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Record W4225163130 · doi:10.3390/ijerph19095453

Effects of the Mobility-Fit Physical Activity Program on Strength and Mobility in Older Adults in Assisted Living: A Feasibility Study

2022· article· en· W4225163130 on OpenAlexafffund
Yijian Yang, Kimberley S. van Schooten, Vicki Komisar, Heather McKay, Joanie Sims‐Gould, Debbie Cheong, Stephen N. Robinovitch

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanadian Institutes of Health ResearchChinese University of Hong KongMichael Smith Health Research BC
KeywordsAttendancePhysical therapyBalance (ability)MedicineActivities of daily livingPhysical medicine and rehabilitationPhysical activityFall preventionGerontologyInjury preventionPoison controlMedical emergency

Abstract

fetched live from OpenAlex

Physical activity programs focusing on fall prevention often overlook upper-limb strength, which is important for transferring, balance recovery, and arresting a fall. We developed and evaluated a physical activity program, Mobility-Fit for older adults in Assisted Living (AL) that includes upper-limb strengthening, agility, coordination, and balance exercises. Thirty participants (85 ± 6 years) were recruited from two AL facilities; 15 were assigned to Mobility-Fit (three times/week, 45 min/session for 12 weeks) and 15 maintained usual care. Twenty-two participants (11 in each group) completed the study. We compared outcome changes between groups and interviewed participants and staff to explore the effectiveness and feasibility of the program. Among participants who attended Mobility-Fit, knee extension strength increased by 6%, reaction time decreased by 16%, and five-time sit-to-stand duration decreased by 15%. Conversely, participants in the usual care group had a 6% decrease in handgrip strength. Changes of these outcomes were significantly different between two groups (p < 0.05). Participants enjoyed the program and staff suggested some changes to improve attendance. Our results indicate that Mobility-Fit is feasible to deliver and beneficial for older adults in AL and may guide future clinical trials to evaluate the effectiveness of upper limb strengthening on safe mobility of older adults in care facilities.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Non-randomized triallow
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.456
Teacher spread0.386 · 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

Labeled directly by 2 models reading the full record.

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

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Non-randomized trial
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

Citations6
Published2022
Admission routes2
Has abstractyes

Explore more

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