A Prognostic Index to Identify the Risk of Developing Depression Symptoms Among U.S. Medical Students Derived From a National, Four-Year Longitudinal Study

Liselotte N. Dyrbye, Natalie M. Wittlin, Rachel R. Hardeman, Mark Yeazel, Jeph Herrin, John F. Dovidio, Sara E. Burke, Brooke Cunningham, Sean M. Phelan, Tait D. Shanafelt, Michelle van Ryn

Research output: Contribution to journalArticle

Abstract

PURPOSE: To determine baseline individual and school-related factors associated with increased risk of developing depression symptoms by year four (Y4) of medical school, and to develop a prognostic index that stratifies risk of developing depression symptoms (Depression-PI) among medical students. METHOD: The authors analyzed data from 3,743 students (79% of 4,732) attending 49 U.S. medical schools who completed baseline (2010) and Y4 (2014) surveys. Surveys included validated scales measuring depression, stress, coping, and social support. The authors collected demographics and school characteristics and conducted multivariate analysis to identify baseline factors independently associated with Y4 depression symptoms. They used these factors to create a prognostic index for developing depression. They randomly divided the data into discovery (n = 2,455) and replication (n = 1,288) datasets and calculated c statistics (c). RESULTS: The authors identified eight independent prognostic factors for experiencing depression symptoms during training within the discovery dataset: age; race; ethnicity; tuition; and baseline depression symptoms, stress, coping behaviors, and social support. The Depression-PI stratified four risk groups. Compared with the low risk group, those in the intermediate, high, and very high risk groups had an odds ratio of developing depression of, respectively, 1.75, 3.98, and 9.19 (c = 0.71). The replication dataset confirmed the risk groups. CONCLUSIONS: Demographics; tuition; and baseline depression symptoms, stress, coping behaviors, and social support are independently associated with risk of developing depression during training among U.S. medical students. By stratifying students into four risk groups, the Depression-PI may allow for a tiered primary prevention approach.

Original languageEnglish (US)
Pages (from-to)217-226
Number of pages10
JournalAcademic medicine : journal of the Association of American Medical Colleges
Volume94
Issue number2
DOIs
StatePublished - Feb 1 2019

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medical student
longitudinal study
coping behavior
social support
Group
school
multivariate analysis
coping
ethnicity
student
statistics

ASJC Scopus subject areas

  • Education

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A Prognostic Index to Identify the Risk of Developing Depression Symptoms Among U.S. Medical Students Derived From a National, Four-Year Longitudinal Study. / Dyrbye, Liselotte N.; Wittlin, Natalie M.; Hardeman, Rachel R.; Yeazel, Mark; Herrin, Jeph; Dovidio, John F.; Burke, Sara E.; Cunningham, Brooke; Phelan, Sean M.; Shanafelt, Tait D.; van Ryn, Michelle.

In: Academic medicine : journal of the Association of American Medical Colleges, Vol. 94, No. 2, 01.02.2019, p. 217-226.

Research output: Contribution to journalArticle

Dyrbye, Liselotte N. ; Wittlin, Natalie M. ; Hardeman, Rachel R. ; Yeazel, Mark ; Herrin, Jeph ; Dovidio, John F. ; Burke, Sara E. ; Cunningham, Brooke ; Phelan, Sean M. ; Shanafelt, Tait D. ; van Ryn, Michelle. / A Prognostic Index to Identify the Risk of Developing Depression Symptoms Among U.S. Medical Students Derived From a National, Four-Year Longitudinal Study. In: Academic medicine : journal of the Association of American Medical Colleges. 2019 ; Vol. 94, No. 2. pp. 217-226.
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AU - Hardeman, Rachel R.

AU - Yeazel, Mark

AU - Herrin, Jeph

AU - Dovidio, John F.

AU - Burke, Sara E.

AU - Cunningham, Brooke

AU - Phelan, Sean M.

AU - Shanafelt, Tait D.

AU - van Ryn, Michelle

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N2 - PURPOSE: To determine baseline individual and school-related factors associated with increased risk of developing depression symptoms by year four (Y4) of medical school, and to develop a prognostic index that stratifies risk of developing depression symptoms (Depression-PI) among medical students. METHOD: The authors analyzed data from 3,743 students (79% of 4,732) attending 49 U.S. medical schools who completed baseline (2010) and Y4 (2014) surveys. Surveys included validated scales measuring depression, stress, coping, and social support. The authors collected demographics and school characteristics and conducted multivariate analysis to identify baseline factors independently associated with Y4 depression symptoms. They used these factors to create a prognostic index for developing depression. They randomly divided the data into discovery (n = 2,455) and replication (n = 1,288) datasets and calculated c statistics (c). RESULTS: The authors identified eight independent prognostic factors for experiencing depression symptoms during training within the discovery dataset: age; race; ethnicity; tuition; and baseline depression symptoms, stress, coping behaviors, and social support. The Depression-PI stratified four risk groups. Compared with the low risk group, those in the intermediate, high, and very high risk groups had an odds ratio of developing depression of, respectively, 1.75, 3.98, and 9.19 (c = 0.71). The replication dataset confirmed the risk groups. CONCLUSIONS: Demographics; tuition; and baseline depression symptoms, stress, coping behaviors, and social support are independently associated with risk of developing depression during training among U.S. medical students. By stratifying students into four risk groups, the Depression-PI may allow for a tiered primary prevention approach.

AB - PURPOSE: To determine baseline individual and school-related factors associated with increased risk of developing depression symptoms by year four (Y4) of medical school, and to develop a prognostic index that stratifies risk of developing depression symptoms (Depression-PI) among medical students. METHOD: The authors analyzed data from 3,743 students (79% of 4,732) attending 49 U.S. medical schools who completed baseline (2010) and Y4 (2014) surveys. Surveys included validated scales measuring depression, stress, coping, and social support. The authors collected demographics and school characteristics and conducted multivariate analysis to identify baseline factors independently associated with Y4 depression symptoms. They used these factors to create a prognostic index for developing depression. They randomly divided the data into discovery (n = 2,455) and replication (n = 1,288) datasets and calculated c statistics (c). RESULTS: The authors identified eight independent prognostic factors for experiencing depression symptoms during training within the discovery dataset: age; race; ethnicity; tuition; and baseline depression symptoms, stress, coping behaviors, and social support. The Depression-PI stratified four risk groups. Compared with the low risk group, those in the intermediate, high, and very high risk groups had an odds ratio of developing depression of, respectively, 1.75, 3.98, and 9.19 (c = 0.71). The replication dataset confirmed the risk groups. CONCLUSIONS: Demographics; tuition; and baseline depression symptoms, stress, coping behaviors, and social support are independently associated with risk of developing depression during training among U.S. medical students. By stratifying students into four risk groups, the Depression-PI may allow for a tiered primary prevention approach.

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