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Physician burnout, characterized by emotional exhaustion, depersonalization, and a low sense of personal accomplishment, is associated with career dissatisfaction and early retirement. Dyrbye and colleagues surveyed 4696 second-year resident physicians and found that symptoms of burnout and career choice regret varied by clinical specialty. In an Editorial, Schwenk and Gold suggest that physicians reporting burnout are receiving recommendations for treatments before there is any real understanding of the “diagnosis.”
Editorial and Related Article
The term burnout is used to characterize job-related stress in health practice environments. In a systematic review of 182 studies involving 109 628 participants in 45 countries, Rotenstein and colleagues found substantial variability in the methods of defining and measuring burnout among practicing physicians.
Ossenkoppele and colleagues analyzed imaging data for 719 patients recruited from memory disorder clinics and found that the [18F]flortaucipir positron emission tomography scan was able to discriminate Alzheimer dementia from other neurodegenerative diseases.
Obesity is associated with health problems such as increased risks for coronary heart disease, type 2 diabetes, cancer, gallstones, and disability. This US Preventive Services Task Force statement recommends that adults with a body mass index of 30 or higher receive intensive, multicomponent behavioral interventions for weight loss in primary care settings. In an Editorial, Yanovski suggests that obese patients should receive treatment for related comorbidities regardless of their motivation to lose weight.
Editorial, Related Article, and JAMA Patient Page
Author Audio Interview and CME
In a review of 122 trials with 62 533 participants and 2 observational studies with 209 993 participants, LeBlanc and colleagues found that behavior-based weight loss interventions with or without weight loss medications were associated with more weight loss and a lower risk of developing diabetes than control conditions.
Neural network technology is used to identify pathology in medical images by “learning” from information in prior images. In this JAMA Guide to Statistics and Methods, Carin and Pencina explain how a computer can be trained to recognize complex visual patterns.
Animated Summary Video
Highlights. JAMA. 2018;320(11):1083–1085. doi:10.1001/jama.2017.12548