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Record W4409245872 · doi:10.1080/09687637.2025.2487452

Courtesy stigma toward parents of adolescents with cannabis use disorder: examining the role of language and gender in a Canadian sample

2025· article· en· W4409245872 on OpenAlexaffabout
Molly K. Downey, Ashlee R. L. Coles

Bibliographic record

VenueDrugs Education Prevention and Policy · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCourtesyPsychologyStigma (botany)CannabisSample (material)Developmental psychologyClinical psychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.328
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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