Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review

Abstract

BackgroundMobile apps are being widely used for delivering health interventions, with their ubiquitous access and sensing capabilities. One such use is the delivery of interventions for healthy eating behavior.ObjectiveThe aim of this study was to provide a comprehensive view of the literature on the use of mobile interventions for eating behavior change. We synthesized the studies with such interventions and mapped out their input methods, interventions, and outcomes.MethodsWe conducted a scoping literature search in PubMed/MEDLINE, Association for Computing Machinery Digital Library, and PsycINFO databases to identify relevant papers published between January 2013 and April 2018. We also hand-searched relevant themes of journals in the Journal of Medical Internet Research and registered protocols. Studies were included if they provided and assessed mobile-based interventions for dietary behavior changes and/or health outcomes.ResultsThe search resulted in 30 studies that we classified by 3 main aspects: input methods, mobile-based interventions, and dietary behavior changes and health outcomes. First, regarding input methods, 5 studies allowed photo/voice/video inputs of diet information, whereas text input methods were used in the remaining studies. Other than diet information, the content of the input data in the mobile apps included user’s demographics, medication, health behaviors, and goals. Second, we identified 6 categories of intervention contents, that is, self-monitoring, feedback, gamification, goal reviews, social support, and educational information. Although all 30 studies included self-monitoring as a key component of their intervention, personalized feedback was a component in 18 studies, gamification was used in 10 studies, goal reviews in 5 studies, social support in 3 studies, and educational information in 2 studies. Finally, we found that 13 studies directly examined the effects of interventions on health outcomes and 12 studies examined the effects on dietary behavior changes, whereas only 5 studies observed the effects both on dietary behavior changes and health outcomes. Regarding the type of studies, although two-thirds of the included studies conducted diverse forms of randomized control trials, the other 10 studies used field studies, surveys, protocols, qualitative interviews, propensity score matching method, and test and reference method.ConclusionsThis scoping review identified and classified studies on mobile-based interventions for dietary behavior change as per the input methods, nature of intervention, and outcomes examined. Our findings indicated that dietary behavior changes, although playing a mediating role in improving health outcomes, have not been adequately examined in the literature. Dietary behavior change as a mechanism for the relationship between mobile-based intervention and health outcomes needs to be further investigated. Our review provides guidance for future research in this promising mobile health area.

Weight Reduction Through a Digital Nutrition and Food Purchasing Platform Among Users With Obesity: Longitudinal Study

“…Digital health technologies that incorporate nutrition education and monitoring have gained increasing popularity to change and manage dietary choices [ 15 - 17 ]. Previous studies on mobile apps to improve nutrition are promising as their results indicate that digital nutrition interventions may be effective in changing dietary behavior to improve weight, glucose, and blood pressure among healthy individuals and people at risk of or with chronic disease [ 18 - 21 ]. While many of these apps provide general diet recommendations, few apps have a decision engine capable of providing personalized dietary advice, meal planning assistance, and online grocery delivery to users [ 16 ].…”

Cardiovascular Risk Factors and Social Development Index

“…The rationale behind studying the association between SDI and CVRF instead of actual disease or co-morbidities is that by unveiling such links in healthy individuals with known risks, one may be able to derive knowledge that could be translated into primary prevention strategies. Public health policy may be designed with a view to early social interventions in neighborhoods with increased risk associated features (see Supplementary Note 1 ) ( 9 , 59 , 60 ).…”

eHealth Delivery of Educational Content Using Selected Visual Methods to Improve Health Literacy on Lifestyle-Related Diseases: Literature Review

“…One limitation is the search process: we searched only a single database and included only studies written in English and published in the decade up to April 2019. As discussed in other review papers about eHealth-based interventions [ 3 , 14 ], selecting from additional databases that include unpublished studies is useful for a broader review and should be a consideration for any future systematic review on the topic. Nevertheless, the search was conducted in a systematic manner using the PRISMA flow diagram [ 25 , 26 ].…”

“…This literature review was performed using a systematic search and was conducted to emphasize the integration of studies across broader topics [ 3 ], with reference to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [ 25 , 26 ]. The search strategy was developed on April 2, 2019, by AA and TS, who also conducted the search.…”

“…Lifestyle behaviors (eg, smoking, harmful consumption of alcohol, overeating, lack of exercise) or conditions (eg, overweight or obesity, hypertension, abnormal lipid metabolism, and hyperglycemia) are common risk factors for lifestyle-related diseases [ 3 , 4 ]. Lifestyle improvement (eg, high-quality diet, increased exercise) plays an important role in the prevention of lifestyle-related diseases [ 4 , 5 ], and improvement for some conditions can be achieved using eHealth-based interventions [ 3 ]. Furthermore, the association between lifestyle behavior and health literacy has been widely recognized [ 4 , 6 ].…”