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Record W2915308986 · doi:10.1111/dar.12912

Context matters: Characteristics of solitary versus social cannabis use

2019· article· en· W2915308986 on OpenAlexafffundabout
Toni C. Spinella, Sherry H. Stewart, Sean P. Barrett

Bibliographic record

VenueDrug and Alcohol Review · 2019
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsCannabisContext (archaeology)Cannabis DependencePsychiatryPsychologySocial environmentHarmHarm reductionMedicineClinical psychologyPublic healthSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: Given the increase in cannabis availability and use in North America, identification of risk factors for cannabis use and dependence is paramount. One factor that may be associated with various cannabis-related adverse outcomes is the context in which it is used. This secondary analysis study sought to examine the extent to which the social context of cannabis use is related to patterns of use and associated harms. DESIGN AND METHODS: One hundred and eighty-eight adult cannabis users were community-recruited in Halifax, Canada. Participants took part in a face-to-face structured interview where they provided information about the social context of their most recent cannabis-using occasion and about their patterns of, and motives for, cannabis use. RESULTS: Compared to individuals reporting their most recent cannabis-using occasion as social, solitary users (n = 55) were significantly more likely to screen positive for psychosis, endorse more symptoms of cannabis abuse/dependence, report using cannabis to cope, and use cannabis on more days within the previous 30 days. On the other hand, social users were significantly more likely to report using alcohol in addition to cannabis during their most recent cannabis-using occasion (all P < 0.05). DISCUSSION AND CONCLUSIONS: Results suggest that solitary cannabis use may be associated with specific motives for use and future adverse consequences. Findings from this study serve as a guide for future investigations which could ultimately inform public policy and the development of targeted harm-reduction strategies.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.039
GPT teacher head0.331
Teacher spread0.293 · 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 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

Citations39
Published2019
Admission routes3
Has abstractyes

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