Mobile Mental Health Crisis Intervention \nin the Western Health Region of Newfoundland and Labrador
Bibliographic record
Abstract
The impetus for this research is Recommendation #15 of the 2003 Luther Inquiry into the deaths of Norman Reid and Darryl Power: “IT IS FURTHER RECOMMENDED that the Regional Health Boards establish mobile health units to respond to mentally ill persons in crisis where no criminal offence is alleged. Each unit would be developed locally and based on local needs.” \n \nOur stakeholder partners in the Western Regional Health Authority asked us to identify a range of mobile crisis intervention service models, some of which may be better suited to lower-density, rural populations and some of which may be better suited to higher-density areas like Corner Brook. Our partners expressed a particular interest in models that can be implemented with minimal additional human resources, but that involve local, face-to-face contact rather than telephone, electronic, or clinic-based models of service delivery. \n \nThe term “crisis intervention” generally refers to any immediate, short-term therapeutic interventions or assistance provided to an individual or group of individuals who are in acute psychological distress or crisis. The term encompasses a number of after-the-fact interventions – such as rape counseling and critical incident stress debriefing – that would not be relevant to the kinds of situations described in the Luther Report. Given the project parameters specified by our partners at Western Health, we formulated a research question and a literature search strategy that would enable us to focus specifically on forms of crisis intervention that are designed to manage potentially dangerous mental health crises on-site rather than to mediate their impacts after the fact. Our research question is as follows: “What models of mobile– i.e., face-to-face – crisis intervention have proven effective in managing potentially violent mental health crises occurring outside the hospital setting?”
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".