Publications by authors named "Srijan Sen"

72 Publications

Efficacy and Safety of Cannabidiol Plus Standard Care vs Standard Care Alone for the Treatment of Emotional Exhaustion and Burnout Among Frontline Health Care Workers During the COVID-19 Pandemic: A Randomized Clinical Trial.

JAMA Netw Open 2021 08 2;4(8):e2120603. Epub 2021 Aug 2.

Department of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.

Importance: Frontline health care professionals who work with patients with COVID-19 have an increased incidence of burnout symptoms. Cannabidiol (CBD) has anxiolytic and antidepressant properties and may be capable of reducing emotional exhaustion and burnout symptoms.

Objective: To investigate the safety and efficacy of CBD therapy for the reduction of emotional exhaustion and burnout symptoms among frontline health care professionals working with patients with COVID-19.

Design, Setting, And Participants: This prospective open-label single-site randomized clinical trial used a 1:1 block randomization design to examine emotional exhaustion and burnout symptoms among frontline health care professionals (physicians, nurses, and physical therapists) working with patients with COVID-19 at the Ribeirão Preto Medical School University Hospital in São Paulo, Brazil. Participants were enrolled between June 12 and November 12, 2020. A total of 214 health care professionals were recruited and assessed for eligibility, and 120 participants were randomized in a 1:1 ratio by a researcher who was not directly involved with data collection.

Interventions: Cannabidiol, 300 mg (150 mg twice per day), plus standard care or standard care alone for 28 days.

Main Outcomes And Measures: The primary outcome was emotional exhaustion and burnout symptoms, which were assessed for 28 days using the emotional exhaustion subscale of the Brazilian version of the Maslach Burnout Inventory-Human Services Survey for Medical Personnel.

Results: A total of 120 participants were randomized to receive either CBD, 300 mg, plus standard care (treatment arm; n = 61) or standard care alone (control arm; n = 59) for 28 days. Of those, 118 participants (59 participants in each arm; 79 women [66.9%]; mean age, 33.6 years [95% CI, 32.3-34.9 years]) received the intervention and were included in the efficacy analysis. In the treatment arm, scores on the emotional exhaustion subscale of the Maslach Burnout Inventory significantly decreased at day 14 (mean difference, 4.14 points; 95% CI, 1.47-6.80 points; partial eta squared [ηp2] = 0.08), day 21 (mean difference, 4.34 points; 95% CI, 0.94-7.73 points; ηp2 = 0.05), and day 28 (mean difference, 4.01 points; 95% CI, 0.43-7.59 points; ηp2 = 0.04). However, 5 participants, all of whom were in the treatment group, experienced serious adverse events: 4 cases of elevated liver enzymes (1 critical and 3 mild, with the mild elevations reported at the final 28-day assessment) and 1 case of severe pharmacodermia. In 2 of those cases (1 with critical elevation of liver enzymes and 1 with severe pharmacodermia), CBD therapy was discontinued, and the participants had a full recovery.

Conclusions And Relevance: In this study, CBD therapy reduced symptoms of burnout and emotional exhaustion among health care professionals working with patients during the COVID-19 pandemic. However, it is necessary to balance the benefits of CBD therapy with potential undesired or adverse effects. Future double-blind placebo-controlled clinical trials are needed to confirm the present findings.

Trial Registration: ClinicalTrials.gov Identifier: NCT04504877.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.20603DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363917PMC
August 2021

Genomic heterogeneity affects the response to Daylight Saving Time.

Sci Rep 2021 Jul 20;11(1):14792. Epub 2021 Jul 20.

Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, 48109, USA.

Circadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual's ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well.
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http://dx.doi.org/10.1038/s41598-021-94459-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292316PMC
July 2021

A preliminary study on the relationship between sleep, depression and cardiovascular dysfunction in a 4 sample population.

Int J Cardiol Heart Vasc 2021 Aug 25;35:100814. Epub 2021 Jun 25.

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Background: Major Depressive Disorder (MDD) has been linked in the literature to poorer prognosis in patients with cardiovascular dysfunction, although the mechanisms of this relationship remain unclear. Underlying Sleep Disordered Breathing (SDB) serves as a potential candidate to explain this effect due to its downstream effects on inflammatory activation and decreased nitric oxide (NO) bioavailability, both of which have been shown to contribute to the pathophysiology of both MDD and cardiovascular disease (CVD).

Methods: This study utilizes overnight polysomnography and an inflammation panel to examine the links between cardiovascular dysfunction and sleep difficulties in control participants and patients diagnosed with SDB only, MDD only, and both SDB and MDD.

Results: Results demonstrate a strong positive relationship between sleep dysfunction and the nitric oxide synthesis inhibitor Symmetric Dimethyl Arginine (SDMA) in the MDD-only cohort, suggesting a link between SDMA-mediated NO dysregulation and CVD pathogenesis in individuals with MDD. Additionally, hypopneas, a form of sleep impairment characterized by partial reduction of airflow, were found to play a significant role in the relationship between SDB and cardiovascular dysfunction in MDD-only patients.

Conclusions: Results of this study demonstrate the need for widespread screening for SDB in MDD populations to detect predisposition to CVD, and also offer SDMA as a new potential target for CVD treatment in individuals with MDD.
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http://dx.doi.org/10.1016/j.ijcha.2021.100814DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253961PMC
August 2021

A preliminary study on the relationship between sleep, depression and cardiovascular dysfunction in a 4 sample population.

Int J Cardiol Heart Vasc 2021 Aug 25;35:100814. Epub 2021 Jun 25.

Department of Psychology, University of Michigan, Ann Arbor, MI, USA.

Background: Major Depressive Disorder (MDD) has been linked in the literature to poorer prognosis in patients with cardiovascular dysfunction, although the mechanisms of this relationship remain unclear. Underlying Sleep Disordered Breathing (SDB) serves as a potential candidate to explain this effect due to its downstream effects on inflammatory activation and decreased nitric oxide (NO) bioavailability, both of which have been shown to contribute to the pathophysiology of both MDD and cardiovascular disease (CVD).

Methods: This study utilizes overnight polysomnography and an inflammation panel to examine the links between cardiovascular dysfunction and sleep difficulties in control participants and patients diagnosed with SDB only, MDD only, and both SDB and MDD.

Results: Results demonstrate a strong positive relationship between sleep dysfunction and the nitric oxide synthesis inhibitor Symmetric Dimethyl Arginine (SDMA) in the MDD-only cohort, suggesting a link between SDMA-mediated NO dysregulation and CVD pathogenesis in individuals with MDD. Additionally, hypopneas, a form of sleep impairment characterized by partial reduction of airflow, were found to play a significant role in the relationship between SDB and cardiovascular dysfunction in MDD-only patients.

Conclusions: Results of this study demonstrate the need for widespread screening for SDB in MDD populations to detect predisposition to CVD, and also offer SDMA as a new potential target for CVD treatment in individuals with MDD.
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http://dx.doi.org/10.1016/j.ijcha.2021.100814DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253961PMC
August 2021

Exposure to Workplace Trauma and Posttraumatic Stress Disorder Among Intern Physicians.

JAMA Netw Open 2021 Jun 1;4(6):e2112837. Epub 2021 Jun 1.

Michigan Neuroscience Institute, University of Michigan, Ann Arbor.

Importance: Physicians are exposed to traumatic events during their work, but the impact and outcomes of these exposures are understudied.

Objective: To determine the prevalence and associations of work-related trauma exposure and posttraumatic stress disorder (PTSD) among a cohort of resident physicians in their internship year of training.

Design, Setting, And Participants: This cohort study involved physicians entering internship at US residency programs nationwide in 2018. Participants completed a baseline survey 1 to 2 months before commencing internship, as well as follow-up surveys at 4 time points during internship. Statistical analysis was performed from April 2020 to January 2021.

Exposures: Twelve months of internship.

Main Outcomes And Measures: Prevalence of work-related trauma and prevalence of PTSD among those who experienced work-related trauma. Trauma exposure and PTSD symptoms were assessed using the Primary Care PTSD Screen for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PC-PTSD-5). Risk factors assessed included depression, anxiety, early family environment, stressful life experiences, medical specialty, hours worked, and concern about medical errors.

Results: Among 1134 interns who completed the PC-PTSD-5 at month 12 of internship, 665 (58.6%) were female and 695 (61.6%) were non-Hispanic White; the mean (SD) age was 27.52 (2.50) years. There were 640 interns (56.4%) who reported work-related trauma exposure; among these interns with trauma exposure, 123 (19.0%) screened positive for PTSD. Overall, 123 of 1134 training physicians (10.8%) screened positive for PTSD by the end of internship year, as compared with a 12-month PTSD prevalence rate of 3.6% in the general population. Multivariable logistic regression analyses, adjusting for demographic characteristics, indicated that risk factors associated with trauma exposure included non-Hispanic White race/ethnicity (odds ratio [OR], 1.51 [95% CI, 1.14-2.01]; P = .004), more hours worked (OR, 1.01 [95% CI, 1.00-1.03]; P = .03), early family environment (OR, 1.03 [95% CI, 1.01-1.05]; P < .001), and stressful life experiences at baseline (OR, 1.46 [95% CI, 1.06-2.01]; P = .02). Risk factors associated with PTSD were being unmarried (OR, 2.00 [95% CI, 1.07-3.73]; P = .03) and non-Hispanic White (OR, 1.77 [95% CI, 1.01-3.11]; P = .05), concern about medical errors (OR, 1.21 [95% CI, 1.00-1.46]; P = .05), stressful life experiences during internship (OR, 1.43 [95% CI, 1.14-1.81]; P = .002), depression at month 12 of internship (OR, 2.52 [95% CI = 1.36-4.65], P = .003), and anxiety at month 12 of internship (OR, 2.14, [95% CI, 1.13-4.04]; P = .02).

Conclusions And Relevance: This study found that work-related PTSD was 3 times more prevalent among intern physicians than the general population. These findings suggest that effective interventions to reduce trauma exposure and mitigate the effects of trauma are needed.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.12837DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188264PMC
June 2021

Differences in Gender Representation in the Altmetric Top 100.

J Gen Intern Med 2021 May 4. Epub 2021 May 4.

Foundation Medicine, Inc., Cambridge, MA, USA.

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http://dx.doi.org/10.1007/s11606-021-06829-yDOI Listing
May 2021

A Caveat to Using Wearable Sensor Data for COVID-19 Detection: The Role of Behavioral Change after Receipt of Test Results.

medRxiv 2021 Apr 22. Epub 2021 Apr 22.

Recent studies indicate that wearable sensors have the potential to capture subtle within-person changes that signal SARS-CoV-2 infection. However, it remains unclear the extent to which observed discriminative performance is attributable to behavioral change after receiving test results. We conducted a retrospective study in a sample of medical interns who received COVID-19 test results from March to December 2020. Our data confirmed that sensor data were able to differentiate between symptomatic COVID-19 positive and negative individuals with good accuracy (area under the curve (AUC) = 0.75). However, removing post-result data substantially reduced discriminative capacity (0.75 to 0.63; delta= -0.12, p=0.013). Removing data in the symptomatic period prior to receipt of test results did not produce similar reductions in discriminative capacity. These findings suggest a meaningful proportion of the discriminative capacity of wearable sensor data for SARS-CoV-2 infection may be due to behavior change after receiving test results.
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http://dx.doi.org/10.1101/2021.04.17.21255513DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8077587PMC
April 2021

Learning From Others Without Sacrificing Privacy: Simulation Comparing Centralized and Federated Machine Learning on Mobile Health Data.

JMIR Mhealth Uhealth 2021 03 30;9(3):e23728. Epub 2021 Mar 30.

Department of Statistics, University of Michigan, Ann Arbor, MI, United States.

Background: The use of wearables facilitates data collection at a previously unobtainable scale, enabling the construction of complex predictive models with the potential to improve health. However, the highly personal nature of these data requires strong privacy protection against data breaches and the use of data in a way that users do not intend. One method to protect user privacy while taking advantage of sharing data across users is federated learning, a technique that allows a machine learning model to be trained using data from all users while only storing a user's data on that user's device. By keeping data on users' devices, federated learning protects users' private data from data leaks and breaches on the researcher's central server and provides users with more control over how and when their data are used. However, there are few rigorous studies on the effectiveness of federated learning in the mobile health (mHealth) domain.

Objective: We review federated learning and assess whether it can be useful in the mHealth field, especially for addressing common mHealth challenges such as privacy concerns and user heterogeneity. The aims of this study are to describe federated learning in an mHealth context, apply a simulation of federated learning to an mHealth data set, and compare the performance of federated learning with the performance of other predictive models.

Methods: We applied a simulation of federated learning to predict the affective state of 15 subjects using physiological and motion data collected from a chest-worn device for approximately 36 minutes. We compared the results from this federated model with those from a centralized or server model and with the results from training individual models for each subject.

Results: In a 3-class classification problem using physiological and motion data to predict whether the subject was undertaking a neutral, amusing, or stressful task, the federated model achieved 92.8% accuracy on average, the server model achieved 93.2% accuracy on average, and the individual model achieved 90.2% accuracy on average.

Conclusions: Our findings support the potential for using federated learning in mHealth. The results showed that the federated model performed better than a model trained separately on each individual and nearly as well as the server model. As federated learning offers more privacy than a server model, it may be a valuable option for designing sensitive data collection methods.
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http://dx.doi.org/10.2196/23728DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044739PMC
March 2021

Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians.

NPJ Digit Med 2021 Feb 18;4(1):28. Epub 2021 Feb 18.

Department of Neurology, University of Michigan, Ann Arbor, MI, USA.

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 r = 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.
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http://dx.doi.org/10.1038/s41746-021-00400-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892862PMC
February 2021

Opinion: A risk-benefit framework for human research during the COVID-19 pandemic.

Proc Natl Acad Sci U S A 2020 11 21;117(45):27749-27753. Epub 2020 Oct 21.

Office of the Vice President for Research, University of Michigan, Ann Arbor, MI 48104;

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http://dx.doi.org/10.1073/pnas.2020507117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668055PMC
November 2020

Opinion: A risk-benefit framework for human research during the COVID-19 pandemic.

Proc Natl Acad Sci U S A 2020 11 21;117(45):27749-27753. Epub 2020 Oct 21.

Office of the Vice President for Research, University of Michigan, Ann Arbor, MI 48104;

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http://dx.doi.org/10.1073/pnas.2020507117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668055PMC
November 2020

Promoting Health and Well-Being Through Mobile Health Technology (Roadmap 2.0) in Family Caregivers and Patients Undergoing Hematopoietic Stem Cell Transplantation: Protocol for the Development of a Mobile Randomized Controlled Trial.

JMIR Res Protoc 2020 Sep 18;9(9):e19288. Epub 2020 Sep 18.

Department of Pediatrics, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States.

Background: Cancer patients who undergo allogeneic hematopoietic stem cell transplantation are among the most medically fragile patient populations with extreme demands for caregivers. Indeed, with earlier hospital discharges, the demands placed on caregivers continue to intensify. Moreover, an increased number of allogeneic hematopoietic stem cell transplantations are being performed worldwide, and this expensive procedure has significant economic consequences. Thus, the health and well-being of family caregivers have attracted widespread attention. Mobile health technology has been shown to deliver flexible, and time- and cost-sparing interventions to support family caregivers across the care trajectory.

Objective: This protocol aims to leverage technology to deliver a novel caregiver-facing mobile health intervention named Roadmap 2.0. We will evaluate the effectiveness of Roadmap 2.0 in family caregivers of patients undergoing hematopoietic stem cell transplantation.

Methods: The Roadmap 2.0 intervention will consist of a mobile randomized trial comparing a positive psychology intervention arm with a control arm in family caregiver-patient dyads. The primary outcome will be caregiver health-related quality of life, as assessed by the PROMIS Global Health scale at day 120 post-transplant. Secondary outcomes will include other PROMIS caregiver- and patient-reported outcomes, including companionship, self-efficacy for managing symptoms, self-efficacy for managing daily activities, positive affect and well-being, sleep disturbance, depression, and anxiety. Semistructured qualitative interviews will be conducted among participants at the completion of the study. We will also measure objective physiological markers (eg, sleep, activity, heart rate) through wearable wrist sensors and health care utilization data through electronic health records.

Results: We plan to enroll 166 family caregiver-patient dyads for the full data analysis. The study has received Institutional Review Board approval as well as Code Review and Information Assurance approval from our health information technology services. Owing to the COVID-19 pandemic, the study has been briefly put on hold. However, recruitment began in August 2020. We have converted all recruitment, enrollment, and onboarding processes to be conducted remotely through video telehealth. Consent will be obtained electronically through the Roadmap 2.0 app.

Conclusions: This mobile randomized trial will determine if positive psychology-based activities delivered through mobile health technology can improve caregiver health-related quality of life over a 16-week study period. This study will provide additional data on the effects of wearable wrist sensors on caregiver and patient self-report outcomes.

Trial Registration: ClinicalTrials.gov NCT04094844; https://www.clinicaltrials.gov/ct2/show/NCT04094844.

International Registered Report Identifier (irrid): PRR1-10.2196/19288.
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http://dx.doi.org/10.2196/19288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532463PMC
September 2020

Assessment of Disclosure of Psychological Disability Among US Medical Students.

JAMA Netw Open 2020 07 1;3(7):e2011165. Epub 2020 Jul 1.

Michigan Neuroscience Institute, The University of Michigan Medical School, Ann Arbor.

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http://dx.doi.org/10.1001/jamanetworkopen.2020.11165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378748PMC
July 2020

A randomized controlled trial of digital cognitive behavioral therapy for insomnia in pregnant women.

Sleep Med 2020 08 21;72:82-92. Epub 2020 Mar 21.

Thomas Roth Sleep Disorders & Research Center, Henry Ford Health System, Detroit, MI, USA.

Objective: Despite high rates of prenatal insomnia, efficacious treatment options for this population are quite limited. Early evidence from randomized controlled trials (RCTs) support the efficacy of face-to-face cognitive-behavioral therapy for insomnia (CBTI) for prenatal insomnia. Yet, as many patients are unable to access this specialist-driven care, a critical need exists to increase its accessibility. This RCT examined the efficacy internet-based digital CBTI in pregnant women with insomnia.

Methods: Single-site RCT. A total of 91 pregnant women (29.03 ± 4.16 years) nearing/entering the third trimester who screened positive for clinical insomnia on the Insomnia Severity Index (ISI) were randomized to digital CBTI or digital sleep education control. The ISI, Pittsburgh Sleep Quality Index (PSQI), Edinburgh Postnatal Depression Scale (EPDS), and Pre-Sleep Arousal Scale's Cognitive factor (PSAS-C) served as study outcomes, which were collected before treatment and after treatment during pregnancy, then six weeks after childbirth.

Results: From pre to posttreatment, CBTI patients reported reductions in ISI (-4.91 points, p < 0.001) and PSQI (-2.98 points, p < 0.001) and increases in nightly sleep duration by 32 min (p = 0.008). Sleep symptoms did not change during pregnancy in the control group. After childbirth, CBTI patients, relative to controls, slept longer by 40 min per night (p = 0.01) and reported better sleep maintenance. No pre or postnatal treatment effects on depression or cognitive arousal were observed.

Conclusions: Digital CBTI improves sleep quality and sleep duration during pregnancy and after childbirth. To better optimize outcomes, CBTI should be tailored to meet the changing needs of women as the progress through pregnancy and early parenting. NAME: Insomnia and Rumination in Late Pregnancy and the Risk for Postpartum Depression. URL: clinicaltrials.gov. Registration: NCT03596879.
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http://dx.doi.org/10.1016/j.sleep.2020.03.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8210706PMC
August 2020

Relationship Between Faculty Characteristics and Emotional Exhaustion in a Large Academic Medical Center.

J Occup Environ Med 2020 08;62(8):611-617

Department of Psychiatry (Dr Zivin, Dr Brower, Ms Brownlee); Center for Clinical Management Research, Departments of Veterans Affairs and Obstetrics and Gynecology (Dr Zivin); Department of Psychiatry and Molecular and Behavioral Neuroscience Institute (Dr Sen); Departments of Family Medicine and Obstetrics and Gynecology (Dr Gold), University of Michigan Medical School, Ann Arbor, Michigan.

Objective: We evaluated associations between emotional exhaustion (EE), a measure of burnout, among medical school faculty and: demographic and professional characteristics, workplace stressors, coping skills, resilience, sufficient personal time, and depressive symptoms. Respondents completed surveys in November 2017.

Methods: We conducted bivariate and multivariable logistic regression and recycled predictions models to estimate associations between characteristics and probability of EE.

Results: Of 1401 respondents, 42% endorsed EE. Faculty with more clinical effort, more workplace stress, less resilience, less personal time, and more depressive symptoms reported statistically significantly higher probabilities of EE compared with their counterparts. Female sex, mid-career stage, and coping skills were no longer associated with EE, after accounting for stress, resilience, personal time, and depressive symptoms.

Conclusions: Coping skills may not mitigate physician EE when coupled with substantial time and mental health burdens.
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http://dx.doi.org/10.1097/JOM.0000000000001898DOI Listing
August 2020

Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial.

J Med Internet Res 2020 03 31;22(3):e15033. Epub 2020 Mar 31.

Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States.

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.
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http://dx.doi.org/10.2196/15033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7157494PMC
March 2020

Poor sleep is a health crisis for physicians and nurses.

Sleep Med 2020 03 15;67:256-257. Epub 2020 Jan 15.

Thomas Roth Sleep Disorders & Research Center, Henry Ford Health System, Detroit, MI, USA.

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http://dx.doi.org/10.1016/j.sleep.2020.01.004DOI Listing
March 2020

Substantial Overlap Between Factors Predicting Symptoms of Depression and Burnout Among Medical Interns.

J Gen Intern Med 2021 01 5;36(1):240-242. Epub 2020 Feb 5.

Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.

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http://dx.doi.org/10.1007/s11606-020-05664-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859012PMC
January 2021

Political events and mood among young physicians: a prospective cohort study.

BMJ 2019 12 9;367:l6322. Epub 2019 Dec 9.

Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.

Objective: To study the effects of recent political events on mood among young physicians.

Design: Prospective cohort study.

Setting: United States medical centres.

Participants: 2345 medical interns provided longitudinal mood data as part of the Intern Health Study between 2016 and 2018.

Main Outcome Measures: Mean mood score during the week following influential political and non-political events as compared with mean mood during the preceding four week control period.

Results: We identified nine political events and eight non-political events for analysis. With the start of internship duties in July, the mean decline in mood for interns was -0.30 (95% confidence interval -0.33 to -0.27, t=-17.45, P<0.001). The decline in mood was of similar magnitude following the 2016 presidential election (mean mood change -0.32, 95% confidence interval -0.45 to -0.19, t=-4.73, P<0.001) and subsequent inauguration (mean mood change -0.25, 95% confidence interval -0.37 to -0.12, t=-3.93, P<0.001). Further, compared with men, women reported greater mood declines after both the 2016 election (mean gender difference 0.31, 95% confidence interval 0.05 to 0.58, t=2.33, P=0.02) and the inauguration (mean gender difference 0.25, 95% confidence interval 0.01 to 0.49, t=2.05, P=0.04). Overall, there were statistically significant changes in mood following 66.7% (6/9) of political events assessed. In contrast, none of the non-political events included in the analysis were statistically significantly associated with a change in mood.

Conclusions: Macro level factors such as politics may be correlated with the mood of young doctors. This finding signals the need for further evaluation of the consequences of increasing entanglement between politics and medicine moving forward for young physicians and their patients.
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http://dx.doi.org/10.1136/bmj.l6322DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190044PMC
December 2019

Racial and Ethnic Diversity and Depression in Residency Programs: a Prospective Cohort Study.

J Gen Intern Med 2020 04 3;35(4):1325-1327. Epub 2019 Dec 3.

Molecular & Behavioral Neuroscience Institute, Michigan Medicine, 205 Zina Pitcher Pl, Ann Arbor, MI, 48109-5720, USA.

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http://dx.doi.org/10.1007/s11606-019-05570-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174529PMC
April 2020

Association Between Physician Depressive Symptoms and Medical Errors: A Systematic Review and Meta-analysis.

JAMA Netw Open 2019 11 1;2(11):e1916097. Epub 2019 Nov 1.

Department of Psychiatry, University of Michigan Medical School, Ann Arbor.

Importance: Depression is highly prevalent among physicians and has been associated with increased risk of medical errors. However, questions regarding the magnitude and temporal direction of these associations remain open in recent literature.

Objective: To provide summary relative risk (RR) estimates for the associations between physician depressive symptoms and medical errors.

Data Sources: A systematic search of Embase, ERIC, PubMed, PsycINFO, Scopus, and Web of Science was performed from database inception to December 31, 2018.

Study Selection: Peer-reviewed empirical studies that reported on a valid measure of physician depressive symptoms associated with perceived or observed medical errors were included. No language restrictions were applied.

Data Extraction And Synthesis: Study characteristics and RR estimates were extracted from each article. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using subgroup meta-analysis and metaregression. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed.

Main Outcomes And Measures: Relative risk estimates for the associations between physician depressive symptoms and medical errors.

Results: In total, 11 studies involving 21 517 physicians were included. Data were extracted from 7 longitudinal studies (64%; with 5595 individuals) and 4 cross-sectional studies (36%; with 15 922 individuals). The overall RR for medical errors among physicians with a positive screening for depression was 1.95 (95% CI, 1.63-2.33), with high heterogeneity across the studies (χ2 = 49.91; P < .001; I2 = 82%; τ2 = 0.06). Among the variables assessed, study design explained the most heterogeneity across studies, with lower RR estimates associated with medical errors in longitudinal studies (RR, 1.62; 95% CI, 1.43-1.84; χ2 = 5.77; P = .33; I2 = 13%; τ2 < 0.01) and higher RR estimates in cross-sectional studies (RR, 2.51; 95% CI, 2.20-2.83; χ2 = 5.44; P = .14; I2 = 45%; τ2 < 0.01). Similar to the results for the meta-analysis of physician depressive symptoms associated with subsequent medical errors, the meta-analysis of 4 longitudinal studies (involving 4462 individuals) found that medical errors associated with subsequent depressive symptoms had a pooled RR of 1.67 (95% CI, 1.48-1.87; χ2 = 1.85; P = .60; I2 = 0%; τ2 = 0), suggesting that the association between physician depressive symptoms and medical errors is bidirectional.

Conclusions And Relevance: Results of this study suggest that physicians with a positive screening for depressive symptoms are at higher risk for medical errors. Further research is needed to evaluate whether interventions to reduce physician depressive symptoms could play a role in mitigating medical errors and thus improving physician well-being and patient care.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.16097DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6902829PMC
November 2019

Genomic prediction of depression risk and resilience under stress.

Nat Hum Behav 2020 01 28;4(1):111-118. Epub 2019 Oct 28.

Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.

Advancing ability to predict who is likely to develop depression holds great potential in reducing the disease burden. Here, we use the predictable and large increase in depression with physician training stress to identify predictors of depression. Applying the major depressive disorder polygenic risk score (MDD-PRS) derived from the most recent Psychiatric Genomics Consortium-UK Biobank-23andMe genome-wide association study to 5,227 training physicians, we found that MDD-PRS predicted depression under training stress (β = 0.095, P = 4.7 × 10) and that MDD-PRS was more strongly associated with depression under stress than at baseline (MDD-PRS × stress interaction β = 0.036, P = 0.005). Further, known risk factors accounted for substantially less of the association between MDD-PRS and depression when under stress than at baseline, suggesting that MDD-PRS adds unique predictive power in depression prediction. Finally, we found that low MDD-PRS may have particular use in identifying individuals with high resilience. Together, these findings suggest that MDD-PRS holds promise in furthering our ability to predict vulnerability and resilience under stress.
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http://dx.doi.org/10.1038/s41562-019-0759-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980948PMC
January 2020

Gender Disparities in Work and Parental Status Among Early Career Physicians.

JAMA Netw Open 2019 08 2;2(8):e198340. Epub 2019 Aug 2.

Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston.

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http://dx.doi.org/10.1001/jamanetworkopen.2019.8340DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6681644PMC
August 2019

Physician-Training Stress and Accelerated Cellular Aging.

Biol Psychiatry 2019 11 9;86(9):725-730. Epub 2019 May 9.

Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan; Department of Psychiatry, University of Michigan, Ann Arbor, Michigan. Electronic address:

Background: Stress is a key precipitant for many common diseases, but established biological markers to track stress and guide investigations into mechanisms linking stress and disease are lacking. Cross-sectional studies have identified correlations between stress and telomere attrition, but no large, longitudinal studies examining the impacts of chronic stress on telomere length exist. Residency training for physicians is a well-established stressful experience and can be used as a prospective stress model.

Methods: In a longitudinal cohort study of 250 interns (first-year residents) at 55 United States hospital systems serving during the 2015-2016 academic year, we examined associations between measures of the residency experience and saliva-measured telomere attrition.

Results: Telomere length shortened significantly over the course of internship year, from mean ± SD of 6465.1 ± 876.8 base pairs before internship to 6321.5 ± 630.6 base pairs at the end of internship (t = 2.69; p = .008). Stressful early family environments and neuroticism were significantly associated with shorter preinternship telomere length. Longer work hours were associated with greater telomere intern telomere loss over the year (p = .002). Of note, the mean telomere attrition during internship year was six times greater than the typical annual attrition rate identified in a recent meta-analysis.

Conclusions: This work implicates telomere attrition as a biologically measurable consequence of physician training, with the magnitude of attrition associated with workload. Identification of an objective, biological sequela of residency stress may help to facilitate the development of effective interventions. Further, the findings implicate telomere attrition as an objective biomarker to follow the pathologic effects of stress, in general.
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http://dx.doi.org/10.1016/j.biopsych.2019.04.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6788968PMC
November 2019

Physician-Training Stress and Accelerated Cellular Aging.

Biol Psychiatry 2019 11 9;86(9):725-730. Epub 2019 May 9.

Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan; Department of Psychiatry, University of Michigan, Ann Arbor, Michigan. Electronic address:

Background: Stress is a key precipitant for many common diseases, but established biological markers to track stress and guide investigations into mechanisms linking stress and disease are lacking. Cross-sectional studies have identified correlations between stress and telomere attrition, but no large, longitudinal studies examining the impacts of chronic stress on telomere length exist. Residency training for physicians is a well-established stressful experience and can be used as a prospective stress model.

Methods: In a longitudinal cohort study of 250 interns (first-year residents) at 55 United States hospital systems serving during the 2015-2016 academic year, we examined associations between measures of the residency experience and saliva-measured telomere attrition.

Results: Telomere length shortened significantly over the course of internship year, from mean ± SD of 6465.1 ± 876.8 base pairs before internship to 6321.5 ± 630.6 base pairs at the end of internship (t = 2.69; p = .008). Stressful early family environments and neuroticism were significantly associated with shorter preinternship telomere length. Longer work hours were associated with greater telomere intern telomere loss over the year (p = .002). Of note, the mean telomere attrition during internship year was six times greater than the typical annual attrition rate identified in a recent meta-analysis.

Conclusions: This work implicates telomere attrition as a biologically measurable consequence of physician training, with the magnitude of attrition associated with workload. Identification of an objective, biological sequela of residency stress may help to facilitate the development of effective interventions. Further, the findings implicate telomere attrition as an objective biomarker to follow the pathologic effects of stress, in general.
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http://dx.doi.org/10.1016/j.biopsych.2019.04.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6788968PMC
November 2019

Cognitive Control as a 5-HT-Based Domain That Is Disrupted in Major Depressive Disorder.

Front Psychol 2019 29;10:691. Epub 2019 Mar 29.

The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States.

Heterogeneity within Major Depressive Disorder (MDD) has hampered identification of biological markers (e.g., intermediate phenotypes, IPs) that might increase risk for the disorder or reflect closer links to the genes underlying the disease process. The newer characterizations of dimensions of MDD within Research Domain Criteria (RDoC) domains may align well with the goal of defining IPs. We compare a sample of 25 individuals with MDD compared to 29 age and education matched controls in multimodal assessment. The multimodal RDoC assessment included the primary IP biomarker, positron emission tomography (PET) with a selective radiotracer for 5-HT [(11C)WAY-100635], as well as event-related functional MRI with a Go/No-go task targeting the Cognitive Control network, neuropsychological assessment of affective perception, negative memory bias and Cognitive Control domains. There was also an exploratory genetic analysis with the serotonin transporter (5-HTTLPR) and monamine oxidase A (MAO-A) genes. In regression analyses, lower 5-HT binding potential (BP) in the MDD group was related to diminished engagement of the Cognitive Control network, slowed resolution of interfering cognitive stimuli, one element of Cognitive Control. In contrast, higher/normative levels of 5-HT BP in MDD (only) was related to a substantial memory bias toward negative information, but intact resolution of interfering cognitive stimuli and greater engagement of Cognitive Control circuitry. The serotonin transporter risk allele was associated with lower 1a BP and the corresponding imaging and cognitive IPs in MDD. Lowered 5HT 1a BP was present in half of the MDD group relative to the control group. Lowered 5HT 1a BP may represent a subtype including decreased engagement of Cognitive Control network and impaired resolution of interfering cognitive stimuli. Future investigations might link lowered 1a BP to neurobiological pathways and markers, as well as probing subtype-specific treatment targets.
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http://dx.doi.org/10.3389/fpsyg.2019.00691DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450211PMC
March 2019

Insomnia symptoms and short sleep predict anxiety and worry in response to stress exposure: a prospective cohort study of medical interns.

Sleep Med 2019 03 14;55:40-47. Epub 2018 Dec 14.

Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, USA. Electronic address:

Study Objectives: While anxiety rates are alarmingly high in short sleeping insomniacs, the relationship between insomnia and anxiety symptoms has not been extensively studied, especially in comparison to the relationship between insomnia and depressive symptoms. Using residency training as a naturalistic stress exposure, we prospectively assessed the role of sleep disturbance and duration on anxiety-risk in response to stress.

Methods: Web-based survey data from 1336 first-year training physicians (interns) prior to and then quarterly across medical internship. Using mixed effects modeling, we examined how pre-internship sleep disturbance and internship sleep duration predicted symptoms of anxiety, using an established tool for quantifying symptom severity in generalized anxiety disorder (GAD).

Results: Pre-internship poor sleepers are at more than twice the odds of having short sleep (≤6 h) during internship as good sleepers (OR = 2.38, 95% CI = 1.61, 3.57). Poor sleepers were also at twice the odds for screening positive for probable GAD diagnosis (OR = 2.08, 95% CI = 1.26, 3.45). Notably, sleep onset insomnia strongly predicted anxiety development under stress (OR = 3.55, 95% CI = 1.49, 8.45). During internship, short sleep associated with concurrent anxiety symptoms (b = -0.26, 95% CI = -0.38, -0.14) and predicted future anxiety symptoms even more strongly (b = -0.39, 95% CI = -0.76, -0.03).

Conclusions: Poor sleepers, particularly those with sleep onset insomnia symptoms, are vulnerable to short sleep and GAD anxiety and worry during chronic stress.
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http://dx.doi.org/10.1016/j.sleep.2018.12.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7045299PMC
March 2019

Residency Program Factors Associated With Depressive Symptoms in Internal Medicine Interns: A Prospective Cohort Study.

Acad Med 2019 06;94(6):869-875

K. Pereira-Lima is a research scholar, Department of Psychiatry, University of Michigan Medical School, Ann Arbor, Michigan, and PhD candidate, Department of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. R.R. Gupta is an MD candidate, University of Michigan Medical School, Ann Arbor, Michigan. C. Guille is assistant professor, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina. S. Sen is research associate professor, Molecular and Behavioral Neuroscience Institute, and associate professor, Department of Psychiatry, University of Michigan Medical School, Ann Arbor, Michigan.

Purpose: To investigate the associations between program-level variables such as organizational structure, workload, and learning environment and residents' development of depressive symptoms during internship.

Method: Between 2012 and 2015, 1,276 internal medicine interns from 54 U.S. residency programs completed the Patient Health Questionnaire-9 (PHQ-9) before internship, and then quarterly throughout the internship. The training environment was assessed via a resident questionnaire and average weekly work hours. The authors gathered program structural variables from the American Medical Association Fellowship and Residency Electronic Interactive Database (FREIDA online) and program research rankings from Doximity. Associations between program-level variables and change in depressive symptoms were determined using stepwise linear regression modeling.

Results: Mean program PHQ-9 scores increased from 2.3 at baseline to 5.9 during internship (mean difference 3.6; SD 1.4; P < .001), with the mean increase ranging from -0.3 to 8.8 (interquartile range 1.1) among included programs. In multivariable models, faculty feedback (β = -0.37; 95% CI: -0.62, -0.12; P = .005), learning experience in inpatient rotations (β = -0.28; 95% CI: -0.54, -0.02; P = .030), work hours (β = 0.34; 95% CI: 0.13, 0.56; P = .002), and research ranking position (β = -0.25; 95% CI: -0.47, -0.03; P = .036) were associated with change in depressive symptoms.

Conclusions: Poor faculty feedback and inpatient learning experience, long work hours, and high institutional research rankings were associated with increased depressive symptoms among internal medicine interns. These factors may be potential targets for interventions to improve wellness and mental health among these professionals.
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http://dx.doi.org/10.1097/ACM.0000000000002567DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538448PMC
June 2019
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