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

Early Results from COVID-19 Studies (339) JMIR Theme Issue: COVID-19 Special Issue (2500) Public (e)Health, Digital Epidemiology and Public Health Informatics (867) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (153) Outbreak and Pandemic Preparedness and Management (1783) Mobile Health (mhealth) (3173)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41479, first published .
The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis

The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis

The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis

Authors of this article:

Tessi M Hengst1 Author Orcid Image ;   Lilian Lechner1 Author Orcid Image ;   Laura Nynke van der Laan2 Author Orcid Image ;   Arjen Hommersom3 Author Orcid Image ;   Daan Dohmen4 Author Orcid Image ;   Lotty Hooft5 Author Orcid Image ;   Esther Metting6, 7 Author Orcid Image ;   Wolfgang Ebbers8 Author Orcid Image ;   Catherine A W Bolman1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Wang H, Lin T, Yao Y, Hsu C, Yang C, Chen T, Yeh Y. Community-Based Digital Contact Tracing of Emerging Infectious Diseases: Design and Implementation Study With Empirical COVID-19 Cases. Journal of Medical Internet Research 2023;25:e47219 View
  2. van Tuyl L, Keuper J, Standaar L, Alblas E, Keij B. Toegankelijkheid van digitale zorg: signalen uit de e‑healthmonitor 2023. TSG - Tijdschrift voor gezondheidswetenschappen 2025;103(S1):3 View