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Record W2116884557 · doi:10.1310/tsr1605-357

Poststroke Fear of Falling in the Hospital Setting

2009· article· en· W2116884557 on OpenAlexaboutno aff
Arlene A. Schmid, Marvin Acuff, Kristen Doster, Amanda Gwaltney-Duiser, Amanda T. Whitaker, Teresa M. Damush, Linda S. Williams, Hugh C. Hendrie

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2009
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsFear of fallingAnxietyStroke (engine)Depression (economics)Quality of life (healthcare)Hospital Anxiety and Depression ScaleMedicineObservational studyPhysical therapyPsychologyPoison controlInjury preventionPsychiatryMedical emergency

Abstract

fetched live from OpenAlex

PURPOSE: Fear of falling (FoF) has a negative impact on older adults, however there is a paucity of research regarding the development and impact of FoF after stroke. Therefore, our objectives were to determine the proportion of individuals with FoF and the affect of FoF during the immediate poststroke period. METHODS: This observational study of baseline data from a pilot cohort study includes a convenience sample of 28 adults with acute stroke before discharge home. Measures include self-reported FoF, the Falls Efficacy Scale-Swedish Version [FES(S)], Stroke-Specific Quality of Life (SS-QOL), performance and satisfaction with performance (Canadian Occupational Performance Measure), anxiety (Generalized Anxiety Disorder-7), and depression (Patient Health Questionnaire-9). RESULTS: Fifteen (54%) of the participants reported FoF. Those with FoF were more likely to have decreased SS-QOL domain scores for energy (p = .013), personality (p = .015), and thinking (p = .008); decreased performance (self-care, productivity, and leisure) (p = .019) and satisfaction with performance (p = .010); and increased anxiety (p = .002) than those without FoF. CONCLUSIONS: Those with FoF demonstrated significantly increased anxiety and showed decreased performance and satisfaction with performance, energy, thinking, and personality than those without FoF. This suggests that poststroke FoF is related not only to physical challenges but also to cognitive and emotional factors in the poststroke period. Identifying and treating these conditions should be evaluated as a means to decrease FoF and improve outcomes post stroke.

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)0.001
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 score0.062
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.284
Teacher spread0.276 · 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

Citations31
Published2009
Admission routes1
Has abstractyes

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