Can alexithymia be assessed through an interview in adolescents? The Toronto Structured Interview for Alexithymia: Reliability, concurrent validity, discriminant validity, and relationships with emotional-behavioral symptoms
Bibliographic record
Abstract
Alexithymia is connected to adolescents' psychopathology, but the current methods of assessment present limitations. The Toronto Structured Interview for Alexithymia (TSIA) was developed to overcome the limits of the main used self-rating scale in adults, but no studies investigated its feasibility with adolescents. This study involved 95 community adolescents aged 12-19 years. Adolescents were assessed with the TSIA, the 20-item Toronto Alexithymia Scale (TAS-20), the Verbal Comprehension Index of the WISC-IV for verbal skills, and the Child Behavior Checklist and Youth Self Report for emotional-behavioral symptoms. The aims were to investigate the TSIA internal consistency, concurrent validity with the TAS-20, discriminant validity with participants' verbal skills, and relationships with emotional-behavioral symptoms. TSIA showed good internal consistency, concurrent validity with the TAS-20 (except for factor DDF), and independence by participants' verbal skills, but few relationships with emotional-behavioral symptoms. In conclusion, TSIA showed some good psychometric proprieties but little convergence with research findings obtained with the TAS-20, suggesting the need for further research to check the feasibility of using the TSIA with adolescents. Meanwhile, a precautionary multi-method assessment of alexithymia is recommended.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".