Diagnosis of Schizophrenia Using Statistical Analysis of Assessment Tools

Nandini Manickam1, Vijayakumar Ponnusamy1,
SRM Institute of Science and Technology,  Kattankulathur, Chengalpattu, Tamil Nadu, India
nm6075@srmist.edu.in
vijayakp@srmist.edu.in
DOI: 10.46793/BISEC25.418M

 

ABSTRACT: Schizophrenia is a severe mental disorder that impacts a person’s thought process, perception, social interaction, and interpersonal relationships. This disorder causes psychosis that makes a person feel disconnected from the real world. There are three types of symptoms, namely positive, negative and cognitive symptoms. Different assessment tools are designed based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-11) in order to assess the severity of symptoms. The Positive and Negative Symptoms Scale (PANSS), Brief Negative Symptom Scale (BNSS), Scale for Assessment of Negative Symptoms (NSA-16), and Scale for Assessment of Positive Symptoms (SAPS) are the evaluation instruments that are used in this paper to identify the symptoms.  Each scale comprises 20 questions related to symptoms, and these are self-report questionnaires. Participant responses are collected from both online and offline modes. Statistical techniques, such as Analysis of Variance (ANOVA), T-test, and Chi-square test, are used to determine the validity and reliability of the data for both healthy controls and individuals with schizophrenia.  The statistical results showed that the validity of the data was measured in terms of p-value for assessment scales. For healthy controls, the p-values for PANSS, SAPS, and BNSS were found to be 0.305, 0.948, and 0.565, respectively. Similarly, for schizophrenia patients, the p-value of PANSS was found to be p=0.007, SAPS was found to be p=0.611, and BNSS was found to be p=0.637. The validity data from schizophrenia patients for PANSS alone revealed a significant difference since the p-value was <0.05, whereas there was no significant difference in the remaining scales. Though this approach has proven to be promising in identifying the severity of symptoms, it can still be enhanced by combining a statistical approach with multimodal data for better performance.

KEYWORDS: Reliability of data, Schizophrenia, Severity of symptoms, Statistical analysis, Validity of data.

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