Wearable sensors and Mobile Health (mHealth) technologies to assess and promote physical activity in stroke: a narrative review

2016 ◽  
Vol 17 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Shamala Thilarajah ◽  
Ross A Clark ◽  
Gavin Williams
Keyword(s):  
Physical Activity ◽  
Behaviour Change ◽  
Mobile Health ◽  
Wearable Sensors ◽  
Chronic Illnesses ◽  
Behaviour Change Techniques ◽  
Health Issues ◽  
Activity Trackers ◽  
Wearable Activity Trackers ◽  
Smartphone Technology

Stroke is a leading cause of disability worldwide, with approximately one third of people left with permanent deficits impacting on their function. This may contribute to a physically inactive lifestyle and further associated health issues. Current research suggests that people after stroke are not meeting the recommended levels of physical activity, and are less active than people with other chronic illnesses. Thus, it is important to understand how to support people after stroke to uptake and maintain physical activity. Wearable sensors and mobile health (mHealth) technologies are a potential platform to measure and promote physical activity. Some of these technologies may incorporate behaviour change techniques such as real-time feedback. Although wearable activity trackers and smartphone technology are widely available, the feasibility and applicability of these technologies for people after stroke is unclear. This article reviews the devices available for assessment of physical activity in stroke and discusses the potential for advances in technology to promote physical activity in this population.

scholarly journals The Acceptability, Feasibility and Effectiveness of Wearable Activity Trackers for Increasing Physical Activity in Children and Adolescents: A Systematic Review

2021 ◽  
Vol 18 (12) ◽  
pp. 6211
Author(s):  
Amy V. Creaser ◽  
Stacy A. Clemes ◽  
Silvia Costa ◽  
Jennifer Hall ◽  
Nicola D. Ridgers ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Children And Adolescents ◽  
Behaviour Change Techniques ◽  
Physically Active ◽  
Self Monitoring ◽  
Start Date ◽  
Activity Trackers ◽  
Wearable Activity Trackers

Wearable activity trackers (wearables) embed numerous behaviour change techniques (BCTs) that have previously been shown to increase adult physical activity (PA). With few children and adolescents achieving PA guidelines, it is crucial to explore ways to increase their PA. This systematic review examined the acceptability, feasibility, and effectiveness of wearables and their potential mechanisms of action for increasing PA in 5 to 19-year-olds. A systematic search of six databases was conducted, including data from the start date of each database to December 2019 (PROSPERO registration: CRD42020164506). Thirty-three studies were included. Most studies (70%) included only adolescents (10 to 19 years). There was some—but largely mixed—evidence that wearables increase steps and moderate-to-vigorous-intensity PA and reduce sedentary behaviour. There were no apparent differences in effectiveness based on the number of BCTs used and between studies using a wearable alone or as part of a multi-component intervention. Qualitative findings suggested wearables increased motivation to be physically active via self-monitoring, goal setting, feedback, and competition. However, children and adolescents reported technical difficulties and a novelty effect when using wearables, which may impact wearables’ long-term use. More rigorous and long-term studies investigating the acceptability, feasibility, and effectiveness of wearables in 5 to 19-year-olds are warranted.

scholarly journals Effects of Mobile Health Including Wearable Activity Trackers to Increase Physical Activity Outcomes Among Healthy Children and Adolescents: Systematic Review (Preprint)

2017 ◽  
Author(s):  
Birgit Böhm ◽  
Svenja D Karwiese ◽  
Harald Böhm ◽  
Renate Oberhoffer
Keyword(s):  
Physical Activity ◽  
Children And Adolescents ◽  
Mobile Health ◽  
Methodological Quality ◽  
Controlled Trials ◽  
Cochrane Central Register ◽  
Healthy Children ◽  
Intervention Delivery ◽  
Activity Trackers ◽  
Wearable Activity Trackers

BACKGROUND Children and adolescents do not meet the current recommendations on physical activity (PA), and as such, the health-related benefits of regular PA are not achieved. Nowadays, technology-based programs represent an appealing and promising option for children and adolescents to promote PA. OBJECTIVE The aim of this review was to systematically evaluate the effects of mobile health (mHealth) and wearable activity trackers on PA-related outcomes in this target group. METHODS Electronic databases such as the Cochrane Central Register of Controlled Trials, PubMed, Scopus, SPORTDiscus, and Web of Science were searched to retrieve English language articles published in peer-reviewed journals from January 2012 to June 2018. Those included were articles that contained descriptions of interventions designed to increase PA among children (aged 6 to 12 years) only, or adolescents (aged 13 to 18 years) only, or articles that include both populations, and also, articles that measured at least 1 PA-related cognitive, psychosocial, or behavioral outcome. The interventions had to be based on mHealth tools (mobile phones, smartphones, tablets, or mobile apps) or wearable activity trackers. Randomized controlled trials (RCTs) and non-RCTs, cohort studies, before-and-after studies, and cross-sectional studies were considered, but only controlled studies with a PA comparison between groups were assessed for methodological quality. RESULTS In total, 857 articles were identified. Finally, 7 studies (5 with tools of mHealth and 2 with wearable activity trackers) met the inclusion criteria. All studies with tools of mHealth used an RCT design, and 3 were of high methodological quality. Intervention delivery ranged from 4 weeks to 12 months, whereby mainly smartphone apps were used as a tool. Intervention delivery in studies with wearable activity trackers covered a period from 22 sessions during school recess and 8 weeks. Trackers were used as an intervention and evaluation tool. No evidence was found for the effect of mHealth tools, respectively wearable activity trackers, on PA-related outcomes. CONCLUSIONS Given the small number of studies, poor compliance with accelerometers as a measuring instrument for PA, risk of bias, missing RCTs in relation to wearable activity trackers, and the heterogeneity of intervention programs, caution is warranted regarding the comparability of the studies and their effects. There is a clear need for future studies to develop PA interventions grounded on intervention mapping with a high methodological study design for specific target groups to achieve meaningful evidence.

scholarly journals Mobile health apps: An exploration of user-generated reviews in Google Play Store on a physical activity application

2021 ◽  
Vol 7 ◽  
pp. 205520762110149
Author(s):  
Miznah Al-Abbadey ◽  
Megan M-W Fong ◽  
Laura J Wilde ◽  
Roger Ingham ◽  
Daniela Ghio
Keyword(s):  
Physical Activity ◽  
Behaviour Change ◽  
Mobile Health ◽  
Behaviour Change Techniques ◽  
User Friendliness ◽  
Self Monitoring ◽  
Health Apps ◽  
Specific Behaviour ◽  
Social Features ◽  
Mobile Health Apps

Objective This study aimed to evaluate reviews that have been posted publicly on the app ‘MapMyRun’ to investigate which features were associated with usage of the app. A secondary aim was to determine whether MapMyRun consisted of specific behaviour change techniques that would have increased the likelihood of users being engaged with the app. Methods Reviews posted on MapMyRun by users between 1st May 2017- 30th April 2018 were extracted, coded and analysed using content analysis. Results Eleven behaviour change techniques were identified among the features of MapMyRun. A total of 3,253 reviews met the inclusion/exclusion criteria, and 12 codes were developed. The codes were grouped into 8 subthemes within 2 main themes: ‘Effort’ and ‘Self-monitoring’. Consistent with previous literature, ‘Goal-Setting’ and ‘Self-Monitoring of Behaviour’ were two techniques included in MapMyRun. Social features of MapMyRun facilitated competition among users, their family, and friends. Conclusions This was the first qualitative review to assess a single mobile health physical activity app and analyse it from the perspectives of the users. Creators of future mobile health apps should focus on user friendliness and the use of social features, as both may increase the chances of users’ continued use with the app.

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