ReviewYearbook of medical informatics2019
Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications.
Review in Yearbook of medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
- Effectiveness of Al-Assisted Patient Health Education Using Voice Cloning and ChatGPT: Prospective Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- How weak AI promotes exercise in China: evidence from CLDS2018.BMC public health · 2026Article
- Artificial Intelligence in the Management of Infectious Diseases in Older Adults: Diagnostic, Prognostic, and Therapeutic Applications.Biomedicines · 2025Review
- The role of chatbots and virtual assistants in enhancing tobacco cessation counselling.Frontiers in digital health · 2025Review
- Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review.Journal of medical Internet research · 2023Article
- USING MACHINE LEARNING METHODS TO ASSESS THE RISK OF ALCOHOL MISUSE IN OLDER ADULTS.Research square · 2023Article
- Defining and Scoping Participatory Health Informatics: An eDelphi Study.Methods of information in medicine · 2023Article
- How Participatory Health Informatics Catalyzes One Digital Health.Yearbook of medical informatics · 2023Article
- Artificial Intelligence and Medical Humanities.The Journal of medical humanities · 2022Article
- The Application of the Principles of Responsible AI on Social Media Marketing for Digital Health.Information systems frontiers : a journal of research and innovation · 2021Article
- Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review.Yearbook of medical informatics · 2021Review
- Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.Journal of medical systems · 2020Article
- Ethical Considerations for Participatory Health through Social Media: Healthcare Workforce and Policy Maker Perspectives.Yearbook of medical informatics · 2020Article
- Evolution of Wearable Devices in Health Coaching: Challenges and Opportunities.Frontiers in digital health · 2020Article
- Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications.Yearbook of medical informatics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveArtificial intelligence (AI) provides people and professionals working in the field of participatory health informatics an opportunity to derive robust insights from a variety of online sources. The objective of this paper is to identify current state of the art and application areas of AI in the context of participatory health.
methodsA search was conducted across seven databases (PubMed, Embase, CINAHL, PsychInfo, ACM Digital Library, IEEExplore, and SCOPUS), covering articles published since 2013. Additionally, clinical trials involving AI in participatory health contexts registered at clinicaltrials.gov were collected and analyzed.
resultsTwenty-two articles and 12 trials were selected for review. The most common application of AI in participatory health was the secondary analysis of social media data: self-reported data including patient experiences with healthcare facilities, reports of adverse drug reactions, safety and efficacy concerns about over-the-counter medications, and other perspectives on medications. Other application areas included determining which online forum threads required moderator assistance, identifying users who were likely to drop out from a forum, extracting terms used in an online forum to learn its vocabulary, highlighting contextual information that is missing from online questions and answers, and paraphrasing technical medical terms for consumers.
conclusionsWhile AI for supporting participatory health is still in its infancy, there are a number of important research priorities that should be considered for the advancement of the field. Further research evaluating the impact of AI in participatory health informatics on the psychosocial wellbeing of individuals would help in facilitating the wider acceptance of AI into the healthcare ecosystem.
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.