Turkish Adaptation, Validity, and Reliability Study of Shitsu-Taikan-Sho (Alexisomia) Scale
Bibliographic record
Abstract
Background: The Shitsu-Taikan-Sho (Alexisomia) Scale is a self-report scale for measuring alexisomia, defined as the difficulty in awareness and expression of somatic emotions or feelings. The scale is available in Japanese and Finnish versions. This research aims to examine the psychometric properties of the Turkish version of the Shitsu-Taikan-Sho (Alexisomia) Scale. Methods: The study sample consists of 320 patients who applied to the outpatient clinic of consultation-liaison psychiatry. Participants completed the Sociodemographic Information Form, the Turkish version of the Shitsu-Taikan-Sho (Alexisomia) Scale, and the Toronto Alexithymia Scale. Internal consistency and test-retest reliability were used for reliability analyses. Exploratory factor analysis, confirmatory factor analysis, and co-validity analyses were used for validity analyses. Results: < .001). Conclusion: The Turkish adaptation of the Shitsu-Taikan-Sho (Alexisomia) Scale demonstrated adequate psychometric properties. It is an appropriate scale for evaluating the concept of alexisomia in the population of consultation-liaison psychiatry.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".