Social Support, Social Isolation, and Burnout: Cross-Sectional Study of U.S. Residents Exploring Associations With Individual, Interpersonal, Program, and Work-Related Factors.

PURPOSE: To examine associations of social support and social isolation with burnout, program satisfaction, and organization satisfaction among a large population of U.S. residents and fellows and to identify correlates of social support and social isolation. METHOD: All residents and fellows enrolled in graduate medical education programs at Mayo Clinic sites were surveyed in February 2019. Survey items measured social support (emotional and tangible), social isolation, burnout, program satisfaction, and organization satisfaction. Factors of potential relevance to social support were collected (via the survey, institutional administrative records, and interviews with program coordinators and/or program directors) and categorized as individual, interpersonal, program, or work-related factors (duty hours, call burden, elective time, vacation days used before survey administration, required away rotations, etc.). Multivariable regression analyses were conducted to examine relationships between variables. RESULTS: Of 1,146 residents surveyed, 762 (66%) from 58 programs responded. In adjusted models, higher emotional and tangible support were associated with lower odds of burnout and higher odds of program and organization satisfaction, while higher social isolation scores were associated with higher odds of burnout and lower odds of program satisfaction and organization satisfaction. Independent predictors of social support and/or social isolation included age, gender, relationship status, parental status, postgraduate year, site, ratings of the program leadership team, ratings of faculty relationships and faculty professional behaviors, satisfaction with autonomy, and vacation days used before survey administration. CONCLUSIONS: This study demonstrates that social support and social isolation are strongly related to burnout and satisfaction among residents and fellows. Personal and professional relationships, satisfaction with autonomy, and vacation days are independently associated with social support and/or social isolation, whereas most program and work-related factors are not. Additional studies are needed to determine if social support interventions targeting these factors can improve well-being and enhance satisfaction with training.

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants.

BACKGROUND: The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo. METHODS: The study samples included training datasets (N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine (N = 255) or placebo (N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment. RESULTS: Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self-esteem, and depressed feelings) assessed with the Children's Depression Rating Scale-Revised at 4-6 weeks predicted treatment outcomes with fluoxetine at 10-12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10-12 week outcomes at 4-6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo-treated patients with accuracies of 67%. In placebo-treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants. CONCLUSIONS: PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression.

Medical Student Suicide Rates: A Systematic Review of the Historical and International Literature.

PURPOSE: Physician suicide rates are reportedly higher than those of the general population, but medical student suicide rates are not well studied. It is difficult to determine whether physician suicide rates can be predicted by medical student risk factors for suicide and difficult to identify those risk factors without knowing medical student suicide rates. The authors systematically reviewed the literature to collate data on medical student suicide rates. METHOD: The authors searched the PubMed, Web of Science, and Library of Congress databases for papers published in any language before November 11, 2017. They identified 3,429 papers; after the initial screening process, they assessed 82 full-text articles for eligibility. Twelve ultimately met the full inclusion criteria; meta-analysis was not possible. Data regarding medical student suicide numbers and rates were extracted and compared with contemporaneous general population suicide rates using public epidemiological data, when available. RESULTS: Medical student suicide rates were infrequently reported in the historical and international literature, and data collection techniques were inconsistent. Generally, U.S. medical student suicide rates were lower than those of the contemporaneous general population. Proportionate mortality of medical students (number of deaths by a particular cause such as suicide divided by total number of deaths) was not reported in the literature. CONCLUSIONS: Gaps exist in knowledge of medical student suicide rates, risk factors, and targets for intervention. Significant barriers have impeded information collection. Yet, more comprehensive data collection is needed to understand suicide risk in this population and to implement and improve effective intervention strategies.

Psychometric Properties of the Patient Health Questionnaire-9 Modified for Major Depressive Disorder in Adolescents.

OBJECTIVES: The Patient Health Questionnaire-9 Modified (PHQ-9M) is a self-report tool used to assess the presence and severity of depressive symptoms in teenagers. Despite widespread use in primary care clinics and psychiatric settings, the PHQ-9M has not been validated nor are its psychometric properties adequately understood for the adolescent population. This study sought to examine the psychometrics of the PHQ-9M in treatment-seeking, depressed adolescents at a psychiatric psychopharmacology clinic who were concurrently assessed with the Children's Depression Rating Scale Revised (CDRS-R) and Quick Inventory of Depressive Symptomatology-Adolescent (17-item) Self-Report (QIDS-A17-SR). METHODS: Adolescents (N = 160) aged 13 through 18 years with a diagnosis of major depressive disorder, determined on the basis of a clinical interview and semi-structured interview using the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version, were assessed for severity of depressive symptoms with the PHQ-9M, CDRS-R (adolescent interview only), and QIDS-A17-SR assessments at baseline, 4, and 8 weeks. Classical test theory analysis was used to evaluate the internal consistency and dimensionality of the PHQ-9M. Convergent validity was evaluated via intraclass correlations of the PHQ-9M with the CDRS-R and QIDS-A17-SR. Sensitivity to treatment response was also evaluated. RESULTS: The internal consistency (Cronbach's coefficient α) at baseline, 4, and 8 weeks was 0.879, 0.859, and 0.827 for the PHQ-9M; 0.739, 0.835, and 0.867 for CDRS-R; and 0.712, 0.777, and 0.804 for QIDS-A17-SR, respectively. The PHQ-9M had moderate convergent validity with the CDRS-R but good convergent validity with the QIDS-A17-SR. The PHQ-9M was less sensitive to changes in symptom severity than the CDRS-R and QIDS-A17-SR. CONCLUSIONS: The PHQ-9M appears to be a valid and reliable assessment tool for the severity of depressive symptoms in a psychiatric clinic setting. However, its utility as a treatment outcome measure may be limited compared with other available rating scales.

Completed suicide in medical/surgical patients: who is at risk?

Factors contributing to patients killing themselves while admitted to general hospital medical/surgical (med/surg) units have not been well described. These rare yet devastating suicides appear to have characteristics distinguishing them from suicides in psychiatric inpatients. This article emphasizes the importance of both agitation and readily available lethal means in suicides that are almost invariably impulsive. It also emphasizes how traditional risk factors such as past history of psychiatric illness, substance abuse, or suicidality typically are absent in this population, as are present depression and known suicidality. Caregivers seeking to prevent suicide in the med/surg environment therefore must appreciate the potential lethality of acute psychic and motoric agitation. Close surveillance of agitated patients, with interventions to calm them and secure their surroundings, will assure safety and save lives.