Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study

Background There has recently been exponential growth in the development and use of health apps on mobile phones. As with most mobile apps, however, the majority of users abandon them quickly and after minimal use. One of the most critical factors for the success of a health app is how to support users’ commitment to their health. Despite increased interest from researchers in mobile health, few studies have examined the measurement of user engagement with health apps. Objective User engagement is a multidimensional, complex phenomenon. The aim of this study was to understand the concept of user engagement and, in particular, to demonstrate the applicability of a user engagement scale (UES) to mobile health apps. Methods To determine the measurability of user engagement in a mobile health context, a UES was employed, which is a psychometric tool to measure user engagement with a digital system. This was adapted to Ada, developed by Ada Health, an artificial intelligence–powered personalized health guide that helps people understand their health. A principal component analysis (PCA) with varimax rotation was conducted on 30 items. In addition, sum scores as means of each subscale were calculated. Results Survey data from 73 Ada users were analyzed. PCA was determined to be suitable, as verified by the sampling adequacy of Kaiser-Meyer-Olkin=0.858, a significant Bartlett test of sphericity (χ2300=1127.1; P<.001), and communalities mostly within the 0.7 range. Although 5 items had to be removed because of low factor loadings, the results of the remaining 25 items revealed 4 attributes: perceived usability, aesthetic appeal, reward, and focused attention. Ada users showed the highest engagement level with perceived usability, with a value of 294, followed by aesthetic appeal, reward, and focused attention. Conclusions Although the UES was deployed in German and adapted to another digital domain, PCA yielded consistent subscales and a 4-factor structure. This indicates that user engagement with health apps can be assessed with the German version of the UES. These results can benefit related mobile health app engagement research and may be of importance to marketers and app developers.

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Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study (Preprint)

10.2196/preprints.13244 ◽

2018 ◽

Author(s):

Marianne Holdener ◽

Alain Gut ◽

Alfred Angerer

Keyword(s):

Mobile Health ◽

Mobile Apps ◽

Principal Component ◽

Focused Attention ◽

User Engagement ◽

Aesthetic Appeal ◽

Health Apps ◽

Perceived Usability ◽

Sum Scores ◽

Engagement Scale

BACKGROUND There has recently been exponential growth in the development and use of health apps on mobile phones. As with most mobile apps, however, the majority of users abandon them quickly and after minimal use. One of the most critical factors for the success of a health app is how to support users’ commitment to their health. Despite increased interest from researchers in mobile health, few studies have examined the measurement of user engagement with health apps. OBJECTIVE User engagement is a multidimensional, complex phenomenon. The aim of this study was to understand the concept of user engagement and, in particular, to demonstrate the applicability of a user engagement scale (UES) to mobile health apps. METHODS To determine the measurability of user engagement in a mobile health context, a UES was employed, which is a psychometric tool to measure user engagement with a digital system. This was adapted to Ada, developed by Ada Health, an artificial intelligence–powered personalized health guide that helps people understand their health. A principal component analysis (PCA) with varimax rotation was conducted on 30 items. In addition, sum scores as means of each subscale were calculated. RESULTS Survey data from 73 Ada users were analyzed. PCA was determined to be suitable, as verified by the sampling adequacy of Kaiser-Meyer-Olkin=0.858, a significant Bartlett test of sphericity (χ<sup>2</sup><sub>300</sub>=1127.1; <italic>P</italic><.001), and communalities mostly within the 0.7 range. Although 5 items had to be removed because of low factor loadings, the results of the remaining 25 items revealed 4 attributes: perceived usability, aesthetic appeal, reward, and focused attention. Ada users showed the highest engagement level with perceived usability, with a value of 294, followed by aesthetic appeal, reward, and focused attention. CONCLUSIONS Although the UES was deployed in German and adapted to another digital domain, PCA yielded consistent subscales and a 4-factor structure. This indicates that user engagement with health apps can be assessed with the German version of the UES. These results can benefit related mobile health app engagement research and may be of importance to marketers and app developers.

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Mobile Health Apps for Medical Emergencies: Systematic Review

JMIR mhealth and uhealth ◽

10.2196/18513 ◽

2020 ◽

Vol 8 (12) ◽

pp. e18513

Author(s):

Alejandro Plaza Roncero ◽

Gonçalo Marques ◽

Beatriz Sainz-De-Abajo ◽

Francisco Martín-Rodríguez ◽

Carlos del Pozo Vegas ◽

...

Keyword(s):

Health Care ◽

Mobile Health ◽

Mobile Apps ◽

Current Status ◽

Health Technologies ◽

Health Apps ◽

App Store ◽

Mobile Health Apps ◽

Medical Emergencies ◽

Google Play

Background Mobile health apps are used to improve the quality of health care. These apps are changing the current scenario in health care, and their numbers are increasing. Objective We wanted to perform an analysis of the current status of mobile health technologies and apps for medical emergencies. We aimed to synthesize the existing body of knowledge to provide relevant insights for this topic. Moreover, we wanted to identify common threads and gaps to support new challenging, interesting, and relevant research directions. Methods We reviewed the main relevant papers and apps available in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used in this review. The search criteria were adopted using systematic methods to select papers and apps. On one hand, a bibliographic review was carried out in different search databases to collect papers related to each application in the health emergency field using defined criteria. On the other hand, a review of mobile apps in two virtual storage platforms (Google Play Store and Apple App Store) was carried out. The Google Play Store and Apple App Store are related to the Android and iOS operating systems, respectively. Results In the literature review, 28 papers in the field of medical emergency were included. These studies were collected and selected according to established criteria. Moreover, we proposed a taxonomy using six groups of applications. In total, 324 mobile apps were found, with 192 identified in the Google Play Store and 132 identified in the Apple App Store. Conclusions We found that all apps in the Google Play Store were free, and 73 apps in the Apple App Store were paid, with the price ranging from US $0.89 to US $5.99. Moreover, 39% (11/28) of the included studies were related to warning systems for emergency services and 21% (6/28) were associated with disaster management apps.

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Nick Noguez and Michael Gonzalez Discuss their Research Project: Are Social Features in Mobile Health Apps Effective in Engaging Users? A Content Analysis of Smoking Cessation Mobile Apps

The Boller Review ◽

10.18776/tcu/br/4/104 ◽

2019 ◽

Vol 4 ◽

Author(s):

Nick Noguez And Michael Gonzalez

Keyword(s):

Smoking Cessation ◽

Content Analysis ◽

Mobile Health ◽

Social Engagement ◽

Rating Scale ◽

Mobile Apps ◽

Mobile App ◽

Health Apps ◽

Social Features ◽

Mobile Health Apps

Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, thesocial engagement features that exist in current smoking cessation apps and how effective these social features are in engaging users remain unclear. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps isconducted to examine a) the presence of socialengagement features(e.g., social support, social announcement, social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting), and b) their relationship with user ratingsand engagement scores (e.g., Mobile App rating scale [MARS]). The findings will not only extend the mobile health apps engagement typology,but also inform smoking cessation mobile apps design.

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Mobile Health Apps for Medical Emergencies: Systematic Review (Preprint)

10.2196/preprints.18513 ◽

2020 ◽

Author(s):

Alejandro Plaza Roncero ◽

Gonçalo Marques ◽

Beatriz Sainz-De-Abajo ◽

Francisco Martín-Rodríguez ◽

Carlos del Pozo Vegas ◽

...

Keyword(s):

Health Care ◽

Mobile Health ◽

Mobile Apps ◽

Current Status ◽

Health Technologies ◽

Health Apps ◽

App Store ◽

Mobile Health Apps ◽

Medical Emergencies ◽

Google Play

BACKGROUND Mobile health apps are used to improve the quality of health care. These apps are changing the current scenario in health care, and their numbers are increasing. OBJECTIVE We wanted to perform an analysis of the current status of mobile health technologies and apps for medical emergencies. We aimed to synthesize the existing body of knowledge to provide relevant insights for this topic. Moreover, we wanted to identify common threads and gaps to support new challenging, interesting, and relevant research directions. METHODS We reviewed the main relevant papers and apps available in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used in this review. The search criteria were adopted using systematic methods to select papers and apps. On one hand, a bibliographic review was carried out in different search databases to collect papers related to each application in the health emergency field using defined criteria. On the other hand, a review of mobile apps in two virtual storage platforms (Google Play Store and Apple App Store) was carried out. The Google Play Store and Apple App Store are related to the Android and iOS operating systems, respectively. RESULTS In the literature review, 28 papers in the field of medical emergency were included. These studies were collected and selected according to established criteria. Moreover, we proposed a taxonomy using six groups of applications. In total, 324 mobile apps were found, with 192 identified in the Google Play Store and 132 identified in the Apple App Store. CONCLUSIONS We found that all apps in the Google Play Store were free, and 73 apps in the Apple App Store were paid, with the price ranging from US $0.89 to US $5.99. Moreover, 39% (11/28) of the included studies were related to warning systems for emergency services and 21% (6/28) were associated with disaster management apps.

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Mobile Apps for Health Behavior Change: Protocol for a Systematic Review (Preprint)

10.2196/preprints.16931 ◽

2019 ◽

Author(s):

Madison Milne-Ives ◽

Ching Lam ◽

Michelle Helena Van Velthoven ◽

Edward Meinert

Keyword(s):

Systematic Review ◽

Health Behavior ◽

Behavior Change ◽

Mobile Health ◽

Mobile Apps ◽

Health Behavior Change ◽

Mobile App ◽

Risk Of Bias ◽

Health Apps ◽

Mobile Health Apps

BACKGROUND The popularity and ubiquity of mobile apps have rapidly expanded in the past decade. With a growing focus on patient interaction with health management, mobile apps are increasingly used to monitor health and deliver behavioral interventions. The considerable variation in these mobile health apps, from their target patient group to their health behavior, and their behavioral change strategy, has resulted in a large but incohesive body of literature. OBJECTIVE The purpose of this protocol is to provide an overview of the current landscape, theories behind, and effectiveness of mobile apps for health behavior change. METHODS The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols will be used to structure this protocol. The focus of the systematic review is guided by a population, intervention, comparator, and outcome framework. A systematic search of Medline, EMBASE, CINAHL, and Web of Science will be conducted. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. One reviewer will extract data into a standardized form, which will be validated by a second reviewer. Risk of bias was assessed using the Cochrane Collaboration Risk of Bias tool, and a descriptive analysis will summarize the effectiveness of all the apps. RESULTS As of November 2019, the systematic review has been completed and is in peer review for publication. CONCLUSIONS This systematic review will summarize the current mobile app technologies and their effectiveness, usability, and coherence with behavior change theory. It will identify areas of improvement (where there is no evidence of efficacy) and help inform the development of more useful and engaging mobile health apps. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/16931

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Mobile Apps for Health Behavior Change: Protocol for a Systematic Review

JMIR Research Protocols ◽

10.2196/16931 ◽

2020 ◽

Vol 9 (1) ◽

pp. e16931

Author(s):

Madison Milne-Ives ◽

Ching Lam ◽

Michelle Helena Van Velthoven ◽

Edward Meinert

Keyword(s):

Systematic Review ◽

Health Behavior ◽

Behavior Change ◽

Mobile Health ◽

Mobile Apps ◽

Health Behavior Change ◽

Mobile App ◽

Risk Of Bias ◽

Health Apps ◽

Mobile Health Apps

Background The popularity and ubiquity of mobile apps have rapidly expanded in the past decade. With a growing focus on patient interaction with health management, mobile apps are increasingly used to monitor health and deliver behavioral interventions. The considerable variation in these mobile health apps, from their target patient group to their health behavior, and their behavioral change strategy, has resulted in a large but incohesive body of literature. Objective The purpose of this protocol is to provide an overview of the current landscape, theories behind, and effectiveness of mobile apps for health behavior change. Methods The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols will be used to structure this protocol. The focus of the systematic review is guided by a population, intervention, comparator, and outcome framework. A systematic search of Medline, EMBASE, CINAHL, and Web of Science will be conducted. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. One reviewer will extract data into a standardized form, which will be validated by a second reviewer. Risk of bias was assessed using the Cochrane Collaboration Risk of Bias tool, and a descriptive analysis will summarize the effectiveness of all the apps. Results As of November 2019, the systematic review has been completed and is in peer review for publication. Conclusions This systematic review will summarize the current mobile app technologies and their effectiveness, usability, and coherence with behavior change theory. It will identify areas of improvement (where there is no evidence of efficacy) and help inform the development of more useful and engaging mobile health apps. Trial Registration PROSPERO CRD42019155604; https://tinyurl.com/sno4lcu International Registered Report Identifier (IRRID) PRR1-10.2196/16931

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Smart Healthcare Apps for Quality Cancer Patient Support

International Journal of Big Data and Analytics in Healthcare ◽

10.4018/ijbdah.2020010103 ◽

2020 ◽

Vol 5 (1) ◽

pp. 28-48

Author(s):

Angelina Kouroubali ◽

Lefteris Koumakis ◽

Haridimos Kondylakis ◽

Dimitrios G. Katehakis

Keyword(s):

Mobile Health ◽

Mobile Apps ◽

Integrated Approach ◽

Well Being ◽

Coordinated Care ◽

Cancer Disease ◽

Health Apps ◽

Smart Healthcare ◽

Mobile Health Apps ◽

Digital Engagement

This paper analyzes the clinical and technological characteristics of cancer mobile apps that enable patients to securely record, manage, and share their information. It proposes an integrated approach towards developing quality mobile health apps for cancer and discusses issues relevant to the enhancement of patient experience and acceptance, adherence to treatment, and effective support of coordinated care. Regulation, standardization, and interoperability together with the existence of useful, accurate, and reliable tools for active patient engagement are important aids towards efficient cancer disease management. Improving quality of life and well-being, in a secure and safe manner that respects the patients' privacy, seems to be a key challenge, together with the exploitation of the outcomes of recent research projects, relevant to end user digital engagement towards an integrated approach for the introduction of trustworthy, interoperable, usable, adaptable, and quality mobile health apps.

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Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review

JMIR mhealth and uhealth ◽

10.2196/17046 ◽

2020 ◽

Vol 8 (3) ◽

pp. e17046 ◽

Cited By ~ 10

Author(s):

Madison Milne-Ives ◽

Ching Lam ◽

Caroline De Cock ◽

Michelle Helena Van Velthoven ◽

Edward Meinert

Keyword(s):

Health Behavior ◽

Behavior Change ◽

Mobile Health ◽

Mobile Apps ◽

Health Behavior Change ◽

Risk Of Bias ◽

Health Apps ◽

Mobile Health Apps ◽

Drug And Alcohol Use ◽

Drug And Alcohol

Background With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature. Objective This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps. Methods PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer. Results A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes. Conclusions There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

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Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review (Preprint)

10.2196/preprints.17046 ◽

2019 ◽

Cited By ~ 2

Author(s):

Madison Milne-Ives ◽

Ching Lam ◽

Caroline De Cock ◽

Michelle Helena Van Velthoven ◽

Edward Meinert

Keyword(s):

Health Behavior ◽

Behavior Change ◽

Mobile Health ◽

Mobile Apps ◽

Health Behavior Change ◽

Risk Of Bias ◽

Health Apps ◽

Mobile Health Apps ◽

Drug And Alcohol Use ◽

Drug And Alcohol

BACKGROUND With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature. OBJECTIVE This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps. METHODS PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer. RESULTS A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes. CONCLUSIONS There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

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Mobile health applications for managing atrial fibrillation for healthcare professionals and patients: a systematic review

EP Europace ◽

10.1093/europace/euaa269 ◽

2020 ◽

Vol 22 (10) ◽

pp. 1567-1578

Author(s):

Deirdre A Lane ◽

Naoimh McMahon ◽

Josephine Gibson ◽

Jo C Weldon ◽

Michal M Farkowski ◽

...

Keyword(s):

Quality Of Life ◽

Mobile Health ◽

User Engagement ◽

Post Intervention ◽

Health Apps ◽

Mobile Health Applications ◽

Mobile Health Apps ◽

The Impact ◽

Health Applications

Abstract Aims A plethora of mobile health applications (m-health apps) to support healthcare are available for both patients and healthcare professionals (HCPs) but content and quality vary considerably and few have undergone formal assessment. The aim is to systematically review the literature on m-health apps for managing atrial fibrillation (AF) that examine the impact on knowledge of AF, patient and HCP behaviour, patients’ quality-of-life, and user engagement. Methods and results MEDLINE, EMBASE, CINAHL, and PsychInfo were searched from 1 January 2005 to 5 September 2019, with hand-searching of clinical trial registers and grey literature. Studies were eligible for inclusion if they reported changes in any of the following: (i) knowledge of AF; (ii) provider behaviour (e.g. guideline adherence); (iii) patient behaviour (e.g. medication adherence); (iv) patient quality-of-life; and (v) user engagement. Two reviewers independently assessed articles for eligibility. A narrative review was undertaken as included studies varied widely in their design, interventions, comparators, and outcomes. Seven studies were included; six m-health apps aimed at patients and one at HCPs. Mobile health apps ranged widely in design, features, and method of delivery. Four studies reported patient knowledge of AF; three demonstrated significant knowledge improvement post-intervention or compared to usual care. One study reported greater HCP adherence to oral anticoagulation guidelines after m-health app implementation. Two studies reported on patient medication adherence and quality-of-life; both showed improved quality-of-life post-intervention but only one observed increased adherence. Regarding user engagement, five studies reported patient perspectives on usability, three on acceptability, and one on feasibility; overall all m-health apps were rated positively. Conclusion Mobile health apps demonstrate improvements in patient knowledge, behaviour, and quality of life. Studies formally evaluating the impact of m-health on HCP behaviour are scarce and larger-scale studies with representative patient cohorts, appropriate comparators, and longer-term assessment of the impact of m-health apps are warranted.

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