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Record W4405813014 · doi:10.1101/2024.12.22.24319526

Effects of a School-Based Physical Activity Intervention on Children with Intellectual Disability: A Cluster Randomised Trial

2024· preprint· en· W4405813014 on OpenAlexaff
Michael Noetel, Taren Sanders, Danielle Tracey, David R. Lubans, Viviene A. Temple, Andrew Bennie, James H. Conigrave, Mark Babic, Bridget Booker, Rebecca Pagano, James Boyer, Chris Lonsdale

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCluster randomised controlled trialIntervention (counseling)Cluster (spacecraft)PsychologyIntellectual disabilityPhysical therapyMedicineDevelopmental psychologyClinical psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Abstract Importance Young people living with disability have poorer health outcomes than their typically developing peers. They are less physically active and at increased risk of chronic disease. Teacher-led, whole-of-school physical activity interventions are promising levers for population-level change, but are seldom tested among children with disability. Objective To evaluate the effect of a blended teacher-professional learning program (online and in-person) on fundamental movement skills among children with disability. Design, Setting, and Participants In this cluster randomised clinical trial, we randomised 20 government-funded primary schools, including 238 consenting students between Grades 2-5. Ten schools received the blended teacher-professional learning intervention and 10 received the control intervention. The professional learning was designed to support teachers as they implemented a whole-of-school intervention designed to enhance fundamental movement skills and increase physical activity levels. Recruitment and baseline assessments occurred in 2020. Research assistants, blinded to treatment allocation, completed follow-up outcome assessments at 21 months. Interventions The school-based intervention was mostly online learning for teachers, followed by one lesson observation from a project mentor and one from a peer. Between one and three teachers also met quarterly with the mentor to plan whole-of-school strategies to promote activity. Main Outcomes and Measures Test of Gross Motor Development-3 test of fundamental movement skill competency. Secondary outcomes were self-concept, enjoyment, wellbeing, 300-yard run time, and accelerometer-measured physical activity. Results We found no significant group-by-time effects for the primary outcome (fundamental movement skill competency: b = 1.07 [95% CI -3.70, 5.84], p = .658) or any of the secondary outcomes. About half the teachers assigned to the training completed the modules. Conclusions and Relevance In this study, a school-based intervention did not improve children’s fundamental movement skill competency or any other outcomes. Results may be attenuated by the disruptive effects of the COVID-19 pandemic due to reduced teacher participation and delayed post-test measurement. Alternatively, low intensity teacher-professional learning interventions may not be enough to improve motor competence or physical activity among children with intellectual disability. Key Points Question Does a blended-learning intervention for teachers improve fundamental movement skills among children with intellectual disability? Findings In this cluster randomised clinical trial of 20 schools and 238 children, a blended teacher-professional learning intervention did not improve fundamental movement skill competency at 21 months. Meaning Given similar programs increased outcomes among typically developing children, results of this randomised clinical trial suggest different models are needed to support children with disability.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.036
GPT teacher head0.365
Teacher spread0.330 · 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 designRandomized 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

Citations0
Published2024
Admission routes1
Has abstractyes

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