Translating Anxiety-Focused CBT for Youth in a First Nations Context in Northwestern Ontario.
Bibliographic record
Abstract
OBJECTIVE: We sought to evaluate a translation of anxiety-focused cognitive behavioral therapy (CBT) to a First Nations children's mental health provider in rural Ontario and to enhance our understanding of CBT challenges and adaptations unique to the First Nations context. METHODS: The study was conceptualized as a mixed methods sequential explanatory approach using a quasi-experimental (before and after) design with quantitative and qualitative components. Data were produced in two ways: questionnaires completed by therapists, parents and clients pre- and post-training, and through a focus group with therapists working with First Nations clients. Participants of this study were a subset of a larger knowledge translation study involving ten agencies, and comprised nine therapists (two males and seven females), and seven children (six males and one female) from a single First Nations agency. The mean age of children was 11.8 years (±2.71), comparable to children in other agencies. RESULTS: First Nations therapists' scores on a child CBT knowledge questionnaire post-training did not differ from those of therapists in other agencies when controlling for initial values, suggesting comparable training benefit. Children did not differ between groups on any key measures, and all key measures showed improvement from pre- to post-training. Four key themes emerged from therapist focus groups: client challenges, value of supervision, practice challenges, and Northern/rural/remote challenges. CONCLUSIONS: The study highlights the importance of delivering a culturally appropriate CBT program to First Nations populations in Northern Ontario, and provides preliminary evidence of its effectiveness.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".