The role of early emotional neglect in alexithymia.
Bibliographic record
Abstract
Alexithymia is a personality trait associated with difficulties in identifying and communicating personal feelings. It is shown to be a risk factor for affective disorders. Previous studies have demonstrated the co-occurrence of alexithymia and early life stress in clinical samples; however, research in the absence of psychological and somatic disorders rarely exists. We therefore investigated alexithymia and early life stress in a high alexithymic but healthy community sample (n 46) in comparison with low alexithymic healthy subjects (n 44). Alexithymia was assessed by the Toronto Alexithymia Scale and BermondVorst Alexithymia Questionnaire. Emotional functioning was also measured using the Emotional Experience Scales. Early life stress was assessed by the Childhood Trauma Questionnaire and Early Trauma Inventory. There was a significantly positive correlation between alexithymia and early emotional neglect (EN) in the total sample (r .37; p .001), while physical or sexual traumata were not associated with high alexithymic features. EN also predicted the overall level of alexithymia. Within the high alexithymic group only, EN was related to significantly increased emotional dysfunction when controlling for alexithymia. The results show a first indication of differentiation between a “neglect” and a “nonneglect” subtype of alexithymia. We therefore conclude that EN should be taken into account in future studies on psychological functioning in alexithymia.
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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 | 0.002 |
| 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 | 0.000 |
| 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".