Growth Models of Positive Caregiving Behaviours and Concurrent Autonomic Activity in Caregivers and Children during a Challenging Puzzle Task: Replication and Extension
Bibliographic record
Abstract
Caregivers exhibiting low levels of positive caregiving tend to have reduced dynamic range in high- frequency heart rate variability (HRV), an index of parasympathetic nervous system activity. Yet less is known about the involvement of the sympathetic nervous system, which may impact the plausible range of parasympathetic reactivity. Here, caregiver–child dyads completed resting assessments of HRV and pre-ejection period (PEP), followed by a videotaped puzzle task during which HRV was measured and observers coded the degree of caregivers’ positive emotionality. Multilevel modelling was employed to characterize task fluctuations in HRV as a function of resting PEP and caregivers’ positive emotional expressions. Higher frequency of caregiver positivity was associated with greater HRV reactivity in caregivers but not children. Increased caregiver positivity was correlated with longer resting PEP in children. These results replicate findings of greater caregiver parasympathetic flexibility during positive caregiving and extend those findings to children’s resting sympathetic activity.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".