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

Mark Antoniou   1 , PhD ;   Dominique Estival   1 , PhD ;   Christa Lam-Cassettari   1 , PhD ;   Weicong Li   1 , PhD ;   Anne Dwyer   1 , PhD ;   Abìlio de Almeida Neto   2 , PhD

1 The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, Australia

2 Centre for Work Health and Safety, New South Wales Government, Gosford, Australia

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