Are dietary pattern associated with alexithymia in Saudi adults?
Bibliographic record
Abstract
BACKGROUND: Alexithymia is characterized by difficulties in describing feelings and physical sensations. Few studies have shown that there is a relation between alexithymia and dietary habits. OBJECTIVES: To determine the prevalence of alexithymia and its association with dietary patterns among a sample of communities in the Eastern Region of the Kingdom of Saudi Arabia. MATERIALS AND METHODS: A cross-sectional study was conducted using a sample of 247 participants, were selected using convenience sampling. A well-organized and valid online questionnaire was administered, which covered variables related to socio-demographic data, anthropometric measurements, dietary patterns, and the Toronto Alexithymia Scale (TAS). RESULTS: The prevalence of Alexithymia was found as 39.3%. Moreover, among the alexithymia and possible alexithymia groups, the majority eat pasta 1-4 times per week (70% and 67% respectively). Alexithemic participants eat fewer vegetables and fruits 46%), while the remaining eat more (70%), p = .001. Only 34% of the cases eat breakfast regularly (p = .005). Furthermore, the cases drink soft drinks and juices at meals more than controls in this study (p = .025). CONCLUSION: The present study provides further experimental evidence which supports existing literature that indicating the strong association between alexithymia and unhealthy dietary patterns. Also, Alexithymia prevalence in our study is (39.3%) ; because of the cultural impact of the Saudi environment due to the fact that the face of Saudi women is not revealed, and because the face is one of the main sources of expression of feelings, which makes females unable to express or read feelings well.
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.
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 | 0.001 |
| 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".