Published August 9, 2021
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Gender-specificity of resilience in major depressive disorder
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Abstract
Introduction The major stressors associated with the COVID-19 pandemic provide an opportunity to understand the extent to which protective factors against depression may exhibit gender-specificity. Method This study examined responses from multiple waves of a 50 states non-probability internet survey conducted between May 2020 and January 2021. Participants completed the PHQ-9 as a measure of depression, as well as items characterizing social supports. We used logistic regression models with population reweighting to examine association between absence of even mild depressive symptoms and sociodemographic features and social supports, with interaction terms and stratification used to investigate sex-specificity. Results Among 73,917 survey respondents, 31,199 (42.2%) reported absence of mild or greater depression-11,011/23,682 males (46.5%) and 20,188/50,235 (40.2%) females. In a regression model, features associated with greater likelihood of depression-resistance included at least weekly attendance of religious services (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.16) and greater trust in others (OR: 1.04 for a 2-unit increase, 95% CI: 1.02-1.06), along with level of social support measured as number of social ties available who could provide care (OR: 1.05, 95% CI: 1.02-1.07), talk to them (OR: 1.10, 95% CI: 1.07-1.12), and help with employment (OR: 1.06, 95% CI: 1.04-1.08). The first two features showed significant interaction with gender (p < .0001), with markedly greater protective effects among women. Conclusion Aspects of social support are associated with diminished risk of major depressive symptoms, with greater effects of religious service attendance and trust in others observed among women than men.Other
original_citation: Perlis RH, Ognyanova K, Quintana A, Green J, Santillana M, Lin JN, Druckman J, Lazer D, Simonson MD, Baum MA, Chwe HY. Gender-specificity of resilience in major depressive disorder. Depression and Anxiety. 2021;38(10):1026-1033.Files
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Additional details
Identifiers
- PMID
- 34370885
Related works
- Is related to
- https://onlinelibrary.wiley.com/doi/10.1002/da.23203 (URL)
Funding
- Machine learning for data-driven subtyping of major depression 1R56MH115187
- National Institute of Mental Health
- 1/2 Leveraging electronic health records for pharmacogenomics of psychiatric disorders R01MH116270
- National Institute of Mental Health
- RAPID: Collaborative Research: Relationships, social distancing, social media and the spread of COVID-19 SES-2029292
- National Science Foundation
- RAPID: Collaborative Research: Relationships, social distancing, social media and the spread of COVID-19 SES-2029292
- National Science Foundation
Dates
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2021-08-09When the item was originally created.