Alexithymia Assessed through Auditory-Affective Perception and Interpersonal Problems as Mediators of the Relationship between Trauma and Depression
Bibliographic record
Abstract
Alexithymia involves difficulties identifying and describing emotions and externally-oriented thinking, and is associated with numerous psychological problems. Though commonly assessed through self-report questionnaires, the present study also used a performance-based neuropsychological measure of auditory-affective perception (AAP). Hypotheses were: (1) AAP would be associated with self-reported alexithymia, and (2) AAP, alexithymia, and interpersonal problems would mediate the relationship between trauma exposure and depression. Fifty-three undergraduate students pre-screened for trauma exposure reported above-average alexithymia and interpersonal problems, mild trauma exposure and depression, and made an average number of AAP mistakes. Regression analyses supported self-reported alexithymia as a partial mediator of the relationship between trauma exposure and depression, suggesting that depressive symptoms developed following trauma exposure are partially related to the development of alexithymic symptoms. AAP performance was not significantly correlated with the measure of alexithymia, suggesting self-reported alexithymic symptoms are independent of the ability to recognize auditorially-presented emotions; possible explanations are discussed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".