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1.
Patient Use of Cardiovascular Devices and Apps: Are We Getting Our Money's Worth?
Aguillard, K, Garson, A
Methodist DeBakey cardiovascular journal. 2020;(4):291-295
Abstract
The evolution of technology makes it likely that a large number of people will invest in and use health-related mobile applications and wearable devices. Yet the question remains: Do these technology-based interventions modify health behavior and improve health…and are we getting our money's worth? The vast majority of studies concerning health-related apps and wearable devices have small sample sizes and short time spans of 6 months or less, so it is not clear if these durations were determined by lack of consistent use over time. Furthermore, many of the most popular applications have not been subjected to randomized trials. Overall, the small demonstrated improvements in outcomes are often associated with professional involvement from clinicians, coaches, or diabetes educators provided in conjunction with use of mobile health (mHealth) platforms. This paper explores the use of mHealth technologies that address cardiovascular disease/prevention (eg, diabetes, diet, physical activity, and associated weight loss) and discusses the lack of adequate evidence to support even minimal patient investment in mobile applications or wearable devices at this time.
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2.
Methods of usability testing in the development of eHealth applications: A scoping review.
Maramba, I, Chatterjee, A, Newman, C
International journal of medical informatics. 2019;:95-104
Abstract
BACKGROUND The number of eHealth applications has exponentially increased in recent years, with over 325,000 health apps now available on all major app stores. This is in addition to other eHealth applications available on other platforms such as PC software, web sites and even gaming consoles. As with other digital applications, usability is one of the key factors in the successful implementation of eHealth apps. Reviews of the literature on empirical methods of usability testing in eHealth were last published in 2015. In the context of an exponentially increasing rate of App development year on year, an updated review is warranted. OBJECTIVE To identify, explore, and summarize the current methods used in the usability testing of eHealth applications. METHODS A scoping review was conducted on literature available from April 2014 up to October 2017. Four databases were searched. Literature was considered for inclusion if it was (1) focused on an eHealth application (which includes websites, PC software, smartphone and tablet applications), (2) provided information about usability of the application, (3) provided empirical results of the usability testing, (4) a full or short paper (not an abstract) published in English after March 2014. We then extracted data pertaining to the usability evaluation processes described in the selected studies. RESULTS 133 articles met the inclusion criteria. The methods used for usability testing, in decreasing order of frequency were: questionnaires (n = 105), task completion (n = 57), 'Think-Aloud' (n = 45), interviews (n = 37), heuristic testing (n = 18) and focus groups (n = 13). Majority of the studies used one (n = 45) or two (n = 46) methods of testing. The rest used a combination of three (n = 30) or four (n = 12) methods of testing usability. None of the studies used automated mechanisms to test usability. The System Usability Scale (SUS) was the most frequently used questionnaire (n = 44). The ten most frequent health conditions or diseases where eHealth apps were being evaluated for usability were the following: mental health (n = 12), cancer (n = 10), nutrition (n = 10), child health (n = 9), diabetes (n = 9), telemedicine (n = 8), cardiovascular disease (n = 6), HIV (n = 4), health information systems (n = 4) and smoking (n = 4). Further iterations of the app were reported in a minority of the studies (n = 41). The use of the 'Think-Aloud' (Pearson Chi-squared test: χ2 = 11.15, p < 0.05) and heuristic walkthrough (Pearson Chi-squared test: χ2 = 4.48, p < 0.05) were significantly associated with at least one further iteration of the app being developed. CONCLUSION Although there has been an exponential increase in the number of eHealth apps, the number of studies that have been published that report the results of usability testing on these apps has not increased at an equivalent rate. The number of digital health applications that publish their usability evaluation results remains only a small fraction. Questionnaires are the most prevalent method of evaluating usability in eHealth applications, which provide an overall measure of usability but do not pinpoint the problems that need to be addressed. Qualitative methods may be more useful in this regard. The use of multiple evaluation methods has increased. Automated methods such as eye tracking have not gained traction in evaluating health apps. Further research is needed into which methods are best suited for the different types of eHealth applications, according to their target users and the health conditions being addressed.
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3.
Evaluating mobile phone applications for health behaviour change: A systematic review.
McKay, FH, Cheng, C, Wright, A, Shill, J, Stephens, H, Uccellini, M
Journal of telemedicine and telecare. 2018;(1):22-30
Abstract
Introduction Increasing smartphones access has allowed for increasing development and use of smart phone applications (apps). Mobile health interventions have previously relied on voice or text-based short message services (SMS), however, the increasing availability and ease of use of apps has allowed for significant growth of smartphone apps that can be used for health behaviour change. This review considers the current body of knowledge relating to the evaluation of apps for health behaviour change. The aim of this review is to investigate approaches to the evaluation of health apps to identify any current best practice approaches. Method A systematic review was conducted. Data were collected and analysed in September 2016. Thirty-eight articles were identified and have been included in this review. Results Articles were published between 2011- 2016, and 36 were reviews or evaluations of apps related to one or more health conditions, the remaining two reported on an investigation of the usability of health apps. Studies investigated apps relating to the following areas: alcohol, asthma, breastfeeding, cancer, depression, diabetes, general health and fitness, headaches, heart disease, HIV, hypertension, iron deficiency/anaemia, low vision, mindfulness, obesity, pain, physical activity, smoking, weight management and women's health. Conclusion In order to harness the potential of mobile health apps for behaviour change and health, we need better ways to assess the quality and effectiveness of apps. This review is unable to suggest a single best practice approach to evaluate mobile health apps. Few measures identified in this review included sufficient information or evaluation, leading to potentially incomplete and inaccurate information for consumers seeking the best app for their situation. This is further complicated by a lack of regulation in health promotion generally.
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4.
Effectiveness of mobile health (mHealth) interventions for promoting healthy eating in adults: A systematic review.
McCarroll, R, Eyles, H, Ni Mhurchu, C
Preventive medicine. 2017;:156-168
Abstract
Unhealthy eating is a major risk factor for chronic disease. However, many current strategies to promote healthy eating are not sustainable over the longer-term. More cost-effective wide-reaching initiatives are urgently needed. Mobile health (mHealth) interventions, delivered via mobile devices, could provide a solution. This systematic review summarized the evidence on the effect of mHealth interventions for promoting healthy eating in adults. A comprehensive systematic search of five scientific databases was conducted using methods adapted from the Cochrane Handbook. Eligible studies were randomized controlled trials (RCTs), published up to 1 July 2016, which examined healthy eating interventions delivered via mobile device. Of 879 articles identified, 84 full text articles were potentially eligible and further assessed, and 23 included. Narrative review results indicated small positive effects of mHealth interventions on healthy eating (5/8 trials) and weight loss (5/13 trials). However, the current evidence base is insufficient (studies are of poor quality) to determine conclusive positive effects. More rigorous RCTs with longer-term (>6months) follow-up are warranted to determine if effects are maintained.
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Impact of mobile apps to combat obesity in children and adolescents: A systematic literature review.
Quelly, SB, Norris, AE, DiPietro, JL
Journal for specialists in pediatric nursing : JSPN. 2016;(1):5-17
Abstract
PURPOSE This review examines the impact of mobile app technology on obesity-related anthropometric, psychosocial, and behavioral outcomes in children and adolescents. CONCLUSIONS Nine research articles retrieved from a systematic review of the literature met criteria. Evidence is limited and mixed, but argues for an impact of mobile app use on motivation and goal-setting behavior, and supports further study of the impact on childhood obesity-related outcomes such as attitudes, perceptions, physical activity, and dietary habits. PRACTICE IMPLICATIONS Nurses can use this evidence to discuss potential benefits of health promotion mobile apps with parents, children, and adolescents to combat childhood obesity.
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The Wild Wild West: A Framework to Integrate mHealth Software Applications and Wearables to Support Physical Activity Assessment, Counseling and Interventions for Cardiovascular Disease Risk Reduction.
Lobelo, F, Kelli, HM, Tejedor, SC, Pratt, M, McConnell, MV, Martin, SS, Welk, GJ
Progress in cardiovascular diseases. 2016;(6):584-94
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Abstract
Physical activity (PA) interventions constitute a critical component of cardiovascular disease (CVD) risk reduction programs. Objective mobile health (mHealth) software applications (apps) and wearable activity monitors (WAMs) can advance both assessment and integration of PA counseling in clinical settings and support community-based PA interventions. The use of mHealth technology for CVD risk reduction is promising, but integration into routine clinical care and population health management has proven challenging. The increasing diversity of available technologies and the lack of a comprehensive guiding framework are key barriers for standardizing data collection and integration. This paper reviews the validity, utility and feasibility of implementing mHealth technology in clinical settings and proposes an organizational framework to support PA assessment, counseling and referrals to community resources for CVD risk reduction interventions. This integration framework can be adapted to different clinical population needs. It should also be refined as technologies and regulations advance under an evolving health care system landscape in the United States and globally.
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A review and content analysis of engagement, functionality, aesthetics, information quality, and change techniques in the most popular commercial apps for weight management.
Bardus, M, van Beurden, SB, Smith, JR, Abraham, C
The international journal of behavioral nutrition and physical activity. 2016;:35
Abstract
BACKGROUND There are thousands of apps promoting dietary improvement, increased physical activity (PA) and weight management. Despite a growing number of reviews in this area, popular apps have not been comprehensively analysed in terms of features related to engagement, functionality, aesthetics, information quality, and content, including the types of change techniques employed. METHODS The databases containing information about all Health and Fitness apps on GP and iTunes (7,954 and 25,491 apps) were downloaded in April 2015. Database filters were applied to select the most popular apps available in both stores. Two researchers screened the descriptions selecting only weight management apps. Features, app quality and content were independently assessed using the Mobile App Rating Scale (MARS) and previously-defined categories of techniques relevant to behaviour change. Inter-coder reliabilities were calculated, and correlations between features explored. RESULTS Of the 23 popular apps included in the review 16 were free (70%), 15 (65%) addressed weight control, diet and PA combined; 19 (83%) allowed behavioural tracking. On 5-point MARS scales, apps were of average quality (Md = 3.2, IQR = 1.4); "functionality" (Md = 4.0, IQR = 1.1) was the highest and "information quality" (Md = 2.0, IQR = 1.1) was the lowest domain. On average, 10 techniques were identified per app (range: 1-17) and of the 34 categories applied, goal setting and self-monitoring techniques were most frequently identified. App quality was positively correlated with number of techniques included (rho = .58, p < .01) and number of "technical" features (rho = .48, p < .05), which was also associated with the number of techniques included (rho = .61, p < .01). Apps that provided tracking used significantly more techniques than those that did not. Apps with automated tracking scored significantly higher in engagement, aesthetics, and overall MARS scores. Those that used change techniques previously associated with effectiveness (i.e., goal setting, self-monitoring and feedback) also had better "information quality". CONCLUSIONS Popular apps assessed have overall moderate quality and include behavioural tracking features and a range of change techniques associated with behaviour change. These apps may influence behaviour, although more attention to information quality and evidence-based content are warranted to improve their quality.
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Mobile Phone and Web 2.0 Technologies for Weight Management: A Systematic Scoping Review.
Bardus, M, Smith, JR, Samaha, L, Abraham, C
Journal of medical Internet research. 2015;(11):e259
Abstract
BACKGROUND Widespread diffusion of mobile phone and Web 2.0 technologies make them potentially useful tools for promoting health and tackling public health issues, such as the increasing prevalence of overweight and obesity. Research in this domain is growing rapidly but, to date, no review has comprehensively and systematically documented how mobile and Web 2.0 technologies are being deployed and evaluated in relation to weight management. OBJECTIVE To provide an up-to-date, comprehensive map of the literature discussing the use of mobile phone and Web 2.0 apps for influencing behaviors related to weight management (ie, diet, physical activity [PA], weight control, etc). METHODS A systematic scoping review of the literature was conducted based on a published protocol (registered at PROSPERO CRD42014010323). Using a comprehensive search strategy, we searched 16 multidisciplinary electronic databases for original research documents published in English between 2004 and 2014. We used duplicate study selection and data extraction. Using an inductively developed charting tool, selected articles were thematically categorized. RESULTS We identified 457 articles, mostly published between 2013 and 2014 in 157 different journals and 89 conference proceedings. Articles were categorized around two overarching themes, which described the use of technologies for either (1) promoting behavior change (309/457, 67.6%) or (2) measuring behavior (103/457, 22.5%). The remaining articles were overviews of apps and social media content (33/457, 7.2%) or covered a combination of these three themes (12/457, 2.6%). Within the two main overarching themes, we categorized articles as representing three phases of research development: (1) design and development, (2) feasibility studies, and (3) evaluations. Overall, articles mostly reported on evaluations of technologies for behavior change (211/457, 46.2%). CONCLUSIONS There is an extensive body of research on mobile phone and Web 2.0 technologies for weight management. Research has reported on (1) the development, feasibility, and efficacy of persuasive mobile technologies used in interventions for behavior change (PA and diet) and (2) the design, feasibility, and accuracy of mobile phone apps for behavioral assessment. Further research has focused exclusively on analyses of the content and quality of available apps. Limited evidence exists on the use of social media for behavior change, but a segment of studies deal with content analyses of social media. Future research should analyze mobile phone and Web 2.0 technologies together by combining the evaluation of content and design aspects with usability, feasibility, and efficacy/effectiveness for behavior change, or accuracy/validity for behavior assessment, in order to understand which technological components and features are likely to result in effective interventions.