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.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Small Research Grants (R03)
Project #
1R03MH092622-01
Application #
8028699
Study Section
Adult Psychopathology and Disorders of Aging Study Section (APDA)
Program Officer
Morris, Sarah E
Project Start
2011-02-01
Project End
2012-11-30
Budget Start
2011-02-01
Budget End
2011-11-30
Support Year
1
Fiscal Year
2011
Total Cost
$74,000
Indirect Cost
Name
Louisiana State University A&M Col Baton Rouge
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
075050765
City
Baton Rouge
State
LA
Country
United States
Zip Code
70803
Ecker, Anthony H; Cohen, Alex S; Buckner, Julia D (2017) Overestimation of close friend drinking problems in the prediction of one's own drinking problems. Addict Behav 64:107-110
Le, Thanh P; Najolia, Gina M; Minor, Kyle S et al. (2017) The effect of limited cognitive resources on communication disturbances in serious mental illness. Psychiatry Res 248:98-104
Cohen, Alex S; Mitchell, Kyle R; Docherty, Nancy M et al. (2016) Vocal expression in schizophrenia: Less than meets the ear. J Abnorm Psychol 125:299-309
Cohen, Alex S; Renshaw, Tyler L; Mitchell, Kyle R et al. (2016) A psychometric investigation of ""macroscopic"" speech measures for clinical and psychological science. Behav Res Methods 48:475-86
Cohen, Alex S; Callaway, Dallas A; Mitchell, Kyle R et al. (2016) A temporal examination of co-activated emotion valence networks in schizophrenia and schizotypy. Schizophr Res 170:322-9
Cohen, Alex S; Dinzeo, Thomas J; Donovan, Neila J et al. (2015) Vocal acoustic analysis as a biometric indicator of information processing: implications for neurological and psychiatric disorders. Psychiatry Res 226:235-41
Macaulay, Rebecca; Cohen, Alex (2014) Self-conscious emotions? role in functional outcomes within clinical populations. Psychiatry Res 216:17-23
Cohen, Alex S; Elvevåg, Brita (2014) Automated computerized analysis of speech in psychiatric disorders. Curr Opin Psychiatry 27:203-9
Cohen, Alex S; Auster, Tracey L; MacAulay, Rebecca K et al. (2014) Illusory superiority and schizotypal personality: explaining the discrepancy between subjective/objective psychopathology. Personal Disord 5:413-8
Cohen, Alex S; Mitchell, Kyle R; Elvevåg, Brita (2014) What do we really know about blunted vocal affect and alogia? A meta-analysis of objective assessments. Schizophr Res 159:533-8

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