Examining implementation of mobile, police-mental health crisis intervention teams in a large urban center
Bibliographic record
Abstract
BACKGROUND: Mobile Crisis Intervention Teams (MCITs) have emerged as a police and mental health system co-response to assist police in responding to individuals experiencing mental health crises. There is a gap in knowledge regarding the critical program components that contribute to successful MCIT implementation. AIMS: This evaluation study aimed to understand processes of implementation of a multi-site MCIT program in a large urban center and to identify program strengths and challenges, as well as levels of satisfaction in service delivery. METHODS: Fifty-seven stakeholders participated in qualitative interviews and focus groups, including: MCIT consumers and staff, individuals from the health system, police services, and community organizations. RESULTS: Overall, program stakeholders perceived the MCIT program positively and viewed it as meeting its key goals. The implementation evaluation has highlighted the importance of respectful interaction with consumers, cross-sector training and collaboration, and ensuring clarity in program mandate and staff roles. These program components can continue to be built upon to improve MCIT service delivery. CONCLUSIONS: Future studies should further evaluate the role of key strengths in MCIT program implementation as well as the impact of recommended improvements on program outcomes.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".