Psychometrics of Pediatric Heart Rate Variability: Reliability and Stability
Bibliographic record
Abstract
Measures of heart rate variability (HRV) are commonly used in longitudinal studies among infants, children, and adolescents as an indicator of autonomic cardiovascular control. However, the psychometric properties of pediatric HRV measures have yet to be established. This thesis examined the psychometrics of time- and frequency-domain HRV measures among infants and youth through two complementary studies. The first study was a systematic review and meta-analysis of 46 studies that evaluated how study methodology (study protocol, sample characteristics, ECG signal acquisition and pre-processing, HRV analyses) affects HRV test-retest reliability. HRV displayed moderate reliability overall across infant/toddler (Mage <5 yrs; Fisher’s Z = 0.42) and child/adolescent groups (Mage 5–18 yrs; Z = 0.64); reliability among infant/toddler studies was relatively more sensitive to examined a priori moderator variables. The second study examined temporal stability of HRV measures obtained from children (Mage 9 yrs) participating in a large, longitudinal cohort study (N = 632) within Quebec. Results indicated that HRV is a moderately stable individual difference in children (ICCrange = 0.74–0.85; rrange = 0.67–0.75), and stability was robust to initial differences in, and developmental changes among demographic (age, puberty), cardiovascular (blood pressure), anthropometric (height, adiposity indices), and physical activity (e.g., weekday/end screen time) covariates. However, stability of HRV measures reflecting parasympathetic (rMSSD, pNN50, HF) activity was augmented following statistical control of time-varying heart rate measures. Together, this thesis contributes original knowledge regarding the psychometrics of pediatric HRV measures. Pertinent methodological and intra-individual factors recommended for consideration by future researchers are discussed.
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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 | 0.040 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".