Supporting addictions affected families effectively (SAFE): a mixed methods exploratory study of the 5-step method delivered in Goa, India, by lay counsellors
Bibliographic record
Abstract
Aims: To explore the effect of the relatives’ drinking on their family members, and the preliminary impact of the 5-step method intervention on the adverse effect of the relatives’ drinking on their family members.Methods: In-depth interviews were conducted with eligible Affected Family Members (AFMs) (n = 30) to understand the effect of the relatives’ drinking on their family members. Subsequently, a different group of consecutive eligible AFMs (n = 21) received the five-step method from lay counsellors, with outcomes measured at baseline and 3 months after delivery of the first session, to examine the impact of the intervention on AFMs.Findings: In the in-depth interviews, the perceived impact of the relatives’ drinking on the AFM included substantial physical/emotional abuse, financial difficulties, shame, poor health, impaired interpersonal relationships and change in the AFM’s role in the family. In the case series, for AFMs who received at least one session of the intervention, there was significantly increased engaged coping, increased stress and increased professional social support; and in those who completed the intervention, there was significantly increased engaged coping, increased strain, and increased informal social support.Conclusions: Compared to developed countries, stresses experienced by AFMs in our study are somewhat qualitatively different. The impact of an un-adapted five-step method intervention is less helpful than found elsewhere; hence an adapted version of the five-step method which is responsive to the realities of the cultural context may be better suited to Indian settings.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".