EPA-0687 – I have words for feelings: a longitudinal study of alexithymia in personality disorders.
Bibliographic record
Abstract
While several theoretical models imply that personality disorders (PD) show an altered cognitive processing of emotions (alexithymia), empirical evidence linking alexithymia with PD is controversial. investigating whether alexithymia is associated with PD regardless of psychopathology severity. 1) evaluating the association between alexithymia (Toronto Alexithymia Scale, TAS-20) and PD, controlling for comorbid psychopathology severity; 2) evaluating whether alexithymia decreases over a 2-year follow-up as a function of the remission of PD, Axis I disorder or their interaction. 167 psychiatric outpatients (56 males) completed the Structured Interviews for DSM-IV Personality and Axis I disorders, the General Severity Index (GSI) of the Symptom- Checklist-90 and the TAS-20. At two-years follow-up, patients who had both an Axis I and II disorder at baseline (n=121) were re-evaluated, and TAS-20 reduction was calculated. The association between PD, TAS scores and severity and presence of Axis I disorders was assessed using Hayes’(2012) bootstrapping procedure for conditional effects. At baseline PD criteria predicted TAS-20 score at low (CI=.238-1.364, p=.006) and average (CI=.153-.757, p=.003) levels of GSI, but not at high GSI scores (CI=-.174-.393, p=.44). At follow-up, TAS-20 reduction did not differ between non-remitted and remitted PD patients, but was higher among patients remitted from their Axis I conditions. However, the remission from PD was associated with a greater decrease in ‘Externally Oriented Thinking’ for men who still had an Axis I disorder (B=11.95, p=.01, CI= 2.33-21.57). The relationship between alexithymia and PD could be influenced by comorbid psychopathology severity and gender.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".