Courtesy stigma toward parents of adolescents with cannabis use disorder: examining the role of language and gender in a Canadian sample
Bibliographic record
Abstract
Background Parents of individuals with substance use disorder (SUD) may be stigmatized by association, known as courtesy stigma. Language may influence SUD stigma, and parents impacted by a child’s SUD have identified the terms ‘enabler’ and ‘codependent’ as stigmatizing. This study examined how language and parent gender influence public perceptions of courtesy stigma toward the parent of an adolescent with cannabis use disorder (CUD).Methods Participants (324 Canadian adults) read a vignette depicting the relationship between a parent and their adolescent child with CUD. The vignette varied by the language describing the parent (deficit-based/neutral) and parent gender (mother/father). Stigma toward the parent was assessed using three Attribution Questionnaire subscales (help/interact, responsibility, and negative emotions).Results 2 × 2 ANOVAs revealed more willingness to help the father and more negative emotions toward the parent when described using deficit-based language. Perceived responsibility of the parent did not differ by language or parent gender depicted in the vignette.Conclusion The findings provide preliminary evidence that using deficit-based terminology like ‘enabler’ and ‘codependent’ may contribute to courtesy stigma toward parents of children with SUD. The results highlight the importance of using person-first, neutral language when referring to parents of individuals with SUD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".