ArticleJMIR mHealth and uHealth2017
Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
87 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Understanding Inequalities in Mobile Health Utilization Across Phases: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- The transformative power of mHealth apps: empowering patients with obesity and diabetes - a narrative review.Journal of medicine and life · 2024Pooled it
- Pooled it
- Mobile health technologies for the management of systemic lupus erythematosus: a systematic review.Lupus · 2020Pooled it
- Behavior Change Content, Understandability, and Actionability of Chronic Condition Self-Management Apps Available in France: Systematic Search and Evaluation.JMIR mHealth and uHealth · 2019Pooled it
- Factors Influencing Telehealth Service Use and Health Outcomes in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis: Cross-Sectional Study.Journal of medical Internet research · 2023Trial
- Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2021Trial
- Use of a Smartphone-Based Mobile App for Weight Management in Obese Minority Stroke Survivors: Pilot Randomized Controlled Trial With Open Blinded End Point.JMIR mHealth and uHealth · 2020Trial
- Reducing Incomplete Mobile Health Application Registration in Oncology.Applied clinical informatics · 2026Article
- Technology Acceptance of 2 mHealth Apps During an Observational Technology Evaluation Study: Qualitative Results of a Mixed Methods Study.JMIR human factors · 2026Observational
- Obesity Prevention and Reduction in China Using the Social Media Platform WeChat: Scoping Review.Interactive journal of medical research · 2025Review
- Unraveling the Factors Associated With Digital Health Intervention Uptake: Cross-Sectional Study.JMIR mHealth and uHealth · 2025Article
- Mobile Admission Process and Administrative Turnaround Time for Hospitalization of Outpatients: A Retrospective Study.Applied clinical informatics · 2025Article
- Examining the Influence of Demographic and Socioeconomic Factors on Disparities in Health Care App Usage: Protocol for a Systematic Scoping Review.JMIR research protocols · 2025Article
- Prevalence of menstrual pain and symptoms and their association with age and BMI among Japanese female app users.Scientific reports · 2025Article
- Technological-Based Interventions in Cancer and Factors Associated With the Use of Mobile Digital Wellness and Health Apps Among Cancer Information Seekers: Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Persian adaptation and validation of the user version of The Mobile Application Rating Scale (uMARS).PloS one · 2025Article
- Smartphone addiction as a risk factor for medication non-adherence in renal transplant recipients.Archives of medical science : AMS · 2025Article
- Achieving clinically meaningful outcomes in digital health: a six-step, cyclical precision engagement framework (ENGAGE).Frontiers in digital health · 2025Article
- Evaluating mobile apps for sun protection: content analysis and user preferences in a two-part study.Health psychology and behavioral medicine · 2025Article
27 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundMobile apps hold promise for serving as a lifestyle intervention in public health to promote wellness and attenuate chronic conditions, yet little is known about how individuals with chronic illness use or perceive mobile apps.
objectiveThe objective of this study was to explore behaviors and perceptions about mobile phone-based apps for health among individuals with chronic conditions.
methodsData were collected from a national cross-sectional survey of 1604 mobile phone users in the United States that assessed mHealth use, beliefs, and preferences. This study examined health app use, reason for download, and perceived efficacy by chronic condition.
resultsAmong participants, having between 1 and 5 apps was reported by 38.9% (314/807) of respondents without a condition and by 6.6% (24/364) of respondents with hypertension. Use of health apps was reported 2 times or more per day by 21.3% (172/807) of respondents without a condition, 2.7% (10/364) with hypertension, 13.1% (26/198) with obesity, 12.3% (20/163) with diabetes, 12.0% (32/267) with depression, and 16.6% (53/319) with high cholesterol. Results of the logistic regression did not indicate a significant difference in health app download between individuals with and without chronic conditions (P>.05). Compared with individuals with poor health, health app download was more likely among those with self-reported very good health (odds ratio [OR] 3.80, 95% CI 2.38-6.09, P<.001) and excellent health (OR 4.77, 95% CI 2.70-8.42, P<.001). Similarly, compared with individuals who report never or rarely engaging in physical activity, health app download was more likely among those who report exercise 1 day per week (OR 2.47, 95% CI 1.6-3.83, P<.001), 2 days per week (OR 4.77, 95% CI 3.27-6.94, P<.001), 3 to 4 days per week (OR 5.00, 95% CI 3.52-7.10, P<.001), and 5 to 7 days per week (OR 4.64, 95% CI 3.11-6.92, P<.001). All logistic regression results controlled for age, sex, and race or ethnicity.
conclusionsResults from this study suggest that individuals with poor self-reported health and low rates of physical activity, arguably those who stand to benefit most from health apps, were least likely to report download and use these health tools.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.