Literature DB >> 28368180

Predictors of response to cognitive remediation in service recipients with severe mental illness.

Jean-Pierre Lindenmayer1, Veronica Anna Ozog1, Anzalee Khan1, Isidora Ljuri1, Samantha Fregenti1, Susan R McGurk2.   

Abstract

OBJECTIVE: Cognitive challenges are prominent features of individuals diagnosed with schizophrenia, impairing occupational, social, and economic functioning. These challenges are predictive of social and work outcomes. Cognitive remediation has been shown to be effective in improving both cognitive and social functions. However, cognitive remediation does not produce improvement in all participants. We investigated demographic, neurocognitive, and psychopathological predictors associated with improvement following cognitive remediation interventions in service recipients with severe mental illnesses.
METHOD: One hundred thirty-seven adult participants with a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.) were enrolled in 12-week cognitive remediation programs. Assessments of demographic and illness variables, together with baseline and end point assessment of psychopathology (Positive and Negative Syndrome Scale [PANSS]), neurocognition (Measurement and Treatment Research to Improve Cognition in Schizophrenia [MATRICS] Consensus Cognitive Battery [MCBB]), and social functions (Personal and Social Performance Scale [PSP]) were conducted. Change in cognitive domains was calculated using the reliable change index. Logistic regression analysis was used to assess predictors of cognitive improvement after the intervention.
RESULTS: Sixty-two percent of participants improved on at least 1 of the MCCB domains. Higher baseline speed of processing, attention or vigilance, and working memory predicted a positive response to cognitive remediation. Younger age, higher education level, shorter length of stay, and lower PANSS Negative and Disorganized factors were additional predictors. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Our results indicate the clinical usefulness of cognitive remediation and identified a pattern of clinical and cognitive predictors of good response to the intervention. Identification of these predictive factors by clinicians may enhance the outcome and aid in the development of individualized rehabilitative cognitive remediation treatment plans. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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Year:  2017        PMID: 28368180     DOI: 10.1037/prj0000252

Source DB:  PubMed          Journal:  Psychiatr Rehabil J        ISSN: 1095-158X


  15 in total

1.  Cognitive functioning as a predictor of response to comprehensive cognitive remediation.

Authors:  Nicole R DeTore; Kim T Mueser; Jessica A Byrd; Susan R McGurk
Journal:  J Psychiatr Res       Date:  2019-03-21       Impact factor: 4.791

2.  Individual Alpha Peak Frequency Moderates Transfer of Learning in Cognitive Remediation of Schizophrenia.

Authors:  B C Castelluccio; J G Kenney; J K Johannesen
Journal:  J Int Neuropsychol Soc       Date:  2020-01       Impact factor: 2.892

3.  Neurophysiologic measures of target engagement predict response to auditory-based cognitive training in treatment refractory schizophrenia.

Authors:  William C Hochberger; Yash B Joshi; Michael L Thomas; Wendy Zhang; Andrew W Bismark; Emily B H Treichler; Melissa Tarasenko; John Nungaray; Joyce Sprock; Lauren Cardoso; Neal Swerdlow; Gregory A Light
Journal:  Neuropsychopharmacology       Date:  2018-10-30       Impact factor: 7.853

4.  Compensatory Interventions for Cognitive Impairments in Psychosis: A Systematic Review and Meta-Analysis.

Authors:  Kelly Allott; Kristi van-der-El; Shayden Bryce; Emma M Parrish; Susan R McGurk; Sarah Hetrick; Christopher R Bowie; Sean Kidd; Matthew Hamilton; Eoin Killackey; Dawn Velligan
Journal:  Schizophr Bull       Date:  2020-07-08       Impact factor: 9.306

Review 5.  The effects of cognitive remediation in patients with affective psychosis: A systematic review: Special Section on "Translational and Neuroscience Studies in Affective Disorders". Section Editor, Maria Nobile MD, PhD. This Section of JAD focuses on the relevance of translational and neuroscience studies in providing a better understanding of the neural basis of affective disorders. The main aim is to briefly summaries relevant research findings in clinical neuroscience with particular regards to specific innovative topics in mood and anxiety disorders.

Authors:  Bruno Biagianti; Jaisal Merchant; Paolo Brambilla; Kathryn E Lewandowski
Journal:  J Affect Disord       Date:  2019-03-08       Impact factor: 4.839

6.  Effects of Clozapine on Neurocognitive Functions in Schizophrenia: A Naturalistic Comparison to Non-clozapine Antipsychotics.

Authors:  J P Lindenmayer; Beverly J Insel; Anzalee Khan; McKenzie Osborne; Abraham Goldring; Mary Seddo
Journal:  Innov Clin Neurosci       Date:  2021 Oct-Dec

7.  The effects of cognitive remediation on cognitive abilities and real-world functioning among people with bipolar disorder: A systematic review: Special Section on "Translational and Neuroscience Studies in Affective Disorders". Section Editor, Maria Nobile MD, PhD. This Section of JAD focuses on the relevance of translational and neuroscience studies in providing a better understanding of the neural basis of affective disorders. The main aim is to briefly summaries relevant research findings in clinical neuroscience with particular regards to specific innovative topics in mood and anxiety disorders.

Authors:  Marcella Bellani; Bruno Biagianti; Niccolò Zovetti; Maria Gloria Rossetti; Cinzia Bressi; Cinzia Perlini; Paolo Brambilla
Journal:  J Affect Disord       Date:  2019-07-19       Impact factor: 4.839

8.  Predicting response to cognitive training for schizophrenia using results from two studies with different outcomes.

Authors:  Alice M Saperstein; C Jean Choi; Carol Jahshan; David A Lynch; Melanie Wall; Michael F Green; Alice Medalia
Journal:  Schizophr Res       Date:  2021-03-23       Impact factor: 4.939

9.  A randomized controlled trial comparing a "bottom-up" and "top-down" approach to cognitive training in schizophrenia.

Authors:  Carol Jahshan; Sophia Vinogradov; Jonathan K Wynn; Gerhard Hellemann; Michael F Green
Journal:  J Psychiatr Res       Date:  2018-12-01       Impact factor: 5.250

10.  Model selection and prediction of outcomes in recent onset schizophrenia patients who undergo cognitive training.

Authors:  Ian S Ramsay; Sisi Ma; Melissa Fisher; Rachel L Loewy; J Daniel Ragland; Tara Niendam; Cameron S Carter; Sophia Vinogradov
Journal:  Schizophr Res Cogn       Date:  2017-11-08
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