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Record W3151225537 · doi:10.1123/apaq.2020-0136

“How Come You Sent Me the Canadian One?” Application and Uptake of the Canadian Physical Activity Guidelines for Adults With Multiple Sclerosis in the United States

2021· article· en· W3151225537 on OpenAlexaboutno aff
Whitney N. Neal, Emma V. Richardson, Robert W. Motl

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisPhysical activityPsychologyThematic analysisGerontologyMedical educationPhysical therapyMedicineQualitative researchPsychiatrySociology

Abstract

fetched live from OpenAlex

The uptake and benefits of the Canadian Physical Activity Guidelines for Adults with Multiple Sclerosis (PAGs) have been validated, but there is limited understanding regarding the knowledge, needs, and preferences of people with multiple sclerosis (MS) for implementing the PAGs outside of clinical research. The authors conducted online, semistructured interviews with 40 persons with MS from across the United States seeking information on awareness of and potential approaches for increasing the uptake of the PAGs. They identified first impressions and potential approaches for increasing the uptake of the PAGs through inductive, semantic thematic analysis. Participants perceived the PAGs as a good introduction for structured exercise but desired more information on how to meet the PAGs. Participants further believed that modifying the PAGs for inclusivity and applying a multifaceted approach for dissemination and implementation may increase uptake of exercise behavior. Physical activity research in MS should include both analyzing the effects of exercise and the unique challenges faced by persons with MS in putting the PAGs into practice.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.097
GPT teacher head0.313
Teacher spread0.216 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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