Use of non-parametric item response theory to develop a shortened version of the Positive and Negative Syndrome Scale (PANSS) for patients with schizophrenia

Anzalee Khan, Fordham University

Abstract

Nonparametric item response theory (IRT) was used to examine (a) the performance of individual Positive and Negative Syndrome Scale (PANSS) items and their options, (b) the effectiveness of various subscales to discriminate among individual differences in symptom severity, and (c) the development of an abbreviated version of the PANSS (Mini-PANSS) linking scores on the original PANSS. Option characteristic curves (OCCs) and Item Characteristic Curves (ICCs) were estimated to examine the probability of rating each of seven options within each of 30 PANSS items as a function of subscale severity, and summed-score linking was applied to items selected for the Mini-PANSS. Data were baseline PANSS scores from 7187 patients with Schizophrenia or Schizoaffective disorder who were enrolled between 1995 and 2005 in clinical trials. Results show that the majority of items forming the Positive and Negative subscales perform very well and better discriminate along symptoms severity compared to the General Psychopathology subscale. Six of the seven Positive Symptom items, six of the seven Negative Symptom items, and seven out of the 16 General Psychopathology items were selected for inclusion in the Mini-PANSS. Summed score linking and linear interpolation was able to produce a translation table for comparing total subscale scores on the Mini-PANSS to total subscale scores on the original PANSS. Results show scores on the subscales of the Mini-PANSS can be linked to scores on the original PANSS subscales with very little bias.

Subject Area

Statistics|Clinical psychology|Quantitative psychology

Recommended Citation

Khan, Anzalee, "Use of non-parametric item response theory to develop a shortened version of the Positive and Negative Syndrome Scale (PANSS) for patients with schizophrenia" (2010). ETD Collection for Fordham University. AAI3438465.
https://research.library.fordham.edu/dissertations/AAI3438465

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