mHealth Acceptance and Usage among South Asian Adults in the U.S.

Background: Modifiable lifestyle factors such as physical inactivity and unhealthy diet contribute to the increased risk of cardiovascular diseases (CVD) and diabetes (DM) in South Asians (SAs) (Volgman et al., 2018). Interventions using mobile health (mHealth) have demonstrated feasibility and potential efficacy for ethnic minorities (Bender et al., 2018), and have the potential to be of preventive and therapeutic value in reducing the burden of CVD and DM in SAs living in the US. However, there is a gap in knowledge regarding the usage and acceptance of mHealth among SAs. Purpose: The objectives were to examine the overall usage of mHealth and examine factors associated with the acceptance, usage, non-usage, and discontinuation of mHealth technology among SA adults living in the US. Methods: The study utilized a cross-sectional research design. A total of 134 South Asian adults were recruited to the study. Self-reported measures included demographics, health status, motivations for using mHealth, factors associated with technology acceptance and usage, reasons for non-usage and discontinuation of mHealth applications (apps) and smart and connected devices using the survey developed by Paré, Leaver, & Bourget (2018). Correlation analyses were conducted using Pearson’s and Spearman’s correlation tests. Chi-square and Kruskal-Wallis analyses were conducted to compare group differences among current users, past users, and non-users of mHealth technology. Results: About 62.4% of the participants were current users of mobile health apps, and 43.1% were current users of smart and connected devices. Users were on an average between the ages 35-54 years, female, healthy, employed, university educated, with an annual family income of over $80,000. There was a statistically significant difference in age (χ2 (2) = 9.638, p = .007) and employment (χ2 (4, N = 105) = 12.262, p = 0.019) between the current users, past users, and non-users of smart devices. Non-users of smart devices were more likely to be students, and between 18-34 years of age. The mean scores for the scales of perceived ease of use, perceived usefulness, confirmation of expectations, user satisfaction, and intent to continue using mHealth technology ranged from 3.5 – 4.2 (somewhat agree to strongly agree) for mobile health apps and from 4.1 to 4.4 (somewhat agree to strongly agree) for smart and connected devices. Conclusions: mHealth technology was used, accepted, and appreciated by more than half of the South Asian adults that we surveyed. The results from this study may help in selecting and utilizing the most accepted mHealth technology for designing interventions for South Asian adults living in the US to lower the risk of CVD and DM

Evaluating the impact of physical activity apps and wearables: interdisciplinary review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

Using mHealth applications for self-care – An integrative review on perceptions among adults with type 1 diabetes

Background Individually designed interventions delivered through mobile health applications (mHealth apps) may be able to effectively support diabetes self-care. Our aim was to review and synthesize available evidence in the literature regarding perception of adults with type 1 diabetes on the features of mHealth apps that help promote diabetes self-care, as well as facilitators and barriers to their use. An additional aim was to review literature on changes in patient reported outcome measures (PROMs) in the same population while using mHealth apps for diabetes self-care. Methods Quantitative and qualitative studies focusing on adults aged 18 years and over with type 1 diabetes in any context were included. A systematic literature search using selected databases was conducted. Data was synthesised using narrative synthesis. Results We found that features of mHealth apps designed to help promote and maintain diabetes self-care could be categorized into self-care data monitoring, app display, feedback & reminders, data entry, data sharing, and additional features. Factors affecting the use of mHealth apps reported in the literature were personal factors, app design or usability factors, privacy and safety factors, or socioeconomic factors. Quality of life and diabetes distress were the most commonly reported PROMs in the included studies. Conclusion We are unable to reach a conclusive result due to the heterogeneity of the included studies as well as the limited number of studies reporting on these areas among adults with type 1 diabetes. We therefore recommend further large-scale studies looking into these areas that can ultimately improve mHealth app use in type 1 diabetes self-care.publishedVersio