Defining Alexithymia: The Clinical Relevance of Cognitive Behavioral vs Psychoanalytic Conceptualizations
Bibliographic record
Abstract
Alexithymia is widely seen as a risk factor for psychopathology, and is thus of high clinical interest. However, there is ongoing debate about the definition of alexithymia, much of which focuses on its externally oriented thinking (EOT) facet. Cognitive behavioral conceptualizations (i.e., the attention-appraisal model) define EOT in a manner specific to emotion processing, as difficulties focusing attention on emotions. Psychoanalytic conceptualizations define EOT more broadly, including difficulties attending to emotions, but also a tendency toward utilitarian thinking focused on the concrete details of the external world, which is closely linked with a reduced capacity for daydreaming. In this paper, across two studies (Ns = 508; 595), we examine the clinical relevance of both EOT conceptualizations via the strength of their associations with a range of clinical symptoms: depression, anxiety, stress, somatic symptoms, alcohol use problems, post-traumatic stress disorder, eating disorder symptoms, dissociation, and obsessive-compulsive disorder. Cognitive behavioral EOT was operationalised using the Perth Alexithymia Questionnaire and psychoanalytic EOT with the Toronto Alexithymia Scale-20. Across both studies, the cognitive behavioral conceptualization consistently demonstrated stronger relationships with clinical symptoms and explained more variance in regression models. Overall, our findings support the cognitive behavioral conceptualization of EOT, which shows higher clinical relevance.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".