Early affective empathy, emotion contagion, and empathic concern in borderline personality disorder: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Individuals with Borderline Personality Disorder (BPD) are theorized to experience lower cognitive empathy but heightened affective empathy. Despite meta-analyses addressing cognitive empathy, affective empathy remains unexplored. This pre-registered systematic review and meta-analysis investigated affective empathy in individuals with BPD or high BPD traits relative to healthy comparisons, using a multidimensional approach including, early affective empathy, emotion contagion, and empathic concern. METHODS: Systematic search of SCOPUS, PubMed, Medline COMPLETE, and PsycINFO (June 27, 2022, May 14, 2023, and July 1, 2024) was completed. Included studies compared affective empathy in those with BPD/high BPD traits with healthy comparisons, utilized experimental or self-report designs, and were peer-reviewed or PhD theses. Risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: = 189, g = 0.34, 95 % CI [-0.1.50, 2.18]). LIMITATIONS: Few included studies for early affective empathy, methodological shortcomings in the broader literature and study heterogeneity suggest caution when interpreting these effects, emphasizing the need for targeted research. CONCLUSIONS: While individuals with BPD/high BPD traits are more likely to subjectively experience others' distress through emotion contagion, no differences were found in early affective empathy or ability to direct sympathy and concern towards others.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.023 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".