Using machine learning to increase access to and engagement with trauma-focused interventions for posttraumatic stress disorder.

Journal: The British journal of clinical psychology
Published Date:

Abstract

BACKGROUND: Post-traumatic stress disorder (PTSD) poses a global public health challenge. Evidence-based psychotherapies (EBPs) for PTSD reduce symptoms and improve functioning (Forbes et al., Guilford Press, 2020, 3). However, a number of barriers to access and engagement with these interventions prevail. As a result, the use of EBPs in community settings remains disappointingly low (Charney et al., Psychological Trauma: Theory, Research, Practice, and Policy, 11, 2019, 793; Richards et al., Community Mental Health Journal, 53, 2017, 215), and not all patients who receive an EBP for PTSD benefit optimally (Asmundson et al., Cognitive Behaviour Therapy, 48, 2019, 1). Advancements in artificial intelligence (AI) have introduced new possibilities for increasinfg access to and quality of mental health interventions.

Authors

  • Ariella P Lenton-Brym
    Nellie Health.
  • Alexis Collins
    Nellie Health.
  • Jeanine Lane
    Toronto Metropolitan University, Toronto, Ontario, Canada.
  • Carlos Busso
  • Jessica Ouyang
    University of Texas at Dallas, Richardson, Texas, USA.
  • Skye Fitzpatrick
    Nellie Health.
  • Janice R Kuo
    Nellie Health.
  • Candice M Monson
    Nellie Health.