1
|
Nunes A, Pavlova B, Cunningham JEA, Nuñez JJ, Quilty LC, Foster JA, Harkness KL, Ho K, Lam RW, Li QS, Milev R, Rotzinger S, Soares CN, Taylor VH, Turecki G, Kennedy SH, Frey BN, Rudzicz F, Uher R. Depression-Anxiety Coupling Strength as a predictor of relapse in major depressive disorder: A CAN-BIND wellness monitoring study report. J Affect Disord 2024; 361:189-197. [PMID: 38866253 DOI: 10.1016/j.jad.2024.06.023] [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: 02/05/2024] [Revised: 06/01/2024] [Accepted: 06/05/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND A critical challenge in the study and management of major depressive disorder (MDD) is predicting relapse. We examined the temporal correlation/coupling between depression and anxiety (called Depression-Anxiety Coupling Strength, DACS) as a predictor of relapse in patients with MDD. METHODS We followed 97 patients with remitted MDD for an average of 394 days. Patients completed weekly self-ratings of depression and anxiety symptoms using the Quick Inventory of Depressive Symptoms (QIDS-SR) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Using these longitudinal ratings we computed DACS as random slopes in a linear mixed effects model reflecting individual-specific degree of correlation between depression and anxiety across time points. We then tested DACS as an independent variable in a Cox proportional hazards model to predict relapse. RESULTS A total of 28 patients (29 %) relapsed during the follow-up period. DACS significantly predicted confirmed relapse (hazard ratio [HR] 1.5, 95 % CI [1.01, 2.22], p = 0.043; Concordance 0.79 [SE 0.04]). This effect was independent of baseline depressive or anxiety symptoms or their average levels over the follow-up period, and was identifiable more than one month before relapse onset. LIMITATIONS Small sample size, in a single study. Narrow phenotype and comorbidity profiles. CONCLUSIONS DACS may offer opportunities for developing novel strategies for personalized monitoring, early detection, and intervention. Future studies should replicate our findings in larger, diverse patient populations, develop individual patient prediction models, and explore the underlying mechanisms that govern the relationship of DACS and relapse.
Collapse
Affiliation(s)
- Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada; Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; Mood Disorders Program, Nova Scotia Health Authority, Halifax, NS, Canada.
| | - Barbara Pavlova
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada; Mood Disorders Program, Nova Scotia Health Authority, Halifax, NS, Canada
| | | | - John-Jose Nuñez
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lena C Quilty
- Campbell Family Mental Health Research Institute, CAMH, Toronto, ON, Canada
| | - Jane A Foster
- Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Treatment and Research Centre, St. Joseph's Healthcare Hamilton, ON, Canada; Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, Ontario, Canada
| | - Keith Ho
- Mood Disorders Treatment and Research Centre, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Qingqin S Li
- Neuroscience, Janssen Research & Development, LLC, Titusville, NJ, USA
| | - Roumen Milev
- Department of Psychiatry, Providence Care, Queen's University, Kingston, ON, Canada
| | - Susan Rotzinger
- Mood Disorders Treatment and Research Centre, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Claudio N Soares
- Department of Psychiatry, Providence Care, Queen's University, Kingston, ON, Canada
| | - Valerie H Taylor
- Cumming School of Medicine, Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Gustavo Turecki
- Douglas Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Treatment and Research Centre, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Frank Rudzicz
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada; Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada; Mood Disorders Program, Nova Scotia Health Authority, Halifax, NS, Canada
| |
Collapse
|
2
|
Li R, Shi C, Yang W, Liu X, Ren Z. Network Analysis of Depressive Symptoms in Chinese Sexual Minority Women During the COVID-19 Pandemic: An Intra-Group Perspective. JOURNAL OF HOMOSEXUALITY 2024:1-17. [PMID: 38833635 DOI: 10.1080/00918369.2024.2359950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
The prevalence of depression among sexual minority women is a significant concern, yet no prior research has conducted a network analysis of depressive symptoms in this population. This is the first study to address this gap by examining the network structure of depressive symptoms in Chinese sexual minority women during the COVID-19 pandemic, considering both sexual orientation and gender expression as part of an intra-group perspective. 1420 Chinese sexual minority women completed the Center for Epidemiologic Studies Depressive Symptoms (CES-D). Network analysis was employed to calculate edge and centrality measures, and the network structures of lesbians and bisexual women were compared based on sexual orientation and of femme, androgyny, and butch based on gender expression. Network analysis revealed that the core depressive symptoms of Chinese sexual minority women are "Felt depressed," "Fatigue," "Sad," and "Failure." Although no significant differences were found in the network structure and global strength of depressive symptoms between different sexual orientations and gender expressions, there were significant differences in the core symptoms. This study suggests the unique associations between depressive symptoms and social and historical contexts among sexual minority women and emphasizes the importance of considering these differences when providing targeted mental health interventions.
Collapse
Affiliation(s)
- Rui Li
- Key Laboratory of Human Development and Mental Health of Hubei Province, School of Psychology, Central China Normal University, Wuhan, Hubei, China
- Key Laboratory of Adolescent CyberPsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
| | - Congrong Shi
- School of Educational Science, Anhui Normal University, Wuhu, Anhui, China
| | - Wanyi Yang
- School of Education, Nanchong Vocational College of Science and Technology, Nanchong, China
| | - Xinyi Liu
- Key Laboratory of Human Development and Mental Health of Hubei Province, School of Psychology, Central China Normal University, Wuhan, Hubei, China
- Key Laboratory of Adolescent CyberPsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
| | - Zhihong Ren
- Key Laboratory of Human Development and Mental Health of Hubei Province, School of Psychology, Central China Normal University, Wuhan, Hubei, China
- Key Laboratory of Adolescent CyberPsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
| |
Collapse
|
3
|
Mårtensson G, Johansson F, Buhrman M, Åhs F, Clason van de Leur J. A network analysis of exhaustion disorder symptoms throughout treatment. BMC Psychiatry 2024; 24:389. [PMID: 38783205 PMCID: PMC11112805 DOI: 10.1186/s12888-024-05842-9] [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: 11/10/2023] [Accepted: 05/13/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Stress-induced Exhaustion Disorder (ED) is associated with work absenteeism and adverse health outcomes. Currently, little is known regarding how the symptoms of ED are interrelated and whether the patterns of symptoms influence treatment outcomes. To this end, the current study applied network analyses on ED patients participating in a multimodal intervention. METHODS The first aim of the study was to explore the internal relationships between exhaustion symptoms and identify symptoms that were more closely related than others. A second aim was to examine whether the baseline symptom network of non-responders to treatment was more closely connected than the baseline symptom networks of responders, by comparing the sum of all absolute partial correlations in the respective groups' symptom network. This comparison was made based on the hypothesis that a more closely connected symptom network before treatment could indicate poorer treatment outcomes. Network models were constructed based on self-rated ED symptoms in a large sample of patients (n = 915) participating in a 24-week multimodal treatment program with a 12-month follow-up. RESULTS The internal relations between self-rated exhaustion symptoms were stable over time despite markedly decreased symptom levels throughout participation in treatment. Symptoms of limited mental stamina and negative emotional reactions to demands were consistently found to be the most closely related to other ED symptoms. Meanwhile, sleep quality and irritability were weakly related to other exhaustion symptoms. The symptom network for the full sample became significantly more closely connected from baseline to the end of treatment and 12-month follow-up. The symptom network of non-responders to treatment was not found to be more closely connected than the symptom network of responders at baseline. CONCLUSIONS The results of the current study suggest symptoms of limited mental stamina and negative emotional reactions to demands are central ED symptoms throughout treatment, while symptoms of irritability and sleep quality seem to have a weak relation to other symptoms of ED. The implications of these findings are discussed in relation to the conceptualization, assessment, and treatment of ED. TRIAL REGISTRATION The clinical trial was registered on Clinicaltrials.gov 2017-12-02 (Identifier: NCT03360136).
Collapse
Affiliation(s)
- Gustav Mårtensson
- Department of Psychology, Uppsala University, Box 1225, Uppsala, 751 42, Sweden.
| | - Fred Johansson
- Department of Health Promotion Science, Sophiahemmet University, Valhallavägen 91, Stockholm, SE-114 28, Sweden
| | - Monica Buhrman
- Department of Psychology, Uppsala University, Box 1225, Uppsala, 751 42, Sweden
| | - Fredrik Åhs
- Department of Psychology and Social Work, Mid Sweden University, Kunskapens väg 1, Östersund, SE-831 40, Sweden
| | | |
Collapse
|
4
|
Janssen NP, Guineau MG, Lucassen P, Hendriks GJ, Ikani N. Depressive symptomatology in older adults treated with behavioral activation: A network perspective. J Affect Disord 2024; 352:445-453. [PMID: 38387671 DOI: 10.1016/j.jad.2024.02.073] [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: 12/27/2023] [Revised: 02/16/2024] [Accepted: 02/19/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND Late-life depression is a serious mental health problem. Behavioral Activation (BA) is an effective, accessible psychotherapeutic treatment for older adults. However, little is known about which symptoms decrease and how associations between depressive symptoms change during BA treatment. METHODS Using data from a cluster-randomized trial for older adults with late-life depression, we estimated a partial correlation network and a relative importance network of depressive symptoms before and after 8 weeks of BA treatment in primary care (n = 96). Networks were examined with measures of network structure, connectivity, centrality as well as stability. RESULTS The most central symptoms at baseline and post-treatment were anhedonia, fatigue, and feeling depressed. In contrast, sleeping problems had the lowest centrality. The post-treatment network was significantly more interconnected than at baseline. Moreover, all symptoms were significantly more central at post-treatment. CONCLUSION Our findings highlight the utility of the network approach to better understand symptom networks of depressed older adults before and after BA treatment. Results show that network connectivity and centrality of all symptoms increased after treatment. Future studies should investigate longitudinal idiographic networks to explore symptom dynamics within individuals over time.
Collapse
Affiliation(s)
- Noortje P Janssen
- Behavioural Science Institute, Radboud University, Thomas van Aquinostraat 4, 6525 GD Nijmegen, the Netherlands; Department of Primary and Community Care, Research Institute of Health Sciences, Radboud University Medical Centre Nijmegen, Nijmegen, the Netherlands; Institute for Integrated Mental Health Care Pro Persona, Nijmeegsebaan 61, 6525 DX Nijmegen, the Netherlands.
| | - Melissa G Guineau
- Behavioural Science Institute, Radboud University, Thomas van Aquinostraat 4, 6525 GD Nijmegen, the Netherlands; Institute for Integrated Mental Health Care Pro Persona, Nijmeegsebaan 61, 6525 DX Nijmegen, the Netherlands.
| | - Peter Lucassen
- Department of Primary and Community Care, Research Institute of Health Sciences, Radboud University Medical Centre Nijmegen, Nijmegen, the Netherlands.
| | - Gert-Jan Hendriks
- Behavioural Science Institute, Radboud University, Thomas van Aquinostraat 4, 6525 GD Nijmegen, the Netherlands; Institute for Integrated Mental Health Care Pro Persona, Nijmeegsebaan 61, 6525 DX Nijmegen, the Netherlands.
| | - Nessa Ikani
- Institute for Integrated Mental Health Care Pro Persona, Nijmeegsebaan 61, 6525 DX Nijmegen, the Netherlands; Department of Developmental Psychology, Tilburg University, Warandelaan 2, 5037 AB Tilburg, the Netherlands.
| |
Collapse
|
5
|
Castro D, Gysi D, Ferreira F, Ferreira-Santos F, Ferreira TB. Centrality measures in psychological networks: A simulation study on identifying effective treatment targets. PLoS One 2024; 19:e0297058. [PMID: 38422083 PMCID: PMC10903921 DOI: 10.1371/journal.pone.0297058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 12/26/2023] [Indexed: 03/02/2024] Open
Abstract
The network theory of psychopathology suggests that symptoms in a disorder form a network and that identifying central symptoms within this network might be important for an effective and personalized treatment. However, recent evidence has been inconclusive. We analyzed contemporaneous idiographic networks of depression and anxiety symptoms. Two approaches were compared: a cascade-based attack where symptoms were deactivated in decreasing centrality order, and a normal attack where symptoms were deactivated based on original centrality estimates. Results showed that centrality measures significantly affected the attack's magnitude, particularly the number of components and average path length in both normal and cascade attacks. Degree centrality consistently had the highest impact on the network properties. This study emphasizes the importance of considering centrality measures when identifying treatment targets in psychological networks. Further research is needed to better understand the causal relationships and predictive capabilities of centrality measures in personalized treatments for mental disorders.
Collapse
Affiliation(s)
- Daniel Castro
- University of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| | - Deisy Gysi
- Center for Complex Network Research, Northeastern University, Boston, Massachusetts, United States of America
| | - Filipa Ferreira
- University of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| | - Fernando Ferreira-Santos
- Laboratory of Neuropsychophysiology, Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
| | - Tiago Bento Ferreira
- University of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| |
Collapse
|
6
|
Lee CT, Kelley SW, Palacios J, Richards D, Gillan CM. Estimating the prognostic value of cross-sectional network connectivity for treatment response in depression. Psychol Med 2024; 54:317-326. [PMID: 37282838 DOI: 10.1017/s0033291723001368] [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] [Indexed: 06/08/2023]
Abstract
BACKGROUND Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder v. non-responder networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance. METHODS N = 40 518 patients receiving treatment for depression in routine care in England from 2015-2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 (PHQ-9) for responders and non-responders (N = 20 259 each). To conduct parametric tests investigating the contribution of PHQ-9 sum score mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, n = 250 per sample). RESULTS The baseline non-responder network was more connected than responders (3.15 v. 2.70, S = 0.44, p < 0.001), but effects were small, requiring n = 750 per group to have 85% power. Parametric analyses revealed baseline network connectivity, PHQ-9 sum score mean, and PHQ-9 sum score variance were correlated (r = 0.20-0.58, all p < 0.001). Both PHQ-9 sum score mean (β = -1.79, s.e. = 0.07, p < 0.001), and PHQ-9 sum score variance (β = -1.67, s.e. = 0.09, p < 0.001) had larger effect sizes for predicting response than connectivity (β = -1.35, s.e. = 0.12, p < 0.001). The association between connectivity and response disappeared when PHQ-9 sum score variance was accounted for (β = -0.28, s.e. = 0.19, p = 0.14). We replicated these results in patients completing longer treatment (8-12 weeks, N = 22 952) and using anxiety symptom networks (N = 70 620). CONCLUSIONS The association between baseline network connectivity and treatment response may be largely due to differences in baseline score variance.
Collapse
Affiliation(s)
- Chi Tak Lee
- Department of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean W Kelley
- Department of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jorge Palacios
- Department of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Derek Richards
- Department of Psychology, Trinity College Dublin, Dublin, Ireland
- SilverCloud Science, SilverCloud Health Ltd, Dublin, Ireland
| | - Claire M Gillan
- Department of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
Kelley SW, Fisher AJ, Lee CT, Gallagher E, Hanlon AK, Robertson IH, Gillan CM. Elevated emotion network connectivity is associated with fluctuations in depression. Proc Natl Acad Sci U S A 2023; 120:e2216499120. [PMID: 37903279 PMCID: PMC10636367 DOI: 10.1073/pnas.2216499120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 08/18/2023] [Indexed: 11/01/2023] Open
Abstract
Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from two independent samples of N = 155 paid students and N = 194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 wk. We constructed thousands of personalized emotion networks for each participant and tested whether connectivity was associated with severity of depression or its variance over 8 wk. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-wk variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N = 519). We conclude that elevated network connectivity is associated with greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings, although correlational, suggest that while emotional network connectivity could predispose individuals to severe depression, it could also be leveraged to bring about therapeutic improvements.
Collapse
Affiliation(s)
- Sean W. Kelley
- School of Psychology, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Aaron J. Fisher
- Department of Psychology, University of California, Berkeley, CA94720
| | - Chi Tak Lee
- School of Psychology, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Eoghan Gallagher
- School of Psychology, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Anna K. Hanlon
- School of Psychology, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Ian H. Robertson
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
- Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Claire M. Gillan
- School of Psychology, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
- Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
| |
Collapse
|
9
|
Schumacher L, Klein JP, Elsaesser M, Härter M, Hautzinger M, Schramm E, Kriston L. Implications of the Network Theory for the Treatment of Mental Disorders: A Secondary Analysis of a Randomized Clinical Trial. JAMA Psychiatry 2023; 80:1160-1168. [PMID: 37610747 PMCID: PMC10448377 DOI: 10.1001/jamapsychiatry.2023.2823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/07/2023] [Indexed: 08/24/2023]
Abstract
Importance Conceptualizing mental disorders as latent entities has been challenged by the network theory of mental disorders, which states that psychological problems are constituted by a network of mutually interacting symptoms. While the implications of the network approach for planning and evaluating treatments have been intensively discussed, empirical support for the claims of the network theory regarding treatment effects is lacking. Objective To assess the extent to which specific hypotheses derived from the network theory regarding the (interindividual) changeability of symptom dynamics in response to treatment align with empirical data. Design, Setting, and Participants This secondary analysis entails data from a multisite randomized clinical trial, in which 254 patients with chronic depression reported on their depressive symptoms at every treatment session. Data collection was conducted between March 5, 2010, and October 14, 2013, and this analysis was conducted between November 1, 2021, and May 31, 2022. Intervention Thirty-two sessions of either disorder-specific or nonspecific psychotherapy for chronic depression. Main Outcomes and Measures Longitudinal associations of depressive symptoms with each other and change of these associations through treatment estimated by a time-varying longitudinal network model. Results In a sample of 254 participants (166 [65.4%] women; mean [SD] age, 44.9 [11.9] years), symptom interactions changed through treatment, and this change varied across treatments and individuals. The mean absolute (ie, valence-ignorant) strength of symptom interactions (logarithmic odds ratio scale) increased from 0.40 (95% CI, 0.36-0.44) to 0.60 (95% CI, 0.52-0.70) during nonspecific psychotherapy and to 0.56 (95% CI, 0.48-0.64) during disorder-specific psychotherapy. In contrast, the mean raw (ie, valence-sensitive) strength of symptom interactions decreased from 0.32 (95% CI, 0.28-0.36) to 0.26 (95% CI, 0.20-0.32) and to 0.09 (95% CI, 0.02-0.16), respectively. Changing symptom severity could be explained to a large extent by symptom interactions. Conclusions and Relevance These findings suggest that specific treatment-related hypotheses of the network theory align well with empirical data. Conceptualizing mental disorders as symptom networks and treatments as measures that aim to change these networks is expected to give further insights into the working mechanisms of mental health treatments, leading to the improvement of current and the development of new treatments. Trial Registration ClinicalTrials.gov Identifier: NCT00970437.
Collapse
Affiliation(s)
- Lea Schumacher
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Philipp Klein
- Department of Psychiatry, Psychosomatics and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Moritz Elsaesser
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Martin Härter
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Martin Hautzinger
- Department of Psychology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Elisabeth Schramm
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Levente Kriston
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| |
Collapse
|
10
|
Whiston A, Igou ER, Fortune DG, Semkovska M. Longitudinal interactions between residual symptoms and physiological stress in the remitted symptom network structure of depression. Acta Psychol (Amst) 2023; 241:104078. [PMID: 37944268 DOI: 10.1016/j.actpsy.2023.104078] [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: 03/28/2023] [Revised: 10/16/2023] [Accepted: 11/04/2023] [Indexed: 11/12/2023] Open
Abstract
Residual symptoms and stress are amongst the most reliable predictors of relapse in remitted depression. Standard methodologies often preclude continuous stress sampling or the evaluation of complex symptom interactions. This limits knowledge acquisition relative to the day-to-day interactions between residual symptoms and stress. The study aims to explore the interactions between physiological stress and residual symptoms network structure in remitted depression. Twenty-two individuals remitted from depression completed baseline, daily diary (DD), and post-DD assessments. Self-reported stress and residual symptoms were measured at baseline and post-DD. Daily diaries required participants to use a wearable electrodermal activity (EDA) device during waking hours and complete residual symptom measures twice daily for 3-weeks. Two-step multilevel vector auto-regression models were used to estimate contemporaneous and dynamic networks. Depressed mood and concentration problems were central across networks. Skin conductance responses (SCRs), suicide, appetite, and sleep problems were central in the temporal and energy loss in the contemporaneous network. Increased SCRs predicted decreased energy loss. Residual symptoms and stress showed bi-directional interactions. Overall, depressed mood and concentration problems were consistently central, thus potentially important intervention targets. Non-obtrusive bio-signal measures should be used to provide the clinical evidence-base for modelling the interactions between depressive residual symptoms and stress. Practical implications are discussed throughout related to focusing on symptom-specific interactions in clinical practice, simultaneously reducing residual symptom and stress occurrences, EDA as pioneering signal for stress detection, and the central role of specific residual symptoms in remitted depression.
Collapse
Affiliation(s)
- Aoife Whiston
- Department of Psychology, University of Limerick, Co., Limerick, Ireland.
| | - Eric R Igou
- Department of Psychology, University of Limerick, Co., Limerick, Ireland
| | - Dònal G Fortune
- Department of Psychology, University of Limerick, Co., Limerick, Ireland
| | - Maria Semkovska
- DeFREE Research Unit, Department of Psychology, University of Southern Denmark, Denmark
| |
Collapse
|
11
|
de la Torre-Luque A, Pemau A, Galvez-Merlin A, Garcia-Ramos A. Immunometabolic alterations in older adults with heightened depressive symptom trajectories: a network approach. Aging Ment Health 2023; 27:2229-2237. [PMID: 37401624 DOI: 10.1080/13607863.2023.2227114] [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: 10/26/2022] [Accepted: 06/05/2023] [Indexed: 07/05/2023]
Abstract
Objective: To analyse the patterns of relationships between depressive symptoms and immunometabolic markers across longitudinal depression status in older people. Methods: A sample of 3349 older adults (55.21% women; initial age: m = 58.44, sd = 5.21) from the English Longitudinal Study of Ageing was used. Participants were classified according to their longitudinal depression status: minimal depressive symptoms (n = 2736), depressive episode onset (n = 481), or chronic depression (n = 132). Network analysis was used to study the relationships between depression symptoms (CES-D 8 items), inflammatory (white blood cell, C-reactive protein, fibrinogen) and metabolic biomarkers (metabolic syndrome markers). Results: Network structure remained invariant across groups. The minimal symptom group had higher overall strength than both clinical groups (p < .01). Moreover, significant relationships between symptoms and markers were observed across group-specific networks. C-reactive protein and effort symptom were positively connected in the minimal symptom group but not in the other groups. Loneliness and diastolic blood pressure were positively associated only in the chronic depression group. Finally, metabolic markers were identified as central nodes in the clinical status networks. Conclusion: The network analysis constitutes a useful approach to disentangle pathophysiological relationships that may maintain mental disorders in old age.
Collapse
Affiliation(s)
- Alejandro de la Torre-Luque
- Department of Legal Medicine, Psychiatry and Pathology, Universidad Complutense de Madrid, Spain
- Centre for Biomedical Research in Mental Health (CIBERSAM), Spain
| | - Andres Pemau
- Faculty of Psychology, Universidad Complutense de Madrid, Spain
| | | | - Adriana Garcia-Ramos
- Department of Legal Medicine, Psychiatry and Pathology, Universidad Complutense de Madrid, Spain
| |
Collapse
|
12
|
Boschloo L, Hieronymus F, Lisinski A, Cuijpers P, Eriksson E. The complex clinical response to selective serotonin reuptake inhibitors in depression: a network perspective. Transl Psychiatry 2023; 13:19. [PMID: 36681669 PMCID: PMC9867733 DOI: 10.1038/s41398-022-02285-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/29/2022] [Accepted: 12/08/2022] [Indexed: 01/22/2023] Open
Abstract
The clinical response to selective serotonin reuptake inhibitors (SSRIs) in depression takes weeks to be fully developed and is still not entirely understood. This study aimed to determine the direct and indirect effects of SSRIs relative to a placebo control condition on clinical symptoms of depression. We included data of 8262 adult patients with major depression participating in 28 industry-sponsored US Food and Drug Administration (FDA) registered trials on the efficacy of SSRIs. Clinical symptoms of depression were assessed by the 17 separate items of the Hamilton Depression Rating Scale (HDRS) after 1, 2, 3, 4 and 6 weeks of treatment. Network estimation techniques showed that SSRIs had quick and strong direct effects on the two affective symptoms, i.e., depressed mood and psychic anxiety; direct effects on other symptoms were weak or absent. Substantial indirect effects were found for all four cognitive symptoms, which showed larger reductions in the SSRI condition but mainly in patients reporting larger reductions in depressed mood. Smaller indirect effects were found for two arousal/somatic symptoms via the direct effect on psychic anxiety. Both direct and indirect effects on sleep problems and most arousal/somatic symptoms were weak or absent. In conclusion, our study revealed that SSRIs primarily caused reductions in affective symptoms, which were related to reductions in mainly cognitive symptoms and some specific arousal/somatic symptoms. The results can contribute to disclosing the mechanisms of action of SSRIs, and has the potential to facilitate early detection of responders and non-responders in clinical practice.
Collapse
Affiliation(s)
- Lynn Boschloo
- Department of Clinical Psychology, Utrecht University, Utrecht, The Netherlands. .,Department of Clinical, Neuro, and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fredrik Hieronymus
- grid.8761.80000 0000 9919 9582Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Alexander Lisinski
- grid.8761.80000 0000 9919 9582Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Pim Cuijpers
- grid.12380.380000 0004 1754 9227Department of Clinical, Neuro, and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands ,grid.7399.40000 0004 1937 1397International Institute for Psychotherapy, Babeș-Bolyai University, Cluj-Napoca, Romania
| | - Elias Eriksson
- grid.8761.80000 0000 9919 9582Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| |
Collapse
|
13
|
Imperiale MN, Lieb R, Calkins ME, Meinlschmidt G. Transdiagnostic symptom networks in relation to mental health service use in community youth. Clin Psychol Psychother 2023; 30:119-130. [PMID: 36059253 PMCID: PMC10087894 DOI: 10.1002/cpp.2782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 07/28/2022] [Accepted: 07/31/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The objective of this study is to scrutinize whether psychopathology symptom networks differ between those with and without lifetime: treatment seeking, treatment and treatment of longer duration. METHODS We created non-exclusive groups of subjects with versus without lifetime treatment seeking, treatment and treatment of mid-long-term duration. We estimated Ising models and carried out network comparison tests (NCTs) to compare (a) overall connectivity and (b) network structure. Furthermore, we examined node strength. We used propensity score matching (PSM) to minimize potential confounding by indication for service use. RESULTS Based on data from 9,172 participants, there were no statistically significant differences in overall connectivity and network structure in those with versus without lifetime: treatment seeking (p = .75 and p = .82, respectively), treatment (p = .63 and p = .49, respectively) and treatment of mid-longterm duration (p = .15 and p = .62, respectively). Notably, comparing networks with versus without service use consistently revealed higher node strength in 'obsessions' and 'aggression' and lower node strength in 'elevated mood' in all networks with service use. CONCLUSIONS Findings suggest that after adjusting for potential confounding by indication for service use, there was no indication of an association in overall connectivity or network structure for lifetime treatment seeking, treatment and treatment of longer duration. However, selected structurally important symptoms differed consistently in all three comparisons. Our findings highlight the potential of network analysis methods to examine treatment mechanisms and outcomes. Specifically, more granular network characteristics on the node level may complement and enrich traditional outcomes in clinical research.
Collapse
Affiliation(s)
- Marina N Imperiale
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.,Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Roselind Lieb
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland
| | - Monica E Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gunther Meinlschmidt
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.,Department of Clinical Psychology and Cognitive Behavioral Therapy, International Psychoanalytic University, Berlin, Germany.,Department of Psychosomatic Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| |
Collapse
|
14
|
Ferreira F, Gysi D, Castro D, Ferreira TB. The nosographic structure of posttraumatic stress symptoms across trauma types: An exploratory network analysis approach. J Trauma Stress 2022; 35:1115-1128. [PMID: 35246860 DOI: 10.1002/jts.22818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/06/2021] [Accepted: 01/11/2022] [Indexed: 11/12/2022]
Abstract
The nosographic structure of posttraumatic stress disorder (PTSD) remains unclear, and attempts to determine its symptomatic organization have been unsatisfactory. Several explanations have been suggested, and the impact of trauma type is receiving increasing attention. As little is known about the differential impact trauma type in the nosographic structure of PTSD, we explored the nosology of PTSD and the effect of trauma type on its symptomatic organization. We reanalyzed five cross-sectional psychopathological networks involving different trauma types, encompassing a broad range of traumatic events in veterans, war-related trauma in veterans, sexual abuse, terrorist attacks, and various traumatic events in refugees. The weighted topological overlap was used to estimate the networks and attribute weights to their links. Coexpression differential network analysis was used to identify the common and specific network structures of the connections across different trauma types and to determine the importance of symptoms across the networks. We found a set of symptoms with more common connections with other symptoms, suggesting that these might constitute the prototypical nosographic structure of PTSD. We also found a set of symptoms that had a high number of specific connections with other symptoms; these connections varied according to trauma type. The importance of symptoms across the common and specific networks was ascertained. The present findings offer new insights into the symptomatic organization of PTSD and support previous research on the impact of trauma type on the nosology of this disorder.
Collapse
Affiliation(s)
- Filipa Ferreira
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
| | - Deisy Gysi
- Center for Complex Network Research, Northeastern University, Boston, Massachusetts, USA
| | - Daniel Castro
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
| | - Tiago Bento Ferreira
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
| |
Collapse
|
15
|
Jumping back onto the giants' shoulders: Why emotional memory should be considered in a network perspective of psychopathology. Behav Res Ther 2022; 156:104154. [PMID: 35850017 DOI: 10.1016/j.brat.2022.104154] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 06/21/2022] [Accepted: 06/27/2022] [Indexed: 12/22/2022]
Abstract
Clinical psychology finds itself with a paradox: On the one hand, there is abundant empirical evidence showing that aversive experiences increase the risk for psychopathology. In fact, a learning and memory framework forms the foundation of numerous psychological theories and treatments. For example, various CBT approaches aim to target maladaptive emotional memories (e.g., schemas or cognitions) that are deemed to lie at the core of mental health conditions. On the other hand, a new approach - the network theory - is gaining ground, which ignores underlying causes for mental disorders and instead dictates a focus on symptoms and their causal interactions. While radical shifts are sometimes necessary in science, we argue why completely neglecting common causes, such as emotional memory, is not justified. We critically discuss the strengths and limitations of the network approach: While its transdiagnostic nature and recognition of symptom interactions have the potential to invigorate the field, the framework is merely descriptive, its concepts not well defined, and its clinical utility still to be established. To move forward, we propose an incorporation of latent constructs into the network model, starting with clearer definitions and operationalisations of concepts in both network and latent variable models.
Collapse
|
16
|
Höller I, Schreiber D, Bos F, Forkmann T, Teismann T, Margraf J. The Mereology of Depression-Networks of Depressive Symptoms during the Course of Psychotherapy. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19127131. [PMID: 35742380 PMCID: PMC9222343 DOI: 10.3390/ijerph19127131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/03/2022]
Abstract
(1) Background: Research has shown that it is important to examine depressive symptoms in the light of the mereology (the ratio between one symptom and the whole disorder). The goal of this study was to examine changes in the symptom interrelations of patients undergoing cognitive behavioral therapy treatment (CBT) via network analyses. (2) Method: Outpatients with depressive symptoms (N = 401) were assessed with the Beck Depression Inventory three times (pretreatment, after 12 sessions, and post-treatment) during CBT. Gaussian graphical models were used to estimate the relationships among symptoms. (3) Results: The severity of depressive symptoms significantly decreased over the course of therapy, but connectivity in the networks significantly increased. Communities of symptoms changed during treatment. The most central and predictable symptom was worthlessness at baseline and after 12 sessions, and loss of energy and self-dislike at post-treatment. (4) Conclusion: The results indicate that the severity of depressive symptoms decreased during cognitive behavior therapy, while network connectivity increased. Furthermore, the associations among symptoms and their centrality changed during the course of therapy. Future studies may investigate individual differences and their impact on the planning of psychotherapeutic treatment.
Collapse
Affiliation(s)
- Inken Höller
- Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany; (D.S.); (T.F.)
- Correspondence: ; Tel.: +49-201-183-6117
| | - Dajana Schreiber
- Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany; (D.S.); (T.F.)
| | - Fionneke Bos
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of Groningen, 9700RB Groningen, The Netherlands;
- Psychiatric Hospital Mental Health Services Drenthe, Outpatient Clinics, 9401LA Assen, The Netherlands
| | - Thomas Forkmann
- Department of Clinical Psychology, University of Duisburg-Essen, 45141 Essen, Germany; (D.S.); (T.F.)
| | - Tobias Teismann
- Mental Health Research and Treatment Center, Faculty of Psychology, Ruhr-Universität Bochum, 44787 Bochum, Germany; (T.T.); (J.M.)
| | - Jürgen Margraf
- Mental Health Research and Treatment Center, Faculty of Psychology, Ruhr-Universität Bochum, 44787 Bochum, Germany; (T.T.); (J.M.)
| |
Collapse
|
17
|
Xie T, Wen J, Liu X, Wang J, Poppen PJ. Utilizing network analysis to understand the structure of depression in Chinese adolescents: Replication with three depression scales. CURRENT PSYCHOLOGY 2022; 42:1-12. [PMID: 35669214 PMCID: PMC9157480 DOI: 10.1007/s12144-022-03201-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2022] [Indexed: 12/15/2022]
Abstract
Depression involves a heterogenous collection of symptoms. Network perspective views depressive symptoms as an interrelated network. The current study aimed to replicate network analyses on adolescent depression in three samples assessed with three instruments to examine the consistency of network structures and also examine the variance of networks between genders. Three samples of adolescents (total N = 4375, mean age = 15, 49.1% boys) were assessed with PHQ-9, SMFQ and CDI, respectively. Network analyses were carried out on depression symptoms. Network stability, node centrality and network comparisons between genders were examined. Three networks were reliably stable. Sadness and self-hatred were unanimously identified to be central symptoms of adolescent depression in three networks. In addition, fatigue, no good, everything wrong and loneliness also appeared to be central in specific networks. Among three depression networks, PHQ-9 network demonstrated gender difference in network structure. The current study is exploratory in nature. The differences in three networks can be due to various samples or different node inclusions. Further, the study is cross-sectional precluding causal interpretation and the samples are nonclinical. Besides "hallmark" symptom sadness, self-hatred was also identified unanimously in three networks, which demonstrated the significant role self-worth played in adolescent depression. The results also suggested that differences in node inclusion may have influence on the network structure. Supplementary Information The online version contains supplementary material available at 10.1007/s12144-022-03201-z.
Collapse
Affiliation(s)
- Tong Xie
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, People’s Republic of China
| | - Jun Wen
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, People’s Republic of China
- Division of Psychopathology and Clinical Intervention, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Xiaoyan Liu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, People’s Republic of China
| | - Jianping Wang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, People’s Republic of China
| | - Paul J. Poppen
- Psychological and Brain Sciences, George Washington University, Washington, DC USA
| |
Collapse
|
18
|
Schlechter P, Hellmann JH, McNally RJ, Morina N. The longitudinal course of posttraumatic stress disorder symptoms in war survivors: Insights from cross-lagged panel network analyses. J Trauma Stress 2022; 35:879-890. [PMID: 35030294 PMCID: PMC9303894 DOI: 10.1002/jts.22795] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/22/2021] [Accepted: 11/30/2021] [Indexed: 12/23/2022]
Abstract
Many war survivors suffer from chronic posttraumatic stress disorder (PTSD). Unraveling the complexities of PTSD symptoms over time is crucial for understanding this condition. Going beyond a common pathogenic pathway perspective, we applied the network approach to psychopathology to analyze longitudinal data from war survivors with PTSD in five Balkan countries approximately 8 years after war in the region and a follow-up assessment 1 year later (N = 698). PTSD diagnosis was established using the Mini-International Neuropsychiatric Interview, and PTSD symptoms were assessed using the Impact of Events Scale-Revised. Undirected cross-sectional networks for baseline and follow-up revealed no differences in the overall connectivity between these two networks. The intrusion symptom "I had waves of strong feelings about it" had the strongest expected influence centrality. Directed cross-lagged panel network models indicated that hyperarousal symptoms predicted other PTSD symptoms from baseline to follow-up, whereas several avoidance symptoms were predicted by other PTSD symptoms. The findings underscore the importance of emotional reactions and further suggest that hyperarousal symptoms may influence other PTSD symptoms. Future research should investigate causality and associations between between-person and within-person networks.
Collapse
|
19
|
Keshishian AC, Christian C, Williams BM, Spoor SP, Peiper NC, Levinson CA. A Network Analysis Investigation of Disordered Eating Across Demographic and Developmental Subpopulations Using a National Epidemiological Sample of High School Students. Behav Ther 2022; 53:535-545. [PMID: 35473655 DOI: 10.1016/j.beth.2021.12.005] [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: 05/11/2021] [Revised: 12/09/2021] [Accepted: 12/19/2021] [Indexed: 11/15/2022]
Abstract
Disordered eating (DE) poses a large societal burden, yet limited research has examined DE from a developmental epidemiological perspective. It is important to consider how demographics influence DE symptoms to inform prevention and early intervention programs across diverse subpopulations. Therefore, we conducted network analyses using a large nationally representative epidemiological sample of high school students (Youth Risk Behavior Survey, United States; n = 59,582) to identify the most important symptoms and symptom relationships among six DE behaviors. We compared networks by sex, grade, and race to identify differences in symptom networks. Dieting for weight loss was highly central across networks. Networks significantly differed across sex, grade, and race. Our results suggest that dieting for weight loss may be an early intervention target for eating disorders, regardless of demographic and developmental factors. In addition, sex, race, and age should be accounted for when researching and developing prevention programs for DE and eating disorders. Public health officials, as well as mental health professionals, should present a more balanced message about dieting and weight loss to high school students to prevent the detrimental impact of DE on physical and mental health. Notably, this study is the first large, nationwide epidemiological sample using DE symptoms in network analysis.
Collapse
Affiliation(s)
| | | | | | | | - Nicholas C Peiper
- University of Louisville School of Public Health and Information Sciences
| | | |
Collapse
|
20
|
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.
Collapse
|
21
|
Using language in social media posts to study the network dynamics of depression longitudinally. Nat Commun 2022; 13:870. [PMID: 35169166 PMCID: PMC8847554 DOI: 10.1038/s41467-022-28513-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/21/2022] [Indexed: 12/13/2022] Open
Abstract
Network theory of mental illness posits that causal interactions between symptoms give rise to mental health disorders. Increasing evidence suggests that depression network connectivity may be a risk factor for transitioning and sustaining a depressive state. Here we analysed social media (Twitter) data from 946 participants who retrospectively self-reported the dates of any depressive episodes in the past 12 months and current depressive symptom severity. We construct personalised, within-subject, networks based on depression-related linguistic features. We show an association existed between current depression severity and 8 out of 9 text features examined. Individuals with greater depression severity had higher overall network connectivity between depression-relevant linguistic features than those with lesser severity. We observed within-subject changes in overall network connectivity associated with the dates of a self-reported depressive episode. The connectivity within personalized networks of depression-associated linguistic features may change dynamically with changes in current depression symptoms.
Collapse
|
22
|
Whiston A, Lennon A, Brown C, Looney C, Larkin E, O'Sullivan L, Sik N, Semkovska M. A Systematic Review and Individual Patient Data Network Analysis of the Residual Symptom Structure Following Cognitive-Behavioral Therapy and Escitalopram, Mirtazapine and Venlafaxine for Depression. Front Psychiatry 2022; 13:746678. [PMID: 35178002 PMCID: PMC8843824 DOI: 10.3389/fpsyt.2022.746678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 01/06/2022] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE Consistent evidence suggests residual depressive symptomology are the strongest predictors of depression relapse following cognitive-behavioral therapy (CBT) and antidepressant medications (ADM's). Psychometric network models help detecting and understanding central symptoms that remain post-treatment, along with their complex co-occurrences. However, individual psychometric network studies show inconsistent findings. This systematic review and IPD network analysis aimed to estimate and compare the symptom network structures of residual depressive symptoms following CBT, ADM's, and their combination. METHODS PsycINFO, PsycArticles, and PubMed were systematically searched through October 2020 for studies that have assessed individuals with major depression at post-treatment receiving either CBT and/or ADM's (venlafaxine, escitalopram, mirtazapine). IPD was requested from eligible samples to estimate and compare residual symptom psychometric network models post-CBT and post-ADM's. RESULTS In total, 25 from 663 eligible samples, including 1,389 patients qualified for the IPD. Depressed mood and anhedonia were consistently central residual symptoms post-CBT and post-ADM's. For CBT, fatigue-related and anxiety symptoms were also central post-treatment. A significant difference in network structure across treatments (CBT vs. ADM) was observed for samples measuring depression severity using the MADRS. Specifically, stronger symptom occurrences were present amongst lassitude-suicide post-CBT (vs. ADM's) and amongst lassitude-inability to feel post-ADM's (vs. CBT). No significant difference in global strength was observed across treatments. CONCLUSIONS Core major depression symptoms remain central across treatments, strategies to target these symptoms should be considered. Anxiety and fatigue related complaints also remain central post-CBT. Efforts must be made amongst researchers, institutions, and journals to permit sharing of IPD.Systematic Review Registration: A protocol was prospectively registered on PROSPERO (CRD42020141663; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=141663).
Collapse
Affiliation(s)
- Aoife Whiston
- Department of Psychology, University of Limerick, Limerick, Ireland
| | - Amy Lennon
- Department of Psychology, University of Limerick, Limerick, Ireland
| | - Catherine Brown
- Department of Psychology, University of Limerick, Limerick, Ireland
| | - Chloe Looney
- Department of Psychology, University of Limerick, Limerick, Ireland
| | - Eve Larkin
- Department of Psychology, University of Limerick, Limerick, Ireland
| | | | - Nurcan Sik
- Department of Psychology, University of Limerick, Limerick, Ireland
| | - Maria Semkovska
- Department of Psychology, University of Southern Denmark, Odense, Denmark
| |
Collapse
|
23
|
Belvederi Murri M, Grassi L, Caruso R, Nanni MG, Zerbinati L, Andreas S, Ausín B, Canuto A, Härter M, Lopez MM, Weber K, Wittchen HU, Volkert J, Alexopoulos GS. Depressive symptom complexes of community-dwelling older adults: a latent network model. Mol Psychiatry 2022; 27:1075-1082. [PMID: 34642459 DOI: 10.1038/s41380-021-01310-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 03/23/2021] [Accepted: 09/15/2021] [Indexed: 11/09/2022]
Abstract
Late-life depression has multiple, heterogeneous clinical presentations. The aim of the study was to identify higher-order homogeneous clinical features (symptom complexes), while accounting for their potential causal interactions within the network approach to psychopathology. We analyzed cross-sectional data from community-dwelling adults aged 65-85 years recruited by the European MentDis_ICF65+ study (n = 2623, mean age 74, 49% females). The severity of 33 depressive symptoms was derived from the age-adapted Composite International Diagnostic Interview. Symptom complexes were identified using multiple detection algorithms for symptom networks, and their fit to data was assessed with latent network models (LNMs) in exploratory and confirmatory analyses. Sensitivity analyses included the Partial Correlation Likelihood Test (PCLT) to investigate the data-generating structure. Depressive symptoms were organized by the Walktrap algorithm into eight symptom complexes, namely sadness/hopelessness, anhedonia/lack of energy, anxiety/irritability, self-reproach, disturbed sleep, agitation/increased appetite, concentration/decision making, and thoughts of death. An LNM adequately fit the distribution of individual symptoms' data in the population. The model suggested the presence of reciprocal interactions between the symptom complexes of sadness and anxiety, concentration and self-reproach and between self-reproach and thoughts of death. Results of the PCLT confirmed that symptom complex data were more likely generated by a network, rather than a latent-variable structure. In conclusion, late-life depressive symptoms are organized into eight interacting symptom complexes. Identification of the symptom complexes of late-life depression may streamline clinical assessment, provide targets for personalization of treatment, and aid the search for biomarkers and for predictors of outcomes of late-life depression.
Collapse
Affiliation(s)
- Martino Belvederi Murri
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Luigi Grassi
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Rosangela Caruso
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Maria Giulia Nanni
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Luigi Zerbinati
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Sylke Andreas
- Department of Medical Psychology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.,Institute for Psychology, Universität Klagenfurt, A-9020, Klagenfurt, Austria
| | - Berta Ausín
- School of Psychology, Personality, Evaluation and Clinical Psychology Department, University Complutense of Madrid, Campus de Somosaguas s/n, 28223, Madrid, Spain
| | - Alessandra Canuto
- Division of Institutional Measures, University Hospitals of Geneva, 1208, Geneva, Switzerland
| | - Martin Härter
- Department of Medical Psychology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Manuel Muñoz Lopez
- School of Psychology, Personality, Evaluation and Clinical Psychology Department, University Complutense of Madrid, Campus de Somosaguas s/n, 28223, Madrid, Spain
| | - Kerstin Weber
- Division of Institutional Measures, University Hospitals of Geneva, 1208, Geneva, Switzerland
| | - Hans-Ulrich Wittchen
- Clinical Psychology & Psychotherapy RG, Department of Psychiatry & Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Jana Volkert
- Department of Psychosocial Prevention, University of Heidelberg, Bergheimer Str. 54, 69115, Heidelberg, Germany.,Institute of Psychology, University of Kassel, Holländische Str. 36-38, 34127, Kassel, Germany
| | - George S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA.
| |
Collapse
|
24
|
Schreuder MJ, Wigman JTW, Groen RN, Weinans E, Wichers M, Hartman CA. Anticipating the direction of symptom progression using critical slowing down: a proof-of-concept study. BMC Psychiatry 2022; 22:49. [PMID: 35062917 PMCID: PMC8781362 DOI: 10.1186/s12888-022-03686-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 01/03/2022] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND As complex dynamic systems approach a transition, their dynamics change. This process, called critical slowing down (CSD), may precede transitions in psychopathology as well. This study investigated whether CSD may also indicate the direction of future symptom transitions, i.e., whether they involve an increase or decrease in symptoms. METHODS In study 1, a patient with a history of major depression monitored their mental states ten times a day for almost eight months. Study 2 used data from the TRAILS TRANS-ID study, where 122 young adults at increased risk of psychopathology (mean age 23.64±0.67 years, 56.6% males) monitored their mental states daily for six consecutive months. Symptom transitions were inferred from semi-structured diagnostic interviews. In both studies, CSD direction was estimated using moving-window principal component analyses. RESULTS In study 1, CSD was directed towards an increase in negative mental states. In study 2, the CSD direction matched the direction of symptom shifts in 34 individuals. The accuracy of the indicator was higher in subsets of individuals with larger absolute symptom transitions. The indicator's accuracy exceeded chance levels in sensitivity analyses (accuracy 22.92% vs. 11.76%, z=-2.04, P=.02) but not in main analyses (accuracy 27.87% vs. 20.63%, z=-1.32, P=.09). CONCLUSIONS The CSD direction may predict whether upcoming symptom transitions involve remission or worsening. However, this may only hold for specific individuals, namely those with large symptom transitions. Future research is needed to replicate these findings and to delineate for whom CSD reliably forecasts the direction of impending symptom transitions.
Collapse
Affiliation(s)
- Marieke J Schreuder
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Internal Postal Code: CC72, Triade Building Entrance 24, Hanzeplein 1, Groningen, 9713, GZ, The Netherlands.
| | - Johanna T W Wigman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Internal Postal Code: CC72, Triade Building Entrance 24, Hanzeplein 1, Groningen, 9713, GZ, The Netherlands
| | - Robin N Groen
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Internal Postal Code: CC72, Triade Building Entrance 24, Hanzeplein 1, Groningen, 9713, GZ, The Netherlands
| | - Els Weinans
- Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Marieke Wichers
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Internal Postal Code: CC72, Triade Building Entrance 24, Hanzeplein 1, Groningen, 9713, GZ, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Internal Postal Code: CC72, Triade Building Entrance 24, Hanzeplein 1, Groningen, 9713, GZ, The Netherlands
| |
Collapse
|
25
|
Mares SHW, Burger J, Lemmens LHJM, van Elburg AA, Vroling MS. Evaluation of the cognitive behavioural theory of eating disorders: A network analysis investigation. Eat Behav 2022; 44:101590. [PMID: 34896868 DOI: 10.1016/j.eatbeh.2021.101590] [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: 04/02/2021] [Revised: 11/19/2021] [Accepted: 11/22/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE One of the prevailing theories of eating disorders (ED) is the transdiagnostic cognitive behavioural theory of eating disorders, which suggests that certain ED symptoms, such as over-valuation of eating, shape, and weight, may be more central than others. In the present study, network analyses were used to evaluate these assumptions in a patient sample. METHODS Participants were 336 individuals receiving treatment at an expert center for ED in the Netherlands. Eating disorder symptoms were used to create transdiagnostic and diagnosis-specific networks and assess symptom centrality and density of the networks. RESULTS Networks for patients with bulimia nervosa and binge eating disorder confirmed that over-valuation of shape, weight, and eating is the most central symptom in the network. A transdiagnostic network of ED symptoms and separate networks for patients with anorexia nervosa and bulimia nervosa showed that strict dieting was an additional central ED symptom. An exploratory analysis revealed that, although eating disorder symptoms decreased, there were no differences in density of the eating disorder networks before and after treatment with cognitive behavioural therapy. DISCUSSION In conclusion, the current study confirmed that over-valuation of shape, weight, and eating is a central symptom across eating disorders, in agreement with the transdiagnostic cognitive behavioural model of eating disorders. Specifically targeting this symptom in treatment could lead to other symptoms improving as a result.
Collapse
Affiliation(s)
- Suzanne H W Mares
- Department of Eating Disorders (Amarum), GGNet Mental Health, Warnsveld, the Netherlands.
| | - Julian Burger
- University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, the Netherlands
| | - Lotte H J M Lemmens
- Department of Clinical Psychological Science, Maastricht University, Maastricht, the Netherlands
| | - Annemarie A van Elburg
- Department of Eating Disorders (Amarum), GGNet Mental Health, Warnsveld, the Netherlands; Altrecht Eating Disorders Rintveld, Zeist, the Netherlands; Department of Clinical Psychology, Utrecht University, Utrecht, the Netherlands
| | - Maartje S Vroling
- Department of Eating Disorders (Amarum), GGNet Mental Health, Warnsveld, the Netherlands; Radboud University Nijmegen, Behavioural Science Institute, NijCa2re, the Netherlands
| |
Collapse
|
26
|
Berlim MT, Richard-Devantoy S, Dos Santos NR, Turecki G. The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: a randomized clinical trial. Psychol Med 2021; 51:2399-2413. [PMID: 32312344 DOI: 10.1017/s0033291720001002] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment. METHODS In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy. RESULTS At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar. CONCLUSION Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.
Collapse
Affiliation(s)
- Marcelo T Berlim
- Depressive Disorders Program & McGill Group for Suicide Studies, McGill University & Douglas Mental Health University Institute, Montréal, Québec, Canada
| | - Stephane Richard-Devantoy
- Depressive Disorders Program & McGill Group for Suicide Studies, McGill University & Douglas Mental Health University Institute, Montréal, Québec, Canada
| | - Nicole Rodrigues Dos Santos
- Depressive Disorders Program & McGill Group for Suicide Studies, McGill University & Douglas Mental Health University Institute, Montréal, Québec, Canada
| | - Gustavo Turecki
- Depressive Disorders Program & McGill Group for Suicide Studies, McGill University & Douglas Mental Health University Institute, Montréal, Québec, Canada
| |
Collapse
|
27
|
Baez LM, Newport DJ, Stowe ZN, Knight BT, Heller AS. The severity and role of somatic depressive symptoms in psychological networks in a longitudinal sample of peripartum women. J Psychiatr Res 2021; 142:283-289. [PMID: 34403970 PMCID: PMC8429214 DOI: 10.1016/j.jpsychires.2021.07.049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/09/2021] [Accepted: 07/31/2021] [Indexed: 10/20/2022]
Abstract
The inclusion of somatic symptoms in assessing peripartum depression (PPD), which encompasses depression during pregnancy and the postpartum period, has remained controversial, as there is substantial overlap between somatic depression symptoms and normal features of pregnancy/postpartum. This study examined whether trajectories differed by PPD symptom subscale and whether PPD symptom networks changed as a function of the peripartum phase. 418 women with a history of neuropsychiatric illness participated in a longitudinal observational study, completing symptom questionnaires assessing affective, cognitive, and somatic symptoms throughout pregnancy and the first year postpartum. Assessments were grouped into five peripartum phases: three trimesters of pregnancy and early/late postpartum. Two analyses were performed. First, a series of multilevel spline regression models examined depression subscale trajectories over peripartum phase. Second, symptom networks and related metrics were estimated for each peripartum phase and compared. Somatic symptoms were most severe and had the most variable peripartum trajectory. The role of somatic symptoms within the networks also changed as a function of peripartum phase. Our results suggest that somatic symptoms can be severe and may play a crucial role in the maintenance of PPD. Thus, somatic symptoms should not be disregarded when assessing for PPD in obstetrical, psychiatric, and pediatric clinics, and clinical research.
Collapse
Affiliation(s)
- Lara Michelle Baez
- University of Miami, Department of Psychology, 5665 Ponce de Leon Blvd., Coral Gables, FL, 33124, USA.
| | - D Jeffrey Newport
- The University of Texas at Austin Dell Medical School, Departments of Psychiatry & Behavioral Sciences and Women's Health, 1601 Trinity Street, Austin TX, 78712, USA.
| | - Zachary N Stowe
- University of Wisconsin at Madison, Wisconsin Psychiatric Institute and Clinics, 6001 Research Park Boulevard, Madison, WI, 53719-1176, USA.
| | - Bettina T Knight
- University of Arkansas for Medical Sciences, Department of Psychiatry, 4301 West Markham St., Little Rock, AR, 72205-7199, USA.
| | - Aaron Shain Heller
- University of Miami, Department of Psychology, 5665 Ponce de Leon Blvd., Coral Gables, FL, 33124, USA.
| |
Collapse
|
28
|
Dobias ML, Sugarman MB, Mullarkey MC, Schleider JL. Predicting Mental Health Treatment Access Among Adolescents With Elevated Depressive Symptoms: Machine Learning Approaches. ADMINISTRATION AND POLICY IN MENTAL HEALTH AND MENTAL HEALTH SERVICES RESEARCH 2021; 49:88-103. [PMID: 34213666 DOI: 10.1007/s10488-021-01146-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/14/2021] [Indexed: 11/26/2022]
Abstract
A large proportion of adolescents experiencing depression never access treatment. To increase access to effective mental health care, it is critical to understand factors associated with increased versus decreased odds of adolescent treatment access. This study used individual depression symptoms and sociodemographic variables to predict whether and where adolescents with depression accessed mental health treatments. We performed a pre-registered, secondary analysis of data from the 2017 National Survey of Drug Use and Health (NSDUH), a nationally representative sample of non-institutionalized civilians in the United States. Using four cross-validated random forest models, we predicted whether adolescents with elevated past-year depressive symptoms (N = 1,671; ages 12-17 years) accessed specific mental health treatments in the previous 12 months ("yes/no" for inpatient, outpatient, school, any). 53.38% of adolescents with elevated depressive symptoms accessed treatment of any kind. Even with depressive symptoms and sociodemographic factors included as predictors, pre-registered random forests explained < 0.00% of pseudo out-of-sample deviance in adolescent access to inpatient, outpatient, school, or overall treatments. Exploratory elastic net models explained 0.80-2.50% of pseudo out-of-sample deviance in adolescent treatment access across all four treatment types. Neither individual depressive symptoms nor any socioeconomic variables meaningfully predicted specific or overall mental health treatment access in adolescents with elevated past-year symptoms. This study highlights substantial limitations in our capacity to predict whether and where adolescents access mental health treatment and underscores the broader need for more accessible, scalable adolescent depression treatments.
Collapse
Affiliation(s)
- Mallory L Dobias
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA.
| | - Michael B Sugarman
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA
| | - Michael C Mullarkey
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA
| | - Jessica L Schleider
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA
| |
Collapse
|
29
|
Network dynamics of depressive symptoms in antidepressant medication treatment: secondary analysis of eight clinical trials. Mol Psychiatry 2021; 26:3328-3335. [PMID: 32939019 DOI: 10.1038/s41380-020-00884-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 08/24/2020] [Accepted: 09/07/2020] [Indexed: 01/29/2023]
Abstract
Depression can be viewed as a network of depressive symptoms that tend to reinforce each other via feedback loops. Specific symptoms of depression may be differently responsive to antidepressant treatment, and some symptoms may be more important than others in the overall improvement of depression associated with treatment. We pooled prospective data from eight industry-sponsored placebo-controlled trials for paroxetine, fluoxetine and imipramine (total n = 3559) to examine whether improvements in specific depressive symptoms were more strongly related to improvements in other depressive symptoms among patients on active antidepressant treatment as compared to placebo. Depressive symptoms were assessed with the 17-item Hamilton Depression Rating Scale. Data on treatment was dichotomized into active treatment (receiving any antidepressant agent) vs. placebo. Time-lagged longitudinal analyses suggested that improvement in three symptoms-depressed mood, insomnia, and suicidality-had a broader overall impact on subsequent improvement in other depressive symptoms in the antidepressant condition compared to placebo (i.e., greater out-strength). Moreover, improvements in depressed mood and insomnia were more likely to follow the improvements in other symptoms in the antidepressant condition compared to placebo (i.e., greater in-strength). These results from clinical trial data suggest that depressed mood, insomnia, and suicidality may be particularly important in accounting for the remission and recovery in response to antidepressant treatment.
Collapse
|
30
|
Malgaroli M, Calderon A, Bonanno GA. Networks of major depressive disorder: A systematic review. Clin Psychol Rev 2021; 85:102000. [DOI: 10.1016/j.cpr.2021.102000] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 01/06/2021] [Accepted: 02/23/2021] [Indexed: 12/14/2022]
|
31
|
Izquierdo A, Cabello M, Leal I, Ayora M, Rodriguez-Jimenez R, Ibáñez Á, Díaz-Marsá M, Bravo-Ortiz MF, Baca-García E, Madrigal JLM, Fares-Otero NE, Díaz-Caneja CM, Arango C, Ayuso Mateos JL. How does neighbourhood socio-economic status affect the interrelationships between functioning dimensions in first episode of psychosis? A network analysis approach. Health Place 2021; 69:102555. [PMID: 33744489 DOI: 10.1016/j.healthplace.2021.102555] [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: 11/24/2020] [Revised: 03/01/2021] [Accepted: 03/01/2021] [Indexed: 10/21/2022]
Abstract
The links between psychosis and socio-economic disadvantage have been widely studied. No previous study has analysed the interrelationships and mutual influences between functioning dimensions in first episode of psychosis (FEP) according to their neighbourhood household income, using a multidimensional and transdiagnostic perspective. 170 patients and 129 controls, participants in an observational study (AGES-CM), comprised the study sample. The WHO Disability Assessment Schedule (WHODAS 2.0) was used to assess functioning, whereas participants' postcodes were used to obtain the average household income for each neighbourhood, collected by the Spanish National Statistics Institute (INE). Network analyses were conducted with the aim of defining the interrelationships between the different dimensions of functioning according to the neighbourhood household income. Our results show that lower neighbourhood socioeconomic level is associated with lower functioning in patients with FEP. Moreover, our findings suggest that "household responsibilities" plays a central role in the disability of patients who live in low-income neighbourhoods, whereas "dealing with strangers" is the most important node in the network of patients who live in high-income neighbourhoods. These results could help to personalize treatments, by allowing the identification of potential functioning areas to be prioritized in the treatment of FEP according to the patient's neighbourhood characteristics.
Collapse
Affiliation(s)
- Ana Izquierdo
- Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Del Hospital Universitario de La Princesa, IIS Princesa, CIBERSAM, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain
| | - María Cabello
- Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Del Hospital Universitario de La Princesa, IIS Princesa, CIBERSAM, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain
| | - Itziar Leal
- Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Del Hospital Universitario de La Princesa, IIS Princesa, CIBERSAM, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain
| | - Miriam Ayora
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Roberto Rodriguez-Jimenez
- Department of Psychiatry, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), CIBERSAM, CogPsy Group, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Ángela Ibáñez
- Department of Psychiatry, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria, IRYCIS, CIBERSAM, School of Medicine, Universidad de Alcalá, Madrid, Spain
| | - Marina Díaz-Marsá
- Institute of Psychiatry and Mental Health, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria Del Hospital Clínico San Carlos (IdISSC), CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - María-Fé Bravo-Ortiz
- Department of Psychiatry, Clinical Psychology and Mental Health, Hospital Universitario de La Paz, Hospital La Paz Institute for Health Research (IdiPAZ), School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain
| | - Enrique Baca-García
- Department of Psychiatry, Hospital Universitario Fundación Jiménez Diaz, Hospital Universitario Rey Juan Carlos, Hospital General de Villalba, Hospital Universitario Infanta Elena, CIBERSAM, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain; Universidad Católica Del Maule, Talca, Chile
| | - José L M Madrigal
- Department of Pharmacology and Toxicology (FarmaMED), School of Medicine, Universidad Complutense de Madrid, CIBERSAM, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), IUIN-UCM, Madrid, Spain
| | - Natalia E Fares-Otero
- Department of Psychiatry, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), CIBERSAM, CogPsy Group, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Jose Luis Ayuso Mateos
- Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Del Hospital Universitario de La Princesa, IIS Princesa, CIBERSAM, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain.
| | | |
Collapse
|
32
|
Kreiter D, Drukker M, Mujagic Z, Vork L, Rutten BPF, van Os J, Masclee AAM, Kruimel JW, Leue C. Symptom-network dynamics in irritable bowel syndrome with comorbid panic disorder using electronic momentary assessment: A randomized controlled trial of escitalopram vs. placebo. J Psychosom Res 2021; 141:110351. [PMID: 33412422 DOI: 10.1016/j.jpsychores.2020.110351] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/15/2020] [Accepted: 12/22/2020] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Momentary ecological assessment indicated alleviated abdominal pain in escitalopram treatment of irritable bowel syndrome (IBS) with comorbid panic disorder. Hitherto, little is known about symptom formation, i.e., how psychological impact physical symptoms, and vice versa, and about the effect of SSRI-treatment on symptom formation. OBJECTIVE To investigate how psychological and somatic symptoms co-vary over time in IBS patients with comorbid panic disorder and how they are affected by escitalopram treatment. METHODS Experience sampling data from 14 IBS patients with panic disorder were obtained from a single-centre, double-blind, parallel-group, randomized controlled trial on escitalopram versus placebo. At baseline, after three and six months, multilevel time-lagged linear regression analysis was used to construct symptom networks. Network connections represented coefficients between various affect and gastrointestinal items. RESULTS Connectivity increased up to 3 months in both groups. Between 3 and 6 months, connectivity decreased for placebo and further increased in the escitalopram group. Additionally, a steep increase in node strength for negative affect nodes was observed in the escitalopram network and the opposite for positive affect nodes. Over time, group symptom networks became increasingly different from each other. Anxious-anxious and enthusiastic-relaxed became significantly different between groups at 6 months. The connection that changed significantly in all analyses was anxious-anxious. CONCLUSIONS Escitalopram treatment was associated with changes in the symptom networks in IBS patients with panic disorder. While mood and physical symptoms improve over time, mainly connectivity between mood nodes changed, possibly pointing towards a healthier emotion regulation resulting in alleviation of physical symptoms.
Collapse
Affiliation(s)
- Daniël Kreiter
- Faculty of Health, Medicine & Life Sciences, Maastricht University, Maastricht, the Netherlands.
| | - Marjan Drukker
- Department of Psychiatry and Psychology, School of Mental Health and Neuroscience (MHeNS), Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Zlatan Mujagic
- Division of Gastroenterology-Hepatology, Department of Internal Medicine, Maastricht University Medical Centre, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht, the Netherlands
| | - Lisa Vork
- Division of Gastroenterology-Hepatology, Department of Internal Medicine, Maastricht University Medical Centre, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht, the Netherlands
| | - Bart P F Rutten
- Department of Psychiatry and Psychology, School of Mental Health and Neuroscience (MHeNS), Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jim van Os
- Department of Psychiatry and Psychology, School of Mental Health and Neuroscience (MHeNS), Maastricht University Medical Centre, Maastricht, the Netherlands; Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Ad A M Masclee
- Division of Gastroenterology-Hepatology, Department of Internal Medicine, Maastricht University Medical Centre, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht, the Netherlands
| | - Joanna W Kruimel
- Division of Gastroenterology-Hepatology, Department of Internal Medicine, Maastricht University Medical Centre, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht, the Netherlands
| | - Carsten Leue
- Department of Psychiatry and Psychology, School of Mental Health and Neuroscience (MHeNS), Maastricht University Medical Centre, Maastricht, the Netherlands.
| |
Collapse
|
33
|
Yun JY, Kim YK. Phenotype Network and Brain Structural Covariance Network of Major Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:3-18. [PMID: 33834391 DOI: 10.1007/978-981-33-6044-0_1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Phenotype networks enable clinicians to elucidate the patterns of coexistence and interactions among the clinical symptoms, negative cognitive styles , neurocognitive performance, and environmental factors in major depressive disorder (MDD). Results of phenotype network approach could be used in finding the target symptoms as these are tightly connected or associated with many other phenomena within the phenotype network of MDD specifically when comorbid psychiatric disorder(s) is/are present. Further, by comparing the differential patterns of phenotype networks before and after the treatment, changing or enduring patterns of associations among the clinical phenomena in MDD have been deciphered.Brain structural covariance networks describe the inter-regional co-varying patterns of brain morphologies, and overlapping findings have been reported between the brain structural covariance network and coordinated trajectories of brain development and maturation. Intra-individual brain structural covariance illustrates the degrees of similarities among the different brain regions for how much the values of brain morphological features are deviated from those of healthy controls. Inter-individual brain structural covariance reflects the degrees of concordance among the different brain regions for the inter-individual distribution of brain morphologic values. Estimation of the graph metrics for these brain structural covariance networks uncovers the organizational profile of brain morphological variations in the whole brain and the regional distribution of brain hubs.
Collapse
Affiliation(s)
- 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.
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, College of Medicine, Ansan, Republic of Korea
| |
Collapse
|
34
|
Wichers M, Riese H, Hodges TM, Snippe E, Bos FM. A Narrative Review of Network Studies in Depression: What Different Methodological Approaches Tell Us About Depression. Front Psychiatry 2021; 12:719490. [PMID: 34777038 PMCID: PMC8581034 DOI: 10.3389/fpsyt.2021.719490] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/30/2021] [Indexed: 11/13/2022] Open
Abstract
The network theory of psychopathology proposes that mental disorders arise from direct interactions between symptoms. This theory provides a promising framework to understand the development and maintenance of mental disorders such as depression. In this narrative review, we summarize the literature on network studies in the field of depression. Four methodological network approaches are distinguished: (i) studies focusing on symptoms at the macro-level vs. (ii) on momentary states at the micro-level, and (iii) studies based on cross-sectional vs. (iv) time-series (dynamic) data. Fifty-six studies were identified. We found that different methodological approaches to network theory yielded largely inconsistent findings on depression. Centrality is a notable exception: the majority of studies identified either positive affect or anhedonia as central nodes. To aid future research in this field, we outline a novel complementary network theory, the momentary affect dynamics (MAD) network theory, to understand the development of depression. Furthermore, we provide directions for future research and discuss if and how networks might be used in clinical practice. We conclude that more empirical network studies are needed to determine whether the network theory of psychopathology can indeed enhance our understanding of the underlying structure of depression and advance clinical treatment.
Collapse
Affiliation(s)
- Marieke Wichers
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Harriëtte Riese
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Taylor M Hodges
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Evelien Snippe
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands
| | - Fionneke M Bos
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, Groningen, Netherlands.,University of Groningen, University Medical Center Groningen, Department of Psychiatry, Rob Giel Research Center, Groningen, Netherlands
| |
Collapse
|
35
|
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: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 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.
Collapse
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
| |
Collapse
|
36
|
Cervin M, Storch EA, Piacentini J, Birmaher B, Compton SN, Albano AM, Gosch E, Walkup JT, Kendall PC. Symptom-specific effects of cognitive-behavioral therapy, sertraline, and their combination in a large randomized controlled trial of pediatric anxiety disorders. J Child Psychol Psychiatry 2020; 61:492-502. [PMID: 31471911 DOI: 10.1111/jcpp.13124] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/06/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Pediatric anxiety disorders are highly prevalent and associated with significant functional disabilities and lifelong morbidity. Cognitive-behavioral therapy (CBT), sertraline, and their combination are effective treatments, but little is known about how these treatments exert their effects. METHODS Using network intervention analysis (NIA), we analyzed data from the largest randomized controlled treatment trial of pediatric anxiety disorders (Child/Adolescent Anxiety Multimodal Study, NCT00052078, clinicaltrials.gov/ct2/show/NCT00052078) and outlined the causal symptom domain-specific effects of CBT, sertraline, and their combination over the course of the 12-week treatment while taking into account both specificity and overlap between symptom domains. RESULTS All active treatments produced positive effects with the most pronounced and consistent effects emerging in relation to psychological distress, family interference, and avoidance. Psychological distress was consistently the most and physical symptoms the least central symptom domain in the disorder network. CONCLUSIONS All active treatments showed beneficial effects when compared to placebo, and NIA identified that these effects were exerted similarly across treatments and primarily through a reduction of psychological distress, family interference, and avoidance. CBT and sertraline may have differential mechanisms of action in relation to psychological distress. Given the lack of causal effects on interference outside family and physical symptoms, interventions tailored to target these domains may aid in the building of more effective treatments. Psychological distress and avoidance should remain key treatment focuses because of their central roles in the disorder network. The findings inform and promote developing more effective interventions.
Collapse
Affiliation(s)
- Matti Cervin
- Department of Clinical Sciences Lund, Lund University and Skåne Child and Adolescent Psychiatry, Lund, Sweden
| | - Eric A Storch
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - John Piacentini
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
| | - Boris Birmaher
- Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Scott N Compton
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | | | - Elizabeth Gosch
- Department of Clinical Psychology, Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA
| | - John T Walkup
- Department of Psychiatry, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Philip C Kendall
- Department of Psychology, Temple University, Philadelphia, PA, USA
| |
Collapse
|
37
|
Wasil AR, Venturo-Conerly KE, Shinde S, Patel V, Jones PJ. Applying network analysis to understand depression and substance use in Indian adolescents. J Affect Disord 2020; 265:278-286. [PMID: 32090752 DOI: 10.1016/j.jad.2020.01.025] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 11/14/2019] [Accepted: 01/05/2020] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Network analysis has been used to better understand relationships between depressive symptoms. Existing work has rarely examined networks of adolescents or individuals in non-western countries. METHODS We used data from 13,035 adolescents (52.5% male; Mage=13.8) from Bihar, a low-resource state in India. Depression was measured using the Patient Health Questionnaire-9, and substance use was measured using a questionnaire adapted from the World Health Organization. We modeled a network of depressive symptoms and a network examining connections between depressive symptoms and substance use. RESULTS The most commonly reported depressive symptoms were sleep problems, poor appetite, and low energy. In the depression network, feeling like a failure and sad mood were the most central symptoms, and somatic symptoms clustered together. To our surprise, depressive symptoms were only weakly associated with substance use. LIMITATIONS Our study uses cross-sectional data, which are not sufficient to draw causal inferences about the relationships between symptoms. Additionally, we used an exploratory data-driven approach, and we did not pose a priori hypotheses about the relationships between symptoms. DISCUSSION Our findings suggest that feelings like a failure and sad mood are highly central symptoms in Indian adolescents; future research may examine if these symptoms are strong targets for intervention. Sad mood has commonly been identified as a central symptom of depression in western samples, while feeling like a failure has not. We offer avenues for future research, illustrating how network analysis may enhance our ability to understand, prevent, and treat psychopathology in LMICs.
Collapse
Affiliation(s)
- Akash R Wasil
- Department of Psychology, Harvard University, United States; Department of Psychology, University of Pennsylvania, United States
| | | | | | - Vikram Patel
- Department of Global Health and Social Medicine, Harvard Medical School, United States; Sangath, Goa, India
| | - Payton J Jones
- Department of Psychology, Harvard University, United States
| |
Collapse
|
38
|
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: 279] [Impact Index Per Article: 69.8] [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.
Collapse
Affiliation(s)
- Donald J. Robinaugh
- Massachusetts General Hospital, Department of Psychiatry
- Harvard Medical School
| | | | - Emma R. Toner
- Massachusetts General Hospital, Department of Psychiatry
| | | |
Collapse
|
39
|
Funkhouser CJ, Correa KA, Gorka SM, Nelson BD, Phan KL, Shankman SA. The replicability and generalizability of internalizing symptom networks across five samples. JOURNAL OF ABNORMAL PSYCHOLOGY 2020; 129:191-203. [PMID: 31829638 PMCID: PMC6980885 DOI: 10.1037/abn0000496] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
The popularity of network analysis in psychopathology research has increased exponentially in recent years. Yet, little research has examined the replicability of cross-sectional psychopathology network models, and those that have used single items for symptoms rather than multiitem scales. The present study therefore examined the replicability and generalizability of regularized partial correlation networks of internalizing symptoms within and across 5 samples (total N = 2,573) using the Inventory for Depression and Anxiety Symptoms, a factor analytically derived measure of individual internalizing symptoms. As different metrics may yield different conclusions about the replicability of network parameters, we examined both global and specific metrics of similarity between networks. Correlations within and between nonclinical samples suggested considerable global similarities in network structure (rss = .53-.87) and centrality strength (rss = .37-.86), but weaker similarities in network structure (rss = .36-.66) and centrality (rss = .04-.54) between clinical and nonclinical samples. Global strength (i.e., connectivity) did not significantly differ across all 5 networks and few edges (0-5.5%) significantly differed between networks. Specific metrics of similarity indicated that, on average, approximately 80% of edges were consistently estimated within and between all 5 samples. The most central symptom (i.e., dysphoria) was consistent within and across samples, but there were few other matches in centrality rank-order. In sum, there were considerable similarities in network structure, the presence and sign of individual edges, and the most central symptom within and across internalizing symptom networks estimated from nonclinical samples, but global metrics suggested network structure and symptom centrality had weak to moderate generalizability from nonclinical to clinical samples. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
Collapse
Affiliation(s)
- Carter J. Funkhouser
- University of Illinois at Chicago Department of Psychology
- Northwestern University Department of Psychiatry and Behavioral Sciences
| | - Kelly A. Correa
- University of Illinois at Chicago Department of Psychology
- Northwestern University Department of Psychiatry and Behavioral Sciences
| | | | | | - K. Luan Phan
- The Ohio State University Department of Psychiatry and Behavioral Health
| | - Stewart A. Shankman
- University of Illinois at Chicago Department of Psychology
- Northwestern University Department of Psychiatry and Behavioral Sciences
- University of Illinois at Chicago Department of Psychiatry
| |
Collapse
|
40
|
Network structure of depression symptomology in participants with and without depressive disorder: the population-based Health 2000-2011 study. Soc Psychiatry Psychiatr Epidemiol 2020; 55:1273-1282. [PMID: 32047972 PMCID: PMC7544719 DOI: 10.1007/s00127-020-01843-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 02/03/2020] [Indexed: 12/31/2022]
Abstract
PURPOSE Putative causal relations among depressive symptoms in forms of network structures have been of recent interest, with prior studies suggesting that high connectivity of the symptom network may drive the disease process. We examined in detail the network structure of depressive symptoms among participants with and without depressive disorders (DD; consisting of major depressive disorder (MDD) and dysthymia) at two time points. METHODS Participants were from the nationally representative Health 2000 and Health 2011 surveys. In 2000 and 2011, there were 5998 healthy participants (DD-) and 595 participants with DD diagnosis (DD+). Depressive symptoms were measured using the 13-item version of the Beck Depression Inventory (BDI). Fused Graphical Lasso was used to estimate network structures, and mixed graphical models were used to assess network connectivity and symptom centrality. Network community structure was examined using the walktrap-algorithm and minimum spanning trees (MST). Symptom centrality was evaluated with expected influence and participation coefficients. RESULTS Overall connectivity did not differ between networks from participants with and without DD, but more simple community structure was observed among those with DD compared to those without DD. Exploratory analyses revealed small differences between the samples in the order of one centrality estimate participation coefficient. CONCLUSIONS Community structure, but not overall connectivity of the symptom network, may be different for people with DD compared to people without DD. This difference may be of importance when estimating the overall connectivity differences between groups with and without mental disorders.
Collapse
|
41
|
Castro D, Ferreira F, de Castro I, Rodrigues AR, Correia M, Ribeiro J, Ferreira TB. The Differential Role of Central and Bridge Symptoms in Deactivating Psychopathological Networks. Front Psychol 2019; 10:2448. [PMID: 31827450 PMCID: PMC6849493 DOI: 10.3389/fpsyg.2019.02448] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 10/15/2019] [Indexed: 12/19/2022] Open
Abstract
The network model of psychopathology suggests that central and bridge symptoms represent promising treatment targets because they may accelerate the deactivation of the network of interactions between the symptoms of mental disorders. However, the evidence confirming this hypothesis is scarce. This study re-analyzed a convenience sample of 51 cross-sectional psychopathological networks published in previous studies addressing diverse mental disorders or clinically relevant problems. In order to address the hypothesis that central and bridge symptoms are valuable treatment targets, this study simulated five distinct attack conditions on the psychopathological networks by deactivating symptoms based on two characteristics of central symptoms (degree and strength), two characteristics of bridge symptoms (overlap and bridgeness), and at random. The differential impact of the characteristics of these symptoms was assessed in terms of the magnitude and the extent of the attack required to achieve a maximum impact on the number of components, average path length, and connectivity. Only moderate evidence was obtained to sustain the hypothesis that central and bridge symptoms constitute preferential treatment targets. The results suggest that the degree, strength, and bridgeness attack conditions are more effective than the random attack condition only in increasing the number of components of the psychopathological networks. The degree attack condition seemed to perform better than the strength, bridgeness, and overlap attack conditions. Overlapping symptoms evidenced limited impact on the psychopathological networks. The need to address the basic mechanisms underlying the structure and dynamics of psychopathological networks through the expansion of the current methodological framework and its consolidation in more robust theories is stressed.
Collapse
Affiliation(s)
- Daniel Castro
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| | - Filipa Ferreira
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| | - Inês de Castro
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
| | - Ana Rita Rodrigues
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| | - Marta Correia
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
| | - Josefina Ribeiro
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
| | - Tiago Bento Ferreira
- Department of Social and Behavioural Sciences, University Institute of Maia, Maia, Portugal
- Center for Psychology at University of Porto, Porto, Portugal
| |
Collapse
|
42
|
McElroy E, Napoleone E, Wolpert M, Patalay P. Structure and Connectivity of Depressive Symptom Networks Corresponding to Early Treatment Response. EClinicalMedicine 2019; 8:29-36. [PMID: 31193604 PMCID: PMC6537518 DOI: 10.1016/j.eclinm.2019.02.009] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 02/14/2019] [Accepted: 02/25/2019] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND There are suggestions that denser network connectivity (i.e., the strength of associations between individual symptoms) may be a prognostic indicator of poor treatment response in depression. We sought to examine this aspect of depressive symptom networks in the context of early responses to treatment in adolescents. METHODS Routine psychiatric data were obtained for child/adolescent service users who underwent at least three treatment sessions in publicly funded services in England between 2011 and 2015 (N = 3017, 78% female; mean age [SD] = 14.43 years [1.75]). Depressive symptoms were assessed using the Revised Children's Anxiety and Depression Scale at presentation, and again after three treatment sessions. Treatment response was determined using the Reliable Change Index. Network analysis was used to compare the depressive symptom structure and connectivity of sub-samples who, after three treatment sessions had: 1) positively responded (n = 566), 2) not reliably changed (n = 2277), and 3) reliably deteriorated (n = 174), using matched samples to control for baseline severity. FINDINGS Overall connectivity (i.e., the summed total of weighted connections) was significantly weaker for the positive treatment response group at baseline (compared with unchanged and deteriorated groups), however, this group saw the largest increase in connectivity over the course of treatment. With regard to the overall importance of specific symptoms within the networks, fatigue was highest in strength for the unchanged and deteriorated groups, whereas low mood was highest in strength for the improved group. INTERPRETATION This study demonstrates that adolescents who respond early to treatment for depression are characterised by symptom networks that are less densely connected initially, yet increase in connectivity over the course of treatment. This may be indicative of 'positive spirals' whereby improvement in one symptom triggers improvements in other symptoms, thereby increasing symptom-symptom associations even as severity decreases. FUNDING The study was supported by the Wellcome Trust grant 204366/Z/16/Z. The funders had no role in the study design, data collection, data analysis, interpretation, or writing of the report.
Collapse
Affiliation(s)
- Eoin McElroy
- Institute of Psychology, Health and Society, University of Liverpool, Liverpool, UK
| | - Elisa Napoleone
- Evidence Based Practice Unit, University College London, London, UK
- The Anna Freud Centre, London, UK
| | - Miranda Wolpert
- Evidence Based Practice Unit, University College London, London, UK
- The Anna Freud Centre, London, UK
| | - Praveetha Patalay
- Institute of Psychology, Health and Society, University of Liverpool, Liverpool, UK
| |
Collapse
|