Exercise Management Using a Mobile App in Patients With Parkinsonism: Prospective, Open-Label, Single-Arm Pilot Study
Bibliographic record
Abstract
BACKGROUND: Patients with parkinsonism have higher inactivity levels than the general population, and this results in increased comorbidities. Although exercise has benefits for motor function and quality of life (QOL) in patients with parkinsonism, these patients face many barriers to exercise participation, such as lack of motivation, fatigue, depression, and time constraints. Recently, the use of mobile apps has been highlighted as a remote exercise management strategy for patients with chronic diseases. OBJECTIVE: This study aimed to evaluate the effects of home-based exercise management with a customized mobile app on the exercise amount, physical activity, and QOL of patients with parkinsonism. METHODS: This was a prospective, open-label, single-arm pilot study. The therapist installed the app in the smartphones of the participants and educated them on how to use the app. The therapist developed an individualized multimodal exercise program that consisted of stretching, strengthening, aerobic, balance and coordination, and oral-motor and vocal exercises. Participants were encouraged to engage in an 8-week home-based exercise program delivered through a customized app. The alarm notifications of the app provided reminders to exercise regularly at home. The primary outcome was the exercise amount. The secondary outcomes were assessed using the International Physical Activity Questionnaire (IPAQ), Parkinson's Disease Questionnaire-39 (PDQ-39), and Geriatric Depression Scale (GDS). The usability of the customized app was assessed using a self-report questionnaire. RESULTS: A total of 21 participants with parkinsonism completed the intervention and assessment between September and December 2020 (mean age: 72 years; women: 17/21, 81%; men: 4/21, 19%). The participants reported a significant increase in the total amount of exercise (baseline: mean 343.33, SD 206.70 min/week; 8-week follow-up: mean 693.10, SD 373.45 min/week; P<.001) and in the amount of each exercise component, including stretching, strengthening, balance and coordination, and oral-motor and vocal exercise after 8 weeks. Analysis of the secondary outcomes revealed significant improvements in the IPAQ (P=.006), PDQ-39 (P=.02), and GDS (P=.04) scores. The usability of the program with the mobile app was verified based on the positive responses such as "intention to use" and "role expectation for rehabilitation." CONCLUSIONS: Exercise management with a customized mobile app may be beneficial for improving exercise adherence, physical activity levels, depression management, and QOL in patients with parkinsonism. This remotely supervised technology-based, reinforcing, and multimodal exercise management strategy is recommended for use in patients with parkinsonism. In addition, this program proved useful as an alternative exercise management strategy during the COVID-19 pandemic when patients with Parkinson disease were less physically active than before and showed aggravation of symptoms. However, additional clinical trials are needed to evaluate the efficacy of this exercise program in a large population and to confirm its disease-modifying effects.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".