Identifying specific cues and contexts related to bingeing behavior for the development of effective virtual environments

Pla-Sanjuanelo, Joana; Ferrer-García, Marta; Gutiérrez-Maldonado, José; Riva, Giuseppe; Andreu-Gracia, Alexis; Dakanalis, Antonios; Fernández‐Aranda, Fernando; Forcano, Laura; Ribas-Sabaté, Joan; Riesco, Nadine; Rus-Calafell, Mar; Sánchez, Isabel; Sánchez-Planell, Luis

doi:10.1016/j.appet.2014.12.098

Cited by 63 publications

(42 citation statements)

References 43 publications

(75 reference statements)

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“…Participants categorized with mild, moderate, severe, and extreme severity, based on their pretreatment clinician‐rated BE frequency, differed significantly from each other in physical characteristics (BMI) and another 16 variables of clinical interest assessed at pretreatment regarding ED psychopathology and putative maintenance factors, psychiatric comorbidity and distress, and psychosocial impairment, with significantly higher levels/rates across the severity groups. These findings expand on recent work revealing that the BED severity groups were statistically distinguishable in levels of ED psychopathology (Grilo, Ivezaj, & White, a, b) and depression (Grilo, Ivezaj, & White, a) and are also consistent with earlier research indicating that greater BE frequency was significantly associated with higher mean BMI, ED psychopathology, lifetime and current psychiatric comorbidity, and psychosocial impairment (Dakanalis, Carrà, Calogero, Fida, et al, 2015; Dakanalis, Carrà, Clerici, & Riva, ; Dakanalis, Carrà, Timko, et al, 2015; Dakanalis, Favagrossa, Clerici, et al, ; Grilo, White, & Masheb, ; Peterson, Miller, Crow, Thuras, & Mitchell, ; Pla‐Sanjuanelo et al, ; Striegel, Bedrosian, Wang, & Schwartz, ; Wilfley et al, ). In addition, in keeping with past research (Grilo, Ivezaj, & White, a; Grilo, Ivezaj, & White, b; Smink, van Hoeken, Oldehinkel, & Hoek, ), the severity groups were statistically indistinguishable in demographics and age‐of‐BED onset, lending some credence to scholars' suggestions that age‐at‐onset is probably more disorder‐dependent than severity‐dependent (Smink, van Hoeken, Oldehinkel, & Hoek, ).…”

Section: Discussionsupporting

confidence: 89%

Validity and utility of the DSM‐5 severity specifier for binge‐eating disorder

Dakanalis

Colmegna

Riva

et al. 2017

Intl J Eating Disorders

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Section: Discussionsupporting

confidence: 89%

Validity and utility of the DSM‐5 severity specifier for binge‐eating disorder

Dakanalis

Colmegna

Riva

et al. 2017

Intl J Eating Disorders

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“…Participants classified with mild (31.2%), moderate (33.3%), severe (18%) and extreme (17.5%) severity of BED differed significantly from each other in BMI but also in ED features and putative maintenance factors, mood, anxiety and personalitydisorder comorbidity, MetSyn, psychological distress, social All severity groups differed statistically in post hoc pairwise comparisons (with Bonferroni correction) at p < 0.008 or less. Bentley et al, 2014;Dakanalis, Carrà, Clerici & Riva, 2015b;Dakanalis, Zanetti et al, 2015d;Grilo et al, 2009;Picot & Lilenfeld, 2003;Pla-Sanjuanelo et al, 2015;Riva, Gaggioli, & Dakanalis, 2013;Serino et al, 2016;Striegel et al, 2012;Wilfley et al, 2000). Cut-off conventions for partial η 2 are as follows: small (0.01-0.09), medium (0.10-0.24) and large (≥0.25) (Reid, 2014).…”

Section: Discussionmentioning

confidence: 99%

Classifying Adults with Binge Eating Disorder Based on Severity Levels

Dakanalis

Riva

Serino

et al. 2017

Euro Eating Disorders Rev

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The clinical utility of the severity criterion for binge eating disorder (BED), introduced in the DSM-5 as a means of addressing heterogeneity and variability in the severity of this disorder, was evaluated in 189 treatment-seeking adults with (DSM-5) BED. Participants classified with mild, moderate, severe and extreme severity of BED, based on their weekly frequency of binge eating episodes, differed significantly from each other in body mass index (BMI), eating disorder features, putative factors involved in the maintenance process of the disorder, comorbid mood, anxiety and personality disorders, psychological distress, social maladjustment and illness-specific functional impairment (medium-to-large effect sizes). They were also statistically distinguishable in metabolic syndrome prevalence, even after adjusting for BMI (large effect size), suggesting the possibility of non-BMI-mediated mechanisms. The implications of the findings, providing support for the utility of the binge frequency as a severity criterion for BED, and directions for future research are outlined. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.

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“…Given that high-calorie food has been related to high levels of craving (Greeno, Wing, & Shiffman, 2000;Pelchat, 1997;Rogers & Smit, 2000), different types of food (low-calorie versus high-calorie) were considered as specific cues. In addition, the fact of being alone has been considered a trigger of overeating in BN patients (Pla-Sanjuanelo et al, 2015). When possible, people prefer to eat with others (Larson, Nelson, Neumark-Sztainer, Story, & Hannan, 2009), and they do not usually eat alone (Redd & Castro, 1992).…”

Section: Introductionmentioning

confidence: 99%

Craving for Food in Virtual Reality Scenarios in Non‐Clinical Sample: Analysis of its Relationship with Body Mass Index and Eating Disorder Symptoms

Ferrer-García

Gutiérrez‐Maldonado

Treasure

et al. 2015

Euro Eating Disorders Rev

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Virtual reality (VR) technology has been successfully used to study the influence of specific and contextual food-related cues on emotional, cognitive and behavioural responses in patients with eating disorders (ED) and healthy controls. Following this research line, the present study assesses the effect on reported food craving of the type of food (low calorie versus high calorie) and the presence or absence of other people (private versus social context) in VR environments. Relationships between craving and body mass index (BMI) and ED symptoms are also explored. Eighty-seven female students were exposed to four VR scenarios presented in random order: a low-calorie kitchen, a high-calorie kitchen, a low-calorie restaurant and a high-calorie restaurant. After 2 minutes of exposure to each virtual scenario, food craving was assessed. Repeated measures analyses of covariance were conducted to assess changes in food craving following exposure to the different VR environments. Time elapsed since the last meal was introduced as a covariate to control for responses produced by food deprivation. Correlation and hierarchical multiple regression analyses were also conducted to assess the relationship between reported food craving and BMI and ED symptoms. Participants experienced higher levels of food craving after exposure to high-calorie foods (in both the kitchen and restaurant environments) than after exposure to low-calorie foods. Being alone in the kitchen or with friends in the restaurant had no effect on reported craving. Overall, neither BMI nor ED symptoms were related with reported food craving; only in the restaurant with low-calorie food was a significant negative correlation found between BMI and food craving. The results suggest that cue exposure in virtual environments is an effective procedure for inducing food craving in healthy controls and may be useful as a research and therapeutic tool in clinical populations.

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Identifying specific cues and contexts related to bingeing behavior for the development of effective virtual environments

Cited by 63 publications

References 43 publications

Validity and utility of the DSM‐5 severity specifier for binge‐eating disorder

Validity and utility of the DSM‐5 severity specifier for binge‐eating disorder

Classifying Adults with Binge Eating Disorder Based on Severity Levels

Craving for Food in Virtual Reality Scenarios in Non‐Clinical Sample: Analysis of its Relationship with Body Mass Index and Eating Disorder Symptoms

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