Alexithymia, psychological signs, social support, and the levels of hematological parameters in diabetes
Bibliographic record
Abstract
AIM: The main aim of the study is to investigate relationship between alexithymia, psychological signs, social support, and hematological parameters (cholesterol, glycosylated hemoglobin, and blood sugar) in a sample of patients with type II diabetes.METHODOLOGY: One hundred and twenty-six patients with type II diabetes (38 males and 88 females) with a medical history in the division of diabetes of the health center no. 1 in Isfahan participated in the study in 2015. They filled in the Farsi version of Toronto Alexithymia Scale (Bagby, Parker and Taylor, 1994), social support questionnaire in chronic patients (Khodapanahi, 2009), and depression anxiety stress scales (Lovibond and Lovibond, 1995).RESULTS: The results showed that there was a positive significant relationship between cholesterol level and difficulty identifying and describing feelings (P < 0.05) and between glycosylated hemoglobin and anxiety and stress (P < 0.05). Furthermore, there was a negative significant relationship between fasting blood sugar and emotional support (P < 0.05).DISCUSSION: Therefore, it is therapeutically important to regard the psychological states of patients (especially alexithymia, psychological signs, and social support) to make a speedy recovery of type II diabetes.CONCLUSION: Regarding the results, it can be concluded that complexity and extent of effects of diabetes on an individual with alexithymia make diabetes difficult to treat and prevent its progress.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".