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Record W4413791639 · doi:10.1186/s12877-025-06257-1

Influence of a multicomponent exercise intervention on fear of falling and gait parameters in community-dwelling older adults: a prospective study

2025· article· en· W4413791639 on OpenAlexaff
Aymeric Courtay‐Breuil, Léo Delaire, Joannès Humblot, Thomas Gilbert, Mylène Aubertin‐Leheudre, Marc Bonnefoy

Bibliographic record

VenueBMC Geriatrics · 2025
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalUniversité du Québec à Montréal
FundersHospices Civils de Lyon
KeywordsFear of fallingGaitMedicinePhysical medicine and rehabilitationPhysical therapyRehabilitationRepeated measures designProspective cohort studyPoison controlInjury preventionSurgery

Abstract

fetched live from OpenAlex

BACKGROUNDS: The effects of exercise interventions on gait parameters and fear of falling (FOF) have been under-explored and the influence of FOF on exercise-induced adaptations of gait parameters is unclear. This interventional and comparative pilot study aimed to explore the influence of FOF status on gait parameters changes following a multicomponent exercise intervention in community-dwelling older adults at risk of mobility disability and implemented in routine care. METHODS: One-hundred five older adults (80.63 ± 5.80 years) completed a supervised group-based exercise (6–8 participants) intervention (10 weeks, 2x/week, 1 h). Participants of this open cohort and prospective study were divided a-posteriori in 2 subgroups: with FOF subgroup (Falls Efficacy Scale-International (FES-I) > 23; n = 64) or without FOF subgroup (FES-I ≤ 23; n = 41). A two-way repeated measure ANOVA was performed to measure time, group and group*time interactions effects. Paired t-test were performed to measure changes within the subgroups. Correlations were performed between FOF delta’s changes and gait parameters changes. Spatiotemporal gait parameters (i.e. gait speed; stride variability, symmetry, length; swing, stance and double support phases; lift and strike angles; number of cycles at the turn; turning angle), perceived gait quality (i.e. the “Locomotion” domain of the “SarQoL®” questionnaire), functional parameters (i.e. Short Physical Performance Battery and its subtests; Timed Up and Go) and FOF were assessed. RESULTS: A time effect was observed for all spatial gait parameters (p < .05), all functional parameters (p < .001), perceived gait quality (p < .001) and FOF (p < .01) assessed after the intervention for the total cohort. A group effect was observed for FOF (p < .001), spatiotemporal gait parameters (p < .05) and perceived gait quality (p < .001). A group*time interaction was only observed for FOF (p < .001). Stride length, lift off angle, strike angle and turning angle (p < .05) improved in both subgroups. Stride variability (p < .05) and FOF (p < .001) improved only in the FOF subgroup. Correlations between gait parameters changes and FOF changes were only observed in FOF subgroup for double support phase (r =.25, p < .05), swing phase (r =-.25, p < .05) and stance phase (r =.25, p < .05). A moderate correlation was observed between FOF changes and perceived gait quality changes (r =-.49, p < .01) in no-FOF subgroup. This correlation became weak for the total cohort (r =-.25, p < .05). CONCLUSIONS: Our results demonstrate that a multicomponent exercise intervention lead to significant changes in FOF, spatial gait parameters and perceived gait quality in older adults and more in those with FOF. Thus, this routine care intervention could be widely proposed to older adults at risk of falls, and particularly to those with a FOF. Finally, although FOF and gait parameters are related, their changes over time do not seem to be as related. This study confirmed that managing the FOF is complex, multifactorial and might be orientated to a holistic approach. TRIAL REGISTRATION NUMBER: NCT03667664 (registration date: 12/09/2018) and NCT06659484 (registration date: 26/10/2024).

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.022
GPT teacher head0.344
Teacher spread0.322 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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