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Record W2741139578 · doi:10.5539/jfr.v6n4p150

A Retrospective Study on Changes in Food Preferences of Japanese High School Students from Childhood to the Present Day

2017· article· en· W2741139578 on OpenAlexvenueno aff
Tomoko Osera, Mitsuyo Awai, Setsuko Tsutie, Misako Kobayashi, Nobutaka Kurihara

Bibliographic record

VenueJournal of Food Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Technology, Consumer Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsFood preferenceOdds ratioConfidence intervalLogistic regressionPsychologyOddsDemographyPreferenceEarly childhoodMedicineDevelopmental psychologyFood science

Abstract

fetched live from OpenAlex

Background: To conduct a retrospective study for investigating changes in food preferences of high school students from childhood to the present day.Methods: The study included 1,300 students aged 16–18 years who responded to a questionnaire regarding food items that they disliked at present and in their childhood; they selected a list of 55 foods and responded to 35 questions regarding their food habits. The distribution was categorized into four patterns of food preferences based on whether a particular student had disliked a particular food item during childhood (+) and during high school at present (+). Food preference at present was examined for all other items using logistic regression analysis after adjusting for gender and age. Results: In total, 66.9% of the subjects reported (+) to (+), 12.5% reported (+) to (−), 6.5% reported (−) to (+), and 14.1% reported (−) to (−). Even in the (+) to (+) group, a significant decrease was observed in the number of disliked foods from childhood (5.5 ± 5.4) to the present day (4.2 ± 4.1) (P < 0.001, ANOVA). No dislike for any food item at present was related to no dislike for any food item during childhood [odds ratio (OR), 12.57; 95% confidence interval (CI), 8.3–19.1]] and talking positively about food (OR, 1.28; 95% CI, 1.11–1.49) but inversely related to the limited use of smartphone while eating (OR, 0.86; 95% CI, 0.75–0.98). Conclusion: Decreasing the dislike for foods at present as well as no dislike for any food item during childhood may be crucial for developing future good food habits in high school students. In addition, to improve current food preferences, students may need to eat together.

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)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.005
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 head0.263
GPT teacher head0.546
Teacher spread0.283 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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