Tilaka, Anne Debra, Diederich, Joachim, Song, Insu, Teoh, Ai Ni, and UNSPECIFIED (2014) Automated method for diagnosing speech and language dysfunction in schizophrenia. In: Lech, Margaret, Song, Insu, Yellowlees, Peter, and Diederich, Joachim, (eds.) Mental Health Informatics. Studies in Computational Intelligence, 491 . Springer, Berlin, Germany, pp. 201-215.

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Abstract

Speech and language dysfunction (SLD) is one of the primary symptoms of schizophrenia. However, SLD measures, such as observer-rated scales, are based on clinical experience and are subjective in nature. This study compares two scales—the Thought, Language and Communication Scale (TLC) and the Clinical Language Disorder Rating Scale (CLANG)—with a novel and automated measure called Ex-Ray. The core hypothesis is that Ex-Ray either outperforms the rating scales in terms of accuracy (i.e., differentiating between schizophrenic participants and non-psychotic controls) or performs at the same level. Twenty-minute audio-recorded, unstructured interviews with 54 Singaporean participants (27 schizophrenics and 27 controls) were conducted. The interviews were rated by use of the TLC and CLANG scales. Manually transcribed texts, based on the interviews, were analysed by Ex-Ray. The three methods were then compared. Receiver Operating Characteristic (ROC) curve analysis demonstrated that Ex-Ray differentiated schizophrenic patients from normal subjects with an accuracy rate of 98 %, but did not outperform the scales at a significant level. Even though Ex-Ray is a valid and reliable measure of SLD in schizophrenia, it failed to outperform the rating scales (TLC and CLANG) for two reasons: (1) the unusually high inter-rater reliability; and (2) the uneven ethnic composition of the sample population. In a follow-up study, Ex-Ray performed at a high level even if subject and control groups were comparable in terms of [1] educational background, [2] ethnic composition (including language background) and [3] socio-economic status.

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