Auditory sensation with affective agnosia: A prevalence of alexithymia among tinnitus patients
Bibliographic record
Abstract
OBJECTIVES: The aim of the present study was to determine the prevalence and association of alexithymia, depression, and anxiety in patients affected by tinnitus. METHODS: The study was conducted among the patients referred for audiometric evaluation for tinnitus. They were further evaluated with the Hospital Anxiety and Depression Scale, the Tinnitus Handicap Inventory, and the Toronto Alexithymia Scale. Analysis was done for prevalence and the sample was categorized as high and low tinnitus handicap subgroups, and mean scores of alexithymia, anxiety, and depression were compared. RESULTS: A total of 70 patients (55.7% - male and 44.3% - female) with a mean age of 33.17 ± 12.24 years were finally analyzed. The severity of tinnitus was most severe (34.3%), followed by moderate (20%), catastrophic (18.6%), mild (17.1%), and slight (10%). The prevalence of alexithymia, anxiety, and depression among patients of tinnitus was found to be 65.7%, 37.1%, and 20%, respectively. The high tinnitus handicap group showed higher scoring on total alexithymia score, anxiety, and depression and higher scoring with describing emotion and identification of emotion, but there was no difference for the subscale of externally oriented thinking. CONCLUSIONS: The study found a prevalence of alexithymia, anxiety, and depression as 65.7%, 37.1%, and 20%, respectively, among patients of tinnitus, and problem of describing and identification of emotion are associated with higher tinnitus handicap.
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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".