Effectiveness of a SNAPPS in psychiatric residents assessed using objective structured teaching encounters: a case-control study
Bibliographic record
Abstract
BACKGROUND: Residents play the role of teachers in almost one-quarter of their activities in residency programs. OBJECTIVE: To evaluate whether a 45-minute class using summarize, narrow, analyze, probe, plan, and select (SNAPPS) could improve psychiatry residents' case discussion skills in diverse practical learning settings. DESIGN AND SETTING: This case-control, randomized, blinded study was conducted in a psychiatry hospital at Fortaleza-Ceará. METHODS: Using "resident as teacher" (RaT), objective structured teaching encounters (OSTEs), and SNAPPS, we conducted a study with 26 psychiatry residents. We analyzed video footage of psychiatric cases in three settings: outpatient, nursing, and emergency. An intervention was held two months later with the residents, who were then assigned to two groups: group A (lecture on SNAPPS) and group B (lecture on a topics in psychiatry). Shortly after the lectures, they were video recorded while discussing the same cases. Three blinded examiners analyzed the videos using an instrument based on the Stanford Faculty Development Program (SFDP-26). RESULTS: We found high internal consistency among external examiners and an interaction effect, group effect, and moment effect (P < 0.05). The residents who received the SNAPPS lecture scored significantly higher than their counterparts who received a traditional case presentation. CONCLUSION: This study indicates the efficacy of SNAPPS over traditional case presentation in all three settings as assessed by OSTEs and supports its implementation to improve the teaching of clinical reasoning.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".