A Methodologic Systematic Review of Mobile Health Behavior Change Randomized Trials

2019 ◽  
Vol 57 (6) ◽  
pp. 836-843 ◽  
Author(s):  
Theodora Oikonomidi ◽  
Alexandre Vivot ◽  
Viet-Thi Tran ◽  
Carolina Riveros ◽  
Elisabeth Robin ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Behavior ◽  
Behavior Change ◽  
Mobile Health ◽  
Randomized Trials ◽  
Health Behavior Change

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 Counseling for health behavior change in people with COPD: systematic review

2017 ◽  
Vol Volume 12 ◽  
pp. 2165-2178 ◽  
Author(s):  
Marie T Williams ◽  
Tanja Effing ◽  
Catherine Paquet ◽  
Carole Gibbs ◽  
Hayley Lewthwaite ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change

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.

Sign in / Sign up

Export Citation Format

Share Document