The relationship between alexithymia, health literacy, and diet quality in obese adolescents
Bibliographic record
Abstract
OBJECTIVES: Alexithymia and low health literacy are the barriers of self-management. This study aims to examine the relationship between alexithymia, health literacy and diet quality in obese adolescents, and their effects on anthropometric and biochemical markers. METHODS: The 20-item Toronto alexithymia scale (TAS-20) was used to determine the alexithymic traits of the adolescents, and "The Newest Vital Sign" (NVS) scales were used to determine their health literacy levels. Diet quality was evaluated with the Healthy Eating Index-2010 (HEI-2010). RESULTS: 39.7% of the obese adolescents were alexithymic, and 69.4% of alexithymics and 35.1% of non-alexithymics had metabolic syndrome. Alexithymic adolescents were lack of adequate health literacy. There were positive correlations between alexithymia scores and insulin, triglyceride, systolic and diastolic blood pressure levels, and all anthropometric values except height (p<0.05). There was a negative correlation between alexithymia scores and health literacy scores (p<0.05). There were negative correlations between health literacy and alexithymia scores, insulin, total cholesterol, triglyceride, ALT, systolic, diastolic blood pressure levels and all anthropometric values except height, and positive correlation was observed between health literacy scores and diet quality (p<0.05). Total HEI score was negatively correlated with waist circumference, neck circumference, body weight, BMI, triglyceride, AST, ALT, systolic and diastolic blood pressure, and positively correlated with health literacy and HDL levels (p<0.05). CONCLUSIONS: As alexithymia severity increased in obese adolescents, the degree of obesity and the incidence of metabolic syndrome increased while the level of health literacy decreased. The increase in health literacy levels, on the other hand, decreased the level of alexithymia and increased the quality of the diet.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".