Psychosomatic complaints profile in patients with type 2 diabetes: a matched case-control study
Bibliographic record
Abstract
To compare the prevalence of psychosomatic symptoms and their mean scores of profiles in diabetic patients and sample of sex-age-matched healthy controls. This case-control study was conducted on 87 patients with type 2 diabetes. The control group consisted of 259 age- and gender-matched healthy participants. Psychosomatic symptoms were assessed using a comprehensive 31-item questionnaire, and psychological problems were evaluated by 12-item General Health Questionnaire and Hospital Anxiety and Depression Scale. Factor analysis, independent Student’s t test, analysis of variance, and chi-square test were used for analyzing of data. The frequency of 18 psychosomatic symptoms was significantly higher in diabetic patients with psychological problems compared with controls ( P < 0.05), and the most frequent were “severe fatigue” (54.3%), “feeling low on energy” (48.6%), “disturbing thoughts” (45.7%), “pain in the joints” (34.3%), and “eyesore” (32.4%). There were significant differences in terms of “psycho-fatigue” ( P ≤ 0.0001), “gastrointestinal” ( P = 0.018), “neuro-skeletal” ( P = 0.001), and “pharyngeal-respiratory” ( P = 0.009) profiles between studied groups. In conclusion, diabetic patients with psychological problems had a higher frequency of psychosomatic symptoms and also higher scores of psychosomatic disorder profiles than control participants. However, further prospective investigations are required to assess whether the psychosomatic disorder/symptom pattern was caused by conditions of diabetes disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".