This paper is in the following e-collection/theme issue:

Development and Evaluation of Research Methods, Instruments and Tools (511) Chatbots and Conversational Agents (543) Symptom Checkers (33) Research Instruments, Questionnaires, and Tools (589) mHealth for Data Collection and Research (981) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (847) Mobile Health (mhealth) (2982)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49907, first published .
Controlling Inputter Variability in Vignette Studies Assessing Web-Based Symptom Checkers: Evaluation of Current Practice and Recommendations for Isolated Accuracy Metrics

Controlling Inputter Variability in Vignette Studies Assessing Web-Based Symptom Checkers: Evaluation of Current Practice and Recommendations for Isolated Accuracy Metrics

Controlling Inputter Variability in Vignette Studies Assessing Web-Based Symptom Checkers: Evaluation of Current Practice and Recommendations for Isolated Accuracy Metrics

Authors of this article:

András Meczner1, 2 Author Orcid Image ;   Nathan Cohen1 Author Orcid Image ;   Aleem Qureshi1 Author Orcid Image ;   Maria Reza1 Author Orcid Image ;   Shailen Sutaria3 Author Orcid Image ;   Emily Blount1 Author Orcid Image ;   Zsolt Bagyura2 Author Orcid Image ;   Tamer Malak1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Kopka M, Feufel M. Software symptomcheckR: an R package for analyzing and visualizing symptom checker triage performance. BMC Digital Health 2024;2(1) View