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Record W4400483826 · doi:10.1016/j.drugpo.2024.104512

Beyond struggle: A strengths-based qualitative study of cannabis use among queer and trans youth in Québec

2024· article· en· W4400483826 on OpenAlexafffundabout
Kira London-Nadeau, Connor Lafortune, Catherine Gorka, Mélodie Lemay-Gaulin, Jean R. Séguin, Rebecca Haines‐Saah, Olivier Ferlatte, Nicholas Chadi, Robert‐Paul Juster, Sean Bristowe, Heath D'Alessio, Laura Rangel Bernal, Kiah Ellis-Durity, João Paulo Silva Barbosa, Leila Afra Akira Clelia Da Costa De Carlos, Natalie Castellanos Ryan

Bibliographic record

VenueInternational Journal of Drug Policy · 2024
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsConcordia UniversityInstitut National de Santé Publique du QuébecNipissing UniversityUniversity of CalgaryInstitut Universitaire en Santé Mentale de QuébecUniversité de MontréalMontreal Police ServiceCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health ResearchCommission de la santé mentale du Canada
KeywordsCannabisThematic analysisQueerPsychologyPrideMental healthQualitative researchShameSocial psychologyPsychiatrySociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Queer and trans (QT) youth report higher rates of cannabis use than their cisgender and heterosexual peers. Explanations for this have overwhelmingly focused on the difficulties QT youth face, while little research has examined how cannabis use can relate to QT youth's strengths. We sought to explore how cannabis use could be involved in the experiences of QT youth from a strengths-based perspective. METHODS: We conducted a QT youth-led, community-based study composed of 27 semi-structured interviews with QT young adults aged 21-25 years and living in Québec who use(d) cannabis regularly. Through reflexive thematic analysis (Braun & Clarke, 2019), we used a strengths-based lens informed by the Minority Strengths Model (Perrin et al., 2020) to explore how cannabis use featured in participants' efforts to survive and thrive. RESULTS: We generated three themes representing how cannabis featured in participants' efforts to survive and thrive. First, cannabis was used to facilitate the production of an authentic QT self, a process that involved self-discovery, introspection, exploration, awareness, and expression. Cannabis supported, accompanied, and/or complicated this process. Second, cannabis use (and non-use) was involved in building QT community and connection, which constituted a crux of participants' wellbeing. Third, cannabis was used to face adversity, such as marginalization, QT oppression, mental health challenges, and structural under-resourcing. This adversity contrasted experiences of QT identities themselves, which were described as a source of joy and pride. CONCLUSION: Our analysis illustrates many ways in which cannabis use (and non-use) features in QT youth's efforts to survive and thrive. As a result, we encourage loved ones, clinicians, researchers and policy makers to adopt a view of QT cannabis use that is expansive and inclusive of QT youth's strengths.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.242
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0170.009
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.424
Teacher spread0.394 · 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

Citations6
Published2024
Admission routes3
Has abstractyes

Explore more

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