Alexithymia according to Bucci's multiple code theory: A preliminary investigation with healthy and hypertensive individuals
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relation between alexithymia and Referential Activity (RA), a linguistic measure of the process by which non-verbal emotional experience is connected to language. METHODS: The 20-Item Toronto Alexithymia Scale (TAS-20) and the Toronto Structured Interview for Alexithymia (TSIA) were administered to 20 postgraduate students and 15 outpatients with hypertension. The Weighted Referential Activity Dictionary (WRAD) and other linguistic measures (Reflection, Disfluency, and Somatic Sense) were applied to texts derived from the TSIA using the Discourse Attributes Analysis Program (DAAP). RESULTS: Multiple linear regressions performed in the whole sample showed a relation between TSIA scores and Somatic Sense. Comparing the two groups, hypertensive subjects yielded higher scores on the TSIA than the young adult sample; no differences in DAAP measures emerged. A significant negative correlation was found between the TAS-20 Difficulty Describing Feelings score and the DAAP measure of references to body activations (Somatic Sense) both in the young adult sample and in hypertensives. In the young adult sample, negative relations emerged between different TSIA factors, WRAD score, and Somatic Sense; a positive relation with fragmented speech (Disfluency) and use of rationalization (Reflection) was also found. In hypertensive subjects, using the TSIA, a negative correlation between alexithymia and Somatic Sense and a positive correlation between alexithymia and the Mean High WRAD (a measure of intensity of engagement during the speech) were found. CONCLUSION: The TSIA seems to be a more adequate instrument than the TAS-20 to explore relations between alexithymia and RA. Results appear to suggest a complex, nonlinear relation between alexithymia and RA, presumably influenced by subject-specific characteristics. PRACTITIONER POINTS: A relation between alexithymia and RA has been proposed on theoretical grounds, but there has been minimal empirical investigation. This was the first study to employ both a self-report measure and a structured interview for measuring alexithymia in relation to RA. The results of this study suggest a complex, nonlinear relation between alexithymia and RA; this finding is essentially obtained with the structured interview measure of alexithymia. This relation is presumably influenced by subject-specific characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".