Bouncing back from life's perturbations: Formalizing psychological resilience from a complex systems perspective.

Experiencing stressful or traumatic events can lead to a range of responses, from mild disruptions to severe and persistent mental health issues. Understanding the various trajectories of response to adversity is crucial for developing effective interventions and support systems. Researchers have identified four commonly observed response trajectories to adversity, from which the resilient is the most common one.

Differential impact of preventive cognitive therapy while tapering antidepressants versus maintenance antidepressant treatment on affect fluctuations and individual affect networks and impact on relapse: a secondary analysis of a randomised controlled trial.

Background: There is an urgent need to better understand and prevent relapse in major depressive disorder (MDD). We explored the differential impact of various MDD relapse prevention strategies (pharmacological and/or psychological) on affect fluctuations and individual affect networks in a randomised setting, and their predictive value for relapse.

Methods: We did a secondary analysis using experience sampling methodology (ESM) data from individuals with remitted recurrent depression that was collected alongside a randomised controlled trial that ran in the Netherlands, comparing: (I) tapering antidepressants while receiving preventive cognitive therapy (PCT), (II) combining antidepressants with PCT, or (III) continuing antidepressants without PCT, for the prevention of depressive relapse, as well as ESM data from 11 healthy controls.

Does the network structure of obsessive-compulsive symptoms at treatment admission identify patients at risk for non-response?

Exposure and response prevention is the gold-standard treatment for obsessive compulsive disorder (OCD), yet up to half of patients do not adequately respond. Thus, different approaches to identifying and intervening with non-responders are badly needed. One approach would be to better understand the functional connections among aspects of OCD symptoms and, ultimately, how to target those associations in treatment.

Comparing network structures on three aspects: A permutation test.

Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking.

Intervening on psychopathology networks: Evaluating intervention targets through simulations.

Identifying the different influences of symptoms in dynamic psychopathology models may hold promise for increasing treatment efficacy in clinical applications. Dynamic psychopathology models study the behavioral patterns of symptom networks, where symptoms mutually enforce each other. Interventions could be tailored to specific symptoms that are most effective at lowering symptom activity or that hinder the further development of psychopathology.

Advancing urban mental health research: from complexity science to actionable targets for intervention.

Urbanisation and common mental disorders (CMDs; ie, depressive, anxiety, and substance use disorders) are increasing worldwide. In this Review, we discuss how urbanicity and risk of CMDs relate to each other and call for a complexity science approach to advance understanding of this interrelationship. We did an ecological analysis using data on urbanicity and CMD burden in 191 countries.

Symptom networks in major depression do not diverge across sex, familial risk, and environmental risk.

Background: Major depression (MD) is a heterogeneous disorder in terms of its symptoms. Symptoms vary by presence of risk factors such as female sex, familial risk, and environmental adversity. However, it is unclear if these factors also influence interactions between symptoms.

The Mental Health Ecosystem: Extending Symptom Networks With Risk and Protective Factors.

Inspired by modeling approaches from the ecosystems literature, in this paper, we expand the network approach to psychopathology with risk and protective factors to arrive at an integrated analysis of resilience. We take a complexity approach to investigate the multifactorial nature of resilience and present a system in which a network of interacting psychiatric symptoms is targeted by risk and protective factors. These risk and protective factors influence symptom development patterns and thereby increase or decrease the probability that the symptom network is pulled toward a healthy or disorder state.

Inflammatory phenotype of depression symptom structure: A network perspective.

Background: There has been increasing interest in classifying inflammatory phenotypes of depression. Most investigations into inflammatory phenotypes only have tested whether elevated inflammation is associated with elevated levels of depression symptoms, or risk for a diagnosis. This study expanded the definition of phenotype to include the structure of depression symptoms as a function of inflammation.

On the Importance of Estimating Parameter Uncertainty in Network Psychometrics: A Response to Forbes et al. (2019).

In their recent paper, Forbes et al. (2019; FWMK) evaluate the replicability of network models in two studies. They identify considerable replicability issues, concluding that "current 'state-of-the-art' methods in the psychopathology network literature […] are not well-suited to analyzing the structure of the relationships between individual symptoms".

Investigating the Utility of Fixed-margin Sampling in Network Psychometrics.

Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. We argue that fixed-margin sampling cannot be used for this purpose, as it generates data under a particular null-hypothesis: a unidimensional factor model with interchangeable indicators (i.

Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections.

Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures.

Assessment of Symptom Network Density as a Prognostic Marker of Treatment Response in Adolescent Depression.

This cohort study uses the 33-item Mood and Feelings Questionnaire to examine whether symptom network density is associated with treatment response in adolescent depression.

False alarm? A comprehensive reanalysis of "Evidence that psychopathology symptom networks have limited replicability" by Forbes, Wright, Markon, and Krueger (2017).

Forbes, Wright, Markon, and Krueger (2017) stated that "psychopathology networks have limited replicability" (p. 1011) and that "popular network analysis methods produce unreliable results" (p. 1011).

A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders.

Depressive symptoms occur frequently in patients with schizophrenia. Several factor analytical studies investigated the associations between positive, negative and depressive symptoms and reported difficulties differentiating between these symptom domains. Here, we argue that a network approach may offer insights into these associations, by exploring interrelations between symptoms.

The Cascade of Stress: A Network Approach to Explore Differential Dynamics in Populations Varying in Risk for Psychosis.

Stress plays a central role in the development and persistence of psychosis. Network analysis may help to reveal mechanisms at the level of the micro-dynamic effects between stress, other daily experiences and symptomatology. This is the first study to examine time-lagged networks of the relations between minor daily stress, momentary affect/thoughts, psychotic experiences, and other potentially relevant daily life contexts in individuals varying in risk for psychosis.

A symptom network structure of the psychosis spectrum.

Current diagnostic systems mainly focus on symptoms needed to classify patients with a specific mental disorder and do not take into account the variation in co-occurring symptoms and the interaction between the symptoms themselves. The innovative network approach aims to further our understanding of mental disorders by focusing on meaningful connections between individual symptoms of a disorder and has thus far proven valuable insights to psychopathology. The aims of current study were to I) construct a symptom network and investigate interactions between a wide array of psychotic symptoms; II) identify the most important symptoms within this network and III) perform an explorative shortest pathway analysis between depressive and delusional symptoms.

Major Depression as a Complex Dynamic System.

In this paper, we characterize major depression (MD) as a complex dynamic system in which symptoms (e.g., insomnia and fatigue) are directly connected to one another in a network structure.

Mental disorders as networks of problems: a review of recent insights.

Purpose: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years.

Methods: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention.

Measuring depression over time . . . Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression.

In depression research, symptoms are routinely assessed via rating scales and added to construct sum-scores. These scores are used as a proxy for depression severity in cross-sectional research, and differences in sum-scores over time are taken to reflect changes in an underlying depression construct. To allow for such interpretations, rating scales must (a) measure a single construct, and (b) measure that construct in the same way across time.

A Network Approach to Psychosis: Pathways Between Childhood Trauma and Psychotic Symptoms.

Childhood trauma (CT) has been identified as a potential risk factor for the onset of psychotic disorders. However, to date, there is limited consensus with respect to which symptoms may ensue after exposure to trauma in early life, and whether specific pathways may account for these associations. The aim of the present study was to use the novel network approach to investigate how different types of traumatic childhood experiences relate to specific symptoms of psychotic disorders and to identify pathways that may be involved in the relationship between CT and psychosis.

The network structure of psychopathology in a community sample of preadolescents.

Psychopathology is often classified according to diagnostic categories or scale scores. These ignore potentially important information about associations between specific symptoms and, consequently, lead to heterogeneous constructs that may mask relevant individual differences. Network analyses focus on these specific symptom associations, providing the opportunity to explore the complex structure of psychopathology in more detail.