Depressive personality traits and temperament and character personality traits in a clinical sample: Results from regression and network analyses

Personality and psychopathology are highly relevant and easily relatable constructs. The current study investigated the relationships between dependency and self-criticism, sociotropy and autonomy depressive personality traits, and Cloninger's temperament and character personality traits postulated as vulnerability factors for depression, in relation to depressive and general psychopathology symptoms in a clinical sample of 100 patients diagnosed with major depressive disorder. The results showed that self-directedness, a character trait of the temperament and character model, was positively associated with dependency, self-criticism, sociotropy, and autonomy. Applying more in-depth analyses with regression models revealed associations between self-directedness and depressive personality styles dependency and sociotropy, and general psychopathology symptoms was a significant clinical indicator in these relationships. Going beyond the regression models, network analysis showed that self-directedness is associated with self-criticism, sociotropy, autonomy, and general psychopathology symptoms. The relationship between self-directedness and sociotropy, self-criticism and autonomy suggests that these depressive personality traits may be attributable to aspects of self-determination, maturity, responsibility, discipline, and self-acceptance. General psychopathology research informed by literature incorporating personality traits has far-reaching implications for understanding individual differences as well as increasing efforts to contribute to the amelioration of disabling psychological disorders like major depressive disorders.

The Network Theory of Psychiatric Disorders: A Critical Assessment of the Inclusion of Environmental Factors

Borsboom and colleagues have recently proposed a "network theory" of psychiatric disorders that conceptualizes psychiatric disorders as relatively stable networks of causally interacting symptoms. They have also claimed that the network theory should include non-symptom variables such as environmental factors. How are environmental factors incorporated in the network theory, and what kind of explanations of psychiatric disorders can such an "extended" network theory provide? The aim of this article is to critically examine what explanatory strategies the network theory that includes both symptoms and environmental factors can accommodate. We first analyze how proponents of the network theory conceptualize the relations between symptoms and between symptoms and environmental factors. Their claims suggest that the network theory could provide insight into the causal mechanisms underlying psychiatric disorders. We assess these claims in light of network analysis, Woodward's interventionist theory, and mechanistic explanation, and show that they can only be satisfied with additional assumptions and requirements. Then, we examine their claim that network characteristics may explain the dynamics of psychiatric disorders by means of a topological explanatory strategy. We argue that the network theory could accommodate topological explanations of symptom networks, but we also point out that this poses some difficulties. Finally, we suggest that a multilayer network account of psychiatric disorders might allow for the integration of symptoms and non-symptom factors related to psychiatric disorders and could accommodate both causal/mechanistic and topological explanations.

Folk psychology and network theory: Fact or gamble? A reply to Kalis and Borsboom

Kalis and Borsboom (2020) defend their realism about folk psychology against my challenge to provide a grounding argument for the correctness of folk psychological explanation (Oude Maatman, 2020). In this reply, I show how their clarified realism in fact vindicates this challenge, as it heavily relies on the predictive success of folk psychology. I then proceed by describing how their realist interpretation of “intentional content” complicates the usability of network theory, and show that both their antireductionism and realism are grounded in an empirical gamble against alternatives. I end with a brief defense of my own version of network theory.

Folk psychology as a causal language

According to Oude Maatman (2020), our recent suggestion (Borsboom et al., 2019) that symptom networks are irreducible because they rely on folk psychological descriptions, threatens to undermine the main achievements of the network approach. In this article, we take up Oude Maatman’s challenge and develop an argument showing in what sense folk psychological concepts describe features of reality, and what it means to say that folk psychology is a causal language.