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Record W4389137235 · doi:10.1016/j.jamda.2023.10.022

Effects of an Exercise Program to Reduce Falls in Older People Living in Long-Term Care: A Randomized Controlled Trial

2023· article· en· W4389137235 on OpenAlexaboutno aff
Lynne Taylor, John Parsons, Simon Moyes, Elizabeth Binns, Alana Cavadino, Denise Taylor, Sue Lord, Silvia Del Din, Jochen Klenk, Lynn Rochester, Ngaire Kerse

Bibliographic record

VenueJournal of the American Medical Directors Association · 2023
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
FundersHealth Research Council of New ZealandNIHR Newcastle Biomedical Research CentreNewcastle upon Tyne Hospitals NHS Foundation TrustEuropean CommissionNewcastle UniversityNational Institute for Health and Care ResearchEuropean Federation of Pharmaceutical Industries and AssociationsWellcome Trust
KeywordsMedicineRandomized controlled trialAttendanceFall preventionFear of fallingHazard ratioPhysical therapyPoison controlRate ratioInjury preventionConfidence intervalEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate the effect of an exercise program on falls in intermediate and high-level long-term care (LTC) residents and to determine whether adherence, physical capacity, and cognition modified outcomes. DESIGN: Randomized controlled trial. SETTING AND PARTICIPANTS: Residents (n = 520, aged 84 ± 8 years) from 25 LTC facilities in New Zealand. METHODS: Individually randomized to Staying UpRight, a physical therapist-led, balance and strength group exercise program delivered for 1 hour, twice weekly over 12 months. The control arm was dose-matched and used seated activities with no resistance. Falls were collected using routinely collected incident reports. RESULTS: Baseline fall rates were 4.1 and 3.3 falls per person-year (ppy) for intervention and control groups. Fall rates over the trial period were 4.1 and 4.3 falls ppy respectively [P = .89, incidence rate ratio (IRR) 0.98, 95% CI 0.76, 1.27]. Over the 12-month trial period, 74% fell, with 63% of intervention and 61% of the control group falling more than once. Risk of falls (P = .56, hazard ratio 1.08, 95% CI 0.85, 1.36) and repeat falling or fallers sustaining an injury at trial completion were similar between groups. Fall rates per 100 hours walked did not differ between groups (P = .42, IRR 1.15, 95% CI 0.81, 1.63). Program delivery was suspended several times because of COVID-19, reducing average attendance to 26 hours over 12 months. Subgroup analyses of falls outcomes for those with the highest attendance (≥50% of classes), better physical capacity (Short Physical Performance Battery scores ≥8/12), or cognition (Montreal Cognitive Assessment scores ≥ 18/30) showed no significant impact of the program. CONCLUSIONS/IMPLICATIONS: In intermediate and high-level care residents, the Staying UpRight program did not reduce fall rates or risk compared with a control activity, independent of age, sex, or care level. Inadequate exercise dose because of COVID-19-related interruptions to intervention delivery likely contributed to the null result.

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 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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.007
GPT teacher head0.359
Teacher spread0.352 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations18
Published2023
Admission routes1
Has abstractyes

Explore more

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