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Record W4385661437 · doi:10.1002/bin.1970

An exploration of a physical activity intervention in a community fitness setting for adolescents with autism

2023· article· en· W4385661437 on OpenAlexaff
Laura Bassette, Shawna Sundberg, Abby Magnusen, Alysan Ramirez, Emily Badger

Bibliographic record

VenueBehavioral Interventions · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsAutismMultiple baseline designIntervention (counseling)PsychologyGeneralizationPhysical activityAutism spectrum disorderIndependence (probability theory)Developmental psychologyBaseline (sea)Clinical psychologyPhysical therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Abstract It is well established that adolescents with autism spectrum disorders often do not engage in physical activity, which may contribute to secondary health concerns (e.g., poor cardiovascular health and diabetes). The purpose of this study was to extend the research on a behavioral intervention package and address previous limitations (i.e., small number of exercises and minimal maintenance). A multiple baseline design across participants was used to determine if there was a functional relationship between the intervention and independence of physical activity, creating workouts, and navigating workouts. The results indicate that participants were able to acquire and maintain skills. When new exercises were presented in generalization, two participants demonstrated higher levels of independence in physical activity and one participant displayed a similar level to baseline. Implications and areas for future research are discussed.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.251
GPT teacher head0.473
Teacher spread0.222 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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