Depression screening tool accuracy individual participant data meta-analyses: data contribution was associated with multiple factors

Abstract

Objectives: To examine the proportion of eligible primary studies that contributed data, study characteristics associated with data contribution, and reasons for noncontribution using diagnostic test accuracy Individual Participant Data Meta-Analysis (IPDMA) data sets from the DEPRESsion Screening Data project.

Study design and setting: We reviewed data set contributions from four IPDMAs. A multivariable logistic regression model was fitted to evaluate study factors associated with data contribution.

Results: Of 456 eligible studies from four included IPDMAs, 295 (65%) contributed data. More recent year of publication and higher journal impact factor were associated with greater odds of data contribution. Studies conducted in Europe (excluding the United Kingdom), Oceania, Canada, the Middle East, Africa, and Central or South America (reference = the United States), that have recruitment from inpatient care or nonmedical settings (reference = outpatient), that reported screening accuracy results, or that drew negative conclusions (reference = positive conclusions) were more likely to contribute data. Studies of the Geriatric Depression Scale (reference = the Patient Health Questionnaire) or lacking funding information were negatively associated with data contribution. Over 80% of noncontributions were due to authors being unreachable or data being unavailable.

Conclusion: The study identified factors associated with data contribution that may support future research to promote data contribution to IPDMAs.

Keywords: Data contribution; Data sharing; Depression screening; Diagnostic test accuracy; Individual participant data meta-analysis; Meta-analysis.