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

Crowdsourcing and Mechanical Turks (98) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832) Demographics of Users, Social & Digital Divide (739) Prevention and Health Promotion (987)

Published on in Vol 24, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30216, first published .
The Benefits of Crowdsourcing to Seed and Align an Algorithm in an mHealth Intervention for African American and Hispanic Adults: Survey Study

The Benefits of Crowdsourcing to Seed and Align an Algorithm in an mHealth Intervention for African American and Hispanic Adults: Survey Study

The Benefits of Crowdsourcing to Seed and Align an Algorithm in an mHealth Intervention for African American and Hispanic Adults: Survey Study

Authors of this article:

Neil Jay Sehgal1, 2 Author Orcid Image ;   Shuo Huang1 Author Orcid Image ;   Neil Mason Johnson2, 3 Author Orcid Image ;   John Dickerson2, 3 Author Orcid Image ;   Devlon Jackson2, 4 Author Orcid Image ;   Cynthia Baur2 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Zrubka Z, Champion A, Holtorf A, Di Bidino R, Earla J, Boltyenkov A, Tabata-Kelly M, Asche C, Burrell A. The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report. Value in Health 2024;27(4):383 View
  2. Bucher A, Chaudhry B, Davis J, Lawrence K, Panza E, Baqer M, Feinstein R, Fields S, Huberty J, Kaplan D, Kusters I, Materia F, Park S, Kepper M, Kuo P. How to design equitable digital health tools: A narrative review of design tactics, case studies, and opportunities. PLOS Digital Health 2024;3(8):e0000591 View