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Record W4402250349 · doi:10.1186/s12984-024-01446-2

Feasibility of a home-based home videogaming intervention with a family-centered approach for children with cerebral palsy: a randomized multiple baseline single-case experimental design

2024· article· en· W4402250349 on OpenAlexafffundabout
Daniela Chan-Víquez, Heilyn Fernández-Huertas, Carles Montserrat-Gonzalez, Ajmal Khan, Darcy Fehlings, Sarah Munce, F. Virginia Wright, Elaine Biddiss

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity Health NetworkHolland Bloorview Kids Rehabilitation HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversidad de Costa RicaHolland Bloorview Kids Rehabilitation Hospital FoundationAzrieli FoundationOntario Brain Institute
KeywordsCerebral palsyIntervention (counseling)Physical therapyActivities of daily livingMedicineBaseline (sea)Occupational therapyPhysical medicine and rehabilitationDescriptive statisticsQuality of life (healthcare)Repeated measures designPsychologyNursing

Abstract

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BACKGROUND: Worldwide, children with cerebral palsy (CP) living in underserved communities face barriers to accessing motor therapy services. This study assessed the implementation and effectiveness of an 8-week, upper limb (UL) home-based intervention with a movement-tracking videogame (Bootle Blast) in Costa Rican children with CP. METHODS: Children established a weekly playtime goal and two UL activities of daily living (ADLs) that they would like to improve on. A multiple-baseline, single-case experimental design, was used with the Performance Quality Rating Scale (PQRS) as the repeated measure to track changes in performance of the selected ADLs between the baseline (usual care) and intervention (Bootle Blast) phases. The Canadian Occupational Performance Measure (COPM), the Box and Blocks Test (BBT) and the Children's Hand-Use Experience Questionnaire (CHEQ) were collected before and after the intervention. Technical barriers were documented during weekly video calls with a monitoring therapist. Treatment effect size, slope changes and percentage of non-overlapping data were identified for the PQRS. Descriptive statistics summarized results for the BBT, CHEQ, videogame logs (e.g., playtime) and technical barriers. RESULTS: Fifteen children participated and 13 completed the intervention. Both participants who dropped out did so after completing baseline assessments, but before experiencing Bootle Blast. Children's mean active playtime (i.e., mini-games targeting the UL) across the 8-weeks was 377 min, while mean total time spent engaging with Bootle Blast (active + passive play time [e.g., time navigating menus, reviewing rewards]) was 728 min. In total, eight technical issues (from five children) were reported, and all but three were resolved within 48 h. Partial effectiveness was associated with the intervention. Specifically, 85% of participants improved on the PQRS and 69% achieved clinically important improvements ≥ 2 points in performance on the COPM. Children improved by 1.8 blocks on average on the BBT, while on the CHEQ, five children had a clinically important increase of 10% of the total number of UL activities performed with both hands. CONCLUSION: Bootle Blast is a feasible and effective option to facilitate access and engage children with cerebral palsy in UL home rehabilitation. Trial registration Trial registration number: NCT05403567.

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)0.004
metaresearch head score (Gemma)0.004
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: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.031
GPT teacher head0.261
Teacher spread0.230 · 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

Citations3
Published2024
Admission routes3
Has abstractyes

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