Somatosensory amplification, health anxiety, and alexithymia in generalized anxiety disorder
Bibliographic record
Abstract
AIM: The aim of this study was to study somatosensory amplification, health anxiety (hypochondriasis), and alexithymia among patients with generalized anxiety disorder (GAD) and to evaluate the association of these variables with the severity of GAD. MATERIALS AND METHODS: Cross-sectional design was employed, and patients were recruited from the outpatient clinic of the psychiatry department of a multispecialty tertiary care medical institute in North India. The patients who were clinically diagnosed to have GAD by the two independent qualified psychiatrists were screened with Mini International Neuropsychiatry Interview to confirm the diagnosis. Forty patients with GAD meeting the inclusion criteria were assessed with GAD-7 scale, somatosensory amplification scale (SSAS), the Whiteley Index (WI) and Toronto alexithymia scale - 20 Hindi version (TAS-H-20). RESULTS: The mean scores of patients with GAD on SSAS, WI, TAS-H-20, and GAD-7 scale were 25.70 (SD-5.84), 7.75 (SD-3.30), 59.77 (SD- 8.63), and 13.37 (SD- 3.58), respectively. Half of the patients with GAD had significant health anxiety as defined by WI score of >7. Around 40% of GAD patients were alexithymic as defined with TAS-H-20 scores of >60. SSAS, WI, TAS-H-20 had a positive correlation with the severity of GAD as measured with GAD-7 scale. CONCLUSIONS: GAD patients have significant somatosensory amplification, health anxiety (hypochondriasis), and alexithymia. Accordingly, there is a need to develop effective psychological interventions focused on these factors in GAD.
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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) | 0.002 | 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".