Developing an initial program theory for peer support groups for substance-affected family members: a participatory realist evaluation
Bibliographic record
Abstract
Abstract Background Amidst an unregulated drug crisis in Canada, the needs of affected family members have been largely ignored. Evidence supports the efficacy of peer support group interventions in health and social care; however, a better understanding of how peer support groups produce outcomes is required for successfully implementing interventions for substance-affected family members. Methods The study uses a participatory realist evaluation framework to develop an initial program theory (IPT). Data collection includes interviews of program staff and participants, program evaluation surveys, internal program documents, and observational field notes. We employ deductive and inductive coding and retroductive analysis theorizing contexts, mechanisms, and outcomes configurations (CMOCs). Results We present three nested implementation contexts containing 10 CMOCs. Our IPT suggests: Strong organizational support in an environment that values lived expertise promotes program sustainability; a skilled facilitator with lived experience will leverage unique approaches to foster a positive group culture; a positive group culture activates the program’s pillars of emotional support, education and skill-building to produce reduced social isolation, improved emotional wellbeing, increased self-efficacy, and improvements in relationships. Conclusion This participatory realist evaluation presents an IPT of a peer support group for substance-affected families that will inform future implementation and evaluation of family supports.
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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 | 0.099 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".