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The self-directed violence classification system and the columbia classification algorithm for suicide assessment: a
Bridget B Matarazzo1, Tracy A Clemans, Morton M Silverman
1Veteran Integrated Service Network 19 Mental Illness Research, Education and Clinical Center, Denver, CO 80220, USA. Bridget.Matarazzo@va.gov
Suicide & Life-Threatening Behavior
|November 14, 2012
Summary
This study bridges two suicide assessment systems: the Self-Directed Violence Classification System (SDVCS) and the Columbia Classification Algorithm for Suicide Assessment. It offers a crosswalk to improve suicide risk evaluation and clinical practice.
Area of Science:
- Mental Health Research
- Clinical Psychology
- Public Health Surveillance
Background:
- Standardized nomenclature for suicide-related thoughts and behaviors is lacking.
- The Centers for Disease Control and Prevention developed the Self-Directed Violence Classification System (SDVCS).
- The Columbia Classification Algorithm for Suicide Assessment is FDA-recommended.
Purpose of the Study:
- To create a crosswalk between the SDVCS and the Columbia Classification Algorithm for Suicide Assessment.
- To facilitate the adoption and use of both classification systems.
- To enhance consistency in suicide risk assessment.
Main Methods:
- Comparative analysis of the two classification systems.
- Development of a mapping tool (crosswalk) between SDVCS and Columbia Algorithm.
- Review of existing literature and system documentation.
Main Results:
- A comprehensive crosswalk detailing the correspondence between SDVCS and Columbia Algorithm criteria.
- Identification of areas of overlap and divergence between the systems.
- Facilitation of data integration and comparative research.
Conclusions:
- The developed crosswalk enhances the utility of both SDVCS and the Columbia Algorithm.
- Improved standardization in suicide risk assessment can be achieved.
- This facilitates research and clinical practice in suicide prevention.
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