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Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior.
Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J.
Afiliación
  • Delgado-Gomez D; Department of Statistics, Carlos III University, Madrid, Spain.
  • Baca-Garcia E; Department of Psychiatry, IIS-Jimenez Diaz Foundation, CIBERSAM, Madrid, Spain; Department of Psychiatry, Columbia University/New York State Psychiatric Institute, New York, United States.
  • Aguado D; Instituto Ingeniería del Conocimiento, Autonoma University of Madrid, Madrid, Spain.
  • Courtet P; CHRU Montpellier and University of Montpellier, France; INSERM Unit 1061, Montpellier, France.
  • Lopez-Castroman J; INSERM Unit 1061, Montpellier, France; CHU Nimes and University of Montpellier, France. Electronic address: jorgecastroman@gmail.com.
J Affect Disord ; 206: 204-209, 2016 Dec.
Article en En | MEDLINE | ID: mdl-27475891
BACKGROUND: Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. METHODS: Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. RESULTS: The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CONCLUSION: CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escalas de Valoración Psiquiátrica / Intento de Suicidio / Árboles de Decisión / Ideación Suicida / Trastornos Mentales Tipo de estudio: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Affect Disord Año: 2016 Tipo del documento: Article País de afiliación: España Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escalas de Valoración Psiquiátrica / Intento de Suicidio / Árboles de Decisión / Ideación Suicida / Trastornos Mentales Tipo de estudio: Diagnostic_studies / Etiology_studies / Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Affect Disord Año: 2016 Tipo del documento: Article País de afiliación: España Pais de publicación: Países Bajos