Negative symptoms reflect one of the gravest sources of debilitation in schizophrenia. Despite thousands of empirical studies examining negative symptoms to date, our understanding of their nature is very poor and we lack any FDA-approved strategies for treating them. One major constraint for understanding negative symptoms involves a current dependence on symptom rating scales for their assessment. This assessment method offers insufficient resolution for measuring specific negative symptoms and for tracking their severity over time. To address this concern, our group has developed a protocol for measuring cardinal negative symptoms using acoustic analysis of natural speech. Preliminary research suggests that this protocol is promising for identifying negative symptoms in both patients with the disorder and in individuals with a putative-genetic vulnerability for developing the disorder. However, the measures employed in this protocol are based on broad speech markers and recent advances in speech analysis have paved the way for a much more sophisticated approach. The proposed project will adopt techniques from contemporary communication sciences to schizophrenia research by analyzing a large, archived set of speech samples procured from our prior research. We are testing six new markers of vocal deficits that map onto symptoms of blunt affect, alogia and amotivation. We propose to examine the convergent validity of these novel variables by examining vocal deficits in patients with clinically-rated negative symptoms, patients without and healthy controls. To determine the degree to which these novel measures reflect vulnerability markers of liability to negative schizophrenia, we will also compare them in individuals with psychometrically-defined negative schizotypy, those without and healthy controls. We will also compare the novel acoustic-based measures to existing acoustic-based ones to determine their degree of added valuation. As a set of exploratory analyses, we will examine the relationship between our novel acoustic-based measures and """"""""real world"""""""" social functioning. Advancing the technological capability of negative symptom measurement has critical implications for improving the lives of individuals afflicted with schizophrenia. The results from this project will advance the use of computerized technologies for understanding negative symptoms by revealing their optimal acoustic-based measures. The fruits of the proposed project are critical for the implementation of our long range research plan to develop a manualized protocol for evaluating negative symptoms using shareware software. The insights from this line of research will have a wide range of applications, for example, to allow for sensitive outcome measures for pharmacology trials and psychosocial rehabilitation programs, for efficient and standardized clinical monitoring of negative symptoms, for advancing telepsychiatry, and for studies focusing on elucidating the pathological underpinnings of negative symptoms more generally.
This proposed project will advance a line of research to develop computer-based, objective technology to measure the most crippling symptoms of one of the most severe mental illnesses - schizophrenia. It is hoped that insights from this project will lead to the development of automated assessments that can be applied to both clinical and research settings as a cost-effective and highly sensitive assessment of key symptoms.
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