The Nature of Night Eating Syndrome: Using Network Analysis to Understand Causal Symptomological Relationships

The purpose of this study was to examine and characterize the core symptoms in a psychopathology network for night eating syndrome (NES) among persons with and without overweight/obesity, and to compare the network density between samples with and without NES. The current conceptualization of NES, and interventions based on that conceptualization, are grounded in a latent variable, medical model nosology and theory of etiology. A recently developed advanced statistical technique, network analysis, allows for better understanding of the functional relationship among symptoms of behavioral health disorders. Network analysis has been applied to other eating disorders, but no studies to date have used network analysis to understand the functional relationship among proposed core symptoms of NES. Data from 148 individuals with NES and 69 individuals without NES were used to evaluate the unique variance among core symptoms and identify key symptom relationships. It was hypothesized that nocturnal ingestion of food and evening hyperphagia would present as the most central symptoms within the psychopathology network of NES compared to other symptoms. A Gaussian graphical model (GGM), utilizing a graphical least absolute shrinkage and selection operator (GLASSO) method, was used to estimate network. Symptoms with high centrality indices were assessed via bootstrapped difference tests. Results indicated that depressed mood and a strong urge to eat upon awakening at night were highly central to the psychopathology network for NES and were significantly more central than most other NES symptoms. These symptoms represent key elements of the core psychopathology of NES and should represent primary treatment targets for intervention.

Name thesis:degree_name

Ph.D. (Doctor of Philosophy)

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Clinical Psychology (UMKC)

Grantor

University of Missouri--Kansas City

Author dc:creator

• Beauchamp, Marshall Thomas

Advisor dc:contributor.advisor

• Lundgren, Jennifer D.

Handle dc:identifier.uri

https://hdl.handle.net/10355/70621

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/70621