Modeling and estimating the feedback mechanisms among depression, rumination, and stressors in adolescents

Hosseinichimeh, Niyousha; Rick, J.; Jalali, Mohammad S.; Rahmandad, Hazhir

doi:10.1371/journal.pone.0204389

Cited by 32 publications

(20 citation statements)

References 48 publications

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“…It will thus be important to develop computational models in which the assumptions embodied in the model better align with how specific disorders are thought to operate (e.g. see Hosseinichimeh, Wittenborn, Rick, Jalali, & Rahmandad, 2018). This work can (indeed, must) be directly informed by each of the areas of work that have already contributed to network theory.…”

Section: Network Theorymentioning

confidence: 99%

The network approach to psychopathology: a review of the literature 2008–2018 and an agenda for future research

et al. 2019

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The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.

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Section: Network Theorymentioning

confidence: 99%

The network approach to psychopathology: a review of the literature 2008–2018 and an agenda for future research

et al. 2019

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“…The thought-emotion-action-physiological patterns that make up the maladaptive attractor can be dense and strongly interconnected, especially with more recurrent and chronic disorders such as depression, bipolar disorder, and substance use disorders. Maintaining processes (e.g., rumination, avoidance, and other maladaptive emotion regulation strategies) can interfere with the processing of new information, creating feedback loops that perpetuate the pathological patterns and symptoms and make them difficult to destabilize [17,48,49]. In contrast, the components of more healthy functioning (left side) are sparse, weakly connected, and not likely to sustain if activated.…”

Section: Application To Psychotherapy: Network Destabilization and Trmentioning

confidence: 99%

A complex systems approach to the study of change in psychotherapy

Hayes

Andrews

2020

BMC Med

103

102

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Background: A growing body of research highlights the limitations of traditional methods for studying the process of change in psychotherapy. The science of complex systems offers a useful paradigm for studying patterns of psychopathology and the development of more functional patterns in psychotherapy. Some basic principles of change are presented from subdisciplines of complexity science that are particularly relevant to psychotherapy: dynamical systems theory, synergetics, and network theory. Two early warning signs of system transition that have been identified across sciences (critical fluctuations and critical slowing) are also described. The network destabilization and transition (NDT) model of therapeutic change is presented as a conceptual framework to import these principles to psychotherapy research and to suggest future research directions. Discussion: A complex systems approach has a number of implications for psychotherapy research. We describe important design considerations, targets for research, and analytic tools that can be used to conduct this type of research. Conclusions: A complex systems approach to psychotherapy research is both viable and necessary to more fully capture the dynamics of human change processes. Research to date suggests that the process of change in psychotherapy can be nonlinear and that periods of increased variability and critical slowing might be early warning signals of transition in psychotherapy, as they are in other systems in nature. Psychotherapy research has been limited by small samples and infrequent assessment, but ambulatory and electronic methods now allow researchers to more fully realize the potential of concepts and methods from complexity science.

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“…The computational model proposed here can also serve as a resource for developing theories. We suspect that many emotional disorders arise from the same dynamical system motifs we used to construct this model, including positive feedback loops (e.g., between rumination and depressed mood; Hosseinichimeh, Wittenborn, Rick, Jalali, & Rahmandad, 2018), negative feedback loops (e.g., between social anxiety and avoidance of social situations), and an interaction between fast-changing variables and the slow-changing variables that guide their behavior. Indeed, the similarity of system motifs across emotional disorders is implicitly posited and exploited to greater effect in recent transdiagnostic approaches to treatment, which argue that there is a similar structure in the causal relationships among cognitions, emotions, and behavior across emotional disorders (Barlow, 2011;Barlow et al, 2017).…”

Section: Developing Theories For Other Mental Disordersmentioning

confidence: 99%

Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder

Robinaugh¹,

Jmb²,

Waldorp³

et al. 2019

Preprint

108

140

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The network theory of psychopathology posits that mental disorders are complex systems of mutually reinforcing symptoms. This overarching framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. We address this gap in the literature by developing a network theory of Panic Disorder and formalizing that theory as a computational model. We first review prior psychological theory and research on Panic Disorder in order to identify its core components as well as the plausible causal relations among those components. We then construct and evaluate a computational model of Panic Disorder as a non-linear dynamical system. We show that this model can explain a great deal, including individual differences in the propensity to experience panic attacks, key phenomenological characteristics of those attacks, the onset of Panic Disorder, and the efficacy of cognitive behavioral therapy. We also show that the model identifies significant gaps in our understanding of Panic Disorder and propose a theory-driven research agenda for Panic Disorder that follows from our evaluation of the model. We conclude by discussing the implications of the model for how we understand and investigate mental disorders as complex systems.

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Modeling and estimating the feedback mechanisms among depression, rumination, and stressors in adolescents

Cited by 32 publications

References 48 publications

The network approach to psychopathology: a review of the literature 2008–2018 and an agenda for future research

The network approach to psychopathology: a review of the literature 2008–2018 and an agenda for future research

A complex systems approach to the study of change in psychotherapy

Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder

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