Perspectives on internal vs. external facilitation for implementing guidelines for recovery-oriented practice: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Seven organizations supporting adults with mental health challenges collaborated with researchers to implement Chapter Six of Canada's Guidelines for Recovery-Oriented Practice. An implementation strategy was developed that combined external facilitation, mixed Implementation Teams, a 12-meeting planning process, and ongoing coaching. This paper focuses on the facilitation component, specifically exploring participants' perspectives on internal versus external facilitation within Implementation Teams. METHODS: Forty semi-structured individual online interviews were conducted with 32 members of Implementation Teams, including service users, providers, family members, managers, and knowledge users, along with eight researchers who acted as external facilitators. Participants discussed their experiences of implementing the guidelines supported by an external facilitator and were asked to consider how their experience may differ if it had been led by an internal facilitator. RESULTS: Thematic analysis identified seven themes relating to what was perceived as important about internal versus external facilitation: (1) Effect of facilitator position (external versus internal); (2) Flattening power hierarchies; (3) Enacting cultural shifts; (4) Understanding context; (5) Encouraging candour; (6) Building relationships, and (7) Internal facilitator identity and influence. These highlight how participants valued different skills, knowledge, and attributes in each scenario, with responses varying depending on the participant's identity. No clear preference emerged for either approach. Instead, participants debated the benefits and drawbacks of both, where insider knowledge vied with outsider neutrality for primacy. CONCLUSIONS: Whether facilitation is internal or external, its effectiveness relies on the facilitator's ability to establish rapport, develop allies, and foster unity between Implementation Team members and the implementation setting itself. A blended approach, which integrates the strengths of both internal and external facilitators, may offer the most effective model for supporting the implementation of recovery-oriented practice. AUTHOR(S): .
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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 | 0.042 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".