ArticleWiley interdisciplinary reviews. Computational statistics2013
Uncovering patterns of technology use in consumer health informatics.
Article in Wiley interdisciplinary reviews. Computational statistics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of smartphone-based passive sensing for health and wellbeing.Journal of biomedical informatics · 2018Pooled it
- What Patients See: Evaluating the Quality, Readability, and Ethnic Inclusivity of Online Resources for Breast Reconstruction.Plastic and reconstructive surgery. Global open · 2026Article
- Intention to use and perceived satisfaction with a digital tool for dementia prevention among the Dutch general public: a cross-sectional study.BMC public health · 2025Observational
- Design of patient-facing immunization visualizations affects task performance: an experimental comparison of 4 electronic visualizations.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Health Consumer Engagement, Enablement, and Empowerment in Smartphone-Enabled Home-Based Diagnostic Testing for Viral Infections: Mixed Methods Study.JMIR mHealth and uHealth · 2022Article
- Care Staff Perspectives on Using Mobile Technology to Support Communication in Long-Term Care: Mixed Methods Study.JMIR nursing · 2020Article
- Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- 3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study.JMIR serious games · 2018Article
- Consumer Health Informatics Adoption among Underserved Populations: Thinking beyond the Digital Divide.Yearbook of medical informatics · 2018Review
- Technology use and preferences to support clinical practice guideline awareness and adherence in individuals with sickle cell disease.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Body Mass Index and the Literacy on Obesity in Relation to Media Following.Iranian journal of public health · 2018Article
- Focus Section Health IT Usability: Applying a Task-Technology Fit Model to Adapt an Electronic Patient Portal for Patient Work.Applied clinical informatics · 2018Article
- The Association Between Commonly Investigated User Factors and Various Types of eHealth Use for Self-Care of Type 2 Diabetes: Case of First-Generation Immigrants From Pakistan in the Oslo Area, Norway.JMIR public health and surveillance · 2017Article
- Using eHealth Technologies: Interests, Preferences, and Concerns of Older Adults.Interactive journal of medical research · 2017Article
- Does Informatics Enable or Inhibit the Delivery of Patient-centred, Coordinated, and Quality-assured Care: a Delphi Study. A Contribution of the IMIA Primary Health Care Informatics Working Group.Yearbook of medical informatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Internet usage and accessibility has grown at a staggering rate, influencing technology use for healthcare purposes. The amount of health information technology (Health IT) available through the Internet is immeasurable and growing daily. Health IT is now seen as a fundamental aspect of patient care as it stimulates patient engagement and encourages personal health management. It is increasingly important to understand consumer health IT patterns including who is using specific technologies, how technologies are accessed, factors associated with use, and perceived benefits. To fully uncover consumer patterns it is imperative to recognize common barriers and which groups they disproportionately affect. Finally, exploring future demand and predictions will expose significant opportunities for health IT. The most frequently used health information technologies by consumers are gathering information online, mobile health (mHealth) technologies, and personal health records (PHRs). Gathering health information online is the favored pathway for healthcare consumers as it is used by more consumers and more frequently than any other technology. In regard to mHealth technologies, minority Americans, compared with White Americans utilize social media, mobile Internet, and mobile applications more frequently. Consumers believe PHRs are the most beneficial health IT. PHR usage is increasing rapidly due to PHR integration with provider health systems and health insurance plans. Key issues that have to be explicitly addressed in health IT are privacy and security concerns, health literacy, unawareness, and usability. Privacy and security concerns are rated the number one reason for the slow rate of health IT adoption.
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.