P473. Estimating Self-Disturbance in Psychosis and Its Risk States Using Natural Language Processing Analysis of Open-Ended Interviews

Angela Lu,Riaz Shaik,Zarina Bilgrami,Agrima Srivastava,Barnaby Nelson,Alessia Mcgowan,Romina Mizrahi,Cheryl Corcoran,Shaynna Herrera,Guillermo Cecchi,Cansu Sarac,Avner Abrami,Shalaila Haas

doi:10.1016/j.biopsych.2022.02.709

P473. Estimating Self-Disturbance in Psychosis and Its Risk States Using Natural Language Processing Analysis of Open-Ended Interviews

Angela Lu, Riaz Shaik + Show 11 more

https://doi.org/10.1016/j.biopsych.2022.02.709

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Journal: Biological Psychiatry

Publication Date: Apr 28, 2022

Affiliation: Icahn School of Medicine at Mount Sinai, Orygen Youth Health, Centre for Addiction and Mental Health, IBM (United States)

#Inventory Of Psychotic-Like Anomalous Self-Experiences #Disturbances In Sense Of Self + Show 8 more

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Abstract

Schizophrenia is characterized by disturbances in sense of self (ipseity) and heightened awareness of experiences normally tacit or implicit (hyperreflexivity), typically measured using the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) clinical rating scale. Natural language processing (NLP) analyses of spoken language may capture report of these self-disturbances in psychosis and its risk states.

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