MétaCan
Menu
Back to cohort
Record W2992937662

Parental perceptions of e-cigarette and vaping usage among single-sex, school-going adolescents in Toronto, Canada

2019· article· en· W2992937662 on OpenAlexaboutno aff
James Crossland

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPsychologyAdvertisingBusiness
DOInot available

Abstract

fetched live from OpenAlex

This study explores parental perceptions of adolescent e-cigarette usage, specifically, examining adolescents who attend independent private schools in Toronto, Canada, in order to investigate if those of high socioeconomic status are more educated on the issue of increasing adolescent nicotine consumption. This study employs a quantitative, non-experimental research methodology through the use of surveys administered to parents who have a child at one of the two used independent private schools. This study finds that parents are largely unaware of the increasing e-cigarette usage within schools and more generally, across the globe. Additionally, it finds that parents are unaware of the health risks associated with e-cigarette usage. This study also finds a strong relationship between parental substance use and adolescents perceived risk of substance use. Mainly, it shows that if an adolescent has a parent who smokes or uses substances, that adolescent will have a positive view on substance use, resulting in a greater likelihood of usage in the future. These findings imply that governments and schools have not been effective in preventing this health epidemic and have not been educating parents and adolescents on the potential risks of e-cigarette usage and nicotine consumption.

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)0.000
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 score0.028
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.135
GPT teacher head0.502
Teacher spread0.367 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicSexuality, Behavior, and TechnologyFrench-language works237,207