A clinical protocol for group-based ketamine-assisted therapy in a community of practice: The Roots To Thrive model
Bibliographic record
Abstract
Ketamine-assisted therapy (KaT) has demonstrated therapeutic potential in treating depression, anxiety, and PTSD, driving interest in group-based models of care. Yet, few published protocols offer the comprehensive structure required for safe, scalable application in real-world clinical settings. The RTT-KaT model offers a resilience-informed, community-anchored framework that integrates trauma-aware care with a respectful and intentional weaving of Western and Indigenous knowledge systems. Initially launched as a quality improvement initiative through a partnership between a Canadian university and a regional health authority, RTT-KaT has since evolved into a non-profit clinical program. To date, it has supported over 750 participants through more than 2,000 KaT sessions and 700 Community of Practice groups. RTT-KaT is a culturally informed, resilience-focused model of group-based psychedelic-assisted therapy developed and refined since 2018. The model is rooted in the intentional weaving of Western clinical frameworks and Indigenous knowledge systems, grounded in principles of relational accountability, cultural humility, and trauma-informed care.
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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 | 0.046 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.025 |
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".