Moral Distress among Family Medicine Resident Physicians
Bibliographic record
Abstract
Context: Moral distress was first described as knowing the right thing to do, but facing organizational barriers in making it possible. Moral distress has been linked to burnout and intentions to leave the healthcare profession. Moral distress has been classified into three groups: 1) patient level factors, 2) team miscommunication or inadequate collaboration, and 3) system-level causes. Experiencing moral distress in healthcare is a well-known issue, however, there is limited evidence exploring it among resident physicians. Objectives: Determine what factors contribute to moral distress among family medicine residents and if there are differences in the intensity of distress between R1s/R2s, training sites, and CMGs/IMGs. Study design: An online cross-sectional survey was distributed via email in January 2024. Composite scores for different demographic characteristics were compared using Mann Whitney U or Kruskal-Wallis tests. Setting: University of Saskatchewan Population: Family medicine residents at the University of Saskatchewan. Intervention/Instrument: The survey included the Moral Distress Scale – Revised, which was modified to the Canadian context. Outcome measures: Each item was scored, and an overall composite score was calculated by summing participants’ responses to assess moral distress intensity. Results: Forty-seven family medicine residents completed the survey. All participants identified items causing moral distress. The most highly rated items were: 1) Moral distress in providing care that does not relieve the patient’s suffering due to limited healthcare services available. 2) Moral distress in witnessing care suffer because of physicians or nurses’ lack of time to provide quality patient care 3) Moral distress in watching patient care suffer because of a lack of provider continuity. There were no significant differences in composite scores between demographic groups. Conclusions: This study aligns with findings in the literature and shows moral distress stems from lack of provider continuity. Further, it reaffirms that working in an environment with short staffing and time constraints may cause moral distress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".