Never the twain? Reconciling national suicide prevention strategies with the practice, educational, and policy needs of mental health nurses (Part two)
Bibliographic record
Abstract
Suicide remains as a distinct global public health problem and the reduction of rates continues to be a major concern of the governments of many countries. This two-part paper focuses on national suicide prevention strategies; it highlights common policy directions that appear to speak directly to the practice and/or educational needs of mental health (MH) nurses and juxtaposes these against the realities of their practice and educational needs. Part one focused on two of these policy directions, whereas part two concentrates on the following policy directions: (iii) initiatives to reduce access to lethal means; (iv) improve surveillance systems; and (v) training for caregivers to improve delivery of effective treatments. The paper argues that while being mindful of the physical environment and its associated access to means, the national suicide prevention policy literature should consider reflecting that this should be an adjunct to the more central aspects of MH nursing care of people who are suicidal. Further, it is argued that the suicide policy literature should consider replacing 'improving surveillance systems' with 'improving the ability and capacity of MH nurses to engage with people who are suicidal'. Lastly, the paper asserts that the suicide policy literature might consider refining the policy direction on additional training to indicate the need for additional post-graduate (post-basic) education and training in care of the person with suicidal tendencies, which includes dialectical behavioural therapy; the work emanating from the University of Toronto; and the skills, attitudes, and knowledge perhaps captured with the terms, engagement, co-presencing, and inspiring hope.
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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 | 0.024 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".