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Record W2934993238 · doi:10.1016/j.pmedr.2019.100865

Youth consumption of alcohol mixed with energy drinks in Canada: Assessing the role of energy drinks

2019· article· en· W2934993238 on OpenAlexafffundabout
Amanda Doggett, Wei Qian, Adam G. Cole, Scott T. Leatherdale

Bibliographic record

VenuePreventive Medicine Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsEnvironmental healthConsumption (sociology)Binge drinkingMedicinePopulationLogistic regressionEnergy (signal processing)Energy consumptionDemographyPsychologyInjury preventionPoison controlEngineeringMathematics

Abstract

fetched live from OpenAlex

Consuming alcohol mixed with energy drinks (AmED) is a risk behaviour among youth, and previous research has reported a positive association between binge drinking and AmED consumption. However, limited research has examined how regular consumption of energy drinks is associated with AmED consumption among youth. The purpose of this report is to examine the role of energy drink use on AmED consumption in a Canadian youth population. Using data from the 2015-2016 COMPASS survey including 35,300 grade 9 to 12 students, two logistic regression models investigated if the inclusion of energy drink consumption in the past week altered the results of a model examining AmED consumption. In this sample, 13.2% of students reported AmED consumption in the last 12 months. Those who reported drinking energy drinks in the past week were 3.38 times more likely to consume AmED than those who did not drink energy drinks. The inclusion of past week energy drink use decreased the effect size of other associated substance use behaviours. This report demonstrates that past week energy drink use is associated with increased likelihood of AmED consumption and suggests that previous research may have missed this important contributor. These findings along with existing energy drink research highlight the importance of addressing the lack of energy drink regulations 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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 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

Citations13
Published2019
Admission routes3
Has abstractyes

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