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Cardiovascular Recovery From Acute Laboratory Stress: Reliability and Concurrent Validity

2000· article· en· W2323078332 on OpenAlexaff
Thomas Rutledge, Wolfgang Linden, David Paul

Bibliographic record

VenuePsychosomatic Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAmbulatoryMedicinePsychosocialReliability (semiconductor)Protocol (science)Heart ratePhysical therapyConfidence intervalStress testing (software)Blood pressureInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.026
GPT teacher head0.328
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2000
Admission routes1
Has abstractyes

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