Anne M Brafford, Brendon Ellis, Greg Guldner, Gabrielle Riazi, Xitao Liu, Jessica C Wells, Jason T Siegel
{"title":"关于住院医师参与度、抑郁、倦怠和住院意向相关因素的多波研究。","authors":"Anne M Brafford, Brendon Ellis, Greg Guldner, Gabrielle Riazi, Xitao Liu, Jessica C Wells, Jason T Siegel","doi":"10.36518/2689-0216.1837","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Many studies have documented the epidemic of mental ill-being among resident physicians, but fewer have focused on mental well-being or on guiding intervention design to make progress toward positive change in residency programs to support resident thriving. Informed by the job demands-resources model (JD-R) and positive psychology, the current study examines 4 potential predictors of residents' ill-being (burnout, depression) and well-being (engagement, stay intent) that are malleable and thus capable of change through intervention: psychological capital (PsyCap), supervising physicians' autonomy-supportive leadership style (ASL), social support, and meaningful work.</p><p><strong>Methods: </strong>Three waves of data were collected between November 2017 and September 2018 at a large hospital system in the United States. Due to participant response rates, we were unable to conduct a planned longitudinal analysis. Therefore, for each wave, Bayesian regression analyses were used to examine cross-sectional relationships between the 4 predictors and each outcome.</p><p><strong>Results: </strong>Although findings varied across the study's 3 waves, the outcomes were largely as expected. With only 1 exception (depressive symptoms in Wave 2), meaningful work significantly predicted all outcome variables in the expected direction across all 3 waves. PsyCap significantly predicted burnout, depressive symptoms, and engagement in the expected direction across all 3 waves. ASL significantly predicted engagement in the expected direction across all 3 waves, as well as depressive symptoms and stay intent in 2 waves, and burnout in 1 wave. Social support significantly negatively predicted depressive symptoms in all 3 waves and burnout in 1 wave.</p><p><strong>Conclusion: </strong>Applying the JD-R framework and a positive psychology lens can open new pathways for developing programming to support resident thriving. Meaningful work, PsyCap, ASL, and social support all significantly predicted 1 or more outcomes related to resident thriving (burnout, depression, engagement, stay intent) across all 3 waves. Thus, this study provides theoretical and practical implications for future intervention studies and designing current programming for resident thriving.</p>","PeriodicalId":73198,"journal":{"name":"HCA healthcare journal of medicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11249185/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Multi-Wave Study of Factors Associated With Resident Engagement, Depression, Burnout, and Stay Intent.\",\"authors\":\"Anne M Brafford, Brendon Ellis, Greg Guldner, Gabrielle Riazi, Xitao Liu, Jessica C Wells, Jason T Siegel\",\"doi\":\"10.36518/2689-0216.1837\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Many studies have documented the epidemic of mental ill-being among resident physicians, but fewer have focused on mental well-being or on guiding intervention design to make progress toward positive change in residency programs to support resident thriving. Informed by the job demands-resources model (JD-R) and positive psychology, the current study examines 4 potential predictors of residents' ill-being (burnout, depression) and well-being (engagement, stay intent) that are malleable and thus capable of change through intervention: psychological capital (PsyCap), supervising physicians' autonomy-supportive leadership style (ASL), social support, and meaningful work.</p><p><strong>Methods: </strong>Three waves of data were collected between November 2017 and September 2018 at a large hospital system in the United States. Due to participant response rates, we were unable to conduct a planned longitudinal analysis. Therefore, for each wave, Bayesian regression analyses were used to examine cross-sectional relationships between the 4 predictors and each outcome.</p><p><strong>Results: </strong>Although findings varied across the study's 3 waves, the outcomes were largely as expected. With only 1 exception (depressive symptoms in Wave 2), meaningful work significantly predicted all outcome variables in the expected direction across all 3 waves. PsyCap significantly predicted burnout, depressive symptoms, and engagement in the expected direction across all 3 waves. ASL significantly predicted engagement in the expected direction across all 3 waves, as well as depressive symptoms and stay intent in 2 waves, and burnout in 1 wave. Social support significantly negatively predicted depressive symptoms in all 3 waves and burnout in 1 wave.</p><p><strong>Conclusion: </strong>Applying the JD-R framework and a positive psychology lens can open new pathways for developing programming to support resident thriving. Meaningful work, PsyCap, ASL, and social support all significantly predicted 1 or more outcomes related to resident thriving (burnout, depression, engagement, stay intent) across all 3 waves. Thus, this study provides theoretical and practical implications for future intervention studies and designing current programming for resident thriving.</p>\",\"PeriodicalId\":73198,\"journal\":{\"name\":\"HCA healthcare journal of medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11249185/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HCA healthcare journal of medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36518/2689-0216.1837\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HCA healthcare journal of medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36518/2689-0216.1837","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Wave Study of Factors Associated With Resident Engagement, Depression, Burnout, and Stay Intent.
Background: Many studies have documented the epidemic of mental ill-being among resident physicians, but fewer have focused on mental well-being or on guiding intervention design to make progress toward positive change in residency programs to support resident thriving. Informed by the job demands-resources model (JD-R) and positive psychology, the current study examines 4 potential predictors of residents' ill-being (burnout, depression) and well-being (engagement, stay intent) that are malleable and thus capable of change through intervention: psychological capital (PsyCap), supervising physicians' autonomy-supportive leadership style (ASL), social support, and meaningful work.
Methods: Three waves of data were collected between November 2017 and September 2018 at a large hospital system in the United States. Due to participant response rates, we were unable to conduct a planned longitudinal analysis. Therefore, for each wave, Bayesian regression analyses were used to examine cross-sectional relationships between the 4 predictors and each outcome.
Results: Although findings varied across the study's 3 waves, the outcomes were largely as expected. With only 1 exception (depressive symptoms in Wave 2), meaningful work significantly predicted all outcome variables in the expected direction across all 3 waves. PsyCap significantly predicted burnout, depressive symptoms, and engagement in the expected direction across all 3 waves. ASL significantly predicted engagement in the expected direction across all 3 waves, as well as depressive symptoms and stay intent in 2 waves, and burnout in 1 wave. Social support significantly negatively predicted depressive symptoms in all 3 waves and burnout in 1 wave.
Conclusion: Applying the JD-R framework and a positive psychology lens can open new pathways for developing programming to support resident thriving. Meaningful work, PsyCap, ASL, and social support all significantly predicted 1 or more outcomes related to resident thriving (burnout, depression, engagement, stay intent) across all 3 waves. Thus, this study provides theoretical and practical implications for future intervention studies and designing current programming for resident thriving.