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Depression screening tool accuracy individual participant data meta-analyses: data contribution was associated with
1Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
Journal of Clinical Epidemiology
|August 24, 2023
Summary
Most eligible studies (65%) contributed data to diagnostic test accuracy Individual Participant Data Meta-Analyses (IPDMAs). Factors like publication year and journal impact influenced contribution, with over 80% of noncontributions due to author unreachability or data unavailability.
Area of Science:
- Medical Informatics
- Psychiatry Research
- Meta-Analysis Methodology
Background:
- Individual Participant Data Meta-Analyses (IPDMAs) are crucial for diagnostic test accuracy research.
- Understanding factors influencing data contribution is vital for maximizing IPDMA utility.
- The DEPRESsion Screening Data project provides a unique dataset for this analysis.
Approach:
- Reviewed data contributions from four diagnostic test accuracy IPDMAs.
- Analyzed 456 eligible studies, identifying 295 (65%) data contributors.
- Employed multivariable logistic regression to pinpoint factors associated with data contribution.
Key Points:
- Publication year and journal impact factor positively correlated with data contribution.
- Geographic location, recruitment setting, reported results (accuracy vs. negative conclusions), and specific scales (Geriatric Depression Scale) influenced contribution.
- Primary reasons for noncontribution were author unreachability (over 80%) or data unavailability.
Conclusions:
- Identified key characteristics of studies that contribute data to IPDMAs.
- Findings can inform strategies to enhance data sharing and improve future IPDMA research.
- Addressing barriers like author contact and data accessibility is crucial for maximizing research potential.
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