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Record W3086309283 · doi:10.3233/jpd-202247

Barriers and Motivators to Engage in Exercise for Persons with Parkinson’s Disease

2020· review· en· W3086309283 on OpenAlexaff
Sabine Schootemeijer, Nicolien M. van der Kolk, Terry D. Ellis, Anat Mirelman, Alice Nieuwboer, Freek Nieuwhof, Michael A. Schwarzschild, Nienke M. de Vries, Bastiaan R. Bloem

Bibliographic record

VenueJournal of Parkinson s Disease · 2020
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsCentre for Movement Disorders
FundersFarmer Family FoundationZonMwParkinson's Foundation
KeywordsParkinson's diseaseDiseasePsychologyMedicineGerontologyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Exercise is increasingly being recognized as a key element in the overall management of persons living with Parkinson's disease (PD) but various (disease-specific) barriers may impede even motivated patients to participate in regular exercise. We aimed to provide a comprehensive review of the various barriers and motivators for exercise in persons with PD. We scrutinized data on compliance-related factors published in cross-sectional studies, randomized controlled trials and reviews. We classified the barriers and motivators to exercise from a patient perspective according to the International Classification of Functioning, Disability and Health. We present an overview of the large range of potential motivators and barriers for exercise in persons with PD. Healthcare professionals should consider a wide and comprehensive range of factors, in order to identify which specific determinants matter most for each individual. Only when persons with PD are adequately motivated in a way that appeals to them and after all person-specific barriers have been tackled, we can begin to expect their long-term adherence to exercise. Such long-term compliance will be essential if exercise is to live up to its expectations, including the hope that prolonged engagement in regular exercise might help to modify the otherwise relentlessly progressive course of PD.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.032
GPT teacher head0.312
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations199
Published2020
Admission routes1
Has abstractyes

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