Advancing the network theory of mental disorders: A computational model of panic disorder.

The network theory of psychopathology posits that mental disorders are systems of mutually reinforcing symptoms. This framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. Cognitive behavioral theories of mental disorders provide considerable insight into how these systems may operate.

Ecological momentary assessment in prolonged grief research: Feasibility, acceptability, and measurement reactivity.

Ecological momentary assessment (EMA) is a method of data collection that entails prompting individuals to report their experiences (e.g., thoughts, feelings, and behaviors) in real time over the course of their day-to-day lives.

Productive explanation: A framework for evaluating explanations in psychological science.

The explanation of psychological phenomena is a central aim of psychological science. However, the nature of explanation and the processes by which we evaluate whether a theory explains a phenomenon are often unclear. Consequently, it is often unknown whether a given psychological theory indeed explains a phenomenon.

Towards a general modeling framework of resource competition in cognitive development.

The current paper presents an integrated formal model of typical and atypical development based on the mechanisms of mutualism and resource competition. The mutualistic network model is extended with the dynamics of competition for limited resources, such as time and environmental factors. The proposed model generates patterns that resemble established phenomena in cognitive development: the positive manifold, developmental phases, developmental delays and lack of early indicators in atypical development, developmental regression, and "quasi-autism" caused by extreme environmental deprivation.

Quantifying and addressing the impact of measurement error in network models.

Network psychometric models are often estimated using a single indicator for each node in the network, thus failing to consider potential measurement error. In this study, we investigate the impact of measurement error on cross-sectional network models. First, we conduct a simulation study to evaluate the performance of models based on single indicators as well as models that utilize information from multiple indicators per node, including average scores, factor scores, and latent variables.

Revisiting the theoretical and methodological foundations of depression measurement.

Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes and treatments for these disorders. In this Perspective, we suggest that such progress crucially depends on our ability to measure depression. We review the many problems with depression measurement, including limited evidence of validity and reliability.

The course of symptoms in the first 27 months following bereavement: A latent trajectory analysis of prolonged grief, posttraumatic stress, and depression.

Background: Much remains unknown about the course of grief in the early months following bereavement, including the prevalence and timing of a recovery trajectory, whether specific symptoms mark a failure to recover, and the co-occurrence of chronic prolonged grief (PG), posttraumatic stress (PTS) and depression symptoms.

Methods: Two hundred fifty-nine participants completed PG, PTS and depression questionnaires up to eleven times every six weeks during the two years post-bereavement. We used Latent Class Growth Mixture Modeling (LCGMM) to identify subgroups of bereaved individuals sharing similar trajectories for each disorder.

Estimating the symptom structure of bipolar disorder via network analysis: Energy dysregulation as a central symptom.

Using network analysis, we estimated the structure of relations among manic and depressive symptoms, respectively, in 486 patients (59% women; age: M = 37, SD = 12.1) with bipolar disorder prior to their entering a clinical trial. We computed three types of networks: (a) Gaussian graphical models (GGMs) depicting regularized partial correlations, (b) regression-based GGMs depicting nonregularized partial correlations, and (c) directed acyclic graphs (DAGs) via a Bayesian hill-climbing algorithm.

Modeling psychopathology: From data models to formal theories.

Over the past decade, there has been a surge of empirical research investigating mental disorders as complex systems. In this article, we investigate how to best make use of this growing body of empirical research and move the field toward its fundamental aims of explaining, predicting, and controlling psychopathology. We first review the contemporary philosophy of science literature on scientific theories and argue that fully achieving the aims of explanation, prediction, and control requires that we construct formal theories of mental disorders: theories expressed in the language of mathematics or a computational programming language.

An Answer to "So What?" Implications of Network Theory for Research and Practice.

Research and practice in psychiatry and clinical psychology have been guided by differing schools of thought over the years. Recently, the network theory of psychopathology has arisen as a framework for thinking about mental health. Network theory challenges three common assumptions: psychological problems are caused by disease entities that exist independently of their signs and symptoms, classification and diagnosis of psychological problems should follow a medical model, and psychological problems are caused by diseases or aberrations in the brain.

Traumatic grief research and care in the aftermath of the COVID-19 pandemic.

Background: A significant increase in the number of individuals suffering from prolonged grief disorder is expected in the aftermath of the COVID-19 pandemic for two main reasons. First, the number of excess deaths has contributed to an immense number of bereaved individuals. Second, recent literature has shown that circumstances associated with COVID-19 deaths may be contributing to increased risk for the development of prolonged grief disorder.

The causal systems approach to prolonged grief: Recent developments and future directions.

The network theory of prolonged grief posits that causal interactions among symptoms of prolonged grief play a significant role in their coherence and persistence as a syndrome. Drawing on recent developments in the broader network approach to psychopathology, we argue that advancing our understanding of the causal system that gives rise to prolonged grief will require that we (a) strengthen our assessment of each component of the grief syndrome, (b) investigate intra-individual relationships among grief components as they evolve over time within individuals, (c) incorporate biological and social components into network studies of grief, and (d) generate formal theories that posit precisely how these biological, psychological, and social components interact with one another to give rise to prolonged grief disorder.

On the Control of Psychological Networks.

The combination of network theory and network psychometric methods has opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, simply estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, nor is it sufficient for determining the potential efficacy of any given intervention.

Posttraumatic Distress Symptoms and Their Response to Treatment in Adults With Prolonged Grief Disorder.

Objective: Posttraumatic stress disorder and prolonged grief disorder (PGD) arise following major life stressors and may share some overlapping symptomatology. This study aimed to examine the presence and response to treatment of posttraumatic stress symptoms (PTSS) in bereaved adults with a primary diagnosis of PGD.

Methods: A randomized controlled trial of 395 adults with PGD (defined as an Inventory of Complicated Grief score ≥ 30 plus confirmation on structured clinical interview) randomly assigned participants to either complicated grief treatment (CGT) with citalopram, CGT plus placebo, citalopram, or placebo between March 2010 and September 2014.

Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction.

In recent years, a growing chorus of researchers has argued that psychological theory is in a state of crisis: Theories are rarely developed in a way that indicates an accumulation of knowledge. Paul Meehl raised this very concern more than 40 years ago. Yet in the ensuing decades, little has improved.

Sex differences in depressive symptoms and their networks in a treatment-seeking population - a cross-sectional study.

Background: The higher prevalence of major depressive disorder (MDD) in females relative to males is well-established. Some authors have posited this difference arises to divergent symptom profiles in females vs. males.

Systems all the way down: embracing complexity in mental health research.

In this editorial for the collection on complexity in mental health research, we introduce and summarize the inaugural contributions to this collection: a series of theoretical, methodological, and empirical papers that aim to chart a path forward for investigating mental health in all its complexity. A central theme emerges from these contributions: if we are to make genuine progress in explaining, predicting, and treating mental illness, we must study the systems from which psychopathology emerges. As the articles in this collection make clear, the systems that give rise to psychopathology encompass a host of components across biological, psychological, and social levels of analysis, intertwined in a web of complex interactions.

"Identity confusion in complicated grief: A closer look": Correction.

Reports an error in "Identity confusion in complicated grief: A closer look" by Benjamin W. Bellet, Nicole J. LeBlanc, Marie-Christine Nizzi, Mikaela L.