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Roel C.j. Hermans - One of the best experts on this subject based on the ideXlab platform.
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Social Modeling of eating: A review of when and why Social influence affects food intake and choice
Appetite, 2014Co-Authors: Tegan Cruwys, K.e. Bevelander, Roel C.j. HermansAbstract:A major determinant of human eating behavior is Social Modeling, whereby people use others' eating as a guide for what and how much to eat. We review the experimental studies that have independently manipulated the eating behavior of a Social referent (either through a live confederate or remotely) and measured either food choice or intake. Sixty-nine eligible experiments (with over 5800 participants) were identified that were published between 1974 and 2014. Speaking to the robustness of the Modeling phenomenon, 64 of these studies have found a statistically significant Modeling effect, despite substantial diversity in methodology, food type, Social context and participant demographics. In reviewing the key findings from these studies, we conclude that there is limited evidence for a moderating effect of hunger, personality, age, weight or the presence of others (i.e., where the confederate is live vs. remote). There is inconclusive evidence for whether sex, attention, impulsivity and eating goals moderate Modeling, and for whether Modeling of food choice is as strong as Modeling of food intake. Effects with substantial evidence were: Modeling is increased when individuals desire to affiliate with the model, or perceive themselves to be similar to the model; Modeling is attenuated (but still significant) for healthy-snack foods and meals such as breakfast and lunch, and Modeling is at least partially mediated through behavioral mimicry, which occurs without conscious awareness. We discuss evidence suggesting that Modeling is motivated by goals of both affiliation and uncertainty-reduction, and outline how these might be theoretically integrated. Finally, we argue for the importance of taking Modeling beyond the laboratory and bringing it to bear on the important societal challenges of obesity and disordered eating.
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Imitation of snack food intake among normal-weight and overweight children
Frontiers in Psychology, 2013Co-Authors: K.e. Bevelander, Anna Lichtwarck-aschoff, Doeschka J. Anschutz, Roel C.j. Hermans, Rutger C. M. E. EngelsAbstract:This study investigated whether Social Modeling of palatable food intake might partially be explained by the direct imitation of a peer reaching for snack food and, further, assessed the role of the children’s own weight status on their likelihood of imitation during the Social interaction. Real-time observations during a 10-minute play situation in which 68 participants (27.9% overweight) interacted with normal-weight confederates (instructed peers) were conducted. Children’s imitated and non-imitated responses to the confederate’s food picking movements were compared using a paired sample t-test. In addition, the pattern of likelihood of imitation was tested using multilevel proportional hazard models in a survival analysis framework. Children were more likely to eat after observing a peer reaching for snack food than without such a cue (t(67) = 5.69, P < .0001). Moreover, findings suggest that children may display different imitation responses during a Social interaction based on their weight status (HR = 2.6, P = .03, 95% CI =1.09 – 6.20). Overweight children were almost twice as likely to imitate, whereas normal-weight children had a smaller chance to imitate at the end of the interaction. Further, the mean difference in the likelihood of imitation suggest that overweight children might be less likely to imitate in the beginning of the interaction than normal-weight children. The findings provide preliminary evidence that children’s imitation food picking movements may partly contribute to Social Modeling effects on palatable food intake. That is, a peer reaching for food is likely to trigger children’s snack intake. However, the influence of others on food intake is a complex process that might be explained by different theoretical perspectives.
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mimicry of food intake the dynamic interplay between eating companions
PLOS ONE, 2012Co-Authors: Roel C.j. Hermans, K.e. Bevelander, Anna Lichtwarckaschoff, Peter C Herman, Junilla K Larsen, Rutger C. M. E. EngelsAbstract:Numerous studies have shown that people adjust their intake directly to that of their eating companions; they eat more when others eat more, and less when others inhibit intake. A potential explanation for this Modeling effect is that both eating companions' food intake becomes synchronized through processes of behavioral mimicry. No study, however, has tested whether behavioral mimicry can partially account for this Modeling effect. To capture behavioral mimicry, real-time observations of dyads of young females having an evening meal were conducted. It was assessed whether mimicry depended on the time of the interaction and on the person who took the bite. A total of 70 young female dyads took part in the study, from which the total number of bites (N = 3,888) was used as unit of analyses. For each dyad, the total number of bites and the exact time at which each person took a bite were coded. Behavioral mimicry was operationalized as a bite taken within a fixed 5-second interval after the other person had taken a bite, whereas non-mimicked bites were defined as bites taken outside the 5-second interval. It was found that both women mimicked each other's eating behavior. They were more likely to take a bite of their meal in congruence with their eating companion rather than eating at their own pace. This behavioral mimicry was found to be more prominent at the beginning than at the end of the interaction. This study suggests that behavioral mimicry may partially account for Social Modeling of food intake.
Rutger C. M. E. Engels - One of the best experts on this subject based on the ideXlab platform.
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Imitation of snack food intake among normal-weight and overweight children
Frontiers in Psychology, 2013Co-Authors: K.e. Bevelander, Anna Lichtwarck-aschoff, Doeschka J. Anschutz, Roel C.j. Hermans, Rutger C. M. E. EngelsAbstract:This study investigated whether Social Modeling of palatable food intake might partially be explained by the direct imitation of a peer reaching for snack food and, further, assessed the role of the children’s own weight status on their likelihood of imitation during the Social interaction. Real-time observations during a 10-minute play situation in which 68 participants (27.9% overweight) interacted with normal-weight confederates (instructed peers) were conducted. Children’s imitated and non-imitated responses to the confederate’s food picking movements were compared using a paired sample t-test. In addition, the pattern of likelihood of imitation was tested using multilevel proportional hazard models in a survival analysis framework. Children were more likely to eat after observing a peer reaching for snack food than without such a cue (t(67) = 5.69, P < .0001). Moreover, findings suggest that children may display different imitation responses during a Social interaction based on their weight status (HR = 2.6, P = .03, 95% CI =1.09 – 6.20). Overweight children were almost twice as likely to imitate, whereas normal-weight children had a smaller chance to imitate at the end of the interaction. Further, the mean difference in the likelihood of imitation suggest that overweight children might be less likely to imitate in the beginning of the interaction than normal-weight children. The findings provide preliminary evidence that children’s imitation food picking movements may partly contribute to Social Modeling effects on palatable food intake. That is, a peer reaching for food is likely to trigger children’s snack intake. However, the influence of others on food intake is a complex process that might be explained by different theoretical perspectives.
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mimicry of food intake the dynamic interplay between eating companions
PLOS ONE, 2012Co-Authors: Roel C.j. Hermans, K.e. Bevelander, Anna Lichtwarckaschoff, Peter C Herman, Junilla K Larsen, Rutger C. M. E. EngelsAbstract:Numerous studies have shown that people adjust their intake directly to that of their eating companions; they eat more when others eat more, and less when others inhibit intake. A potential explanation for this Modeling effect is that both eating companions' food intake becomes synchronized through processes of behavioral mimicry. No study, however, has tested whether behavioral mimicry can partially account for this Modeling effect. To capture behavioral mimicry, real-time observations of dyads of young females having an evening meal were conducted. It was assessed whether mimicry depended on the time of the interaction and on the person who took the bite. A total of 70 young female dyads took part in the study, from which the total number of bites (N = 3,888) was used as unit of analyses. For each dyad, the total number of bites and the exact time at which each person took a bite were coded. Behavioral mimicry was operationalized as a bite taken within a fixed 5-second interval after the other person had taken a bite, whereas non-mimicked bites were defined as bites taken outside the 5-second interval. It was found that both women mimicked each other's eating behavior. They were more likely to take a bite of their meal in congruence with their eating companion rather than eating at their own pace. This behavioral mimicry was found to be more prominent at the beginning than at the end of the interaction. This study suggests that behavioral mimicry may partially account for Social Modeling of food intake.
Delfien Van Dyck - One of the best experts on this subject based on the ideXlab platform.
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mediators of physical activity change in a behavioral modification program for type 2 diabetes patients
International Journal of Behavioral Nutrition and Physical Activity, 2011Co-Authors: Karlijn De Greef, Johannes Ruige, Catrine Tudorlocke, Delfien Van Dyck, Neville Owen, Benedicte Deforche, Jeanmarc Kaufman, Ilse De BourdeaudhuijAbstract:Background: Many studies have reported significant behavioral impact of physical activity interventions. However, few have examined changes in potential mediators of change preceding behavioral changes, resulting in a lack of information concerning how the intervention worked. Our purpose was to examine mediation effects of changes in psychoSocial variables on changes in physical activity in type 2 diabetes patients. Methods: Ninety-two patients (62 ± 9 years, 30, 0 ± 2.5 kg/m 2 , 69% males) participated in a randomized controlled trial. The 24-week intervention was based on Social-cognitive constructs and consisted of a face-to-face session, telephone follow-ups, and the use of a pedometer. Social-cognitive variables and physical activity (device-based and self-reported) were collected at baseline, after the 24-week intervention and at one year post-baseline. PA was measured by pedometer, accelerometer and questionnaire. Results: Post-intervention physical activity changes were mediated by coping with relapse, changes in Social norm, and Social Modeling from family members (p ≤ 0.05). One-year physical activity changes were mediated by coping with relapse, changes in Social support from family and self-efficacy towards physical activity barriers (p ≤ 0.05) Conclusions: For patients with type 2 diabetes, initiatives to increase their physical activity could usefully focus on strategies for resuming regular patterns of activity, on engaging family Social support and on building confidence about dealing with actual and perceived barriers to activity. Trial Registration: NCT00903500, ClinicalTrials.gov.
Hsinchun Chen - One of the best experts on this subject based on the ideXlab platform.
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Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2007, Chengdu, China, April 11-12, 2007, Proceedings
Lecture Notes in Computer Science, 2007Co-Authors: Christopher C. Yang, D Zeng, Mcl Chau, Kuiyu Chang, Fy Wang, J. Wang, Xueqi Cheng, Hsinchun ChenAbstract:Keynote.- Exploring Extremism and Terrorism on the Web: The Dark Web Project.- Long Papers.- Analyzing and Visualizing Gray Web Forum Structure.- An Empirical Analysis of Online Gaming Crime Characteristics from 2002 to 2004.- Detecting Cyber Security Threats in Weblogs Using Probabilistic Models.- What-if Emergency Management System: A Generalized Voronoi Diagram Approach.- Agent Based Framework for Emergency Rescue and Assistance Planning.- Object Tracking with Self-updating Tracking Window.- A Case-Based Evolutionary Group Decision Support Method for Emergency Response.- Lightweight Anomaly Intrusion Detection in Wireless Sensor Networks.- ASITL: Adaptive Secure Interoperation Using Trust-Level.- A RT0-Based Compliance Checker Model for Automated Trust Negotiation.- TCM-KNN Algorithm for Supervised Network Intrusion Detection.- Research on Hidden Markov Model for System Call Anomaly Detection.- Towards Identifying True Threat from Network Security Data.- Security Assessment for Application Network Services Using Fault Injection.- A Secure Data Transmission Protocol for Mobile Ad Hoc Networks.- Defending DDoS Attacks Using Hidden Markov Models and Cooperative Reinforcement Learning.- A Novel Relational Database Watermarking Algorithm.- Short Papers.- Anticipatory Event Detection for Bursty Events.- Community Detection in Scale-Free Networks Based on Hypergraph Model.- The Treelike Assembly Classifier for Pedestrian Detection.- A Proposed Data Mining Approach for Internet Auction Fraud Detection.- Trends in Computer Crime and Cybercrime Research During the Period 1974-2006: A Bibliometric Approach.- The Study of Government Website Information Disclosure in Taiwan.- Informed Recognition in Software Watermarking.- An Inference Control Algorithm for RDF(S) Repository.- PPIDS: Privacy Preserving Intrusion Detection System.- Evaluating the Disaster Defense Ability of Information Systems.- Airline Safety Evaluation Based on Fuzzy TOPSIS.- A Framework for Proving the Security of Data Transmission Protocols in Sensor Network.- Port and Address Hopping for Active Cyber-Defense.- A Hybrid Model for Worm Simulations in a Large Network.- Posters.- A Web Portal for Terrorism Activities in China.- An Overview of Telemarketing Fraud Problems and Countermeasures in Taiwan.- Mining the Core Member of Terrorist Crime Group Based on Social Network Analysis.- Providing Personalized Services for HWME System by Item-Based Collaborative Filtering.- An Intelligent Agent-Oriented System for Integrating Network Security Devices and Handling Large Amount of Security Events.- Link Analysis-Based Detection of Anomalous Communication Patterns.- Social Modeling and Reasoning for Security Informatics.- Detecting Botnets by Analyzing DNS Traffic.- HMM-Based Approach for Evaluating Risk Propagation.- A Symptom-Based Taxonomy for an Early Detection of Network Attacks.
Mark D Wood - One of the best experts on this subject based on the ideXlab platform.
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fraternity and sorority involvement Social influences and alcohol use among college students a prospective examination
Psychology of Addictive Behaviors, 2007Co-Authors: Christy Capone, Mark D Wood, Brian Borsari, Robert D LairdAbstract:This study used latent growth curve Modeling to investigate whether the effects of gender and Greek involvement on alcohol use and problems over the first 2 years of college are best characterized by selection, Socialization, or reciprocal influence processes. Three Social influences (alcohol offers, Social Modeling, and perceived norms) were examined as potential mediators of these effects. Undergraduate participants (N = 388) completed self-report measures prior to enrollment and in the spring of their freshmen and sophomore years. Male gender and involvement in the Greek system were associated with greater alcohol use and problems prior to college. Both gender and Greek involvement significantly predicted increases in alcohol use and problems over the first 2 years of college. Cross-domain analyses provided strong support for a mediational role of each of the Social influence constructs on alcohol use and problems prior to matriculation, and prematriculation Social Modeling and alcohol offers mediated relations between Greek involvement and changes in alcohol use over time. Findings suggest that students, particularly men, who affiliate with Greek organizations constitute an at-risk group prior to entering college, suggesting the need for selected interventions with this population, which should take place before or during the pledging process.
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Social influence processes and college student drinking the mediational role of alcohol outcome expectancies
Journal of Studies on Alcohol and Drugs, 2001Co-Authors: Mark D Wood, Jennifer P Read, Tibor P Palfai, John F StevensonAbstract:Objective: Social influences are among the most robust predictors of adolescent substance use and misuse. Studies with early adolescent samples have supported the need to distinguish among various types of Social influences to better delineate relations between Social factors and alcohol use and problems. Method: The first major goal of the present study (N = 399, 263 women) was to examine unique relations between particular facets of Social influence and alcohol use and problems in a relatively heavy-drinking population (i.e., college students). We hypothesized that active Social influences (offers to drink alcohol) and passive Social influences (Social Modeling and perceived norms) would demonstrate positive associations with measures of alcohol use and problems. We also tested the hypothesis that alcohol outcome expectancies would mediate associations between Social influences and drinking behaviors. Results: Structural equation Modeling analyses provided strong support for the first hypothesis. Social...