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

2019 ◽  
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.

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

10.2196/17046 ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. e17046 ◽  
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.

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

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

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

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

scholarly journals Mobile Health Apps for Medical Emergencies: Systematic Review

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.

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

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.

scholarly journals Archetypes of Gamification: Analysis of mHealth Apps

10.2196/19280 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e19280
Author(s):  
Manuel Schmidt-Kraepelin ◽  
Philipp A Toussaint ◽  
Scott Thiebes ◽  
Juho Hamari ◽  
Ali Sunyaev
Keyword(s):  
Best Practices ◽  
Health Behavior ◽  
Health Behaviors ◽  
Mobile Health ◽  
Positive Reinforcement ◽  
Mobile Apps ◽  
Health Behavior Change ◽  
Future Research ◽  
Research Approach ◽  
Health Related

Background Nowadays, numerous health-related mobile apps implement gamification in an attempt to draw on the motivational potential of video games and thereby increase user engagement or foster certain health behaviors. However, research on effective gamification is still in its infancy and researchers increasingly recognize methodological shortcomings of existing studies. What we actually know about the phenomenon today stems from fragmented pieces of knowledge, and a variety of different perspectives. Existing research primarily draws on conceptual knowledge that is gained from research prototypes, and isolated from industry best practices. We still lack knowledge on how gamification has been successfully designed and implemented within the industry and whether certain gamification approaches have shown to be particularly suitable for certain health behaviors. Objective We address this lack of knowledge concerning best practices in the design and implementation of gamification for health-related mobile apps by identifying archetypes of gamification approaches that have emerged in pertinent health-related mobile apps and analyzing to what extent those gamification approaches are influenced by the underlying desired health-related outcomes. Methods A 3-step research approach is employed. As a first step, a database of 143 pertinent gamified health-related mobile apps from the Apple App Store and Google Play Store is set up. Second, the gamification approach of each app within the database is classified based on an established taxonomy for gamification in health-related apps. Finally, a 2-step cluster analysis is conducted in order to identify archetypes of the most dominant gamification approaches in pertinent gamified health-related mobile apps. Results Eight archetypes of gamification emerged from the analysis of health-related mobile apps: (1) competition and collaboration, (2) pursuing self-set goals without rewards, (3) episodical compliance tracking, (4) inherent gamification for external goals, (5) internal rewards for self-set goals, (6) continuous assistance through positive reinforcement, (7) positive and negative reinforcement without rewards, and (8) progressive gamification for health professionals. The results indicate a close relationship between the identified archetypes and the actual health behavior that is being targeted. Conclusions By unveiling salient best practices and discussing their relationship to targeted health behaviors, this study contributes to a more profound understanding of gamification in mobile health. The results can serve as a foundation for future research that advances the knowledge on how gamification may positively influence health behavior change and guide practitioners in the design and development of highly motivating and effective health-related mobile health apps.

scholarly journals The Needle in the Haystack: Identifying Credible Mobile Health Apps for Pediatric Populations during a Pandemic and beyond

2020 ◽  
Vol 45 (10) ◽  
pp. 1106-1113
Author(s):  
Alexandra M Psihogios ◽  
Colleen Stiles-Shields ◽  
Martha Neary
Keyword(s):  
Mobile Health ◽  
Digital Health ◽  
Health Behavior Change ◽  
Clinical Expertise ◽  
The Public ◽  
Health Apps ◽  
Theoretical Support ◽  
Mobile Health Apps ◽  
Pediatric Populations ◽  
Mhealth Apps

Abstract Background The COVID-19 pandemic has ignited wider clinical adoption of digital health tools, including mobile health apps (mHealth apps), to address mental and behavioral health concerns at a distance. While mHealth apps offer many compelling benefits, identifying effective apps in the crowded and largely unregulated marketplace is laborious. Consumer demand and industry productivity are increasing, although research is slower, making it challenging for providers to determine the most credible and safe apps for patients in need. Objectives/Methods This commentary offers a practical, empirically guided framework and associated resources for selecting appropriate mHealth apps for pediatric populations during the pandemic and beyond. Results In the first stage, Narrow the target problem, end user, and contender apps. Beginning the search with continuously updated websites that contain expert app ratings can help expedite this process (e.g., Psyberguide). Second, Explore each contender app’s: (a) scientific and theoretical support (e.g., are app components consistent with health behavior change theories?), (b) privacy policies, and (c) user experience (e.g., through crowdsourcing feedback about app usability and appeal via social media). Third, use clinical expertise and stakeholder feedback to Contextualize whether the selected app is a good fit for a particular patient and/or caregiver (e.g., by considering age, race/ethnicity, ability, gender, sexual orientation, technology access), including conducting a brief self-pilot of the app. Conclusion Youth are increasingly turning to technology for support, especially during the pandemic, and pediatric psychologists must be primed to recommend the most credible tools. We offer additional recommendations for rapidly disseminating evidence-based apps to the public.

scholarly journals A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment (Preprint)

2020 ◽  
Author(s):  
Ginger E Nicol ◽  
Amanda R Ricchio ◽  
Christopher L Metts ◽  
Michael D Yingling ◽  
Alex T Ramsey ◽  
...  
Keyword(s):  
Young Adults ◽  
Health Behavior ◽  
Behavior Change ◽  
Needs Assessment ◽  
Mobile Health ◽  
Health Behavior Change ◽  
Mobile App ◽  
User Needs ◽  
Self Monitoring ◽  
Psychiatric Conditions

BACKGROUND Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals’ needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation. OBJECTIVE The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app. METHODS Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health–assisted health behavior change. RESULTS A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content. CONCLUSIONS The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed.

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