Examining the Relationship Between Network-Based Subgroups and Treatment Outcomes Among Individuals with Eating Disorders

Objective: Psychological treatment effects and response rates have largely plateaued over the past few decades. A potential answer to this problem is personalized treatment approaches, which match treatment to a client’s specific presenting concerns, which should increase its precision and efficacy. Examining predictors and moderators of treatment outcome (who is likely to benefit from treatment, and which treatment) is one way to guide such personalized decision making. The current study aimed to investigate the relationship between network-derived subgroups, treatment condition, and treatment response using data from two clinical trials on eating disorders (N = 80). This study is also a proof-of-concept for the clinical utility of network-based subgroups. Method: Subgroups were identified using Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) and ANOVAs were used to compare changes in symptom severity and clinical impairment among subgroups. Results: We found three subgroups (n = 71; mean age = 34.4 [SD = 11.8], 87.3% cisgender women, 85.9% white, non-Hispanic), which were differentiated by how shame and guilt were related in the network. The subgroup with a contemporaneous pathway from guilt to shame showed the least improvement in clinical impairment from pre- to posttreatment (F(2, 64) = 5.92, p = .004). Conclusions: Overall, our findings suggest that network-based subgroups may have utility as prognostic indicators, at least in the context of eating disorders, though replication of present findings is warranted. Limitations included potentially unstable subgroups and use of mostly cisgender women and white samples.