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Using nominal group technique among resident physicians to identify key attributes of a burnout prevention program

<p>Purpose:<b> </b>To identify preferred burnout interventions within a resident physician population, utilizing the Nominal Group Technique. The results will be used to design a discrete choice experiment study to inform the development of resident burnout prevention programs.</p> <p>Methods:<b> </b>Three resident focus groups met (10-14 participants/group) to prioritize a list of 23 factors for burnout prevention programs. The Nominal Group Technique consisted of three steps: an individual, confidential ranking of the 23 factors by importance from 1 to 23, a group discussion of each attribute, including a group review of the rankings, and an opportunity to alter the original ranking across participants.</p> <p>Results:<b> </b>The total number of residents (36) were a representative sample of specialty, year of residency, and sex. There was strong agreement about the most highly rated attributes which grouped naturally into themes of autonomy, meaning, competency and relatedness. There was also disagreement on several of the attributes that is likely due to the differences in residency specialty and subsequently rotation requirements.</p> <p>Conclusion:<b> </b>This study identified the need to address multiple organizational factors that may lead to physician burnout. There is a clear need for complex interventions that target systemic and program level factors rather than focus on individual interventions. These results may help residency program directors understand the specific attributes of a burnout prevention program valued by residents. Aligning burnout interventions with resident preferences could improve the efficacy of burnout prevention programs by improving adoption of, and satisfaction with, these programs.</p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
0
Harmonization
12
Access
12
Reuse readiness
0
Engagement
4

Dataset details

Repository
dryad
Published
July 7, 2021
License
cc-zero
DOI
10.5061/dryad.n8pk0p2vv

Scored with release 0.9.0

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