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Record W2257149495 · doi:10.1177/1352458515606526

Physical activity and pediatric multiple sclerosis: Developing a research agenda

2015· review· en· W2257149495 on OpenAlexaff
E. Ann Yeh, Dominique Kinnett-Hopkins, Stephanie A. Grover, Robert W. Motl

Bibliographic record

VenueMultiple Sclerosis Journal · 2015
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMultiple sclerosisNeurocognitiveMedicineDiseasePhysical activityDepression (economics)MEDLINEPhysical therapyPediatricsPsychologyPhysical medicine and rehabilitationGerontologyCognitionPsychiatryPathology

Abstract

fetched live from OpenAlex

Three-quarters of children with multiple sclerosis (MS) experience fatigue or depression, and progressive neurocognitive decline may be seen as early as two years after MS diagnosis. Furthermore, a higher magnetic resonance imaging disease burden is seen in pediatric-onset MS compared with adult-onset MS. To date, limited knowledge exists regarding behavioral methods for managing symptoms and disease progression in pediatric MS. To that end, this paper builds an evidence-based argument for the possible symptomatic and disease-modifying effects of exercise and physical activity in pediatric MS. This will be accomplished through: (a) a review of pediatric MS and its consequences; (b) a brief overview of physical activity and its consequences in children and adults with MS; and (c) a selective review of research on the neurological benefits of physical activity in pediatric populations. This topical review concludes with a list of 10 questions to guide future research on physical activity and pediatric MS. The objective of this paper is the provision of a research interest, focus and agenda involving pediatric MS and its lifelong management though exercise and physical activity behavior. Such an agenda is critical as the effects and maintenance of physical activity and exercise track across the lifespan, particularly when developed in the early stages of life.

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)0.007
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.007
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 head0.584
GPT teacher head0.464
Teacher spread0.120 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations19
Published2015
Admission routes1
Has abstractyes

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