A simulated patient evaluation of pharmacist’s performance in a men’s mental health program
Bibliographic record
Abstract
OBJECTIVE: The Headstrong program, a pharmacy based men's mental health promotion program, was designed to enhance pharmacists' care of men with mental illness and addictions and was focused on six conditions. A simulated patient (SP) encounter on insomnia was used to evaluate pharmacist's performance as a part of the Headstrong program. RESULTS: Six Headstrong pharmacists consented to participate in the SP encounter as part of the evaluation of the Headstrong program. Pharmacists' mean scores in most categories that were evaluated (e.g., pre-supply/assessment score, sleep score) were lower than expected. In assessing the SP during the encounter, pharmacists' mean score was 5.7 (SD 2.0) of a possible 13 points. No pharmacists asked about the SP's age, availability of other supports, allergies, and whether they had an existing relationship with a pharmacist. One pharmacist inquired about medical conditions, and two asked about pre-existing mental health conditions. Three pharmacists inquired about concurrent medications. The Headstrong program was discussed by half of the pharmacists and a resource recommended by the Headstrong program was suggested by one pharmacist. Several pharmacists used self-disclosure as a mechanism to support rapport building. Overall, the SP felt cared for and respected by the pharmacists and had confidence in their knowledge.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".