Collaborative partnerships: bridging the knowledge practice gap in client-centred care in mental health
Bibliographic record
Abstract
Purpose – The purpose of this paper is to describe a partnership, the Ryerson-Centre for Addiction and Mental Health Collaborative for Client-Centred and Family Sensitive Care Collaborative, between an urban university and tertiary care mental health facility to build capacity in using research evidence to support client-centred care. A cornerstone of the partnership was a study exploring the connection between effective interprofessional collaboration and the capacity to provide exemplary client-centred care in mental health. Design/methodology/approach – The Collaborative brings together organizations with shared values and a commitment to client-centred interprofessional care. It is a strategic approach in amplifying opportunities for the uptake of research evidence and knowledge transfer. One of the principal deliverables for the Collaborative was a multi-phased study exploring the relationship between team collaboration and client-centred care. Findings – Research findings identified a significant association between the level of team effectiveness and collaboration and the staffs’ perceived capacity to deliver client-centred care. Client and family member perspectives highlighted the importance of interprofessional team functioning and collaboration. The work of the Collaborative helped narrow the knowledge practice gap through: a research practicum to mentor graduate students; knowledge exchange and dissemination; and working with advanced practice staff to support change within the organization. Originality/value – Inter-organizational relationships, such as the Collaborative, support initiatives that accelerate the use of clinically relevant research and bridge the knowledge practice gap. A university/tertiary care teaching facility partnership represents a promising model for advancing and disseminating evidenced-based knowledge.
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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 | 0.082 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.025 |
| Scholarly communication | 0.024 | 0.023 |
| Open science | 0.006 | 0.054 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".