Quality in Standardized Patient Training and Delivery: Retrospective Documentary Analysis of Trainer and Instructor Feedback
Bibliographic record
Abstract
Background An important aspect of developing and maintaining a high-quality standardized patient (SP) program is incorporating quality assurance processes. Trainer and instructor feedbacks are considered critical in achieving these goals. The aim of this study is to determine programmatic and systematic issues in the scope of quality assurance and improvement through trainer and instructor feedback on SP performance. We also presented a logic model based on a synthesis of the current literature to ensure the development and maintenance of a quality management culture in the SP program. Methods A retrospective analysis of SP scoring was conducted, and written feedback forms completed by trainers and instructors in a large Canadian university's SP program were collected. The previous six years (2014-2020) of SP feedback forms in the scope of quality assurance were reviewed and analyzed. Descriptive statistics were utilized to analyze the ratings. Thematic analysis was conducted on the data gathered from the written feedback. Results A total of 138 feedback forms were reviewed and analyzed in the study. The mean ratings given by the trainers for feedback and professionalism were 4.27 ± 1.29 and 4.77 ± 0.8, respectively. The mean ratings given by the instructors for knowledge of case information, appropriate responses, and affect were 4.84 ± 0.64, 4.86 ± 0.35, and 4.71 ± 0.76, respectively (from a range of 1 to 5). Four key themes emerged from the written feedback: nonverbal behaviors in simulation activity or feedback sessions, providing feedback from the patient perspective, consistency between role portrayal and scenario, and adapting easily to changing situations. Conclusions Component scoring on SP performance did not discriminate individual issues, but the qualitative comments identified certain specific issues. Further research is needed to establish standards of continuous quality improvement (CQI) within an SP program.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".