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Record W2949348815 · doi:10.1177/0844562119856224

Impact of Function Focused Care and Physical Activity on Falls in Assisted Living Residents

2019· article· en· W2949348815 on OpenAlexvenueno aff
Barbara Resnick, Elizabeth Galik, Marie Boltz, Shijun Zhu, Steven Fix, Erin Vigne

Bibliographic record

VenueCanadian Journal of Nursing Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsOddsMedicineFalling (accident)CognitionOdds ratioFear of fallingPhysical activityActivities of daily livingGerontologyPoison controlInjury preventionHuman factors and ergonomicsRandomized controlled trialPsychologyPhysical therapyLogistic regressionPsychiatryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Background There continues to be a belief among nurses, patients, and families that physical activity increases the risk of falling. Purpose The purpose of this study was to test the hypothesis that controlling for age, function, cognition, medication use, gender, comorbidities, and cognition, residents who are exposed to Function Focused Care for Assisted Living (FFC-AL-EIT) and engage in moderate levels of physical activity would not be more likely to fall. Methods This was a secondary data analysis using data from the first two cohorts of a randomized trial testing FFC-AL-EIT in the United States. Results The study included 381 residents, the majority of whom were female (70%), white (97%), with a mean age of 87.72 (standard deviation = 7.47). Those who engaged in more moderate-intensity physical activity were 1% less likely to fall (odds ratio = .99, p = .03). There was no significant association between exposure to function focused care and falling (odds ratio = 1.58, p = .09). Conclusion There was no indication that those who were exposed to function focused care or those who engaged in moderate-level physical activity were more likely to fall. In fact, engaging in moderate-level physical activity was noted to be slightly protective of falling.

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)0.001
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 score0.192
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.101
GPT teacher head0.477
Teacher spread0.375 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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