ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022
User Experience of Symptom Checkers: A Systematic Review.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Towards mHealth applications for pet animal owners: a comprehensive literature review of requirements.BMC veterinary research · 2025Pooled it
- [Age and gender aspects in the utilization of emergency departments and their consideration in the management of emergency care].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026Article
- A light-weight symptom checker and its methodological validation.Veterinary research communications · 2026Article
- Economic evaluation of a digital symptom checker for endometriosis using a Markov decision process model.NPJ digital medicine · 2026Article
- Factors Influencing the Use of Online Symptom Checkers in the United Kingdom: Cross-Sectional Study.JMIR formative research · 2025Article
- Artificial Intelligence in Digital Self-Diagnosis Tools: A Narrative Overview of Reviews.Mayo Clinic proceedings. Digital health · 2025Review
- Artificial Intelligence in Healthcare: A Narrative Review of Recent Clinical Applications, Implementation Strategies, and Challenges.Journal of healthcare leadership · 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
- Population-based user-perceived experience ofRMD open · 2023Article
- Consumer opinion on the use of machine learning in healthcare settings: A qualitative systematic review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review reports the user experience of symptom checkers, aiming to characterize users studied in the existing literature, identify the aspects of user experience of symptom checkers that have been studied, and offer design suggestions. Our literature search resulted in 31 publications. We found that (1) most symptom checker users are relatively young; (2) eight relevant aspects of user experience have been explored, including motivation, trust, acceptability, satisfaction, accuracy, usability, safety/security, and functionality; (3) future symptom checkers should improve their accuracy, safety, and usability. Although many facets of user experience have been explored, methodological challenges exist and some important aspects of user experience remain understudied. Further research should be conducted to explore users' needs and the context of use. More qualitative and mixed-method studies are needed to understand actual users' experiences in the future.
Identifiers
37128443PMC10148318What 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.