ArticleTranslational behavioral medicine2017
Who are mobile app users from healthy lifestyle websites? Analysis of patterns of app use and user characteristics.
Article in Translational behavioral medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.
- Associations Between the Use of Fitness and Diet Tracking Technology and Disordered Eating Behaviour: A Systematic Review.European eating disorders review : the journal of the Eating Disorders Association · 2025Pooled it
- Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- The impact of psychological user characteristics on adherence to an mHealth intervention among women in their postpartum period.Internet interventions · 2026Article
- Temporal patterns of everyday movement while working from home: a longitudinal study of step counts in Sweden during COVID-19.BMC public health · 2026Article
- Patterns and Characteristics of Mobile App Use to Promote Wellness and Manage Illness: Cross-Sectional Study.Journal of medical Internet research · 2026Article
- 'Journal of health psychology · 2024Article
- The use of digital platforms and physical activity practice in a population from southern Brazil: Findings from the PAMPA Cohort.Preventive medicine reports · 2024Article
- Individual and Parental Factors of Adolescents' mHealth App Use: Nationally Representative Cross-sectional Study.JMIR mHealth and uHealth · 2022Article
- UK Adults' Exercise Locations, Use of Digital Programs, and Associations with Physical Activity During the COVID-19 Pandemic: Longitudinal Analysis of Data From the Health Behaviours During the COVID-19 Pandemic Study.JMIR formative research · 2022Article
- Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach.Frontiers in nutrition · 2022Article
- Fitness Apps, Live Streaming Workout Classes, and Virtual Reality Fitness for Physical Activity During the COVID-19 Lockdown: An Empirical Study.Frontiers in public health · 2022Article
- Patterns of digital information and communication technology use among patients at primary health care centres in Colombia: Phase I of the DIADA project.Revista Colombiana de psiquiatria · 2021Article
- Evaluation is Key: Providing Appropriate Evaluation Measures for Participatory and User-Centred Design Processes of Healthcare IT.International journal of integrated care · 2021Article
- Smartphone Medical App Use and Associated Factors Among Physicians at Referral Hospitals in Amhara Region, North Ethiopia, in 2019: Cross-sectional Study.JMIR mHealth and uHealth · 2021Article
- The Use of Digital Platforms for Adults' and Adolescents' Physical Activity During the COVID-19 Pandemic (Our Life at Home): Survey Study.Journal of medical Internet research · 2021Article
- Article
- Use of the Consumer-Based Meditation App Calm for Sleep Disturbances: Cross-Sectional Survey Study.JMIR formative research · 2020Article
- The Use of Fitness Influencers' Websites by Young Adult Women: A Cross-Sectional Study.International journal of environmental research and public health · 2020Article
- Effect of mHealth With Offline Antiobesity Treatment in a Community-Based Weight Management Program: Cross-Sectional Study.JMIR mHealth and uHealth · 2020Article
- Characteristics and Usage Patterns Among 12,151 Paid Subscribers of the Calm Meditation App: Cross-Sectional Survey.JMIR mHealth and uHealth · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.