Mobile Applications for Weight Management: Theory-Based Content Analysis
Introduction
Overweight and obesity continue to be common, costly, preventable public health issues in the U.S., where nearly seven of every 10 adults would benefit from weight loss.1 Current methods of promoting weight reduction through lifestyle intervention, reliant on intensive educational and counseling sessions to promote reduction in energy intake and increased energy expenditure, have largely failed to change the trajectory of the obesity epidemic.2 Although research is limited, some studies have suggested a benefit to using technology, such as Internet3, 4, 5, 6 and mobile technologies,7, 8, 9 to deliver health behavior interventions for lifestyle behavior change and weight management.
The development of smartphones has led to a proliferation of software applications (apps), which offer a relatively new and promising approach to behavioral lifestyle interventions7 by enhancing the delivery of interventions to individuals en masse with favorable cost utility.10 Apps can potentially serve as a platform from which behavioral interventions can be delivered.11 Of an estimated 91% of U.S. adults who currently own a mobile phone, 61% own smartphones.12 Half of all smartphone owners have used their phone to search for health information,5 with 60% of all downloaded health-related apps involving the topics of “weight loss” and “exercise.”13 However, with more than 10,000 apps currently offered that specifically target diet and weight loss,14 assessing the effectiveness of apps in promoting behavior change is a difficult task in the absence of efficacy studies.
Although smartphone apps show potential for helping some individuals lose weight and maintain healthy lifestyle habits,7, 15, 16 concerns have been raised about whether apps are failing to incorporate evidence-based content10, 11, 17, 18 and theory-based strategies9, 19, 20 aimed at promoting behavioral changes in health habits. One recent study performed a content analysis of apps primarily aimed at increasing exercise and found that overall the apps contained few features based on behavioral change theory.19 A review of developer descriptions of health and fitness apps revealed that many apps have insufficient evidence-informed content according to U.S. government diet and exercise recommendations.17 The National Weight Control Registry, which follows a cohort of participants who have lost and maintained at least 10% of initial body weight for at least 1 year, has shown that the most important predictors of maintenance of weight loss are daily caloric tracking, daily weight measurements, and daily exercise.21 Given recent literature on exercise apps, the focus chosen for the current paper is apps that target primarily diet/nutrition and/or anthropometric tracking.
There are several theory-based behavioral modification strategies that are commonly utilized in clinical practice to promote weight loss, changes in diet and exercise and to prevent relapse.22 These behavioral strategies include, for example, regular self-monitoring of health behaviors (i.e., tracking dietary intake23, 24) or health outcomes (i.e., tracking weight25, 26), which arise from self-regulation theory27 and have been shown to play an important role in weight loss and lifestyle behavior change success.22 However, although researchers may focus on whether apps contain traditional theory-based behavioral strategies, app developers are primarily focused on the user interface and keeping users engaged. Traditional theories may be insufficient to inform mobile intervention development9 because these interventions are often responsive, interactive, adaptive, and dynamic and allow for frequent iterative intervention adjustments in response to specific user input.9
These features are more in line with more contemporary theories.28, 29, 30 Persuasive technology theory, for example, posits that technology can be designed to change user attitudes and behaviors through persuasion and social influence, but not coercion.30 Similarly, the Fogg Behavioral Model (FBM)29 delineates three main factors necessary to persuade an individual to change behavior: motivation, ability, and triggers. The model suggests that when technology increases motivation and ability to make change, triggers to change behavior are more likely to work. This paper reports the results of an examination of the inclusion of both traditional and more modern health behavior theory constructs in smartphone apps focused on diet/nutrition and anthropometric tracking.
Section snippets
Study Design
This study is a comparative, descriptive assessment of the top-rated free smartphone apps in the Health and Fitness category available in the iTunes App Store. Included is a content analysis of constructs from behavior change theory and persuasive technology theory within each app. Four independent raters assessed each of the selected apps using the previously validated behavioral theory content survey,31 which assesses the presence of essential constructs of four major theories of behavior
Results
Of the 200 apps that were considered, 78 were primarily aimed at promoting physical activity, 88 were not related to diet/nutrition or anthropometric tracking, three were excluded for focusing on a specific diet subcategory, and eight were excluded because of not being stand-alone (Figure 1). A total of 23 apps met the inclusion criteria. These 23 apps were subsequently organized into five subcategories (Table 3). Dietary tracking apps was the largest category, containing a total of 12 apps.
Discussion
All apps were found to be very low in theoretic content or use of theory to guide behavior change, which was consistent with findings among physical activity–only apps.19 Among the apps reviewed, the maximum BTS was 14. The persuasive technology content survey resulted in a similar ranking of apps (Table 4). It is unfortunate how few theory-based behavioral strategies have been included as components in these apps, given the evidence for the effective use of these strategies in behavioral
Acknowledgments
The authors thank Melissa Raby for her intellectual contribution and critical review of this study. This paper was supported by internal funds from the Palo Alto Medical Foundation Research Institute.
No financial disclosures were reported by the authors of this paper.
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