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Record W4313946036 · doi:10.1123/japa.2022-0071

Sex-Related Differences in Functional Fitness Outcomes in Older Adults

2023· article· en· W4313946036 on OpenAlexaff
Michael J. Marsala, Shannon Belfry, J. B. Orange, Anita Christie

Bibliographic record

VenueJournal of Aging and Physical Activity · 2023
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsWestern University
Fundersnot available
KeywordsNormativeFunctional trainingAerobic exerciseFlexibility (engineering)Physical fitnessGerontologyCardiovascular fitnessExercise prescriptionMedicinePhysical therapyLower bodyPsychologyPhysical medicine and rehabilitationDemography

Abstract

fetched live from OpenAlex

Sex-related differences in changes in functional fitness over time were longitudinally assessed in older adults participating in a group-based multimodal exercise program. From a database, functional fitness scores were obtained for 89 older adults (71.6 ± 6.5 years old) who had completed two assessments, 5-8 years apart. Lower body strength, upper body strength, aerobic endurance, flexibility, and change of direction performances were compared over time and with normative values. Females (p = .02), but not males, had an improvement in upper body strength over time. Females were also more flexible than males at both assessments (p ≤ .02). Of those who had five consecutive assessments, females were more flexible than males (p ≤ .05) and had a faster change of direction ability (p < .001). When compared with normative values, our results indicate that typical time-related functional fitness loss can be attenuated with group exercise. Our results further support the need to tailor exercise prescription according to the individual.

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 score0.053
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.321
Teacher spread0.280 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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