Discriminative capacities of the Toronto Structured Interview for Alexithymia in different clinical situations
Bibliographic record
Abstract
Evaluation of alexithymia through self-report measures meets the difficulty of being dependent on the subject's capacity to report what (s)he feels and this very capacity is supposed to be deficient in alexithymics. Results may also be distorted by social desirability issues and defensive manouvers. Bagby et al. (2006) introduced the Toronto Structured Interview for Alexithymia (TSIA), where scores are not attributed by the subject but by the interviewer, on the basis of pertinent life examples. The original scale showed good psychometric properties. The Italian version (Caretti et al., 2011) confirmed the original 4-factor structure: Difficulty Identifying Feelings; Difficulty Describing Feelings; Externally Oriented Thinking; Imaginal Processes (the first three of which overlap with the corresponding factors of the TAS-20). The Italian version of the TSIA also demonstrated good internal and interrater reliability, and concurrent validity with the TAS-20. In order to begin testing the different discriminative capacities of the two instrument the TSIA and the TAS-20 were administered to different groups: general population; hypertensives; parents of children with emotional problems; subjects with common emotional disorders; subjects with eating disorders. It appears plausible that some of these groups may have difficulties in recognizing their deficit (somatic patients) or motives for denying them (parents). As expected, while the TAS-20 found differences with the general population only in Common Emotional Problems and in Eating Disorders, where subjects are clearly aware of some difficulty, the TSIA found high scores - in fact, the highest among groups - also in Hypertensives and in Parents. The TSIA appeared therefore capable to uncover deficits which were not apparent with the TAS-20.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".