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

Clinical Information and Decision Making (1407) Depression and Mood Disorders; Suicide Prevention (1363) Artificial Intelligence (1371) Machine Learning (1465) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (36) Machine Learning (49) mHealth for Wellness, Behavior Change and Prevention (2871) New Methods (944)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53562, first published .
Automated Behavioral Coding to Enhance the Effectiveness of Motivational Interviewing in a Chat-Based Suicide Prevention Helpline: Secondary Analysis of a Clinical Trial

Automated Behavioral Coding to Enhance the Effectiveness of Motivational Interviewing in a Chat-Based Suicide Prevention Helpline: Secondary Analysis of a Clinical Trial

Automated Behavioral Coding to Enhance the Effectiveness of Motivational Interviewing in a Chat-Based Suicide Prevention Helpline: Secondary Analysis of a Clinical Trial

Authors of this article:

Mathijs Pellemans1, 2 Author Orcid Image ;   Salim Salmi2, 3 Author Orcid Image ;   Saskia Mérelle2, 4 Author Orcid Image ;   Wilco Janssen2, 4 Author Orcid Image ;   Rob van der Mei1, 3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Mathijs Pellemans   1, 2 , MSc ;   Salim Salmi   2, 3 , MSc ;   Saskia Mérelle   2, 4 , PhD ;   Wilco Janssen   2, 4 , MSc ;   Rob van der Mei   1, 3 , PhD

1 Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

2 113 Suicide Prevention, Amsterdam, Netherlands

3 Centrum Wiskunde & Informatica, Amsterdam, Netherlands

4 Department of Psychiatry, Amsterdam UMC, Amsterdam, Netherlands

Corresponding Author:

  • Mathijs Pellemans, MSc
  • Department of Mathematics
  • Vrije Universiteit Amsterdam
  • De Boelelaan 1111
  • Amsterdam, 1081 HV
  • Netherlands
  • Phone: 31 20 5987700
  • Email: m.j.pellemans@vu.nl