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Record W4406794767 · doi:10.1123/apaq.2024-0109

A Characterization of Physical Activity in People Living With Advanced Multiple Sclerosis

2025· article· en· W4406794767 on OpenAlexaff
Julia Ludgate, Thomas Edwards, Katherine Cardwell, Afolasade Fakolade, Lara A. Pilutti

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsQueen's UniversityUniversity of Ottawa
Fundersnot available
KeywordsMultiple sclerosisExpanded Disability Status ScaleWheelchairPhysical activityPhysical therapyMedicineGerontologyPsychologyPhysical medicine and rehabilitationPopulationEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Little is known about physical activity (PA) participation in people with advanced multiple sclerosis (MS). The purpose of this study was to (a) characterize self-reported PA levels and (b) explore how PA levels might differ based on sociodemographic (e.g., gender) and clinical (e.g., MS clinical course) characteristics in people with advanced MS. We used a cross-sectional online survey design with 101 participants. PA was measured using the Physical Activity Scale for Individuals With Physical Disabilities. The mean score on the scale was 4.5 (SD = 5.9) metabolic equivalent hours per day. There was a significant difference in scores based on employment, population density, living situation, disability, and assistive-device type (all p < .05). PA levels were higher in those who were employed, lived alone, required bilateral support for mobility, and were manual wheelchair users (all p < .05). This study highlights low PA levels in people with advanced MS and potential variables that might impact PA in this MS subgroup.

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)
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 score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.288
Teacher spread0.261 · 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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