Dataset Information

Effect of children's shoes on gait: a systematic review and meta-analysis.

ABSTRACT:

Background

The effect of footwear on the gait of children is poorly understood. This systematic review synthesises the evidence of the biomechanical effects of shoes on children during walking and running.

Methods

Study inclusion criteria were: barefoot and shod conditions; healthy children aged ? 16 years; sample size of n > 1. Novelty footwear was excluded. Studies were located by online database-searching, hand-searching and contact with experts. Two authors selected studies and assessed study methodology using the Quality Index. Meta-analysis of continuous variables for homogeneous studies was undertaken using the inverse variance approach. Significance level was set at P < 0.05. Heterogeneity was measured by I2. Where I2 > 25%, a random-effects model analysis was used and where I2 < 25%, a fixed-effects model was used.

Results

Eleven studies were included. Sample size ranged from 4-898. Median Quality Index was 20/32 (range 11-27). Five studies randomised shoe order, six studies standardised footwear. Shod walking increased: velocity, step length, step time, base of support, double-support time, stance time, time to toe-off, sagittal tibia-rearfoot range of motion (ROM), sagittal tibia-foot ROM, ankle max-plantarflexion, Ankle ROM, foot lift to max-plantarflexion, 'subtalar' rotation ROM, knee sagittal ROM and tibialis anterior activity. Shod walking decreased: cadence, single-support time, ankle max-dorsiflexion, ankle at foot-lift, hallux ROM, arch length change, foot torsion, forefoot supination, forefoot width and midfoot ROM in all planes. Shod running decreased: long axis maximum tibial-acceleration, shock-wave transmission as a ratio of maximum tibial-acceleration, ankle plantarflexion at foot strike, knee angular velocity and tibial swing velocity. No variables increased during shod running.

Conclusions

Shoes affect the gait of children. With shoes, children walk faster by taking longer steps with greater ankle and knee motion and increased tibialis anterior activity. Shoes reduce foot motion and increase the support phases of the gait cycle. During running, shoes reduce swing phase leg speed, attenuate some shock and encourage a rearfoot strike pattern. The long-term effect of these changes on growth and development are currently unknown. The impact of footwear on gait should be considered when assessing the paediatric patient and evaluating the effect of shoe or in-shoe interventions.

SUBMITTER: Wegener C

PROVIDER: S-EPMC3031211 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Publications

Effect of children's shoes on gait: a systematic review and meta-analysis.

Wegener Caleb C Hunt Adrienne E AE Vanwanseele Benedicte B Burns Joshua J Smith Richard M RM

Journal of foot and ankle research 20110118

<h4>Background</h4>The effect of footwear on the gait of children is poorly understood. This systematic review synthesises the evidence of the biomechanical effects of shoes on children during walking and running.<h4>Methods</h4>Study inclusion criteria were: barefoot and shod conditions; healthy children aged ≤ 16 years; sample size of n > 1. Novelty footwear was excluded. Studies were located by online database-searching, hand-searching and contact with experts. Two authors selected studies an ...[more]

PMID: 21244647

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Project description:BackgroundRobotic-Assisted Gait Training (RAGT) may enable high-intensive and task-specific gait training post-stroke. The effect of RAGT on gait movement patterns has however not been comprehensively reviewed. The purpose of this review was to summarize the evidence for potentially superior effects of RAGT on biomechanical measures of gait post-stroke when compared with non-robotic gait training alone.MethodsNine databases were searched using database-specific search terms from their inception until January 2021. We included randomized controlled trials investigating the effects of RAGT (e.g., using exoskeletons or end-effectors) on spatiotemporal, kinematic and kinetic parameters among adults suffering from any stage of stroke. Screening, data extraction and judgement of risk of bias (using the Cochrane Risk of bias 2 tool) were performed by 2-3 independent reviewers. The Grading of Recommendations Assessment Development and Evaluation (GRADE) criteria were used to evaluate the certainty of evidence for the biomechanical gait measures of interest.ResultsThirteen studies including a total of 412 individuals (mean age: 52-69 years; 264 males) met eligibility criteria and were included. RAGT was employed either as monotherapy or in combination with other therapies in a subacute or chronic phase post-stroke. The included studies showed a high risk of bias (n = 6), some concerns (n = 6) or a low risk of bias (n = 1). Meta-analyses using a random-effects model for gait speed, cadence, step length (non-affected side) and spatial asymmetry revealed no significant differences between the RAGT and comparator groups, while stride length (mean difference [MD] 2.86 cm), step length (affected side; MD 2.67 cm) and temporal asymmetry calculated in ratio-values (MD 0.09) improved slightly more in the RAGT groups. There were serious weaknesses with almost all GRADE domains (risk of bias, consistency, directness, or precision of the findings) for the included outcome measures (spatiotemporal and kinematic gait parameters). Kinetic parameters were not reported at all.ConclusionThere were few relevant studies and the review synthesis revealed a very low certainty in current evidence for employing RAGT to improve gait biomechanics post-stroke. Further high-quality, robust clinical trials on RAGT that complement clinical data with biomechanical data are thus warranted to disentangle the potential effects of such interventions on gait biomechanics post-stroke.

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Dataset Information

Effect of children's shoes on gait: a systematic review and meta-analysis.

Background

Methods

Results

Conclusions

Publications

Effect of children's shoes on gait: a systematic review and meta-analysis.

Similar Datasets

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