Content Analysis of Diet-Related Mobile Apps: A Self-Regulation Perspective

Self-Regulation and External Influence: The Relative Efficacy of Mobile Apps and Offline Channels for Personal Weight Management

On the basis of a novel panel data set on customers enrolled in an actual weight loss program that delivers services through a mobile app and offline stores, this study shows that use of the mobile app is positively associated with weight management by both free and paid users. For paid users, who have access to the mobile app and office visits, usage of both channels is associated with short-term weight loss. Furthermore, the two channels function as substitutes for one another, with users able to compensate for infrequent offline store visits through more intense mobile app usage. In the long term, however, only mobile app usage (and not offline store visits) contributes to the sustainability of weight loss. Additional empirical analyses further reveal that frequency and granularity of mobile app usage are positively associated with weight loss. We also find that individuals exposed to low performance pressure benefit more fully from mobile app usage. Overall, the empirical results, together with qualitative evidence gleaned from interviews with actual customers, suggest that mobile app usage and the self-regulation that it enables exert a relatively greater impact on personal weight management compared with the external influence stemming from human experts in offline channels.

Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints

The science and tools of measuring energy intake and output in humans have rapidly advanced in the last decade. Engineered devices such as wearables and sensors, software applications, and Web-based tools are now ubiquitous in both research and consumer environments. The assessment of energy expenditure in particular has progressed from reliance on self-report instruments to advanced technologies requiring collaboration across multiple disciplines, from optics to accelerometry. In contrast, assessing energy intake still heavily relies on self-report mechanisms. Although these tools have improved, moving from paper-based to online reporting, considerable room for refinement remains in existing tools, and great opportunities exist for novel, transformational tools, including those using spectroscopy and chemo-sensing. This report reviews the state of the science, and the opportunities and challenges in existing and emerging technologies, from the perspectives of 3 key stakeholders: researchers, users, and developers. Each stakeholder approaches these tools with unique requirements: researchers are concerned with validity, accuracy, data detail and abundance, and ethical use; users with ease of use and privacy; and developers with high adherence and utilization, intellectual property, licensing rights, and monetization. Cross-cutting concerns include frequent updating and integration of the food and nutrient databases on which assessments rely, improving accessibility and reducing disparities in use, and maintaining reliable technical assistance. These contextual challenges are discussed in terms of opportunities and further steps in the direction of personalized health.

Determinants of Continuance Intention to Use Health Apps among Users over 60: A Test of Social Cognitive Model

Promoting healthy behavior among seniors is important in reducing the burden of care and healthcare expenses in a rapidly aging society. Health apps can play an important role in health promotion for older adults, but the level of user retention in health apps is low. To increase continued health app use among older adults, this study examined the factors influencing older users’ continuance intentions to use health apps. The research model was developed based on the social cognitive theory of health behavior, which integrates cognitive, environmental, and behavioral perspectives. To test the research model, an anonymous online survey was conducted among respondents aged 60 to 79 years who were using health apps. The measurement items in the questionnaire were developed based on validated scales from the literature. A total of 250 samples were analyzed. The assessment of the measurement model indicates that the reliability and validity of the items are satisfactory. The results of testing the structural model illustrate the determinants of health app continuance intention: health technology self-efficacy, self-evaluative outcome expectations, self-regulation, and privacy risk. The interrelationships among determinants are also investigated. Theoretical and practical implications are suggested to encourage older adults’ continued health app use and promote their health behavior over the long term.

Insights into mobile health application market via a content analysis of marketplace data with machine learning

BACKGROUND

Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come.

OBJECTIVE

This study aims to investigate the current landscape of smartphone apps that focus on improving and sustaining health and wellbeing. Understanding the categories that popular apps focus on and the relevant features provided to users, which lead to higher user scores and downloads will offer insights to enable higher adoption in the general populace. This study on 1,000 mobile health applications aims to shed light on the reasons why particular apps are liked and adopted while many are not.

METHODS

User-generated data (i.e. review scores) and company-generated data (i.e. app descriptions) were collected from app marketplaces and manually coded and categorized by two researchers. For analysis, Artificial Neural Networks, Random Forest and Naïve Bayes Artificial Intelligence algorithms were used.

RESULTS

The analysis led to features that attracted more download behavior and higher user scores. The findings suggest that apps that mention a privacy policy or provide videos in description lead to higher user scores, whereas free apps with in-app purchase possibilities, social networking and sharing features and feedback mechanisms lead to higher number of downloads. Moreover, differences in user scores and the total number of downloads are detected in distinct subcategories of mobile health apps.

CONCLUSION

This study contributes to the current knowledge of m-health application use by reviewing mobile health applications using content analysis and machine learning algorithms. The content analysis adds significant value by providing classification, keywords and factors that influence download behavior and user scores in a m-health context.

Does Health Information Technology Promote Healthy Behaviors? The Mediating Role of Self-Regulation

Health information technology (health IT) has the potential to facilitate the self-regulation of fruit and vegetable intake (FVI) and physical activity (PA). This study explores whether using health IT for self-regulation mediates the relationship between sociodemographic factors and health behaviors including FVI and PA among U.S. adults. Bayesian mediation analysis was used to analyze a nationally representative sample of the U.S. adults (N = 3285) from Cycle 1 of the 2017 Health Information National Trends Survey (HINTS). The 95% credibility intervals (CI) were calculated for each sociodemographic factor and the mediator using health IT for self-regulation in relation to FVI and PA. About 58% of the participants used at least one type of health IT for self-regulation. Age was negatively associated with using health IT for self-regulation, whereas being a female and having a higher income and education were positively associated with it. Using health IT for self-regulation partially mediated the positive relationships between income, education, and FVI, but it is unrelated to PA. The findings support the efficacy of using health IT to regulate healthier eating. Nevertheless, the digital divide is a critical issue to consider when applying health IT to promote behavior change.

Actual Use of Multiple Health Monitors Among Older Adults With Diabetes: Pilot Study

Background

Previous studies have reported older adults’ perceptions of using health monitors; however, no studies have examined the actual use of multiple health monitors for lifestyle changes over time among older adults with type 2 diabetes (T2D).

Objective

The primary aim of this study was to examine the actual use of multiple health monitors for lifestyle changes over 3 months among older adults with T2D. The secondary aim was to explore changes in caloric intake and physical activity (PA) over 3 months.

Methods

This was a single-group study lasting 3 months. The study sample included participants who were aged ≥65 years with a diagnosis of T2D. Participants were recruited through fliers posted at the Joslin Diabetes Center in Boston. Participants attended five 60-min, biweekly group sessions, which focused on self-monitoring, goal setting, self-regulation to achieve healthy eating and PA habits, and the development of problem-solving skills. Participants were provided with the Lose It! app to record daily food intake and devices such as a Fitbit Alta for monitoring PA, a Bluetooth-enabled blood glucose meter, and a Bluetooth-enabled digital scale. Descriptive statistics were used for analysis.

Results

Of the enrolled participants (N=9), the sample was white (8/9, 89%) and female (4/9, 44%), with a mean age of 76.4 years (SD 6.0; range 69-89 years), 15.7 years (SD 2.0) of education, 33.3 kg/m² (SD 3.1) BMI, and 7.4% (SD 0.8) hemoglobin A_1c. Over the 84 days of self-monitoring, the mean percentage of days using the Lose It!, Fitbit Alta, blood glucose meter, and scale were 82.7 (SD 17.6), 85.2 (SD 19.7), 65.3 (SD 30.1), and 53.0 (SD 34.5), respectively. From baseline to completion of the study, the mean daily calorie intake was 1459 (SD 661) at week 1, 1245 (SD 554) at week 11, and 1333 (SD 546) at week 12, whereas the mean daily step counts were 5618 (SD 3654) at week 1, 5792 (SD 3814) at week 11, and 4552 (SD 3616) at week 12. The mean percentage of weight loss from baseline was 4.92% (SD 0.25). The dose of oral hypoglycemic agents or insulin was reduced in 55.6% (5/9) of the participants.

Conclusions

The results from the pilot study are encouraging and suggest the need for a larger study to confirm the outcomes. In addition, a study design that includes a control group with educational sessions but without the integration of technology would offer additional insight to understand the value of mobile health in behavior changes and the health outcomes observed during this pilot study.

Time to Work Out! Examining the Behavior Change Techniques and Relevant Theoretical Mechanisms that Predict the Popularity of Fitness Mobile Apps with Chinese-Language User Interfaces

Eyeing the huge potential mHealth market in China, developers both inside and outside of China have created an increasing number of fitness mobile applications with Chinese-language user interfaces. The present study analyzes the content of those fitness mobile apps (N = 177), with a particular focus on their behavior change techniques and relevant theoretical mechanisms. It finds that three theoretical mechanisms, modeling/observational learning, self-regulation, and social comparison/social support, are prevalent among fitness mobile apps with Chinese-language user interfaces. Moreover, based on the configurations of the behavior change techniques, three distinct clusters are identified: "instructional apps" (N = 75), "self-regulation apps" (N = 58), and "triathlon apps" (N = 44). Among them, "triathlon apps" equipped with technical features reflecting all three theoretical mechanisms are found to be the most popular among users. This suggests the usefulness of health behavior change theories in promoting physical activity via mobile apps in that the inclusion of more theoretical content in the app design enhances the app's effectiveness. More theoretical and practical implications are also discussed.

How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours

OBJECTIVE

The objective of this review was to analyse how researchers conducting studies about mobile health applications (MHApps) effectiveness assess the conditions of this effectiveness.

STUDY DESIGN

A scoping review according to PRIMSA-ScR checklist.

METHODS

We conducted a scoping review of efficacy/effectiveness conditions in high internal validity studies assessing the efficacy of MHApps in changing physical activity behaviours and eating habits. We used the PubMed, Web of Science, SPORTDiscus and PsycINFO databases and processed the review according to the O'Malley and PRISMA-ScR recommendations. We selected studies with high internal validity methodologies (randomised controlled trials, quasi-experimental studies, systematic reviews and meta-analyses), dealing with dietary and/or physical activity behaviours; covering primary, secondary or tertiary prevention and dealing with behaviour change (uptake, maintenance). We excluded articles on MHApps relating to high-level sport and telemedicine. The process for selecting studies followed a set protocol with two authors who independently appraised the studies.

RESULTS

Twenty-two articles were finally selected and analysed. We noted that the mechanisms and techniques to support behaviour changes were poorly reported and studied. There was no explanation of how these MHApps work and how they could be transferred or not. Indeed, the main efficacy conditions reported by authors refer to practical aspects of the tools. Moreover, the issue of social inequalities was essentially reduced to access to the technology (the shrinking access divide), and literacy was poorly studied, even though it is an important consideration in digital prevention. All in all, even when they dealt with behaviours, the evaluations were tool-focused rather than intervention-focused and did not allow a comprehensive assessment of MHApps.

CONCLUSION

To understand the added value of MHApps in supporting behaviour changes, it seems important to draw on the paradigms relating to health technology assessment considering the characteristics of the technologies and on the evaluation of complex interventions considering the characteristics of prevention. This combined approach may help to clarify how these patient-focused MHApps work and is a condition for improved assessment of MHApps in terms of effectiveness, transferability and scalability.

Smartphone apps and the nutrition care process: Current perspectives and future considerations

OBJECTIVE

To provide dietitians with practical guidance on incorporating smartphone applications (apps) in the nutrition care process (NCP) to optimize patient education and counseling.

METHODS

The current evidence-base for mobile health (mHealth) apps was searched using PubMed and Google Scholar. Where and how apps could be implemented by dietitians across the four steps of the NCP is discussed.

RESULTS

With functionality to automatically convert patient dietary records into nutrient components, nutrition assessment can be streamlined using nutrition apps, allowing more time for dietitians to deliver education and nutrition counseling. Dietitians could prescribe apps to provide patients with education on nutrition skills and in counseling for better adherence to behavior change. Improved patient-provider communication is also made possible through the opportunity for real-time monitoring and evaluation of patient progress via apps. A practical framework termed the 'Mobile Nutrition Care Process Grid' provides dietitians with best-practice guidance on how to use apps.

CONCLUSIONS

Including apps into dietetic practice could enhance the efficiency and quality of nutrition care and counseling delivered by dietitians.

PRACTICE IMPLICATIONS

Apps should be considered an adjunct to enable dietetic counseling and care, rather than to replace the expertise, social support and accountability provided by dietitians.

Complementary Support from Facilitators and Peers for Promoting mHealth Engagement and Weight Loss

This study investigates the effects of mHealth interventions on sustainable behavior change and weight loss, drawing on in-app user activity data and online survey data. Specifically, we focus on the interactions within mobile support groups in Noom, an mHealth application for obesity intervention, to delve into how social support from facilitators and peers may play differential roles in promoting health outcomes. The results of structural equation modeling (N = 301) demonstrated that (a) perceived facilitator support was positively associated with group members' health information acquisition such as fitness-themed article reading whereas perceived peer support was positively linked to group participation such as posting and responding; (b) perceived peer support was positively related to normative influence among group members, which subsequently increased group members' responses to others' posts; and (c) health information reading and in-group posting promoted weight loss; however, merely responding to others' posts did not lead to weight-loss success. The findings suggest that the complementary influences of facilitators and peers must be considered to enhance the efficacy of support group interventions.

Can existing mobile apps support healthier food purchasing behaviour? Content analysis of nutrition content, behaviour change theory and user quality integration

OBJECTIVE

To assess the quality of nutrition content and the integration of user quality components and behaviour change theory relevant to food purchasing behaviour in a sample of existing mobile apps.

DESIGN

Descriptive comparative analysis of eleven mobile apps comprising an assessment of their alignment with existing evidence on nutrition, behaviour change and user quality, and their potential ability to support healthier food purchasing behaviour.

SETTING

Mobile apps freely available for public use in GoogePlay were assessed and scored according to agreed criteria to assess nutrition content quality and integration of behaviour change theory and user quality components.

SUBJECTS

A sample of eleven mobile apps that met predefined inclusion criteria to ensure relevance and good quality.

RESULTS

The quality of the nutrition content varied. Improvements to the accuracy and appropriateness of nutrition content are needed to ensure mobile apps support a healthy behaviour change process and are accessible to a wider population. There appears to be a narrow focus towards behaviour change with an overemphasis on behavioural outcomes and a small number of behaviour change techniques, which may limit effectiveness. A significant effort from the user was required to use the mobile apps appropriately which may negatively influence user acceptability and subsequent utilisation.

CONCLUSIONS

Existing mobile apps may offer a potentially effective approach to supporting healthier food purchasing behaviour but improvements in mobile app design are required to maximise their potential effectiveness. Engagement of mobile app users and nutrition professionals is recommended to support effective design.

Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review

Smartphone applications are increasingly being used to support nutrition improvement in community settings. However, there is a scarcity of practical literature to support researchers and practitioners in choosing or developing health applications. This work maps the features, key content, theoretical approaches, and methods of consumer testing of applications intended for nutrition improvement in community settings. A systematic, scoping review methodology was used to map published, peer-reviewed literature reporting on applications with a specific nutrition-improvement focus intended for use in the community setting. After screening, articles were grouped into 4 categories: dietary self-monitoring trials, nutrition improvement trials, application description articles, and qualitative application development studies. For mapping, studies were also grouped into categories based on the target population and aim of the application or program. Of the 4818 titles identified from the database search, 64 articles were included. The broad categories of features found to be included in applications generally corresponded to different behavior change support strategies common to many classic behavioral change models. Key content of applications generally focused on food composition, with tailored feedback most commonly used to deliver educational content. Consumer testing before application deployment was reported in just over half of the studies. Collaboration between practitioners and application developers promotes an appropriate balance of evidence-based content and functionality. This work provides a unique resource for program development teams and practitioners seeking to use an application for nutrition improvement in community settings.

Challenges in Assessing Mobile Health App Quality: A Systematic Review of Prevalent and Innovative Methods

CONTEXT

Mobile apps are poised to become a major source of health guidance; however, concerns about their quality and safety remain. Governments, clinicians, and health researchers are struggling to determine how to adequately evaluate the content and function of mobile health apps to guide consumers toward apps that will effectively and safely support their health. Researchers are both adapting existing research methods, such as those for systematic reviews, and exploring novel methods toward this aim. The purpose of this systematic review was to describe prevalent and emerging methods for searching, data extraction, and analysis in the context of mobile health apps and commercial app stores.

EVIDENCE ACQUISITION

A systematic search was conducted on April 6, 2016, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, for published studies that evaluated health-related apps targeted at consumers in a commercial app store, and a descriptive content analysis of their methods was performed.

EVIDENCE SYNTHESIS

Although the majority of studies self-identified as "reviews" or "systematic reviews," their claims to have performed an exhaustive, replicable, and systematic search and data extraction are unsupported, given the nature of commercial app stores' search engines and personalized app content. Currently, studies of health-related app content are largely descriptive, and most use surrogate and one-dimensional outcome measures for app content quality.

CONCLUSIONS

This field is rapidly developing, and innovative methods for systematic searches, multidimensional quality assessment, and contextualizing content assessment are emerging. Areas for future methodologic development are highlighted, including expanding definitions of app "content" and assessing risk of bias.

A qualitative study of user perceptions of mobile health apps

Background

Mobile apps for health exist in large numbers today, but oftentimes, consumers do not continue to use them after a brief period of initial usage, are averse toward using them at all, or are unaware that such apps even exist. The purpose of our study was to examine and qualitatively determine the design and content elements of health apps that facilitate or impede usage from the users’ perceptive.

Methods

In 2014, six focus groups and five individual interviews were conducted in the Midwest region of the U.S. with a mixture of 44 smartphone owners of various social economic status. The participants were asked about their general and health specific mobile app usage. They were then shown specific features of exemplar health apps and prompted to discuss their perceptions. The focus groups and interviews were audio recorded, transcribed verbatim, and coded using the software NVivo.

Results

Inductive thematic analysis was adopted to analyze the data and nine themes were identified: 1) barriers to adoption of health apps, 2) barriers to continued use of health apps, 3) motivators, 4) information and personalized guidance, 5) tracking for awareness and progress, 6) credibility, 7) goal setting, 8) reminders, and 9) sharing personal information. The themes were mapped to theories for interpretation of the results.

Conclusions

This qualitative research with a diverse pool of participants extended previous research on challenges and opportunities of health apps. The findings provide researchers, app designers, and health care providers insights on how to develop and evaluate health apps from the users’ perspective.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3808-0) contains supplementary material, which is available to authorized users.