Assessing Social, Emotional, and Economic Indicators of Eating Behavior Among University Students in Jordan
Bibliographic record
Abstract
This study aims to analyze the influence of social, emotional, and economic factors on shaping the eating behavior of university students by understanding the interconnected roles of family, community, mood, and living conditions in guiding their food choices. The results show significant differences across most variables, with the highest distribution within middle-income families (54.85%) and low-income families (53.19%). The mean BMI was 26.07, with significant correlations with weight and age. Social influence on eating behavior was moderate (M = 0.44), with the highest influence being social support (0.88) and the lowest influence being social pressure (0.20). The proportion of males in the household had a significant influence, with the highest means being found among small families, working families, and individuals with a low proportion of males. The influence of mood was low (M = 2.28), with a slight increase in taste-driven eating (2.43). No statistically significant differences were recorded between demographic and economic variables, except for a slight correlation with family size, with large families recording the highest mean (2.33). The economic impact was moderate (M=0.61), with rising prices of healthy foods being the main factor (0.81). Employment and income variables recorded significant effects, with the highest means appearing in large families (0.58), working families (0.59), and low-income families (0.63), indicating increased economic pressures with limited resources. Statistically significant positive relationships were found between the social index, age, and weight, and negative relationships with the mood index for age, weight, and height. The economic index was positively correlated with both age and weight. The study recommends strengthening family and community support, providing affordable, healthy food, and adopting policies that take into account individual and demographic differences in students’ eating behavior.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".