Methodological and reporting quality in laboratory studies of human eating behavior

Contains fulltext : 191329.pdf (publisher's version ) (Open Access)The methodological quality and reporting practices of laboratory studies of human eating behavior determine the validity and replicability of nutrition science. The aim of this research was to examine basic methodology and reporting practices in recent representative laboratory studies of human eating behavior. We examined laboratory studies of human eating behavior (N = 140 studies) published during 2016. Basic methodology (e.g., sample size, use of participant blinding) and reporting practices (e.g., information on participant characteristics) were assessed for each study. Some information relating to participant characteristics (e.g., age, gender) and study methodology (e.g., length of washout periods in within-subjects studies) were reported in the majority of studies. However, other aspects of study reporting, including participant eligibility criteria and how sample size was determined were frequently not reported. Studies often did not appear to standardize pre-test meal appetite or attempt to blind participants to study aims. The average sample size of studies was small (between-subjects design studies in particular) and the primary statistical analyses in a number of studies (24%) were reliant on very small sample sizes that would be likely to produce unreliable results. There are basic methodology and reporting practices in the laboratory study of human eating behavior that are sub-optimal and this is likely to be affecting the validity and replicability of research. Recommendations to address these issues are discussed.6 p

Crowdsourcing novel childhood predictors of adult obesity

Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age = 26.5±6.7; BMI = 29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children\u27s lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors. © 2014 Bevelander et al

The Impact of Social Media Influencers on Children’s Dietary Behaviors

Over the past years vlogs rapidly have become an attractive platform for food industries, sponsoring social media influencers to promote their products. As with more traditional media, social media influencers predominantly promote unhealthy drinks and foods that are high in sugar, fat, and salt – consumption of which may increase the risk of overweight, obesity, and non-communicable diseases. The aim of the current Brief Research Report is to examine the impact of vlogs on children’s unhealthy dietary behaviors. Drawing on longitudinal survey data from 453 8- to 12-year-old children, we analyzed the longitudinal relations between children’s frequency of watching vlogs and their consumption of unhealthy beverages and snacks. Structural path modeling analyses of three waves of data with 1-year intervals showed that children’s self-reported frequency of watching vlogs influenced consumption of unhealthy beverages 2 years later. The analyses did not yield significant relat

Testing a Social Network Intervention Using Vlogs to Promote Physical Activity Among Adolescents: A Randomized Controlled Trial

There is a need to stimulate physical activity among adolescents, but unfortunately, they are hard to reach with traditional mass media interventions. A promising alternative is to carry out social network interventions. In social network interventions, a small group of individuals (influence agents) is selected to promote health-related behaviors within their social network. This study investigates whether a social network intervention is more effective to promote physical activity, compared to a mass media intervention and no intervention. Ad

Mimicry of Food Intake: The Dynamic Interplay between Eating Companions

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

The role of mental models in citizen science

An increasing number of citizen science projects involve citizens on levels of participation that go beyond data collection and entail the co-creation of research questions and methods as well as the project pathway. The success of such projects depends on the establishment of shared knowledge, a task that can be especially challenging in citizen science that focuses on complex societal issues and the so-called wicked problems. We suggest that this challenge can be addressed through a deeper engagement with research on mental models—cognitive representations of external reality that largely define human thinking, decision-making and behaviour. Moreover, particular emphasis should be placed on the effective co-creation of shared mental models, whereby design thinking could provide valuable methodologies and tools. The objective of the workshop “Mental Models in Citizen Science” was to dive into mental model theory and design thinking toolbox and explore their potential for citizen science. This paper provides an overview of the workshop activities and insights and proposes a research agenda shaped around mental models and their role in citizen science

Social modeling of eating: A review of when and why social influence affects food intake and choice

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

Comments on methodological and reporting quality in laboratory studies of human eating behaviourE

In a recent research report (Robinson, Bevelander, Field, & Jones, 2018) we examined the methodological and reporting quality of laboratory-based studies of human eating behaviour. Overall, we found that both the methodological and reporting quality of studies was sub-optimal. Based on our findings, we also made recommendations about how to address these issues including the likely need for design and reporting guidelines for laboratory studies of eating behaviour. Hetherington and Rolls (2018), Buckland and Dalton (2018), Stubbs and Finlayson (2018), Best, Barsalou, and Papies (2018) and Meule (2018) expanded on our recommendations and added some of their own in response to our paper

Reprint of "Methodological and reporting quality in laboratory studies of human eating behavior" (Reprinted from Appetite, vol 125, pg 486, 2018)

The methodological quality and reporting practices of laboratory studies of human eating behavior determine the validity and replicability of nutrition science. The aim of this research was to examine basic methodology and reporting practices in recent representative laboratory studies of human eating behavior. We examined laboratory studies of human eating behavior (N = 140 studies) published during 2016. Basic methodology (e.g., sample size, use of participant blinding) and reporting practices (e.g., information on participant characteristics) were assessed for each study. Some information relating to participant characteristics (e.g., age, gender) and study methodology (e.g., length of washout periods in within-subjects studies) were reported in the majority of studies. However, other aspects of study reporting, including participant eligibility criteria and how sample size was determined were frequently not reported. Studies often did not appear to standardize pre-test meal appetite or attempt to blind participants to study aims. The average sample size of studies was small (between-subjects design studies in particular) and the primary statistical analyses in a number of studies (24%) were reliant on very small sample sizes that would be likely to produce unreliable results. There are basic methodology and reporting practices in the laboratory study of human eating behavior that are sub-optimal and this is likely to be affecting the validity and replicability of research. Recommendations to address these issues are discussed

Toward Inclusive Approaches in the Design, Development, and Implementation of eHealth in the Intellectual Disability Sector: Scoping Review

BackgroundThe use of eHealth is more challenging for people with intellectual disabilities (IDs) than for the general population because the technologies often do not fit the complex needs and living circumstances of people with IDs. A translational gap exists between the developed technology and users’ needs and capabilities. User involvement approaches have been developed to overcome this mismatch during the design, development, and implementation processes of the technology. The effectiveness and use of eHealth have received much scholarly attention, but little is known about user involvement approaches. ObjectiveIn this scoping review, we aimed to identify the inclusive approaches currently used for the design, development, and implementation of eHealth for people with IDs. We reviewed how and in what phases people with IDs and other stakeholders were included in these processes. We used 9 domains identified from the Centre for eHealth Research and Disease management road map and the Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability framework to gain insight into these processes. MethodsWe identified both scientific and gray literature through systematic searches in PubMed, Embase, PsycINFO, CINAHL, Cochrane, Web of Science, Google Scholar, and (websites of) relevant intermediate (health care) organizations. We included studies published since 1995 that showed the design, development, or implementation processes of eHealth for people with IDs. Data were analyzed along 9 domains: participatory development, iterative process, value specification, value proposition, technological development and design, organization, external context, implementation, and evaluation. ResultsThe search strategy resulted in 10,639 studies, of which 17 (0.16%) met the inclusion criteria. Various approaches were used to guide user involvement (eg, human or user-centered design and participatory development), most of which applied an iterative process mainly during technological development. The involvement of stakeholders other than end users was described in less detail. The literature focused on the application of eHealth at an individual level and did not consider the organizational context. Inclusive approaches in the design and development phases were well described; however, the implementation phase remained underexposed. ConclusionsThe participatory development, iterative process, and technological development and design domains showed inclusive approaches applied at the start of and during the development, whereas only a few approaches involved end users and iterative processes at the end of the process and during implementation. The literature focused primarily on the individual use of the technology, and the external, organizational, and financial contextual preconditions received less attention. However, members of this target group rely on their (social) environment for care and support. More attention is needed for these underrepresented domains, and key stakeholders should be included further on in the process to reduce the translational gap that exists between the developed technologies and user needs, capabilities, and context