@article{vonGlischinskiTeismannPrinzetal.2016,
  author    = {Michael von Glischinski and Tobias Teismann and S. Prinz and Jochen E. Gebauer and Gerrit Hirschfeld},
  title     = {Depressive Symptom Inventory Suicidality Subscale : Optimal Cut Points for Clinical and Non-Clinical Samples},
  series   = {Clinical Psychology and Psychotherapy},
  volume    = {29},
  number    = {6},
  issn      = {1099-0879},
  doi       = {10.1002/cpp.2007},
  pages     = {543 -- 549},
  year      = {2016},
  abstract  = {Suicide is a major cause of death in adulthood and specifically in patients suffering from mental illnesses. The Depressive Symptom Inventory Suicidality Subscale (DSI-SS) is widely used to detect and prevent suicidal ideation. The aim of the present study was to determine optimal cut points for the DSI-SS in different populations. We analysed the data of one population-based sample (n = 532), one outpatient sample (n = 180) and one inpatient sample (n = 244). Internal consistency, convergent validity and optimal cut points according to receiver operating characteristics were calculated. In all samples, we found excellent item-total correlations and internal consistencies for the DSI-SS. Zero-order correlations between the DSI-SS and theoretically related constructs showed positive correlation coefficients, ranging from 0.50 to 0.67. The DSI-SS differentiated well between patients with and without suicide attempts in the population-based sample, but less so in the inpatient sample and only marginally in the outpatient sample. A bootstrapping analysis showed some variability in the cut points that emerged as optimal, but there was no overlap between the different samples. The specific cut points that we identified may be used to improve the diagnostic utility of the DSI-SS and the chance to detect suicidal ideation.},
  language  = {en}
}