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Record W2804194090 · doi:10.1177/2158244018778096

Self-Reported Physical Activity Among Individuals With Parkinson’s Disease

2018· article· en· W2804194090 on OpenAlexaff
Andrew M. Johnson, J. Jimenez-Pardo, Mary E. Jenkins, Jeffrey D. Holmes, Shauna M. Burke

Bibliographic record

VenueSAGE Open · 2018
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysical activityParkinson's diseasePsychologyBalance (ability)PopulationGerontologyDiseaseMedicineClinical psychologyPhysical medicine and rehabilitationEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Although physical activity is generally thought to be beneficial for individuals with Parkinson’s disease (PD), there is limited information regarding current rates of physical activity within this population. In this study, we measured self-reported physical activity levels of individuals with PD and explored factors that affected physical activity engagement. Sixty-one individuals living with PD completed a modified form of the Physical Activity Scale for Individuals With Physical Disabilities. Reported activity was high and exceeds published guidelines for individuals with limited mobility. Major facilitators of physical activity included (a) positive impact on PD-related symptoms, (b) social motivation, and (c) regularity or predictability of the activity. The major barrier to physical activity was PD symptom severity (e.g., lack of balance, gait impairment, tremor, and fatigue).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.306
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2018
Admission routes1
Has abstractyes

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