Alexithymia and affect regulation: A clinimetric study
Bibliographic record
Abstract
Introduction The concept of alexithymia refers to difficulties in identifying and verbalizing emotions, an externally oriented thinking style and a paucity of fantasy. Theoretically and clinically we expect typical ways of regulating affect in alexithymic individuals. The few existing studies on this topic mainly rely on self-report methods, which are inherently problematic since affect representation and affect regulation are not conscious processes. Objectives/aims This study investigates whether alexithymia is associated with dysfunctional methods of affect regulation using clinical ratings of interviews. We hypothesize that alexithymic individuals will use affect regulation methods that do not reflect psychic mediation (H1) and will be unable to solicit cognitive resources (H2) or social support (H3) when confronted with emotional distress. Methods 51 psychiatric in-patients were interviewed with 1) the Clinical Diagnostic Interview which was coded with the Affect Regulation and Experiences Q-sort (ARE-q) and 2) the Toronto Structured Interview for Alexithymia (TSIA). Results In general, alexithymia was positively related to avoidant defenses and negatively to reality focused responses. On item level, we found relationships with for example self-destructive behavior and dissociation (H1), items referring to the inability to use self-talk to cope with distress and the inability to anticipate problems and develop realistic plans for them (H2), and finally a negative relation with ‘responds to potentially distressing situations by talking directly to the people involved.’ (H3). Conclusions Alexithymia is associated with typical dysfunctional methods of affect regulation. This should be taken into account in the diagnostic process as well as treatment for 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".