ArticleJMIR aging2019
Mobilizing mHealth Data Collection in Older Adults: Challenges and Opportunities.
Article in JMIR aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis 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
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.
- Effectiveness of Mobile Health Intervention in Medication Adherence: a Systematic Review and Meta-Analysis.Journal of medical systems · 2025Pooled it
- Leveraging Student-Athlete Mental Health Through an AI-Augmented Mobile Platform: The ThriveNudge Study Protocol.Behavioral sciences (Basel, Switzerland) · 2026Article
- eHealth and the Digital Divide Among Older Canadians: Insights from a National Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Nutritional assessment system integrating semantic segmentation and point cloud modeling techniques.Scientific reports · 2025Article
- Daily Diary Smartphone Assessment of Subjective Cognitive Concerns in Motoric Cognitive Risk Syndrome: A Pilot Study.Health science reports · 2025Article
- Article
- From Steps to Context: Optimizing Digital Phenotyping for Physical Activity Monitoring in Older Adults by Integrating Wearable Data and Ecological Momentary Assessment.Sensors (Basel, Switzerland) · 2025Article
- Empathy mapping and hybrid persona creation: Understanding older adults' needs in technology design for ageing in place.Computational and structural biotechnology journal · 2025Article
- Article
- Monitoring reaction time to digital device in the very-old to detect early cognitive decline.npj aging · 2024Article
- Association Between the Composite Cardiovascular Risk and mHealth Use Among Adults in the 2017-2020 Health Information National Trends Survey: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- Guidelines to Establish an Equitable Mobile Health Ecosystem.Psychiatric services (Washington, D.C.) · 2023Article
- Older adults' experience with virtual conversational agents for health data collection.Frontiers in digital health · 2023Article
- Understanding Barriers to the Collection of Mobile and Wearable Device Data to Monitor Health and Cognition in Older Adults: A Scoping Review.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Lessons learned on data collection for a digital health intervention-insights and challenges from Nigeria.SAGE open medicine · 2023Article
- Ambient Assisted Living: Scoping Review of Artificial Intelligence Models, Domains, Technology, and Concerns.Journal of medical Internet research · 2022Article
- Validation of the Mobile App Version of the EQ-5D-5L Quality of Life Questionnaire Against the Gold Standard Paper-Based Version: Randomized Crossover Study.JMIR formative research · 2022Article
- Attitudes of Patients With Chronic Heart Failure Toward Digital Device Data for Self-documentation and Research in Germany: Cross-sectional Survey Study.JMIR cardio · 2022Article
- mHealth Interventions to Support Caregivers of Older Adults: Equity-Focused Systematic Review.JMIR aging · 2022Review
- The Dispersion of Health Information-Seeking Behavior and Health Literacy in a State in the Southern United States: Cross-sectional Study.JMIR formative research · 2022Article
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 at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Worldwide, there is an unprecedented and ongoing expansion of both the proportion of older adults in society and innovations in digital technology. This rapidly increasing number of older adults is placing unprecedented demands on health care systems, warranting the development of new solutions. Although advancements in smart devices and wearables present novel methods for monitoring and improving the health of aging populations, older adults are currently the least likely age group to engage with such technologies. In this commentary, we critically examine the potential for technology-driven data collection and analysis mechanisms to improve our capacity to research, understand, and address the implications of an aging population. Alongside unprecedented opportunities to harness these technologies, there are equally unprecedented challenges. Notably, older adults may experience the first-level digital divide, that is, lack of access to technologies, and/or the second-level digital divide, that is, lack of use/skill, alongside issues with data input and analysis. To harness the benefits of these innovative approaches, we must first engage older adults in a meaningful manner and adjust the framework of smart devices to accommodate the unique physiological and psychological characteristics of the aging populace. Through an informed approach to the development of technologies with older adults, the field can leverage innovation to increase the quality and quantity of life for the expanding population of older adults.
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.