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Record W4283380484 · doi:10.1080/10400435.2022.2084183

Pediatric powered mobility training: powered wheelchair versus simulator-based practice

2022· article· en· W4283380484 on OpenAlexaff
Naomi Gefen, Philippe S. Archambault, Amihai Rigbi, Patrice L. Weiss

Bibliographic record

VenueAssistive Technology · 2022
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversité de MontréalMcGill UniversityUniversité du Québec à Montréal
FundersUniversity of Haifa
KeywordsWheelchairCerebral palsyChristian ministryPhysical therapyPhysical medicine and rehabilitationManual wheelchairMedicineTest (biology)SimulationEngineeringComputer science

Abstract

fetched live from OpenAlex

Many children with physical disabilities lack independent mobility. Powered mobility can be a viable option, but to become proficient drivers, children need opportunities to practice. As is often the case, practice powered wheelchairs are scarce and direct therapy hours dedicated to powered mobility are often limited. Hence, alternative options are needed to enable safe, unsupervised practice. Simulator-based learning has been shown to be an effective training method for powered mobility and other skill-based tasks for adults. The goal of this study was to compare two training methods of powered mobility, powered wheelchair (control group) versus simulator-based (experimental group) practice to determine whether simulation is a feasible and effective method for youth.Method Participants included 30 children and adolescents (23 males, 13 females) with cerebral palsy and other neuromuscular diseases, aged 6–18. Data were collected and compared at baseline and after 12 weeks of home-based practice via a powered wheelchair or a simulator. Powered mobility ability was determined by the Powered Mobility Program (PMP), the Israel Ministry of Health’s Powered Mobility Proficiency Test (PM-PT) and the Assessment of Learning Powered Mobility (ALP).Results All participants practiced for the required amount of time and both groups reported a similar user experience. Both groups achieved significant improvement following the practice period as assessed by the PMP and PM-PT assessments, with no significant differences between them. A significant improvement was found in the ALP assessment outcomes for the powered wheelchair group only.Conclusions This is the first study, to our knowledge, that compares two different wheelchair training methods. Simulator-based practice is an effective training option for powered mobility for children with physical disabilities aged 6–18 years old, demonstrating that it is possible to provide driving skill practice opportunities safe, controlled environments.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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 designNon-randomized trial
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".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

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