Goal pursuit increases more after dietary success than after dietary failure: examining conflicting theories of self-regulation using ecological momentary assessment.

BACKGROUND: Maintaining a healthy body weight and reaching long-term dietary goals requires ongoing self-monitoring and behavioral adjustments. How individuals respond to successes and failures is described in models of self-regulation: while cybernetic models propose that failures lead to increased self-regulatory efforts and successes permit a reduction of such efforts, motivational models (e.g., social-cognitive theory) make opposite predictions. Here, we tested these conflicting models in an ecological momentary assessment (EMA) context and explored whether effort adjustments are related to inter-individual differences in perceived self-regulatory success in dieting (i.e., weight management). METHODS: Using linear mixed effects models, we tested in 174 diet-interested individuals whether current day dietary success or failure (e.g., on Monday) was followed by self-regulatory effort adjustment for the next day (e.g., on Tuesday) across 14 days. Success vs. failure was operationalized with two EMA items: first, whether food intake was higher vs. lower than usual and second, whether food intake was perceived as more vs. less goal-congruent than usual. Trait-level perceived self-regulatory success in dieting was measured on a questionnaire. RESULTS: Intended self-regulatory effort increased more strongly after days with dietary success (i.e., eating less than usual / rating intake as goal-congruent) than after days with dietary failure (i.e., eating more than usual / rating intake as goal-incongruent), especially in those individuals with lower scores on perceived self-regulatory success in dieting. CONCLUSIONS: Findings support mechanisms proposed by social-cognitive theory, especially in unsuccessful dieters. Thus, future dietary interventions could focus on preventing the decrease in self-regulatory effort after instances of dietary failures and thereby mitigate the potential risk that a single dietary failure initiates a downward spiral into unhealthy eating.

A smartphone application to reduce problematic drinking: a feasibility trial.

BACKGROUND: Problematic drinking is common among college students and associated with various somatic and mental health problems. Given significant evidence for the efficacy of smartphone-based interventions and the frequent use of smartphones among college students, it can be assumed that such interventions have great potential to facilitate access to evidence-based interventions for students suffering from problematic drinking. Thus, we developed a brief intervention that combined a counseling session with an app that utilizes approach-avoidance modification training to reduce alcohol consumption. METHODS: To test the feasibility and explore the potential efficacy of the intervention, we conducted a before-after single-arm study with N = 11 participants reportedly engaging in problematic drinking, who were instructed to practice with the app for 14 days. Feasibility was assessed with the System Usability Scale (SUS). Outcomes included the reduction of self-reported problematic drinking behavior, dysfunctional attitudes about alcohol, and craving, as well as implicit associations between alcohol and self during the training period. Additionally, self-reported problematic drinking behavior was assessed at a 4-week follow-up. RESULTS: On average, participants rated app usability on the SUS (possible range: 0 to 100) with M = 84.32 (SD = 6.53). With regard to efficacy, participants reported a significant reduction of problematic drinking behavior (dpre vs. post = 0.91) which was sustained at follow-up (dfollow-up vs. baseline = 1.07). Additionally, participants reported a significant reduction of dysfunctional attitudes about alcohol (dpre vs. post = 1.48). Results revealed no significant changes in craving nor in implicit associations regarding alcohol. CONCLUSIONS: Findings from this feasibility study provide preliminary evidence that smartphone-based interventions might help reduce problematic drinking in college students. Further research needs to replicate these findings with larger samples in randomized controlled trials. TRIAL REGISTRATION: DRKS00014675 (retrospectively registered).

Why we don't eat as intended: Moderators of the short-term intention-behaviour relation in food intake.

OBJECTIVES: A healthy diet is essential for preventing chronic disease and promoting overall health. Translating one's intention to eat healthy into actual behaviour has, however, proven difficult with a range of internal and contextual factors identified as driving eating behaviour. DESIGN: We leverage Temporal Self-Regulation Theory to examine these momentary determinants' direct and moderating effects on the intention-behaviour relation with Ecological Momentary Assessment (EMA). METHODS: Eighty-seven healthy participants (mage = 24.1 years; 59 women, 28 men) reported, 5 times daily for 10 weekdays, their intentions to stick to a self-set dietary restriction goal for the next 3 hr, the goal congruency of their eating behaviour in the past 3 hr, and a range of factors potentially influencing food intake, such as stress, emotions and environmental eating cues. RESULTS: Two-part multilevel modelling revealed that craving, availability of goal-incongruent foods, social eating cues, giving in to other temptations and weaker momentary intentions directly increased the risk and severity of goal-incongruent intake within the next 3 hr. Social cues, stress and craving further influence behaviour through altering intention implementation. CONCLUSIONS: Results imply that people regularly fail to implement intentions for 3-hr periods and that a range of factors influences this, both directly and by disrupting intentional processes. While for some barriers, fostering strong intentions throughout the day could be beneficial, others require different strategies for dietary adherence.

Excess after stress-A three-study validation of the salzburg stress drinking scale as a new tool to measure the stress-drinking relationship.

Stress frequently influences a person's propensity to drink alcohol. Inter-individual differences in such stress-related drinking can be assessed through psychometric scales; however, available questionnaires conflate stress- with emotion-related reasons to drink and ignore evidence of decreased alcohol consumption in response to stress. Therefore, we developed a genuine stress-drinking scale (Salzburg Stress Drinking Scale; SSDS), adapted from the Salzburg Stress Eating Scale, and assessed its psychometric properties. In study 1 (n = 639), the SSDS was found to have a one-factor structure, excellent internal consistency, and acceptable test-retest reliability. SSDS scores were significantly correlated with other measures assessing emotional drinking, but uncorrelated with general alcohol pathology and other health-relevant consummatory behaviors such as stress-related eating or nicotine consumption. In addition, no significant sex differences arose. In study 2 (n = 42) patients with an alcohol use disorder or addiction scored significantly higher on the SSDS compared to healthy controls. In an Ecological Momentary Assessment study 3 (n = 67), the SSDS showed partial ecological validity through significant relationships with daily alcohol consumption, but not daily stress-drinking relationships. In sum, the SSDS represents a psychometrically sound tool for the measurement of stress-related drinking and complements a battery of stress-related changes in health-relevant behaviors.

Imagine chocolate: The craving experience questionnaire in the food domain.

Measurement of food craving has gained relevance in the current obesity epidemic. The Craving Experience Questionnaire (CEQ) considers not only craving intensity but also cognitive intrusiveness and imagery vividness as separate craving factors and could thus refine food craving assessment. It is available in two versions with ten items each. The CEQ-F assesses craving frequency across specific time periods and the CEQ-S time-point specific craving strength. Across three independent studies, N = 533 participants completed the German chocolate CEQ-F referenced at the past year to operationalise trait-like craving. Among them, N = 402 also completed the German chocolate CEQ-S referenced at the current moment to operationalise state-like craving. Four-week test-retest reliability was measured. For external validity, we assessed self-reported chocolate consumption, body-mass-index, trait approach motivation, general imagery vividness, and the most widely used food craving questionnaire, namely the Food Cravings Questionnaires in a trait (FCQ-T-r) and state version (FCQ-S), as well as behavioural approach bias (reaction time-based measurement). The three-factor structure was replicated with excellent internal consistency for both CEQ-F and CEQ-S. Test-retest reliability was moderate for both CEQ versions. CEQ-F scores were related to higher levels of chocolate consumption, approach motivation, and FCQ-T-r scores, but not to body-mass-index, imagery vividness, or approach bias. CEQ-S scores were associated with FCQ-S scores and partly with approach bias, but not with approach motivation and imagery vividness. The current results support the factor structure, validity and reliability of the German chocolate CEQ-S and CEQ-F with questions remaining regarding the ability of the CEQ-S to measure state craving. Thus, CEQ-F and CEQ-S usefully contribute to food craving assessment.

Within-person association of volitional factors and physical activity: Insights from an ecological momentary assessment study.

OBJECTIVE: Current health behavior models of physical activity (PA) suggest that not all PA intentions are translated into actual PA behavior, resulting in a significant intention-behavior gap (IBG) of almost 50%. These models further suggest that higher self-efficacy and specific planning can aid in decreasing this gap. However, as most evidence stems from between-person (trait level), questionnaire-based research, it is unclear how large short-term IBGs are, how self-efficacy and planning covary within-persons across time and whether they similarly predict smaller IBGs. It is likely that day-to-day changes in circumstances and barriers affect these variables thus the applicability of theoretical models is uncertain. Here, within-person prospective analyses of ecological momentary assessment (EMA) data can provide insights. METHODS: 35 healthy participants (aged 23-67) completed four EMA-based questionnaires every day for three weeks. Each prompt assessed PA (retrospectively, "since the last EMA prompt"); PA intentions, planning specificity, self-efficacy, and intrinsic motivation (prospectively, "until the next EMA prompt") and momentary affect. Generalized logistic mixed-effect modeling was used to test predictors of PA. RESULTS: Across the 2341 answered EMA prompts, PA intentions were not enacted in 25% of the episodes (IBG). In episodes with given intentions, PA likelihood increased with higher levels of self-efficacy, planning specificity, and intrinsic motivation. The latter two also positively predicted PA duration and intensity. CONCLUSIONS: Short-term intention behavior gaps seem to be smaller than what is known from more long-term studies, most likely as individuals can anticipate the actual circumstances of PA. Further, current health behavior models show validity in explaining within-person dynamics in IBGs across time. Knowing the relevance of planning specificity, self-efficacy and intrinsic motivation for day-to-day variations in PA enactment can inform respective real-time mHealth interventions for facilitating PA.

Emotional eating: elusive or evident? Integrating laboratory, psychometric and daily life measures.

PURPOSE: Emotional eating (EE) refers to eating in response to (negative) emotions. Evidence for the validity of EE is mixed: some meta-analyses find EE only in eating disordered patients, others only in restrained eaters, which suggest that only certain subgroups show EE. Furthermore, EE measures from lab-based assessments, ecological momentary assessment (EMA), and psychometric measures often diverge. This paper tested whether the covariance of these three different EE methods can be modeled through a single latent variable (factorial validity), and if so, how this variable would relate to restrained eating (construct validity), Body-Mass-Index (BMI), and subclinical eating disorder symptomatology (concurrent validity). METHODS: 102 non-eating disordered female participants with a wide BMI range completed EE measures from three methods: psychometric questionnaires, a laboratory experiment (craving ratings of food images in induced neutral vs. negative emotion) and EMA questionnaires (within-participant correlations of momentary negative emotions and momentary food cravings across 9 days). Two measures for each method were extracted and submitted to confirmatory factor analysis. RESULTS: A one-factor model provided a good fit. The resulting EElat factor correlated positively with subclinical eating disorder symptoms and BMI but not with restrained eating. CONCLUSIONS: The one-factor solution shows that the EE construct can validly be assessed with three different methods. Individual differences in EE are supported by the data and are related to eating and weight problem symptomatology but not to restrained eating. This supports learning accounts of EE and underscores the relevance of the EE construct to physical and mental health. LEVEL OF EVIDENCE: II (Evidence obtained from well-designed controlled trials without randomization).

Emotional food-cue-reactivity in anorexia nervosa and bulimia nervosa: An electroencephalography study.

OBJECTIVE: Food-cue-reactivity entails neural and experiential responses to the sight and smell of attractive foods. Negative emotions can modulate such cue-reactivity and this might be central to the balance between restrictive versus bulimic symptomatology in Anorexia Nervosa (AN) and Bulimia Nervosa (BN). METHOD: Pleasantness ratings and electrocortical responses to food images were measured in patients with AN (n = 35), BN (n = 32) and matched healthy controls (HC, n = 35) in a neutral state and after idiosyncratic negative emotion induction while electroencephalography (EEG) was recorded. The EEG data were analyzed using a mass testing approach. RESULTS: Individuals with AN showed reduced pleasantness for foods compared to objects alongside elevated widespread occipito-central food-object discrimination between 170 and 535 ms, indicative of strong neural cue-reactivity. Food-object discrimination was further increased in the negative emotional condition between 690 and 1200 ms over centroparietal regions. Neither of these effects was seen in individuals with BN. DISCUSSION: Emotion modulated food-cue-reactivity in AN might reflect a decreased appetitive response in negative mood. Such specific (emotion-)regulatory strategies require more theoretical work and clinical attention. The absence of any marked effects in BN suggests that emotional cue-reactivity might be less prominent in this group or quite specific to certain emotional contexts or food types. PUBLIC SIGNIFICANCE: Negative affectivity is a risk factor for the development of eating disorders and individuals with eating disorders experience problems with emotion regulation. To better understand the effects of negative emotions, the present study investigated how they affected neural correlates of food perception in anorexia nervosa and bulimia nervosa.

Predicting food craving in everyday life through smartphone-derived sensor and usage data.

Background: Food craving relates to unhealthy eating behaviors such as overeating or binge eating and is thus a promising target for digital interventions. Yet, craving varies strongly across the day and is more likely in some contexts (external, internal) than in others. Prediction of food cravings ahead of time would enable preventive interventions. Objective: The objective of this study was to investigate whether upcoming food cravings could be detected and predicted from passive smartphone sensor data (excluding geolocation information) without the need for repeated questionnaires. Methods: Momentary food craving ratings, given six times a day for 14 days by 56 participants, served as the dependent variable. Predictor variables were environmental noise, light, device movement, screen activity, notifications, and time of the day recorded from 150 to 30 min prior to these ratings. Results: Individual high vs. low craving ratings could be predicted on the test set with a mean area under the curve (AUC) of 0.78. This outperformed a baseline model trained on past craving values in 85% of participants by 14%. Yet, this AUC value is likely the upper bound and needs to be independently validated with longer data sets that allow a split into training, validation, and test sets. Conclusions: Craving states can be forecast from external and internal circumstances as these can be measured through smartphone sensors or usage patterns in most participants. This would allow for just-in-time adaptive interventions based on passive data collection and hence with minimal participant burden.

Conflict in a word-based approach-avoidance task is stronger with positive words.

BACKGROUND: Valence and motivational direction are linked. We approach good things and avoid bad things, and experience overriding these links as conflicting. Positive valence is more consistently linked with approach than negative valence is linked with avoidance. Therefore, avoiding positive stimuli should produce greater behavioral and neural signs of conflict than approaching negative stimuli. METHODS: In the present event-related potential study, we tested this assumption by contrasting positive and negative conflict. We used the manikin task, in which we read positive and negative words that they needed to approach and avoid. RESULTS: Consistent with our prediction, positive conflict prolonged reaction times more than negative conflict did. A late (500-1000 ms following word onset) event-related potential that we identified as the Conflict slow potential, was only sensitive to positive conflict. CONCLUSION: The results of this study support the notion that avoiding positive stimuli is more conflicting than approaching negative stimuli. The fact that the conflict slow potential is typically sensitive to response conflict rather than stimulus conflict suggests that the manikin task primarily requires people to override prepotent responses rather than to identify conflicting stimuli. Thus, the present findings also shed light on the psychological processes subserving conflict resolution in the manikin task.

Testing the effectiveness of a mobile approach avoidance intervention and measuring approach biases in an ecological momentary assessment context: study protocol for a randomised-controlled trial.

INTRODUCTION: Unhealthy eating behaviour is a major contributor to obesity and related diseases and is associated with a behavioural bias to approach rather than avoid desired foods, as measured with reaction time tasks. Approach-avoidance interventions (AAIs) have been proposed as a way to modify food evaluations and help people to eat in accordance with their dietary goals. Mobile implementations of AAI might be easily accessible, low threshold interventions, but their effectiveness has not been established yet. METHODS AND ANALYSIS: Participants who aim to change their eating behaviour are randomised to intervention or control groups. They complete six sessions of a smartphone-based AAI, in which they push (ie, avoid) or pull (ie, approach) personalised food images. Intervention group participants always avoid foods that they personally want to eat less often and approach foods that they personally want to eat more often. In the control group, images are paired equally often with both response directions. To evaluate contextual and dynamic intervention effects, ecological momentary assessment (EMA) is measured throughout, with questions about food intake, hunger, stress, emotions, eating intentions, food craving and impulsivity twice a day. Additional EMA preintervention and postintervention measures are administered before and after the intervention phase (4 days each) with a 1-day follow-up EMA 4 weeks after the intervention. Multilevel models will examine the temporal covariance between approach bias and self-reported variables as well as short-term and long-term intervention effects on approach bias, food intake and craving. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of the University of Salzburg. Results will be published in peer-reviewed scientific journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER: German Clinical Trials Register DRKS, registration number DRKS00030780.

How pre-processing decisions affect the reliability and validity of the approach-avoidance task: Evidence from simulations and multiverse analyses with six datasets.

Reaction time (RT) data are often pre-processed before analysis by rejecting outliers and errors and aggregating the data. In stimulus-response compatibility paradigms such as the approach-avoidance task (AAT), researchers often decide how to pre-process the data without an empirical basis, leading to the use of methods that may harm data quality. To provide this empirical basis, we investigated how different pre-processing methods affect the reliability and validity of the AAT. Our literature review revealed 108 unique pre-processing pipelines among 163 examined studies. Using empirical datasets, we found that validity and reliability were negatively affected by retaining error trials, by replacing error RTs with the mean RT plus a penalty, and by retaining outliers. In the relevant-feature AAT, bias scores were more reliable and valid if computed with D-scores; medians were less reliable and more unpredictable, while means were also less valid. Simulations revealed bias scores were likely to be less accurate if computed by contrasting a single aggregate of all compatible conditions with that of all incompatible conditions, rather than by contrasting separate averages per condition. We also found that multilevel model random effects were less reliable, valid, and stable, arguing against their use as bias scores. We call upon the field to drop these suboptimal practices to improve the psychometric properties of the AAT. We also call for similar investigations in related RT-based bias measures such as the implicit association task, as their commonly accepted pre-processing practices involve many of the aforementioned discouraged methods. HIGHLIGHTS: • Rejecting RTs deviating more than 2 or 3 SD from the mean gives more reliable and valid results than other outlier rejection methods in empirical data • Removing error trials gives more reliable and valid results than retaining them or replacing them with the block mean and an added penalty • Double-difference scores are more reliable than compatibility scores under most circumstances • More reliable and valid results are obtained both in simulated and real data by using double-difference D-scores, which are obtained by dividing a participant's double mean difference score by the SD of their RTs.

Toward Individualized Prediction of Binge-Eating Episodes Based on Ecological Momentary Assessment Data: Item Development and Pilot Study in Patients With Bulimia Nervosa and Binge-Eating Disorder.

BACKGROUND: Prevention of binge eating through just-in-time mobile interventions requires the prediction of respective high-risk times, for example, through preceding affective states or associated contexts. However, these factors and states are highly idiographic; thus, prediction models based on averages across individuals often fail. OBJECTIVE: We developed an idiographic, within-individual binge-eating prediction approach based on ecological momentary assessment (EMA) data. METHODS: We first derived a novel EMA-item set that covers a broad set of potential idiographic binge-eating antecedents from literature and an eating disorder focus group (n=11). The final EMA-item set (6 prompts per day for 14 days) was assessed in female patients with bulimia nervosa or binge-eating disorder. We used a correlation-based machine learning approach (Best Items Scale that is Cross-validated, Unit-weighted, Informative, and Transparent) to select parsimonious, idiographic item subsets and predict binge-eating occurrence from EMA data (32 items assessing antecedent contextual and affective states and 12 time-derived predictors). RESULTS: On average 67.3 (SD 13.4; range 43-84) EMA observations were analyzed within participants (n=13). The derived item subsets predicted binge-eating episodes with high accuracy on average (mean area under the curve 0.80, SD 0.15; mean 95% CI 0.63-0.95; mean specificity 0.87, SD 0.08; mean sensitivity 0.79, SD 0.19; mean maximum reliability of rD 0.40, SD 0.13; and mean rCV 0.13, SD 0.31). Across patients, highly heterogeneous predictor sets of varying sizes (mean 7.31, SD 1.49; range 5-9 predictors) were chosen for the respective best prediction models. CONCLUSIONS: Predicting binge-eating episodes from psychological and contextual states seems feasible and accurate, but the predictor sets are highly idiographic. This has practical implications for mobile health and just-in-time adaptive interventions. Furthermore, current theories around binge eating need to account for this high between-person variability and broaden the scope of potential antecedent factors. Ultimately, a radical shift from purely nomothetic models to idiographic prediction models and theories is required.

Differential Orbitofrontal Cortex Responses to Chocolate Images While Performing an Approach-Avoidance Task in the MRI Environment.

Background: Chocolate is one of the most frequently craved foods, and it often challenges self-regulation. These cravings may be underpinned by a neural facilitation of approach behavior toward chocolate. This preregistered study investigated the behavioral and neural correlates of such a bias using functional magnetic resonance imaging (fMRI) and reaction times (RTs). Methods: A total of n = 30 frequent chocolate eaters performed a relevant-feature approach-avoidance task (AAT) in the MRI scanner using buttons to enlarge (approach) or to shrink (avoid) pictures of chocolate and inedible control objects. We tested (a) whether implicit RT-based approach biases could be measured in a supine position in the scanner, (b) whether those biases were associated with activity in reward-related brain regions such as the insula, amygdala, striatum, and orbitofrontal cortex (OFC), and (c) whether individual RT-based bias-scores correlated with measures of chocolate craving. Results: Behaviorally, we found a highly reliable approach bias toward chocolate, defined by faster RTs in the compatible conditions (approach chocolate, avoid objects) compared to the incompatible conditions (avoid chocolate, approach objects). Neurally, this compatibility effect involved activity in the left medial OFC, a neural response that was positively correlated with individual approach bias scores. Conclusions: This study shows that the relevant feature AAT can be implemented in an fMRI setting in a supine position using buttons. An approach bias toward chocolate seems related to medial OFC activation that might serve to devalue chocolate when it has to be avoided. Our demonstration of neural and behavioral approach biases for chocolate underscores the need for stimulus-specific cognitive trainings to support healthy consumption and successful self-regulation.

Touchscreen-based approach-avoidance responses to appetitive and threatening stimuli.

BACKGROUND AND OBJECTIVES: Individuals are thought to be biased towards approaching positive stimuli and avoiding negative stimuli. Yet, it is unclear whether this general pattern applies to all stimulus classes or whether biases are more specific. We expected significant approach biases towards two types of positive stimuli, appetitive foods and butterflies; and avoidance biases away from two types of negative stimuli, spoiled foods and spiders. METHODS: A touchscreen-based Approach-Avoidance Task (AAT), using hand gestures toward or away from stimuli assessed biases. Questionnaires and image ratings assessed individual differences in stimulus evaluations. RESULTS: Approach biases for butterflies and appetitive foods were found, the latter being strongest towards individually liked foods. There was no avoidance bias for spoiled foods. An avoidance bias for spiders was found in individuals with elevated spider fear. LIMITATIONS: Incomplete counterbalancing precluded direct comparison between both positive and negative stimuli. CONCLUSIONS: Behavioural biases in the touchscreen AAT generally co-vary with individuals' affective evaluation of the stimuli. Approach biases were elicited by positive stimuli independently of whether they were regularly (foods) or rarely (butterflies) approached in everyday life. This may hint towards a tendency to approach positive stimuli regardless of the specific category, whereas avoidance biases may be more stimulus specific.

Clustering individuals' temporal patterns of affective states, hunger, and food craving by latent class vector-autoregression.

BACKGROUND: Eating plays an important role in mental and physical health and is influenced by affective (e.g., emotions, stress) and appetitive (i.e., food craving, hunger) states, among others. Yet, substantial temporal variability and marked individual differences in these relationships have been reported. Exploratory data analytical approaches that account for variability between and within individuals might benefit respective theory development and subsequent confirmatory studies. METHODS: Across 2 weeks, 115 individuals (83% female) reported on momentary affective states, hunger, and food craving six times a day. Based on these ecological momentary assessment (EMA) data we investigated whether latent class vector-autoregression (LCVAR) can identify different clusters of participants based on similarities in their temporal associations between these states. RESULTS: LCVAR allocated participants into three distinct clusters. Within clusters, we found both positive and negative associations between affective states and hunger/food craving, which further varied temporally across lags. Associations between hunger/food craving and subsequent affective states were more pronounced than vice versa. Clusters differed on eating-related traits such as stress-eating and food craving as well as on EMA completion rates. DISCUSSION: LCVAR provides novel opportunities to analyse time-series data in affective science and eating behaviour research and uncovers that traditional models of affect-eating relationships might be overly simplistic. Temporal associations differ between subgroups of individuals with specific links to eating-related traits. Moreover, even within subgroups, differences in associations across time and specific affective states can be observed. To account for this high degree of variability, future research and theories should consider individual differences in direction and time lag of associations between affective states and eating behaviour, daytime and specific affective states. In addition to that, methodological implications for EMA research are discussed.

Devaluation of NoGo stimuli is both robust and fragile.

Consistently not responding to stimuli during go/no-go training leads to lower evaluations of these NoGo stimuli. How this NoGo-devaluation-effect can be explained has remained unclear. Here, we ran three experiments to test the hypothesis that people form stimulus-stop-associations during the training, which predict the strength of the devaluation-effect. In Experiment 1, we tried to simultaneously measure the stimulus-stop-associations and NoGo-devaluation, but we failed to find these effects. In Experiment 2, we measured NoGo-devaluation with established procedures from previous work, and stimulus-stop-associations with a novel separate task. Results revealed a clear NoGo-devaluation-effect, which remained visible across multiple rating blocks. Interestingly, this devaluation-effect disappeared when stimulus-stop-associations were measured before stimulus evaluations, and there was no evidence supporting the formation of the stimulus-stop-associations. In Experiment 3, we found evidence for the acquisition of stimulus-stop-associations using an established task from previous work, but this time we found no subsequent NoGo-devaluation-effect. The present research suggests that the NoGo-devaluation-effect and stimulus-stop-associations can be found with standard established procedures, but that these effects are very sensitive to alterations of the experimental protocol. Furthermore, we failed to find evidence for both effects within the same experimental protocol, which has important theoretical and applied implications.

Prone to food in bad mood-Emotion-potentiated food-cue reactivity in patients with binge-eating disorder.

OBJECTIVE: Theories on emotional eating are central to our understanding of etiology, maintenance, and treatment of binge eating. Yet, findings on eating changes under induced negative emotions in binge-eating disorder (BED) are equivocal. Thus, we studied whether food-cue reactivity is potentiated under negative emotions in BED, which would point toward a causal role of emotional eating in this disorder. METHODS: Patients with BED (n = 24) and a control group without eating disorders (CG; n = 69) completed a food picture reactivity task after induction of negative versus neutral emotions. Food-cue reactivity (self-reported food pleasantness, desire to eat [DTE], and corrugator supercilii muscle response, electromyogram [EMG]) was measured for low- and high-caloric food pictures. RESULTS: Patients with BED showed emotion-potentiated food-cue reactivity compared to controls: Pleasantness and DTE ratings and EMG response were increased in BED during negative emotions. This was independent of caloric content of the images. CONCLUSIONS: Food-cue reactivity in BED was consistent with emotional eating theories and points to a heightened response to all foods regardless of calorie content. The discrepancy of appetitive ratings with the aversive corrugator response points to ambivalent food responses under negative emotions in individuals with BED.

(Mouse cursor)-Tracking food decisions in binge eating disorder reveals preference for high-energy foods and a role of BMI.

Binge Eating Disorder (BED) has been associated with deficits in cognitive control and decision-making. Yet, no study has yet investigated the characteristics of food choice and the involved choice conflict in this disorder. In the present study individuals with BED (N = 22) and without BED (N = 61), with a body mass index (BMI) between 21 and 44 completed 153 binary food decisions among foods varying in palatability and energy density. To assess conflict during choice we recorded computer mouse paths and reaction times. Subsequently, participants rated all foods on liking and energy content. Finally, participants completed a bogus taste test with the same foods to measure actual consumption. Predictors were modelled continuously using Bayesian mixed-effects modelling. Individuals with BED liked foods with higher energy content more and chose them more often in the choice task. Yet, actual consumption in the taste test did not differ between groups, neither regarding total consumption, nor of foods with higher energy. Mouse cursor-tracking revealed that control participants with higher BMIs showed more choice conflict than those with lower BMIs. This pattern was reversed in those with BED. The high-energy preference in ratings and food choice represent the first evidence in a controlled laboratory context for disorder-congruent food choice in BED. The fact that this was not reflected in actual consumption might have methodological implications for measuring laboratory eating behaviour. Mouse cursor-tracking gave further insights into choice processes and showed a less conflicted food choice in those with BED with higher BMI compared to those with lower BMI.

Further support for the validity of the social appearance anxiety scale (SAAS) in a variety of German-speaking samples.

PURPOSE: Eating disorders (ED) and social anxiety disorder are highly comorbid with potentially shared symptoms like social appearance anxiety (SAA) referring to a fear of being negatively evaluated by others' because of overall appearance. SAA constitutes a risk factor for eating psychopathology and bridges between EDs and social anxiety disorder. METHODS: The present studies examined internal consistency, factor structure, test-retest reliability, gender and age invariance, convergent validity and differences between individuals with and without an ED of a German version of the social appearance anxiety scale (SAAS) in four independent samples (n1 = 473; n2 = 712; n3 = 79; n4 = 33) including adolescents and patients with EDs. RESULTS: Consistently, the SAAS showed excellent internal consistency (ωs ≥ 0.947) and a one-factorial structure. Convergent validity was shown via high correlations of the SAAS with social anxiety (e.g., social interaction anxiety r = 0.642; fear of negative evaluation rs ≥ 0.694), body image disturbance measures (e.g., shape concerns rs ≥ 0.654; weight concerns rs ≥ 0.607; body avoidance rs ≥ 0.612; body checking rs ≥ 0.651) and self-esteem (r = -0.557) as well as moderate correlations with general eating psychopathology (e.g., restrained rs ≥ 0.372; emotional r = 0.439; external eating r = 0.149). Additionally, the SAAS showed gender and age invariance and test-retest reliability after 4 weeks with r = 0.905 in Study 2 and was able to discriminate between individuals with and without an ED in Study 4. CONCLUSION: Hence, the German version of the SAAS can reliably and validly assess SAA in female and male adolescents or adults with or without an ED. Additionally, the SAAS might be used in a therapeutic context to especially target patient groups suffering from EDs with comorbid social anxiety. LEVEL OF EVIDENCE: Level III: Evidence obtained from cohort or case-control analytic studies.