PapersFlow Research Brief
Mobile Health and mHealth Applications
Research Guide
What is Mobile Health and mHealth Applications?
Mobile Health and mHealth Applications refer to the use of mobile technology, including smartphones and apps, for health interventions, behavior change, chronic disease management, patient engagement, text messaging for health promotion, self-monitoring through mobile apps, adherence to treatment via mobile phone reminders, and improving health outcomes.
This field encompasses 75,224 published works focused on mobile technologies for health purposes. Papers address applications such as self-monitoring apps, text messaging interventions, and tools for treatment adherence. Growth rate over the last 5 years is not available in the provided data.
Topic Hierarchy
Research Sub-Topics
mHealth Interventions for Chronic Disease Management
This sub-topic focuses on mobile apps and wearables for managing conditions like diabetes and hypertension through self-monitoring and personalized feedback. Researchers conduct randomized controlled trials to evaluate efficacy in improving clinical outcomes.
SMS-Based Health Behavior Change Interventions
This sub-topic examines text messaging campaigns for promoting behaviors like smoking cessation, physical activity, and medication adherence. Researchers perform meta-analyses of trials to determine scalability and long-term impact.
eHealth Literacy in mHealth Adoption
This sub-topic investigates how digital health literacy affects user engagement with mHealth apps, including barriers for low-literacy populations. Researchers develop and validate scales like eHEALS for predictive modeling.
Quality Assessment of Health Mobile Applications
This sub-topic develops frameworks like MARS for evaluating app usability, content accuracy, and evidence-based features. Researchers systematically review app stores to benchmark commercial offerings.
Patient Engagement via Mobile Health Reminders
This sub-topic studies reminder systems for treatment adherence in areas like HIV and mental health, using nudges and gamification. Researchers analyze adherence data from app logs in intervention studies.
Why It Matters
Mobile health applications support patient engagement and chronic disease management through tools like self-monitoring apps and reminder systems. Stoyanov et al. (2015) introduced the Mobile App Rating Scale (MARS), a reliable tool for assessing health app quality, which classifies apps objectively and aids developers in creating effective interventions (2384 citations). Norman and Skinner (2006) developed the eHEALS scale to measure eHealth literacy, enabling identification of user skills for engaging with mobile health tools in clinical settings (2515 citations). Holden and Karsh (2009) applied the Technology Acceptance Model to health care, explaining user adoption of mHealth technologies (2494 citations). These contributions improve health outcomes by ensuring apps meet quality standards and users possess necessary digital skills.
Reading Guide
Where to Start
"Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps" by Stoyanov et al. (2015) – read first because it provides a practical, validated framework for evaluating mHealth apps, essential for understanding quality standards before diving into literacy or acceptance models.
Key Papers Explained
Stoyanov et al. (2015) "Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps" establishes quality assessment for apps, which Norman and Skinner (2006) "eHEALS: The eHealth Literacy Scale" complements by measuring user skills needed to engage those apps effectively. Holden and Karsh (2009) "The Technology Acceptance Model: Its past and its future in health care" builds on these by explaining adoption dynamics. Bull et al. (2020) "World Health Organization 2020 guidelines on physical activity and sedentary behaviour" applies such frameworks to evidence-based interventions.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Research emphasizes integrating eHealth literacy scales like eHEALS with app quality tools such as MARS to enhance user adoption. Frontiers involve applying Technology Acceptance Model insights to scale mHealth for chronic disease management amid 75,224 works. No recent preprints or news available limits visibility into ongoing developments.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | World Health Organization 2020 guidelines on physical activity... | 2020 | British Journal of Spo... | 9.8K | ✓ |
| 2 | Health literacy and public health: A systematic review and int... | 2012 | BMC Public Health | 5.6K | ✓ |
| 3 | Low Health Literacy and Health Outcomes: An Updated Systematic... | 2011 | Annals of Internal Med... | 5.1K | ✕ |
| 4 | Health Literacy | 2004 | National Academies Pre... | 3.4K | ✕ |
| 5 | The evolving concept of health literacy | 2008 | Social Science & Medicine | 2.7K | ✕ |
| 6 | eHEALS: The eHealth Literacy Scale | 2006 | Journal of Medical Int... | 2.5K | ✓ |
| 7 | The Technology Acceptance Model: Its past and its future in he... | 2009 | Journal of Biomedical ... | 2.5K | ✕ |
| 8 | Health literacy in Europe: comparative results of the European... | 2015 | European Journal of Pu... | 2.4K | ✓ |
| 9 | Mobile App Rating Scale: A New Tool for Assessing the Quality ... | 2015 | JMIR mhealth and uhealth | 2.4K | ✓ |
| 10 | eHealth Literacy: Essential Skills for Consumer Health in a Ne... | 2006 | Journal of Medical Int... | 2.4K | ✓ |
Frequently Asked Questions
What is the Mobile App Rating Scale?
The Mobile App Rating Scale (MARS) is a simple, objective tool for classifying and assessing the quality of health mobile apps. Stoyanov et al. (2015) validated it as reliable for evaluating app design and functionality. Developers use MARS as a checklist for high-quality health apps.
How does eHEALS measure eHealth literacy?
eHEALS is the eHealth Literacy Scale that captures consumer comfort and skills in using information technology for health. Norman and Skinner (2006) showed it reliably assesses eHealth literacy across repeated administrations. In clinical settings, eHEALS identifies users ready for mobile health tools.
What role does the Technology Acceptance Model play in mHealth?
The Technology Acceptance Model explains user acceptance of health technologies, including mHealth apps. Holden and Karsh (2009) reviewed its application in health care contexts. It predicts adoption factors like perceived ease of use for mobile interventions.
Why is health literacy relevant to mHealth applications?
Health literacy affects users' ability to engage with mHealth apps for self-monitoring and behavior change. Sørensen et al. (2012) integrated definitions showing low literacy links to poorer health outcomes. Norman and Skinner (2006) extended this to eHealth literacy essential for digital health tools.
What do WHO guidelines say about physical activity in mHealth?
WHO 2020 guidelines on physical activity and sedentary behaviour guide mHealth interventions for health promotion. Bull et al. (2020) detailed evidence-based recommendations developed per WHO protocols. These support app-based strategies for behavior change and patient engagement.
How many papers exist on mobile health applications?
The field includes 75,224 works on mHealth for interventions like chronic disease management. Data covers topics from text messaging to self-monitoring apps. Citation leaders include Bull et al. (2020) with 9767 citations.
Open Research Questions
- ? How can mHealth apps be optimized for populations with low eHealth literacy as measured by eHEALS?
- ? What factors in the Technology Acceptance Model most predict long-term adherence to mHealth interventions for chronic diseases?
- ? How does app quality assessed by MARS correlate with real-world health outcomes in behavior change programs?
- ? In what ways do WHO physical activity guidelines integrate with mobile reminders for sedentary behavior reduction?
- ? What metrics best evaluate the effectiveness of text messaging in mHealth for patient engagement across diverse groups?
Recent Trends
The field maintains 75,224 papers with no specified 5-year growth rate.
Top-cited works like Bull et al. "World Health Organization 2020 guidelines on physical activity and sedentary behaviour" (9767 citations) sustain focus on guidelines for mHealth interventions.
2020No recent preprints or news coverage available.
Research Mobile Health and mHealth Applications with AI
PapersFlow provides specialized AI tools for Health Professions researchers. Here are the most relevant for this topic:
Systematic Review
AI-powered evidence synthesis with documented search strategies
AI Literature Review
Automate paper discovery and synthesis across 474M+ papers
Find Disagreement
Discover conflicting findings and counter-evidence
See how researchers in Health & Medicine use PapersFlow
Field-specific workflows, example queries, and use cases.
Start Researching Mobile Health and mHealth Applications with AI
Search 474M+ papers, run AI-powered literature reviews, and write with integrated citations — all in one workspace.
See how PapersFlow works for Health Professions researchers