Resting vagally-mediated heart rate variability in the laboratory is associated with momentary negative affect and emotion regulation in daily life
Bibliographic record
Abstract
High frequency heart rate variability (HRV) is a vagally-mediated physiological index reflecting parasympathetic activity that has been linked to emotion regulation capacity. However, very limited research has examined associations of physiological indices of regulation such as HRV with emotional functioning in daily life. The few studies that exist have small samples sizes and typically focus on only a narrow aspect of emotion regulation or emotional functioning. In this study, we examined associations between HRV assessed in the laboratory and emotional/mental health functioning in daily life using a 7-day ecological momentary assessment design in 303 adult community participants. We hypothesized that higher resting HRV would be associated with higher positive affect, lower negative affect, less affective variability, greater wellbeing, fewer depressive and idiographic [person-specific] symptoms, greater use of engagement emotion regulation strategies, and less use of avoidance emotion regulation strategies, as assessed in daily life. Results revealed that higher resting HRV in the laboratory was significantly associated with lower negative affect and less frequent use of avoidance emotion regulation strategies in daily life, although only avoidance strategies remained significant when both were included in the same model. We also observed a trend association, such that idiographic symptoms in daily life were associated with lower resting HRV. Theoretical and clinical implications are discussed, including the association of HRV with negatively-valenced, rather than positively-valenced, daily life experiences.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".