Objective: Social media is a potentially engaging way to support adolescents and young adults in maintaining healthy diets and learning about nutrition. This review identifies interventions that use social media to promote nutrition, examines their content and features, and evaluates the evidence for the use of such platforms among these groups. Material and methods:We conducted a systematic search of 5 databases (PubMed, CINAHL, EMBASE, PsycINFO, and ACM Digital Library) for studies that included: 1) adolescents and/or young adults (ages 10-19; ages 18-25); 2) a nutrition education or behavior change intervention component, or outcomes related to nutrition knowledge or dietary changes; and 3) a social media component that allowed users to communicate or share information with peers.Results: 16 articles were identified that included a social media component in a nutrition-related intervention for adolescents or young adults. Interventions included features in 7 categories: social media; communication; tracking health; education; tailoring; social support; and gamification. 11 out of the 16 studies had at least one significant nutrition-related clinical or behavioral outcome. Conclusion:Social media is a promising feature for nutrition interventions for adolescents and young adults. A limited number of studies were identified that included social media. A majority of the identified studies had positive outcomes. We found that most studies utilized only basic social media features, did not evaluate the efficacy of social media components, and did not differentiate between the efficacy of social media compared to other delivery mechanisms.

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PN remains a significant risk factor for CLABSIs; further work is needed to identify effective strategies to reduce rates of CLABSI among patients receiving PN.

Knowing which barriers to buying and preparing/cooking vegetables at home are linked with the home availability of vegetables and how food-security status impacts this relationship will facilitate the tailoring of future public health interventions. Baseline data were used from an elementary-school-based intervention. Data on household food-security status, availability of vegetables at home, and barriers to buying and preparing/cooking vegetables were collected from 1942 parents. Differences between food-secure and food-insecure households were examined for barriers to buying and preparing/cooking vegetables. Mixed-effects linear regression was used to estimate the associations between barriers to buying and preparing/cooking vegetables and food-security status on the home availability of vegetables. Food insecurity was reported in 27% of households. Food-insecure households were significantly more likely to report barriers to buying and preparing/cooking vegetables. The barriers to purchasing/cooking vegetables score was associated with a decrease in the home availability of vegetables score (β = −0.77; 95% CI: −0.88, −0.65; p < 0.001). Compared to food-secure households, food-insecure households were 15% less likely to have home vegetable availability (β = −1.18; 95% CI: −1.45, −0.92; p < 0.001). Although home availability of vegetables does not guarantee consumption, this study identified specific barriers that were associated with availability that can be targeted in future interventions seeking to improve vegetable consumption in the homes of low-income families.

Objectives. To elucidate details about the barriers (time, funding, staffing, and space) to integrating and sustaining school gardens. Methods. A total of 99 school gardeners from 15 states participated in an online survey in June 2017. The 29-item survey contained qualitative and quantitative items that we analyzed using descriptive statistics and inductive content analysis. Results. In order of greatest to least barrier, gardeners ranked time, staff, funding, curriculum, and space. Time for classes to use the garden (66% of respondents) and time for staff training (62%) were the most frequently listed time-related challenges. Respondents also reported low engagement within the school community. An overall lack of funding was the most common funding-related barrier, and gardeners were unaware of how to obtain more funding. Conclusions. We identified 3 aspects of school gardens as opportunities to address time- and staff-related issues: strengthening of garden committees, professional development, and community outreach. Better channels are needed to disseminate funding opportunities within schools and to communicate with communities at large. Ultimately, doing so will strengthen existing school gardens as a vehicle to promote dietary, physical, and social health within communities.

The ubiquity of internet-based nutrition information sharing indicates an opportunity to use social computing platforms to promote nutrition literacy and healthy nutritional choices. We conducted a series of experiments with unpaid volunteers using an online Nutrition Knowledge Test. The test asked participants to examine pairs of photographed meals and identify meals higher in a specific macronutrient (e.g., carbohydrate). After each answer, participants received no feedback on the accuracy of their answers, viewed proportions of peers choosing each response, received correctness feedback from an expert dietitian with or without expert-generated explanations, or received correctness feedback with crowd-generated explanations. The results showed that neither viewing peer responses nor correctness feedback alone improved learning. However, correctness feedback with explanations (i.e., modeling) led to significant learning gains, with no significant difference between explanations generated by experts or peers. This suggests the importance of explanations in social computing-based casual learning about nutrition and the potential for scaling this approach via crowdsourcing.

The use of Extended Reality (XR) (i.e. Virtual and Augmented Reality) for nutrition education and behavior change has not been comprehensively reviewed. This paper presents findings from a scoping review of current published research. Articles (n = 92) were extracted from PubMed and Scopus using a structured search strategy and selection approach. Pertinent study information was extracted using a standardized data collection form. Each article was independently reviewed and coded by two members of the research team, who then met to resolve any coding discrepancies. There is an increasing trend in publication in this area, mostly regarding Virtual Reality. Most studies used developmental testing in a lab setting, employed descriptive or observational methods, and focused on momentary behavior change like food selection rather than education. The growth and diversity of XR studies suggest the potential of this approach. There is a need and opportunity for more XR technology focused on children and other foundational theoretical determinants of behavior change to be addressed within nutrition education. Our findings suggest that XR technology is a burgeoning approach in the field of nutrition, but important gaps remain, including inadequate methodological rigor, community application, and assessment of the impact on dietary behaviors.

Childhood obesity is a complex, worldwide problem. Significant resources are invested in its prevention, and high-quality evaluations of these efforts are important. Conducting trials in school settings is complicated, making process evaluations useful for explaining results. Intervention fidelity has been demonstrated to influence outcomes, but others have suggested that other aspects of implementation, including participant responsiveness, should be examined more systematically. During Food, Health & Choices (FHC), a school-based childhood obesity prevention trial designed to test a curriculum and wellness policy taught by trained FHC instructors to fifth grade students in 20 schools during 2012–2013, we assessed relationships among facilitator behaviors (i.e., fidelity and teacher interest), participant behaviors (i.e., student satisfaction and recall), and program outcomes (i.e., energy balance-related behaviors) using hierarchical linear models, controlling for student, class, and school characteristics. We found positive relationships between student satisfaction and recall and program outcomes, but not fidelity and program outcomes. We also found relationships between teacher interest and fidelity when teachers participated in implementation. Finally, we found a significant interaction between fidelity and satisfaction on behavioral outcomes. These findings suggest that individual students in the same class responded differently to the same intervention. They also suggest the importance of teacher buy-in for successful intervention implementation. Future studies should examine how facilitator and participant behaviors together are related to both outcomes and implementation. Assessing multiple aspects of implementation using models that account for contextual influences on behavioral outcomes is an important step forward for prevention intervention process evaluations.