A majority of mental health care providers seek personal therapy (i.e., are prosumers), and many providers experience suicidal ideation. Although mental health care providers may have more awareness of mental health than undergraduates, stigma is prevalent across both mental health care professionals and within universities. Furthermore, suicidality is a particularly stigmatized aspect of mental health. Stigma may affect a client’s willingness to work with therapists who are prosumers. Although client preferences have implications for treatment engagement, retention, and outcomes (Swift & Callahan, 2009, 2010; Swift, Callahan, & Vollmer, 2011), we are unaware of any research that considers clients’ preferences regarding a prosumer therapist. The current study used a delay discounting paradigm to compare undergraduates’ and mental health care providers’ preferences of a prosumer therapist (i.e., with or without prior treatment history or prior suicidal ideation). We hypothesized that mental health care providers would be more accepting of a prosumer therapist, compared to undergraduates. Across both samples we expected a therapist with prior personal therapy to be more preferred than a therapist who has experienced prior suicidal ideation. Results were as expected, which may indicate a greater degree of mental health stigma among undergraduates compared to the mental health profession and greater stigma toward suicide in comparison to therapy experience in general.
Intensive longitudinal research designs are becoming more common in the field of neuropsychology. They are a powerful approach to studying development and change in naturally occurring phenomena. However, to fully capitalize on the wealth of data yielded by these designs, researchers have to understand the nature of multilevel data structures. The purpose of the present article is to describe some of the basic concepts and techniques involved in modeling multilevel data structures. In addition, this article serves as a step-by-step tutorial to demonstrate how neuropsychologists can implement basic multilevel modeling techniques with real data and the R package, lmerTest. R may be an ideal option for some empirical scientists, applied statisticians, and clinicians, because it is a free and open-source programming language for statistical computing and graphics that offers a flexible and powerful set of tools for analyzing data. All data and code described in the present article have been made publicly available.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.