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Depressive Symptom Inventory Suicidality Subscale: Optimal Cut Points for Clinical and Non-Clinical Samples.

M von Glischinski1, T Teismann2, S Prinz2

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Clinical Psychology & Psychotherapy
|February 10, 2016
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Summary

This study identified optimal cut points for the Depressive Symptom Inventory Suicidality Subscale (DSI-SS) to improve suicidal ideation detection. These cut points varied across different patient populations, highlighting the need for tailored use of the DSI-SS.

Keywords:
BootstrapCut PointReceiver Operating CharacteristicsSuicide

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Area of Science:

  • Psychiatry
  • Psychometrics
  • Clinical Psychology

Background:

  • Suicide is a significant cause of death, particularly in individuals with mental illnesses.
  • The Depressive Symptom Inventory Suicidality Subscale (DSI-SS) is a key tool for assessing suicidal ideation.
  • Determining optimal cut points for the DSI-SS is crucial for accurate risk assessment.

Purpose of the Study:

  • To establish optimal cut points for the DSI-SS across diverse populations.
  • To enhance the diagnostic utility of the DSI-SS for detecting suicidal ideation.
  • To evaluate the DSI-SS's performance in population-based, outpatient, and inpatient samples.

Main Methods:

  • Analysis of data from three distinct samples: population-based (n=532), outpatient (n=180), and inpatient (n=244).
  • Calculation of internal consistency, convergent validity, and optimal cut points using receiver operating characteristic (ROC) analysis.
  • Bootstrapping analysis to assess variability in optimal cut points.

Main Results:

  • The DSI-SS demonstrated excellent internal consistency and item-total correlations across all samples.
  • Convergent validity was confirmed with moderate to strong positive correlations (0.50-0.67) with related constructs.
  • Optimal cut points varied significantly between the population-based, outpatient, and inpatient samples, with better differentiation in the non-clinical group.

Conclusions:

  • Developed and validated sample-specific cut points for the DSI-SS to improve early and accurate detection of suicidal ideation.
  • The identified optimal cut points varied across different clinical and non-clinical settings.
  • The DSI-SS shows good differentiation in population-based samples but less so in clinical (outpatient and inpatient) settings, suggesting a need for context-specific interpretation.