Author
Emma R. Toner
Other affiliations: University of Virginia
Bio: Emma R. Toner is an academic researcher from Harvard University. The author has contributed to research in topics: Psychopathology & Psychology. The author has an hindex of 2, co-authored 5 publications receiving 128 citations. Previous affiliations of Emma R. Toner include University of Virginia.
Topics: Psychopathology, Psychology, Complicated grief, Panic, Anxiety
Papers
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TL;DR: An overview and critical analysis of 363 articles produced in the first decade of the network approach to psychopathology is provided, with a focus on key theoretical, methodological, and empirical contributions.
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.
272 citations
TL;DR: Shame is identified as the more pathogenic moral emotion for bereaved adults and guilt predicted greater psychological distress at low levels of shame in this sample, whereas guilt in the absence of shame is often considered adaptive.
13 citations
01 Dec 2019
TL;DR: Findings provide support for the prediction derived from cognitive–behavioural theories and some preliminary evidence that response to a biological challenge may have clinical utility as a marker of vulnerability to panic attacks pending further research and development.
Abstract: Background Cognitive–behavioural theories of panic disorder posit that panic attacks arise from a positive feedback loop between arousal-related bodily sensations and perceived threat. In a recently developed computational model formalising these theories of panic attacks, it was observed that the response to a simulated perturbation to arousal provided a strong indicator of vulnerability to panic attacks and panic disorder. In this review, we evaluate whether this observation is borne out in the empirical literature that has examined responses to biological challenge (eg, CO2 inhalation) and their relation to subsequent panic attacks and panic disorder. Method We searched PubMed, Web of Science and PsycINFO using keywords denoting provocation agents (eg, sodium lactate) and procedures (eg, infusion) combined with keywords relevant to panic disorder (eg, panic). Articles were eligible if they used response to a biological challenge paradigm to prospectively predict panic attacks or panic disorder. Results We identified four eligible studies. Pooled effect sizes suggest that there is biological challenge response has a moderate prospective association with subsequent panic attacks, but no prospective relationship with panic disorder. Conclusions These findings provide support for the prediction derived from cognitive–behavioural theories and some preliminary evidence that response to a biological challenge may have clinical utility as a marker of vulnerability to panic attacks pending further research and development. Trial registration number 135908.
5 citations
TL;DR: In this paper, the authors argue that advancing our understanding of the causal system that gives rise to prolonged grief will require that we strengthen our assessment of each component of the grief syndrome, investigate intra-individual relationships among grief components as they evolve over time within individuals, incorporate biological and social components into network studies of grief, and generate formal theories that posit precisely how these biological, psychological, and social component interact with one another to give rise to the prolonged grief disorder.
Abstract: 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.
2 citations
01 Jan 2020
TL;DR: This chapter reviews a recently developed framework for conceptualizing mental disorders that centers on symptoms and the plausible causal relations among them and applies this framework to anxiety disorders, considering how a causal systems approach might be used to better understand, diagnose, and treat patients with anxiety.
Abstract: Symptoms are at the heart of psychiatric illness. Clinically, this is readily apparent; patients tend to seek help regarding symptom-level difficulties such as chronic worry, severe anxiety, or panic attacks. As mental health clinicians, we aim to understand and ameliorate these psychiatric symptoms. In this chapter, we review a recently developed framework for conceptualizing mental disorders that centers on symptoms and the plausible causal relations among them (Borsboom D, World Psychiatry 16:5–13, 2017; Borsboom D, Cramer AOJ, Annu Rev Clin Psychol 9:91–121, 2013). We then apply this framework to anxiety disorders, considering how a causal systems approach might be used to better understand, diagnose, and treat patients with anxiety. Throughout, we address how conceptualizing mental disorders in this way may be especially useful in understanding individual differences in the development and maintenance of psychiatric illness and in tailoring therapeutic interventions to better fit the needs of individual patients.
1 citations
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TL;DR: Recommendations are that insomnia is assessed routinely in the occurrence of mental health disorders; that sleep disturbance is treated in services as a problem in its own right, yet also recognised as a pathway to reduce other mental health difficulties; and that access to evidence-based treatment for sleep difficulties is expanded in mental health services.
212 citations
19 Aug 2021
TL;DR: This Primer provides an anatomy of network analysis techniques, describes the current state of the art and discusses open problems, as well as assessment techniques to evaluate network robustness and replicability.
Abstract: In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. In these approaches, network nodes represent variables in a data set, and edges represent pairwise conditional associations between variables in the data, while conditioning on the remaining variables. This Primer provides an anatomy of these techniques, describes the current state of the art and discusses open problems. We identify relevant data structures in which network analysis may be applied: cross-sectional data, repeated measures and intensive longitudinal data. We then discuss the estimation of network structures in each of these cases, as well as assessment techniques to evaluate network robustness and replicability. Successful applications of the technique in different research areas are highlighted. Finally, we discuss limitations and challenges for future research. Network analysis allows the investigation of complex patterns and relationships by examining nodes and the edges connecting them. Borsboom et al. discuss the adoption of network analysis in psychological research.
206 citations
TL;DR: The applied social science literature using factor and network models continues to grow rapidly as mentioned in this paper, and most work reads like an exercise in model fitting, and falls short of theory building and testing in social science.
Abstract: The applied social science literature using factor and network models continues to grow rapidly. Most work reads like an exercise in model fitting, and falls short of theory building and testing in...
134 citations
TL;DR: Despite rapidly increasing rates of infections and deaths, there are observed decreases in anxiety, loneliness, and COVID-19-related concerns, especially in the first few days, and other mental health variables remained stable, whereas depressive symptoms increased.
Abstract: For many students, the COVID-19 pandemic caused once-in-a-lifetime disruptions of daily life. In March 2020, during the beginning of the outbreak in the Netherlands, we used ecological momentary as...
79 citations
TL;DR: This dissertation deals with the problem of modeling psychopathology and introduces a number of models for cross-sectional and time series data that can be visualized as a network and puts forward an abductive framework for constructing formal theories for psychological and psychopathological phenomena.
Abstract: This dissertation deals with the problem of modeling psychopathology. Its first part focuses on statistical (data) models and introduces a number of models for cross-sectional and time series data that can be visualized as a network. This includes Mixed Graphical Models (MGMs), which allow one to include variables of different types in a statistical network model, Moderated Network Models (MNMs) which allow pairwise interactions to be moderated by other variables in the model, and time-varying Vector Autoregressive (VAR) models and MGMs that relax the standard assumption of stationarity. In addition, I discuss several methodological issues related to statistical network models such as the importance of considering predictability, model selection between AR and VAR models, and how the interpretation of the Ising model depends on its domain. The second part focuses on formal theories of psychopathology and how to develop them using data models. I first illustrate the fundamental difficulties in obtaining a formal theory with a purely statistical approach, by trying to recover an assumed bistable system for emotion dynamics with currently popular time series analyses. Next, I present a formal theory of panic disorder, based on an extensive review of the literature on the phenomenology of panic disorder and existing theories. Finally, I discuss three different ways to use data models to construct formal theories about psychopathological phenomena. Based on this discussion, I put forward an abductive framework for constructing formal theories for psychological and psychopathological phenomena.
71 citations