MétaCan
Menu
Back to cohort
Record W3035601741 · doi:10.1111/jhn.12789

Prevalence and pattern of energy drink intake among Australian adolescents

2020· article· en· W3035601741 on OpenAlexaff
Gina Trapp, Miriam Hurworth, Hayley Christian, Marilyn Bromberg, Justine Howard, Catrina McStay, Gina L. Ambrosini, Karen Martin, Amelia J. Harray, Donna Cross, Wendy H. Oddy, David Hammond

Bibliographic record

VenueJournal of Human Nutrition and Dietetics · 2020
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsUniversity of Waterloo
FundersNational Health and Medical Research CouncilNational Heart Foundation of Australia
KeywordsMedicinePsychological interventionEnvironmental healthTasteDemographyGerontologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Energy drinks (ED) are popular among young people despite evidence of associated health risks. Research into the prevalence and pattern of ED intake among young people is sparse. The present study investigates the prevalence and pattern of ED intake among a large sample of adolescents, including how many consume them, how often, for what reasons and in what contexts. METHODS: In 2018, all students in grades 7-12 attending 25 randomly selected Western Australian schools were invited to complete an online self-report survey about EDs. RESULTS: Of the 3688 respondents, 51.2% reported consuming an ED. Of these 'ever consumers', 23.4% drank them monthly, 19.2% weekly and 2% every day. The average age of first intake was 10.7 years. One-fifth (19.7%) of 'ever consumers' reported consuming more than two EDs in 1 day. Reasons for ED use included taste, to boost energy levels, sport performance and studying. CONCLUSIONS: The findings add to limited international evidence about adolescent ED use and provide valuable information to help ensure interventions to reduce intake address the underlying reasons and contexts of ED 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 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)0.000
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 score0.091
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.047
GPT teacher head0.317
Teacher spread0.270 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Human Nutrition and DieteticsSame topicCoffee research and impactsFrench-language works237,207