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

Formative Evaluation of Digital Health Interventions (2396) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1509) Text-messaging (SMS, WeChat etc)-Based Interventions (650) Users' and Patients' Needs for Mental Health Services (402) Methods and New Tools in Mental Health Research (452) Anxiety and Stress Disorders (1047) Depression and Mood Disorders; Suicide Prevention (1358)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33036, first published .
Predicting Mental Health Status in Remote and Rural Farming Communities: Computational Analysis of Text-Based Counseling

Predicting Mental Health Status in Remote and Rural Farming Communities: Computational Analysis of Text-Based Counseling

Predicting Mental Health Status in Remote and Rural Farming Communities: Computational Analysis of Text-Based Counseling

Authors of this article:

Mark Antoniou1 Author Orcid Image ;   Dominique Estival1 Author Orcid Image ;   Christa Lam-Cassettari1 Author Orcid Image ;   Weicong Li1 Author Orcid Image ;   Anne Dwyer1 Author Orcid Image ;   Abìlio de Almeida Neto2 Author Orcid Image
Article Authors Cited by (2) Tweetations (16) Metrics

Journals

  1. Corbin L, Griner E, Seyedi S, Jiang Z, Roberts K, Boazak M, Bahrami Rad A, Clifford G, Cotes R. A comparison of linguistic patterns between individuals with current major depressive disorder, past major depressive disorder, and controls in a virtual, psychiatric research interview. Journal of Affective Disorders Reports 2023;14:100645 View
  2. Li W, Tang L, Montayre J, Harris C, West S, Antoniou M. Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data. Journal of Medical Internet Research 2024;26:e49450 View