Brazilian dance self-perceived impacts on quality of life of people with Parkinson’s
Bibliographic record
Abstract
Background: Parkinson’s disease (PD) causes several motor and non-motor symptoms, resulting in negative impacts on physical, mental, emotional, and social aspects of people with PD quality of life. Dance has been considered as a potential non-pharmacological intervention to improve people with PD motor and non-motor symptoms, thereby enhancing quality of life. Purpose: To analyze the self-perceive impacts of Brazilian Dance on the quality of life (physical, mental, emotional, and social) of PwPD, both before and during the COVID-19 pandemic. Methods: Fourteen participants from the “Dança & Parkinson” project were included in this qualitative study. Data collection instruments consisted of a profile and personal data sheet; assessment of accessibility to the online dance classes; Telephone Montreal Cognitive Assessment by phone call; and semistructured interview conducted through ZOOM video call. The participants characterization data were calculated using mean, standard deviation, and percentages with the Excel Program version 2013. Qualitative data was analyzed using the Thematic Analysis technique in the Nvivo, version 8.0, qualitative analysis of text, sound, and video program. Results: The participants reported facing various challenges in dealing with PD, which negatively impact their quality of life. However, their resilience, acceptance, and dedication to treatment play an important role in coping with the issues related to the disease. Brazilian dance, both in-person before the COVID-19 pandemic and online during the pandemic, led the participants to perceive improvements in physical, mental, emotional, and social aspects of quality of life. Conclusion: The Brazilian dance appears to have a positive impact on the physical, mental, emotional, and social aspects of the participants’ quality of life, both before and during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.127 | 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 teacher head, 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".