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Record W6997320347

The WARN Study: Investigating University Student Perceptions of Alcohol Risk and Health Warning Labels

2024· article· en· W6997320347 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2024
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisPerceptionPublic healthReflexivityQualitative researchSocial mediaRisk perceptionHealth risk
DOInot available

Abstract

fetched live from OpenAlex

Products that carry risk, including cigarettes, cannabis, and vaping products, require health warning labels on their packaging. Despite the established health hazards, health warnings are not required on alcohol products. The purpose of this study was to investigate the attitudes, beliefs, and perceptions that Canadian university students have about health risks from alcohol and health warnings. Using mixed methods, Canadian university students were recruited through social media to participate in an online survey (n= 331) and semi-structured interviews (n= 14). Survey results indicate that participants strongly support health warnings and believe that health warnings are valuable. Qualitative data were analyzed using reflexive thematic analysis. Results indicate that students perceive alcohol as less dangerous than other drugs, health warnings are valuable in informing them of risk, and there is an expectation of warnings surrounding dangerous substances. This research supports efforts to legislate health warning labels on alcoholic beverages sold in Canada.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.137
GPT teacher head0.398
Teacher spread0.261 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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