Stigma in Psychiatry: Impact of a Virtual and Traditional Psychiatry Clerkship on Medical Student Attitudes
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to assess the change in medical students' attitudes towards psychiatry following a virtual clerkship experience compared to a traditional clerkship experience. METHOD: Ninety-seven medical students from the University of Ottawa were assessed pre- and post-clerkship on the ATP-30 (Attitudes Towards Psychiatry-30) measure. Cohorts of students were categorized as pre-COVID or during-COVID depending on when and how they experienced their clerkship (traditional or virtual). The total student response rate was approximately 48%. A quasi-experimental design was implemented, and non-parametric statistics were used to analyze the data. RESULTS: Medical students' overall attitudes towards psychiatry improved from pre- to post-clerkship, with the type of clerkship experience (traditional or virtual) having no significant impact on the magnitude to which attitudes improved. CONCLUSION: Implementation of a virtual clerkship in psychiatry did not deteriorate medical student attitudes towards psychiatry as a specialty, with both the traditional and virtual clerkship program enhancing students' attitudes towards psychiatry favorably.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".