Obesity, alexithymia and psychopathology: a case-control study.
Bibliographic record
Abstract
OBJECTIVE: The relationship between psychopathology and alexithymia in obese patients is uncertain. The present study was performed to evaluate this relationship in a clinical sample of patients attending a centre for the diagnosis and treatment of obesity compared to a matched sample of non-obese subjects. METHODS: 293 consecutive obese patients (48 males, 245 females, mean age 45, 41±13.55 yrs; mean BMI 35.60±6.20) were compared with a control group made of 293 non-obese subjects (48 males, 245 females, mean age 45, 66±13.86 yrs; mean BMI 21.8±2.06); all subjects were interviewed by means of SCID I and SCID II together with several self-evaluation instruments including the TAS-20 (Toronto Alexithymia Scale) and SCL-90 (Symptom Check List, Revised). RESULTS: Alexithymia was significantly more frequent among obese patients compared to "normal" controls (12.9% vs 6.9%, p=0.010); moreover obese patients achieved significantly higher mean scores on subscales 1 and 2 and on overall scale of the Toronto Alexithymia Scale; comorbidity with axis I/II disorders, in particular Binge Eating Disorder, was associated with a significantly higher frequency of alexithymic traits and higher scores at TAS. CONCLUSIONS: Alexithymia and psychopathology are strongly correlated among obese patients seeking treatment. Routine evaluation of personality traits and comorbid psychopathology may be relevant in treatment of obesity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".