Quality Prediction of Wearable Apps in the Google Play Store

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.

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A review of mHealth depression apps: Assessing app functions for the Self-Determination Theory (Preprint)

10.2196/preprints.22231 ◽

2020 ◽

Author(s):

Luke Brownlow

Keyword(s):

Health Behavior ◽

Behavior Change ◽

Basic Needs ◽

Health Behavior Change ◽

Self Determination Theory ◽

Healthcare Research ◽

The Self ◽

Self Determination ◽

Ideal Tool ◽

Google Play

BACKGROUND Smartphone applications (apps) are an ideal tool that is highly accessible to people who wish to begin self-treatment for depression. While many studies have performed content analyses on healthcare apps, few studies have reviewed these apps for adherence to behavior theory. Furthermore, apps for depression management are underrepresented in healthcare research. OBJECTIVE The objective of this study is to assess mHealth depression apps using SDT as a theoretical framework for meeting needs of autonomy, competence and, relatedness METHODS All depression healthcare apps available in Australia from the iTunes and Google Play app stores that met the inclusion criteria were analyzed. Each app was reviewed based on price options, store availability, download rates, and how in-app functions met the three basic needs for motivation towards health behavior change outlined in the Self-Determination Theory (SDT). RESULTS The analysis of the apps showed that most apps were free to download (69.9%) and addressed at least one of the three needs (81.4%) of SDT. However, few apps addressed all three of the basic needs through their functions (7.7%), and no apps hosted all functions expected to stimulate motivation for health behavior change. Furthermore, neither store availability, price option nor download rate were accurate predictors that apps hosted in-app functions expected to meet the basic needs. CONCLUSIONS The results suggest that some depression healthcare apps that meet the basic needs would effectively stimulate motivation (i.e., autonomy, competence, and relatedness). However, each individual app is limited in its number of functions that meet the basic needs. People who want access to more functions would need to download a suite of apps.

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Evaluation of Persian language epilepsy-related mobile apps: A systematic review and quality assessment with a focus on content (Preprint)

10.2196/preprints.26647 ◽

2020 ◽

Author(s):

Mina Zibaei ◽

Reza Khajouei

Keyword(s):

Information Quality ◽

Mobile Apps ◽

Self Care ◽

Keywords Epilepsy ◽

Limited Health Literacy ◽

Persian Language ◽

The Mean ◽

Limited Health ◽

Google Play

BACKGROUND In Iran, around 0.05 of population suffer from epilepsy. Poorer health outcomes stem from limited health literacy. The use of mHealth, especially for educating patients in terms of self-care can be very effective. But the important thing is the content that is presented by apps, especially when unreliable or biased information can negatively affect the patient-doctor relationship, causing anxiety or stress. Also, usability of mHealth apps and their impact on behavior change are the other important issues that should be considered. OBJECTIVE The purpose of this study was to assess the quality of Persian language epilepsy-related mobile applications in terms of functionality and quality with a focus on content. METHODS The Persian equivalent of the keywords 'epilepsy' and 'seizure' were searched in the Google Play, Cafe Bazaar and IranApps app stores and the Persian language applications about epilepsy were extracted. These apps were evaluated by two trained reviewers independently using the uMARS scale and DISCERN instrument. Also apps’ prices and the number of installations were assessed. RESULTS A total of 659 applications were retrieved, 78 of which were epilepsy-related. After exclusion of non-Persian language and duplicate apps, there remained 11 relevant apps. The overall mean uMARS score was 2.8 out of 5 while six out of 11 apps (54%) scored higher than 3. The mean figures for the section-specific scores were as follows: engagement 2.2, functionality 4.0, aesthetics 3.3, and information 2.3. The overall DISCERN scores ranged from 26 to 40 out of 80, while the mean score was 34.5. The mean score of reliability was 18.5. CONCLUSIONS This study showed that the overall information quality of the epilepsy apps is poor. The most important missing characteristics of these apps include lack of functionalities for self-care, missing entry date, lack of details about additional sources and inexistence of the risks/benefits of each treatment. The findings suggest that more efforts should be made to develop evidence-based epilepsy-related apps to cover broader domains of self-care and behavioral change techniques.

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App review of anxiety and depression chatbots and their self-care features (Preprint)

10.2196/preprints.26334 ◽

2020 ◽

Author(s):

Arfan Ahmed ◽

Nashva ALi ◽

Sarah Aziz ◽

Alaa A Abd-Alrazaq ◽

Asmaa Hassan ◽

...

Keyword(s):

Mental Health ◽

Meta Analysis ◽

Self Care ◽

Anxiety And Depression ◽

Conversational Agents ◽

Eligibility Criteria ◽

On Demand ◽

User Ratings ◽

Google Play

BACKGROUND Anxiety and depression rates are at an all-time high along with other mental health disorders. Smartphone-based mental health chatbots or conversational agents can aid psychiatrists and replace some of the costly human based interaction and represent a unique opportunity to expand the availability and quality of mental health services and treatment. Regular up-to-date reviews will allow medics and individuals to recommend or use anxiety and depression related smartphone based chatbots with greater confidence. OBJECTIVE Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. METHODS A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbots for anxiety and depression. Eligibility of the chatbots was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and upon installation by 2 reviewers. Finally, chatbots quality information was assessed by following the mHONcode principles. RESULTS Although around 1000 anxiety and depression related chatbots exist, only a few (n=11) contained actual chatbots that could provide the user a real substitute for a human-human based interaction, even with today's Artificial Intelligence advancements, only one of these chatbots had voice as an input/output modality. Of the selected apps that contained chatbots all were clearly built with a therapeutic human substitute goal in mind. The majority had high user ratings and downloads highlighting the popularity of such chatbots and their promising future within the realm of anxiety and depression. CONCLUSIONS Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed assistance to professionals. In the current covid-19 pandemic, chatbots can also serve as a conversational companion with the potential of combating loneliness, especially in lockdowns where there is a lack of social interaction. Due to the ubiquitous nature of chatbots users can access them on-demand at the touch of a screen on ones’ smartphone. Self-care interventions are known to be effective and exist in various forms and some can be made available as chatbot features, such as assessment, mood tracking, medicine tracking, or simply providing conversation in times of loneliness.

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