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Record W2527124087 · doi:10.1093/geront/gnv417.05

UNRAVELLING A MULTICOMPONENT PROGRAM ON CONCERNS ABOUT FALLS AND ENHANCING ACTIVITY IN OLD AGE

2015· article· en· W2527124087 on OpenAlexaboutno aff
G. A. Rixt Zijlstra

Bibliographic record

VenueThe Gerontologist · 2015
Typearticle
Languageen
FieldEngineering
TopicErgonomics and Human Factors
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyGerontologyHuman factors and ergonomicsSuicide preventionPoison controlMedicineMedical emergency

Abstract

fetched live from OpenAlex

In older populations both fallers and non-fallers report fear of falling and activity avoidance. Previous studies have shown that fear to fall can lead to activity avoidance, and has a negative impact on balance, gait, mobility, social activity, mental health and independence. Worldwide research on fear of falling has taken a flight in the past years and even populations challenging to enroll are currently being studied. This warrants connecting international research findings in search for sustainable prevention strategies to tackle fear of falling. During this symposium new, international findings from four innovative research studies will be presented. The presenters from the US, Sweden, Germany and The Netherlands will address respectively: 1) awareness, beliefs, and actions regarding falls and fear of falling in community-living older adults, 2) fall-related activity avoidance in people aging with Parkinson's disease and the relationship with disease severity, fear of falling and falls, 3) life space in vulnerable nursing home residents and associations with motor, cognitive and psychological outcomes, including concerns about falling, and 4) a multicomponent program on concerns about falls and the identification of the least and most promising components. Dr. Desphande, our discussant from Canada / US, will reflect on the presented outcomes. The audience will be invited to interact with the presenters and discussant during the symposium in order to share evidence and opinions, and to take meaningful steps in research and practice related to reducing fear of falling in older populations.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.072
GPT teacher head0.290
Teacher spread0.218 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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