Correlation Of Psychosomatic Factors And Personality Traits With The Severity Of Hidradenitis Suppurativa
Bibliographic record
Abstract
Introduction: Hidradenitis suppurativa is a disease with a decisive burden on sufferers, both physical and psychological. It was expected that the more intense the severity of symptoms the patients experienced, the greater the correlation with the psychosomatic manifestations would be. Objectives: The present study aimed to explore the correlation between hidradenitis suppurativa and the psychosomatic burden, the personality, and the demographic characteristics of the participants. Methods: The participants were 90 outpatients of the hospital, aged 18 to 65, who had been diagnosed with hidradenitis and were sufficiently proficient in Greek. The psychometric instruments administered were the Symptom Checklist-90 (SCL90), the Beck Depression Inventory (BDI), the Eysenck Personality Questionnaire (EPQ), the short-form McGill Pain Questionnaire (SF-MPQ), the Hurley and refined Hurley classifications, the International Hidradenitis Suppurativa Severity Scoring System (IHS4), and a short demographic questionnaire. All statistical analyses were performed using the SPSS-28 statistical package. Results: According to statistical analyses, there was no statistically significant relationship between disease severity, psychosomatic burden, and personality. However, there were statistically significant associations with demographic factors, such as being female or not being in a relationship, the patient’s body mass index, the locus of the skin lesion, a history of hospitalization, comorbidities, psychiatric history, and pain with psychopathological manifestations and personality. Conclusions: It is important that further research be conducted that will include more mental disorders besides anxiety and depression while at the same time excluding confounding factors for safer interpretation of the results.
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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 | 0.000 | 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 | 0.001 |
| 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".