Exploring Intersecting Program Elements in Longer-Term Concurrent Disorder Services for Adults: A Qualitative Evaluation
Bibliographic record
Abstract
Previous research highlights multiple factors that impact the attainment of client-identified recovery goals in substance misuse treatment programs. However, fewer studies examine how programs meet the broad range of needs expressed by clients through their intersecting elements of service delivery. This study seeks to develop an understanding of intersecting program and recovery elements in relation to an overall framework for programming, focusing on how overlapping elements of treatment ventured to support clients in multiple areas of their recovery. Qualitative interviews were conducted with clients (n=41) in three longer term substance use treatment programs, and data from interviews were analysed using analytic induction and constant comparison strategies to surface emergent themes. Data analysis yielded six main findings. These included: Education; Goal Setting; Routine and Stability; Spiritual Development; Exercise; and Transitional Planning. Respondents indicated that programs must focus on bolstering the development of each element across multiple treatment domains (such as group therapy and counselling) to best support clients in achieving recovery outcomes.
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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 | 0.045 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".