Evaluation of Alexithymia, Anger and Temperament Features in Insomnia Patients with Sexual Dysfunction
Bibliographic record
Abstract
Aim: One of the most common sleep disorders is insomnia, and it is also an independent risk factor related to sexual dysfunction (SD). The aim of the present study was to investigate the anger parameters, temperament parameters, and alexithymia in insomnia patients with SD. Material and Methods: The study group consisted of 92 patients diagnosed with insomnia according to the third edition of the International Classification of Sleep Disorders. The sociodemographic data form, Temperament Evaluation of Memphis, Pisa, Paris and San Diego Auto-questionnaire (TEMPS-A), Insomnia Severity Index (ISI), Toronto Structured Interview for Alexithymia (TSIA), Arizona Sexual Experiences Scale (ASEX), Pittsburgh Sleep Quality Index (PSQI), State-Trait Anger Expression Inventory (STAXI) were applied to the patients. Results: While 62 patients had SD, 30 patients had no SD. ISI, PSQI, anger in score were significantly higher in patients with SD (p=0.048, p=0.007, p=0.032, respectively). While depressive and anxious temperament was significantly higher in patients with SD (p=0.026, p=0.008, respectively), hyperthymic temperament was significantly higher in patients without SD (p=0.013). ISI score, depressive, and anxious temperament were significantly correlated with the ASEX score (r=0.214, p=0.041; r=0.261, p=0.012; r=0.286, p=0.007, respectively). Linear regression revealed that depressive, cyclothymic, and irritable temperaments were predictors of ISI (p=0.001). According to logistic regression, hyperthymic temperament was an independent predictor of SD (p=0.001). Conclusion: Psychological factors should also be considered in studies conducted on the relationship between insomnia and SD. Further research is needed on temperament characteristics, alexithymia and anger issues. Thus, patients can be approached more comprehensively.
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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 | 0.001 | 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) | 0.001 | 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".