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Psychometric properties of instrumented tools and outcome measures to assess dynamic, anticipatory and reactive balance in older adults: A scoping review

2025· article· en· W4416293221 on OpenAlexafffund
Alison Bulow, Alison Oates, Faith Olarinde, Jonathan C. Singer, Karen Van Ooteghem, Kathryn M. Sibley

Bibliographic record

VenueGait & Posture · 2025
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of WaterlooUniversity of SaskatchewanGeorge & Fay Yee Centre for Healthcare InnovationManitoba HealthUniversity of Manitoba
FundersCanada Research Chairs
KeywordsBalance (ability)Outcome (game theory)Work (physics)Control (management)Dynamic balanceFall prevention

Abstract

fetched live from OpenAlex

Many technologies are available to assess balance; however, there is not one comprehensive option that meets all requirements for each component of balance. To identify what instrumented measurement tools and subsequent outcome measures have been established to quantify dynamic, anticipatory, and reactive balance in adults ≥ 65 years old. MEDLINE, EMBASE, and CINAHL databases were searched for studies published in English that evaluated one or more psychometric property of instrumented measurement tools and outcome measures to assess dynamic, anticipatory, or reactive balance in adults ≥ 65 years old. Data extraction included participant characteristics, balance component(s), instrumented measurement tools and outcome measures, and psychometric analyses. Twenty-five studies were included. IMUs are the most commonly reported instrumented measurement tool used to assess anticipatory postural control and dynamic stability while force plates have also been established as valid and reliable for assessing all three components of balance. Test-retest validity and criterion reliability have been established to assess anticipatory postural control and dynamic balance using six outcome measure via IMUs (n = 4) and force plates (n = 2). Reactive postural control was assessed using two outcome measures via force plates. Minimal valid and reliable instrumented measurement tools and outcome measures were identified for anticipatory postural control and dynamic stability, and even fewer for reactive postural control. Additional work is needed to establish evidence-based guidance for selecting an instrumented measurement tool and outcome measure(s) to evaluate dynamic, anticipatory, and reactive balance control to appropriately develop and progress balance exercises in community fall prevention programs. • Dynamic stability, anticipatory postural control and reactive postural control are important components of balance. • Exercises that target these components of balance have been identified as essential for fall prevention in older adults. • This review synthesizes valid and reliable instrumented tools and outcome measures of these components of balance. • IMUs and force plates, the most utilized instrumented measurement tools have been established as valid and reliable. • Minimal valid and reliable outcome measures were identified to assess each component of balance.

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)0.079
metaresearch head score (Gemma)0.292
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 score0.079
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.292
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.009
Bibliometrics0.0210.022
Science and technology studies0.0010.002
Scholarly communication0.0060.005
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.410
Teacher spread0.338 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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