Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48496, first published .
A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

Pascale Lehoux   1 , PhD ;   Robson Rocha de Oliveira   2 , MD, PhD ;   Lysanne Rivard   2 , PhD ;   Hudson Pacifico Silva   2 , PhD ;   Hassane Alami   3 , PhD ;   Carl Maria Mörch   4 , MPsy, PhD ;   Kathy Malas   5 , MPO, GCHlthMgt

1 Department of Health Management, Evaluation and Policy, Université de Montréal; Center for Public Health Research, Montréal, QC, Canada

2 Center for Public Health Research, Université de Montréal, Montréal, QC, Canada

3 Interdisciplinary Research in Health Sciences, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom

4 AI for the Common Good Institute, Université Libre de Bruxelles, Bruxelles, Belgium

5 Innovation and Artificial Intelligence, Executive Office, Centre hospitalier de l’Université de Montréal, Montréal, QC, Canada

Corresponding Author:

  • Pascale Lehoux, PhD
  • Department of Health Management, Evaluation and Policy, Université de Montréal; Center for Public Health Research
  • 7101, Avenue du Parc
  • Montréal, QC, H3N 1X9
  • Canada
  • Phone: 1 5143437978
  • Email: pascale.lehoux@umontreal.ca