“I Didn't Do it Alone”: Family Involvement in Recovery from Substance Use
Bibliographic record
Abstract
INTRODUCTION: Family involvement has been identified as pivotal in addressing substance use disorder (SUD). However, family members, and the clinicians supporting them, are often uncertain about how best to help or be involved. The purpose of this study was to examine how those in recovery perceived family involvement in their recovery journey. METHODS: We conducted semi-structured interviews with individuals (n = 18) who identified as being in recovery from SUD. Interviews focused on specific practices that are perceived as helpful or hindering to recovery. The Enhanced Critical Incident Technique (ECIT) was used to analyze interview data and identify critical incidents. RESULTS: We identified 18 categories comprising of relational factors that helped and hindered recovery from SUD, organized into three main themes of factors important to individuals' recovery: interpersonal/relational factors, action, and knowledge and understanding. Participants provided concrete examples of how family members were helpful, hindering, or could have better supported their loved ones. CONCLUSIONS: Family support is critical in supporting recovery efforts of individuals struggling with substance use. Relational, action-oriented, and educational support should be collaboratively negotiated based on the preferences and unique needs of the individual in recovery.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".