Though computational linguistic analyses have revealed the presence of distinctly characteristic language features in schizophrenic disordered speech, the relative stability of these language features in longitudinal samples is still unknown. This longitudinal pilot study analyzed schizophrenic disordered speech data from the archival therapy audio recordings of one patient spanning 23 years. End-to-end Neural Coreference Resolution software was used to analyze transcribed speech data from three therapy sessions to identify ambiguous pronouns, referred to as referential failures, which were reviewed and confirmed by multiple raters. Speech samples were analyzed using Google Cloud Natural Language API software for sentiment variables (i.e., score, valence, and magnitude). Referential failures and sentiment variables were analyzed within each session and all sessions combined to study the relationships between these variables within single sessions and over a span of 23 years. Results and implications for this study are discussed.
","abstract_html":"<p>Though computational linguistic analyses have revealed the presence of distinctly characteristic language features in schizophrenic disordered speech, the relative stability of these language features in longitudinal samples is still unknown. This longitudinal pilot study analyzed schizophrenic disordered speech data from the archival therapy audio recordings of one patient spanning 23 years. End-to-end Neural Coreference Resolution software was used to analyze transcribed speech data from three therapy sessions to identify ambiguous pronouns, referred to as referential failures, which were reviewed and confirmed by multiple raters. Speech samples were analyzed using Google Cloud Natural Language API software for sentiment variables (i.e., score, valence, and magnitude). Referential failures and sentiment variables were analyzed within each session and all sessions combined to study the relationships between these variables within single sessions and over a span of 23 years. Results and implications for this study are discussed.</p>","abstract_has_math":false,"creators":["Musich, Travis A"],"institution":null,"degree_name":"Psy.D. Doctor of Clinical Psychology","degree_level":"Dissertation - Public Access","degree_discipline":"Clinical Psychology","degree_department":null,"school":null,"contributors":["Margaret S. Warner, PhD","Emese Vitalis, PhD","Jin Wu, PsyD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-04-01T07:00:00Z","date_published":"2023-04-01T07:00:00Z","updated_at":"2026-07-24T03:21:12Z","subjects":["schizophrenic disordered speech","formal thought disorder","affective reactivity","referential failures","sentiment analysis","longitudinal","Clinical Psychology","Computational Linguistics","Diagnosis","Mental Disorders","Psychiatric and Mental Health","Psychoanalysis and Psychotherapy","Psycholinguistics and Neurolinguistics","Psychological Phenomena and Processes"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.nl.edu/diss/726","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Margaret S. Warner, PhD","Emese Vitalis, PhD","Jin Wu, PsyD"]},{"key":"dc:creator","label":"Author","values":["Musich, Travis A"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2023-04-07T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Clinical Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation - Public Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Psy.D. Doctor of Clinical Psychology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["schizophrenic disordered speech","formal thought disorder","affective reactivity","referential failures","sentiment analysis","longitudinal","Clinical Psychology","Computational Linguistics","Diagnosis","Mental Disorders","Psychiatric and Mental Health","Psychoanalysis and Psychotherapy","Psycholinguistics and Neurolinguistics","Psychological Phenomena and Processes"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.nl.edu/diss/726"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Though computational linguistic analyses have revealed the presence of distinctly characteristic language features in schizophrenic disordered speech, the relative stability of these language features in longitudinal samples is still unknown. This longitudinal pilot study analyzed schizophrenic disordered speech data from the archival therapy audio recordings of one patient spanning 23 years. End-to-end Neural Coreference Resolution software was used to analyze transcribed speech data from three therapy sessions to identify ambiguous pronouns, referred to as referential failures, which were reviewed and confirmed by multiple raters. Speech samples were analyzed using Google Cloud Natural Language API software for sentiment variables (i.e., score, valence, and magnitude). Referential failures and sentiment variables were analyzed within each session and all sessions combined to study the relationships between these variables within single sessions and over a span of 23 years. Results and implications for this study are discussed.
"]},{"key":"dc:title","label":"Title","values":["Single-Case Pilot Study For Longitudinal Analysis Of Referential Failures And Sentiment In Schizophrenic Speech From Client-Centered Psychotherapy Recordings"]}]}],"canonical_facts":{"dc:contributor":["Margaret S. Warner, PhD","Emese Vitalis, PhD","Jin Wu, PsyD"],"dc:creator":["Musich, Travis A"],"dc:date.available":["2023-04-07T07:00:00Z"],"dc:description.abstract":["Though computational linguistic analyses have revealed the presence of distinctly characteristic language features in schizophrenic disordered speech, the relative stability of these language features in longitudinal samples is still unknown. This longitudinal pilot study analyzed schizophrenic disordered speech data from the archival therapy audio recordings of one patient spanning 23 years. End-to-end Neural Coreference Resolution software was used to analyze transcribed speech data from three therapy sessions to identify ambiguous pronouns, referred to as referential failures, which were reviewed and confirmed by multiple raters. Speech samples were analyzed using Google Cloud Natural Language API software for sentiment variables (i.e., score, valence, and magnitude). Referential failures and sentiment variables were analyzed within each session and all sessions combined to study the relationships between these variables within single sessions and over a span of 23 years. Results and implications for this study are discussed.
"],"dc:identifier":["https://digitalcommons.nl.edu/diss/726"],"dc:subject":["schizophrenic disordered speech","formal thought disorder","affective reactivity","referential failures","sentiment analysis","longitudinal","Clinical Psychology","Computational Linguistics","Diagnosis","Mental Disorders","Psychiatric and Mental Health","Psychoanalysis and Psychotherapy","Psycholinguistics and Neurolinguistics","Psychological Phenomena and Processes"],"dc:title":["Single-Case Pilot Study For Longitudinal Analysis Of Referential Failures And Sentiment In Schizophrenic Speech From Client-Centered Psychotherapy Recordings"],"thesis:degree_discipline":["Clinical Psychology"],"thesis:degree_level":["Dissertation - Public Access"],"thesis:degree_name":["Psy.D. Doctor of Clinical Psychology"]},"updated_at":"2026-07-24T03:21:12Z"}