The Psychosocial Determinants of Obesity Associated with Food Intake (Narrative Review)
Bibliographic record
Abstract
Obesity is known as a major public health problem, with multi-factorial aspects. A complex interaction among genetic, physiological, and behavioral variables affects both the development and maintenance of the obese condition. Currently, there is an increasing interest in recognizing the significant role of psychosocial determinants of dietary behaviors to develop effective interventional weight loss programs. A review of the existing knowledge about the psychosocial determinants of food intake may be beneficial for developing dietary behaviors for health promotion among the populations. Differences in the psychosocial determinants of eating between obese and nonobese individuals and youth and adult groups provide a better understanding of the drivers of socioeconomic disparities in dietary intake, and how to develop targeted intervention strategies. In this review, we discussed the basic psychosocial concepts and theories related to food behaviors. Then, the psychological factors associated with the obesity-related food behaviors and the comparisons between the correlates of dietary behavior in obese and non-obese individuals were explained. Finally, the results of population-based studies which have addressed the contribution of dietary behavior among the youth and adults were presented.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".