IMPORTANCE Depression is common among training physicians and may disproportionately affect women. The identification of modifiable risk factors is key to reducing this disease burden and its negative impact on patient care and physician career attrition. OBJECTIVE To determine the presence and magnitude of a sex difference in depressive symptoms and work-family conflict among training physicians; and if work-family conflict impacts the sex difference in depressive symptoms among training physicians. DESIGN, SETTING, AND PARTICIPANTS A prospective longitudinal cohort study of medical internship in the United States during the 2015 to 2016 academic year in which 3121 interns were recruited across all specialties from 44 medical institutions. MAIN OUTCOMES AND MEASURES Prior to and during their internship year, participants reported the degree to which work responsibilities interfered with family life using the Work Family Conflict Scale and depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9). RESULTS Mean (SD) participant age was 27.5 (2.7) years, and 1571 participants (49.7%) were women. Both men and women experienced a marked increase in depressive symptoms during their internship year, with the increase being statistically significantly greater for women (men: mean increase in PHQ-9, 2.50; 95% CI, 2.26-2.73 vs women: mean increase, 3.20; 95% CI, 2.97-3.43). When work-family conflict was accounted for, the sex disparity in the increase in depressive symptoms decreased by 36%. CONCLUSIONS AND RELEVANCE Our study demonstrates that depressive symptoms increase substantially during the internship year for men and women, but that this increase is greater for women. The study also identifies work-family conflict as an important potentially modifiable factor that is associated with elevated depressive symptoms in training physicians. Systemic modifications to alleviate conflict between work and family life may improve physician mental health and reduce the disproportionate depression disease burden for female physicians. Given that depression among physicians is associated with poor patient care and career attrition, efforts to alleviate depression among physicians has the potential to reduce the negative consequences associated with this disease.

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This survey study examines how gender disparities are associated with attrition from the workforce and how family considerations are associated with decisions about how much to work.

IMPORTANCEThe COVID-19 pandemic has placed increased strain on health care workers and disrupted childcare and schooling arrangements in unprecedented ways. As substantial gender inequalities existed in medicine before the pandemic, physician mothers may be at particular risk for adverse professional and psychological consequences. OBJECTIVE To assess gender differences in work-family factors and mental health among physician parents during the COVID-19 pandemic. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 276 US physicians enrolled in the Intern Health Study since their first year of residency training. Physicians who had participated in the primary study as interns during the 2007 to 2008 and 2008 to 2009 academic years and opted into a secondary longitudinal follow-up study were invited to complete an online survey in August 2018 and August 2020. EXPOSURES Work-family experience included 3 single-item questions and the Work and Family Conflict Scale, and mental health symptoms included the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 scale. MAIN OUTCOMES AND MEASURES The primary outcomes were work-to-family and family-towork conflict and depressive symptoms and anxiety symptoms during August 2020. Depressive symptoms between 2018 (before the COVID-19 pandemic) and 2020 (during the COVID-19 pandemic) were compared by gender.RESULTS Among 215 physician parents who completed the August 2020 survey, 114 (53.0%) were female and the weighted mean (SD) age was 40.1 (3.57) years. Among physician parents, women were more likely to be responsible for childcare or schooling (24.6% [95% CI, 19.0%-30.2%] vs 0.8% [95% CI, 0.01%-2.1%]; P < .001) and household tasks (31.4% [95% CI, 25.4%-37.4%] vs 7.2% [95% CI, 3.5%-10.9%]; P < .001) during the pandemic compared with men. Women were also more likely than men to work primarily from home (40.

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While 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = −0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r2 = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = − 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = −0.011, p < 0.001) and in wake time (b = −0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.

Background Individuals in stressful work environments often experience mental health issues, such as depression. Reducing depression rates is difficult because of persistently stressful work environments and inadequate time or resources to access traditional mental health care services. Mobile health (mHealth) interventions provide an opportunity to deliver real-time interventions in the real world. In addition, the delivery times of interventions can be based on real-time data collected with a mobile device. To date, data and analyses informing the timing of delivery of mHealth interventions are generally lacking. Objective This study aimed to investigate when to provide mHealth interventions to individuals in stressful work environments to improve their behavior and mental health. The mHealth interventions targeted 3 categories of behavior: mood, activity, and sleep. The interventions aimed to improve 3 different outcomes: weekly mood (assessed through a daily survey), weekly step count, and weekly sleep time. We explored when these interventions were most effective, based on previous mood, step, and sleep scores. Methods We conducted a 6-month micro-randomized trial on 1565 medical interns. Medical internship, during the first year of physician residency training, is highly stressful, resulting in depression rates several folds higher than those of the general population. Every week, interns were randomly assigned to receive push notifications related to a particular category (mood, activity, sleep, or no notifications). Every day, we collected interns’ daily mood valence, sleep, and step data. We assessed the causal effect moderation by the previous week’s mood, steps, and sleep. Specifically, we examined changes in the effect of notifications containing mood, activity, and sleep messages based on the previous week’s mood, step, and sleep scores. Moderation was assessed with a weighted and centered least-squares estimator. Results We found that the previous week’s mood negatively moderated the effect of notifications on the current week’s mood with an estimated moderation of −0.052 (P=.001). That is, notifications had a better impact on mood when the studied interns had a low mood in the previous week. Similarly, we found that the previous week’s step count negatively moderated the effect of activity notifications on the current week’s step count, with an estimated moderation of −0.039 (P=.01) and that the previous week’s sleep negatively moderated the effect of sleep notifications on the current week’s sleep with an estimated moderation of −0.075 (P<.001). For all three of these moderators, we estimated that the treatment effect was positive (beneficial) when the moderator was low, and negative (harmful) when the moderator was high. Conclusions These findings suggest that an individual’s current state meaningfully influences their receptivity to mHealth interventions for mental health. Timing interventions to match an individual’s state may be critical to maximizing the efficacy of interventions. Trial Registration ClinicalTrials.gov NCT03972293; http://clinicaltrials.gov/ct2/show/NCT03972293

Author Contributions: Drs Meeks and Pereira-Lima had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Meeks and Pereira-Lima contributed equally to the paper and share first author status.