Bibliographic record
Abstract
OBJECTIVE: To review recent developments in alexithymia theory and research that are relevant to the field of psychosomatic medicine. METHOD: Articles were selected from the alexithymia literature published over the past decade that describe advances in the theoretical understanding of alexithymia or report empirical investigations of the relationships of the construct with emotion regulation and with somatic illness and disease. Empirical investigations of the neural correlates of alexithymia were reviewed also, as were studies that explore therapeutic attempts to modify alexithymic characteristics. RESULTS: The salient features of the alexithymia construct are now thought to reflect deficits in the cognitive processing and regulation of emotions. This is supported by studies showing that alexithymia is associated with maladaptive styles of emotion regulation, low emotional intelligence, a bidirectional interhemispheric transfer deficit, and reduced rapid eye movement (REM) density (number of eye movements divided by number of REM periods). Although empirical evidence demonstrates that alexithymia is associated with several somatic disorders, more prospective studies are required to establish the direction of causality. Preliminary data suggest that psychotherapies involving specific techniques to enhance emotional awareness and integrate symbolic and subsymbolic elements of emotion schemas may be effective in reducing alexithymic characteristics. CONCLUSION: Alexithymia is proving to be a heuristically useful construct for exploring the role of personality and emotions in the pathogenesis of certain somatic illnesses and diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".