Temporal Bayesian Network modeling approach to evaluating the emotional cascade model of borderline personality disorder.

Abstract

Theoretical models of personality disorders can be complex and multifaceted, making it difficult to validate such models in a comprehensive, empirical fashion. One such model of borderline personality disorder (BPD) is the Emotional Cascade Model , which has garnered empirical support in piecemeal fashion, but has not been examined in a gestalt fashion.One way to test comprehensive models of personality pathology is with Temporal Bayesian Network (TBN) modeling, in which the relations between multiple subcomponents of a model can be specified and examined over a dynamic time frame, allowing for the modeling of positive feedback processes in addition to comprehensive model utility. In this study we applied TBN modeling to examine the Emotional Cascade Model in a sample of adolescents and young adults who actively self-injure, including those with BPD. TBN modeling was applied to ecological momentary assessment data provided via participant smartphone assessments for a period of two weeks. TBN analysis suggested that the emotional cascade model has considerable predictive utility, demonstrating substantial accuracy in predicting BPD diagnosis (with accuracy estimates around 90%) and momentary prediction of rumination, negative emotion, and dysregulated behaviors (with accuracy estimates consistently above 70% and reaching up to 100%, depending on the level of momentary prediction specificity). These findings provide support and validity to the notion that BPD may emerge from a dynamic interplay between emotional cascades and dysregulated behaviors. Implications of TBN modeling of BPD and personality disorders, in general, are discussed.

Emotional Cascade Model and Deep Learning

“…In this article is demonstrated, using deep learning techniques, how it is possible to computationally model with an exceedingly small error the interaction between the network elements that intervene in the emotional cascades typical of patients with BPD. Thus, it has been reinforced the predictive value obtained by Selby and collaborators [31] about their model of emotional cascades of psychological disorders and it has been reaffirmed, using the technique of artificial neural networks, the value of their model as a source of explanation for these disorders. Using a different computational technique, it has been improved the accuracy in the validation of the model-reaching 99%.…”

“…Selby et al [31] have proposed a Temporal Bayesian Network (TBN) model to examine the ECM in a sample of adolescents and young adults who actively self-injure and including those with BPD.…”

Examining the role of brooding, distress, and negative urgency in dysregulated behaviors: A cross‐sectional study in treatment‐seeking young people

“…Given the limited opportunity within the survey and the sample to adequately assess whether alcohol and substance use occurred in direct response to distress arising from brooding, this was deemed an unavoidable limitation. Similarly, other studies related to the ECM have measured alcohol use (and misuse) without specifying whether it occurred in relation to distress (Selby & Joiner, 2013 , 2020 ).…”

“…This literature is arguably inadequate to determine whether the model holds clinical utility. Furthermore, the two preliminary studies in clinical samples focus predominantly on NSSI, which limits the conclusions that can be drawn about the applicability of the ECM to other forms of behavioral dysregulation (Selby et al, 2013 , 2020 ). As such, research examining this model's clinical applicability in a clinical sample who engage in a variety of dysregulated behaviors is critical and importantly will inform whether rumination‐focused treatments are worthy of investigation for the treatment of dysregulated behaviors.…”

“…Selby et al ( 2013 ) similarly found via EMA that state rumination, particularly about the past, and distress, predicted daily NSSI. A recent EMA study found that the ECM accurately predicted BPD symptomology and behavioral dysregulation in a clinical sample (Selby et al, 2020 ). However, this sample was small and inclusive criteria related to current engagement in NSSI only, which may have excluded those who do engage in other forms of behavioral dysregulation.…”