HRV reactivity and new romance: cause or consequence?
Bibliographic record
Abstract
This study explored two competing hypotheses explaining the association of heart rate variability (HRV) and romantic relationships. HRV refers to the variation between successive heartbeats and is considered to be a noninvasive index of the social engagement system. Recent cross-sectional research has shown differences in HRV reactivity (the difference between HRV during the presentation of positive and negative stimuli) between single and newly coupled individuals. Two opposing explanations for this association were hypothesized. First, beginning a romantic relationship may decrease HRV reactivity through increased activation of the social engagement system during courting. Alternatively, this association could be explained by individuals with initially lower HRV reactivity being more likely to form romantic relationships. In the present study, single female undergraduate students were presented with film clips of various valences while having their cardiac activity monitored. These participants then returned for follow-up either when they had begun a romantic relationship, or at the end of the 6-month observation period if they remained uncoupled. Moderating influences of body mass index (BMI), self-esteem, attachment, and emotional distress were assessed. Results revealed single and coupled participants were comparable in terms of their HRV reactivity at follow-up; neither group showed a significant decline in HRV during the negative film clip. Further, HRV was not systematically affected by a change in relationship status from single to newly coupled. However, lower HRV reactivity was predictive of coupling for low BMI women while the reverse was true for high BMI women. This interaction may be the result of differing success rates of various mating strategies for low and high BMI women. Results support the hypothesis that HRV reactivity, along with BMI, can predict the formation of romantic relationships.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".