Stages of Behavioral Change for Fruit and Vegetable Intake in Adolescents: A School-Based Cross-Sectional Study in Japan
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to understand why adolescents choose to eat fewer fruits and vegetables by examining the stages of behavioral change and perceived barriers to fruits and vegetable intake in a school-based study in Japan. METHODS: A cross-sectional survey was performed at junior and senior high schools from 2018 to 2020, and 933 students aged 12–18 agreed to participate. A questionnaire obtained information on demographic characteristics, daily fruit and vegetable intake, and to assess the stage of change regarding eating more fruits and vegetables and barriers faced by the participants. RESULTS: The daily average amount of fruit and vegetable intake was 89.3 g and 178 g, respectively. In response to whether they were “Eating 350 g or more vegetables and 200 g or more fruits a day most day,” 52.6% answered “not thinking about doing it” (precontemplation stage); the ratio was particularly high among males (61.1%). Moreover, as the stage of change increased from precontemplation to action/maintenance, the daily intake of fruits and vegetables increased and the perceived barriers decreased. We also found that environment when dining out, personal habits, and family and self-preference were perceived as the most important factors related to barriers to eating more fruits and vegetables. CONCLUSION: This study suggests that stage-tailored interventions need to target the above-mentioned barriers, particularly for students in the precontemplation and contemplation stages, and to enhance knowledge on the health benefits of fruits and vegetables, as well as consider a gender-specific approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".