Is Interoception Deficit Linking Alexithymia and Eating Spectrum Symptoms? Study on a Non-Clinical Sample of Young Adults
Bibliographic record
Abstract
We investigated if interoceptive deficits could be the link between alexithymic traits and eating spectrum manifestations in a non-clinical sample. One-hundred sixty-one young adults (mean age: 23.2 ± 2.4 years) were evaluated with the Toronto Alexithymia Scale-20 (TAS-20), the Interoceptive Accuracy Scale (IAS), the Interoceptive Confusion Questionnaire (ICQ), and the Eating Attitudes Test-26 (EAT-26). Questionnaires were administered with an online procedure (Microsoft Form, Office 365 A1, Pisa, Italy) (Study Protocol #0012005/2023). We compared ICQ, IAS, and TAS-20 scores in subjects who met the threshold for a potential eating spectrum disorder according to EAT-26 scores ≥ 20 (n = 27) vs. subjects who scored <20 (n = 134), with an ANCOVA corrected for ‘age’ and ‘gender’. Subjects with EAT-26 ≥ 20, scored significantly higher at ICQ (54.4 ± 13.2 vs. 50.2 ± 6.8; p = 0.011), TAS-20 ‘Total Score’ (60.8 ± 11.9 vs. 58.1 ± 9.2; p = 0.006), and TAS-20 ‘Identifying Feelings’ (21.5 ± 7.6 vs. 17.3 ± 5.8; p = 0.0001). A binary logistic regression analysis, with EAT-26 scores < 20 vs. ≥20 as the dependent variable, and ICQ, IAS, TAS-20 total scores and dimensions, age, and gender (categorical) as covariates, showed that the only variable predicting eating spectrum symptomatology was ‘ICQ Total Score’ (OR = 1.075, 95% CI: 1.016–1.139; p = 0.013). Interoceptive confusion was the dimension linking the occurrence of alexithymic traits and eating spectrum manifestations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".