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Record W4386068421 · doi:10.1080/09687637.2023.2248356

Gender influences on cannabis use among treatment-seeking adults: a qualitative study

2023· article· en· W4386068421 on OpenAlexafffund
Madison Wright, Justin Matheson, Tara Marie Watson, Beth Sproule, Bernard Le Foll, Bruna Brands

Bibliographic record

VenueDrugs Education Prevention and Policy · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsHealth CanadaPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersUniversity of Toronto
KeywordsCannabisPsychologyThematic analysisNormativeClinical psychologyMasculinityQualitative researchPsychiatryEffects of cannabisMental health

Abstract

fetched live from OpenAlex

Background Gender differences in cannabis use, related harms, and in the development and progression of cannabis use disorder have been reported. Better understanding and identifying why these differences exist is important in developing and tailoring prevention and treatment approaches.Methods This qualitative interview study explored influences of gender on cannabis use trajectories. Twenty-three adults (10 cisgender women, 12 cisgender men, 1 non-binary person) who had received treatment for cannabis-related problems were asked about the relationship between their gender and cannabis experiences.Results Reflexive thematic analysis was used to develop five themes. First, many participants seemingly did not perceive a strong relationship between their gender and cannabis use. Second, men’s cannabis use was impacted by masculinity facilitating the initiation and escalation of use, while simultaneously acting as a barrier to seeking treatment. Third, men’s motivations for using cannabis were almost always reported to be recreational, which is likely linked to men’s use being more normative. Fourth, almost all women reportedly used cannabis to cope, especially with mental health problems. Fifth, social relationships and gender dynamics constrained women’s cannabis use, particularly where many felt pressured into seeking treatment due to increased stigma for women who use cannabis.Conclusions Our findings revealed gender differences in cannabis use trajectories, including treatment seeking, barriers, and facilitators, emphasizing the importance of developing gender-specific approaches for reducing cannabis-related harms.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.049
GPT teacher head0.442
Teacher spread0.393 · 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 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

Citations3
Published2023
Admission routes2
Has abstractyes

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