- Full Text
- Scholarly Journal
Network models can help focus research on the role of culture and context in psychopathology, but don't discount latent variable models
Full text preview
In the target article Borsboom et al. assert that network models have the potential to highlight the important role of cultural and contextual variables in psychopathology, and that they allow for the modeling of such variables so that their roles can be properly elucidated. As the authors correctly note, these variables have been understudied, in part because of past emphasis on universalist, biological explanations in mainstream psychopathology research. A growing body of research suggests that cultural and contextual variables within individuals’ local social worlds play key roles in the development of psychopathology (see Hinton & Good 2016; Kirmayer & Ryder 2016). As psychologists who conduct research on the impact of culture and context on psychopathology, we agree with Borsboom et al.’s critique that the use of latent variable models in cross-cultural research has supported a fruitless search for universal, biological origins of psychopathology (see Littlewood 2002). However, we caution that this may not be an inevitable outcome of the latent variable approach per se. There are several instructive examples of studies in cultural-clinical psychology that use latent variable models to explore how cultural constructs of distress covary (e.g., Rasmussen et al. 2011) and test their construct validity (e.g., Chhim 2012). Furthermore, as both network analytic approaches and latent variable models are based on covariance, both may lead researchers to the discovery of similar patterns. Studies using network analysis to examine patterns of daily stressors, traumas, and symptoms (e.g., De Schryver et al. 2015; Jayawickreme et al. 2017) have reported similar results to studies examining similar variables but using a latent variable approach (e.g., Jordans et al. 2012; Rasmussen et al. 2010). This similarity in findings makes even more sense if one conceptualizes latent variable models as a pragmatic way to specify distributions that summarize the associations among a set of variables...