Exercise knowledge, barriers and motivators among LRRK2 G2019S mutation carriers
Bibliographic record
Abstract
INTRODUCTION: People with a Gly2019Ser mutation in the leucine-rich repeat kinase 2 (LRRK2 G2019S) are at increased risk of developing Parkinson's disease (PD). Recent evidence suggests that exercise may delay or prevent the development of clinically overt symptoms of PD in people at risk of PD. We determined whether LRRK2 G2019S mutation carriers with and without manifest PD are aware of the relationship between exercise and PD and how they differ in awareness, barriers and motivators to exercise. METHODS: We deployed a survey among 4422 LRRK2 G2019S mutation carriers. In total, 505 (11.4%) of them completed the survey, of whom 105 had self-reported manifest PD. RESULTS: Ninety-two percent of the LRRK2 G2019S mutation carriers with manifest PD and 63% of those with non-manifest PD were aware of the relationship between exercise and PD. Lack of motivation was the top barrier for those without manifest PD, while having an injury/disability was the most common barrier for those with manifest PD. Improvement of body functioning was the top motivator for both. CONCLUSION: The fact that many at-risk individuals are not aware of the importance of exercise and would exercise more with fewer barriers creates opportunities for trials using exercise as a possible prevention strategy for PD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".