MétaCan
Menu
Back to cohort
Record W4403489526 · doi:10.1080/17518423.2024.2410180

Feasibility of the <i>Challenge</i> Assessment, the <i>Gait Outcomes Assessment List</i> and ‘ <i>Moving Together’ (‘Sammen I Bevægels</i> e’), a Group-Based Motor Skills Intervention for Independent School-Aged Children with Cerebral Palsy

2024· article· en· W4403489526 on OpenAlexaff
Kirsten Nordbye‐Nielsen, F. Virginia Wright, Ole Rahbek, Bjarne Møller‐Madsen, Thomas Maribo

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersAarhus UniversitetshospitalAarhus UniversitetHealth Research
KeywordsPhysical medicine and rehabilitationGaitIntervention (counseling)Physical therapyPsychologyMotor skillMedicineNursingDevelopmental psychology

Abstract

fetched live from OpenAlex

This single group pre and posttest study evaluated the feasibility of a new 10-week group-based motor skills enhancement intervention: “Moving Together,” and associated use of the Challenge assessment and Gait Outcomes Assessment List (GOAL). Participant attendance/completion and satisfaction with the assessments and intervention were evaluated, and a first estimate of associated motor skill-related changes obtained. Ten ambulatory children with cerebral palsy (7–14 years) and their parents participated. Ninety percent of Challenge sessions were attended and 82.5% of GOAL questionnaires completed. Program attendance was 83% overall. Satisfaction with assessments was high for the Challenge and moderate for the GOAL, and intervention satisfaction was high. Mean change scores (95% CI) post-intervention for the Challenge and GOAL were 4.2 (−11.4 to 3.1) and 3.6 (−14.4 to 4.0) points (/100) respectively. Challenge and GOAL use was feasible and appropriate for “MovingTogether” and associated with gains in motor skill performance and functional abilities.

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 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 score0.836

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 integrity0.0000.000
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 head0.014
GPT teacher head0.294
Teacher spread0.281 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDevelopmental NeurorehabilitationSame topicCerebral Palsy and Movement DisordersFrench-language works237,207