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Record W7025047851

Strategies to Improve Physical Activity Involvement for Children with Exceptionalities: Exploring Teachers' and Parents' Perceptions and Experiences

2022· dissertation· en· W7025047851 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical activityPerceptionCognitionNumeracyAutismMeaning (existential)Focus groupPerspective (graphical)
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, the focus is on the specific strategies parents and educators are using to encourage children with exceptionalities, particularly children with a learning disability, intellectual disability, attention deficit hyperactivity disorder, and autism spectrum disorder, to be involved in physical activity. As defined by Caspersen et al. (1985), physical activity is any bodily movement by skeletal muscles that expends energy. Recent statistics have reported the recommended amounts of physical activity for children compared to what they are actually engaging in. The Canadian 24-hour Movement Guidelines for Children and Youth (2016) recommends that children aged 5-17 accumulate 60 minutes of physical activity per day, meaning moderate-to-vigorous physical activity involving aerobic activities, coupled with light physical activity involving a range of structured and unstructured physical activities. In comparison, a recent health report shows that only one-third of children are able to meet this recommendation (Colley et al., 2017). Further research shows that children with exceptionalities are participating in physical activity even less than children without exceptionalities, and as a result, are overweight, less physically fit, less motor proficient, fatigued, and in pain (Carlon et al., 2013; Davis et al., 2010; Frey & Chow, 2006; Frey, Stanish & Temple, 2008; Rimmer, 2005). Children with exceptionalities participating infrequently in physical activity is a major problem, as physical activity can have a key impact on the overall health and well-being of a child, designated by five health and well-being indicators: cognitive development, which includes facets such as the acquisition of reading, writing, and numeracy skills; physical health and well-being, which focuses on the absence of disease through markers such as good eating habits and having opportunities for recreational activities; social relationships, defined by the relationships that the child engages in with parents, teachers, coaches, and teachers that are close, trusted, caring, and accepting; mental and emotional health and well-being, where a child possesses characteristics such as optimism, positive self-worth, and a stability; and economic and material health and well-being, where a child has access to nutritious food, adequate housing and clothing (Canadian Institute for Health Information, 2013).\nAlthough numerous studies demonstrate the importance of physical activity for all children, including those with exceptionalities, in relation to these five health and well-being indicators (Bell et al, 2019; Chang et al., 2012; Davis & Jowett, 2014; Dunton et al., 2014; Gapin & Etnier, 2010; Kang et al., 2011; Kiluk et al., 2008; MacMahon & Gross, 1987; McMahon et al. 2019; Nakutin et al., 2019; Pan, 2010; Pastula et al., 2012; Ratey, 2008; Wilk et al., 2018; Wouters et al., 2019; Yilmaz et al., 2004), there is limited current research exploring how educators and parents are engaging children with exceptionalities in physical activity (Davis et al., 2010; Norris & Columna, 2016; Ratey, 2008; Rauworth et al., 2003; Seidler et al., 1993; Walker et al., 2019). Discovering specific strategies that parents and educators are implementing on a consistent basis is a must in order to engage children with exceptionalities in physical activity and, as a result, improve their overall health and well-being.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.266
Teacher spread0.239 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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