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Vita A, Nibbio G, Barlati S. Conceptualization and characterization of "primary" and "secondary" cognitive impairment in schizophrenia. Psychiatry Res 2024; 340:116126. [PMID: 39128169 DOI: 10.1016/j.psychres.2024.116126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/25/2024] [Accepted: 08/04/2024] [Indexed: 08/13/2024]
Abstract
Cognitive impairment represents one of the core features of schizophrenia, involves both neurocognition and social cognition domains, and has a significant negative impact on real-world functioning. The present review provides a framework for the conceptualization and characterization of "primary" and "secondary" cognitive impairment in schizophrenia. In this conceptualization, primary cognitive impairment can be defined as a consequence of the neurobiological alterations that underlie psychopathological manifestations of the disorder, while secondary cognitive impairment can be defined as the results of a source issue that has a negative impact on cognitive performance. Sources of secondary cognitive impairment are frequent in people with schizophrenia and include several different factors, such as positive and negative symptoms, depressive symptoms, autistic symptoms, pharmacotherapy, substance abuse, metabolic syndrome, social deprivation, and sleep disorders. It can be hypothesized that secondary cognitive impairment may be improved by effectively resolving the source issue, while primary cognitive impairment may benefit from dedicated treatment. Further research is required to confirm this hypothesis, to better characterize the distinction between primary and secondary cognitive impairment in a clinical and in a neurobiological perspective, and to evaluate the impact of systematically assessing and treating secondary cognitive impairment.
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Affiliation(s)
- Antonio Vita
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Brescia, Italy.
| | - Gabriele Nibbio
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Stefano Barlati
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Brescia, Italy
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2
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Harvey PD, Davidson M, Saoud JB, Kuchibhatla R, Moore RC, Depp CA, Pinkham AE. Prevalence of prominent and predominant negative symptoms across different criteria for negative symptom severity and minimal positive symptoms: A comparison of different criteria. Schizophr Res 2024; 271:246-252. [PMID: 39059248 PMCID: PMC11384184 DOI: 10.1016/j.schres.2024.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/28/2024]
Abstract
Negative symptoms are a source of disability in schizophrenia, but criteria for identifying patients for clinical trials are in flux. Minimum severity for negative symptoms is paired with a definition of minimal psychosis to identify predominant negative symptoms. Two previous successful negative symptoms treatment studies used very different severity and selection criteria. We compared the prevalence of participants meeting those two criteria in a large outpatient sample of participants with schizophrenia. Data from 867 outpatients with schizophrenia who participated in one of four NIMH-funded studies were analyzed. Common data elements included diagnoses, the PANSS, and an assessment of everyday functioning. We compared previous criterion for premoninant negative symptoms based on low levels of agitation and psychosis and different cut-offs for negative symptoms severity. 57 % of the participants met the agitation-based criteria for low scores and 33 % met the psychosis-based criteria. 18 % met total PANSS score ≥ 20 and 8 % met ≥24 prominent negative symptoms criteria. 14 % met low agitation and PANSS≥20 and 2 % met the low psychosis and negative symptoms ≥24 criteria. Participants who met all predominant criteria had more impairments in social functioning (all p < .001, all d > 0.37). Criteria for predominant negative symptoms from previous clinical trials identify widely different numbers of cases, with criteria for negative symptom severity and low symptoms both impacting. All criteria yield the expected profile of relatively specific social deficits. Even in unselected populations who participated in complex research protocols, 14 % meet low- agitation based criteria for predominant negative symptoms and many more participants would be expected to meet criteria with enrichment for the presence of negative symptoms.
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Affiliation(s)
- Philip D Harvey
- University of Miami Miller School of Medicine, Miami, FL, USA.
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3
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Tsui HKH, Wong TY, Sum MY, Chu ST, Hui CLM, Chang WC, Lee EHM, Suen Y, Chen EYH, Chan SKW. Comparison of Negative Symptom Network Structures Between Patients With Early and Chronic Schizophrenia: A Network and Exploratory Graph Analysis. Schizophr Bull 2024:sbae135. [PMID: 39093707 DOI: 10.1093/schbul/sbae135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
BACKGROUND AND HYPOTHESIS Despite the clinical relevance of negative symptoms in schizophrenia, our understanding of negative symptoms remains limited. Although various courses and stages of schizophrenia have been identified, variations in the negative symptom networks between distinct stages of schizophrenia remain unexplored. STUDY DESIGN We examined 405 patients with early schizophrenia (ES) and 330 patients with chronic schizophrenia (CS) using the Scale for the Assessment of Negative Symptoms. Network analysis and exploratory graph analysis were used to identify and compare the network structures and community memberships of negative symptoms between the two groups. Further, associations between communities and social functioning were evaluated. The potential influences of other symptom domains and confounding factors were also examined. STUDY RESULTS Multidimensional differences were found in the networks of negative symptoms between ES and CS. The global connectivity strength was higher in the network of ES than in the network of CS. In ES, central symptoms were mainly related to expressive deficits, whereas in CS they were distributed across negative symptom domains. A three-community structure was suggested across stages but with different memberships and associations with social functioning. Potential confounding factors and symptom domains, including mood, positive, disorganization, and excitement symptoms, did not affect the network structures. CONCLUSION Our findings revealed the presence of stage-specific network structures of negative symptoms in schizophrenia, with negative symptom communities having differential significance for social functioning. These findings provide implications for the future development of tailored interventions to alleviate negative symptoms and improve functionality across stages.
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Affiliation(s)
- Harry Kam Hung Tsui
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Ting Yat Wong
- Department of Psychology, The Education University of Hong Kong, Hong Kong SAR
| | - Min Yi Sum
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Sin Ting Chu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Christy Lai Ming Hui
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Wing Chung Chang
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR
| | - Edwin Ho Ming Lee
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Yinam Suen
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Eric Yu Hai Chen
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
| | - Sherry Kit Wa Chan
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR
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Buchwald K, Narayanan A, Siegert RJ, Vignes M, Arrowsmith K, Sandham M. Centrality statistics of symptom networks of schizophrenia: a systematic review. Psychol Med 2024; 54:1061-1073. [PMID: 38174555 DOI: 10.1017/s003329172300363x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The network theory of psychological disorders posits that systems of symptoms cause, or are associated with, the expression of other symptoms. Substantial literature on symptom networks has been published to date, although no systematic review has been conducted exclusively on symptom networks of schizophrenia, schizoaffective disorder, and schizophreniform (people diagnosed with schizophrenia; PDS). This study aims to compare statistics of the symptom network publications on PDS in the last 21 years and identify congruences and discrepancies in the literature. More specifically, we will focus on centrality statistics. Thirty-two studies met the inclusion criteria. The results suggest that cognition, and social, and occupational functioning are central to the network of symptoms. Positive symptoms, particularly delusions were central among participants in many studies that did not include cognitive assessment. Nodes representing cognition were most central in those studies that did. Nodes representing negative symptoms were not as central as items measuring positive symptoms. Some studies that included measures of mood and affect found items or subscales measuring depression were central nodes in the networks. Cognition, and social, and occupational functioning appear to be core symptoms of schizophrenia as they are more central in the networks, compared to variables assessing positive symptoms. This seems consistent despite heterogeneity in the design of the studies.
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Affiliation(s)
- Khan Buchwald
- School of Clinical Sciences, Auckland University of Technology, 90 Akoranga Drive, Northcote, Auckland 0627, New Zealand
| | - Ajit Narayanan
- Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, 90 Akoranga Drive, Northcote, Auckland, New Zealand
| | - Richard John Siegert
- School of Clinical Sciences, Auckland University of Technology, 90 Akoranga Drive, Northcote, Auckland 0627, New Zealand
| | - Matthieu Vignes
- School of Mathematical and Computational Sciences, Massey University, Tennent Drive, Palmerston North, New Zealand
| | - Kim Arrowsmith
- School of Clinical Sciences, Auckland University of Technology, 90 Akoranga Drive, Northcote, Auckland 0627, New Zealand
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5
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Wolpe N, Vituri A, Jones PB, Shahar M, Fernandez-Egea E. The longitudinal structure of negative symptoms in treatment resistant schizophrenia. Compr Psychiatry 2024; 128:152440. [PMID: 38039918 DOI: 10.1016/j.comppsych.2023.152440] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/29/2023] [Accepted: 11/23/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND AND HYPOTHESIS The negative symptoms of schizophrenia are strong prognostic factors but remain poorly understood and treated. Five negative symptom domains are frequently clustered into the motivation and pleasure (MAP) and emotional expression (EE) 'dimensions', but whether this structure remains stable and behaves as a single entity or not remains unclear. STUDY DESIGN We examined a cohort of 153 patients taking clozapine for treatment-resistant schizophrenia in a regional mental health clinic. Patients were assessed longitudinally over a mean period of 45 months using validated scales for positive, negative and mood symptoms. Network analyses were performed to identify symptom 'communities' and their stability over time. The influence of common causes of secondary negative symptoms as well as centrality measures were also examined. STUDY RESULTS Across patients at baseline, two distinct communities matching the clinical domains of MAP and EE were found. These communities remained highly stable and independent over time. The communities remained stabled when considering psychosis, depression, and sedation severity, and these causes of secondary negative symptoms were clustered into the MAP community. Centrality measures also remained stable over time, with similar centrality measures across symptoms. CONCLUSIONS Our results suggest that MAP and EE are independent dimensions that remain highly stable over time in chronic schizophrenia patients treated with clozapine. Common causes of secondary negative symptoms mapped onto the MAP dimension. Our results emphasise the need for clinical trials to address either MAP or EE, and that treating causes of secondary negative symptoms may improve MAP.
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Affiliation(s)
- Noham Wolpe
- Department of Physical Therapy, The Stanley Steyer School of Health Professions, Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel; Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Aya Vituri
- Tel Aviv Center for Artificial Intelligence & Data Science (TAD), Tel Aviv University, 6997801, Israel
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Fulbourn, Cambridge CB21 5EF, UK
| | - Moni Shahar
- Tel Aviv Center for Artificial Intelligence & Data Science (TAD), Tel Aviv University, 6997801, Israel
| | - Emilio Fernandez-Egea
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Fulbourn, Cambridge CB21 5EF, UK.
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6
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Wen X, Margraf J, Qian M, Berger T, Zhao N, Gou M, Wei S. Pathological network changes in patients with social anxiety disorder before and after an Internet-based CBT. Internet Interv 2023; 34:100691. [PMID: 38034862 PMCID: PMC10684799 DOI: 10.1016/j.invent.2023.100691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 12/02/2023] Open
Abstract
A network perspective may shed light on the understanding of Internet-based CBT efficacy for social anxiety disorder. Previous cross-sectional evidence revealed a densely interconnected network for individuals with social anxiety. Yet, longitudinal network changes before and after ICBT are lacking. This study aimed to investigate pathological network changes with Graphical Gaussian Model among patients with social anxiety disorder (n = 249). Social phobia scale (SPS) and Social interaction anxiety scale (SIAS) were measured before and after 8 weeks Internet-based CBT. Results revealed the connection between symptom tension when speaking and symptom awkward when being watched was the most robust edges during ICBT interventions. The pathological network benefited from ICBT and exhibited modification in several prominent interconnections. The overall network connectivity continues to exhibit comparable strength after ICBT. This study represents the first examination of social anxiety network changes after patients with SAD completed a systematic ICBT. Changes in critical edges and nodes provide valuable insights for the design and efficacy assessment of ICBT interventions.
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Affiliation(s)
- Xu Wen
- Department of Psychology, Mental Health Research and Treatment Center, Ruhr University Bochum, Germany
- Peking University, School of Psychological and Cognitive Sciences, Beijing, China
| | - Juergen Margraf
- Department of Psychology, Mental Health Research and Treatment Center, Ruhr University Bochum, Germany
| | - Mingyi Qian
- Peking University, School of Psychological and Cognitive Sciences, Beijing, China
| | - Thomas Berger
- Department of Psychology, Clinical Psychology and Psychotherapy, Bern, Switzerland
| | - Nan Zhao
- Peking University, School of Psychological and Cognitive Sciences, Beijing, China
| | - Mengke Gou
- Peking University, School of Psychological and Cognitive Sciences, Beijing, China
| | - Shijuan Wei
- Peking University, School of Psychological and Cognitive Sciences, Beijing, China
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Rucci P, Caporusso E, Sanmarchi F, Giordano GM, Mucci A, Giuliani L, Pezzella P, Perrottelli A, Bucci P, Rocca P, Rossi A, Bertolino A, Galderisi S, Maj M. The structure stability of negative symptoms: longitudinal network analysis of the Brief Negative Symptom Scale in people with schizophrenia. BJPsych Open 2023; 9:e168. [PMID: 37674282 PMCID: PMC10594087 DOI: 10.1192/bjo.2023.541] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 06/23/2023] [Accepted: 07/06/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND The structure of negative symptoms of schizophrenia is still a matter of controversy. Although a two-dimensional model (comprising the expressive deficit dimension and the motivation and pleasure dimension) has gained a large consensus, it has been questioned by recent investigations. AIMS To investigate the latent structure of negative symptoms and its stability over time in people with schizophrenia using network analysis. METHOD Negative symptoms were assessed in 612 people with schizophrenia using the Brief Negative Symptom Scale (BNSS) at baseline and at 4-year follow-up. A network invariance analysis was conducted to investigate changes in the network structure and strength of connections between the two time points. RESULTS The network analysis carried out at baseline and follow-up, supported by community detection analysis, indicated that the BNSS's items aggregate to form four or five distinct domains (avolition/asociality, anhedonia, blunted affect and alogia). The network invariance test indicated that the network structure remained unchanged over time (network invariance test score 0.13; P = 0.169), although its overall strength decreased (6.28 at baseline, 5.79 at follow-up; global strength invariance test score 0.48; P = 0.016). CONCLUSIONS The results lend support to a four- or five-factor model of negative symptoms and indicate overall stability over time. These data have implications for the study of pathophysiological mechanisms and the development of targeted treatments for negative symptoms.
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Affiliation(s)
- Paola Rucci
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Edoardo Caporusso
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Francesco Sanmarchi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Giulia M. Giordano
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Luigi Giuliani
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Pasquale Pezzella
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Andrea Perrottelli
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Paola Bucci
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Paola Rocca
- Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
| | - Alessandro Rossi
- Department of Biotechnological and Applied Clinical Sciences, Section of Psychiatry, University of L'Aquila, L'Aquila, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
| | - Mario Maj
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Naples, Italy
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8
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Wang LL, Tam MHW, Ho KKY, Hung KSY, Wong JOY, Lui SSY, Chan RCK. Bridge centrality network structure of negative symptoms in people with schizophrenia. Eur Arch Psychiatry Clin Neurosci 2023; 273:589-600. [PMID: 35972557 DOI: 10.1007/s00406-022-01474-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 08/02/2022] [Indexed: 11/03/2022]
Abstract
Negative symptoms are complex psychopathology. Although evidence generally supported the NIMH five consensus domains, research seldom examined measurement invariance of this model, and domain-specific correspondence across multiple scales. This study aimed to examine the interrelationship between negative symptom domains captured by different rating scales, and to examine the domain-specific correspondence across multiple scales. We administered the Brief Negative Symptom Scale (BNSS), the Self-evaluation of Negative Symptoms (SNS), and the Scale for Assessment of Negative Symptoms (SANS) to 204 individuals with schizophrenia. We used network analysis to examine the interrelationship between negative symptom domains. Besides regularized partial correlation network, we estimated bridge centrality indices to investigate domain-specific correspondence, while taking each scale as an independent community. The regularized partial correlation network showed that the SNS nodes clustered together, whereas the SANS and the BNSS nodes intermingled together. The SANS attention domain lied at the periphery of the network according to the Fruchterman-Reingold algorithm. The SANS anhedonia-asociality (strength = 1.48; EI = 1.48) and the SANS affective flattening (strength = 1.06; EI = 1.06) had the highest node strength and EI. Moreover, the five nodes of the BNSS bridged the nodes of the SANS and the SNS. BNSS blunted affect (strength = 0.76; EI = 0.76) and SANS anhedonia-asociality (strength = 0.76; EI = 0.74) showed the highest bridge strength and bridge EI. The BNSS captures negative symptoms and bridges the symptom domains measured by the SANS and the SNS. The three scales showed domain-specific correspondence.
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Affiliation(s)
- Ling-Ling Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Michelle H W Tam
- Castle Peak Hospital, Hong Kong Special Administrative Region, China
| | - Karen K Y Ho
- Castle Peak Hospital, Hong Kong Special Administrative Region, China
| | - Karen S Y Hung
- Castle Peak Hospital, Hong Kong Special Administrative Region, China
| | - Jessica O Y Wong
- Castle Peak Hospital, Hong Kong Special Administrative Region, China
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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9
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Sun Y, Zhang Y, Lu Z, Yan H, Guo L, Liao Y, Lu T, Wang L, Li J, Li W, Yang Y, Yu H, Lv L, Zhang D, Bi W, Yue W. Longitudinal Network Analysis Reveals Interactive Change of Schizophrenia Symptoms During Acute Antipsychotic Treatment. Schizophr Bull 2023; 49:208-217. [PMID: 36179110 PMCID: PMC9810008 DOI: 10.1093/schbul/sbac131] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS Complex schizophrenia symptoms were recently conceptualized as interactive symptoms within a network system. However, it remains unknown how a schizophrenia network changed during acute antipsychotic treatment. The present study aimed to evaluate the interactive change of schizophrenia symptoms under seven antipsychotics from individual time series. STUDY DESIGN Data on 3030 schizophrenia patients were taken from a multicenter randomized clinical trial and used to estimate the partial correlation cross-sectional networks and longitudinal random slope networks based on multivariate multilevel model. Thirty symptoms assessed by The Positive and Negative Syndrome Scale clustered the networks. STUDY RESULTS Five stable communities were detected in cross-sectional networks and random slope networks that describe symptoms change over time. Delusions, emotional withdrawal, and lack of spontaneity and flow of conversation featured as central symptoms, and conceptual disorganization, hostility, uncooperativeness, and difficulty in abstract thinking featured as bridge symptoms, all showing high centrality in the random slope network. Acute antipsychotic treatment changed the network structure (M-test = 0.116, P < .001) compared to baseline, and responsive subjects showed lower global strength after treatment (11.68 vs 14.18, S-test = 2.503, P < .001) compared to resistant subjects. Central symptoms and bridge symptoms kept higher centrality across random slope networks of different antipsychotics. Quetiapine treatment network showed improvement in excitement symptoms, the one featured as both central and bridge symptom. CONCLUSION Our findings revealed the central symptoms, bridge symptoms, cochanging features, and individualized features under different antipsychotics of schizophrenia. This brings implications for future targeted drug development and search for pathophysiological mechanisms.
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Affiliation(s)
- Yaoyao Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Liangkun Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Lifang Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Jun Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
| | - Wenqiang Li
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Yongfeng Yang
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, Shandong, P. R. China
| | - Luxian Lv
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
| | - Dai Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, P. R. China
| | - Wenjian Bi
- Department of Medical Genetics, School of Basic Medical Sciences, Peking University, Beijing, P. R. China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, P. R. China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, P. R. China
- Henan Key Lab of Biological Psychiatry, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, P. R. China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, P. R. China
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10
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Jones AA, Gicas KM, Mostafavi S, Woodward ML, Leonova O, Vila-Rodriguez F, Procyshyn RM, Cheng A, Buchanan T, Lang DJ, MacEwan GW, Panenka WJ, Barr AM, Thornton AE, Honer WG. Dynamic networks of psychotic symptoms in adults living in precarious housing or homelessness. Psychol Med 2022; 52:2559-2569. [PMID: 33455593 DOI: 10.1017/s0033291720004444] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND People living in precarious housing or homelessness have higher than expected rates of psychotic disorders, persistent psychotic symptoms, and premature mortality. Psychotic symptoms can be modeled as a complex dynamic system, allowing assessment of roles for risk factors in symptom development, persistence, and contribution to premature mortality. METHOD The severity of delusions, conceptual disorganization, hallucinations, suspiciousness, and unusual thought content was rated monthly over 5 years in a community sample of precariously housed/homeless adults (n = 375) in Vancouver, Canada. Multilevel vector auto-regression analysis was used to construct temporal, contemporaneous, and between-person symptom networks. Network measures were compared between participants with (n = 219) or without (n = 156) history of psychotic disorder using bootstrap and permutation analyses. Relationships between network connectivity and risk factors including homelessness, trauma, and substance dependence were estimated by multiple linear regression. The contribution of network measures to premature mortality was estimated by Cox proportional hazard models. RESULTS Delusions and unusual thought content were central symptoms in the multilevel network. Each psychotic symptom was positively reinforcing over time, an effect most pronounced in participants with a history of psychotic disorder. Global connectivity was similar between those with and without such a history. Greater connectivity between symptoms was associated with methamphetamine dependence and past trauma exposure. Auto-regressive connectivity was associated with premature mortality in participants under age 55. CONCLUSIONS Past and current experiences contribute to the severity and dynamic relationships between psychotic symptoms. Interrupting the self-perpetuating severity of psychotic symptoms in a vulnerable group of people could contribute to reducing premature mortality.
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Affiliation(s)
- Andrea A Jones
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kristina M Gicas
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Psychology, York University, Toronto, Ontario, Canada
| | - Sara Mostafavi
- Department of Statistics, University of British Columbia, Vancouver, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Melissa L Woodward
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Olga Leonova
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Fidel Vila-Rodriguez
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ric M Procyshyn
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex Cheng
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tari Buchanan
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donna J Lang
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - G William MacEwan
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - William J Panenka
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alasdair M Barr
- Department of Anesthesia, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Allen E Thornton
- Department of Psychology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - William G Honer
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
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11
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Piao YH, Yun JY, Nguyen TB, Kim WS, Sui J, Kang NI, Lee KH, Ryu S, Kim SW, Lee BJ, Kim JJ, Yu JC, Lee KY, Won SH, Lee SH, Kim SH, Kang SH, Kim E, Chung YC. Longitudinal symptom network structure in first-episode psychosis: a possible marker for remission. Psychol Med 2022; 52:3193-3201. [PMID: 33588966 DOI: 10.1017/s0033291720005280] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND Network approach has been applied to a wide variety of psychiatric disorders. The aim of the present study was to identify network structures of remitters and non-remitters in patients with first-episode psychosis (FEP) at baseline and the 6-month follow-up. METHODS Participants (n = 252) from the Korean Early Psychosis Study (KEPS) were enrolled. They were classified as remitters or non-remitters using Andreasen's criteria. We estimated network structure with 10 symptoms (three symptoms from the Positive and Negative Syndrome Scale, one depressive symptom, and six symptoms related to schema and rumination) as nodes using a Gaussian graphical model. Global and local network metrics were compared within and between the networks over time. RESULTS Global network metrics did not differ between the remitters and non-remitters at baseline or 6 months. However, the network structure and nodal strengths associated with positive-self and positive-others scores changed significantly in the remitters over time. Unique central symptoms for remitters and non-remitters were cognitive brooding and negative-self, respectively. The correlation stability coefficients for nodal strength were within the acceptable range. CONCLUSION Our findings indicate that network structure and some nodal strengths were more flexible in remitters. Negative-self could be an important target for therapeutic intervention.
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Affiliation(s)
- Yan Hong Piao
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, Korea
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Thong Ba Nguyen
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, Korea
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100049, China
| | - Nam-In Kang
- Department of Psychiatry, Maeumsarang Hospital, Wanju, Jeollabuk-do, Korea
| | - Keon-Hak Lee
- Department of Psychiatry, Maeumsarang Hospital, Wanju, Jeollabuk-do, Korea
| | - Seunghyong Ryu
- Department of Psychiatry, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Sung-Wan Kim
- Department of Psychiatry, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Bong Ju Lee
- Department of Psychiatry, Inje University Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Jung Jin Kim
- Department of Psychiatry, The Catholic University of Korea, Seoul St. Mary's Hospital, Seoul, Republic of Korea
| | - Je-Chun Yu
- Department of Psychiatry, Eulji University School of Medicine, Eulji University Hospital, Daejeon, Republic of Korea
| | - Kyu Young Lee
- Department of Psychiatry, Eulji University School of Medicine, Eulji General Hospital, Seoul, Republic of Korea
| | - Seung-Hee Won
- Department of Psychiatry, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Seung-Hwan Lee
- Department of Psychiatry, Inje University College of Medicine, Goyang, Republic of Korea
| | - Seung-Hyun Kim
- Department of Psychiatry, Korea University College of Medicine, Guro Hospital, Seoul, Republic of Korea
| | - Shi Hyun Kang
- Department of Psychiatry, Seoul National Hospital, Seoul, Republic of Korea
| | - Euitae Kim
- Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Young Chul Chung
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, Korea
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12
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Rotstein A, Levine SZ, Samara M, Yoshida K, Goldberg Y, Cipriani A, Iwatsubo T, Leucht S, Furukawa TA. Cognitive impairment networks in Alzheimer's disease: Analysis of three double-blind randomized, placebo-controlled, clinical trials of donepezil. Eur Neuropsychopharmacol 2022; 57:50-58. [PMID: 35093678 DOI: 10.1016/j.euroneuro.2022.01.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 01/04/2022] [Accepted: 01/09/2022] [Indexed: 12/26/2022]
Abstract
Psychometric network analysis is an alternative theoretically-driven analytic approach that has the potential to conceptualize cognitive impairment in Alzheimer's disease differently than was previously assumed and consequently detect unknown treatment effects. Based on individual participant data, extracted from three double-blind, randomized placebo-controlled clinical trials, psychometric networks were computed on observed Alzheimer's Disease Assessment Scale Cognitive Subscale scores at baseline (N=1,554) and on predicted change scores at 24 weeks of follow-up for participants who received donepezil (N=797) or placebo (N=484). A novel conceptualization of cognitive impairment in Alzheimer's disease was displayed through the baseline network, that had 90% (n=27) positive statistically significant (p<0.05) associations, and a most central aspect of ideational praxis. Following 24 weeks, treatment effects emerged via the differences between the change score networks. The donepezil network had more statistically significant (p<0.05) positive associations and a higher global strength (n=15; S=1.22; p=0.03), than the placebo network (n=8; S=0.57). This suggests that for those who were treated with donepezil compared with placebo, cognition is a more unified construct. The main aspects of change in cognitive impairment were comprehension of spoken language for the donepezil network and spoken language ability for the placebo network. Comprehension of spoken language apears to be most sensitive to psychopharmaceutical interventions and should therefore be closely monitored. Overall, our psychometric network analysis presents a new conceptualization of cognitive impairment in Alzheimer's disease, points to previously unknown treatment effects and highlights well-defined aspects of cognitive impairment that may translate into future treatment targets.
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Affiliation(s)
- Anat Rotstein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Stephen Z Levine
- Department of Community Mental Health, University of Haifa, Haifa, Israel
| | - Myrto Samara
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Munich, Germany; Department of Psychiatry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Kazufumi Yoshida
- Department of Health Promotion and Human Behavior, Graduate School of Medicine/ School of Public Health, Kyoto University, Kyoto, Japan
| | - Yair Goldberg
- Faculty of Industrial Engineering and Management, Technion Israel Institute of Technology, Haifa, Israel
| | - Andrea Cipriani
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Takeshi Iwatsubo
- Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, Japan
| | - Stefan Leucht
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Munich, Germany
| | - Toshiaki A Furukawa
- Department of Health Promotion and Human Behavior, Graduate School of Medicine/ School of Public Health, Kyoto University, Kyoto, Japan
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13
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Henry TR, Robinaugh DJ, Fried EI. On the Control of Psychological Networks. PSYCHOMETRIKA 2022; 87:188-213. [PMID: 34390455 PMCID: PMC9205512 DOI: 10.1007/s11336-021-09796-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 06/17/2021] [Indexed: 05/04/2023]
Abstract
The combination of network theory and network psychometric methods has opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, simply estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, nor is it sufficient for determining the potential efficacy of any given intervention. In this paper, we attempt to remedy this gap by introducing fundamental concepts of control theory to both psychometricians and applied psychologists. We introduce two controllability statistics to the psychometric literature, average and modal controllability, to facilitate selecting the best set of intervention targets. Following this introduction, we show how intervention scientists can probe the effects of both theoretical and empirical interventions on networks derived from real data and demonstrate how simulations can account for intervention cost and the desire to reduce specific symptoms. Every step is based on rich clinical EMA data from a sample of subjects undergoing treatment for complicated grief, with a focus on the outcome suicidal ideation. All methods are implemented in an open-source R package netcontrol, and complete code for replicating the analyses in this manuscript are available online.
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Affiliation(s)
- Teague R Henry
- Department of Psychology and School of Data Science, University of Virginia, Charlottesville, VA, USA.
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA.
| | - Donald J Robinaugh
- Department of Psychiatry, Harvard Medical School & Massachusetts General Hospital, Boston, USA
| | - Eiko I Fried
- Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
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14
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Yang HX, Hu HX, Zhang YJ, Wang Y, Lui SSY, Chan RCK. A network analysis of interoception, self-awareness, empathy, alexithymia, and autistic traits. Eur Arch Psychiatry Clin Neurosci 2022; 272:199-209. [PMID: 33987711 DOI: 10.1007/s00406-021-01274-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 05/06/2021] [Indexed: 12/01/2022]
Abstract
Altered interoception has been consistently found in people with autism spectrum disorder (ASD), and this impairment may contribute to social cognitive dysfunctions. However, little is known regarding the intercorrelations between interoceptive sensibility, autistic, alexithymic, empathic, and self-related traits. We recruited 1360 non-clinical college students and adults to investigate the complex inter-relationship between these variables using network analysis. The resultant network revealed patterns connecting autistic traits to interoceptive sensibility, empathy, alexithymia, and self-awareness, with reasonable stability and test-retest consistency. The node of alexithymia exhibited the highest centrality and expected influence. As revealed by the network comparison test, networks constructed in high- and low-autistic subgroups were comparable in global strength and structure. Our findings suggested that alexithymia serves as an important node, bridging interoceptive deficits, self-awareness, and empathic impairments of autism spectrum disorder. The co-morbidity of alexithymia should be considered carefully in future studies of interoceptive impairments and social deficits in ASD.
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Affiliation(s)
- Han-Xue Yang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences; CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Hui-Xin Hu
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences; CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi-Jing Zhang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences; CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences; CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Simon S Y Lui
- Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences; CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Road, Beijing, 100101, China. .,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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15
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The network analysis of depressive symptoms before and after two weeks of antidepressant treatment. J Affect Disord 2022; 299:126-134. [PMID: 34838606 DOI: 10.1016/j.jad.2021.11.059] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/19/2021] [Accepted: 11/22/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND A substantial proportion of patients do not benefit from selective serotonin reuptake inhibitors (SSRIs). We used network analysis to examine changes in symptom associations over time to identify SSRIs treatment targets for patients with major depressive disorder (MDD). METHODS This study was a post-hoc analysis of data originated from the 2-week open-label phase of a multicenter clinical trial. A total of 474 participants who completed 2-week paroxetine treatment and subsequent evaluation were included in this analysis. The sample was divided into early improvement (a reduction of the HAMD-17 total score ⩾20% at week 2) and not early improvement. The network analysis was performed to compare the pattern of relationships among depressive symptoms at baseline and endpoint. In addition, we compared the network structure of the participants who achieved early improvement with those without early improvement. RESULTS We found that the network structure and global strength increased significantly from baseline to endpoint (P<0.05). The baseline network of early improvers was more strongly connected than that of the participants who did not reach early improvement, and the global strength was significantly different (P = 0.049). Psychological anxiety and depressed mood were central symptoms of the early improvers, while somatic anxiety, insomnia, gastrointestinal symptoms and feelings of guilt were central in the network among the participants who did not show early improvement. CONCLUSIONS The connectivity of symptom network significantly increased with treatment. The baseline network connectivity of symptoms is tighter in early improvers than those without early improvement, and their central symptoms are different.
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16
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Kovacs TZ, Hill RW, Watson S, Turkington D. Clusters, lines and webs-so does my patient have psychosis? reflections on the use of psychiatric conceptual frameworks from a clinical vantage point. Philos Ethics Humanit Med 2022; 17:6. [PMID: 35152913 PMCID: PMC8842805 DOI: 10.1186/s13010-022-00118-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 01/22/2022] [Indexed: 06/14/2023] Open
Abstract
Mental health professionals working in hospitals or community clinics inevitably face the realisation that we possess imperfect conceptual means to understand mental disorders. In this paper the authors bring together ideas from the fields of Philosophy, Psychiatry, Cognitive Psychology and Linguistics to reflect on the ways we represent phenomena of high practical importance that we often take for granted, but are nevertheless difficult to define in ontological terms. The paper follows through the development of the concept of psychosis over the last two centuries in the interplay of three different conceptual orientations: the categorical, dimensional and network approaches. Each of these represent the available knowledge and dominant thinking styles of the era in which they emerged and take markedly different stances regarding the nature of mental phenomena. Without particular commitment to any ontological positions or models described, the authors invite the reader into a thinking process about the strengths and weaknesses of these models, and how they can be reconciled in multidisciplinary settings to benefit the process of patient care.
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Affiliation(s)
- Tibor Zoltan Kovacs
- Early Intervention in Psychosis Service, Newcastle upon Tyne, Cumbria, UK.
- Northumberland Tyne and Wear NHS Foundation Trust, 1 Benton View, Forest Hall, Newcastle upon Tyne, NE12 7JJ, UK.
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
| | - Reece William Hill
- School of Medical Education, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
| | - Stuart Watson
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
| | - Douglas Turkington
- Cumbria, Northumberland, Tyne and Wear NHS Trust, Monkwearmouth Hospital, Newcastle Road, Sunderland, SR5 1NB, UK
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17
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Katzenmajer-Pump L, Komáromy D, Balázs J. The importance of recognizing worthlessness for suicide prevention in adolescents with Attention-deficit/hyperactivity disorder. Front Psychiatry 2022; 13:969164. [PMID: 36458127 PMCID: PMC9705741 DOI: 10.3389/fpsyt.2022.969164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 10/31/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric diagnoses among children and adolescents. Depression and general anxiety disorder (GAD) are often co-occurring with ADHD among children and adolescents. Previous studies have found that ADHD, depression and GAD are all strongly correlated with suicidal thoughts and planning. AIM The current study aimed to further explore the association between ADHD, GAD and depressive symptoms as well as their association with suicidal thoughts and planning among adolescents. METHOD Adolescents with ADHD diagnosis were involved from child psychiatry outpatient clinics and adolescents without a psychiatric treatment or diagnosis were enrolled from high schools in Hungary. The Mini International Neuropsychiatric Interview for Children and Adolescents was used to evaluate psychiatric symptoms and disorders as well as suicidal thoughts and planning. Regularized psychological networks were used to investigate the associations. RESULTS Altogether 185 adolescents (58 females and 127 males; mean age 14.79 years, SD = 1.48), 89 with ADHD and 96 without ADHD were enrolled. Depression symptom worthlessness was directly related to suicidal thoughts and planning, CI95 of the logit B between worthlessness and suicidal thought (0.72, 1.66). Both ADHD and anxiety were indirectly related to suicidal thoughts and planning through depression: CI95 of the logit B between being disorganized and feeling worthless is (0.38, 3.02), and CI95 of the logit B between being distressed and feeling worthless is (0.57, 2.52). CONCLUSIONS This study draws the attention of clinicians to the importance of recognizing "worthlessness" for suicide prevention in adolescents with ADHD. Furthermore, the results support previous studies, whereby symptoms of depression and anxiety mediate the relationship between ADHD and suicidal thoughts and planning. These results highlight the importance of ADHD comorbidities with depression and GAD and their effect on suicidal thoughts and planning.
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Affiliation(s)
- Luca Katzenmajer-Pump
- Doctoral School of Psychology, Institute of Psychology, Eötvös Loránd University, Budapest, Hungary
| | - Dániel Komáromy
- Department of Developmental and Clinical Child Psychology, Institute of Psychology, Eötvös Loránd University, Budapest, Hungary.,Department of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, Netherlands.,Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Judit Balázs
- Department of Developmental and Clinical Child Psychology, Institute of Psychology, Eötvös Loránd University, Budapest, Hungary.,Department of Psychology, Oslo New University College, Oslo, Norway
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18
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Network analysis of trauma in patients with early-stage psychosis. Sci Rep 2021; 11:22749. [PMID: 34815435 PMCID: PMC8610987 DOI: 10.1038/s41598-021-01574-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 10/29/2021] [Indexed: 11/24/2022] Open
Abstract
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ChT and negative lifestyle in patients and controls. We used data of patients with early-stage psychosis (n = 500) and healthy controls (n = 202). Networks were constructed using 12 nodes from five scales: the Brief Core Schema Scale (BCSS), Brooding Scale (BS), Dietary Habits Questionnaire, Physical Activity Rating, and Early Trauma Inventory Self Report-Short Form (ETI). Graph metrics were calculated. The nodes with the highest predictability and expected influence in both patients and controls were cognitive and emotional components of the BS and emotional abuse of the ETI. The emotional abuse was a mediator in the shortest pathway connecting the ETI and negative lifestyle for both groups. The negative others and negative self of the BCSS mediated emotional abuse to other BCSS or BS for patients and controls, respectively. Our findings suggest that rumination and emotional abuse were central symptoms in both groups and that negative others and negative self played important mediating roles for patients and controls, respectively. Trial Registration: ClinicalTrials.gov identifier: CUH201411002.
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19
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Griffiths SL, Leighton SP, Mallikarjun PK, Blake G, Everard L, Jones PB, Fowler D, Hodgekins J, Amos T, Freemantle N, Sharma V, Marshall M, McCrone P, Singh SP, Birchwood M, Upthegrove R. Structure and stability of symptoms in first episode psychosis: a longitudinal network approach. Transl Psychiatry 2021; 11:567. [PMID: 34743179 PMCID: PMC8572227 DOI: 10.1038/s41398-021-01687-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 09/21/2021] [Accepted: 10/20/2021] [Indexed: 12/13/2022] Open
Abstract
Early psychosis is characterised by heterogeneity in illness trajectories, where outcomes remain poor for many. Understanding psychosis symptoms and their relation to illness outcomes, from a novel network perspective, may help to delineate psychopathology within early psychosis and identify pivotal targets for intervention. Using network modelling in first episode psychosis (FEP), this study aimed to identify: (a) key central and bridge symptoms most influential in symptom networks, and (b) examine the structure and stability of the networks at baseline and 12-month follow-up. Data on 1027 participants with FEP were taken from the National EDEN longitudinal study and used to create regularised partial correlation networks using the 'EBICglasso' algorithm for positive, negative, and depressive symptoms at baseline and at 12-months. Centrality and bridge estimations were computed using a permutation-based network comparison test. Depression featured as a central symptom in both the baseline and 12-month networks. Conceptual disorganisation, stereotyped thinking, along with hallucinations and suspiciousness featured as key bridge symptoms across the networks. The network comparison test revealed that the strength and bridge centralities did not differ significantly between the two networks (C = 0.096153; p = 0.22297). However, the network structure and connectedness differed significantly from baseline to follow-up (M = 0.16405, p = <0.0001; S = 0.74536, p = 0.02), with several associations between psychosis and depressive items differing significantly by 12 months. Depressive symptoms, in addition to symptoms of thought disturbance (e.g. conceptual disorganisation and stereotyped thinking), may be examples of important, under-recognized treatment targets in early psychosis, which may have the potential to lead to global symptom improvements and better recovery.
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Affiliation(s)
| | - Samuel P Leighton
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | | | - Georgina Blake
- College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Linda Everard
- Birmingham and Solihull Mental Health Foundation Trust, Birmingham, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge and CAMEO, Cambridge and Peterborough NHS Foundation Trust, Cambridge, UK
| | - David Fowler
- Department of Psychology, University of Sussex, Brighton, UK
| | | | - Tim Amos
- Academic Unit of Psychiatry, University of Bristol, Bristol, UK
| | - Nick Freemantle
- Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Vimal Sharma
- Early Intervention Service, Cheshire and Wirral NHS Foundation Trust, Liverpool, UK
| | - Max Marshall
- Lancashire Care NHS Foundation Trust, Preston, UK
| | - Paul McCrone
- Institute for Life Course Development, University of Greenwich, London, UK
| | - Swaran P Singh
- Mental Health and Wellbeing Warwick Medical School, University of Warwick, Coventry, UK
| | - Max Birchwood
- Mental Health and Wellbeing Warwick Medical School, University of Warwick, Coventry, UK
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, UK
- College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
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20
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Demyttenaere K, Leenaerts N, Acsai K, Sebe B, Laszlovszky I, Barabássy Á, Fonticoli L, Szatmári B, Earley W, Németh G, Correll CU. Disentangling the symptoms of schizophrenia: Network analysis in acute phase patients and in patients with predominant negative symptoms. Eur Psychiatry 2021; 65:e18. [PMID: 34641986 PMCID: PMC8926909 DOI: 10.1192/j.eurpsy.2021.2241] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background The Positive and Negative Syndrome Scale (PANSS) is widely used in schizophrenia and has been divided into distinct factors (5-factor models) and subfactors. Network analyses are newer in psychiatry and can help to better understand the relationships and interactions between the symptoms of a psychiatric disorder. The aim of this study was threefold: (a) to evaluate connections between schizophrenia symptoms in two populations of patients (patients in the acutely exacerbated phase of schizophrenia and patients with predominant negative symptoms [PNS]), (b) to test whether network analyses support the Mohr 5 factor model of the PANSS and the Kahn 2 factor model of negative symptoms, and finally (c) to identify the most central symptoms in the two populations. Methods Using pooled baseline data from four cariprazine clinical trials in patients with acute exacerbation of schizophrenia (n = 2193) and the cariprazine–risperidone study in patients with PNS (n = 460), separate network analyses were performed. Network structures were estimated for all 30 items of the PANSS. Results While negative symptoms in patients with an acute exacerbation of schizophrenia are correlated with other PANSS symptoms, these negative symptoms are not correlated with other PANSS symptoms in patients with PNS. The Mohr factors were partially reflected in the network analyses. The two most central symptoms (largest node strength) were delusions and uncooperativeness in acute phase patients and hostility and delusions in patients with PNS. Conclusions This network analysis suggests that symptoms of schizophrenia are differently structured in acute and PNS patients. While in the former, negative symptoms are mainly secondary, in patients with PNS, they are mainly primary. Further, primary negative symptoms are better conceptualized as distinct negative symptom dimensions of the PANSS.
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Affiliation(s)
- Koen Demyttenaere
- University of Leuven, Faculty of Medicine, Department of Neurosciences, Psychiatry Research Group and University Psychiatric Center KU Leuven, Belgium.,University Psychiatric Center KU Leuven, Belgium
| | | | - Károly Acsai
- Gedeon Richter Plc., Medical Division, Budapest, Hungary
| | - Barbara Sebe
- Gedeon Richter Plc., Medical Division, Budapest, Hungary
| | | | | | | | | | | | - György Németh
- Gedeon Richter Plc., Medical Division, Budapest, Hungary
| | - Christoph U Correll
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA.,Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA.,Charité Universitätsmedizin Berlin, Department of Child and Adolescent Psychiatry, Berlin, Germany
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21
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Moura BM, van Rooijen G, Schirmbeck F, Wigman JTW, Madeira L, van Harten P, van Os J, Bakker PR, Marcelis M. A Network of Psychopathological, Cognitive, and Motor Symptoms in Schizophrenia Spectrum Disorders. Schizophr Bull 2021; 47:915-926. [PMID: 33533401 PMCID: PMC8266645 DOI: 10.1093/schbul/sbab002] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Schizophrenia spectrum disorders (SSDs) are complex syndromes involving psychopathological, cognitive, and also motor symptoms as core features. A better understanding of how these symptoms mutually impact each other could translate into diagnostic, prognostic, and, eventually, treatment advancements. The present study aimed to: (1) estimate a network model of psychopathological, cognitive, and motor symptoms in SSD; (2) detect communities and explore the connectivity and relative importance of variables within the network; and (3) explore differences in subsample networks according to remission status. A sample of 1007 patients from a multisite cohort study was included in the analysis. We estimated a network of 43 nodes, including all the items from the Positive and Negative Syndrome Scale, a cognitive assessment battery and clinical ratings of extrapyramidal symptoms. Methodologies specific to network analysis were employed to address the study's aims. The estimated network for the total sample was densely interconnected and organized into 7 communities. Nodes related to insight, abstraction capacity, attention, and suspiciousness were the main bridges between network communities. The estimated network for the subgroup of patients in remission showed a sparser density and a different structure compared to the network of nonremitted patients. In conclusion, the present study conveys a detailed characterization of the interrelations between a set of core clinical elements of SSD. These results provide potential novel clues for clinical assessment and intervention.
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Affiliation(s)
- Bernardo Melo Moura
- Department of Psychiatry, Faculty of Medicine, University of Lisbon, 1649-028 Lisbon, Portugal
- Department of Psychiatry and Mental Health, North Lisbon University Hospital Centre, Avenida Professor Egas Moniz, 1649-028 Lisbon, Portugal
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Geeske van Rooijen
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Frederike Schirmbeck
- Department of Psychiatry, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Arkin Institute for Mental Health, 1033 NN Amsterdam, The Netherlands
| | - Johanna T W Wigman
- Rob Giel Onderzoekscentrum, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Luís Madeira
- Department of Psychiatry, Faculty of Medicine, University of Lisbon, 1649-028 Lisbon, Portugal
- Department of Psychiatry and Mental Health, North Lisbon University Hospital Centre, Avenida Professor Egas Moniz, 1649-028 Lisbon, Portugal
| | - Peter van Harten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, 6200 MD Maastricht, The Netherlands
- GGz Centraal, Innova Medical Centre, 3800 DB Amersfoort, The Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, 6200 MD Maastricht, The Netherlands
- Brain Center Rudolf Magnus University Medical Center Utrecht, Utrecht University, 3508 AB Utrecht, The Netherlands
| | - P Roberto Bakker
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, 6200 MD Maastricht, The Netherlands
- Arkin Institute for Mental Health, 1033 NN Amsterdam, The Netherlands
- Brain Center Rudolf Magnus University Medical Center Utrecht, Utrecht University, 3508 AB Utrecht, The Netherlands
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, 6200 MD Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), 5600 AX Eindhoven, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
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22
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Simpson-Kent IL, Fried EI, Akarca D, Mareva S, Bullmore ET, Kievit RA. Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners. J Intell 2021; 9:32. [PMID: 34204009 PMCID: PMC8293355 DOI: 10.3390/jintelligence9020032] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/26/2021] [Accepted: 06/02/2021] [Indexed: 12/24/2022] Open
Abstract
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role 'between' brain and behavior. We discuss implications and possible avenues for future studies.
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Affiliation(s)
- Ivan L. Simpson-Kent
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Eiko I. Fried
- Department of Clinical Psychology, Leiden University, 2300 RA Leiden, The Netherlands;
| | - Danyal Akarca
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Silvana Mareva
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Edward T. Bullmore
- Department of Psychiatry, University of Cambridge Clinical School, Cambridge, Cambridgeshire CB2 0SP, UK;
| | - the CALM Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
| | - Rogier A. Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire CB2 7EF, UK; (D.A.); (S.M.); (R.A.K.)
- Cognitive Neuroscience Department, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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23
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Gyori D, Farkas BF, Horvath LO, Komaromy D, Meszaros G, Szentivanyi D, Balazs J. The Association of Nonsuicidal Self-Injury with Quality of Life and Mental Disorders in Clinical Adolescents-A Network Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:1840. [PMID: 33672808 PMCID: PMC7918829 DOI: 10.3390/ijerph18041840] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/08/2021] [Accepted: 02/10/2021] [Indexed: 11/17/2022]
Abstract
Although earlier research has highlighted that psychiatric disorders significantly impair patients' quality of life (QoL), few studies have examined the relationship between nonsuicidal self-injury (NSSI) and QoL. Our aim was to investigate whether QoL mediates the mental disorder-NSSI relationship, and to study the QoL ratings agreement of self and parents in a clinical population of adolescents. We involved 202 adolescents from Vadaskert Child Psychiatric Hospital and Outpatient Clinic, Budapest, aged 13-18 years. All participants completed the Deliberate Self-Harm Inventory, Inventar zur Erfassung der Lebensqualität bei Kindern und Jugendlichen, and the Mini International Neuropsychiatric Interview Kid. To map the interrelationship between the NSSI, mental disorders, and QoL dimensions, Mixed Graphical Models were estimated. Adolescents with a history of NSSI rated their QoL to be significantly lower than adolescents without NSSI. Self and parents' QoL ratings are closer in the NSSI sample than in the no-NSSI sample. Among all QoL dimensions, only family problems had a direct significant association with NSSI engagement. Our results highlight that, contrary to our hypothesis, the presence of mental disorders mediates the relationship between most QoL dimensions and the occurrence of NSSI. Our results draw attention to the potential causal effect of environmental factors (e.g., peer problems) on mental disorders that, in turn, result in NSSI. The present paper highlights the importance of network modelling in clinical research.
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Affiliation(s)
- Dora Gyori
- Doctoral School of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (L.O.H.); (D.S.)
- Institute of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (D.K.); (J.B.)
| | - Bernadett Frida Farkas
- Mental Health Sciences Doctoral School, Semmelweis University, 1083 Budapest, Hungary; (B.F.F.); (G.M.)
| | - Lili Olga Horvath
- Doctoral School of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (L.O.H.); (D.S.)
- Institute of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (D.K.); (J.B.)
| | - Daniel Komaromy
- Institute of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (D.K.); (J.B.)
- Faculty of Social and Behavioural Sciences, University of Amsterdam, 1018 WV Amsterdam, The Netherlands
- Department of Behavioural and Movement Sciences, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Gergely Meszaros
- Mental Health Sciences Doctoral School, Semmelweis University, 1083 Budapest, Hungary; (B.F.F.); (G.M.)
- Faculty of Medicine, Department of Psychiatry and Psychotherapy, Semmelweis University, 1083 Budapest, Hungary
| | - Dora Szentivanyi
- Doctoral School of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (L.O.H.); (D.S.)
- Institute of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (D.K.); (J.B.)
- Pedagogical Assistance Services, 1067 Budapest, Hungary
| | - Judit Balazs
- Institute of Psychology, Eotvos Lorand University, 1075 Budapest, Hungary; (D.K.); (J.B.)
- Department of Psychology, Bjørknes University College, 0456 Oslo, Norway
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24
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Motivation in schizophrenia: preliminary findings of a theory-driven approach using time-series network analysis. CURRENT PSYCHOLOGY 2021. [DOI: 10.1007/s12144-020-01321-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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25
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Martín-Brufau R, Suso-Ribera C, Corbalán J. Emotion Network Analysis During COVID-19 Quarantine - A Longitudinal Study. Front Psychol 2020; 11:559572. [PMID: 33240149 PMCID: PMC7683502 DOI: 10.3389/fpsyg.2020.559572] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 09/24/2020] [Indexed: 12/20/2022] Open
Abstract
Introduction: The coronavirus disease 2019 (COVID-19) emergency has imposed important challenges in the lives of individuals, particularly since the restriction of free movement. In Spain, this mandatory home confinement started on March 14, 2020. In this scenario, some calls have been made to better understand the exact impact of the quarantine on the emotional status of individuals across time. Materials and Methods: On the first day that the Spanish government imposed the quarantine, our team launched an online longitudinal study to monitor emotional responses to the COVID-19 emergency over time. For 2 weeks, 187 people have responded to a daily diary on emotion functioning. An emotion network analysis was performed to study the network structure of 30 mood states and its changes during the first 2 weeks of the quarantine. Results: The emotional network showed critical changes in the interactions of emotions over time. An analysis of mean emotional levels did not show statistically significant changes in mood over time. Interestingly, two different network patterns were found when the sample was divided between those with favorable responses and those with unfavorable responses. Discussion: This new approach to the study of longitudinal changes of the mood state network of the population reveals different adaptation strategies reflected on the sample's emotional network. This network approach can help identify most fragile individuals (more vulnerable to external stressors) before they develop clear and identifiable psychopathology and also help identify anti-fragile individuals (those who improve their functioning in the face of external stressors). This is one of the first studies to apply an emotional network approach to study the psychological effects of pandemics and might offer some clues to psychologists and health administrators to help people cope with and adjust to this critical situation.
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Affiliation(s)
- Ramón Martín-Brufau
- Department of Acute Psychiatry Service, Román Alberca’s Hospital, Servicio Murciano de Salud, Murcia, Spain
- Department of Personality, Assessment and Psychological Treatment, Faculty of Psychology, University of Murcia, Murcia, Spain
| | - Carlos Suso-Ribera
- Departamento Psicologia Bàsica, Clínica i Psicobiologia, Faculty of Psychology, Jaume I University, Castellón de la Plana, Spain
| | - Javier Corbalán
- Department of Personality, Assessment and Psychological Treatment, Faculty of Psychology, University of Murcia, Murcia, Spain
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26
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Spiller TR, Levi O, Neria Y, Suarez-Jimenez B, Bar-Haim Y, Lazarov A. On the validity of the centrality hypothesis in cross-sectional between-subject networks of psychopathology. BMC Med 2020; 18:297. [PMID: 33040734 PMCID: PMC7549218 DOI: 10.1186/s12916-020-01740-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 08/10/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In the network approach to psychopathology, psychiatric disorders are considered networks of causally active symptoms (nodes), with node centrality hypothesized to reflect symptoms' causal influence within a network. Accordingly, centrality measures have been used in numerous network-based cross-sectional studies to identify specific treatment targets, based on the assumption that deactivating highly central nodes would proliferate to other nodes in the network, thereby collapsing the network structure and alleviating the overall psychopathology (i.e., the centrality hypothesis). METHODS Here, we summarize three types of evidence pertaining to the centrality hypothesis in psychopathology. First, we discuss the validity of the theoretical assumptions underlying the centrality hypothesis in psychopathology. We then summarize the methodological aspects of extant studies using centrality measures as predictors of symptom change following treatment, while delineating their main findings and several of their limitations. Finally, using a specific dataset of 710 treatment-seeking patients with posttraumatic stress disorder (PTSD) as an example, we empirically examine node centrality as a predictor of therapeutic change, replicating the approach taken by previous studies, while addressing some of their limitations. Specifically, we investigated whether three pre-treatment centrality indices (strength, predictability, and expected influence) were significantly correlated with the strength of the association between a symptom's change and the change in the severity of all other symptoms in the network from pre- to post-treatment (Δnode-Δnetwork association). Using similar analyses, we also examine the predictive validity of two simple non-causal node properties (mean symptom severity and infrequency of symptom endorsement). RESULTS Of the three centrality measures, only expected influence successfully predicted how strongly changes in nodes/symptoms were associated with change in the remainder of the nodes/symptoms. Importantly, when excluding the amnesia node, a well-documented outlier in the phenomenology of PTSD, none of the tested centrality measures predicted symptom change. Conversely, both mean symptom severity and infrequency of symptom endorsement, two standard non-network-derived indices, were found to be more predictive than expected influence and remained significantly predictive also after excluding amnesia from the network analyses. CONCLUSIONS The centrality hypothesis in its current form is ill-defined, showing no consistent supporting evidence in the context of cross-sectional, between-subject networks.
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Affiliation(s)
- Tobias R Spiller
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, Zurich, Switzerland.
| | - Ofir Levi
- Division of Mental Health, Medical Corps, Israel Defense Forces, Tel Aviv, Israel
- Social Work Department, Ruppin Academic Center, Emek Hefer, Israel
- Bob Shapell School of Social Work, Tel Aviv University, Tel Aviv, Israel
| | - Yuval Neria
- Departments of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Benjamin Suarez-Jimenez
- Departments of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Yair Bar-Haim
- School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Amit Lazarov
- Departments of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
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27
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Rotstein A. Network analysis of the structure and change in the mini-mental state examination: a nationally representative sample. Soc Psychiatry Psychiatr Epidemiol 2020; 55:1363-1371. [PMID: 32198595 DOI: 10.1007/s00127-020-01863-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 03/11/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE The structure of the mini-mental state examination (MMSE) is inconsistent across factor analytic studies, and yet to be examined based on network analysis. The current study aims to identify the (I) cross-sectional network structure and (II) longitudinal network changes of the MMSE. METHODS The MMSE was administered to a nationally representative sample of older adults (age 50 and over) in Ireland twice over 4 years (2012-2013: N = 7207; 2016: N = 5715). Psychometric network analysis was computed at each time point to identify structure, strength and magnitude of the network associations. Item clustering was examined, and modularity scores were computed to measure the overall strength of clustering. Centrality indices were used to identify the main aspects of the MMSE. Longitudinal differences between the networks were examined. RESULTS Cross-sectionally, the MMSE network structure clustered into a single community (modularity score = 0) with orientation items identified as most central. Longitudinally, the MMSE was time invariant regarding structure, centrality and magnitude of the positive associations between the items. The average magnitude of the negative associations increased over time[(t(65.15) = 3.78, p < 0.001; time 1: M = - 0.59, SD = 0.58 time 2: M = - 1.65, SD = 1.97] as did their percentage. CONCLUSION Network analysis of the MMSE showed that the measure consisted of a single entity of cognitive functioning irrespective of time. Orientation items were repeatedly identified as most central. Longitudinal changes of the network were evident in increased negative associations between selected cognitive components after 4 years of follow-up. These changes may be explained by neuro-cognitive compensation processes.
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Affiliation(s)
- Anat Rotstein
- Department of Community Mental Health, Faculty of Social Welfare and Health Sciences, University of Haifa, 3498838, Haifa, Israel.
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28
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Chang WC, Wong CSM, Or PCF, Chu AOK, Hui CLM, Chan SKW, Lee EMH, Suen YN, Chen EYH. Inter-relationships among psychopathology, premorbid adjustment, cognition and psychosocial functioning in first-episode psychosis: a network analysis approach. Psychol Med 2020; 50:2019-2027. [PMID: 31451127 DOI: 10.1017/s0033291719002113] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Better understanding of interplay among symptoms, cognition and functioning in first-episode psychosis (FEP) is crucial to promoting functional recovery. Network analysis is a promising data-driven approach to elucidating complex interactions among psychopathological variables in psychosis, but has not been applied in FEP. METHOD This study employed network analysis to examine inter-relationships among a wide array of variables encompassing psychopathology, premorbid and onset characteristics, cognition, subjective quality-of-life and psychosocial functioning in 323 adult FEP patients in Hong Kong. Graphical Least Absolute Shrinkage and Selection Operator (LASSO) combined with extended Bayesian information criterion (BIC) model selection was used for network construction. Importance of individual nodes in a generated network was quantified by centrality analyses. RESULTS Our results showed that amotivation played the most central role and had the strongest associations with other variables in the network, as indexed by node strength. Amotivation and diminished expression displayed differential relationships with other nodes, supporting the validity of two-factor negative symptom structure. Psychosocial functioning was most strongly connected with amotivation and was weakly linked to several other variables. Within cognitive domain, digit span demonstrated the highest centrality and was connected with most of the other cognitive variables. Exploratory analysis revealed no significant gender differences in network structure and global strength. CONCLUSION Our results suggest the pivotal role of amotivation in psychopathology network of FEP and indicate its critical association with psychosocial functioning. Further research is required to verify the clinical significance of diminished motivation on functional outcome in the early course of psychotic illness.
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Affiliation(s)
- W C Chang
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - C S M Wong
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - P C F Or
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - A O K Chu
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - C L M Hui
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - S K W Chan
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - E M H Lee
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - Y N Suen
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
| | - E Y H Chen
- Department of Psychiatry, The University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
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29
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Jimeno N, Gomez-Pilar J, Poza J, Hornero R, Vogeley K, Meisenzahl E, Haidl T, Rosen M, Klosterkötter J, Schultze-Lutter F. Main Symptomatic Treatment Targets in Suspected and Early Psychosis: New Insights From Network Analysis. Schizophr Bull 2020; 46:884-895. [PMID: 32010940 PMCID: PMC7345824 DOI: 10.1093/schbul/sbz140] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The early detection and intervention in psychoses prior to their first episode are presently based on the symptomatic ultra-high-risk and the basic symptom criteria. Current models of symptom development assume that basic symptoms develop first, followed by attenuated and, finally, frank psychotic symptoms, though interrelations of these symptoms are yet unknown. Therefore, we studied for the first time their interrelations using a network approach in 460 patients of an early detection service (mean age = 26.3 y, SD = 6.4; 65% male; n = 203 clinical high-risk [CHR], n = 153 first-episode psychosis, and n = 104 depression). Basic, attenuated, and frank psychotic symptoms were assessed using the Schizophrenia Proneness Instrument, Adult version (SPI-A), the Structured Interview for Psychosis-Risk Syndromes (SIPS), and the Positive And Negative Syndrome Scale (PANSS). Using the R package qgraph, network analysis of the altogether 86 symptoms revealed a single dense network of highly interrelated symptoms with 5 discernible symptom subgroups. Disorganized communication was the most central symptom, followed by delusions and hallucinations. In line with current models of symptom development, the network was distinguished by symptom severity running from SPI-A via SIPS to PANSS assessments. This suggests that positive symptoms developed from cognitive and perceptual disturbances included basic symptom criteria. Possibly conveying important insight for clinical practice, central symptoms, and symptoms "bridging" the association between symptom subgroups may be regarded as the main treatment targets, in order to prevent symptomatology from spreading or increasing across the whole network.
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Affiliation(s)
- Natalia Jimeno
- Department of Psychiatry, School of Medicine University of Valladolid, Valladolid, Spain
- Department of Psychiatry and Psychotherapy, Medical Faculty Heinrich-Heine University, Düsseldorf, Germany
- GINCS, Research Group on Clinical Neuroscience of Segovia, Segovia, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- CIBER-BBN, Centro de Investigacion Biomedica en Red-Bioingenieria, Biomateriales y Biomedicina, Valladolid, Spain
| | - Jesus Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- CIBER-BBN, Centro de Investigacion Biomedica en Red-Bioingenieria, Biomateriales y Biomedicina, Valladolid, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- CIBER-BBN, Centro de Investigacion Biomedica en Red-Bioingenieria, Biomateriales y Biomedicina, Valladolid, Spain
| | - Kai Vogeley
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne University of Cologne, Cologne, Germany
- INM3, Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty Heinrich-Heine University, Düsseldorf, Germany
| | - Theresa Haidl
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne University of Cologne, Cologne, Germany
| | - Marlene Rosen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne University of Cologne, Cologne, Germany
| | - Joachim Klosterkötter
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne University of Cologne, Cologne, Germany
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty Heinrich-Heine University, Düsseldorf, Germany
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Soares GH, Santiago PHR, Michel-Crosato E, Jamieson L. The utility of network analysis in the context of Indigenous Australian oral health literacy. PLoS One 2020; 15:e0233972. [PMID: 32492049 PMCID: PMC7269264 DOI: 10.1371/journal.pone.0233972] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 05/17/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND The study of oral health literacy (OHL) is likely to gain new and interesting insights with the use of network analysis, a powerful analytical tool that allows the investigation of complex systems of relationships. Our aim was to investigate the relationships between oral health literacy and oral health-related factors in a sample of Indigenous Australian adults using a network analysis approach. METHODS Data from 400 Indigenous Australian adults was used to estimate four regularised partial correlation networks. Initially, a network with the 14 items of the Health Literacy in Dentistry scale (HeLD-14) was estimated. In a second step, psychosocial, sociodemographic and oral health-related factors were included in the network. Finally, two networks were estimated for participants with high and low oral health literacy. Participants were categorised into 'high' or 'low' OHL networks based on a median split. Centrality measures, clustering coefficients, network stability, and edge accuracy were evaluated. A permutation-based test was used to test differences between networks. RESULTS Solid connections among HeLD-14 items followed the structure of theoretical domains across all networks. Oral health-related self-efficacy, sporting activities, and self-rated oral health status were the strongest positively associated nodes with items of the HeLD-14 scale. HeLD-14 items were the four most central nodes in both HeLD-14 + covariates network and high OHL network, but not in the low OHL network. Differences between high and low OHL models were observed in terms of overall network structure, edge weight, and clustering coefficient. CONCLUSION Network models captured the dynamic relationships between oral health literacy and psychosocial, sociodemographic and oral health-related factors. Discussion on the implications of these findings for informing the development of targeted interventions to improve oral health literacy is presented.
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Affiliation(s)
| | | | | | - Lisa Jamieson
- Australian Research Centre for Population Oral Health, The University of Adelaide, Adelaide, South Australia, Australia
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Peralta V, Gil-Berrozpe GJ, Librero J, Sánchez-Torres A, Cuesta MJ. The Symptom and Domain Structure of Psychotic Disorders: A Network Analysis Approach. ACTA ACUST UNITED AC 2020. [DOI: 10.1093/schizbullopen/sgaa008] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Abstract
Little is understood about the symptom network structure of psychotic disorders. In the current study, we aimed to examine the network structure of psychotic symptoms in a broad and transdiagnostic sample of subjects with psychotic disorders (n = 2240) and to determine whether network structure parameters vary across demographic, sampling method and clinical variables. Gaussian graphical models were estimated for 73 psychotic symptoms assessed using the Comprehensive Assessment of Symptoms and History. A 7-cluster solution (reality distortion, disorganization, catatonia, diminished expressivity, avolition/anhedonia, mania, and depression) best explained the underlying symptom structure of the network. Symptoms with the highest centrality estimates pertained to the disorganization and, to a lesser extent, negative domains. Most bridge symptoms pertained to the disorganization domain, which had a central position within the network and widespread connections with other psychopathological domains. A comparison of networks in subgroups of subjects defined by premorbid adjustment levels, treatment response, and course pattern significantly influenced both network global strength and network structure. The sampling method and diagnostic class influenced network structure but not network global strength. Subgroups of subjects with less densely connected networks had poorer outcomes or more illness severity than those with more densely connected networks. The network structure of psychotic features emphasizes the importance of disorganization symptoms as a central domain of psychopathology and raises the possibility that interventions that target these symptoms may prove of broad use across psychopathology. The network structure of psychotic disorders is dependent on the sampling method and important clinical variables.
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Affiliation(s)
- Victor Peralta
- Mental Health Department, Servicio Navarro de Salud-Osasunbidea, Pamplona, Spain
- Navarrabiomed and Instituto de Investigación Sanitaria de Navarra (IdISNa), Pamplona, Spain
| | - Gustavo J Gil-Berrozpe
- Navarrabiomed and Instituto de Investigación Sanitaria de Navarra (IdISNa), Pamplona, Spain
- Psychiatry Service, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Julián Librero
- Navarrabiomed and Instituto de Investigación Sanitaria de Navarra (IdISNa), Pamplona, Spain
- Psychiatry Service, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Ana Sánchez-Torres
- Navarrabiomed and Instituto de Investigación Sanitaria de Navarra (IdISNa), Pamplona, Spain
- Psychiatry Service, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Manuel J Cuesta
- Navarrabiomed and Instituto de Investigación Sanitaria de Navarra (IdISNa), Pamplona, Spain
- Psychiatry Service, Complejo Hospitalario de Navarra, Pamplona, Spain
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Robinaugh DJ, Hoekstra RHA, Toner ER, Borsboom D. The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research. Psychol Med 2020; 50:353-366. [PMID: 31875792 PMCID: PMC7334828 DOI: 10.1017/s0033291719003404] [Citation(s) in RCA: 292] [Impact Index Per Article: 73.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.
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Affiliation(s)
- Donald J. Robinaugh
- Massachusetts General Hospital, Department of Psychiatry
- Harvard Medical School
| | | | - Emma R. Toner
- Massachusetts General Hospital, Department of Psychiatry
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Papini S, Rubin M, Telch MJ, Smits JAJ, Hien DA. Pretreatment Posttraumatic Stress Disorder Symptom Network Metrics Predict the Strength of the Association Between Node Change and Network Change During Treatment. J Trauma Stress 2020; 33:64-71. [PMID: 31343789 DOI: 10.1002/jts.22379] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 06/29/2018] [Accepted: 07/06/2018] [Indexed: 01/14/2023]
Abstract
Network analysis has been increasingly applied in an effort to understand complex interactions among symptoms in posttraumatic stress disorder (PTSD). Although methods that initially focused on identifying central symptoms in cross-sectional networks have been extended to longitudinal data that can reveal the relative roles of acute symptoms in the emergence of the PTSD syndrome, the association between network metrics and symptom change during treatment have yet to be explored in PTSD. To address this gap, we estimated pretreatment PTSD symptom networks in a sample of patients from a multisite clinical trial for women with full or subthreshold PTSD and substance use. We tested the hypothesis that node metrics calculated in the pretreatment network would be predictive of the strength of the association between a symptom's change and the change in the severity of all other symptoms through the course of treatment. A symptom node's strength and predictability in the pretreatment network were each strongly correlated with the association between that symptom's change and overall change across the symptom network, r(15) = .79, p < .001 and r(15) = .75, p < .001, respectively, whereas a symptom's mean severity at pretreatment was not, r(15) = .27, p = .292. These findings suggest that a node's centrality prior to treatment engagement is a predictor of its association with overall symptom change throughout the treatment process.
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Affiliation(s)
- Santiago Papini
- Institute for Mental Health Research and Department of Psychology, University of Texas at Austin, Austin, Texas, USA
| | - Mikael Rubin
- Institute for Mental Health Research and Department of Psychology, University of Texas at Austin, Austin, Texas, USA
| | - Michael J Telch
- Institute for Mental Health Research and Department of Psychology, University of Texas at Austin, Austin, Texas, USA
| | - Jasper A J Smits
- Institute for Mental Health Research and Department of Psychology, University of Texas at Austin, Austin, Texas, USA
| | - Denise A Hien
- Center of Alcohol Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.,Columbia University College of Physicians and Surgeons, New York, New York, USA
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Jongeneel A, Aalbers G, Bell I, Fried EI, Delespaul P, Riper H, van der Gaag M, van den Berg D. A time-series network approach to auditory verbal hallucinations: Examining dynamic interactions using experience sampling methodology. Schizophr Res 2020; 215:148-156. [PMID: 31780345 DOI: 10.1016/j.schres.2019.10.055] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/23/2019] [Accepted: 10/29/2019] [Indexed: 12/16/2022]
Abstract
BACKGROUND Identifying variables that influence daily-life fluctuations in auditory verbal hallucinations (AVHs) provides insight into potential mechanisms and targets for intervention. Network analysis, that uses time-series data collected by Experience Sampling Method (ESM), could be used to examine relations between multiple variables over time. METHODS 95 daily voice-hearing individuals filled in a short questionnaire ten times a day for six consecutive days at pseudo-random moments. Using multilevel vector auto-regression, relations between voice-hearing and negative affect, positive affect, uncontrollable thoughts, dissociation, and paranoia were analysed in three types of networks: between-subjects (between persons, undirected), contemporaneous (within persons, undirected), and temporal (within persons, directed) networks. Strength centrality was measured to identify the most interconnected variables in the models. RESULTS Voice-hearing co-occurred with all variables, while on a 6-day period voice-hearing was only related to uncontrollable thoughts. Voice-hearing was not predicted by any of the factors, but it did predict uncontrollable thoughts and paranoia. All variables showed large autoregressions, i.e. mainly predicted themselves in this severe voice-hearing sample. Uncontrollable thoughts was the most interconnected factor, though relatively uninfluential. DISCUSSION Severe voice-hearing might be mainly related to mental state factors on the short-term. Once activated, voice-hearing appears to maintain itself. It is important to assess possible reactivity of AVH to triggers at the start of therapy; if reactive, therapy should focus on the triggering factor. If not reactive, Cognitive Behavioural interventions could be used first to reduce the negative effects of the voices. Limitations are discussed.
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Affiliation(s)
- Alyssa Jongeneel
- Department of Clinical Psychology, Amsterdam UMC, Amsterdam Public Health Research Institute, Van der Boechorstraat 7, 1081 BT, Amsterdam, the Netherlands; Parnassia Psychiatric Institute, Zoutkeetsingel 40, 2512 HN, Den Haag, the Netherlands.
| | - George Aalbers
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, the Netherlands
| | - Imogen Bell
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
| | - Eiko I Fried
- Department of Clinical Psychology, Leiden University, the Netherlands
| | - Philippe Delespaul
- Maastricht University, PO Box 616, 6226 NB, Maastricht, the Netherlands; Mondriaan, PO Box 4436 6401, CX, Heerlen, the Netherlands
| | - Heleen Riper
- Department of Clinical Psychology, Amsterdam UMC, Amsterdam Public Health Research Institute, Van der Boechorstraat 7, 1081 BT, Amsterdam, the Netherlands; Department of Research and Innovation, GGZ InGeest Specialized Mental Health Care, Amsterdam, the Netherlands
| | - Mark van der Gaag
- Department of Clinical Psychology, Amsterdam UMC, Amsterdam Public Health Research Institute, Van der Boechorstraat 7, 1081 BT, Amsterdam, the Netherlands; Parnassia Psychiatric Institute, Zoutkeetsingel 40, 2512 HN, Den Haag, the Netherlands
| | - David van den Berg
- Department of Clinical Psychology, Amsterdam UMC, Amsterdam Public Health Research Institute, Van der Boechorstraat 7, 1081 BT, Amsterdam, the Netherlands; Parnassia Psychiatric Institute, Zoutkeetsingel 40, 2512 HN, Den Haag, the Netherlands
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Levi-Belz Y, Greene T, Zerach G. Associations between moral injury, PTSD clusters, and depression among Israeli veterans: a network approach. Eur J Psychotraumatol 2020; 11:1736411. [PMID: 32313614 PMCID: PMC7155211 DOI: 10.1080/20008198.2020.1736411] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 01/26/2020] [Accepted: 02/23/2020] [Indexed: 12/12/2022] Open
Abstract
Background: Moral Injury (MI) is one of the adverse consequences of combat. Following exposure to potentially morally injurious events (PMIEs)--events perceived as violations of deep moral beliefs by oneself or trusted individuals--a significant minority of veterans could develop posttraumatic stress disorder (PTSD) and depression. Objective: The current study represents the first attempt to apply a network analysis model to examine an exploratory empirical conceptualization of a network of PMIEs during military service, post-traumatic stress disorder (PTSD) symptom clusters, depression, and combat exposure among Israel Defence Forces veterans. Method: A volunteer sample of 191 Israeli combat veterans were recruited during 2017, and completed validated self-report questionnaires tapping PMIEs, PTSD, and depression in a cross-sectional design study. A regularized Gaussian graphical model was estimated. Results: Network analysis revealed strong bridge associations between the PTSD nodes and most of the PMIEs nodes. The nodes of PMIE-betrayal and PTSD negative alterations in cognitions and mood (NACM) symptom cluster were found to have a bridging function between other PMIEs and PTSD. Depression was found to be connected to most of the PMIEs and PTSD nodes. Conclusions: The study's findings offer an overview of the complex relationships between PMIEs and PTSD clusters among Israeli veterans. PMIEs--notably, betrayal-based experiences--are related to PTSD clusters directly and through depressive symptoms. Some possible mechanisms for the links between PMIEs and PTSD and the clinical implications related to specific interventions are discussed.
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Affiliation(s)
- Yossi Levi-Belz
- Department of Behavioral Sciences, Ruppin Academic Center, Emek Hefer, Israel.,The Lior Tsfaty Center for Suicide and Mental Pain Studies, Ruppin Academic Center, Emek Hefer, Israel
| | - Talya Greene
- Department of Community Mental Health, University of Haifa, Haifa, Israel
| | - Gadi Zerach
- Department of Behavioral Sciences, Ariel University, Ariel, Israel
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36
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Jiang W, Ren Z, Yu L, Tan Y, Shi C. A Network Analysis of Post-traumatic Stress Disorder Symptoms and Correlates During the COVID-19 Pandemic. Front Psychiatry 2020; 11:568037. [PMID: 33240124 PMCID: PMC7683419 DOI: 10.3389/fpsyt.2020.568037] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 09/29/2020] [Indexed: 12/14/2022] Open
Abstract
Background and Objective: The coronavirus disease 2019 (COVID-19) outbreak has been suggested as a collective trauma, which presents a continuing crisis. However, the specific post-traumatic implication of this crisis has not been adequately studied yet. The current study was aimed to ascertain the most central symptom and the strong connections between symptoms of post-traumatic stress disorder (PTSD). At the same time, exploring the relationship between covariates and the network of PTSD symptoms, by taking sex, anxiety, depression, suicidal ideation, quality of life, and social support as covariates, may help us to know the arise and maintenance of PTSD symptoms and give specified suggestions to people under the shadow of COVID-19. Method: The Post-traumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was used to assess the PTSD symptoms extent of 338 healthy participants over the past month. Networks were analyzed using state-of-the-art regularized partial correlation models. In addition, the centrality of the symptoms and the robustness of the results were analyzed. Results: The network analysis revealed that the especially strong connections emerged between avoidance of thoughts and avoidance of reminders, hypervigilance and exaggerated startle response, intrusive thoughts and nightmares, flashbacks and emotional cue reactivity, and detachment and restricted affect. The most central symptoms were self-destructive/reckless behavior. Incorporation of covariates into the network revealed the strong connections path between self-destructive/reckless behavior and loss of interest and depression. Conclusion: Self-destructive/reckless behavior was the most central symptom in the network of PTSD symptoms related to the COVID-19 pandemic, which as an important target of interfere may have great benefits.
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Affiliation(s)
- Wanyue Jiang
- School of Psychology, Central China Normal University, Wuhan, China.,Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan, China
| | - Zhihong Ren
- School of Psychology, Central China Normal University, Wuhan, China.,Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan, China
| | - Lixia Yu
- School of Psychology, Central China Normal University, Wuhan, China.,Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan, China.,Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan, China
| | - Yafei Tan
- School of Psychology, Central China Normal University, Wuhan, China.,Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan, China.,Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan, China
| | - Congrong Shi
- School of Psychology, Central China Normal University, Wuhan, China.,Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan, China
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37
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Perko VL, Forbush KT, Siew CSQ, Tregarthen JP. Application of network analysis to investigate sex differences in interactive systems of eating-disorder psychopathology. Int J Eat Disord 2019; 52:1343-1352. [PMID: 31608479 DOI: 10.1002/eat.23170] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 08/09/2019] [Accepted: 08/13/2019] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Although men comprise 25% of persons with eating disorders (EDs), most research has focused on understanding EDs in women. The theoretical framework underlying common ED treatment has not been rigorously tested in men. The purpose of this study was to compare the interconnectivity among ED symptoms in men versus women. METHOD Participants (N = 1,348; 50% men) were individuals with anorexia nervosa, bulimia nervosa, binge-eating disorder, or other specified feeding or eating disorder who were users of Recovery Record, a smartphone app for monitoring ED symptoms. Participants were matched on age and duration of illness. Network analysis was used to create networks of symptoms for both sexes. Strength centrality, network stability, and bootstrapped centrality differences were tested. The network comparison test (NCT) was used to identify sex differences between networks. Key players analysis was used to compare fragmentation of each network. RESULTS For both sexes, items related to binge eating and restricting emerged as highest in strength centrality. The NCT identified significant differences global strength (p = .03) but not network invariance (p = .06) suggesting that although the structure of the networks was not statistically different, the strength of the connections within the network was greater for women. Key players analysis indicated that both networks were similarly disrupted when important nodes within the network were removed. DISCUSSION Findings suggested that there are more similarities than differences in networks of EDs in men and women. Results have important clinical implications by supporting theoretical underpinnings of cognitive-behavioral models of EDs in both men and women.
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Affiliation(s)
- Victoria L Perko
- Department of Psychology, University of Kansas, Lawrence, Kansas
| | - Kelsie T Forbush
- Department of Psychology, University of Kansas, Lawrence, Kansas
| | - Cynthia S Q Siew
- Department of Psychology, National University of Singapore, Singapore
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38
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Rodríguez-Testal JF, Perona-Garcelán S, Dollfus S, Valdés-Díaz M, García-Martínez J, Ruíz-Veguilla M, Senín-Calderón C. Spanish validation of the self-evaluation of negative symptoms scale SNS in an adolescent population. BMC Psychiatry 2019; 19:327. [PMID: 31664965 PMCID: PMC6819523 DOI: 10.1186/s12888-019-2314-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 10/09/2019] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Negative symptoms (NS) may be observed in the general population in an attenuated form and in high-risk mental states. However, they have been less studied in the general population than positive symptoms, in spite of their importance at the insidious onset of schizophrenia and their appearance before positive symptoms. This study aimed to analyze the empirical structure of the Spanish version of the Self-Evaluation of Negative Symptoms (SNS) Scale and find its psychometric properties and invariance of measurement across sex and age in a sample of adolescents. METHODS The sample consisted of 4521 adolescents (53.6% female) from 11 to 18 years of age. RESULTS Confirmatory Factor Analysis of the SNS confirmed an internal structure of five first-order factors by the characteristic dimensions of NS: avolition, social withdrawal, diminished emotional range, anhedonia, alogia, and one second-order factor which includes the total NS score. Multi-group confirmatory factor analysis showed that the scale was invariant across sex and age. Total scale reliability was adequate. A strong relationship was found between the SNS with depressive symptomatology, moderate with ideas of reference and low with aberrant salience. CONCLUSION The results back use of the Spanish version of the SNS scale for detection of NS in the general population of adolescents.
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Affiliation(s)
- Juan F. Rodríguez-Testal
- Personality, Evaluation and Psychological Treatment Department, University of Seville, Seville, Spain. Av. Camilo José Cela, 41018 Seville, SN Spain
| | - Salvador Perona-Garcelán
- Virgen del Rocío Outpatient Mental Hospital, University Hospital Virgen del Rocío, Avenue Manuel Siurot, 41013 Seville, SN Spain
| | - Sonia Dollfus
- CHU de Caen, Service universitaire de Psychiatrie, Centre Esquirol, Avenue Côte de Nacre, F-14000 Caen, France
- UNICAEN, UFR Médecine, F-14074 Caen, France
| | - María Valdés-Díaz
- Department of Psychology, University of Cadiz, Avenue República Árabe Saharaui SN. 11510 Puerto Real, Cádiz, Spain
| | - Jesús García-Martínez
- Department of Psychology, University of Cadiz, Avenue República Árabe Saharaui SN. 11510 Puerto Real, Cádiz, Spain
| | - Miguel Ruíz-Veguilla
- Virgen del Rocío Outpatient Mental Hospital, University Hospital Virgen del Rocío, Avenue Manuel Siurot, 41013 Seville, SN Spain
| | - Cristina Senín-Calderón
- Department of Psychology, University of Cadiz, Avenue República Árabe Saharaui SN. 11510 Puerto Real, Cádiz, Spain
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Contreras A, Nieto I, Valiente C, Espinosa R, Vazquez C. The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review. PSYCHOTHERAPY AND PSYCHOSOMATICS 2019; 88:71-83. [PMID: 30889609 DOI: 10.1159/000497425] [Citation(s) in RCA: 205] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 01/29/2019] [Indexed: 11/19/2022]
Abstract
BACKGROUND Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. METHODS Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of "network analysis" with the terms "anxiety," "affective disorders," "depression," "schizophrenia," "psychosis," "personality disorders," "substance abuse" and "psychopathology." RESULTS The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. CONCLUSIONS A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.
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Affiliation(s)
- Alba Contreras
- Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain
| | - Ines Nieto
- Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain
| | - Carmen Valiente
- Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain,
| | - Regina Espinosa
- Department of Psychology, School of Education and Health, Camilo José Cela University, Madrid, Spain
| | - Carmelo Vazquez
- Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain
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Kan KJ, van der Maas HL, Levine SZ. Extending psychometric network analysis: Empirical evidence against g in favor of mutualism? INTELLIGENCE 2019. [DOI: 10.1016/j.intell.2018.12.004] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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41
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Coêlho BM, Santana GL, Duarte-Guerra LS, Viana MC, Neto FL, Andrade LH, Wang YP. The role of gender in the structure of networks of childhood adversity. Psychiatry Res 2018; 270:348-356. [PMID: 30293013 DOI: 10.1016/j.psychres.2018.09.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 08/16/2018] [Accepted: 09/25/2018] [Indexed: 11/27/2022]
Abstract
The objective of present study is to investigate the relationship between different childhood adversities. The potential impact of early adversity on prevention programs is discussed. Data on twelve childhood adversities was collected from a representative sample of 5037 members of the general population living in a large metropolitan area. Data were analyzed through network analysis, to estimate and compare network connectivity and centrality measures by gender. Over half the respondents had been exposed to at least one adversity during their earlier developmental stage. Among adversity-exposed persons, 48.4% presented simultaneous adversities, most of which were related to 'family dysfunction' and 'maltreatment' (mean = 2.9 adversities). Women reported more adversities than men (59.0% vs. 47.6%). Although the 'global' network connectivity across adversities was similar in both genders, 'regional' distinctions in the network structure were found. While 'neglect' and 'parental death' were more important for women than men, 'parental mental disorders' was more important for men. Gender-related childhood adversities were clustered experiences. Adversities related to 'early family dysfunction' and 'maltreatment' were prominent features in the networks of both boys and girls. Differential preventive and intervention programs should take into account gender-related patterns of exposure and reporting patterns of early adversity.
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Affiliation(s)
- Bruno Mendonça Coêlho
- Nucleo de Epidemiologia Psiquiatrica (LIM-23), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Departamento de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
| | - Geilson Lima Santana
- Nucleo de Epidemiologia Psiquiatrica (LIM-23), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Leorides Severo Duarte-Guerra
- Nucleo de Epidemiologia Psiquiatrica (LIM-23), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Maria Carmen Viana
- Department of Social Medicine Post-Graduate Program in Public Health, Health Sciences Center, Universidade Federal do Espírito Santo, Vitória, ES, Brazil
| | - Francisco Lotufo Neto
- Departamento de Psiquiatria, Faculdade de Medicina (FMUSP), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Laura Helena Andrade
- Nucleo de Epidemiologia Psiquiatrica (LIM-23), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Yuan-Pang Wang
- Nucleo de Epidemiologia Psiquiatrica (LIM-23), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
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Fonseca-Pedrero E, Ortuño J, Debbané M, Chan RCK, Cicero D, Zhang LC, Brenner C, Barkus E, Linscott RJ, Kwapil T, Barrantes-Vidal N, Cohen A, Raine A, Compton MT, Tone EB, Suhr J, Inchausti F, Bobes J, Fumero A, Giakoumaki S, Tsaousis I, Preti A, Chmielewski M, Laloyaux J, Mechri A, Aymen Lahmar M, Wuthrich V, Larøi F, Badcock JC, Jablensky A, Isvoranu AM, Epskamp S, Fried EI. The Network Structure of Schizotypal Personality Traits. Schizophr Bull 2018; 44:S468-S479. [PMID: 29684178 PMCID: PMC6188518 DOI: 10.1093/schbul/sby044] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Elucidating schizotypal traits is important if we are to understand the various manifestations of psychosis spectrum liability and to reliably identify individuals at high risk for psychosis. The present study examined the network structures of (1) 9 schizotypal personality domains and (2) 74 individual schizotypal items, and (3) explored whether networks differed across gender and culture (North America vs China). The study was conducted in a sample of 27001 participants from 12 countries and 21 sites (M age = 22.12; SD = 6.28; 37.5% males). The Schizotypal Personality Questionnaire (SPQ) was used to assess 74 self-report items aggregated in 9 domains. We used network models to estimate conditional dependence relations among variables. In the domain-level network, schizotypal traits were strongly interconnected. Predictability (explained variance of each node) ranged from 31% (odd/magical beliefs) to 55% (constricted affect), with a mean of 43.7%. In the item-level network, variables showed relations both within and across domains, although within-domain associations were generally stronger. The average predictability of SPQ items was 27.8%. The network structures of men and women were similar (r = .74), node centrality was similar across networks (r = .90), as was connectivity (195.59 and 199.70, respectively). North American and Chinese participants networks showed lower similarity in terms of structure (r = 0.44), node centrality (r = 0.56), and connectivity (180.35 and 153.97, respectively). In sum, the present article points to the value of conceptualizing schizotypal personality as a complex system of interacting cognitive, emotional, and affective characteristics.
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Affiliation(s)
- Eduardo Fonseca-Pedrero
- Department of Educational Sciences, University of La Rioja, La Rioja, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Oviedo, Spain
| | - Javier Ortuño
- Department of Educational Sciences, University of La Rioja, La Rioja, Spain
| | - Martin Debbané
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - David Cicero
- Department of Psychology, University of Hawaii at Manoa
| | - Lisa C Zhang
- Department of Psychology, University of British Columbia, Canada
| | - Colleen Brenner
- Department of Psychology, University of British Columbia, Canada
| | - Emma Barkus
- School of Psychology, University of Wollongong, Wollongong, Australia
| | | | - Thomas Kwapil
- Department of Psychology, University of North Carolina at Greensboro, Greensboro, NC
| | - Neus Barrantes-Vidal
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alex Cohen
- Department of Psychology, Louisiana State University, Louisiana, LA
| | - Adrian Raine
- Department of Criminology, University of Pennsylvania
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
- Department of Psychology, University of Pennsylvania
| | | | - Erin B Tone
- Department of Psychology, Georgia State University, Atlanta, GA
| | - Julie Suhr
- Department of Psychology, Ohio University Athens, OH
| | - Felix Inchausti
- Department of Medicine, University of Navarra, Pamplona, Spain
| | - Julio Bobes
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Oviedo, Spain
- Department of Psychiatry, University of Oviedo, Oviedo, Spain
| | - Axit Fumero
- Department of Psychology, University of La Laguna, Tenerife, Spain
| | | | | | | | | | - Julien Laloyaux
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- NORMENT—Norwegian Center of Excellence for Mental Disorders Research, University of Oslo, Oslo, Norway
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège, Belgium
| | - Anwar Mechri
- Psychiatry Department, University Hospital of Monastir, Monastir, Tunisia
| | | | - Viviana Wuthrich
- Centre for Emotional Health, Department of Psychology, Macquarie University, Sydney, Australia
| | - Frank Larøi
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- NORMENT—Norwegian Center of Excellence for Mental Disorders Research, University of Oslo, Oslo, Norway
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège, Belgium
| | - Johanna C Badcock
- Centre for Clinical Research in Neuropsychiatry, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Australia
| | - Assen Jablensky
- Centre for Clinical Research in Neuropsychiatry, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Australia
| | - Adela M Isvoranu
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Sacha Epskamp
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Eiko I Fried
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
- Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
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Abstract
BACKGROUND Conceptualizing posttraumatic stress disorder (PTSD) symptoms as a dynamic system of causal elements could provide valuable insights into the way that PTSD develops and is maintained in traumatized individuals. We present the first study to apply a multilevel network model to produce an exploratory empirical conceptualization of dynamic networks of PTSD symptoms, using data collected during a period of conflict. METHODS Intensive longitudinal assessment data were collected during the Israel-Gaza War in July-August 2014. The final sample (n = 96) comprised a general population sample of Israeli adult civilians exposed to rocket fire. Participants completed twice-daily reports of PTSD symptoms via smartphone for 30 days. We used a multilevel vector auto-regression model to produce contemporaneous and temporal networks, and a partial correlation network model to obtain a between-subjects network. RESULTS Multilevel network analysis found strong positive contemporaneous associations between hypervigilance and startle response, avoidance of thoughts and avoidance of reminders, and between flashbacks and emotional reactivity. The temporal network indicated the central role of startle response as a predictor of future PTSD symptomatology, together with restricted affect, blame, negative emotions, and avoidance of thoughts. There were some notable differences between the temporal and contemporaneous networks, including the presence of a number of negative associations, particularly from blame. The between-person network indicated flashbacks and emotional reactivity to be the most central symptoms. CONCLUSIONS This study suggests various symptoms that could potentially be driving the development of PTSD. We discuss clinical implications such as identifying particular symptoms as targets for interventions.
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Affiliation(s)
- Talya Greene
- Department of Community Mental Health,University of Haifa,Haifa,Israel
| | - Marc Gelkopf
- Department of Community Mental Health,University of Haifa,Haifa,Israel
| | - Sacha Epskamp
- Department of Psychology,University of Amsterdam,Amsterdam,The Netherlands
| | - Eiko Fried
- Department of Psychology,University of Amsterdam,Amsterdam,The Netherlands
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Quality of life disparities between persons with schizophrenia and their professional caregivers: Network analysis in a National Cohort. Schizophr Res 2018; 197:109-115. [PMID: 29325726 DOI: 10.1016/j.schres.2017.12.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 09/28/2017] [Accepted: 12/26/2017] [Indexed: 01/25/2023]
Abstract
BACKGROUND Disparities between mental health patients and their professional caregivers in quality of life appraisals have been identified, however, the structure that such disparities assume is unknown. AIMS To examine the network structure of quality of life appraisals and disparities using network analysis. METHODS Participants were 1639 persons with schizophrenia using psychiatric rehabilitation services and their primary professional caregivers (N=582). Quality of life for persons with schizophrenia was measured based on an abbreviated version of the Manchester Short Assessment of Quality of Life. Appraisals were made self-reported and by professional caregivers. Disparities scores between the aforementioned were computed. Network analysis was performed on all quality of life appraisals. Sensitivity analyses were conducted. RESULTS The self-appraised network significantly (p<0.05) differed by network strength compared to the caregiver-appraised network. Self-appraised network communities (clusters of quality of life items) were health conditions and socioeconomic system, whereas caregiver-appraised network communities were social activities, and combined socioeconomic and health conditions. Strength centrality was highest for self-appraised social status and for caregiver-appraised residential status (Z=1.63, Z=1.12, respectively). The disparity scores network clustered into two communities: social relations and combined financial and health conditions. The most central appraisal disparities were in social status. CONCLUSIONS Quality of life differed when self-appraised by persons with schizophrenia compared to when appraised by their professional caregivers, yet the salient role of social relations was shared. The latter may be an initial focus of discussion by persons with schizophrenia and their caregivers.
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van Rooijen G, Isvoranu AM, Kruijt OH, van Borkulo CD, Meijer CJ, Wigman JTW, Ruhé HG, de Haan L, Cahn W, de Haan L, Kahn RS, Meijer C, Myin-Germeys I, van Os J, Bartels-Velthuis AA. A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders. Schizophr Res 2018; 193:232-239. [PMID: 28844638 DOI: 10.1016/j.schres.2017.07.035] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 07/14/2017] [Accepted: 07/15/2017] [Indexed: 12/18/2022]
Abstract
Depressive symptoms occur frequently in patients with schizophrenia. Several factor analytical studies investigated the associations between positive, negative and depressive symptoms and reported difficulties differentiating between these symptom domains. Here, we argue that a network approach may offer insights into these associations, by exploring interrelations between symptoms. The aims of current study were to I) construct a network of positive, negative and depressive symptoms in male patients with schizophrenia to investigate interactions between individual symptoms; II) identify the most central symptoms within this network and III) examine group-level differences in network connectivity between remitted and non-remitted patients. We computed a network of depressive, positive and negative symptoms in a sample of 470 male patients diagnosed with a psychotic disorder. Depressive symptoms were assessed with the Calgary Depression Rating Scale for Schizophrenia, while psychotic symptoms were assessed with the Positive and Negative Syndrome Scale. Networks of male patients who fulfilled remission criteria (Andreasen et al., 2005) and non-remitters for psychosis were compared. Our results indicate that depressive symptoms are mostly associated with suicidality and may act as moderator between psychotic symptoms and suicidality. In addition, 'depressed mood', 'observed depression', 'poor rapport', 'stereotyped thinking' and 'delusions' were central symptoms within the network. Finally, although remitted male patients had a similar network structure compared to non-remitters the networks differed significantly in terms of global strength. In conclusion, clinical symptoms of schizophrenia were linked in a stable way, independent of symptomatic remission while the number of connections appears to be dependent on remission status.
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Affiliation(s)
- Geeske van Rooijen
- University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands.
| | - Adela-Maria Isvoranu
- University of Amsterdam, Department of Psychology, Psychological Methods, Nieuwe Achtergracht 129-B, 1018 WT Amsterdam, The Netherlands.
| | - Olle H Kruijt
- University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands.
| | - Claudia D van Borkulo
- University of Amsterdam, Department of Psychology, Psychological Methods, Nieuwe Achtergracht 129-B, 1018 WT Amsterdam, The Netherlands; University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Hanzeplein 1, 9700 RB Groningen, The Netherlands.
| | - Carin J Meijer
- University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands.
| | - Johanna T W Wigman
- University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Hanzeplein 1, 9700 RB Groningen, The Netherlands.
| | - Henricus G Ruhé
- University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands; Warneford Hospital, Department of Psychiatry, University of Oxford, United Kingdom.
| | - Lieuwe de Haan
- University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands.
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A symptom network structure of the psychosis spectrum. Schizophr Res 2017; 189:75-83. [PMID: 28237606 DOI: 10.1016/j.schres.2017.02.018] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 02/10/2017] [Accepted: 02/13/2017] [Indexed: 12/25/2022]
Abstract
Current diagnostic systems mainly focus on symptoms needed to classify patients with a specific mental disorder and do not take into account the variation in co-occurring symptoms and the interaction between the symptoms themselves. The innovative network approach aims to further our understanding of mental disorders by focusing on meaningful connections between individual symptoms of a disorder and has thus far proven valuable insights to psychopathology. The aims of current study were to I) construct a symptom network and investigate interactions between a wide array of psychotic symptoms; II) identify the most important symptoms within this network and III) perform an explorative shortest pathway analysis between depressive and delusional symptoms. We analyzed interview data from n=408 male patients with non-affective psychosis using the Comprehensive Assessment of Symptoms and History (CASH). A network structure of 79 symptoms was computed to explore partial correlations between positive, negative, catatonia and affective symptoms. The resulting network showed strong connectivity between individual symptoms of the CASH, both within- and between-domains. Most central symptoms included 'loss of interest', 'chaotic speech', 'inability to enjoy recreational interest in activities', 'inability to form or maintain relationships with friends' and 'poverty of content of speech'. The shortest pathway analysis between depressive and delusional symptoms displayed an important role for 'persecutory delusions'. In conclusion, this study showed that individual psychotic symptoms are meaningfully related to each other not only within their own cluster, but also between different clusters and that important information may be acquired by investigating interactions at a symptom level.
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Fonseca-Pedrero E. Análisis de redes: ¿una nueva forma de comprender la psicopatología? REVISTA DE PSIQUIATRIA Y SALUD MENTAL 2017; 10:206-215. [DOI: 10.1016/j.rpsm.2017.06.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Revised: 06/26/2017] [Accepted: 06/27/2017] [Indexed: 01/15/2023]
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