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Record W4409476348 · doi:10.4300/jgme-d-24-00481.1

Examining Resident Burnout Through the Lens of Self-Determination Theory: The Role of General Causality Orientations

2025· article· en· W4409476348 on OpenAlexaffabout
Adam Neufeld, Greg Malin, Оксана Бабенко, César Orsini

Bibliographic record

VenueJournal of Graduate Medical Education · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of AlbertaUniversity of SaskatchewanUniversity of Calgary
Fundersnot available
KeywordsBurnoutCausality (physics)AutonomyPsychologyOrientation (vector space)Social psychologyStructural equation modelingClinical psychologyStatisticsMathematicsPolitical science

Abstract

fetched live from OpenAlex

Background Burnout continues to plague graduate medical education, and theory-informed approaches are lacking for effectively tackling this problem. Studies on personal factors that explain physician burnout have also neglected the role of self-determination. In self-determination theory, general causality orientations— autonomy , control , and impersonal —represent individual differences in self-determination that can be socialized and primed within environments, each relating to different motivation, behavior, and well-being outcomes. Objective To investigate how each general causality orientation relates to resident burnout, the hypothesis being that the autonomy orientation will negatively correlate, while the control and impersonal orientations will positively correlate. Methods Surveys containing demographic questions and 2 scales—the Causality Orientations at Work Scale and Oldenburg Burnout Inventory—were sent in 2023 to a sample of Canadian residents across 3 institutions. Correlation and multiple regression analyses were performed, controlling for significant demographic factors. Results A total of 243 of 1200 residents (20.5%) completed the survey. The 3 general causality orientations accounted for 31.5% of the variance in resident burnout, with autonomy correlating negatively ( B =-0.24; P <.001; 95% CI, -0.37 to -0.11) and control ( B =0.20; P =.003; 95% CI, 0.07 to 0.33) and impersonal ( B =0.28; P <.001; 95% CI, 0.13 to 0.42) correlating positively. Conclusions Resident burnout is positively associated with the control and impersonal causality orientations, and negatively associated with the autonomy causality orientation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.469
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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