Examining the Relationship Between Alexithymia, Anger, and Self-Esteem in Patients Undergoing Hemodialysis
Bibliographic record
Abstract
Objective: The aim of this study was to examine the correlation between alexithymia, anger, and self-esteem in patients undergoing hemodialysis. Methods: The research was carried out in a descriptive cross-sectional design. The study was conducted with 152 hemodialysis patients between January 2021 and April 2021. The data of the study were collected using Personal Information Form, Toronto Alexithymia Scale, Rosenberg Self-Esteem Scale, and Trait Anger Scale. Numbers, percentage distributions, mean, SD, independent sample t-test, 1-way analysis of variance, Pearson’s correlation, and regression analysis were used in the data analysis. Results: A positive correlation was found between the alexithymia level and self-esteem scores. A positive correlation was found between anger level and alexithymia level. There was a positive correlation between self-esteem level scores and anger levels. It was determined that alexithymia explained 41.7% of the change in anger and self-esteem. It was determined that people with low self-esteem had high levels of alexithymia and anger levels. Conclusion: Alexithymia level had a signi!cant e"ect on anger and self-esteem in hemodialysis patients. As self-esteem decreases in hemodialysis patients, alexithymia and anger levels increase. As the anger level of the patients increases, the level of alexithymia increases. Cite this article as: Polat F, Delibas L, Ekren A. Examining the relationship between alexithymia, anger, and self-esteem in patients undergoing hemodialysis. Arch Health Sci Res. 2023;10(3):168-174.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| 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".