Statistical analyses
illness, eating disorder, depressive symptoms, ill, Depression, DSM-5
SECONDARY, PATHOLOGY, DISORDERS
At pretreatment assessment patients were asked to provide age, gender, nationality and occupational status.LOC and further mental disorders were assessed by the Mini-DIPS, a structured interview to assess mental disorders according to the DSM-5 [The following two online self-report questionnaires were assessed weekly during the waiting-time period, before each session of the active treatment, at posttreatment, before each follow-up session, and at post follow-up (total of 17 assessment points).The WBQ consists of six items that assess the regularity of eating and frequency as well as characteristics of LOC and compensatory behavior during the last seven days. In this study only one single item was included in the statistical analyses to assess the frequency of self-reported weekly LOC episodes by asking youth about the number of episodes in which they experienced loss of control over eating a perceived unusual large amount of food during the last seven days (item 5). It is important to note that self-report assessment of objectively large amounts of food has shown to be less reliable than interview-based assessment [The BDI-FS is a short version of the Beck Depression Inventory [The following two online self-report questionnaires were assessed four times (at pre- and posttreatment, 6-month follow-up, and post follow-up).The EDE-Q assesses eating disorder pathology during the last 28 days. It consists of 28 items, of which 22 items can be assigned to four subscales (To assess appearance-based rejection sensitivity, we applied a shortened and adapted version of the German version of the ARS. In the present version of the ARS-D, we chose to present 10 situations, covering topics which are relevant to our age group (the original ARS-D includes 15 situations). For each situation (e. g. “You are trying on clothes in a department store and notice that you have gained some weight in the last week”), patients rated on a 6-point likert scale their appearance-related The CGI assesses the global clinical impression of patients by clinicians before and after treatment, applying three measures: the global severity of illness measure (CGI-S), the global improvement measure (CGI-I) and an efficacy index. The CGI-S, ranging from 1 = not at all ill to 7 = among the most extremely ill patients, was rated at pre- and posttreatment assessment by therapists and additionally by patients. The CGI-I, ranging from 1 = very much improved to 7 = very much worse, was rated at posttreatment assessment by therapists. In the present study, side effects assessed within the efficacy index are reported. Findings regarding the validity of the CGI are inconsistent. While some studies supported the validity of the CGI in clinical trials (e. g. [Patients reported their satisfaction with BEAT at posttreatment assessment applying eight self-developed items based on the Working Alliance Inventory (WAI; [To report descriptive statistics, we used the mean and standard deviation (Abstainer rates, or, the proportion of patients who were abstinent from LOC after active treatment, were calculated based on the total sample of The primary outcome WBQ (weekly LOC) and the secondary outcome BDI-FS (depressive symptoms) were assessed regularly (altogether 17 times), thereby allowing us to analyze their weekly temporal course using a discontinuous multilevel model [To assess the secondary outcome of the change in the CGI-S scale between pre- and posttreatment, we used the Wilcoxon-test (only completers analysed).For the WBQ, the Number Needed to Treat (NNT) for a significant treatment outcome during the active treatment relative to the waiting-time was calculated according to Preti [The WBQ was transformed (ln[x + 1]) prior to analyses and predicted means from the multilevel models were back-transformed for reporting. All other outcomes were left untransformed. For continuous outcomes, the effect size For analyses related to the second study aim (acceptance of BEAT), we used descriptive statistics, i. e. absolute and relative frequencies or means and standard deviations respectively, to report dropout rates and patients’ subjective evaluation of the BEAT program at posttreatment (completers only).All analysis were performed using R for statistical computing, version 3.2 [