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Prevalent User Bias in Cross-sectional and Longitudinal Studies: A Concept Simply Explained.
1Dept. of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India.
Indian Journal of Psychological Medicine
|August 13, 2025
Summary
Prevalent user bias occurs when studies recruit participants who have already used medication, leading to biased results. Recruiting new users is essential to avoid this bias in medical research.
Area of Science:
- Epidemiology
- Biostatistics
- Clinical Research Methodology
Background:
- User bias in medication studies can skew results by analyzing participants who have already experienced medication use.
- This bias, termed prevalent user bias, affects samples by dividing them into former and continuing users.
Purpose of the Study:
- To define and illustrate prevalent user bias in various study designs.
- To discuss implications of this bias, including its potential role in the obesity paradox and completer analyses in randomized controlled trials (RCTs).
Main Methods:
- The study describes three hypothetical research scenarios: a cross-sectional study, a longitudinal observational study, and a randomized controlled trial (RCT).
- It discusses concepts and implications of prevalent user bias within these contexts.
Main Results:
- Recruiting prevalent users leads to a biased sample when medication experience is relevant to the study outcome.
- Completer analyses in RCTs are identified as fallacious due to examining prevalent users.
Conclusions:
- Prevalent user bias can be avoided by recruiting only new medication users.
- Researchers must consider and ascertain reasons for dropout in longitudinal studies to mitigate this bias.
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