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Record W4416258386 · doi:10.1080/09687637.2025.2587620

The role of fathers in adolescent cannabis use disorder: Public perceptions of paternal shame and responsibility

2025· article· en· W4416258386 on OpenAlexaffabout
Olivia C. Bishop, Jessica M. Perry, Bhavya Sehgal, Molly K. Downey, Ashlee R. L. Coles, Nick Harris

Bibliographic record

VenueDrugs Education Prevention and Policy · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsShamePerceptionCannabisYoung adultPublic healthSuicide prevention

Abstract

fetched live from OpenAlex

Background: When youth experience substance use disorders (SUDs), their parents are often faced with stigma and assigned responsibility for their child’s disorder. While existing literature primarily focuses on the experiences of mothers of children with SUDs, fathers are also subject to blame and stigma from family, healthcare professionals, and the public. The present study qualitatively investigated public perceptions of paternal responsibility and shame in the context of an adolescent with cannabis use disorder (CUD). Methods: After reading a vignette about a father and his adolescent child with CUD, 78 Canadian adults answered two open-ended questions which gauged whether participants assigned responsibility and shame to the father. Responses were thematically analyzed using an inductive approach. Results: Five themes were revealed, which covered a range of perceptions and opinions regarding parenting, substance use, adolescent autonomy, paternal responsibility, and shame. Conclusion: These findings underscore the importance of public education on substance use, the hardships that parents of youth with SUDs face, and the need for SUD de-stigmatization.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.005
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.317
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2025
Admission routes2
Has abstractyes

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