Cardiovascular Recovery From Acute Laboratory Stress: Reliability and Concurrent Validity
Bibliographic record
Abstract
OBJECTIVE: We assessed the value of laboratory measures of cardiovascular recovery across four criteria: reliability across multiple tasks, reliability across a 3-year time interval, ability to predict daily ambulatory blood pressure, and interrelationships with coronary risk factors and psychosocial variables. METHODS: Three hundred twenty-nine healthy adults (mean age = 27.1 years) completed a two-part protocol consisting of 1 day of laboratory testing and 1 day of ambulatory monitoring. The laboratory protocol included a 15-minute baseline assessment followed by three 5-minute laboratory challenges (mental arithmetic, speech, and handgrip). Five-minute recovery periods followed each exercise. One hundred twenty-five participants returned after 3 years to repeat the protocol. RESULTS: When aggregated across tasks, cardiovascular recovery showed acceptable levels of internal consistency (alpha values = 0.7) and proved relatively stable across time (r values = 0.22-0.35). Recovery values statistically improved the prediction of daily ambulatory readings above baseline and stress reactivity laboratory values (p values < .001) but were largely unrelated to coronary risk factors or psychosocial measures. CONCLUSION: These results suggest that cardiovascular recovery from acute laboratory stress can be treated as a stable individual difference variable that can -improve standard laboratory-based predictor models of ambulatory readings.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".