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Record W2261032176 · doi:10.3148/cjdpr-2015-042

Comprehension and Use of Nutrition Facts Tables among Adolescents and Young Adults in Canada

2016· article· en· W2261032176 on OpenAlexaffvenueabout
Erin Hobin, Grace Shen‐Tu, Jocelyn Sacco, Christine M. White, Carolyn Bowman, Judy Sheeshka, Gail McVey, Mary O'Brien, Lana Vanderlee, David Hammond

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2016
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsHospital for Sick ChildrenUniversity of WaterlooPublic Health Ontario
Fundersnot available
KeywordsComprehensionPsychologyGerontologyEnvironmental healthMedicineDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

PURPOSE: Limited evidence exists on the comprehension and use of Nutrition Facts tables (NFt) among adolescents and young adults. This study provides an account of how young people engage with, understand, and apply nutrition information on the current and modified versions of the NFt to compare and choose foods. METHODS: Participants aged 16-24 years (n = 26) were asked to "think aloud" while viewing either the current or 1 of 5 modified NFts and completing a behavioural task. The task included a questionnaire with 9 functional items requiring participants to define, compare, interpret, and manipulate serving size and percentage daily value (%DV) information on NFts. Semi-structured interviews were conducted to further probe thought processes and difficulties experienced in completing the task. RESULTS: Equal serving sizes on NFts improved ability to accurately compare nutrition information between products. Most participants could define %DV and believed it can be used to compare foods, yet some confusion persisted when interpreting %DVs and manipulating serving-size information on NFts. Where serving sizes were unequal, mathematical errors were often responsible for incorrect responses. CONCLUSIONS: Results reinforce the need for equal serving sizes on NFts of similar products and highlight young Canadians' confusion when using nutrition information on NFts.

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)0.001
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 score0.095
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.056
GPT teacher head0.324
Teacher spread0.268 · 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

Citations29
Published2016
Admission routes3
Has abstractyes

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