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Record W2022951685 · doi:10.1186/1471-2318-7-12

A perturbation-based balance training program for older adults: study protocol for a randomised controlled trial

2007· article· en· W2022951685 on OpenAlexafffund
Avril Mansfield, Amy Peters, Barbara A. Liu, Brian E. Maki

Bibliographic record

VenueBMC Geriatrics · 2007
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPhysical medicine and rehabilitationMedicineBalance (ability)Balance trainingFear of fallingFall preventionRandomized controlled trialRehabilitationCognitionCognitive trainingDynamic balancePhysical therapyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

BACKGROUND: Previous research investigating exercise as a means of falls prevention in older adults has shown mixed results. Lack of specificity of the intervention may be an important factor contributing to negative results. Change-in-support (CIS) balance reactions, which involve very rapid stepping or grasping movements of the limbs, play a critical role in preventing falls; hence, a training program that improves ability to execute effective CIS reactions could potentially have a profound effect in reducing risk of falling. This paper describes: 1) the development of a perturbation-based balance training program that targets specific previously-reported age-related impairments in CIS reactions, and 2) a study protocol to evaluate the efficacy of this new training program. METHODS/DESIGN: The training program involves use of unpredictable, multi-directional moving-platform perturbations to evoke stepping and grasping reactions. Perturbation magnitude is gradually increased over the course of the 6-week program, and concurrent cognitive and movement tasks are included during later sessions. The program was developed in accordance with well-established principles of motor learning, such as individualisation, specificity, overload, adaptation-progression and variability. Specific goals are to reduce the frequency of multiple-step responses, reduce the frequency of collisions between the stepping foot and stance leg, and increase the speed of grasping reactions. A randomised control trial will be performed to evaluate the efficacy of the training program. A total of 30 community-dwelling older adults (age 64-80) with a recent history of instability or falling will be assigned to either the perturbation-based training or a control group (flexibility/relaxation training), using a stratified randomisation that controls for gender, age and baseline stepping/grasping performance. CIS reactions will be tested immediately before and after the six weeks of training, using platform perturbations as well as a distinctly different method of perturbation (waist pulls) in order to evaluate the generalisability of the training effects. DISCUSSION: This study will determine whether perturbation-based balance training can help to reverse specific age-related impairments in balance-recovery reactions. These results will help to guide the development of more effective falls prevention programs, which may ultimately lead to reduced health-care costs and enhanced mobility, independence and quality of life.

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)0.024
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.048
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.024
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0180.006
Bibliometrics0.0030.004
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0480.008

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 head0.051
GPT teacher head0.419
Teacher spread0.368 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations104
Published2007
Admission routes2
Has abstractyes

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