Social Integration Prospectively Predicts Changes in Heart Rate Variability Among Individuals Undergoing Migration Stress
Bibliographic record
Abstract
BACKGROUND: Poor social integration increases risk for poor health. The psychobiological pathways underlying this effect are not well-understood. PURPOSE: This study utilized a migration stress model to prospectively investigate the impact of social integration on change in high-frequency heart rate variability (HF-HRV), a marker of autonomic functioning. METHODS: Sixty new international students were recruited shortly after their arrival in the host country and assessed 2 and 5 months later. At each assessment period, participants provided information on social integration and loneliness and had their resting HF-HRV evaluated. RESULTS: There was an overall decrease in HF-HRV over time. The magnitude of the within-person and between-person effects of social integration on HRV increased over time, such that greater social integration was associated with higher HF-HRV at later follow-ups. CONCLUSIONS: These results suggest that altered autonomic functioning might represent a key pathway linking social integration to health outcomes.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".