Theoretically Driven Intervention for Reducing Fast Food Consumption among Students: A Case of Theory of Planned Behavior
Bibliographic record
Abstract
Background The dramatic increase in fast food consumption among students, particularly adolescents and children, over the past two decades reflects a significant shift in lifestyle, with nearly one-third of these young individuals consuming ready-made foods on a daily basis.Purpose This study aims to evaluate the effect of an intervention based on the Theory of Planned Behavior (TPB) in reducing fast food consumption among high-school students.Methods One hundred and sixty Iranian high-school students were randomly assigned to an intervention or control group in a pretest-posttest-follow-up field trial. The intervention comprised four, 45-min teaching sessions over 3 weeks. Fast food consumption beliefs and self-report practices were assessed at pretest, posttest, and follow-up using a validated scale. Data analysis included descriptive statistics analyses-tests and ANOVA tests.Results Findings revealed a statistically significant difference in the posttest between experiment and control groups in the major components of fast food consumption including behavioral beliefs (t = 5.1, p < 0001), evaluation of behavioral outcomes (t = 5.3, p < 0001), normative beliefs (t = 2.3, p < 05), motivation to comply (t = 5.5, p < 0001), control beliefs (t = 4.4, p < 0001), perceived power (t = 3.3, p < 0001), and behavioral intention (t = .68, p < 0001). Similar results were obtained in the follow-up stage.Discussion Results suggest a parent-teacher participation intervention effectively reduced fast food consumption among high-school students, impacting both cognitive and behavioral factors. This model offers potential for customization to promote healthy food intake in wider student populations and beyond the school setting.Translation to Health Education Practice According to our findings, several suggestions can be addressed. First, considering the crucial role of parents and teachers in shaping healthy food habits, future studies should always consider them as a key component of the training intervention. Second, parents and teachers should be trained on how to best transfer and express their knowledge to children and adolescents with regard to their disapproval of fast food consumption. As our findings show, students can perceive this disapproval and change their own attitudes accordingly. Third, future studies are recommended to use multilevel interventions to prevent students from consuming fast food. For both students and parents, we suggest adding more professionally designed visual and graphical messages (e.g. Infographics) or short video clips into interventions that could effectively demonstrate the differences between beliefs related to the consumption of fast food and healthy foods.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".