Validity of mHealth devices for counting steps in individuals with Parkinson's disease

Relationships between physical activities performed under free-living conditions and non-motor symptoms in people with Parkinson's: A systematic review and meta-analysis

BACKGROUND

Physical activities performed under free-living conditions that are unsupervised in the home or community have the potential to modulate non-motor symptoms in people with Parkinson's disease.

OBJECTIVE

This systematic review investigates the relationships between physical activities performed in free-living conditions and non-motor symptoms in people with Parkinson's disease: cognition, anxiety, apathy, depression, sleep disturbances, fatigue, and pain.

DATA SOURCES

A database search was performed on Scopus, Web of Science, Ovid (PsycINFO), CINAHL, PubMed, and ProQuest (Health and Medicine).

REVIEW METHODS

Observational studies published from 2000 to 2024 that examined the relationships between physical activity and non-motor symptoms were included. The methodological quality of reports was evaluated using critical appraisal checklists appropriate to the study design. Where appropriate, a meta-analysis was conducted to combine data from the included articles.

RESULTS

A total of 14 articles met the criteria and used various tools to evaluate non-motor symptoms and physical activity. Meta-analyses showed that people with Parkinson's who are more physically active have better global cognition [β ranged from 0.12 to 0.28; p = 0.00-0.02] and less affective disorders [β -0.20, p = 0.00]. Increased physical activity levels were also associated with better sleep quality (n = 1) and less chronic pain (n = 1). The overall methodological quality of the included articles was considered high.

CONCLUSION

Engagement in increased levels of physical activities performed under free-living conditions is associated with better cognition and less anxiety, apathy, and depression in people with Parkinson's disease.

mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial

BACKGROUND

Physical activity effectively prevents depression and anxiety. Although mobile health (mHealth) technologies offer promising results in promoting physical activity and improving mental health, conflicting evidence exists on their effectiveness, and employees face barriers to using mHealth services. To address these problems, we recently developed a smartphone app named ASHARE to prevent depression and anxiety in the working population; it uses a deep learning model for passive monitoring of depression and anxiety from information about physical activity.

OBJECTIVE

This study aimed to preliminarily investigate (1) the effectiveness of the developed app in improving physical activity and reducing depression and anxiety and (2) the app's implementation outcomes (ie, its acceptability, appropriateness, feasibility, satisfaction, and potential harm).

METHODS

We conducted a single-arm interventional study. From March to April 2023, employees aged ≥18 years who were not absent were recruited. The participants were asked to install and use the app for 1 month. The ideal usage of the app was for the participants to take about 5 minutes every day to open the app, check the physical activity patterns and results of an estimated score of psychological distress, and increase their physical activity. Self-reported physical activity (using the Global Physical Activity Questionnaire, version 2) and psychological distress (using the 6-item Kessler Psychological Distress Scale) were measured at baseline and after 1 month. The duration of physical activity was also recorded digitally. Paired t tests (two-tailed) and chi-square tests were performed to evaluate changes in these variables. Implementation Outcome Scales for Digital Mental Health were also measured for acceptability, appropriateness, feasibility, satisfaction, and harm. These average scores were assessed by comparing them with those reported in previous studies.

RESULTS

This study included 24 employees. On average, the app was used for 12.54 days (44.8% of this study's period). After using the app, no significant change was observed in physical activity (-12.59 metabolic equivalent hours per week, P=.31) or psychological distress (-0.43 metabolic equivalent hours per week, P=.93). However, the number of participants with severe psychological distress decreased significantly (P=.01). The digitally recorded duration of physical activity increased during the intervention period (+0.60 minutes per day, P=.08). The scores for acceptability, appropriateness, and satisfaction were lower than those in previous mHealth studies, whereas those for feasibility and harm were better.

CONCLUSIONS

The ASHARE app was insufficient in promoting physical activity or improving psychological distress. At this stage, the app has many issues that are to be addressed in terms of both implementation and effectiveness. The main reason for this low effectiveness might be the poor evaluation of the implementation outcomes by app users. Improving acceptability, appropriateness, and satisfaction are identified as key issues to be addressed in future implementation.

TRIAL REGISTRATION

University Hospital Medical Information Network Clinical Trials Registry UMIN000050430; https://tinyurl.com/mrx5ntcmrecptno=R000057438.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review

BACKGROUND

People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases.

METHODS

Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device.

RESULTS

One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness.

CONCLUSION

This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.

Identification and description of telerehabilitation assessments for individuals with neurological conditions: A scoping review

Background

The clinical adoption of telerehabilitation accelerated rapidly over the last few years, creating opportunities for clinicians and researchers to explore the use of digital technologies and telerehabilitation in the assessment of deficits related to neurological conditions. The objectives of this scoping review were to identify outcome measures used to remotely assess the motor function and participation in people with neurological conditions and report, when available, the psychometric data of these remote outcome measures.

Methods

MEDLINE (Ovid), CINAHL, PubMed, PsychINFO, EMBASE, and Cochrane databases were searched between December 13, 2020, and January 4, 2021, for studies investigating the use of remote assessments to evaluate motor function and participation in people with neurological conditions. An updated search was completed on May 9, 2022, using the same databases and search terms. Two reviewers independently screened each title and abstract, followed by full-text screening. Data extraction was completed using a pre-piloted data extraction sheet where outcome measures were reported as per the International Classification of Functioning, Disability and Health.

Results

Fifty studies were included in this review. Eighteen studies targeted outcomes related to body structures and 32 targeted those related to activity limitation and participation restriction. Seventeen studies reported psychometric data; of these, most included reliability and validity data.

Conclusion

Clinical assessments of motor function of people living with neurological conditions can be completed in a telerehabilitation or remote context using validated and reliable remote assessment measures.