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[Suicidality in adults].

Remco de Winter1,2, Derek de Beurs3

  • 1GGZ Rivierduinen, Leiden.

Nederlands Tijdschrift Voor Geneeskunde
|August 5, 2020
PubMed
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Economic factors influence suicide rates, particularly in Dutch men over the past decade. Emerging technologies like big data and machine learning may improve future prediction and tailored prevention strategies for suicidality.

Area of Science:

  • Public Health
  • Mental Health Research
  • Sociology

Background:

  • Suicide rates exhibit economic influence, with recent fluctuations primarily observed in men in the Netherlands.
  • The COVID-19 pandemic is anticipated to negatively affect these trends.
  • Current prediction of suicidality lacks reliability, necessitating advancements in the field.

Purpose of the Study:

  • To explore the complex, multifactorial nature of suicidality beyond traditional mental healthcare.
  • To highlight emerging technological and methodological approaches for improved prediction and understanding of suicide.
  • To emphasize the need for differentiated treatment and prevention strategies for suicidality.

Main Methods:

  • Review of economic influences on suicide rates.

Related Experiment Videos

  • Discussion of 'big data' and 'machine learning' applications.
  • Exploration of network approaches to model psychopathology as a dynamic system.

    • Main Results:

    • Economic factors significantly impact suicide rates, especially in men.
    • Technological advancements offer potential for more accurate suicidality prediction.
    • A complex systems approach to psychopathology is being developed.

    Conclusions:

    • Suicidality is a complex issue requiring a multifaceted approach.
    • Improved prediction models can enhance clinical practice for tailored interventions.
    • Collaborative efforts, such as those by the 113 foundation, are crucial for suicide prevention.