Reducing Fast Food Consumption in Students Using a Parent-Teacher Participation-Based Intervention: An Experimental Approach
Bibliographic record
Abstract
Abstract Background: Fast food consumption among students is increasing dramatically. 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. Method: 160 high school students from Iran were randomly recruited and assigned to experiment or control groups. The intervention was conducted over three consecutive weeks, consisting of four, 45-minute teaching sessions. Parameters were assessed on three occasions: pretest, posttest, and follow-up. In these stages, participants responded to a scale on fast food consumption which measures the beliefs and behaviors toward fast food. 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. Conclusion: The findings suggest that the parent-teacher participation based intervention can be used to reduce fast food consumption amongst high school students both cognitively and behaviorally. Moreover, this intervention can be further customized to increase healthy food consumption in school students and other age groups beyond the context of school.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".