Does video e-learning improve pharmacy teams' attitudes and preparedness towards suicide prevention?
Bibliographic record
Abstract
Evidence on the role of pharmacy teams in suicide prevention is growing. To support pharmacy teams, a video e-learning was produced by the Centre for Pharmacy Postgraduate Education (CPPE) involving an ‘on-the-sofa’ style group interview with people with personal and professional experience of suicide and suicide research. The objective was to measure any change in attitudes and preparedness for suicide prevention, following a video e-learning produced for pharmacy staff. People working in any sector of pharmacy in England and who accessed the training video were invited to complete a pre- and post- training questionnaire, between September 2019 and March 2021. Question types included demographics, experiences, attitudes as measured by the Attitudes to Suicide Prevention (ASP) scale, and preparedness. Descriptive statistics were used to summarize demographics and experience and paired t-tests were used to compare pre- and post- questionnaire responses. Both questionnaires were completed by 147 people. Most worked in community pharmacy (88%) and were pharmacists (64%) or pharmacy technicians (20%). Attitudes to suicide prevention improved significantly (pre:31.20 (SD 6.04); post:28.40 (SD 6.50), p < 0.0001) after watching the video, as did self-reported preparedness. Pharmacy teams' self-reported attitudes and preparedness for suicide prevention improved after watching this suicide awareness video compared to baseline. Suicide awareness training tailored to pharmacy teams may be valuable, but the longitudinal impact of any suicide prevention training requires further exploration.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".