AUTHOR=Soodla Helo Liis , Soidla Kärol , Akkermann Kirsti TITLE=Reading tea leaves or tracking true constructs? An assessment of personality-based latent profiles in eating disorders JOURNAL=Frontiers in Psychiatry VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2024.1376565 DOI=10.3389/fpsyt.2024.1376565 ISSN=1664-0640 ABSTRACT=Background

Eating disorder (ED) subtyping studies have often extracted an undercontrolled, an overcontrolled and a resilient profile based on trait impulsivity and perfectionism. However, the extent to which methodological choices impact the coherence and distinctness of resulting subtypes remains unclear.

Objective

In this paper, we aimed to assess the robustness of these findings by extracting personality-based subtypes on a sample of ED patients (N = 221) under different analytic conditions.

Methods

We ran four latent profile analyses (LPA), varying the extent to which we constrained variances and covariances during model parametrization. We then performed a comparative analysis also including state ED symptom measures as indicators. Finally, we used cross-method validation via k-means clustering to further assess the robustness of our profiles.

Results

Our results demonstrated a four-profile model based on variances in impulsivity and perfectionism to fit the data well. Across model solutions, the profiles with the most and least state and trait disturbances were replicated most stably, while more nuanced variations in trait variables resulted in less consistent profiles. Inclusion of ED symptoms as indicator variables increased subtype differentiation and similarity across profiles. Validation cluster analyses aligned most with more restrictive LPA models.

Conclusion

These results suggest that ED subtypes track true constructs, since subtypes emerged method-independently. We found analytic methods to constrain the theoretical and practical conclusions that can be drawn. This underscores the importance of objective-driven analytic design and highlights its relevance in applying research findings in clinical practice.