Use of Evidence-Based Best Practices and Behavior Change Techniques in Breast Cancer Apps: Systematic Analysis

Abstract

Background Theoretically designed mobile health (mHealth) breast cancer interventions are essential for achieving positive behavior change. In the case of breast cancer, they can improve the health outcomes of millions of women by increasing prevention and care efforts. However, little is known about the theoretical underpinnings of breast cancer apps available to the general public. Objective Given that theories may strengthen mHealth interventions, this study aimed to identify breast cancer apps designed to support behavior change, to assess the extent to which they address content along the cancer care continuum and contain behavior change techniques, and to assess the degree to which star rating is related to theory-based design. Methods Using a criteria-based screening process, we searched 2 major app stores for breast cancer apps designed to promote behavior change. Apps were coded for content along the cancer care continuum and analyzed for behavior change techniques. The Mann-Whitney U test was used to examine the relationship between star ratings and the use of behavior change techniques in apps with star ratings compared to those without ratings. Results The search resulted in a total of 302 apps, of which 133 were identified as containing breast cancer content. Only 9.9% (30/302) of apps supported behavior change and were further analyzed. These apps were disproportionally focused on behaviors to enhance early detection, whereas only a few apps supported care management, treatment, and posttreatment behaviors. Regarding theories, 63% (19/30) of apps customized content to users, 70% (21/30) established a health-behavior link, and 80% (24/30) provided behavior change instructions. Of the 30 apps, 15 (50%) prompted intention formation whereas less than half of the apps included goal setting (9/30, 30%) and goal reviewing (7/30, 23%). Most apps did not provide information on peer behavior (7/30, 23%) or allow for social comparison (6/30, 20%). None of the apps mobilized social norms. Only half of the apps (15/30, 50%) were user rated. The results of the Mann-Whitney U test showed that apps with star ratings contained significantly more behavior change techniques (median 6.00) than apps without ratings. The analysis of behavior change techniques used in apps revealed their shortcomings in the use of goal setting and social influence features. Conclusions Our findings indicate that commercially available breast cancer apps have not yet fully realized their potential to promote behavior change, with only a minority of apps focusing on behavior change, and even fewer including theoretical design to support behavior change along the cancer care continuum. These shortcomings are likely limiting the effectiveness of apps and their ability to improve public health. More attention needs to be paid to the involvement of professionals in app development and adherence to theories and best practices in app design to support individuals along the cancer care continuum.

A Review of AI and Data Science Support for Cancer Management

“…Authors of selected studies also discussed behavior change techniques (BCTs) and other theoretical constructs employed in considered apps. First, Kalke et al [107] reviewed 30 apps for breast cancer patients available to the general public in popular app stores and covering nearly all cancer continuum with the exception of end-of-life support. The authors used the taxonomy for coding BCTs in mobile cancer apps [108] (this taxonomy is based on the original proposal by Abraham and Michie [109]) and identified 12 BCTs coming from 6 categories: customization, information/behavior relationship, intention, facilitation, self-efficacy and social influence.…”

Development of Mobile App for Breast Examination Awareness Using Health Belief Model: A Qualitative Study

“…There has been an increasing interest in breast cancer mobile apps that focus on secondary and tertiary breast cancer prevention (Houghton et al, 2019). This technology has the potential to promote behaviour change (Kalke et al, 2020). However, there is lacking study that these mobile apps are integrating theory and utilized a qualitative approach to design and develop apps (Houghton et al, 2019;Kalke et al, 2020).…”

“…This technology has the potential to promote behaviour change (Kalke et al, 2020). However, there is lacking study that these mobile apps are integrating theory and utilized a qualitative approach to design and develop apps (Houghton et al, 2019;Kalke et al, 2020). A study by Ginossar et al, 2017 reported a gap in the expectation for BC apps and suggested that researchers need to identify user expectations for BC apps.…”

Acceptability of Intervention Design Factors in mHealth Intervention Research: Experimental Factorial Study

“…Experimental methods (eg, randomization and manipulation of technology design features) can be particularly informative for studying a priori acceptability because they afford controls that allow researchers to assess whether significant differences in acceptability ratings before participating in a mobile intervention are because of varying conditions of mHealth design factors [ 25 , 26 ]. Surprisingly, many mHealth design studies to date have also lacked attention to theory from implementation and behavioral sciences to inform evaluation plans [ 27 ]. The literature is unclear regarding how various mHealth design conditions differentially influence participant acceptance of the intervention and its participation requirements [ 10 , 28 ].…”