Evaluation of Behavior Change Techniques in Mobile Health Apps

2020 ◽  
Vol 31 (2) ◽  
pp. 126-128
Author(s):  
Linda Harrington
Keyword(s):  
Behavior Change ◽  
Mobile Health ◽  
Behavior Change Techniques ◽  
Health Apps ◽  
Mobile Health Apps

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 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 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 PNS187 US NATIONAL TRENDS OF MOBILE HEALTH APPS USE IN 2014 AND 2018

2019 ◽  
Vol 22 ◽  
pp. S317
Author(s):  
X. Feng ◽  
T. Lavelle ◽  
P.J. Lin
Keyword(s):  
Mobile Health ◽  
Health Apps ◽  
Mobile Health Apps ◽  
National Trends

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.

scholarly journals Patient-Centric Structural Determinants of Adherence Rates Among Asthma Populations: Exploring the Potential of Patient Activation and Encouragement Tool TRUSTR to Improve Adherence

2020 ◽  
Vol 7 (2) ◽  
Author(s):  
Asim Zia ◽  
Arthur Brassart ◽  
Sheila Thomas ◽  
Fen Ye ◽  
Judith Stephenson ◽  
...  
Keyword(s):  
Clinical Data ◽  
Mobile Health ◽  
Medical Condition ◽  
Total Effect ◽  
Adherence Rate ◽  
Administrative Claims ◽  
Structural Determinants ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Patient Centric

Background: Lack of adherence with prescribed medications among the asthma populations exacerbates health outcomes and increases social and economic costs. Objectives: The proposed study aims to model patient-centric structural determinants of adherence rates among asthma patients and explore the potential of mobile health apps such as the TRUSTR platform to improve adherence using its power of monetary and non-monetary chatbotting and non-monetary nudges. Following specific hypotheses are tested: (1) Patient attributes, such as their age and medical condition, have significant effect on their adherence with the prescribed treatment plans. (2) Behavioral nudging with rewards and engagement via mobile health apps will increase adherence rates. Methods: The patient population (N= 37 359) consists of commercially insured patients with asthma who have been identified from administrative claims in the HealthCore Integrated Research Database (HIRD) between April 1, 2018 and March 31, 2019. Two Structural Equation Models (SEMs) are estimated to quantify direct, indirect and total effect sizes of age and medical condition on proportion of days covered (PDC) and medical possession ratio (MPR), mediated by patient medical and pharmacy visits. Fourteen additional SEMs were estimated to lateralize TRUSTR findings and conduct sensitivity analysis. Results: HIRD data reveal mean adherence rate of 59% (standard deviation (SD) 29%) for PDC and 58% for MPR (SD 36%). Key structural findings from SEMs derived from the HIRD dataset indicate that each additional year in the age of the patient has a positive total effect on the adherence rate. Patients with poor medical condition are likely to have lower adherence rate, but this direct effect is countered by mediating variables. Further, each additional reward and higher engagement with a mobile app is likely to have a positive total effect on increasing the adherence rate. Conclusions: HIRD data reveal mean adherence rate of 59% (SD 29%), providing the evidence for the opportunity to increase adherence rate by around 40%. Statistical modeling results reveal structural determinants, such as the opportunity to nudge, are higher among younger patients, as they have higher probability of being non-adherent. Methodologically, lateralization approach demonstrates the potential to capture real-world evidence beyond clinical data and merge it with clinical data.

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