Improvement of alexithymia in patients treated in mental health services for personality disorders: a longitudinal, observational study
Bibliographic record
Abstract
Background: The majority of mental health services include patients with personality disorder (PD) and comorbid conditions. Alexithymia, a psychological construct referring to difficulties in identifying and describing internal mental states, may represent a challenge to the psychotherapeutic treatment of patients with PD. This study aimed to investigate the prevalence of alexithymia among patients in specialized PD mental health services, differences according to PD severity and PD type, and the longitudinal course of alexithymia during treatment. Methods: The study included 1,019 patients treated in specialized PD treatment units, with 70% of them with personality difficulties above the PD diagnostic threshold [borderline PD, 31%; avoidant PD, 39%; PD not otherwise specified (PD-NOS), 15%; other PDs, 15%; and more than one PD, 24%]. Alexithymia was measured repeatedly throughout treatment using the Toronto Alexithymia Scale (TAS-20) self-report questionnaire. Supplementary outcomes included global psychosocial function and health-related life quality. Linear mixed models were applied for data analysis. Results: Alexithymia was highly prevalent in the sample: 53% of subjects reported high levels and 20% moderate levels. The TAS-20 subscale Difficulty Identifying Feelings was more strongly associated with borderline PD, while the subscale Difficulty Describing Feelings was more closely linked to avoidant PD. For all TAS subscales, poorer abilities were associated with more severe PD, higher levels of anxiety and depression, and poorer psychosocial functioning and life quality. Both alexithymia and measures of psychological functioning improved significantly during treatment with moderate effect sizes regardless of initial PD status. In total, 19% of the patients reported full remission of alexithymia. Conclusion: Alexithymia is a common problem among patients with PDs and is associated with mental health difficulties and psychosocial dysfunction, with rates varying across PD type and severity. The study demonstrates moderate improvement of alexithymia during treatment in specialized PD mental health services. Further research should evaluate the effectiveness of different treatments and interventions in reducing alexithymia among PD patients.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".