Comparing the relationship between emotional responsiveness and psychopathy across assessment types: a systematic review and meta-analysis
Bibliographic record
Abstract
Although psychopathic personality traits are widely reported to be related to reduced reactivity to emotion-eliciting situations, findings are not consistent. It has been argued that these differences could be related to variations in the way psychopathy is measured. To examine whether measurement variance resulting from the use of clinical assessment versus self-report assessment could be driving such differences, this systematic review and meta-analysis investigated the comparability of relations between psychopathic traits and responsiveness to emotion-inducing tasks for clinical versus self-report measures. The systematic review resulted in eight studies and 131 effect sizes, which included studies of emotion categorization, emotion regulation, decision-making, and executive functioning tasks. Robust Variance Estimation correlated effects models revealed no significant differences between effect sizes for clinical (PCL-R) versus self-report (PPI, SRP, and LSRP) assessment-based psychopathic traits and emotion tasks. Despite the small number of studies that included both clinical and self-report assessments of psychopathy, these results do not provide any evidence for an assessment-based difference in correlations with emotional responsiveness across tasks. The findings also show no associations between scores on emotional responsiveness and indices of psychopathy. Future research on emotional responsiveness in psychopathy should include both assessment types to be able to increase the research basis for the comparison.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".