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Associations between Gender Expression, Protective Coping Strategies, Alcohol Saliency, and High-Risk Alcohol Use in Post-Secondary Students at Two Canadian Universities

2023· preprint· en· W4389150998 on OpenAlexaffabout
Anees Bahji, Paul Boonmak, Michelle Koller, Christina Milani, Cate Sutherland, Salinda Horgan, Shu‐Ping Chen, Scott B. Patten, Heather Stuart

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsQueen's UniversityUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsAlcoholPsychological interventionCoping (psychology)Clinical psychologyMultivariate analysisMale genderPsychologyHeavy drinkingEnvironmental healthMedicineHuman factors and ergonomicsDemographyPoison controlPsychiatryInternal medicineBiology

Abstract

fetched live from OpenAlex

Background: This study, conducted in October 2017 at two Canadian universities, aimed to explore the relationships between gender expression, protective coping strategies, alcohol saliency, and high-risk alcohol use. Methods: Validated scales were employed to assess these variables using survey data. Multivariate analyses were conducted to investigate the associations between these factors and high-risk drinking. Results: The study revealed significant associations between high-risk drinking and androgynous gender roles (OR=1.58, 95% CI: 1.19-2.10) as well as among self-reported males (OR=2.21; 95% CI: 1.77-2.75). Additionally, protective behavioral strategies were inversely related to high-risk drinking (OR=0.95; 95% CI: 0.94-0.96), while higher alcohol saliency exhibited a positive correlation with high-risk drinking (OR=1.12; 95% CI: 1.11-1.14). Conclusions: These findings underscore the importance of considering gender, alcohol saliency beliefs, and protective behavioral strategies in the development and refinement of interventions aimed at reducing high-risk alcohol use on Canadian campuses.

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)0.002
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 score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.164
GPT teacher head0.375
Teacher spread0.211 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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