The Psychometric Properties of the DS14 in Hebrew and the Prevalence of Type D Personality in Israeli Adults
Bibliographic record
Abstract
Objectives: To examine the psychometric properties of the 14-item Type D Scale (DS14) in Hebrew, and to estimate the prevalence of Type D personality (high negative affectivity and social inhibition) in Israeli adults. Methods: 1,350 consecutive community volunteers were recruited and completed questionnaires that included the DS14, the 140-item Temperament and Character Inventory (TCI-140), the Toronto Alexithymia Scale-20 (TAS-20), the Positive and Negative Affect Scale (PANAS), social support, well-being, assessment of smoking behavior, physical and sexual activity, known medical diagnoses, and family history of coronary heart disease (CHD). Results: The structural validity, as demonstrated by exploratory and confirmatory factor analysis, and the internal reliability of the DS14 was acceptable. Overall prevalence of Type D was 24.1%; individuals of Type D versus non-D were significantly higher in self-reported rates of hypertension, CHD diagnosis, and first-degree relatives diagnosed with CHD. They were also elevated for TCI-140 Harm Avoidance, as well as negative affect, alexithymia, and significantly lower in TCI-140 Novelty Seeking, Reward Dependence, Persistence, Self-Directedness, and Cooperativeness, as well as in subjective well-being, social support, and positive affect. Conclusion: The DS14 in Hebrew has good psychometric qualities, supporting cross-cultural validity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".