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Who are mobile app users from healthy lifestyle websites? Analysis of patterns of app use and user characteristics

  • Original Research
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Translational Behavioral Medicine


The use of online communities and websites for health information has proliferated along with the use of mobile apps for managing health behaviors such as diet and exercise. The scarce evidence available to date suggests that users of these websites and apps differ in significant ways from non-users but most data come from US- and UK-based populations. In this study, we recruited users of nutrition, weight management, and fitness-oriented websites in the Czech Republic to better understand who uses mobile apps and who does not, including user sociodemographic and psychological profiles. Respondents aged 13–39 provided information on app use through an online survey (n = 669; M age = 24.06, SD = 5.23; 84% female). Among users interested in health topics, respondents using apps for managing nutrition, weight, and fitness (n = 403, 60%) were more often female, reported more frequent smartphone use, and more expert phone skills. In logistic regression models, controlling for sociodemographics, web, and phone activity, mHealth app use was predicted by levels of excessive exercise (OR 1.346, 95% CI 1.061–1.707, p < .01). Among app users, we found differences in types of apps used by gender, age, and weight status. Controlling for sociodemographics and web and phone use, drive for thinness predicted the frequency of use of apps for healthy eating (β = 0.14, p < .05), keeping a diet (β = 0.27, p < .001), and losing weight (β = 0.33, p < .001), whereas excessive exercise predicted the use of apps for keeping a diet (β = 0.18, p < .01), losing weight (β = 0.12, p < .05), and managing sport/exercise (β = 0.28, p < .001). Sensation seeking was negatively associated with the frequency of use of apps for maintaining weight (β = − 0.13, p < .05). These data unveil the user characteristics of mHealth app users from nutrition, weight management, and fitness websites, helping inform subsequent design of mHealth apps and mobile intervention strategies.

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The authors acknowledge the support of the Czech Science Foundation (GA15-05696S) and the Faculty of Social Studies, Masaryk University.

Author statements

This manuscript presents original results that have not been previously published and the manuscript has not been submitted elsewhere.

Parts of the results have been reported in an abstract submitted for the Annual Meeting of the Society of Behavioral Medicine in San Diego, CA (April 2017).

The authors have full control of all primary data and they agree to allow the journal to review their data if requested.

The data are part of a study (THINLINE) funded by the Czech Science Foundation (Grantová agentura ČR, GA15-05696S) and the Faculty of Social Studies at Masaryk University.

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Correspondence to Steriani Elavsky Ph.D.

Ethics declarations

The study has been approved by the Research Ethics Committee of Masaryk University.

All procedures performed in this study were in accordance with the ethical standards of the Research Ethics Committee of Masaryk University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Conflict of interest

The authors declare that they have no conflicts of interest.

Human and animal rights and informed consent

Informed consent (implied by survey submission) was obtained from all individual participants included in the study.

This article does not contain any studies with animals performed by any of the authors.

Additional information


Practice: Any potential intervention efforts utilizing mobile apps and targeting users of healthy lifestyle websites should consider underlying user characteristics such as gender, age, and weight status in selection of mHealth apps as well as consider the underlying psychological needs of users. App designers should incorporate user profiles in the design of mHealth apps to facilitate tailoring of app features to maximize their effectiveness as well as minimize any possible negative impact on users with different predispositions.

Policy: Standards for development of mHealth apps should include evaluation for potential to lead to psychological or behavioral vulnerabilities to avoid causing or exacerbating any maladaptive health behaviors in predisposed users.

Research: There are differences between app users and non-users of mHealth apps. Whereas some user characteristics such as excessive exercise or drive for thinness may help motivate app use, they should also be evaluated for potential to interact with mHealth app use in terms of leading to psychological harm or maladaptive health behaviors.

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Elavsky, S., Smahel, D. & Machackova, H. Who are mobile app users from healthy lifestyle websites? Analysis of patterns of app use and user characteristics. Behav. Med. Pract. Policy Res. 7, 891–901 (2017).

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