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Suicide risk prediction by computer interview: a prospective study.

H P Erdman1, J H Greist, D H Gustafson

  • 1Department of Psychiatry, University of Wisconsin, Madison.

The Journal of Clinical Psychiatry
|December 1, 1987
PubMed
Summary
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A computer program using Bayesian probability was evaluated for suicide risk assessment. While clinicians excelled at predicting non-attempters, the computer program demonstrated superior accuracy in identifying potential suicide attempters.

Area of Science:

  • Psychiatry
  • Computer Science
  • Risk Assessment

Background:

  • Suicide risk assessment is crucial in clinical practice.
  • Subjective Bayesian probability models offer a quantitative approach to risk evaluation.
  • Comparing computational models with clinical judgment is essential for improving diagnostic tools.

Purpose of the Study:

  • To evaluate a computer interview program employing a subjective Bayesian probability model for suicide risk assessment.
  • To compare the predictive accuracy of the computer program against that of clinicians.

Main Methods:

  • A computer program utilizing a subjective Bayesian probability model was developed.
  • Predictions for suicide risk were made by both the computer program and clinicians for 52 patients.

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  • Statistical analysis, including receiver operating characteristic (ROC) curve analysis, was used for comparison.

    • Main Results:

    • The computer program was significantly more accurate in predicting suicide attempters (p = .001).
    • Clinicians were significantly more accurate in predicting non-attempters (p = .01).
    • ROC curve analysis indicated better overall discrimination by the computer, though the difference was not statistically significant.

    Conclusions:

    • The computer program shows promise as a tool for identifying suicide attempters.
    • Clinicians remain valuable for identifying individuals at lower suicide risk.
    • Further research may refine computational models for comprehensive suicide risk assessment.