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Record W4411841763 · doi:10.1080/18387357.2025.2522434

Processes of co-response crisis mental health models: a scoping review

2025· review· en· W4411841763 on OpenAlexafffund
Andrew D. Eaton, Megan Rowe, Allannah Nguyen, Leyna Lowe, Ammar Adenwala, Simone Sudom-Young, Rebecca Rackow, Lara Poellet, Mel McDonald, Lauren B. McInroy

Bibliographic record

VenueAdvances in Mental Health · 2025
Typereview
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCanadian Mental Health AssociationUniversity of ReginaUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMental healthPsychologyCrisis responsePsychiatryPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

Objective Police services assume the role of first responders for mental health crisis situations, providing no mental health support risking police-inflicted harm to the person in crisis. Advances in mental health and police reform have produced alternative response models like co-response that includes both police officers and trained mental health service providers. This scoping review synthesises knowledge to present key processes that facilitate co-response models.Method Covidence software was used by two independent reviewers to search eleven databases with terms including ‘co-response’, ‘police partnerships’, and ‘crisis response team’. These reviewers screened 2690 titles and abstracts and 109 full-texts to include 76 articles. Nine independent coders employed thematic content analysis.Results Three themes and seven sub-themes were determined as key processes of co-response. Decriminalising mental health involves re-evaluating the role of police and reducing reliance on police in crisis mental health response. Interprofessional collaboration features partnerships between existing services, unifying strategies, and establishing multidisciplinary teams. A piloting phase permits monitoring and evaluation and highlights the diversity of co-response models.Discussion Co-response crisis mental health models are increasingly common, heterogeneous in design and operation, and built upon existing infrastructure. Future inquiries could include trauma-informed care and the evaluation of civilian-led models..

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.519
Teacher spread0.439 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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