Social media and eating habits: A study on the relationship between digital consumption and eating behavior
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social media plays a fundamental role in shaping eating habits, especially among young people, since their use through digital platforms has transformed the way they access information about nutrition, recipes, diets, and healthy lifestyles. Constant exposure to visual content and messages related to food directly influences daily decisions about what, how, and when to eat. The study aimed to establish the relationship of social media with eating habits in university students from a private university in the city of Huancayo, located in the Junín region of Peru. The research was basic under a quantitative approach with a cross-sectional section, the population was made up of 311 university students enrolled in the 2025-I academic period. The results were processed through structural equations using the Jamovi program. These results indicate a high degree of relationship between the study variables, given that the Spearman Rho correlation coefficient was 0.832 and 0.000 as the significance level, demonstrating a strong, positive relationship. The study concluded that there was a strong, significant relationship between the dimensions of the social media use variable (network use, platform type, social interaction, and personal and social impact) and eating habits.
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.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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