The relationship of Alexithymia with anxiety-depression-stress, quality of life, and social support in Coronary Heart Disease (A psychological model)
Bibliographic record
Abstract
BACKGROUND: Although psychological factors are now recognized as playing a significant and independent role in the development of coronary heart disease (CHD) and its complications, many of these factors are correlated with each other. The present study is aimed at examining the association between alexithymia and anxiety depression, stress, quality of life, and social support in CHD patients. MATERIALS AND METHODS: In this research 398 patients with coronary heart disease (166 females and 232 males) from the city of Isfahan were selected using random sampling. The tools used included depression, anxiety, and stress scale (DASS-21), Health-related to Quality Of Life (HRQOL-26), Multiple Scale Perceived Social Support (MSPSS-12), and the Toronto Alexithymia Scale (TAS-20). The data were analyzed using structural equation modeling by using the Statistical Package for Social Science (SPSS21) (IBM Corp: Armonk, New York.U.S.) and Asset Management Operating System (AMOS21) SPSS, an IBM Company: Chicago, U.S. Software. RESULTS: Results of the structural equation model showed an acceptable goodness of fit, for the explanation alexithymia that was significantly associated with lower HRQOL and social support and increasing anxiety, depression, and stress. CONCLUSIONS: Alexithymia may increase anxiety, depression, and stress and can be a predisposing factor to poorer HRQOL and social support.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".