Procedure
We performed a consecutive sampling of male and female patients attending the Outpatient Unit for Clinical Research and Treatment of Eating Disorders in Catanzaro (Italy). Patients were invited to participate in the present study if they met the following criteria: a) age 18-65 years; b) current diagnosis of BED according to the fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria; c) absence of current Axis I comorbid psychiatric disorders; d) capability to answer self-report questionnaires and to express valid consent.
Participants were deemed ineligible if: a) IQ < 70 [37]; b) drug dependence and/or abuse; c) severe mental illness that could interfere with clinical assessment (i.e. psychosis); d) history of chronic medical illness (i.e. chronic cardiovascular diseases) or neurological conditions (i.e. dementia) affecting cognitive functioning; e) other severe medical comorbidities (i.e. epilepsy); f) medical conditions that influenced eating/weight (i.e. diagnosis of diabetes mellitus); g) history of malignant disease.
Trained psychiatrists interviewed all participants using the Structured Clinical Interview for DSM-5 Disorders—Research Version [38] for diagnostic purposes and collected sociodemographic and clinical data. Researchers informed participants about the aims, procedures, anonymity and voluntary participation in this research. Participants gave their written informed consent to participate in accordance with the latest version of the Declaration of Helsinki [39] and the local Ethical Committee.
Measures
The Eating Disorders Inventory-2 (EDI-2) [40,41] is a self-report questionnaire made up of 91 items, which evaluates ED psychopathology and symptomatology. The EDI-2 provides 11 subscale scores and a global measure of ED severity obtained from the sum of all the items (ranging from 0 to 273). Higher scores indicate more severe ED symptoms. Cronbach’s alpha for the total score in this study was good (.840).
Binge Eating Scale (BES) [42] measures the severity of BED. It consists of 16 items that describe the behaviors, feelings and cognitions associated with binge eating. Total BES scores <17, 17-27 and >27 respectively indicate improbable, possible and probable BED. The internal consistency in this study was .880.
Metacognition Self-Assessment Scale (MSAS) [43] is an 18 items Likert-type (1 = never to 5 = almost always) self-report questionnaire that evaluates the metacognitive functioning. The raw score ranges from 18 to 90 and lower scores indicate impaired self-evaluation of metacognitive function. Specifically, the MSAS measures four abilities of metacognition: 1) monitoring; 2) differentiation/decentration; 3) integration; 4) mastery. In this study, Cronbach’s alpha ranges from .820 to .840.
Difficulties in Emotion Regulation Scale (DERS) [44]. The DERS consists of 36-items 5-point Likert-type and assesses emotion dysregulation across six subscales: (a) non-acceptance of emotions, (b) difficulties in pursuing goals when having strong emotions, (c) difficulties in controlling impulsive behaviors when experiencing negative emotions, (d) lack of emotional awareness, (e) limited access to emotion regulation strategies, and (f) lack of emotional clarity. Higher scores indicate more problems in emotional regulation. In the current study, the internal consistency ranges from .870 to .895.
Beck Depression Inventory II (BDI-II) [45] assesses depressive symptoms through 21 items on a Likert scale (0 – 3); scores between 0–9, 10–16, 17–29, and ≥ 30 indicate minimal, mild, moderate, and severe depression, respectively. Cronbach’s α in present research was .820.
State-Trait Anxiety Inventory (STAI) consists of 20 items that assess state (STAI-St) and 20 items that measure trait (STAI-Tr) anxiety [46]. The present study only included the STAI-Tr for statistical purposes. Cronbach's α was 0.795.
Network estimation and accuracy
NA was performed using R, version 3.6.2, using qgraph and bootnet packages in accordance with Epskamp and colleagues [47].
The network has been inferred by means of Gaussian Markov random field estimation, applying “Least Absolute Shrinkage and Selection Operator” (LASSO) regularization was applied to limit the number of spurious associations [48]. Moreover, the Extended Bayesian Information Criterion (EBIC) [49], a tuning parameter that sets the degree of regularization/penalty applied to sparse correlations, was set to 0.20 in the current study (values between 0 and 0.5 are typically chosen). Network estimation was performed using the estimateNetwork routine of the bootnet package [50].
The centrality of a node is used to infer its influence, or structural importance, in the network. Three main indices estimate the centrality: betweenness, how a node influences the average path between other pairs of nodes; closeness, how a node is indirectly connected to the other nodes; and strength, how a node is directly connected to the other nodes. The centrality Plot function in qgraph was used to calculate indices of centrality.
According to recommendations of Epskamp et al. [51], in order to assess the internal reliability of the network, we calculated the Correlation Stability (CS) coefficient, which is the maximum proportion of the population that can be dropped so that the correlation between the re-calculated indices of the obtained networks and those of the original network is at least 0.7. It is recommended that the minimum cut-off to consider a network stable is 0.25 for betweenness, closeness and strength [51]. The CS coefficient was computed using case-drop bootstrapping (nboots = 2000). Then we estimated the accuracy of edge-weights by drawing bootstrapped confidence intervals calculated using nonparametric bootstrapping (nboots = 2000). Both for case-drop and nonparametric bootstrapping, network stability analyses were performed using the bootnet function in the bootnet package.
Visual inspection of the network reveals that thicker edges indicate stronger associations between symptoms, with positive associations typically illustrated in blue and negative associations typically represented in red.