A Web-Based Well-Being and Resilience Intervention for Family Members and Friends Supporting a Loved One Using Alcohol and Other Drugs: Mixed Methods Pilot Study
Bibliographic record
Abstract
Background: Despite the known psychosocial challenges associated with supporting a loved one using alcohol and other drugs (AOD), there is a scarcity of mental health and well-being interventions for affected friends and family members (AFFMs). Stigma has also been shown to discourage help-seeking among AFFMs. Web-based interventions may facilitate help-seeking by ensuring privacy and anonymity. Objective: This pilot study examines the usability, acceptability, and feasibility of the Family and Friend Support Program (FFSP), a world-first, evidence-based web-based resilience and well-being program designed with, and for, people caring for someone using AOD. This study also examined AFFM's experiences of caring for a loved one using AOD and their help-seeking behaviors and barriers. Methods: In 2021 (November-December), participants across Australia completed a baseline web-based cross-sectional survey that assessed the impact of caring for a loved one using AOD (adapted Short Questionnaire for Family Members-Affected by Addiction), and distress levels (Kessler Psychological Distress Scale [K-10]). Following baseline, participants were invited to interact with the FFSP over 10 weeks. Postprogram and follow-up surveys (10 and 14 wk postbaseline, respectively) and semistructured interviews assessed the usability and acceptability of the program, as well as help-seeking experiences and barriers. Results: Baseline surveys were completed by 131 AFFMs, with 37% (n=49) completing the postprogram survey and 24% (n=32) completing the follow-up survey. A total of 5 participants took part in individual semistructured interviews at postprogram. On average, K-10 scores fell in the moderate to severe range at baseline (mean 28.4, SD 8.6). At postprogram, the majority of participants (n=27, 55.1%) reported that they did not seek help to cope with or manage their role supporting their loved one and the most common endorsed barrier was cost (n=11, 28.6%). Overall, participants found the FFSP easy to use and provided them with relevant, helpful, and validating information. The majority (n=35, 71.5%) of participants said they would be likely to recommend the FFSP to a person supporting a loved one using AOD. Qualitative responses highlighted the need for free, accessible support for AFFMs such as the FFSP. Limitations included low program engagement and high attrition. Conclusions: Overall, the FFSP appears to be a promising mental health intervention for AFFMs. This study builds on existing research finding high levels of distress among AFFMs, while highlighting the ongoing barriers to help-seeking. Limitations and future directions for refinements and future efficacy evaluation of the FFSP are discussed including ways to address attrition and increase engagement.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".