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What gets resident physicians stressed and how would they prefer to be supported? A best–worst scaling study

Abstract

Introduction Physician burnout has severe consequences on clinician well-being. Residents face numerous work-stressors that can contribute to burnout; however, given specialty variation in work-stress, it is difficult to identify systemic stressors and implement effective burnout interventions on an institutional level. Assessing resident preferences by specialty for common wellness interventions could also contribute to improved efficacy.

Methods This cross-sectional study used best–worst scaling (BWS), a type of discrete choice modelling, to explore how 267 residents across nine specialties (anaesthesiology, emergency medicine, internal medicine, neurology, obstetrics and gynaecology, pathology, psychiatry, radiology and surgery) prioritised 16 work-stressors and 4 wellness interventions at a large academic medical centre during the COVID-19 pandemic (December 2020).

Results Top-ranked stressors were work-life integration and electronic health record documentation. Therapy (63%, selected as ‘would realistically consider intervention’) and coaching (58%) were the most preferred wellness supports in comparison to group-based peer support (20%) and individual peer support (22%). Pathology, psychiatry and OBGYN specialties were most willing to consider all intervention options, with emergency medicine and internal medicine specialties least willing to consider intervention options.

Conclusion BWS can identify relative differences in surveyed stressors, allowing for the generation of specialty-specific stressor rankings and preferences for specific wellness interventions that can be used to drive institution-wide changes to improve clinician wellness. BWS surveys are a potential methodology for clinician wellness programmes to gather specific information on preferences to determine best practices for resident wellness.

  • health economics
  • medical education & training
  • mental health
  • human resource management

Data availability statement

Data are available upon reasonable request.

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