Literature DB >> 29692287

Measuring disorganized speech in schizophrenia: automated analysis explains variance in cognitive deficits beyond clinician-rated scales.

K S Minor1, J A Willits2, M P Marggraf1, M N Jones3, P H Lysaker4.   

Abstract

BACKGROUND: Conveying information cohesively is an essential element of communication that is disrupted in schizophrenia. These disruptions are typically expressed through disorganized symptoms, which have been linked to neurocognitive, social cognitive, and metacognitive deficits. Automated analysis can objectively assess disorganization within sentences, between sentences, and across paragraphs by comparing explicit communication to a large text corpus.
METHOD: Little work in schizophrenia has tested: (1) links between disorganized symptoms measured via automated analysis and neurocognition, social cognition, or metacognition; and (2) if automated analysis explains incremental variance in cognitive processes beyond clinician-rated scales. Disorganization was measured in schizophrenia (n = 81) with Coh-Metrix 3.0, an automated program that calculates basic and complex language indices. Trained staff also assessed neurocognition, social cognition, metacognition, and clinician-rated disorganization.
RESULTS: Findings showed that all three cognitive processes were significantly associated with at least one automated index of disorganization. When automated analysis was compared with a clinician-rated scale, it accounted for significant variance in neurocognition and metacognition beyond the clinician-rated measure. When combined, these two methods explained 28-31% of the variance in neurocognition, social cognition, and metacognition.
CONCLUSIONS: This study illustrated how automated analysis can highlight the specific role of disorganization in neurocognition, social cognition, and metacognition. Generally, those with poor cognition also displayed more disorganization in their speech-making it difficult for listeners to process essential information needed to tie the speaker's ideas together. Our findings showcase how implementing a mixed-methods approach in schizophrenia can explain substantial variance in cognitive processes.

Entities:  

Keywords:  Automated analysis; cognition; disorganized symptoms; schizophrenia; speech

Mesh:

Year:  2018        PMID: 29692287     DOI: 10.1017/S0033291718001046

Source DB:  PubMed          Journal:  Psychol Med        ISSN: 0033-2917            Impact factor:   7.723


  12 in total

1.  Personalizing interventions using real-world interactions: Improving symptoms and social functioning in schizophrenia with tailored metacognitive therapy.

Authors:  Kyle S Minor; Matthew P Marggraf; Beshaun J Davis; Jessica L Mickens; Danielle B Abel; Megan L Robbins; Kelly D Buck; Sarah E Wiehe; Paul H Lysaker
Journal:  J Consult Clin Psychol       Date:  2021-08-19

2.  Automatic language analysis identifies and predicts schizophrenia in first-episode of psychosis.

Authors:  Alicia Figueroa-Barra; Daniel Del Aguila; Mauricio Cerda; Pablo A Gaspar; Lucas D Terissi; Manuel Durán; Camila Valderrama
Journal:  Schizophrenia (Heidelb)       Date:  2022-06-01

3.  Modeling Incoherent Discourse in Non-Affective Psychosis.

Authors:  Sandra A Just; Erik Haegert; Nora Kořánová; Anna-Lena Bröcker; Ivan Nenchev; Jakob Funcke; Andreas Heinz; Felix Bermpohl; Manfred Stede; Christiane Montag
Journal:  Front Psychiatry       Date:  2020-08-19       Impact factor: 4.157

Review 4.  Using Language Processing and Speech Analysis for the Identification of Psychosis and Other Disorders.

Authors:  Cheryl Mary Corcoran; Guillermo A Cecchi
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2020-06-14

5.  Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders.

Authors:  Reno Kriz; Sunghye Cho; Sunny X Tang; Suh Jung Park; Jenna Harowitz; Raquel E Gur; Mahendra T Bhati; Daniel H Wolf; João Sedoc; Mark Y Liberman
Journal:  NPJ Schizophr       Date:  2021-05-14

6.  Semantic and phonetic similarity of verbal fluency responses in early-stage psychosis.

Authors:  Nancy B Lundin; Michael N Jones; Evan J Myers; Alan Breier; Kyle S Minor
Journal:  Psychiatry Res       Date:  2022-01-17       Impact factor: 3.222

7.  Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation.

Authors:  Felipe Argolo; Guilherme Magnavita; Natalia Bezerra Mota; Carolina Ziebold; Dirceu Mabunda; Pedro M Pan; André Zugman; Ary Gadelha; Cheryl Corcoran; Rodrigo A Bressan
Journal:  Braz J Psychiatry       Date:  2020 Nov-Dec       Impact factor: 2.697

8.  Acoustic and Facial Features From Clinical Interviews for Machine Learning-Based Psychiatric Diagnosis: Algorithm Development.

Authors:  Michael L Birnbaum; Avner Abrami; John M Kane; Guillermo Cecchi; Stephen Heisig; Asra Ali; Elizabeth Arenare; Carla Agurto; Nathaniel Lu
Journal:  JMIR Ment Health       Date:  2022-01-24

9.  The link between formal thought disorder and social functioning in schizophrenia: A meta-analysis.

Authors:  Matthew P Marggraf; Paul H Lysaker; Michelle P Salyers; Kyle S Minor
Journal:  Eur Psychiatry       Date:  2020-03-23       Impact factor: 5.361

Review 10.  Metacognition, social cognition, and mentalizing in psychosis: are these distinct constructs when it comes to subjective experience or are we just splitting hairs?

Authors:  P H Lysaker; S Cheli; G Dimaggio; B Buck; K A Bonfils; K Huling; C Wiesepape; J T Lysaker
Journal:  BMC Psychiatry       Date:  2021-07-02       Impact factor: 3.630

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.