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Performance monitoring entails rapid error detection to maintain task performance. Impaired performance monitoring is a candidate pathophysiological process in psychotic disorders, which may explain the broader deficit in executive function and its known associations with negative symptoms and poor functioning. The current study models cross-sectional pathways bridging neurophysiological measures of performance monitoring with executive function, symptoms, and functioning.
Data were from the 20-year assessment of the Suffolk County Mental Health Project. Individuals with psychotic disorders (N = 181) were originally recruited from inpatient psychiatric facilities. Data were also collected from a geographically and demographically matched group with no psychosis history (N = 242). Neural measures were the error-related negativity (ERN) and error positivity (Pe). Structural equation modeling tested mediation pathways.
Blunted ERN and Pe in the clinical cohort related to impaired executive function (r = 0.26–0.35), negative symptom severity (r = 0.17–0.25), and poor real-world functioning (r = 0.17–0.19). Associations with executive function were consistent across groups. Multiple potential pathways were identified in the clinical cohort: reduced ERN to inexpressivity was mediated by executive function (β = 0.10); reduced Pe to global functioning was mediated by executive function and avolition (β = 0.10).
This supports a transdiagnostic model of psychotic disorders by which poor performance monitoring contributes to impaired executive function, which contributes to negative symptoms and poor real-world functioning. If supported by future longitudinal research, these pathways could inform the development of targeted interventions to address cognitive and functional deficits that are central to psychotic disorders.
This chapter serves as the conclusion of a volume on the maintenance of relationships, especially romantic relationships. As its author, I sought to reflect on the other chapters in the book, doing some synthesizing, placing the volume’s contents in context, and adding my own views. The chapter unfolds by first discussing what maintenance is and then examining the past, the present, and the future of scholarship on maintenance. The discussion of the past mapped the growth of work on maintenance and reflects on a few comparisons between early and current contributions. The segment on the present identifies a citation count–based who’s who in the area, compares five theoretical perspectives on maintenance, and offers a broad-stroke synthesis of antecedents and consequences of maintenance. The chapter’s final section looks to the future, highlighting what authors in the volume recommend plus identifying four additional directions maintenance researchers might pursue. Overall, the chapter documents that from maintenance scholarship’s modest beginnings nearly 50 years ago, the volume of research, the sophistication of theoretical analyses, and the variety of research paradigms have all substantially advanced. Maintenance has gone from obscurity to being an important topic in good standing as we approach 2020.
Classic conceptual frameworks explaining the relationship of personality traits to depression include the precursor and predisposition models. The former hypothesizes that depression is predicted by traits alone whereas the latter hypothesizes that stress, together with personality, predicts depression. Dynamic vulnerability models (DVM) expand on these perspectives by incorporating fluctuations in personality over time. The stress generation model provides an alternative view, positing that depression generates stress, creating a self-perpetuating cycle. However, these conceptual models are rarely directly compared.
We tested these models, focusing on neuroticism and stressful life events that the participant may have contributed to, using path analysis in a sample of 550 never-depressed, adolescent females assessed five times over 3 years.
A dynamic precursor model with stress generation was best supported. For the precursor component, neuroticism predicted subsequent depression across four assessment intervals. For the dynamic trait component, stressful life events predicted subsequent neuroticism at three of four intervals. Finally, in line with stress generation, depression consistently predicted subsequent stressful life events, and life events then predicted depression.
Finding support for the DVM is noteworthy, as this is the first comprehensive test of this model. Moreover, results supported integrating stress generation with trait vulnerability. Continued use of integrated approaches and refining the statistical implementation of these theories is necessary to advance understanding of the development of depression.