Purpose: To determine the efficacy of a custom-made wheelchair simulation in training children to use a powered wheelchair (PWC).
Design: Randomized controlled trial employing the 4C/ID-model of learning. Twenty-eight typically developing children (13M, 15F; mean age 6 years, SD 6 months) were assessed on their operation of a PWC using a functional evaluation rating scale. Participants were randomly assigned to intervention (8 × 30-minute training sessions using a joystick operated wheelchair simulation) or control conditions (no task), and were reassessed on their PWC use after the intervention phase. Additional data from the simulation on completion times, errors, and total scores were recorded for the intervention group.
Results: Analysis of variance showed a main effect of time, with planned comparisons revealing a statistically significant change in PWC use for the intervention (p = .022) but not the control condition. Although the intervention group showed greater improvement than the controls, this did not reach statistical significance. Multiple regression analyses showed that gender was predictive of pretest (p = .005) functional ability.
Implications: A simulated wheelchair task appears to be effective in helping children learn to operate a PWC. Greater attention should be given to female learners who underperformed when compared with their male counterparts. This low-cost intervention could be easily used at home to reduce PWC training times in children with motor disorders.
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http://dx.doi.org/10.1037/a0034088 | DOI Listing |
Pediatr Phys Ther
January 2025
Parent of a child with CP, GMCS IV who explored power mobility from age 12 months and is now an independent power wheelchair user.
Assist Technol
December 2024
School of Occupational Therapy, Faculty of Health, Dalhousie University, Nova Scotia, Canada.
This study translated and culturally adapted the Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M) and the Wheelchair Use Confidence Scale for Power Wheelchair Users (WheelCon-P) into Arabic and examined their reliability and validity. Internal consistency and test-retest reliability were examined, and concurrent validity was evaluated using Pearson correlation coefficients with the Arabic versions of the Functioning Everyday with a Wheelchair (FEW) and the Functional Mobility Assessment (FMA). The Arabic translated versions of the WheelCon-M (WheelCon-M-A) and the WheelCon-P (WheelCon-P-A) were administered to 33 adult wheelchair users.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Human Engineering Research Laboratories, Department of VA Pittsburgh Healthcare System, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15206, USA.
: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers, which often result in back pain and musculoskeletal disorders due to the physical demands of lifting and repositioning. While mechanical floor lifts, the current standard, reduce back strain, they are time-consuming and require handling techniques that subject caregivers to prolonged and repeated non-neutral trunk postures, increasing the risk of long-term back injuries. : The aim was to assess the time efficiency and ergonomics of the powered personal transfer system (PPTS), a robotic transfer device designed for bed-to/from-wheelchair transfers.
View Article and Find Full Text PDFEur Burn J
September 2024
Department of Plastic and Reconstructive Surgery, The Royal Brisbane and Women's Hospital, Brisbane 4029, Australia.
Cogn Neurodyn
October 2024
College of Electrical Engineering and Automation, Fuzhou University, Fuzhou,, 350108 Fujian China.
Currently, electroencephalogram (EEG)-based motor imagery (MI) signals have been received extensive attention, which can assist disabled subjects to control wheelchair, automatic driving and other activities. However, EEG signals are easily affected by some factors, such as muscle movements, wireless devices, power line, etc., resulting in the low signal-to-noise ratios and the worse recognition results on EEG decoding.
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