The Role of Complex Emotions in Inconsistent Diagnoses of Schizophrenia

Department of Psychiatry, UMDNJ-University Behavioral HealthCare and Robert Wood Johnson Medical School, Piscataway, NJ 08855-1392, USA.
The Journal of nervous and mental disease (Impact Factor: 1.69). 09/2010; 198(9):609-13. DOI: 10.1097/NMD.0b013e3181e9dca9
Source: PubMed


In the case of large-scale epidemiological studies, there is evidence of substantial disagreement when lay diagnoses of schizophrenia based on structured interviews are compared with expert diagnoses of the same patients. Reasons for this level of disagreement are investigated in the current study, which made use of advances in text-mining techniques and associated structural representations of language expressions. Specifically, the current study examined whether content analyses of transcribed diagnostic interviews obtained from 150 persons with serious psychiatric disorders yielded any discernable patterns that correlated with diagnostic inconsistencies of schizophrenia. In summary, it was found that the patterning or structure of spontaneous self-reports of emotion states in the diagnostic interview was associated with diagnostic inconsistencies of schizophrenia, irrespective of confounders; i.e., age of patient, gender, or ethnicity. In particular, complex emotion patterns were associated with greater disagreement between experts and trained lay interviewers than were simpler patterns.

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    • "For example, Chung and Pennebaker (2008) identified dimensions of people thinking about themselves by developing an automated meaning extraction method for natural language . Gara et al. (2010) investigated the reasons for disagreement in schizophrenia diagnosis by mining the textual transcripts of structured interviews. "
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    ABSTRACT: Much evidence has shown that people's physical and mental health can be predicted by the words they use. However, such verbal information is seldom used in the screening and diagnosis process probably because the procedure to handle these words is rather difficult with traditional quantitative methods. The first challenge would be to extract robust information from diversified expression patterns, the second to transform unstructured text into a structuralized dataset. The present study developed a new textual assessment method to screen the posttraumatic stress disorder (PTSD) patients using lexical features in the self narratives with text mining techniques. Using 300 self narratives collected online, we extracted highly discriminative keywords with the Chi-square algorithm and constructed a textual assessment model to classify individuals with the presence or absence of PTSD. This resulted in a high agreement between computer and psychiatrists' diagnoses for PTSD and revealed some expressive characteristics in the writings of PTSD patients. Although the results of text analysis are not completely analogous to the results of structured interviews in PTSD diagnosis, the application of text mining is a promising addition to assessing PTSD in clinical and research settings.
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    • "It is only recently that researchers have begun to examine the clinical and practical signifi cance of different emotions, such as fear, as a behaviour problem in children and adolescents, and to consider these problems as potential indicators of more long-term diffi culties whilst recognizing the developmental and theoretical implications of problem behaviour to school entry and education (Akande & Akande, 1994; Akande, 1997; Holland , Tamir & Kensinger, 2010; Yang et al., 2007). A growing body of prospective evidence indicates that fears identifi ed in the pre-school years often persist and that adolescents identifi ed as performing poorly in school work often have a history of problems that began in the pre-school years emanating from prevailing emotional climate (Akande & Akande, 1994; Akande, Akande & Odewale, 1994; Chaplin, Casey, Sinha, & Mayes, 2010; Gara et al., 2010). "
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    ABSTRACT: Given the history of the past, black South African students from different settings face unique academic and emotional climate. Using the Differential Emotions Scale (DES) which focuses on ten discrete emotions, and building upon Boyle's (1984) seminal work, this study reports a repeated-measure multiple discriminant function analysis for individual items across raters. The findings further indicate that majority of the DES items are sensitive indicators of the different innate and universal facial expressions. However, the construct requires revision so that it offers the examiner maximum flexibility in assessment at diverse levels, in terms of more extensive norming and programmatic replication. In brief, the DES potentially has much to offer provided that it is adequately developed for use in non-Western nations or contexts.
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