Improving Access to Child and Youth Addiction and Mental Health Services in New Brunswick: Implementing One-at-a-Time Therapy Within an Integrated Service Delivery Model
Bibliographic record
Abstract
Abstract This study examines the process of implementing One-at-a-Time (OAAT; i.e., single-session) therapy into child and youth addiction and mental health services in New Brunswick. The implementation process was retrospectively mapped onto implementation science frameworks. Providers were recruited to participate in research associated with the system change, and completed surveys to assess readiness for implementation. Client satisfaction and system-outcomes were measured through surveys and system indicators, respectively. Key implementation considerations included age of consent for services, implementation within an integrated service delivery model, and mapping the client journey to conceptualize changes in service delivery. Providers ( N = 214) felt that OAAT therapy was acceptable and appropriate to implement into practice, and would lead to observable short-term outcomes. During the implementation (April–December 2022), 2266 sessions were delivered, resulting in a 62% waitlist reduction. Most clients who completed the satisfaction survey ( N = 518) reported benefit. This study elucidates the successful implementation of OAAT therapy for children and youth, and can serve as a heuristic for comparable practice change initiatives.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".