Experience of Family Members of Relatives With Substance Use Disorders: An Integrative Literature Review
Bibliographic record
Abstract
Background: Substance use disorders (SUDs) present substantial challenges for family members living with or supporting relatives with SUDs. This review explores existing literature on family members’ experiences with relatives with SUDs and their support needs. Method: An integrative review was conducted by searching literature in the Cumulative Index of Nursing and Allied Health, PubMed, PsycINFO, ProQuest, and Scopus databases. Results: Five themes were generated based on analysis of 26 empirical studies: (a) family members’ and caregivers’ experiences of SUDs; (b) impact of SUDs-related aggressive/violent behaviors on families; (c) dilemmas faced by family members; (d) culture and family stigma related to SUDs; and (e) factors contributing to SUDs, challenges, and support needs. The review highlighted barriers to seeking support due to stigma and guilt, underscoring the need for structured support programs. Conclusions: This review sheds light on the challenges faced by family members with relatives suffering from SUDs and emphasizes the crucial need for structured support programs. The findings provide insights for developing initiatives to address the social and trauma-induced needs of family members and to establish support resources for them.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".