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

Early Results from COVID-19 Studies (335) JMIR Theme Issue: COVID-19 Special Issue (2493) Outbreak and Pandemic Preparedness and Management (1779) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1530) Infectious Diseases (non-STD/STI) (1656) Email Communication, Web-Based Communication, Secure Messaging (175) Text-messaging (SMS, WeChat etc)-Based Interventions (696) mHealth for Data Collection and Research (1080) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (916) Smoking Cessation (591)

Published on in Vol 5, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28929, first published .
A Case Study of an SMS Text Message Community Panel Survey and Its Potential for Use During the COVID-19 Pandemic

A Case Study of an SMS Text Message Community Panel Survey and Its Potential for Use During the COVID-19 Pandemic

A Case Study of an SMS Text Message Community Panel Survey and Its Potential for Use During the COVID-19 Pandemic

Authors of this article:

Lilian Chan1 Author Orcid Image ;   Nouhad El-Haddad2 Author Orcid Image ;   Becky Freeman1 Author Orcid Image ;   Blythe J O'Hara1 Author Orcid Image ;   Lisa Woodland3 Author Orcid Image ;   Ben Harris-Roxas4 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Sturgiss E, Advocat J, Barton C, Walker E, Nielsen S, Wright A, Lam T, Gunatillaka N, Oad S, Wood C. Using Text Messaging Surveys in General Practice Research to Engage With People From Low-Income Groups: Multi-Methods Study. JMIR mHealth and uHealth 2024;12:e55354 View
  2. Yu Z, Zhang C. Research on the Cross-Regional Traveling Welcome Short Messaging Service During the COVID-19 Pandemic: A Survey from Mobile Users’ Perspective. Systems 2025;13(1):40 View

Conference Proceedings

  1. Das A, Bearfield C, Mueller K. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Leveraging Large Language Models for Personalized Public Messaging View