A systematic review of co-responder models of police mental health ‘street’ triage
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Police mental health street triage is an increasingly common intervention when dealing with police incidents in which there is a suspected mental health component. We conducted a systematic review of street triage interventions with three aims. First, to identify papers reporting on models of co-response police mental health street triage. Second, to identify the characteristics of service users who come in to contact with these triage services. Third, to evaluate the effectiveness of co-response triage services. METHODS: We conducted a systematic review. We searched the following databases: Ovid MEDLINE, Embase, PsycINFO, EBSCO CINAHL, Scopus, Thompson Reuters Web of Science Core Collection, The Cochrane Library, ProQuest National Criminal Justice Reference Service Abstracts, ProQuest Dissertations & Theses, EThoS, and OpenGrey. We searched reference and citation lists. We also searched for other grey literature through Google, screening the first 100 PDFs of each of our search terms. We performed a narrative synthesis of our results. RESULTS: Our search identified 11,553 studies. After screening, 26 were eligible. Over two-thirds (69%) had been published within the last 3 years. We did not identify any randomised control trials. Results indicated that street triage might reduce the number of people taken to a place of safety under S136 of the Mental Health Act where that power exists, or reduce the use of police custody in other jurisdictions. CONCLUSIONS: There remains a lack of evidence to evaluate the effectiveness of street triage and the characteristics, experience, and outcomes of service users. There is also wide variation in the implementation of the co-response model, with differences in hours of operation, staffing, and incident response.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| 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) | 0.000 | 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 it