwith, Curt G. ; Feaster, Daniel J. ; Flynn, Patrick M. ; Gordon, Michael S. ; Knight, Kevin ; Kuo, Irene ; Ouellet, Lawrence J. ; Quan, Vu M. ; Seal, David W. ; Springer, Sandra A. / Approaches for creating comparable measures of alcohol use symptoms : Harmonization with eight studies of criminal justice populations. In: Drug and Alcohol Dependence. 2019 ; Vol. 194. pp. 59-68.
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abstract = "Background: With increasing data archives comprised of studies with similar measurement, optimal methods for data harmonization and measurement scoring are a pressing need. We compare three methods for harmonizing and scoring the AUDIT as administered with minimal variation across 11 samples from eight study sites within the STTR (Seek-Test-Treat-Retain) Research Harmonization Initiative. Descriptive statistics and predictive validity results for cut-scores, sum scores, and Moderated Nonlinear Factor Analysis scores (MNLFA; a psychometric harmonization method) are presented. Methods: Across the eight study sites, sample sizes ranged from 50 to 2405 and target populations varied based on sampling frame, location, and inclusion/exclusion criteria. The pooled sample included 4667 participants (82{\%} male, 52{\%} Black, 24{\%} White, 13{\%} Hispanic, and 8{\%} Asian/ Pacific Islander; mean age of 38.9 years). Participants completed the AUDIT at baseline in all studies. Results: After logical harmonization of items, we scored the AUDIT using three methods: published cut-scores, sum scores, and MNLFA. We found greater variation, fewer floor effects, and the ability to directly address missing data in MNLFA scores as compared to cut-scores and sum scores. MNLFA scores showed stronger associations with binge drinking and clearer study differences than did other scores. Conclusions: MNLFA scores are a promising tool for data harmonization and scoring in pooled data analysis. Model complexity with large multi-study applications, however, may require new statistical advances to fully realize the benefits of this approach.",
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AU - Bauer, Dan J.

AU - Curran, Patrick J.

AU - Haroon, Maleeha

AU - Chandler, Redonna

AU - Kahana, Shoshana Y.

AU - Delaney, Joseph A.C.

AU - Altice, Frederick L.

AU - Beckwith, Curt G.

AU - Feaster, Daniel J.

AU - Flynn, Patrick M.

AU - Gordon, Michael S.

AU - Knight, Kevin

AU - Kuo, Irene

AU - Ouellet, Lawrence J.

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AU - Springer, Sandra A.

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N2 - Background: With increasing data archives comprised of studies with similar measurement, optimal methods for data harmonization and measurement scoring are a pressing need. We compare three methods for harmonizing and scoring the AUDIT as administered with minimal variation across 11 samples from eight study sites within the STTR (Seek-Test-Treat-Retain) Research Harmonization Initiative. Descriptive statistics and predictive validity results for cut-scores, sum scores, and Moderated Nonlinear Factor Analysis scores (MNLFA; a psychometric harmonization method) are presented. Methods: Across the eight study sites, sample sizes ranged from 50 to 2405 and target populations varied based on sampling frame, location, and inclusion/exclusion criteria. The pooled sample included 4667 participants (82% male, 52% Black, 24% White, 13% Hispanic, and 8% Asian/ Pacific Islander; mean age of 38.9 years). Participants completed the AUDIT at baseline in all studies. Results: After logical harmonization of items, we scored the AUDIT using three methods: published cut-scores, sum scores, and MNLFA. We found greater variation, fewer floor effects, and the ability to directly address missing data in MNLFA scores as compared to cut-scores and sum scores. MNLFA scores showed stronger associations with binge drinking and clearer study differences than did other scores. Conclusions: MNLFA scores are a promising tool for data harmonization and scoring in pooled data analysis. Model complexity with large multi-study applications, however, may require new statistical advances to fully realize the benefits of this approach.

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