Teaching Spiritual and Religious Competencies to Psychiatry Residents: A Scoping and Systematic Review
Bibliographic record
Abstract
PURPOSE: For many persons worldwide, mental health is inseparably linked with spirituality and religion (S&R), yet psychiatrists have repeatedly expressed doubts regarding their preparedness to address patients' spirituality or religion appropriately. In recent decades, medical educators have developed and implemented curricula for teaching S&R-related competencies to psychiatry residents. The authors reviewed the literature to understand the scope and effectiveness of these educational initiatives. METHOD: The authors searched 8 databases to identify studies for a scoping review and a systematic review. The scoping review explored educational approaches (topics, methods) used in psychiatry residency programs to teach S&R-related competencies. The systematic review examined changes in psychiatry trainees' competencies and/or in patient outcomes following exposure to these educational interventions. RESULTS: Twelve studies met criteria for inclusion in the scoping review. All reported providing residents with both (1) a general overview of the intersections between mental health and S&R and (2) training in relevant interviewing and assessment skills. Seven of these studies-representing an estimated 218 postgraduate psychiatry trainees and at least 84 patients-were included in the systematic review. Residents generally rated themselves as being more competent in addressing patients' S&R-related concerns following the trainings. One randomized controlled trial found that patients with severe mental illness who were treated by residents trained in S&R-related competencies attended more appointments than control patients. CONCLUSIONS: S&R-related educational interventions appeared generally well tolerated and appreciated by psychiatry trainees and their patients; however, some topics (e.g., Alcoholics Anonymous) received infrequent emphasis, and some experiential teaching methodologies (e.g., attending chaplaincy rounds) were less frequently used for psychiatry residents than for medical students. The positive association between teaching S&R-related competencies to psychiatry residents and patient appointment attendance merits further study. Future trainings should supplement classroom learning with experiential approaches and incorporate objective measures of resident competence.
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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 | 0.017 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".