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Record W3137919137 · doi:10.1080/09593985.2021.1901327

Fear of Falling Among Community-Dwelling Older Adults with Heart Disease: Findings from an International Mobility in Aging Study (IMIAS)

2021· article· en· W3137919137 on OpenAlexaff
Ala’ S. Aburub, Susan P. Phillips, Mayis Aldughmi, Carmen‐Lucía Curcio, Ricardo Oliveira Guerra, Mohammad Auais

Bibliographic record

VenuePhysiotherapy Theory and Practice · 2021
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsQueen's University
Fundersnot available
KeywordsFear of fallingMedicineGerontologyRehabilitationPhysical therapyPsychological interventionPoison controlInjury preventionMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Older adults with heart disease (HD) are more likely to report a higher prevalence of falls compared to those without HD. A knowledge gap currently exists regarding the factors associated with fear of falling (FOF) among older adults with HD. Therefore, this study aimed to estimate FOF and identify factors associated with FOF among older adults with HD. METHODS: Data came from a secondary analysis of the International Mobility in Aging Study (IMIAS) baseline (2012) data. FOF was measured using the Falls Efficacy Scale-International (FES-I). Stepwise linear regression was used to identify factors associated with FOF. RESULTS: A total of 429 participants identified themselves as having heart disease diagnosed by their physician (mean age 69.5 ± 2.9). Older adults with HD reported on average (25.6) higher FOF than those without HD. For older adults with HD, FES-I increased significantly by 1.3, 1.0, and 0.6 points, when the Short Physical Performance Battery, the Leganes Cognitive Test, and QOL total scores decreased by one point. FES-I also significantly increased by 3.2 when income was insufficient compared to sufficient or very sufficient income. DISCUSSION: FOF is multifactorial, and our findings provide a base for developing future management rehabilitation intervention programs aimed at decreasing FOF among older adults with HD.

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)0.003
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 score0.064
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.401
Teacher spread0.379 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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