Silvana Galderisi1, Paola Rucci2, Brian Kirkpatrick3, Armida Mucci1, Dino Gibertoni2, Paola Rocca4, Alessandro Rossi5, Alessandro Bertolino6, Gregory P Strauss7, Eugenio Aguglia8, Antonello Bellomo9, Martino Belvederi Murri10, Paola Bucci1, Bernardo Carpiniello11, Anna Comparelli12, Alessandro Cuomo13, Domenico De Berardis14, Liliana Dell'Osso15, Fabio Di Fabio16, Barbara Gelao6, Carlo Marchesi17, Palmiero Monteleone18, Cristiana Montemagni4, Giulia Orsenigo19, Francesca Pacitti5, Rita Roncone20, Paolo Santonastaso21, Alberto Siracusano22, Annarita Vignapiano1, Antonio Vita23,24, Patrizia Zeppegno25, Mario Maj1. 1. Department of Psychiatry, Campania University "Luigi Vanvitelli," Naples, Italy. 2. Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy. 3. Department of Psychiatry and Behavioral Sciences, University of Nevada, Reno School of Medicine, Reno. 4. Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy. 5. Section of Psychiatry, Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy. 6. Department of Neurological and Psychiatric Sciences, University of Bari, Bari, Italy. 7. Department of Psychology, University of Georgia, Athens. 8. Department of Clinical and Molecular Biomedicine, Psychiatry Unit, University of Catania, Catania, Italy. 9. Psychiatry Unit, Department of Medical Sciences, University of Foggia, Foggia, Italy. 10. Section of Psychiatry, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy. 11. Section of Psychiatry, Department of Public Health, Clinical and Molecular Medicine, University of Cagliari, Cagliari, Italy. 12. Department of Neurosciences, Mental Health and Sensory Organs, S. Andrea Hospital, Sapienza University of Rome, Rome, Italy. 13. Department of Molecular Medicine and Clinical Department of Mental Health, University of Siena, Siena, Italy. 14. Department of Neuroscience and Imaging, G. D'Annunzio University, Chieti, Italy. 15. Section of Psychiatry, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. 16. Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy. 17. Department of Neuroscience, Psychiatry Unit, University of Parma, Parma, Italy. 18. Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana," Section of Neuroscience, University of Salerno, Salerno, Italy. 19. Department of Psychiatry, University of Milan, Milan, Italy. 20. Unit of Psychiatry, Department of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy. 21. Psychiatric Clinic, Department of Neurosciences, University of Padua, Padua, Italy. 22. Department of Systems Medicine, Psychiatry and Clinical Psychology Unit, Tor Vergata University of Rome, Rome, Italy. 23. Psychiatric Unit, School of Medicine, University of Brescia, Brescia, Italy. 24. Department of Mental Health, Spedali Civili Hospital, Brescia, Italy. 25. Department of Translational Medicine, Psychiatric Unit, University of Eastern Piedmont, Novara, Italy.
Abstract
Importance: Enhanced understanding of factors associated with symptomatic and functional recovery is instrumental to designing personalized treatment plans for people with schizophrenia. To date, this is the first study using network analysis to investigate the associations among cognitive, psychopathologic, and psychosocial variables in a large sample of community-dwelling individuals with schizophrenia. Objective: To assess the interplay among psychopathologic variables, cognitive dysfunctions, functional capacity, personal resources, perceived stigma, and real-life functioning in individuals with schizophrenia, using a data-driven approach. Design, Setting, and Participants: This multicenter, cross-sectional study involved 26 university psychiatric clinics and/or mental health departments. A total of 921 community-dwelling individuals with a DSM-IV diagnosis of schizophrenia who were stabilized on antipsychotic treatment were recruited from those consecutively presenting to the outpatient units of the sites between March 1, 2012, and September 30, 2013. Statistical analysis was conducted between July 1 and September 30, 2017. Main Outcomes and Measures: Measures covered psychopathologic variables, neurocognition, social cognition, functional capacity, real-life functioning, resilience, perceived stigma, incentives, and service engagement. Results: Of 740 patients (221 women and 519 men; mean [SD] age, 40.0 [10.9] years) with complete data on the 27 study measures, 163 (22.0%) were remitted (with a score of mild or better on 8 core symptoms). The network analysis showed that functional capacity and everyday life skills were the most central and highly interconnected nodes in the network. Psychopathologic variables split in 2 domains, with positive symptoms being one of the most peripheral and least connected nodes. Functional capacity bridged cognition with everyday life skills; the everyday life skills node was connected to disorganization and expressive deficits. Interpersonal relationships and work skills were connected to avolition; the interpersonal relationships node was also linked to social competence, and the work skills node was linked to social incentives and engagement with mental health services. A case-dropping bootstrap procedure showed centrality indices correlations of 0.75 or greater between the original and randomly defined samples up to 481 of 740 case-dropping (65.0%). No difference in the network structure was found between men and women. Conclusions and Relevance: The high centrality of functional capacity and everyday life skills in the network suggests that improving the ability to perform tasks relevant to everyday life is critical for any therapeutic intervention in schizophrenia. The pattern of network node connections supports the implementation of personalized interventions.
Importance: Enhanced understanding of factors associated with symptomatic and functional recovery is instrumental to designing personalized treatment plans for people with schizophrenia. To date, this is the first study using network analysis to investigate the associations among cognitive, psychopathologic, and psychosocial variables in a large sample of community-dwelling individuals with schizophrenia. Objective: To assess the interplay among psychopathologic variables, cognitive dysfunctions, functional capacity, personal resources, perceived stigma, and real-life functioning in individuals with schizophrenia, using a data-driven approach. Design, Setting, and Participants: This multicenter, cross-sectional study involved 26 university psychiatric clinics and/or mental health departments. A total of 921 community-dwelling individuals with a DSM-IV diagnosis of schizophrenia who were stabilized on antipsychotic treatment were recruited from those consecutively presenting to the outpatient units of the sites between March 1, 2012, and September 30, 2013. Statistical analysis was conducted between July 1 and September 30, 2017. Main Outcomes and Measures: Measures covered psychopathologic variables, neurocognition, social cognition, functional capacity, real-life functioning, resilience, perceived stigma, incentives, and service engagement. Results: Of 740 patients (221 women and 519 men; mean [SD] age, 40.0 [10.9] years) with complete data on the 27 study measures, 163 (22.0%) were remitted (with a score of mild or better on 8 core symptoms). The network analysis showed that functional capacity and everyday life skills were the most central and highly interconnected nodes in the network. Psychopathologic variables split in 2 domains, with positive symptoms being one of the most peripheral and least connected nodes. Functional capacity bridged cognition with everyday life skills; the everyday life skills node was connected to disorganization and expressive deficits. Interpersonal relationships and work skills were connected to avolition; the interpersonal relationships node was also linked to social competence, and the work skills node was linked to social incentives and engagement with mental health services. A case-dropping bootstrap procedure showed centrality indices correlations of 0.75 or greater between the original and randomly defined samples up to 481 of 740 case-dropping (65.0%). No difference in the network structure was found between men and women. Conclusions and Relevance: The high centrality of functional capacity and everyday life skills in the network suggests that improving the ability to perform tasks relevant to everyday life is critical for any therapeutic intervention in schizophrenia. The pattern of network node connections supports the implementation of personalized interventions.
Authors: C Beard; A J Millner; M J C Forgeard; E I Fried; K J Hsu; M T Treadway; C V Leonard; S J Kertz; T Björgvinsson Journal: Psychol Med Date: 2016-09-14 Impact factor: 7.723
Authors: Robert S Kern; Keith H Nuechterlein; Michael F Green; Lyle E Baade; Wayne S Fenton; James M Gold; Richard S E Keefe; Raquelle Mesholam-Gately; Jim Mintz; Larry J Seidman; Ellen Stover; Stephen R Marder Journal: Am J Psychiatry Date: 2008-01-02 Impact factor: 18.112
Authors: Justin J Anker; Erich Kummerfeld; Alexander Rix; Scott J Burwell; Matt G Kushner Journal: Alcohol Clin Exp Res Date: 2018-11-25 Impact factor: 3.455
Authors: Hua Ye; Andrew Zalesky; Jinglei Lv; Samantha M Loi; Suheyla Cetin-Karayumak; Yogesh Rathi; Ye Tian; Christos Pantelis; Maria A Di Biase Journal: Schizophr Bull Date: 2021-07-08 Impact factor: 9.306