Social Contagion of Vasovagal Symptoms in Blood Donors: Interactions With Empathy
Bibliographic record
Abstract
BACKGROUND: Vasovagal reactions (VVRs) are commonly experienced in medical situations such as blood donation. Many believe that psychosocial contagion can contribute to the development of VVRs, but this is largely clinical lore. PURPOSE: The goal of the present investigation was to examine the physiological effects of observing another experience a reaction, focusing on the potential moderating effects of empathy. METHODS: This study was part of a randomized controlled trial of behavioral techniques on the prevention of VVRs in blood donors. The sample was composed of 530 healthy university students. Measures of symptoms were obtained with the Blood Donation Reactions Inventory (BDRI) and through observation. Physiological variables were measured using respiratory capnometry and a digital blood pressure monitor. The Affective and Cognitive Measure of Empathy was administered to 230 participants. RESULTS: Donors who witnessed another experiencing a reaction were more likely to spontaneously report symptoms during the blood draw, to be treated for a reaction, to score higher on the BDRI, and to exhibit smaller compensatory heart rate increases. Donors with higher affective empathy reported more symptoms, exhibited hyperventilation, and were more likely to be treated. Donors with higher cognitive empathy were less likely to require treatment if they witnessed a reaction. CONCLUSION: These results suggest that psychosocial contagion of physical symptoms can occur. The moderating effects of empathy differed depending on the subtype of empathy. Perhaps a better cognitive understanding of how other people are feeling functions as a coping response, whereas feeling sympathetic about others' distress increases one's own.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".