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

Formative Evaluation of Digital Health Interventions (2823) Data Science (306) Machine Learning (1738) mHealth for Data Collection and Research (1082) Methods and New Tools in Mental Health Research (499)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34366, first published .
Fairness in Mobile Phone–Based Mental Health Assessment Algorithms: Exploratory Study

Fairness in Mobile Phone–Based Mental Health Assessment Algorithms: Exploratory Study

Fairness in Mobile Phone–Based Mental Health Assessment Algorithms: Exploratory Study

Authors of this article:

Jinkyung Park1 Author Orcid Image ;   Ramanathan Arunachalam2 Author Orcid Image ;   Vincent Silenzio3 Author Orcid Image ;   Vivek K Singh1, 4 Author Orcid Image
Article Authors Cited by (13) Tweetations (3) Metrics

Journals

  1. Gallifant J, Griffin M, Pierce R, Celi L. From quality improvement to equality improvement projects: A scoping review and framework. iScience 2023;26(10):107924 View
  2. Ferrara E. Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies. SSRN Electronic Journal 2023 View
  3. Ferrara E. Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies. Sci 2023;6(1):3 View
  4. Khoo L, Lim M, Chong C, McNaney R. Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches. Sensors 2024;24(2):348 View
  5. Adams J. Examining Ethical and Social Implications of Digital Mental Health Technologies Through Expert Interviews and Sociotechnical Systems Theory. Digital Society 2024;3(2) View
  6. Jiang Z, Seyedi S, Griner E, Abbasi A, Rad A, Kwon H, Cotes R, Clifford G, McGinnis R. Evaluating and mitigating unfairness in multimodal remote mental health assessments. PLOS Digital Health 2024;3(7):e0000413 View
  7. Sasseville M, Ouellet S, Rhéaume C, Sahlia M, Couture V, Després P, Paquette J, Darmon D, Bergeron F, Gagnon M. Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review. Journal of Medical Internet Research 2025;27:e60269 View
  8. Colacci M, Huang Y, Postill G, Zhelnov P, Fennelly O, Verma A, Straus S, Tricco A. Sociodemographic bias in clinical machine learning models: a scoping review of algorithmic bias instances and mechanisms. Journal of Clinical Epidemiology 2025;178:111606 View
  9. Kraft S, Chopra S, Duran M, Rojina J, Beretta A, López K, Javan R, Wilfond B, Rosenfeld M, Fogarty J, Ko L. Perspectives of Hispanic and Latinx Community Members on AI-Enabled mHealth Tools: Qualitative Focus Group Study. Journal of Medical Internet Research 2025;27:e59817 View
  10. El-Sappagh S, Nazih W, Alharbi M, Abuhmed T. Responsible Artificial Intelligence for Mental Health Disorders: Current Applications and Future Challenges. Journal of Disability Research 2025;4(1) View
  11. Baird A, Xia Y. Applying analytics to sociodemographic disparities in mental health. Nature Mental Health 2025;3(1):124 View

Conference Proceedings

  1. Cheong J, Spitale M, Gunes H. 2023 11th International Conference on Affective Computing and Intelligent Interaction (ACII). “It’s not Fair!” – Fairness for a Small Dataset of Multi-modal Dyadic Mental Well-being Coaching View
  2. Cameron J, Cheong J, Spitale M, Gunes H. 2024 12th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). Multimodal Gender Fairness in Depression Prediction: Insights on Data from the USA & China View