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Predicting Participation in a Post-disaster Mental Health Program.

David Crompton1,2, Peter Kohleis3, Jane Shakespeare-Finch1

  • 1Queensland University of Technology, Brisbane, Queensland, Australia.

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|November 18, 2024
PubMed
Summary

Factors like perceived threat, property damage, and financial loss predict post-disaster mental health treatment seeking for those at risk of post-traumatic stress disorder (PTSD).

Keywords:
classification tree analysisprediction of participating in a specialist post disaster mental health programspecialist mental health program

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Area of Science:

  • Disaster mental health
  • Psychotraumatology
  • Public health

Background:

  • Natural disasters can lead to significant psychological distress, including post-traumatic stress disorder (PTSD).
  • Identifying individuals at risk and predicting their engagement with mental health services is crucial for effective post-disaster support.
  • Previous research has explored risk factors for PTSD, but less is known about predictors of treatment seeking in affected populations.

Purpose of the Study:

  • To identify pre- and post-disaster factors that predict the likelihood of individuals at risk for PTSD entering a clinical treatment program.
  • To understand the characteristics distinguishing individuals who seek treatment from those who do not after a natural disaster.

Main Methods:

  • A retrospective naturalistic evaluation of 881 individuals referred to a post-disaster treatment program following the Queensland, Australia, natural disasters (2010-11).
  • Intake data included the Primary Care PTSD scale (score >2), disaster exposure, demographics, clinical information, coping, and resilience measures.
  • Classification Tree Analysis (CTA) was used to identify predictive factors for treatment participation.

Main Results:

  • Individuals in the treatment group were more likely to perceive their life was threatened (85.1% vs 8.1%), less able to cope (67% vs 25.8%), and less resilient (4.2% vs 87.5%) compared to the non-treatment group.
  • Key predictors for treatment participation identified by CTA included the Connor-Davidson scale, property damage, financial losses, perceived life threat, and insurance claims.

Conclusions:

  • Specific pre- and post-disaster factors significantly differentiate individuals who participate in mental health treatment from those who do not.
  • These findings can inform targeted outreach and support strategies for populations affected by natural disasters to improve mental health service engagement.