MétaCan
Menu
Back to cohort
Record W4412073260 · doi:10.1123/apaq.2025-0009

Correlations Between Physiological and Self-Report Measures of Daily Physical Activity Time and Intensity in Adults With Spinal Cord Injury

2025· article· en· W4412073260 on OpenAlexaff
Cameron M. Gee, Ava Neely, Aleksandra Jevdjevic, Kenedy Olsen, Kathleen A. Martin Ginis

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2025
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsSpinal cord injuryIntensity (physics)Physical activityPsychologyPhysical therapyExercise intensityPsychophysiologyPhysical medicine and rehabilitationMedicineRecallSpinal cordInternal medicineBlood pressureHeart ratePsychiatry

Abstract

fetched live from OpenAlex

Spinal cord injury (SCI) can alter physiological responses to acute physical activity (PA), which may influence perceptions and reporting of PA intensity. We examined correlations between physiological and perceptual self-report measures of daily PA in individuals with SCI. Participants completed an assessment of peak aerobic-exercise capacity to determine individualized mild-, moderate-, and vigorous-intensity PA oxygen-uptake (V˙O2) cut points, wore a portable system that measured V˙O2, and completed the Physical Activity Recall Assessment for people with SCI. Time engaged in combined moderate to vigorous PA recorded by portable monitoring and self-report were significantly correlated (r = .659, p = .027). There were no associations between metabolic monitoring and equivalent self-report outcomes within individual PA-intensity levels. These findings highlight challenges people with SCI may have differentiating the intensity of PA, which may be related to the way self-report measures describe sensations associated with each intensity. Whether these findings are specific to SCI-related psychophysiology remains unclear.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.347
Teacher spread0.308 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAdapted Physical Activity QuarterlySame topicSpinal Cord Injury ResearchFrench-language works237,207