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Record W4417009853 · doi:10.1123/apaq.2025-0024

The Effectiveness of an e-Learning Program for Educating Physical Activity Professionals on Supporting Autistic Individuals in Physical Activity

2025· article· en· W4417009853 on OpenAlexaff
Jasmin Ezaddoustdar, Lauren Tristani, Tobi McEvenue, Rebecca Bassett‐Gunter

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsAutism CanadaYork University
Fundersnot available
KeywordsPhysical activityAutismTheory of planned behaviorGoal settingSelf-efficacyPhysical activity level

Abstract

fetched live from OpenAlex

Physical activity (PA) benefits autistic1 individuals, yet barriers including limited support from PA professionals hinder PA engagement. Guided by the theory of planned behavior and the diffusion of innovations theory, this study used a quasi-experimental one-group pretest-posttest design to investigate the effectiveness and practicality of an e-learning program in changing PA professionals' intention and confidence to support autistic individuals in PA. PA professionals (N = 49) completed the Strong Minds Through Active Bodies e-learning program, as well as pre- and postevaluations. Results showed significant improvements in all theory of planned behavior constructs and positive feedback on the module's practicality. Tailored e-learning can enhance PA professionals' understanding and confidence in meeting the unique needs and preferences of autistic individuals in PA. Further research is warranted to understand how e-learning may be leveraged as a tool to foster more inclusive programs, ultimately encouraging greater participation by creating accessible and engaging PA environments that are supportive and conducive to active engagement for autistic individuals.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.027
GPT teacher head0.401
Teacher spread0.374 · 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.

Study designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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