Exploring perceptions of genetic risk and the transmission of substance use disorders
Bibliographic record
Abstract
BACKGROUND: Substance use disorders (SUDs) have been consistently shown to exhibit moderate intergenerational continuity (1-3). While much research has examined genetic and social influences on addiction, less attention has been paid to clients' and lay persons' perceptions of genetic influences on the heritability of SUD (4) and implications for treatment. METHODS: For this qualitative study, twenty-six structured Working Model of the Child Interviews (WMCI) were conducted with mothers receiving inpatient SUD treatment. These interviews were thematically analyzed for themes related to maternal perceptions around intergenerational transmission of substance use behaviours. RESULTS: Findings show that over half of the mothers in this sample were preoccupied with their children's risk factors for addictions. Among this group, 29% spontaneously expressed concerns about their children's genetic risk for addiction, 54% shared worries about their children's propensity for addiction without mentioning the word gene or genetic. Additionally, 37% had challenges in even discussing their children's future when prompted. These concerns mapped onto internal working models of attachment in unexpected ways, with parents who were coded with balanced working models being more likely to discuss intergenerational risk factors and parents with disengaged working models displaying difficulties in discussing their child's future. CONCLUSION: This research suggests that the dominant discourse around the brain-disease model of addictions, in its effort to reduce stigma and self-blame, may have unintended downstream consequences for parents' mental models about their children's risks for future addiction. Parents receiving SUD treatment, and the staff who deliver it, may benefit from psychoeducation about the intergenerational transmission of SUD as part of treatment.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".