The Effective Factors for Fruit and Vegetable Consumption among Adults: A Need Assessment Study Based on Trans-Theoretical Model
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The World Health Organization recommended consuming at least 5 servings of fruits and vegetables (FV) per day in order to reduce the risk of non-communicable diseases (NCDs). The purpose of this study is to determine the influential factors related to intake of FV among adults in Kermanshah city based on Transtheoritical Model. MATERIAL & METHODS: This is a cross-sectional study which is conducted in Kermanshah city. Participants (n=1230) are selected by multi stage sampling; 30-50 year olds people covered by health centers. In order to collect data, we used a TTM-based questionnaire. The results are analyzed using SPSS-16 and Lisrel 8, with P< 0.05 as statistically significant level. RESULTS: The mean age of the participants is 37.75 and 65% of them are women .The mean score of knowledge is 2.4; that is, 80% of men and 78% of women in this study are in poor knowledge about FV consumption. In case of fruit and vegetable consumption behavior, 50% and 61% of participants are in pre-contemplation/contemplation stage, respectively. The average number of fruit servings is 1.42 and the average number of vegetable servings is 0.99 per day. Also, ANOVA test results showed a significant correlation between constructs of TTM and stages of change so that individuals' progress through stages of change from pre-contemplation to maintenance added on the scores of self-efficiency, processes of change, and decisional balance. CONCLUSION: This study indicated that, TTM constructs such as self-efficacy, processes of change, and decisional balance are good predictors for FV consumption.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it