101. Wisconsin Card Sorting Test scores and clinical and sociodemographic correlates in Schizophrenia: multiple logistic regression analysis
- Author
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Naoko Kawano, Tetsuya Iidaka, Takashi Okada, Takayoshi Koide, Tsutomu Kikuchi, Yasunori Adachi, Kunihiro Kohmura, Norio Ozaki, Branko Aleksic, and Masahiro Banno
- Subjects
medicine.medical_specialty ,Positive and Negative Syndrome Scale ,business.industry ,Research ,General Medicine ,medicine.disease ,behavioral disciplines and activities ,Mental health ,Substance abuse ,Mental Health ,Wisconsin Card Sorting Test ,Mood disorders ,Schizophrenia ,Test score ,medicine ,Age of onset ,Psychiatry ,business - Abstract
Objectives This study investigated what clinical and sociodemographic factors affected Wisconsin Card Sorting Test (WCST) factor scores of patients with schizophrenia to evaluate parameters or items of the WCST. Design Cross-sectional study. Setting Patients with schizophrenia from three hospitals participated. Participants Participants were recruited from July 2009 to August 2011. 131 Japanese patients with schizophrenia (84 men and 47 women, 43.5±13.8 years (mean±SD)) entered and completed the study. Participants were recruited in the study if they (1) met DSM-IV criteria for schizophrenia; (2) were physically healthy and (3) had no mood disorders, substance abuse, neurodevelopmental disorders, epilepsy or mental retardation. We examined their basic clinical and sociodemographic factors (sex, age, education years, age of onset, duration of illness, chlorpromazine equivalent doses and the positive and negative syndrome scale (PANSS) scores). Primary and secondary outcome measures All patients carried out the WCST Keio version. Five indicators were calculated, including categories achieved (CA), perseverative errors in Milner (PEM) and Nelson (PEN), total errors (TE) and difficulties of maintaining set (DMS). From the principal component analysis, we identified two factors (1 and 2). We assessed the relationship between these factor scores and clinical and sociodemographic factors, using multiple logistic regression analysis. Results Factor 1 was mainly composed of CA, PEM, PEN and TE. Factor 2 was mainly composed of DMS. The factor 1 score was affected by age, education years and the PANSS negative scale score. The factor 2 score was affected by duration of illness. Conclusions Age, education years, PANSS negative scale score and duration of illness affected WCST factor scores in patients with schizophrenia. Using WCST factor scores may reduce the possibility of type I errors due to multiple comparisons.
- Published
- 2012