Register      Login
Brain Impairment Brain Impairment Society
Journal of the Australasian Society for the Study of Brain Impairment
RESEARCH ARTICLE (Open Access)

Increasing exercise with a mobile app in people with Parkinson’s disease: a pilot study

Jong Hyeon Ahn https://orcid.org/0000-0002-6415-2316 A B # , Dongrul Shin https://orcid.org/0009-0006-1750-7707 C # , Dongyeong Lee https://orcid.org/0000-0001-6093-3900 A B , Hye Young Kim https://orcid.org/0000-0002-0132-6550 B , Jinyoung Youn https://orcid.org/0000-0003-3350-5032 A B and Jin Whan Cho https://orcid.org/0000-0002-9145-6729 A B *
+ Author Affiliations
- Author Affiliations

A Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea.

B Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea.

C Department of Urology, Asan Medical Center, Songpa-gu, Seoul, Republic of Korea.

* Correspondence to: jinwhan.cho@samsung.com
# These authors contributed equally to this paper

Handling Editor: Suzanne Kuys

Brain Impairment 25, IB23061 https://doi.org/10.1071/IB23061
Submitted: 8 June 2023  Accepted: 4 February 2024  Published: 22 March 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the Australasian Society for the Study of Brain Impairment. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

Exercise is crucial for the well-being of people with Parkinson’s disease (PD). Although there are challenges to exercising with PD, mobile apps are seen as potential solutions, though their impact is not yet fully understood. We developed a mobile app and a home-based exercise program specialised for people with PD and investigated the effect of the mobile exercise app for the people with PD.

Methods

Participants from the Movement Disorder Clinic were prompted to download and actively use our app for a duration of 2 weeks. Before commencing, we assessed their self-rated smartphone proficiency. Both at the start and after the 2-week period, we employed the International Physical Activity Questionnaire-Short Form and the PD Questionnaire-39 (PDQ-39) to evaluate their physical activity and overall quality of life (QoL). Exercise metrics were quantified in terms of metabolic equivalent minutes per week (MET-min/week). Furthermore, we gathered feedback on user satisfaction with the app at the end of the study.

Results

Out of 41 recruited patients, 25 completed the 2-week program and 16 dropped out. Median MET-min/week rose from 1386.0 to 3210.0 (P = 0.009), primarily in moderate activities (P = 0.049) and walking (P = 0.002). Median PDQ-39 scores showed improvement from 17.2 to 8.5 (P = 0.005) after the program.

Conclusion

The mobile app holds potential to enhance exercise and QoL for people with PD. For optimal benefits, future studies should focus on e-health literacy education, app quality enhancements, and a broader exercise program variety.

Keywords: application, COVID-19, digital healthcare, exercise, mobile app, motivation, Parkinson’s disease, remote exercise.

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterised by bradykinesia, rigidity, resting tremor, postural instability, and gait disturbance. These symptoms significantly diminish the quality of life (QoL) of those affected. Pharmacological and surgical interventions are often employed to manage the disease. Recent evidence suggests that exercise plays a crucial role in alleviating symptoms and improving overall well-being in people with PD (Mak et al. 2017). However, numerous barriers often prevent people with PD from participating in traditional face-to-face exercise programs. These barriers include physical discomfort, non-motor symptoms, poor accessibility of exercise locations, transportation issues, discomfort in crowded spaces, and financial burden (Schootemeijer et al. 2020). The COVID-19 pandemic has intensified these challenges. This situation underscores the pressing need for more accessible exercise alternatives for people with PD (Song et al. 2020; Langer et al. 2021).

In response to these challenges, various methods and technologies have been explored to facilitate exercise and rehabilitation for people with PD, including community-based resources, virtual reality, telerehabilitation, and motivational tools (Langer et al. 2021; Lau et al. 2021). Mobile apps are increasingly being recognised as valuable tools for motivating individuals with osteoarthritis and knee pain (Danbjørg et al. 2018; Shah et al. 2023). Furthermore, they can offer personalised exercise programs tailored to the specific needs of people with PD, enhancing accessibility (Linares-Del Rey et al. 2019). However, there remains limited scientific evidence on the effectiveness of mobile apps in increasing exercise levels and improving the QoL for individuals with PD (Langer et al. 2021).

To bridge this gap in the literature, we designed a mobile app with a specialised home-based exercise program for people with PD. We investigated whether the app effectively improves physical activity in people with PD, focusing on its potential to reduce barriers, such as poor accessibility to exercise locations, transportation issues, and financial burden.

Methods

Participants

Participants were recruited from the Movement Disorder Clinic of the Samsung Medical Center. The inclusion criteria for participants were (1) a diagnosis of PD based on the UK Parkinson’s Disease Brain Bank Criteria (Hughes et al. 1992), (2) a modified Hoehn and Yahr (H&Y) stage ≤3 (Hoehn and Yahr 1967), and (3) without dementia (Mini-Mental State Examination (MMSE) ≥26). The exclusion criteria were (1) cardiovascular, musculoskeletal, visual impairment or other neurological disorders that can affect exercise and (2) psychiatric disorders, including major depression. This study was approved by the Institutional Review Board of the Samsung Medical Centre, and all participants provided written informed consent. This trial was registered with the Clinical Research Information Service in Korea (KCT0006671).

Mobile app, home-based exercise program, and motivational strategies

The app and home-based exercise program were specifically developed for people with PD and the present study. To motivate exercising, we designed a free mobile app for the present study. The application included (1) a home-based exercise program that does not require any special tools; (2) in-app notifications, which are messages that a researcher can deliver to users to remind them to use the app and perform exercise every morning on weekdays; (3) in-app compliments when the participants performed their exercises; and (4) a tracking system for the number of times the participants have exercised in the last week, last 2 weeks, and last month. The home-based exercise program for PD was developed by professional exercise instructors (H. Y. Kim) and movement specialists (J. W. Cho, J. Youn, and J. H. Ahn). The exercise videos were filmed, and 21 exercise videos were developed. Each video lasted approximately 15–20 min. The program included moderate-intensity exercises: sitting in the right position; walking with the right posture; and stretching and strengthening exercises for the neck/shoulder, back, legs/knees/ankles, and hands/wrists.

The mobile app is available for Android (https://play.google.com/store/apps/details?id=com.movement.PDexercise) or as a progressive web app (https://previewer.adalo.com/594d5e06-c8c9-4ee0-94d5-e0ef4668c8a6). The app was made in Korean, and only designated users were allowed access to the username and password created for each participant. Prior to beginning the exercise program, participants received a 30-min training session that covered how to use and record their exercises using the app. Additionally, we gave each participant a printed manual for reference. They also learned how to answer follow-up assessments embedded in the app. Participants could login to the app with their username and password and select 1 of the 21-exercise videos on the home screen. If they touched a selected video, the screen was connected to the exercise video screen (Fig. 1). The participants could watch a video or switch to another video. Below the video, a brief description of the exercise was provided. Participants could record their exercise by touching the ‘exercise done’ button at the bottom of the screen. The records were automatically recorded on a web-based database, and only the user who recorded them and the researcher could see the personal records. The compliance of each participant was investigated through these self-reported records. Participants can track the number of times they have exercised since the last week, last 2 weeks, and last month. The in-app alarm went off every weekday morning to remind the participants to use the app and perform exercise.

Fig. 1.

The home screen, exercise video screen, tracking system and search system screen of the app.


IB23061_F1.gif

Clinical assessments

The clinical and demographic features of the patients were investigated. At the baseline (T1), the following assessments were administered: U PD Rating Scale-III (UPDRS-III) (Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease 2003), H&Y stage, levodopa equivalent daily dose (LEDD), MMSE (Folstein et al. 1975), questionnaire for assessing confidence in using a smartphone (Kim 2016), International Physical Activity Questionnaire-Short Form (IPAQ-SF), and PD Questionnaire-39 (PDQ-39). The IPAQ-SF and PDQ-39 were further assessed after 2 weeks (T2). User satisfaction, adverse events while using the app, and a survey about the app were assessed at T2.

The IPAQ-SF is a validated scale to assess physical activity (Chun 2012). The IPAQ-SF comprises a seven-item questionnaire to record the frequency and duration of four intensity levels of exercise: (1) vigorous-intensity activity, (2) moderate-intensity activity, (3) walking, and (4) sitting. Participants were asked to respond to the number of days that these activities were performed and the meantime per day. The metabolic equivalent minutes per week (MET-min/week) was calculated using the following formula: MET level × min of activity/day × days per week. The MET for vigorous-intensity activity was 8.0, moderate-intensity activity was 4.0 MET, and walking was 3.3 MET. The total MET-min/week were calculated by summing the METs of the three activities (Chun 2012).

Prior to the start of the program, participants completed a 15-item questionnaire using a four-point Likert scale (4: very confident, 3: fairly confident, 2: not very confident, 1: not at all confident) to investigate how confident participants were in using smartphones (Supplementary Table S1). The questionnaire we used for the present study is part of a validated survey to assess digital literacy in the Korean elderly and is validated (Kim 2016). A higher score indicates higher confidence in using a smartphone.

At the study’s conclusion, participants additionally completed a user satisfaction survey about the mobile app. The questionnaire comprised four items on a five-Likert scale (strongly agree, agree, neutral, disagree, strongly disagree) comprising the following statements: (1) I am satisfied with the app, (2) using the app is generally helpful to me, (3) I am satisfied with the exercise program included in the app, and (4) the duration of each exercise video was appropriate. The adverse events associated with using the app (falls, near falls, and any trauma) were also investigated. Questionnaires were collected using a survey form embedded in the mobile app.

Statistical analysis

The primary outcome of this study was to evaluate the change in MET-min/week measured by the IPAQ-SF after a 2-week exercise program using the app. We compared baseline and post-program MET-min/week using a Wilcoxon signed-rank test. A previous study has demonstrated that mean change in MET-min/week was associated with and improved the health-related QoL for people with PD (Lee et al. 2019). In order to determine the required sample size for our study, we referred to the mean and standard deviation of MET-min/week obtained from a previous study (Lee et al. 2019). Taking into consideration a 20% dropout rate, we calculated that a minimum of 24 patients were needed to achieve a statistical power of 0.8 with a significance level of 0.05, based on these parameters. Normality of the data was evaluated using the Shapiro–Wilk test, a Q–Q plot, and a histogram. Patient clinical and demographic features are presented as the median and interquartile range (IQR). Changes in the IPAQ-SF and PDQ-39 Summary Index (SI) were compared using the Wilcoxon signed-rank test or paired t-test. We compared the completed 2-week program and dropouts using the Student’s t-test, Mann–Whitney test or Chi-squared test. A Pearson correlation analysis was used to investigate the association between the number of completed exercises and the amount of exercise measured in MET-min/week, as well as their correlation with the PDQ-39 SI. Statistical analysis was performed using the IBM SPSS (ver. 27.0; IBM Inc., USA) software for Windows.

Results

A total of 41 patients were recruited, of whom 25 completed the 2-week program and 16 did not (Fig. 2). The demographic and clinical characteristics are described in Table 1. The median number of exercises completed by the participants was 26.0 with an IQR of 14.5–34.0. The median MET-min/week significantly increased from 1386.0 to 3210.0 MET-min/week (P = 0.009), especially in the moderate-intensity (P = 0.049) and walking activities (P = 0.002) but not in the vigorous-intensity activity (P = 0.306, Fig. 3a). The PDQ-39 SI also improved after the 2-week program, especially in terms of activities of daily living (ADL), emotional well-being, cognition, communication, and bodily discomfort (Table 2 and Fig. 1). Correlation analysis showed that the number of completed exercises exhibited positive correlation with change of moderate (P = 0.016, r = 0.477), walking (P = 0.033, r = 0.428) and total MET-min/week (P = 0.009, r = 0.511) but not with vigorous exercise (P = 0.101, r = 0.336, Fig. 3c). The results of our study indicate that there was no correlation between the decrease of PDQ-39 SI and the number of completed exercises or MET-min/week. In the user satisfaction survey, 96.2 and 84.6% of the participants reported that they were satisfied with the app and exercise programs, respectively (Supplementary Table S2). No participants reported any adverse events while using the app (Supplementary Table S2).

Table 1.Demographics and clinical characteristics.

Complete 2-week program (n = 25)Dropouts (n = 16)P value
Age (year)64.1 (58.8, 70.1)65.8 (57.2, 72.6)0.877B
Male (%)13 (52.0%)10 (62.5%)0.540D
Disease duration (m)23.0 (16.0, 63.0)35.0 (11.5, 63.5)0.688C
UPDRS-III11.0 (7.5, 14.5)13.0 (8.3, 15.8)0.817B
H&Y stage2.0 (1.0, 2.0)2.0 (1.0, 2.0)0.906C
LEDD (mg/day)175.0 (120.0, 450.0)255.0 (185.0, 476.3)0.228C
MMSE29.0 (28.0, 30.0)29.0 (27.0, 30.0)0.923C
Education (year)12.0 (9.0, 14.0)12.0 (9.0, 16.0)0.762C
BMI (kg/m2)25.2 (23.3, 28.1)23.0 (20.2, 25.4)0.030B
No. of completed exercises26.0 (14.5, 34.0)2.0 (1.0, 3.0)<0.001C
IPAQ-SFA1386.0 (1035.0, 2868.0)1264.0 (1013.9, 2746.5)0.718C
 VigorousA240.0 (0.0, 720.0)280.0 (0.0, 660.0)0.902C
 ModerateA480.0 (10.0, 1120.0)480.0 (40.0, 720.0)0.978C
 WalkingA792.0 (495.0, 1287.0)800.3 (336.6, 1179.8)0.698C
PDQ-39 SI17.2 (9.1, 26.2)13.5 (7.1, 22.5)0.439C
 Mobility11.3 (5.0, 30.0)10.0 (3.1, 24.4)0.579C
 ADL16.7 (5.2, 24.0)6.3 (0.0, 19.8)0.160C
 Emotional well-being18.8 (5.2, 35.4)20.8 (8.3, 36.5)0.846C
 Stigma18.8 (6.3, 37.5)18.8 (7.8, 42.2)0.801C
 Social support0.0 (0.0, 6.3)0.0 (0.0, 14.6)0.884C
 Cognition18.8 (6.3, 31.3)12.5 (12.5, 25.0)0.568C
 Communication8.3 (0.0, 22.9)0.0 (0.0, 22.9)0.224C
 Bodily discomfort25.0 (8.3, 50.0)25 (10.4, 33.3)0.635C

Data are presented as the median and interquartile range (IQR).

UPDRS, Unified Parkinson’s Disease Rating Scale; H&Y, Hoehn and Yahr; LEDD, levodopa equivalent daily dose; MMSE, Mini-Mental State Examination; BMI, body mass index; IPAQ-SF, International Physical Activity Questionnaire-Short Form; PDQ-39 SI, Parkinson’s Disease Questionnaire-39 Summary Index; ADL, activities of daily living.

A The amount of exercise is presented as metabolic equivalent minutes per week (MET-min/week).
B Student’s t-test was used for statistical analysis.
C Mann–Whitney test was used for statistical analysis.
D Chi-squared test was used for statistical analysis.
Table 2.Changes in the International Physical Activity Questionnaire-Short Form and Parkinson’s Disease Questionnaire-39.

T1 (baseline)T2 (after 2 weeks)P value
IPAQ-SF totalA1386.0 (1035.0, 2868.0)3210.0 (1686.0, 4257.0)0.009
 VigorousA240.0 (0.0, 720.0)320.0 (40.0, 1440.0)0.306
 ModerateA480.0 (10.0, 1120.0)840.0 (360.0, 1800.0)0.049
 WalkingA792.0 (495.0, 1287.0)1386.0 (643.5, 2194.5)0.002
PDQ-39 SI17.2 (9.1, 26.2)8.5 (3.0, 19.1)0.005
 Mobility11.3 (5.0, 30.0)5.0 (0.6, 14.4)0.054
 ADL16.7 (5.2, 24.0)6.3 (0.0, 12.5)0.012
 Emotional well-being18.8 (5.2, 35.4)8.3 (4.2, 24.0)0.041
 Stigma18.8 (6.3, 37.5)9.4 (0.0, 29.7)0.098
 Social Support0.0 (0.0, 14.6)0.0 (0.0, 6.3)0.670
 Cognition18.8 (6.3, 31.3)6.3 (0.0, 23.4)0.003
 Communication8.3 (0.0, 22.9)0.0 (0.0, 16.7)0.018
 Bodily discomfort25.0 (8.3, 50.0)16.7 (0.0, 33.3)0.019

Data are presented as the median and interquartile range (IQR).

IPAQ-SF, International Physical Activity Questionnaire-Short Form; PDQ-39 SI, Parkinson’s Disease Questionnaire-39 Summary Index; ADL, activities of daily living.

A The amount of exercise is presented as the metabolic equivalent minutes per week (MET-min/week).
Fig. 2.

Diagram showing the study flow.


IB23061_F2.gif
Fig. 3.

(a) After the 2-week program, there was a significant increase in MET-min/week as measured by the IPAQ-SF, particularly in moderate-intensity exercise and walking as well as change in the PDQ-39 SI and subdomains. (b) Activities of daily living, emotional well-being, cognition and communication, and bodily discomfort after 2 weeks of study (light grey) improved compared to baseline assessments (dark grey). (c) Correlation analysis showed that the number of completed exercises exhibited positive correlation with change of moderate, walking, and total MET-min/week but not with vigorous exercise. IPAQ-SF, International Physical Activity Questionnaire-Short Form; PDQ-39 SI, Parkinson’s Disease Questionnaire-39 Summary Index; T1, baseline; T2, after 2 weeks. An asterisk (*) in the figure indicates statistical significance (P < 0.05).


IB23061_F3.gif

We compared the clinical features of the participants who completed the program and those who dropped out. There were no differences in the mean age, disease duration, UPDRS-III, or PDQ-39. MET-min/week showed no difference regardless of activity intensity (Supplementary Table S1). However, dropout participants did report lower confidence in using a smartphone, especially with questions 10 and 12 (Table 1).

Discussion

The main objective of the present pilot study was to evaluate the effectiveness of the exercise app in increasing the amount of exercise performed by individuals with PD. The findings indicated that the use of the exercise app can be a valuable tool in enhancing physical activity levels among the people with PD. The overall physical activity of the participants increased, especially for moderate-intensity and walking activities. Moreover, as the amount of exercise increased, the participants’ QoL improved.

Most participants were satisfied with the app and the included exercise videos; consequently, the app successfully helped increase the amount of exercise. As the exercise programs included in the app were of moderate intensity, it is expected than an the observed increase in moderate-intensity activity was expected. However, the results also showed an increase in walking activity, suggesting that the app can motivate general physical activity beyond the guided exercises. Additionally, our findings demonstrated a positive correlation between the number of completed exercises and an increase in MET-min/week, particularly moderate and walking activity, further indicating the app’s effectiveness in promoting physical activity. There are various motivating tools that could make can encourage people with PD to engage in exercise, including social support, feedback on performance, professional support, education about benefits of exercise, and recommendation of exercise by a neurologist (Schootemeijer et al. 2020). We tried to provide several motivators to help participants start and remain engaged in exercise, including supplying the app and the home-based exercise program, in-app alarms, providing complimentary messages, and providing a tracking system; participating in the study itself was also one of the motivating factors. Our results suggest that using the app is useful to motivate and encourage exercise. However, there is a possibility of selection bias due to the nature of using a smartphone app as the intervention. Patients who are not technologically literate or have difficulty using smartphones may have been less likely to participate in the study, resulting in a potentially more tech-savvy sample than the general PD population. Additionally, dropouts who were unsatisfied with the app or lacked confidence in using a smartphone may have also contributed to selection bias.

The QoL of the participants also improved, especially in regards to the domains of ADL, emotional well-being, cognition, communication, and bodily discomfort, but not mobility. This suggests that exercise interventions are effective at improving the overall QoL of people with PD (Chen et al. 2020). A previous study by Goodwin et al. (2008) showed that physical activities and exercises correlate with improved QoL in people with PD. Given the complexity and multifactorial nature of QoL, other factors, such as depression and anxiety, could significantly influence the observed QoL enhancements (Soh et al. 2011). Hence, long-term exercise programs and investigations of other factors, such as depression and anxiety, are necessary to determine their effect on QoL of PD patients.

The study has several limitations that should be considered when interpreting its findings. First, the study only included patients with a H&Y stage 3 or less to minimise the risk of falls or trauma, which may limit the generalisability of the results to the entire PD population, particularly those with advanced PD. Moreover, the small number of participants warrants caution in interpreting the results. Further research is needed to investigate the effectiveness and safety of the exercise program in a broader population of people with PD. Second, the study did not investigate mood symptoms, such as depression or anxiety, which could affect physical activity and potentially impact the dropout rate of the study. These factors may have important roles in the success of exercise interventions and should be explored in future research to determine their impact on outcomes. Third, this study experienced a substantial dropout rate of 39.0%, suggesting that our findings might not be universally applicable to all individuals with PD, especially those unfamiliar with smartphone use. Lastly, the 2-week study duration was too short to accurately reflect the actual effects on motor symptoms, QoL, and the long-term benefits of using the app.

This study exhibited a higher rate of dropouts than expected (39.0%), which is similar to that of the previous study using a paid exercise app (Landers and Ellis 2020). In our study, the reason the dropouts did not use the app is unclear, as they did not answer the user satisfaction survey. There were no differences in the baseline amount of exercise, demographic characteristics, or disease-related factors between the participants who completed the program and those who dropped out. Considering that the median number of completed exercises in the dropouts was two, there may have been dissatisfaction with the app or the exercise program, or there may have been difficulties in using it. The lower confidence in using smartphones reported by dropouts provides support for the latter explanation.

Several recommendations can be made from the findings and limitations of the present study. First, a user-friendly and tailored interface for the target patients is required. Considering that most people with PD are elderly and unfamiliar with a mobile interface, a more intuitive interface is needed. Second, it is necessary to educate participants regarding the use of an app and e-health literacy. Despite the growing importance of e-health literacy (van Olmen 2022), the e-health literacy of people with PD has not been accurately studied. Further research on the status of e-health literacy and education in insufficient areas is required. Finally, providing a real-time exercise program and various levels of exercise programs would be helpful for the remaining participants, ensuring the accuracy of their exercises and monitoring the risk of injury.

In conclusion, the present study showed that an app providing a home-based exercise program was a useful tool for improving the amount of exercise and QoL of people with PD. To maximise the effect of the app, education regarding e-health literacy, improvement in the quality of the app, and diversification of the exercise program should be considered in future studies.

Supplementary material

Supplementary material is available online.

Data availability

The data that support the findings of this study are available on request from the corresponding author (J. W. Cho).

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of funding

This research was supported by a fund (2022-ER100500) by Research of Korea Centers for Disease Control and Prevention.

Ethics standard

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Author contributions

Jong Hyeon Ahn and Jinwhan Cho: conceptualisation. Dongrul Shin, Hye Young Kim, Dongyeong Lee, and Jong Hyeon Ahn: data curation. Jong Hyeon Ahn and Dongyeong Lee: formal analysis. Jong Hyeon Ahn, Jinyoung Youn, and Jin Whan Cho: investigation. Jong Hyeon Ahn, Jinyoung Youn, and Jinwhan Cho: methodology. Jin Whan Cho: project administration. Jong Hyeon Ahn, Hye Young Kim, Jinyoung Youn, and Jin Whan Cho: resources. Jin Whan Cho: supervision. Dongrul Shin: writing – original draft. Jong Hyeon Ahn and Jin Whan Cho: writing – review and editing.

References

Chen K, Tan Y, Lu Y, Wu J, Liu X, Zhao Y (2020) Effect of Exercise on Quality of Life in Parkinson’s Disease: A Systematic Review and Meta-Analysis. Parkinson’s Disease 2020, 20203257623.
| Crossref | Google Scholar | PubMed |

Chun MY (2012) Validity and reliability of Korean version of international physical activity questionnaire short form in the elderly. Korean Journal of Family Medicine 33(3), 144-151.
| Crossref | Google Scholar | PubMed |

Danbjørg DB, Villadsen A, Gill E, Rothmann MJ, Clemensen J (2018) Usage of an exercise app in the care for people with osteoarthritis: user-driven exploratory study. JMIR mHealth and uHealth 6(1), e11.
| Crossref | Google Scholar | PubMed |

Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 12(3), 189-198.
| Crossref | Google Scholar | PubMed |

Goodwin VA, Richards SH, Taylor RS, Taylor AH, Campbell JL (2008) The effectiveness of exercise interventions for people with Parkinson’s disease: a systematic review and meta‐analysis. Movement Disorders 23(5), 631-640.
| Crossref | Google Scholar | PubMed |

Hoehn MM, Yahr MD (1967) Parkinsonism: onset, progression and mortality. Neurology 17(5), 427-442.
| Crossref | Google Scholar | PubMed |

Hughes AJ, Daniel SE, Kilford L, Lees AJ (1992) Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases. Journal of Neurology, Neurosurgery, and Psychiatry 55(3), 181-184.
| Crossref | Google Scholar | PubMed |

Kim Y (2016) A Study on the Senior’s Smartphone Usage patterns based on their Digital Literacy Levels – A Smartphone Log Data Analysis. Master’s dissertation, Seoul National University, Seoul, Korea.

Landers MR, Ellis TD (2020) A Mobile App Specifically Designed to Facilitate Exercise in Parkinson Disease: Single-Cohort Pilot Study on Feasibility, Safety, and Signal of Efficacy. JMIR Mhealth Uhealth 8(10), e18985.
| Crossref | Google Scholar | PubMed |

Langer A, Gassner L, Flotz A, Hasenauer S, Gruber J, Wizany L, Pokan R, Maetzler W, Zach H (2021) How COVID-19 will boost remote exercise-based treatment in Parkinson’s disease: a narrative review. NPJ Parkinsons Disease 7(1), 25.
| Crossref | Google Scholar | PubMed |

Lau YH, Lau KM, Ibrahim NM (2021) Management of Parkinson’s Disease in the COVID-19 Pandemic and Future Perspectives in the Era of Vaccination. Journal of Movement Disorders 14(3), 177-183.
| Crossref | Google Scholar | PubMed |

Lee J, Choi M, Yoo Y, Ahn S, Jeon JY, Kim JY, Byun JY (2019) Impacts of an Exercise Program and Motivational Telephone Counseling on Health-Related Quality of Life in People With Parkinson’s Disease. Rehabilitation Nursing 44(3), 161-170.
| Crossref | Google Scholar | PubMed |

Linares-Del Rey M, Vela-Desojo L, Cano-de la Cuerda R (2019) Mobile phone applications in Parkinson’s disease: a systematic review. Neurologia 34(1), 38-54.
| Crossref | Google Scholar | PubMed |

Mak MK, Wong-Yu IS, Shen X, Chung CL (2017) Long-term effects of exercise and physical therapy in people with Parkinson disease. Nature Reviews: Neurology 13(11), 689-703.
| Crossref | Google Scholar | PubMed |

Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease (2003) The Unified Parkinson’s Disease Rating Scale (UPDRS): status and recommendations. Movement Disorders 18(7), 738-750.
| Crossref | Google Scholar | PubMed |

Schootemeijer S, van der Kolk NM, Ellis T, Mirelman A, Nieuwboer A, Nieuwhof F, Schwarzschild MA, de Vries NM, Bloem BR (2020) Barriers and Motivators to Engage in Exercise for Persons with Parkinson’s Disease. Journal of Parkinson’s Disease 10(4), 1293-1299.
| Crossref | Google Scholar | PubMed |

Shah N, Borrelli B, Kumar D (2023) Perceptions about smartphone-based interventions to promote physical activity in inactive adults with knee pain – a qualitative study. Disability and Rehabilitation: Assistive Technology 24, 1-8.
| Crossref | Google Scholar | PubMed |

Soh SE, Morris ME, McGinley JL (2011) Determinants of health-related quality of life in Parkinson’s disease: a systematic review. Parkinsonism & Related Disorders 17(1), 1-9.
| Crossref | Google Scholar | PubMed |

Song J, Ahn JH, Choi I, Mun JK, Cho JW, Youn J (2020) The changes of exercise pattern and clinical symptoms in patients with Parkinson’s disease in the era of COVID-19 pandemic. Parkinsonism & Related Disorders 80, 148-151.
| Crossref | Google Scholar | PubMed |

van Olmen J (2022) The Promise of Digital Self-Management: A Reflection about the Effects of Patient-Targeted e-Health Tools on Self-Management and Wellbeing. International Journal of Environmental Research and Public Health 19(3), 1360.
| Crossref | Google Scholar | PubMed |