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Record W4366463031 · doi:10.1177/07334648231168983

Fall Risk Screening and Assessment for People Living With Dementia: A Scoping Review

2023· review· en· W4366463031 on OpenAlexfundaboutno aff
Michaela E. Lynds, Catherine M. Arnold

Bibliographic record

VenueJournal of Applied Gerontology · 2023
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
FundersSaskatchewan Health Research Foundation
KeywordsDementiaMedicineHealth careRisk assessmentSystematic reviewPopulationGerontologyMEDLINEEnvironmental healthDiseaseComputer security

Abstract

fetched live from OpenAlex

Falls are the leading cause of injury and hospitalization for older adults in Canada and the second leading cause of unintentional injury deaths worldwide. For people living with dementia (PLWD), falls have an even greater impact, but the standard testing methods for fall risk screening and assessment are often not practical for this population. The purpose of this scoping review is to identify and summarize recent research, practice guidelines and gray literature which have considered fall risk screening and assessment for PLWD. Database search results revealed a dearth in the literature that can support researchers and healthcare providers when considering which option/s are the most suitable for PLWD. Further primary studies into the validity of using the various tests with PLWD are needed if researchers and healthcare providers are to be empowered via the literature and clinical practice guidelines to provide the best possible fall risk care for PLWD.

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)0.006
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0130.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.105
GPT teacher head0.460
Teacher spread0.355 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes2
Has abstractyes

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