Medical training to effectively support patients who use substances across practice settings: a scoping review of recommended competencies
Bibliographic record
Abstract
Background: The responsibility for addressing the healthcare needs of PWUS is the responsibility of all physicians. Within the healthcare system, research consistently reveals inequitable experiences in healthcare with people who use substances (PWUS) reporting stigmatization, marginalization, and a lack of compassion. Objectives: The aim of this scoping review was to find and describe competencies being taught, developed, and fostered within medical education and then to provide recommendations to improve care for this population of patients. Results: Nineteen articles were included. Recommended knowledge competencies tend to promote understanding neurophysiological changes caused by substances, alongside knowing how to evaluate of 'risky' behaviours. Commonly recommended skills relate to the screening and management of substance use disorders. Recommended attitude competencies include identifying personal bias and establishing a patient-centered culture among practice teams. The disease model of addiction informed all papers, with no acknowledgement of potential beneficial or non-problematic experiences of substance use. To enhance knowledge-type competencies, medical education programs are advised to include addiction specialists as educators and prevent stigmatization through the hidden curriculum. Conclusion: To reduce experiences of stigmatization and marginalization among patients who use illicit substances and to improve quality of care, knowledge, skills, and attitudes competencies can be more effectively taught in medical education programs.Résumé.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 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; both teacher heads agree on what is shown here.
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".