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Record W4413006148 · doi:10.1249/esm.0000000000000052

Long-Term Enrollment in a Community Exercise Program Attenuates Age-Related Declines in Fitness in Older Adults

2025· article· en· W4413006148 on OpenAlexaff
Giulia Coletta, Angelica McQuarrie, Stuart M. Phillips, Maureen J. MacDonald

Bibliographic record

VenueExercise Sport and Movement · 2025
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGerontologyTerm (time)Physical fitnessMedicineDemographyPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

ABSTRACT Introduction The purpose of this study was to examine changes in cardiorespiratory fitness (CRF) and muscle strength (MS) in participants of a community-based exercise program through a retrospective chart review. Methods In this observational study, participants ( n = 124, 69 females) completed exercise tests before enrollment and after a minimum of 1 yr of participation. One-sample t -tests were used to compare annualized rates of change in CRF and MS compared with published rates of change. Results After a mean follow-up time of 5.2 ± 2.6 yr, absolute and relative rates of decline in peak oxygen uptake (V˙O 2peak ) were less than expected among males, whereas absolute and relative V˙O 2peak improved over time in females compared with established rates of decline. Rates of decline in strength were less than the established rates of decline in both males and females. Conclusion These findings suggest that enrollment in a community-based exercise program was associated with improved aerobic and muscular fitness outcomes in both females and males compared with established rates of change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.818

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 studies0.0000.000
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 head0.015
GPT teacher head0.317
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.

The models applied no category: nothing in the taxonomy fit this work.
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

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