S0033291718002702jra 1..6

Background. Mental disorders may emerge as the result of interactions between observable symptoms. Such interactions can be analyzed using network analysis. Several recent studies have used network analysis to examine eating disorders, indicating a core role of overvaluation of weight and shape. However, no studies to date have applied network models to binge-eating disorder (BED), the most prevalent eating disorder. Methods.We constructed a cross-sectional graphical LASSO network in a sample of 788 individuals with BED. Symptoms were assessed using the Eating Disorders Examination Interview. We identified core symptoms of BED using expected influence centrality. Results. Overvaluation of shape emerged as the symptom with the highest centrality. Dissatisfaction with weight and overvaluation of weight also emerged as highly central symptoms. On the other hand, behavioral symptoms such as binge eating, eating in secret, and dietary restraint/restriction were less central. The network was stable, allowing for reliable interpretations (centrality stability coefficient = 0.74). Conclusions. Overvaluation of shape and weight emerged as core symptoms of BED. This trend is consistent with past network analyses of eating disorders more broadly, as well as literature that suggests a primary role of shape and weight concerns in BED. Although DSM-5 diagnostic criteria for BED does not currently include a cognitive criterion related to body image or shape/weight overvaluation, our results provide support for including shape/weight overvaluation as a diagnostic specifier. Traditional approaches to psychopathology have conceptualized symptoms of mental disorders as emerging from a latent common cause (Borsboom et al., 2003). This latent model theory posits that underlying latent variables representing psychological disorders produce symptoms that are experienced by individuals with these disorders. More recent theoretical approaches have described how these symptoms might influence one another in a dynamic and casual network, rather than existing independently. The network model has emerged as a novel way to conceptualize psychological disorders, replacing the notion that psychological disorders themselves are the underlying cause of symptoms, or that symptoms are implicitly reflective of certain psychological disorders (Borsboom and Cramer, 2013). Instead, the network approach views symptoms of mental disorders as distinct entities that can influence, maintain, and/or interact with other symptoms (McNally, 2016). Network analysis allows for a depiction and quantification of the symptoms are most central to a disorder, as well as the strength by which symptoms react with and influence one another (Borsboom and Cramer, 2013; McNally, 2016; Fried et al., 2017). In a network model, symptoms are represented as individual nodes, connected by edges that depict the strength (e.g. strong correlation) and direction (e.g. positive correlation) between pairs of symptoms. Thicker edges indicate stronger associations between symptoms, with positive associations typically depicted in green and negative associations typically depicted in red. Central symptoms are nodes that demonstrate many strong connections to other nodes, a greater number of connections with other nodes, and nodes that serve as ‘hubs’ between other, disconnected, nodes (Freeman, 1978). Since its introduction to the study of psychopathology, clinical researchers have applied network analysis to examine psychopathology networks and to identify the core symptoms of many psychological disorders including depression (Fried et al., 2016; McNally et al., 2017), anxiety (Beard et al., 2016; Heeren and McNally, 2016), obsessive-compulsive disorder (Jones et al., 2018), and posttraumatic stress disorder (McNally et al., 2015; Armour et al., 2017). More recent research has also begun to apply network analysis to eating disorders. Levinson et al. (2017) examined a psychopathology network of bulimia nervosa (BN) and found that fear of weight gain was central to the BN network. Other studies have examined eatingdisorder psychopathology networks among mixed diagnostic groups comprised primarily of https://doi.org/10.1017/S0033291718002702 Downloaded from https://www.cambridge. org/core. Harvard University, on 12 Jun 2019 at 15:20:49, subject to the Cambridge Core terms of use, available at https://www.cambridge. org/core/terms. individuals with anorexia nervosa (AN), BN, and other specified feeding and eating disorders (OSFED; Forbush et al., 2016; Dubois et al., 2017; Forrest et al., 2018). Findings from these studies largely indicate that symptoms involving weight and shape concerns, including overvaluation of shape and weight and body checking, are central in networks of eating-disorder psychopathology. Thus, the emerging literature suggests that cognitive symptoms related to overvaluation and/or concerns with weight and shape appear to be core symptoms of eating disorders, at least among individuals with AN, BN, and OSFED. However, it is important to note that the majority of previous studies have relied on self-report questionnaires to assess eating disorder symptoms, which may not capture some of the symptoms as well as semi-structured investigator-based clinical interviews, particularly for some complex behavioral features (such as binge eating) and cognitive-evaluative features (such as overvaluation of shape/weight) as indicated by previous comparative research (Wilfley et al., 1997; Grilo et al., 2001a, 2001b). To date, no studies have applied network models to examine the core psychopathology of binge-eating disorder (BED). BED, which is characterized by recurrent episodes of binge eating (i.e. eating objectively large amounts of food while experiencing a subjective loss of control over eating), marked distress about binge eating, and the absence of inappropriate compensatory behaviors (e.g. self-induced vomiting), is the most prevalent eating disorder and is associated with psychosocial impairment (Udo & Grilo, 2018). Unlike other eating disorder diagnoses (e.g. AN, BN), the diagnostic criteria for BED does not include a cognitive criterion related to body image or shape/weight overvaluation (Grilo, 2013). Research has indicated that overvaluation of shape and weight is associated with significantly greater eating-disorder psychopathology and depression among individuals with BED (Grilo et al., 2008, 2010; Goldschmidt et al., 2010) and appears to be a better indicator of severity than the current DSM-5 severity specifier of binge-eating frequency (Grilo et al., 2015). Therefore, cognitive eating disorder symptoms involving overvaluation of shape and weight, or related constructs of body image, may also be critically important and core symptoms in BED. If cognitive symptoms relating to weight and shape are central to a BED network, this would refine approaches to assessment and diagnosis (Grilo, 2013) and inform efforts ability to design well-specified treatments to target key symptoms of this disorder. Therefore, the current study aimed to apply network analysis to examine the psychopathology of BED among a large sample of treatment-seeking patients with BED, as well as to identify the most central and influential symptoms of BED. Given previous research demonstrating the importance of overvaluation of shape and weight in BED (Grilo et al., 2008, 2010; Goldschmidt et al., 2010) and emerging findings on the centrality of weight/ shape overvaluation in other eating disorder networks (e.g. Forbush et al., 2016; Dubois et al., 2017; Forrest et al., 2018), we hypothesized that symptoms reflecting overvaluation of shape and weight, as well as dissatisfaction with shape and weight, would be central to the network.