DEPRESSD is an international collaborative project involving experts in health policy, psychiatry and statistics as well as investigators who have collected depression screening data. Our mission is to synthesize the global depression screening data in order to develop and apply rigourous methods on assessing depression screening tool accuracy that minimize bias and provide evidence to inform research and policy to improve mental health care. The project builds a database for shared usage and also provides a unique platform for trainee development, including skills in evidence synthesis and statistical modelling.
We have contributed data from a study to DEPRESSD and Felix Fischer spent 4 months in Montreal investigating, whether scoring based on latent variable models improves diagnostic accuracy of the PHQ-9.
Given the comprehensive data collected, DEPRESSD builds a strong evidence based for depression screening. Results from DEPRESSD have been published in top-tier journals like the BMJ, JAMA, Psychological Medicine and others.
- New publication: Latent variable scoring of the PHQ-9
- Comparison of different scoring methods based on latent variable models of the PHQ-9: an individual participant data meta-analysis
- Accuracy of the PHQ-2 Alone and in Combination with the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis
- Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis
- Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale – Depression subscale scores: An individual participant data meta-analysis of 73 primary