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Record W1992740254 · doi:10.7224/1537-2073-11.3.114

Physical Activity Levels in People with Multiple Sclerosis in Saskatchewan

2009· article· en· W1992740254 on OpenAlexaboutno aff
Angela S. Currie, Katherine Knox, Karen E. Glazebrook, Lawrence R. Brawley

Bibliographic record

VenueInternational Journal of MS Care · 2009
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical activityMultiple sclerosisDemographicsPhysical therapyDemographyPsychiatry

Abstract

fetched live from OpenAlex

A substantial body of literature supports the benefits of physical activity for people with multiple sclerosis (MS). This study examined the types and amounts of physical activity reported by a cross-sectional sample of people with MS in Saskatchewan, Canada. Individuals with MS who were seen in the Saskatoon Multiple Sclerosis Clinic in 2006 were mailed a physical activity survey. Demographic information was collected from a confidentiality-protected clinical database. The response rate was 38.2% (108 of 283). No statistically significant differences in baseline demographics were found between responders and nonresponders. Of the responders, 93.5% engaged in some form of moderate physical activity at least once per week. Of these, 15.7% participated in group classes (mean [SD], 2.35 [1.32] days per week), 63.9% performed a minimum of 15 minutes of self-directed continuous activity (mean [SD], 4.5 [1.8] days per week), and 88.0% accumulated short bouts of moderate physical activity totaling a minimum of 20 minutes daily (mean [SD], 5.4 [1.9] days per week). In addition, 28.7% of responders reported that daily self-care required moderate physical effort. Physical activity decreased with increasing disability. The majority of responders participated in regular physical activity when multiple types of activity are considered. All activity sources should be considered when examining activity levels of individuals with MS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.373

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.338
Teacher spread0.286 · 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.

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

Citations8
Published2009
Admission routes1
Has abstractyes

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