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Record W4401998021 · doi:10.1002/mdc3.14197

Exercise Habits in People with Parkinson's: A Multinational Survey

2024· article· en· W4401998021 on OpenAlexaff
Priya Jagota, Phanupong Phutrakool, Nitish Kamble, Thuong Huyen Thi Dang, Zakiyah Aldaajani, Taku Hatano, Deva Kumar Hoskere Sreenivasa, Telugu Tripura, Prashanth Lingappa Kukkle, Beomseok Jeon, Noriko Nishikawa, Yutaka Oji, Tai Ngọc Tran, Frandy Susatia, Margherita Fabbri, Clémence Leung, Araceli Alonso‐Cánovas, Walaa A. Kamel, Pramod Kumar Pal, K. Rakesh, Muneer Abu Snineh, Parnsiri Chairangsaris, Praween Lolekha, Roland Dominic G. Jamora, Norlinah Mohamed Ibrahim, Siti Hajar Mat Desa, Ai Huey Tan, Tzi Shin Toh, Mona Obaid, Victor S.C. Fung, Anthony E. Lang, Chin‐Hsien Lin, Wafa Regragui, Naïma Bouslam, Roongroj Bhidayasiri

Bibliographic record

VenueMovement Disorders Clinical Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersNational Institute of Mental HealthPhilippine Council for Health Research and DevelopmentFaculty of Medicine, Chulalongkorn UniversityJapan Society for the Promotion of ScienceCollege of Medicine, Seoul National UniversityItalfarmacoOno PharmaceuticalEisaiMinistério da Ciência, Tecnologia e InovaçãoThailand Science Research and InnovationThammasat UniversityMultiple System Atrophy CoalitionKementerian Sains, Teknologi dan InovasiSun PharmaSeoul National UniversitySinyang Cultural FoundationChulalongkorn UniversityIpsenSunovionH. Lundbeck A/SNational Institute of Mental Health and NeurosciencesDepartment of Science and Technology, Ministry of Science and Technology, IndiaKing Fahad Medical CityIndian Council of Medical ResearchTeva Pharmaceutical IndustriesSeoul National University HospitalScience and Engineering Research BoardDepartment of Biotechnology, Ministry of Science and Technology, IndiaMichael J. Fox Foundation for Parkinson's Research
KeywordsMultinational corporationParkinson's diseasePsychologyMedicinePhysical medicine and rehabilitationBusinessInternal medicineFinance

Abstract

fetched live from OpenAlex

BACKGROUND: Exercise has been demonstrated to result in improvements in physical function, cognition, and quality of life in People with Parkinson's (PwP) but its adoption is variable. OBJECTIVES: To investigate exercise preferences, levels, influencing factors among a diverse Parkinson's disease (PD) population, to understand exercise adoption patterns and plan informed interventions. METHODS: A cross-sectional survey collected data through online platforms and paper-based methods. The Exercise Index (ExI) calculated exercise level based on frequency and duration. RESULTS: Of 2976 PwP, 40.6% exercised regularly, 38.3% occasionally, and 21.2% did not exercise. The overall mean ExI was 18.99 ± 12.37. Factors associated with high exercise levels included exercising in groups (ExI 24-26), weightlifting (ExI 27 (highest)), using muscle-building equipment (ExI 25-26), and exercising at home following an app (ExI 26). A positive trend between ExI and varied exercise groups, locations, types, and equipment was observed. No expected benefit from exercise achieved the lowest ExI (8). Having at least two exercise-promoting factors, a bachelor's degree or higher, receiving exercise advice at initial visits, and aged ≤40 years at PD onset were strong predictors of exercise (adjust OR = 7.814; 6.981; 4.170; 3.565). Falls and "other" most troublesome PD symptoms were negative predictors (aOR = 0.359; 0.466). Barriers to exercise did not predict the odds of exercise. CONCLUSIONS: The study shows that PwP's exercise behavior is influenced by their exercise belief, age at PD onset, doctor's advice at initial visits, education level, symptoms, and exercise-promoting factors. High exercise levels were associated with certain types of exercises and exercising in groups.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.128
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.364
Teacher spread0.332 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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