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Mitigating systematic measurement error in comparative effectiveness research in heterogeneous populations
1Division of Health Policy and Clinical Effectiveness, Cincinnati Children's Hospital Medical Center, University of Cincinnati Medical School, Cincinnati, OH 45226, USA. adam.carle@cchmc.org
Medical Care
|May 18, 2010
Summary
Measurement bias can distort alcohol abuse research findings across racial and ethnic groups. Adjusting for this bias reveals comparable alcohol abuse levels between whites and Hispanics, and lower levels in Black/African-Americans.
Area of Science:
- Psychometrics and Health Services Research
- Epidemiology of Substance Abuse
Background:
- Accurate assessment of treatment effectiveness in diverse populations necessitates equivalent measurement across all groups.
- Measurement bias, where identical health states yield dissimilar responses due to ethnicity, hinders comparative evaluation and evidence-based policy.
Purpose of the Study:
- To evaluate and correct for measurement bias in assessing alcohol abuse.
- To investigate measurement equivalence of alcohol abuse indicators across educational and income levels for White, Black/African-American, and Hispanic individuals in the US.
Main Methods:
- Utilized data from a representative 2001-2002 US sample.
- Applied multiple-group, multiple-indicator, multiple-cause (MIMIC) models to assess measurement bias.
- Analyzed 10 items measuring alcohol abuse across racial/ethnic groups (White, Black/African-American, Hispanic) and socioeconomic factors.
Main Results:
- Identified significant measurement bias related to education, poverty, and minority status.
- Unadjusted analyses suggested higher alcohol abuse among Black/African-Americans and Hispanics compared to Whites.
- Bias-adjusted analyses revealed comparable alcohol abuse between Whites and Hispanics, and lower levels among Black/African-Americans.
Conclusions:
- Measurement bias can lead to inaccurate conclusions regarding alcohol abuse across racial and ethnic groups.
- Failure to account for bias distorts research on alcohol abuse correlates and treatment effectiveness.
- Model-based adjustments are crucial for accurate comparative conclusions in heterogeneous populations.
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