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Correlates of interpersonal emotion regulation problems in Loss of Control eating (LOC) in youth: study protocol of the combined online and App based questionnaire, laboratory and randomized controlled online intervention i-BEAT trial

BMC Psychology volume 9, Article number: 193 (2021) Cite this article

Abstract

Background

Binge Eating Disorder (BED) represents a common eating disorder associated with marked health impairments. A subclinical variant, loss of control eating (LOC) is prevalent in youth. LOC is associated with similar mental distress as full-blown BED, increases the risk to develop a BED and promotes continuous weight gain. The etiology of LOC is not yet fully understood and specialized treatment for youth is scarce.

Methods

The i-BEAT study includes a cross-sectional and longitudinal online questionnaire study (N = 600), an App based daily-life approach and a laboratory virtual reality study in N = 60 youths (14–24 years) with and without LOC as well as a controlled randomized online treatment trial to investigate the feasibility, acceptance and efficacy of a CBT and an interpersonal emotion regulation module for youth (N = 120). The primary outcomes include self-reported as well as measured (heart rate variability, gaze behavior, reaction times in stop signal task) associations between emotion regulation problems (such as dealing with RS), psychological impairment and binge eating in a healthy control group and youth with LOC. Secondary outcomes encompass general eating disorder pathology, social anxiety, body mass index, hyperscanning behavior and therapists’ rating of patients’ condition pre and post treatment. Epigenetic correlates of RS are assessed in healthy controls and youth with LOC and explored before and after treatment.

Discussion

The expected findings will specify the role of interpersonal emotion regulation problems such as coping with the experience of social exclusion and rejection sensitivity (RS) in LOC and clarify, whether including a training to cope with RS adds to the efficacy of a cognitive behavioral treatment (CBT).

Trial registration: German Clinical Trial Register: DRKS00023706. Registered 27 November 2020, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00023706

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Background

Binge eating disorder (BED) and loss of control over eating (LOC)

Since the introduction of the fifth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5 [1]) in 2013, BED, characterized by recurrent binge eating episodes associated with marked distress represents a separate entity in the section of feeding and eating disorders. BED is relatively common, associated with weight gain and detrimental consequences for mental and physical health [2]. Current research [3, 4] shows that BED variants are common during puberty and early adulthood, a period characterized by rapid biological changes, e.g. growth spurts, brain and secondary sex characteristics development, shifts in the accumulation of body fat. Puberty and early adulthood are furthermore accompanied by psychological challenges such as striving for autonomy and identity based on the acceptance of appearance and interpersonal competences [5]. This period at the age of c. 14 to 24 years has been named youth by the UN (www.unesco.org) and is critical for the onset of eating disorders (ED) [6]. A substantial group of youth experiences LOC, defined as loss of control eating over smaller food amounts which do not fulfil the criteria of an objective large food amount as required according to DSM-5, but with equivalent psychopathological relevance [7, 8]. The consequences of LOC in youth include weight gain, stress symptoms, substance use and low quality of life as well as increased suicide risks in female and male youth [9]. There is a consensus to apply age adapted criteria to capture the presentation of youthful BED variants and LOC (the two of them thereafter summarized as LOC). Existing research applies various frequency and duration criteria, from at least one LOC episode during the prior month to once a week during the previous 3 months [4, 10]. Up to now, most of the research in LOC relies on female participants, even though males are more often affected with BED and LOC than in other EDs [11].

Epidemiology of LOC

Data on prevalence and the course of LOC in youth is scarce. According to a recent review [3] prevalence rates vary from 1 to 5% for BED and from 2.5 to 4.6% for subclinical forms of BED like LOC [12], with higher prevalence of LOC and BED in obese youth than in the general population. One of the rare longitudinal studies on the persistence of LOC in an US cohort found that LOC was significantly related to the stability of ED symptoms over the course of 10 years [13]. Another, smaller study found moderate stability of LOC over a 5-years period [14].

Interpersonal emotion regulation as a risk factor for LOC

Recent studies on psychological risk factors for the development of disordered eating confirm dual-pathway models, where sociocultural influences such as an unrealistic thin ideal are assumed to lead to body dissatisfaction, which promotes dieting and binge eating (e.g. [15]). While data on the dieting pathway remains controversial, the negative affect pathway has been confirmed in cross-sectional and longitudinal studies [16,17,18]. Recently, the model has been applied to LOC, where dysfunctional short-term emotion regulation strategies to alleviate negative affect play an important role [18]. An impaired awareness, understanding and acceptance of emotions or few appropriate emotion regulation strategies [19] are related to interpersonal problems [20, 21]. It can be assumed that interpersonal problems in youth interact with negative affect and lead to vicious circles promoting continued LOC [22]. Research in youth with LOC has only begun to assess the role of negative interpersonal and appearance-related evaluation, which are likely to be salient at that age [23], and therefore the sensitivity to general or appearance-related rejection (referred to as rejection sensitivity, RS) also gained interest [24]. RS describes an individual’s tendency to anxiously expect, readily perceive and overact to real or imagined rejection; often associated with past and current adverse experiences [25]. In youth, questionnaire-assessed appearance-related RS independent of gender, was related to dysfunctional eating behavior, lower self-esteem and more frequent experience of appearance-related teasing [26]. So far, there is only one laboratory study in youth with LOC which underlines the effect of negative peer evaluation in a small sample of overweight to obese females. In this study, the fictitious evaluation by peers based on photographs of the participants was associated with increased activation of anxiety related brain regions and failure to engage prefrontal cortex regions involved in emotion regulation attempts, all of which might be alleviated by overeating [27]. An increased RS in interaction with impaired emotion regulation and negative affect or mood has the potential to promote the development and maintenance of LOC in youth, but needs further clarification (Fig. 1). In addition, it can be assumed that the continued experience of rejection threatens the homeostasis of a person’s milieu, leads to a prolonged physiological stress response and might contribute to the intake of palatable food at an increased eating rate [28] and therefore to overeating and LOC. The capacity of the organism to adequately respond to stress conditions depends on the flexibility of the autonomic nervous system (ANS) which is connected to the amygdala and the medial prefrontal cortex and is indexed by heart rate variability (HRV) [29]. Reduced emotion regulation abilities are common in adults with EDs, but little is known about similar difficulties in youth with LOC [30, 31]. Consequently, investigating HRV responses to being exposed to social exclusion might help to understand emotion regulation skills in stressful situations and clarify the impact on LOC.

Fig. 1
figure 1

Working model of the role of interpersonal emotion regulation problems, rejection sensitivity, in youth with LOC

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Treatment research in LOC

Despite the relatively high prevalence of LOC in youth and the negative effects on mental and physical health, studies on psychological treatments in youth are scarce [32]. The existing evidence from diverse samples regarding LOC in youth point to the efficacy of cognitive behavioral therapy (CBT) [33], interpersonal therapy (IPT) [34] or dialectic behavioral therapy (DBT) [35] in reducing binge eating frequency. One online treatment study applied CBT to a sample of 105 male and female high school students at risk for overweight and/ or with overeating or LOC at a mean age of 15 years. The online treatment resulted in decreased LOC episodes and a moderate weight reduction up to the 9 months follow-up [36]. Consequently, it can be assumed, that an explicit focus on eating behavior as in CBT for eating disorders (CBT-E) might be appropriate for youth [33], but there is further promise in targeting interpersonal emotion regulation deficits, leading to negative affect and LOC [34], while the differential or additive efficacy of CBT-E and interventions on interpersonal emotion regulation in female and male youth needs further investigation.

Methods/design

Study aims and hypotheses

The general aim of the i-BEAT (online Binge Eating for Adolescent Treatment) study is to explore the role of interpersonal emotion regulation in terms of social exclusion and RS in youth with LOC compared to a healthy control group (HCG). The investigation includes a cross-sectional and longitudinal questionnaire and an App based daily-life self-report assessment about the association of negative affect, social rejection, RS, emotion regulation difficulties and LOC episodes (study 1), a laboratory based virtual reality (VR) cyber ball task to address the effects of social exclusion on psychological and physiological correlates of stress and a gamified Stop Signal Task (gSST) to assess behavioral motor inhibition capacities (study 2) and a randomized controlled online treatment trial to investigate the separate (superiority for specific outcomes) and additive effect of a self-help CBT-E and an interpersonal emotion regulation module for eating disorders (INTER-E) (study 3).

The following hypotheses are addressed in the three substudies:

Hypotheses concerning (1) primary and (2) secondary outcomes in study 1:

  1. 1.

    Questionnaire and App based daily-life assessed RS at baseline is positively associated with the number of weekly LOC episodes, ED pathology, past and current exclusion experiences, emotion regulation difficulties, impaired mental health and with Body Mass Index (BMI) in all groups. Questionnaire and App based daily-life assessed RS at baseline is positively associated with the number of weekly LOC episodes, ED pathology, past and current exclusion experiences, emotion regulation difficulties, impaired mental health and with Body Mass Index (BMI) in all groups.

    • Rejection sensitivity at baseline is positively associated with the number and severity of LOC episodes, with problems of emotion regulation, impaired mental health and with ED pathology at year 2.

    • Emotional eating and/or LOC episodes in daily-life result in a short-term reduction of negative affect but contribute to increased body dissatisfaction, especially in youth with LOC.

  2. 2.

    Lower inhibition capacities precede and predict weekly LOC episodes, emotional eating and urge to eat.

    • Lower inhibition capacities correlate with impaired mental health.

    • Effects become stronger with increasing values of RS.

Hypotheses concerning (1) primary and (2) secondary outcomes in study 2:

  1. 1.

    Exposure to the exclusion condition of the VR Cyberball task leads to greater social threat-related effects during and after the exclusion (lower HRV; increased negative/reduced positive affect, impairment of basic needs) and to a delayed recovery in youth with LOC compared to the HCG. Exposure to the exclusion condition of the VR Cyberball task leads to greater social threat-related effects during and after the exclusion (lower HRV; increased negative/reduced positive affect, impairment of basic needs) and to a delayed recovery in youth with LOC compared to the HCG.

    • Exposure to the exclusion condition leads to higher values of body dissatisfaction and of urge to engage in disinhibited eating after the task and during recovery in youth with LOC compared to HCG.

  2. 2.

    RS interpretation bias (underestimation of ball tosses while included, misinterpretation as being excluded during inclusion condition, negative evaluation of ambiguous social scenarios) is more pronounced in youth with LOC than in the HCG.

    • Exposure to the exclusion condition leads to stronger pupillary dilation response, stronger hyperscanning (eye gaze), more closed hand posture, stronger aversion of social gaze (measured as gaze dwell time) in youth with LOC compared to the HCG.

    • Youth with LOC show lower motor inhibition capacities indicated by longer SSRTs than the HCG during the gSST.

    • The motor inhibition capacity group difference is especially apparent in the food stimuli condition of the gSST in the LOC group compared to the HCG.

Hypotheses concerning (1) primary and (2) secondary outcomes in study 3:

  1. 1.

    Applying an INTER-E or a CBT-E module leads to a greater reduction of the number and severity of LOC episodes, problems of emotion regulation and negative mood than a 4-weeks’ waiting period.

    • The INTER-E module reduces weekly RS experiences, negative mood and problems of emotion regulation more strongly than the CBT-E module, whereas CBT-E decreases numbers and severity of weekly LOC episodes and urge to engage in disinhibited eating more importantly than the INTER-E module.

    • Applying the additional CBT-E or INTER-E module results in additional improvement of RS experiences, numbers or severity of weekly LOC episodes, problems of emotion regulation and urge to engage in disinhibited eating.

  2. 2.

    BMI remains stable during active treatment and follow-up.

    • Effects of the initial INTER-E or the CBT-E module remain stable during a 3-weeks pause.

    • Effects of the treatment remain stable during 6- and 12-months follow-up.

    • Therapist ratings of improvement are in line with the self-report of the patients.

    • CBT-E and INTER-E result in similar acceptance, usability, attrition and adherence rates.

We further aim to explore epigenetic underpinnings (DNA methylation, DNAm) of RS and emotion regulation capacity [37]. DNAm patterns are thought to reflect exposure to various psychosocial influences across the life-span and have been shown to relate to behavioral, emotional and cognitive styles especially in youth [38, 39]. We seek to explore the DNAm levels of genes involved in stress regulation and social interaction (FK-506-binding protein 5 (FKBP5) [40], the glucocorticoid receptor (NR3C1) [41], oxytocin receptor (OXTR) [42, 43] and the serotonin transporter (SLC6A4) in youth with LOC compared to a HCG (prior to treatment) and in LOC prior versus post treatment.

Study design

This study protocol has been written according to the SPIRIT statement (Standard Protocol Items for Randomized Trials) [44].

The i-BEAT project includes a multimethod three study arms approach. Study 1 encompasses a cross sectional and a longitudinal questionnaire-based survey. At baseline and one year later, questionnaire-based data is acquired online and the sample is screened to identify youth with LOC and HCG. The procedure is based on our pilot study BEAT (Binge Eating for Adolescent Treatment; DRKS00014580). App based daily-life data is assessed in a subgroup with LOC and in a HCG. We compare changes concerning the primary and secondary end points of study 1 between LOC versus HCG at T1.0, after one year at T1.6 and repeatedly during the 7-days of the App based daily life study (T1.5). Study 2 applies an adapted VR Cyberball task in the laboratory [45] and primary and secondary outcomes are compared between youth with LOC and age and gender matched HCG youth. Study 3 is a randomized wait-list between and within-subject online intervention study with a repeated measures design to evaluate the separate and additive effect of each of the two 6-weeks CBT-E or INTER-E modules (within subject effect) up to 6 and 12-months follow-up. After completion of the first module, participants wait 3 weeks until they receive the other module. We compare changes concerning the primary and secondary end points in participants from T3.00 to T3.1, T3.1 to T3.2 (active treatment in module 1), T3.2 to T3.3 (three weeks waiting between modules) and T3.3 to T3.4 (active treatment in module 2) as well as from T3.4 to the follow ups T3.4 and T3.5 (see Fig. 2 for study procedure).

Fig. 2
figure 2figure 2

Instruments. Note. (1) The complete DIPS will be conducted after the questionnaire-based screening study 1 and before further participation in either the laboratory study 2 or the online treatment study 3. The DIPS will only be conducted, if participants indicated their interest in either study 2 or study 3. (2) The Weekly Binges Post-Interview (WBQ-Post-Interview) is performed at the measurement point "Post Module 2", see above. (3) The DIPS short version will be conducted again at measurement point "Post Module 2". This short version only checks for disorders that have been identified as prominent in the first DIPS, and does not ask for eating disorder pathology. Note, almost all questionnaires and scales that will be used in i-BEAT study have been validated in German in the past. The respective citations are presented in the list of abbreviations. Only few questionnaires have been developed for the project at hand and are marked as “self-developed”. For a more detailed overview of the instruments, see additional file 1, "Instruments"

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Participants

Study 1 serves as a tool to increase awareness and recruit youth suffering from LOC and a HCG participating in all substudies. Youth with LOC participating in study 3 are randomized according to a permuted block design [46] to CBT-E or INTER-E first. Participants’ inclusion criteria for studies 1–3 are age between 14 and 24 years, sufficient German language competences and written informed consent. Criteria for LOC [47] are fulfilled and youth included if they experience at least 3 episodes of LOC during the last 3 months accompanied by at least 3 out of 5 behavioral indicators and/or some degree of distress, absence of AN or BN. Inclusion criteria for youth participating in the HCG are healthy body weight (BMI 18.5–24.9), absence of any past or present ED and absence of any present mental disorder according to the diagnostic interview. Youth from the LOC group are excluded if they suffer from any current mental disorder preventing safe participation in the i-BEAT study or if there is an intake of weight affecting drugs, participation in an ED related psychotherapy or weight loss treatment. Females in pregnancy or lactation are excluded. Additional in- and exclusion criteria for study 2 are intact or corrected vision capacity and nausea in VR. Figure 3 illustrates the study sample.

Fig. 3
figure 3

Study sample

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Sample size

For study 1 we will recruit N = 600 youth and expect a participation rate of c. 70–80% after one year. Power is sufficient (1−β = 0.8) to detect small to medium effect sizes f2 of c. 0.08, applying multiple regression models including covariates and testing specific predictors, for a given β of 0.05. For the App based study 1 multilevel models are applied to carry out between-subjects analysis of covariance. Moderators will be included to test for the interaction effects between groups (LOC vs HCG) within the Cyberball task. We expect moderate to large effect sizes (d = 0.8) with sufficient power to detect significant effects given 1−b = 0.8 and a = 0.05 for study 2 with N = 60 youths, even when accounting for c. 13% dropouts. For study 3, mixed between and within-subjects analysis of covariance or linear mixed models are carried out. Based on our BEAT pilot trial (DRKS00014580), where a high effect size for within subject measures revealed (d = 1.37) a medium to high effect size for these effects can be assumed (f = 0.25, taking r = 0.5 for the correlation among repeated measures), the required sample size would be N = 34 with sufficient power to detect significant effects given 1−β = 0.8 and β = 0.05 for study 3 with N = 120 youths, even when accounting for dropouts. Exploratory epigenetic goals involve predictors and within-subject effects and are expected to be sufficiently powered if effect sizes are medium to large (Fig. 3 depicts the study sample).

Recruitment

Recruitment efforts include media, posting on websites, contacting health care institutions and secondary, professional schools or Universities in the German speaking part of Switzerland [33]. In case of positive LOC scores or interest in study participation as part of the HCG, an online screening will be conducted and eligibility, diagnostic status, in and exclusion criteria will be verified (see Fig. 2). The first participant in study 1 is planned to be enrolled in March 2021.

Procedure and interventions

Cyberball task in virtual reality (VR)

The procedure of the i-BEAT study is illustrated in Fig. 2. Each participant is eligible to take part at one, two or at each of the three studies.

Interested youth are provided with a link to participate in study 1 and if eligible invited to participate in the App based study 1, study 2 and/or 3. Study 2 takes place between 2 and 4 PM after a regular meal at home. Upon arrival at the VR Lab at the Department of Psychology, University of Fribourg, First, electrodes to measure HRV (biosignalsplux, https://plux.info/12-biosignalsplux) are placed and a photograph of the participants is taken. HRV will be assessed continuously during the whole experiment.

With respect to eye tracking, we will use an HTC Vive Pro Eye (2160 × 1200 pixel resolution, 110° field of view) with a built-in eye-tracker (Tobii) to display the VR scene and concurrently collect gaze direction data at a sampling rate of 60 Hz. Gaze rays in 3D space obtained for both eyes will be geometrically transposed to represent horizontal and vertical deviations from regions of interest (as introduced in [48]). The procedure results in a form of data representation which is comparable to that obtained in traditional stationary eye-tracking where gaze deviations are described along a screen’s x- and y-axes. This form of data representation allows to apply a drift correction if samples directed towards regions of interest exhibit a drift over time (e.g. caused by a gradual lowering of the HMD on the participant’s head). After removing data obtained during blinks, data from both eyes will be averaged. Gaze will be labeled as either resting on a conspecific’s face (if deviation to any of the two faces present in the scene is lower than two degrees visual angle) or elsewhere.

At the beginning of the preparatory phase (see Fig. 4), participants self-report their psychological well-being and complete questionnaires (see Fig. 2). They are introduced to the adapted Cyberball task [27] (developed using the Unity 3D Game Engine) based on our pilot BEAT study and are informed that they will play with 2 peers and are shown pictures of these peers. Then, the motor-inhibition task, the gSST is applied. After a training trial with the oculus rift VR headset and oculus touch controller (preparation phase), the Cyberball task starts. All participants are exposed to the exclusion condition first followed by the inclusion condition. The order of the conditions is kept secret. The psychological effects of experiencing exclusion are repeatedly assessed during the VR Cyberball task. Participants rate how excluded or ignored they felt (manipulation check) as well as the percentage of received ball tosses. During recovery phase (see Fig. 4), they receive instructions in the App based daily-life study and during the preparatory phase, buccal cell samples to measure DNAm of candidate genes are provided (see Fig. 2). DNA methylation will be assessed using targeted bisulfite sequencing. In brief, bisulfite treated DNA will undergo two rounds of PCR (1st round: amplification for specific target regions; 2nd round: introduce identifiers for individuals), and will be sequenced on a MiSeq platform. To capture possible medium-term effects as a result of ostracism, a short questionnaire will be filled-out by all participants on their way home via the daily-life App and participants are debriefed about the purpose of study 2.

Fig. 4
figure 4

Experimental procedure during Cyberball-task in virtual reality, VR

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Online self-help treatment for LOC

Based on our previous work in BED in adults [49, 50] and based on our preliminary results of the blended treatment in our pilot BEAT study (active treatment consisting of 3 face to face sessions and 6 weekly e-mail guided self-help sessions, followed by 1, 3, 6, and 12-month follow-up sessions), we developed an online self-help treatment consisting of two distinct modules CBT-E and INTER-E (see Table 1). To increase compliance and decrease dropouts, therapists provide guidance via an Email generated system within the online platform [51]. Therapists (psychologists attending a post graduate training in CBT psychotherapy) will be trained and regularly supervised by SM.

Table 1 Content of CBT-E and INTER-E treatment modules
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Outcome measures

Data assessors are trained and supervised in diagnostics, application of experimental procedures of study 1–2. The time schedule of the data assessment during i-BEAT studies is presented in Fig. 2.

Diagnostic assessment

Body weight and height are self-reported in study 1 and measured upon arrival for study 2 in light clothing to compute BMI (kg/m2). The diagnostic interview according to DSM-5, "Diagnostisches Interview bei Psychischen Störungen" (DIPS; [52]) is applied to identify mental disorders and LOC criteria, which are further confirmed via the Eating Disorder Examination Questionnaire (EDE-Q, German version; [53]). Frequency and severity of LOC or binge eating episodes are measured using the self-constructed weekly binge eating questionnaire (WBQ; [50, 54]). Measures and assessment time points during the i-BEAT study are presented in Fig. 2. In study 3, besides pre to post and follow-up measurements, the treatment process is assessed by weekly online questionnaires provided via the platform encompassing the primary outcomes frequency and severity of weekly LOC episodes, weekly interpersonal emotion regulation problems/ RS as well as attrition, adherence, dropouts, acceptance and feasibility.

Data analysis

Data will be analyzed with the Statistical Package of Social Sciences (SPSS) and R. We will apply multiple regression models including covariates and testing specific predictors (study 1), multilevel models including moderators (App based study 1), between subjects analysis of covariance including moderators (study 2) and mixed between and within subjects analysis of covariance or linear mixed models (study 3). Exploratory epigenetic goals involve predictors and within-subject effects. Expected dropouts are assumed to amount up to 10–18%. Random occurrence should lead to equal distribution of dropouts in the different groups (LOC vs. HCG; CBT-E first vs. INTER-E first). However, in the case of an unequal distribution of the number of participants to the different groups, this issue will be addressed with multi-level models. Multi-level models are assumed to be robust against violations of equal group sizes [55]. Additionally, we will test whether a missing at random pattern is a reasonable assumption with respect to dropout.

Discussion

The overarching goal of this project is to better understand the role of interpersonal emotion regulation problems, especially when feeling rejected (RS), in youth suffering from LOC. LOC importantly promotes EDs, general psychopathology and interferes with the development of a positive identity and the capability to engage in meaningful relationships. The interventional part of the project will show how youth accepts, reacts to and benefits from a CBT-E and an INTER-E module and whether there are specific and additive effects. The i-BEAT study represents a multi-method approach including psychological, behavioral, psychophysiological and epigenetic data, which is unique in the field and generates interdisciplinary evidence.

List of abbreviations and questionnaire sources

  • Adapted German version of the Sociocultural Attitudes Towards Appearance Questionnaire, [56].

  • Adapted German version of the Thought Shape Fusion questionnaire (TSF-B; [57]).

  • Adapted Rejection Sensitivity Questionnaire (RSquest, adapted from the RSQ, [58]; CRSQ, German version, FZE-K, [59]).

  • Adapted version of the Brief Mood Scale, Three-dimensional Affect Scale, [61].

  • Adapted Working Alliance Inventory (WAI-SR; [62]).

  • Ambiguous Scenario-Sentence Completion Task; Cognitive Bias Modification-Interpretation (rejectbias; according to [63]).

  • App-based adapted Three Dimensions Affect scale (AppNegaff; [61, 64]).

  • App-based adapted Visual Analog Scale Body Image Satisfaction (AppBD; [64]).

  • Rejection Sensitivity Qu [60]).

  • Autonomic Nervous System (ANS).

  • Barratt Impulsiveness Scale (BIS-15; [65]).

  • Beck Depression Inventory Fast Screen German (BDI-FS; [66]).

  • Binge Eating Adolescents and young adults Training (i-BEAT).

  • Binge Eating Disorder (BED).

  • Body Mass Index (BMI).

  • Body Shape Questionnaire (BSQ; [67]).

  • Brief Mood Scale (BMS; [64]).

  • CBT for eating disorders (CBT-E).

  • .

  • Clinical Global Impression scale (CGI; [68]).

  • Cognitive Behavioral Therapy (CBT).

  • Diagnostic and Statistical Manual of Mental Disorders (DSM-5).

  • Dialectic Behavioral Therapy (DBT).

  • Diagnostisches Interview bei Psychischen Störungen (DIPS).

  • Difficulties in Emotion Regulation Scale (DERS; [69]).

  • Difficulties in Emotion Regulation Scale—Short Form (DERS-SF; [70]).

  • DNA methylation (DNAm).

  • Dutch Eating Behavior Questionnaire (DEBQ; German version; [71]).

  • Eating Disorder Examination- Questionnaire Kurzversion (EDE-Q8; [53]).

  • Eating Disorder(s) ED(s).

  • EmoReg weekly - Self-developed and adapted from the DERS ([69]), the TAS-20 [72], the H-FERS [73] and the TOMS [74].

  • Final evaluation of the online-therapy; self-developed items (Therapeut*innen Fragebogen).

  • Food Craving Questionnaire (FCQ; [75]).

  • Gamified Stop Signal Task (gSST).

  • Healthy Control Group (HCG).

  • Heart Rate Variability (HRV).

  • Heidelberger Fragebogen zur Erfassung von Emotionsregulationsstrategien (H-FERS; [73]).

  • Igroup Presence Questionnaire (IPQ; [76]).

  • Illusion of Virtual Body Ownership Scale (IVBO; [77]).

  • Inventar zur Erfassung negativer Effekte von Psychotherpie (INEP; [78]).

  • Interpersonal Emotion Regulation module for eating disorders (INTER-E).

  • Inter-Personal Therapy (IPT).

  • Loss Of Control eating (LOC).

  • Modified version of the Weekly Binges Questionnaire (wLOC, AppLOC, AppUrge, WBQ; [79]).

  • Need Threat Scale (NTS; [80]).

  • Patient Health Questionnaire for Depression and Anxiety (PHQ-4; [81]).

  • Perception of Teasing Scale (POTS; [82]).

  • Questionnaire on frequency and intensity of rejection experiences and bullying (reject; adapted from [83, 84]).

  • RS interpretation bias: Visual Analogue Scale of misinterpretation of being excluded in the Cyberball game (exclmisinterpret; [85]).

    Rejection sensitivity, RS.

  • RS interpretation bias: Visual Analogue Scale of misinterpretation of being included in the Cyberball game (inclmisinterpret; [85]).

  • Short version of the Social Phobia Scale (SPS; [86]).

  • Simulator Sickness Questionniare (SSQ; [87]).

  • Social Interaction Anxiety Scale (SIAS; [86]).

  • Sociodemographic items (self-developed items).

  • Standard Protocol Items for Randomized Trials (SPIRIT).

  • State-Trait Anxiety Inventory, short-version (STAI; [88]).

  • Stop Signal Task, (vrSSRT, SSRT; [89]).

  • Tanner questionnaire (Tanner; [90]).

  • Tolerance of Mood States Scale (TOMS; [74]).

  • Translated and adapted Social Presence Survey (SPSurvey; [91]).

  • UPPS Impulsive Behaviour Scale (UPPS; [92]).

  • Virtual Reality (VR).

  • Visual Analog Scale Body Image Satisfaction (VASBD; [64]).

  • Visual Analog Scale - distress photo (distressphoto; self-developed items).

  • Visual Analog Scale - rejection (rejectphoto; self-developed items).

  • Visual Analog Scale - urge to eat (VASurge; self-developed items based on [93]).

  • Weekly Binges Questionnaire (WBQ; [79]).

Availability of data and materials

Youth will give informed consent to the open data access according to the Swiss National Foundation Foundation (http://www.snf/SiteCollectionDocuments/FAIR data repositories examples.pdf). The datasets generated and/or analyzed during the current study will be available in ZENODO (https://zenodo.org).

References

  1. American Psychiatric Association: Diagnostic and Statistical Manual. 5th edition. Arlington: American Psychiatric Association; 2013.

  2. Kessler RC, Berglund PA, Chiu WT, Deitz AC, Hudson JI, Shahly V, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Benjet C, et al. The prevalence and correlates of binge eating disorder in the World Health Organization World Mental Health Surveys. Biol Psychiatry. 2013;73(9):904–914.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Marzilli E, Cerniglia L, Cimino S. A narrative review of binge eating disorder in adolescence: prevalence, impact, and psychological treatment strategies. Adolesc Health Med Ther. 2018;9:17–30.

    PubMed  PubMed Central  Google Scholar 

  4. Swanson SA, Crow SJ, Le Grange D, Swendsen J, Merikangas KR. Prevalence and correlates of eating disorders in adolescents. Results from the national comorbidity survey replication adolescent supplement. Arch Gen Psychiatry 2011;68(7):714–723.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bray S, Krongold M, Cooper C, Lebel C: Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence. eNeuro 2015;2(4):1–13.

    Article  Google Scholar 

  6. Culbert KM, Racine SE, Klump KL. Research Review: What we have learned about the causes of eating disorders - a synthesis of sociocultural, psychological, and biological research. J Child Psychol Psychiatry. 2015;56(11):1141–1164.

    Article  PubMed  Google Scholar 

  7. Goldschmidt AB, Tanofsky-Kraff M, Goossens L, Eddy KT, Ringham R, Yanovski SZ, Braet C, Marcus MD, Wilfley DE, Yanovski JA. Subtyping children and adolescents with loss of control eating by negative affect and dietary restraint. Behav Res Ther. 2008;46(7):777–787.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Shomaker LB, Tanofsky-Kraff M, Zocca JM, Courville A, Kozlosky M, Columbo KM, Wolkoff LE, Brady SM, Crocker MK, Ali AH et al: Eating in the absence of hunger in adolescents: intake after a large-array meal compared with that after a standardized meal. Am J Clin Nutr 2010;92(4):697-703.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Forrest LN, Zuromski KL, Dodd DR, Smith AR. Suicidality in adolescents and adults with binge-eating disorder: Results from the national comorbidity survey replication and adolescent supplement. Int J Eat Disord. 2017;50(1):40–49.

    Article  PubMed  Google Scholar 

  10. Schluter N, Schmidt R, Kittel R, Tetzlaff A, Hilbert A. Loss of control eating in adolescents from the community. Int J Eat Disord. 2016;49(4):413–420.

    Article  PubMed  Google Scholar 

  11. Smink FR, van Hoeken D, Oldehinkel AJ, Hoek HW. Prevalence and severity of DSM-5 eating disorders in a community cohort of adolescents. Int J Eat Disord. 2014;47(6):610–619.

    Article  PubMed  Google Scholar 

  12. Lee-Winn AE, Reinblatt SP, Mojtabai R, Mendelson T. Gender and racial/ethnic differences in binge eating symptoms in a nationally representative sample of adolescents in the United States. Eat Behav. 2016;22:27–33.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pearson CM, Miller J, Ackard DM, Loth KA, Wall MM, Haynos AF, Neumark-Sztainer D. Stability and change in patterns of eating disorder symptoms from adolescence to young adulthood. Int J Eat Disord. 2017;50(7):748–757.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Hilbert A, Brauhardt A. Childhood loss of control eating over five-year follow-up. Int J Eat Disord. 2014;47(7):758–761.

    Article  PubMed  Google Scholar 

  15. Stice E, Gau JM, Rohde P, Shaw H. Risk factors that predict future onset of each DSM-5 eating disorder: predictive specificity in high-risk adolescent females. J Abnorm Psychol. 2017;126(1):38–51.

    Article  PubMed  Google Scholar 

  16. Allen KL, Byrne SM, McLean NJ. The dual-pathway and cognitive-behavioural models of binge eating: prospective evaluation and comparison. Eur Child Adolesc Psychiatry. 2012;21(1):51–62.

    Article  PubMed  Google Scholar 

  17. Dakanalis A, Timko CA, Carra G, Clerici M, Zanetti MA, Riva G, Caccialanza R. Testing the original and the extended dual-pathway model of lack of control over eating in adolescent girls: a two-year longitudinal study. Appetite. 2014;82:180–193.

    Article  PubMed  Google Scholar 

  18. Goldschmidt AB, Lavender JM, Hipwell AE, Stepp SD, Keenan K. Emotion regulation and loss of control eating in community-based adolescents. J Abnorm Child Psychol. 2017;45(1):183–191.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Gratz KL, Roemer L. Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and initial validation of the difficulties in emotion regulation scale. J Psychopathol Behav Assess. 2004;26(1):41–54.

    Article  Google Scholar 

  20. Aldao A, Nolen-Hoeksema S. When are adaptive strategies most predictive of psychopathology? J Abnorm Psychol. 2012;121(1):276–281.

    Article  PubMed  Google Scholar 

  21. Humbel N, Messerli-Burgy N, Schuck K, Wyssen A, Garcia-Burgos D, Biedert E, Lennertz J, Meyer AH, Whinyates K, Isenschmid B et al: Self-reported emotion regulation difficulties are associated with mood but not with the biological stress response to thin ideal exposure. PLoS One 2018;13(6):1-18.

  22. Elliott CA, Tanofsky-Kraff M, Shomaker LB, Columbo KM, Wolkoff LE, Ranzenhofer LM, Yanovski JA. An examination of the interpersonal model of loss of control eating in children and adolescents. Behav Res Ther. 2010;48(5):424–428.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ambwani S, Roche MJ, Minnick AM, Pincus AL. Negative affect, interpersonal perception, and binge eating behavior: an experience sampling study. Int J Eat Disord. 2015;48(6):715–726.

    Article  PubMed  Google Scholar 

  24. De Paoli T, Fuller-Tyszkiewicz M, Halliwell E, Puccio F, Krug I. Social rank and rejection sensitivity as mediators of the relationship between insecure attachment and disordered eating. Eur Eat Disord Rev. 2017;25(6):469–478.

    Article  PubMed  Google Scholar 

  25. Downey G, Feldman SI. Implications of rejection sensitivity for intimate relationships. J Pers Soc Psychol. 1996;70(6):1327–1343.

    Article  PubMed  Google Scholar 

  26. Webb HJ, Zimmer-Gembeck MJ, Waters AM, Farrell LJ, Nesdale D, Downey G. “Pretty pressure” from peers, parents, and the media: a longitudinal study of appearance-based rejection sensitivity. J Res Adolesc. 2017;27(4):718–735.

    Article  PubMed  Google Scholar 

  27. Jarcho JM, Tanofsky-Kraff M, Nelson EE, Engel SG, Vannucci A, Field SE, Romer AL, Hannallah L, Brady SM, Demidowich AP et al: Neural activation during anticipated peer evaluation and laboratory meal intake in overweight girls with and without loss of control eating. Neuroimage 2015;108:343-353.

    Article  PubMed  Google Scholar 

  28. Naish KR, Laliberte M, MacKillop J, Balodis IM. Systematic review of the effects of acute stress in binge eating disorder. Eur J Neurosci. 2019;50(3):2415–2429.

    Article  PubMed  Google Scholar 

  29. Thayer JF, Ahs F, Fredrikson M, Sollers JJ 3rd, Wager TD. A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neurosci Biobehav Rev. 2012;36(2):747–756.

    Article  PubMed  Google Scholar 

  30. Goldschmidt AB, Crosby RD, Cao L, Engel SG, Durkin N, Beach HM, Berg KC, Wonderlich SA, Crow SJ, Peterson CB. Ecological momentary assessment of eating episodes in obese adults. Psychosom Med. 2014;76(9):747–752.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Ranzenhofer LM, Engel SG, Crosby RD, Haigney M, Anderson M, McCaffery JM, Tanofsky-Kraff M. Real-time assessment of heart rate variability and loss of control eating in adolescent girls: a pilot study. Int J Eat Disord. 2016;49(2):197–201.

    Article  PubMed  Google Scholar 

  32. Crow S. Treatment of binge eating disorder. Curr Treat Options Psychiatry. 2014;1(4):307–314.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Debar LL, Wilson GT, Yarborough BJ, Burns B, Oyler B, Hildebrandt T, Clarke GN, Dickerson J, Striegel RH. Cognitive behavioral treatment for recurrent binge eating in adolescent girls: a pilot trial. Cogn Behav Pract. 2013;20(2):147–161.

    Article  PubMed  Google Scholar 

  34. Tanofsky-Kraff M, Wilfley DE, Young JF, Mufson L, Yanovski SZ, Glasofer DR, Salaita CG, Schvey NA. A pilot study of interpersonal psychotherapy for preventing excess weight gain in adolescent girls at-risk for obesity. Int J Eat Disord. 2010;43(8):701–706.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Safer DL, Lock J, Couturier JL. Dialectical behavior therapy modified for adolescent binge eating disorder: a case report. Cogn Behav Pract. 2007;14(2):157–167.

    Article  Google Scholar 

  36. Jones M, Luce KH, Osborne MI, Taylor K, Cunning D, Doyle AC, Wilfley DE, Taylor CB. Randomized, controlled trial of an internet-facilitated intervention for reducing binge eating and overweight in adolescents. Pediatrics. 2008;121(3):453–462.

    Article  PubMed  Google Scholar 

  37. Unternaehrer E, Luers P, Mill J, Dempster E, Meyer AH, Staehli S, Lieb R, Hellhammer DH, Meinlschmidt G: Dynamic changes in DNA methylation of stress-associated genes (OXTR, BDNF) after acute psychosocial stress. Transl Psychiatry 2012;2:1-7.

  38. Barker ED, Walton E, Cecil CAM. Annual Research Review: DNA methylation as a mediator in the association between risk exposure and child and adolescent psychopathology. J Child Psychol Psychiatry. 2018;59(4):303–322.

    Article  PubMed  Google Scholar 

  39. Kumsta R, Marzi SJ, Viana J, Dempster EL, Crawford B, Rutter M, Mill J, Sonuga-Barke EJ. Severe psychosocial deprivation in early childhood is associated with increased DNA methylation across a region spanning the transcription start site of CYP2E1. Transl Psychiatry 2016;6(6):1-7.

  40. Lester KJ, Roberts S, Keers R, Coleman JR, Breen G, Wong CC, Xu X, Arendt K, Blatter-Meunier J, Bogels S, et al. Non-replication of the association between 5HTTLPR and response to psychological therapy for child anxiety disorders. Br J Psychiatry. 2016;208(2):182–188.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Oberlander TF, Grunau R, Mayes L, Riggs W, Rurak D, Papsdorf M, Misri S, Weinberg J. Hypothalamic-pituitary-adrenal (HPA) axis function in 3-month old infants with prenatal selective serotonin reuptake inhibitor (SSRI) antidepressant exposure. Early Hum Dev. 2008;84(10):689–697.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Auer BJ, Byrd-Craven J, Grant DM, Granger DA. Common oxytocin receptor gene variant interacts with rejection sensitivity to influence cortisol reactivity during negative evaluation. Horm Behav. 2015;75:64–69.

    Article  PubMed  Google Scholar 

  43. Kim YR, Kim JH, Kim CH, Shin JG, Treasure J. Association between the oxytocin receptor gene polymorphism (rs53576) and bulimia nervosa. Eur Eat Disord Rev. 2015;23(3):171–178.

    Article  PubMed  Google Scholar 

  44. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gotzsche PC, Krleza-Jeric K, Hrobjartsson A, Mann H, Dickersin K, Berlin JA, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200–207.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Hartgerink CH, van Beest I, Wicherts JM, Williams KD: The ordinal effects of ostracism: a meta-analysis of 120 Cyberball studies. PLoS One 2015; 10(5):1-24.

  46. Lachin JM, Matts JP, Wei LJ. Randomization in clinical trials: conclusions and recommendations. Control Clin Trials. 1988;9(4):365–374.

    Article  PubMed  Google Scholar 

  47. Munsch S, Dremmel D, Kurz S, De Albuquerque J, Meyer AH, Hilbert A. Influence of parental expressed emotions on children’s emotional eating via children’s negative urgency. Eur Eat Disord Rev. 2017;25(1):36–43.

    Article  PubMed  Google Scholar 

  48. Rubo M, Gamer M. Stronger reactivity to social gaze in virtual reality compared to a classical laboratory environment. Br J Psychol. 2021;112(1):301–314.

    Article  PubMed  Google Scholar 

  49. Munsch S, Meyer AH, Biedert E. Efficacy and predictors of long-term treatment success for cognitive-behavioral treatment and behavioral weight-loss-treatment in overweight individuals with binge eating disorder. Behav Res Ther. 2012;50(12):775–785.

    Article  PubMed  Google Scholar 

  50. Munsch S, Wyssen A, Vanhulst P, Lalanne D, Steinemann ST, Tuch A. Binge-eating disorder treatment goes online - feasibility, usability, and treatment outcome of an Internet-based treatment for binge-eating disorder: study protocol for a three-arm randomized controlled trial including an immediate treatment, a waitlist, and a placebo control group. Trials. 2019;20(128):1-11.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Aardoom JJ, Dingemans AE, Spinhoven P, Van Furth EF. Treating eating disorders over the internet: a systematic review and future research directions. Int J Eat Disord. 2013;46(6):539–552.

    Article  PubMed  Google Scholar 

  52. Margraf J, Cwik JC, Pflug V, Schneider S. Structured clinical interviews for mental disorders across the life span: psychometric quality and further developments of the DIPS open access interviews. Zeitschrift Fur Klinische Psychologie Und Psychotherapie. 2017;46(3):176–186.

    Article  Google Scholar 

  53. Hilbert A, Tuschen-Caffier B. Eating disorder examination: DGVT-Verlag; 2016.

  54. Munsch S, Milenkovic N, Meyer A, Schlup B, Margraf J, Wilhelm P: Electronic diaries to evaluate efficacy of a Cognitive Behavioral Treatment for BED. International Journal of Obesity 2008;32.

  55. Lane P. Handling drop-out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches. Pharm Stat. 2008;7(2):93–106.

    Article  PubMed  Google Scholar 

  56. Knauss C, Paxton SJ, Alsaker FD. Validation of the german version of the Sociocultural Attitudes Towards Appearance Questionnaire (SATAQ-G). Body Image. 2009;6(2):113–120.

    Article  PubMed  Google Scholar 

  57. Wyssen A, Debbeler LJ, Meyer AH, Coelho JS, Humbel N, Schuck K, Lennertz J, Messerli-Bürgy N, Biedert E, Trier SN. Cognitive distortions associated with imagination of the thin ideal: validation of the thought-shape fusion body questionnaire (TSF-B). Front Psychol. 2017;8:1-10.

  58. Staebler K, Helbing E, Rosenbach C, Renneberg B. Rejection sensitivity and borderline personality disorder. Clin Psychol Psychother. 2011;18(4):275–283.

    Article  PubMed  Google Scholar 

  59. Rosenbach C: Rejection Sensitivity-etiological aspects and psychopathological impact. Berlin: Freie Universität; 2013.

  60. Schmidt J, Martin A. Appearance-Based Rejection Sensitivity and Validation of a German Version of the Appearance-Based Rejection Sensitivity Scale (ARS-D). Zeitschrift fur Klinische Psychologie und Psychotherapie. 2017;46(3):157–168.

    Article  Google Scholar 

  61. Wilhelm P, Schoebi D. Assessing mood in daily life. Eur J Psychol Assess. 2007;23(4):258–267.

    Article  Google Scholar 

  62. Wilmers F, Munder T, Leonhart R, Herzog T, Plassmann R, Barth J, Linster HW. Die deutschsprachige Version des Working Alliance Inventory-short revised (WAI-SR)-Ein schulenübergreifendes, ökonomisches und empirisch validiertes Instrument zur Erfassung der therapeutischen Allianz. Klinische Diagnostik und Evaluation. 2008;1(3):343–358.

    Google Scholar 

  63. Cardi V, Turton R, Schifano S, Leppanen J, Hirsch CR, Treasure J. Biased interpretation of ambiguous social scenarios in anorexia nervosa. Eur Eat Disord Rev. 2017;25(1):60–64.

    Article  PubMed  Google Scholar 

  64. Wyssen A, Coelho JS, Wilhelm P, Zimmermann G, Munsch S. Thought-shape fusion in young healthy females appears after vivid imagination of thin ideals. J Behav Ther Exp Psychiatry. 2016;52:75–82.

    Article  PubMed  Google Scholar 

  65. Patton JH, Stanford MS, Barratt ES. Factor structure of the Barratt impulsiveness scale. J Clin Psychol. 1995;51(6):768–774.

    Article  PubMed  Google Scholar 

  66. Neitzer A, Sun S, Doss S, Moran J, Schiller B. B eck D epression I nventory-F ast S creen (BDI-FS): an efficient tool for depression screening in patients with end-stage renal disease. Hemodial Int. 2012;16(2):207–213.

    Article  PubMed  Google Scholar 

  67. Pook M, Tuschen-Caffier B, Brähler E. Evaluation and comparison of different versions of the Body Shape Questionnaire. Psychiatry Res. 2008;158(1):67–73.

    Article  PubMed  Google Scholar 

  68. NIMH: CGI. Clinical Global Impressions. In: The documentation of clinical psychotropic trug trials. edn. Rockville, Maryland: National Institute of Mental Health; 1973: 217–222.

  69. Neumann A, van Lier PA, Gratz KL, Koot HM. Multidimensional assessment of emotion regulation difficulties in adolescents using the difficulties in emotion regulation scale. Assessment. 2010;17(1):138–149.

    Article  PubMed  Google Scholar 

  70. Kaufman EA, Xia M, Fosco G, Yaptangco M, Skidmore CR, Crowell SE. The difficulties in emotion regulation scale short form (DERS-SF): validation and replication in adolescent and adult samples. J Psychopathol Behav Assess. 2016;38(3):443–455.

    Article  Google Scholar 

  71. Grunert SC: Ein Inventar zur Erfassung von Selbstaussagen zum Ernährungsverhalten. Diagnostica 1989.

  72. Lichev V, Rufer M, Rosenberg N, Ihme K, Grabe H-J, Kugel H, Donges U-S, Kersting A, Suslow T. Assessing alexithymia and emotional awareness: relations between measures in a German non-clinical sample. Compr Psychiatry. 2014;55(4):952–959.

    Article  PubMed  Google Scholar 

  73. 8.Barnow S, Reinelt E, Sauer C: Emotionsregulation Manual und Materialien für Trainer und Therapeuten. Berlin, Heidelberg: Springer; 2016.

  74. Allen KL, McLean NJ, Byrne SM. Evaluation of a new measure of mood intolerance, the Tolerance of Mood States Scale (TOMS): psychometric properties and associations with eating disorder symptoms. Eat Behav. 2012;13(4):326–334.

    Article  PubMed  Google Scholar 

  75. Meule A. Food cravings in food addiction: exploring a potential cut-off value of the Food Cravings Questionnaire-Trait-reduced. Eating Weight Disorders-Stud Anorexia Bulimia Obesity. 2018;23(1):39–43.

    Article  Google Scholar 

  76. Schubert T, Friedmann F, Regenbrecht H: The experience of presence: factor analytic insights. Presence: Teleoper Virtual Environ. 2001;10(3):266–281.

  77. Roth D, Lugrin JL, Latoschik ME, Huber S. Alpha IVBO-construction of a scale to measure the illusion of virtual body ownership. In: Proceedings of the 2017 CHI conference extended abstracts on human factors in computing systems, 2017:2875–2883.

  78. Bieda A, Pflug V, Scholten S, Lippert MW, Ladwig I, Nestoriuc Y, Schneider S. Unerwünschte Nebenwirkungen in der Kinder-und Jugendlichenpsychotherapie–Eine Einführung und Empfehlungen. PPmP-Psychotherapie· Psychosomatik· Medizinische Psychologie 2018; 68(09/10):383–390.

  79. Munsch S, Biedert E, Meyer A, Michael T, Schlup B, Tuch A, Margraf J. A randomized comparison of cognitive behavioral therapy and behavioral weight loss treatment for overweight individuals with binge eating disorder. Int J Eat Disord. 2007;40(2):102–113.

    Article  PubMed  Google Scholar 

  80. Williams KD, Jarvis B. Cyberball: a program for use in research on interpersonal ostracism and acceptance. Behav Res Methods. 2006;38(1):174–180.

    Article  PubMed  Google Scholar 

  81. Kroenke K, Spitzer RL, Williams JB, Löwe B. An ultra-brief screening scale for anxiety and depression: the PHQ–4. Psychosomatics. 2009;50(6):613–621.

    PubMed  Google Scholar 

  82. Thompson J, Cattarin J, Fowler B, Fisher E. Perception of Teasing Scale 1995. 1999.

  83. Sitzer P, Marth J, Kocik C, Müller KN: Ergebnisbericht der Online-Studie "Cyberbullying bei Schülerinnen und Schülern". 2012.

  84. Wolke D: Bullying und psychische Gesundheit. In: Lehrbuch der Verhaltenstherapie, Band 3. edn.: Springer; 2019:979–995.

  85. Williams KD. Ostracism: effects of being excluded and ignored. Adv Exp Soc Psychol. 2009;41:275–314.

    Article  Google Scholar 

  86. Fergus TA, Valentiner DP, McGrath PB, Gier-Lonsway SL, Kim H-S. Short forms of the social interaction anxiety scale and the social phobia scale. J Pers Assess. 2012;94(3):310–320.

    Article  PubMed  Google Scholar 

  87. Kennedy RS, Lane NE, Berbaum KS, Lilienthal MG. Simulator sickness questionnaire: an enhanced method for quantifying simulator sickness. Int J Aviat Psychol. 1993;3(3):203–220.

    Article  Google Scholar 

  88. Grimm J: State-trait-anxiety inventory nach Spielberger. Deutsche Lang-und Kurzversion. Methodenforum der Universität Wien: MF-Working Paper 2; 2009.

  89. Logan GD, Schachar RJ, Tannock R. Impulsivity and inhibitory control. Psychol Sci. 1997;8(1):60–64.

    Article  Google Scholar 

  90. Taylor S, Whincup P, Hindmarsh P, Lampe F, Odoki K, Cook D. Performance of a new pubertal self-assessment questionnaire: a preliminary study. Paediatr Perinat Epidemiol. 2001;15(1):88–94.

    Article  PubMed  Google Scholar 

  91. Bailenson JN, Blascovich J, Beall AC, Loomis JM. Interpersonal distance in immersive virtual environments. Pers Soc Psychol Bull. 2003;29(7):819–833.

    Article  PubMed  Google Scholar 

  92. Cyders MA, Littlefield AK, Coffey S, Karyadi KA. Examination of a short English version of the UPPS-P Impulsive Behavior Scale. Addict Behav. 2014;39(9):1372–1376.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Munsch S. Study protocol: psychological and physiological consequences of exposure to mass media in young women-an experimental cross-sectional and longitudinal study and the role of moderators. BMC Psychol. 2014;2(1):1–12.

    Article  Google Scholar 

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Acknowledgements

We thank Alexander Ariu for his support during the preparation of the submission of this study protocol.

Funding

This work was peer-reviewed and supported by the SNSF within the framework of project funding (Grant Number SNFNr.: 100001C_185387). The pilot study was funded by the research foundation of the University of Fribourg (No. 419).

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Authors and Affiliations

  1. Clinical Psychology and Psychotherapy, Department of Psychology, University of Fribourg, Rue P.-A.-de-Faucigny 2, 1700, Fribourg, Switzerland

    Simone Munsch, Felicitas Forrer, Adrian Naas, Verena Mueller & Marius Rubo

  2. Technology for Human Well-Being Institute (HumanTech), University of Applied Sciences of Western Switzerland, Boulevard de Pérolles 80, Fribourg, Switzerland

    Fouad Hannoun & Elena Mugellini

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  1. Simone Munsch
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Contributions

S.M. designed the pilot study and the i-BEAT trial and FF, MR as well as VM and AN participated in adapting the design of the study. SM, FF together with AN and VM co-developed the treatment modules, EM and FH developed the digital tools of i-BEAT platform. SM wrote the initial draft of the study protocol and manuscript and all coauthors revised the manuscript critically and for important intellectual content. All the authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Simone Munsch.

Ethics declarations

Ethics approval and consent to participate

Diagnostics, assessments in VR, HRV recordings or the gSST are not expected to produce negative side effects beyond increased awareness. Participants will be remunerated for their expenditure of time in the App based study 1 and study 2. Providing CBT-E and INTER-E interventions for LOC adapted to the needs of youth should produce positive effects (the pilot BEAT trial had strong within subject effects on LOC episodes, ED pathology and mood, and 81% of participants reported at the end of the treatment to have no LOC anymore or that the consumed food amount during a LOC episode decreased). Upcoming problems are monitored and in case of difficulties, support in coping is given by the therapists under supervision of SM and emergency contacts are provided. Collaborators will be trained to handle subject burden of participating youth together with SM. This study has been approved by the ethics committee of the canton of Berne (2018-00230). All participants will be asked for written informed consent before inclusion in the study. The i-BEAT study is registered at the German Clinical Trials Register (DRKS00023706). The participants age ranges between 14 and 24 years. According to swiss law, youth, even below the age of 14 years has the right of non-information of their legal guardians with respect to a participation in a psychotherapeutic treatment. All participants under the age of 18 years are therefore invited but not obliged to inform the legal guardians about their participation in i-BEAT and a respective parents’ information sheet can be provided. Therefore, informed consents are signed either by participating youth alone or together with their legal guardians.

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Not applicable.

Competing interests

There are no competing interests.

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Additional file 1

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Munsch, S., Forrer, F., Naas, A. et al. Correlates of interpersonal emotion regulation problems in Loss of Control eating (LOC) in youth: study protocol of the combined online and App based questionnaire, laboratory and randomized controlled online intervention i-BEAT trial. BMC Psychol 9, 193 (2021). https://0-doi-org.brum.beds.ac.uk/10.1186/s40359-021-00690-8

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