Implications of the choice of method to identify major depressive disorder in large research cohorts

Our results demonstrate how the methods used to identify patients with history of MDD can affect sample characteristics and risk factor associations, highlighting the importance of considering phenotype ascertainment in the interpretation of research results.

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Publication Details

Journal
Journal of Mood and Anxiety Disorders
Published
2025-06-19
DOI
https://doi.org/10.1016/j.xjmad.2025.100136
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
0.00

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article

Implications of the choice of method to identify major depressive disorder in large research cohorts

Myrna M. Weissman, Mark Olfson, Lauren Lepow, Braja Gopal Patra et al.
Journal of Mood and Anxiety Disorders
Health Systems, Economic Evaluations, Quality of Life
article

Implications of the choice of method to identify major depressive disorder in large research cohorts

Myrna M. Weissman, Mark Olfson, Lauren Lepow, Braja Gopal Patra, Ardesheer Talati, Jorge A. Sánchez-Ruiz, Brandon J. Coombes, Joanna M. Biernacka, Jyotishman Pathak, Euijung Ryu, J. John Mann, Gregory D. Jenkins, Nicolás A. Núñez, Alexander W. Charney
article en

Abstract

Our results demonstrate how the methods used to identify patients with history of MDD can affect sample characteristics and risk factor associations, highlighting the importance of considering phenotype ascertainment in the interpretation of research results.

Journal of Mood and Anxiety DisordersVol. 11
Mayo Clinic (US), Cornell University (US), University of Utah (US), WinnMed (US), New York Psychoanalytic Society and Institute (US), Mayo Clinic in Florida (US), Weill Cornell Medicine (US), New York State Psychiatric Institute, Columbia University (US), Icahn School of Medicine at Mount Sinai (US)
Mayo Clinic, Regeneron Pharmaceuticals, Center for Individualized Medicine, Mayo Clinic, National Institute of Mental Health
Gender equality
Openalex Percentile: Top 80%
Health Systems, Economic Evaluations, Quality of Life
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