HERITABILITY OF SOCIAL ANXIETY-RELATED CONCERNS AND PERSONALITY CHARACTERISTICS: A TWIN STUDY
Bibliographic record
Abstract
Negative evaluation fears figure prominently in the cognitive psychology of patients with social phobia. In this study, we examine the heritability of negative evaluation fears by using a twin sample. The authors also examine the relationships between negative evaluation fears and personality dimensions relevant to social phobia. Scores on the brief version of the Fear of Negative Evaluation Scale (BFNE) were examined in a sample of 437 (245 monozygotic and 192 dizygotic) twin pairs. Biometrical model fitting was conducted by using standard statistical methods. Genetic and environmental correlations with personality dimensions (from the Dimensional Assessment of Personality Pathology-Basic Questionnaire) were also calculated. Broad heritability estimate of the BFNE was 48%. Additive genetic effects and unique environmental effects emerged as the primary influences on negative evaluation fears. Genetic correlations between BFNE scores and the submissiveness, anxiousness, and social avoidance facets of the Dimensional Assessment of Personality Pathology-Basic Questionnaire were high (r(g) =.78 to.80). A cognitive dimension central to the phenomenology (and, perhaps, cause) of social phobia, the fear of being negatively evaluated, is moderately heritable. Moreover, the same genes that influence negative evaluation fears appear to influence a cluster of anxiety-related personality characteristics. Implications and limitations of these findings are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".