Role of childhood trauma in interoception and alexithymia in schizophrenia
Bibliographic record
Abstract
Childhood trauma (CT) is a notable risk factor for schizophrenia. Separately, CT has been associated with alexithymia, referring to difficulties in identifying and describing one's own feelings, as well as disturbed interoception, referring to difficulties sensing and responding to signals that originate from within the body. Both self-perception impairments have been observed in schizophrenia; however, the role of CT in these observations in schizophrenia is unclear. To address this gap, interoception was assessed using the Multidimensional Assessment of Interoceptive Awareness (MAIA), alexithymia was assessed using the Toronto Alexithymia Scale (TAS-20), and CT was measured using the Childhood Trauma Questionnaire (CTQ) in a sample of 73 patients with schizophrenia or schizoaffective disorder (SSD) and 50 healthy controls. Patients had higher TAS-20 total score compared to controls (F = 36.0, p < 0.001) but groups were not different on any of the MAIA subscales. Across the full sample, CTQ total score was correlated with MAIA "trusting" subscale (ρ = -0.26, p = 0.005), and with TAS total score (ρ = 0.22, p = 0.016). Moreover, the MAIA "trusting" relationship remained significant within the SSD group. CT is associated with decreased feelings of trust in bodily sensations in schizophrenia, similar to findings in other major psychiatric disorders.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".