Assessing Alexithymia and Type A Behavior in Coronary Heart Disease Patients: A Multimethod Approach
Bibliographic record
Abstract
BACKGROUND: Despite increasing emphasis on using multiple methods to assess personality constructs in psychosomatic research, previous investigations of relations between alexithymia and type A behavior (TAB) have been limited by the use of single methods of measurement and almost no attempt to assess subcomponents of TAB. The aims of this study were to (1) evaluate levels of agreement between structured interview assessments of alexithymia, TAB, hostility, and time urgency and well-established self-report measures of these constructs, and (2) explore relations between alexithymia and TAB and its subcomponents in patients with coronary heart disease (CHD). METHODS: 62 CHD patients were investigated 6 weeks after coronary angioplasty. Alexithymia was assessed with the Diagnostic Criteria for Psychosomatic Research (DCPR) and the 20-item Toronto Alexithymia Scale (TAS-20). TAB was assessed with the DCPR and the Short Form of the Jenkins Activity Survey Type A scale (JAS-SF). Time urgency was assessed with the DCPR and the Speed/Impatience scale of the Jenkins Activity Survey (JAS-S), and hostility was assessed with the DCPR and the Hostility subscale of the Revised Symptom Checklist-90 (SCL-HOS). RESULTS: The DCPR classifications showed reasonably high levels of agreement with the TAS-20 and JAS-SF classifications of alexithymia and TAB, but lower levels of agreement in identifying patients with high hostility on the SCL-HOS and high time urgency on the JAS-S. Alexithymia measured by both the DCPR and the TAS-20 was unrelated to both self-report and structured interview measures of TAB, hostility, and time urgency. CONCLUSIONS: The DCPR is a suitable screening instrument for assessing alexithymia and TAB, although the two constructs are unrelated.
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 | 0.008 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".