Social Cognitive Predictors of Breakfast Consumption in Primary School’s Male Students
Bibliographic record
Abstract
PURPOSE: This study aimed to test the usefulness of social cognitive theory (SCT) in explaining breakfast consumption in a sample of primary male students. METHODS: Participants in this cross-sectional study were 358 male students (3rd, 4th and 5th grades) from eight public primary schools of Ilam city. Data were collected by a self-administered questionnaire based on components of SCT. Bivariate correlations and multiple logistic regression analysis using an Enter method were used to identify social cognitive correlates and determinants of breakfast consumption. RESULTS: A total of 358 participants ranging in age from 8-12 years (M=10.06) were studied. The result of the study showed that the SCT significantly predicted breakfast consumption. SCT variables explained 41.4% of the variance in breakfast consumption behaviors, though, self-regulation was found to be the strongest predictor of breakfast consumption behaviors. There was the strongest correlation between behaviors and self-regulation, (r=0.561; P<0.001). CONCLUSION: The findings support the usefulness of SCT in explaining breakfast consumption behaviors. These results suggest an essential role for self-regulation, self-efficacy and social support in the breakfast consumption behaviors of primary male students.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".