Social robots are becoming increasingly influential in shaping the behavior of humans with whom they interact. Here, we examine how the actions of a social robot can influence human-to-human communication, and not just robot–human communication, using groups of three humans and one robot playing 30 rounds of a collaborative game (n= 51 groups). We find that people in groups with a robot making vulnerable statements converse substantially more with each other, distribute their conversation somewhat more equally, and perceive their groups more positively compared to control groups with a robot that either makes neutral statements or no statements at the end of each round. Shifts in robot speech have the power not only to affect how people interact with robots, but also how people interact with each other, offering the prospect for modifying social interactions via the introduction of artificial agents into hybrid systems of humans and machines.

Household consumption and expenditure surveys are frequently conducted around the world and they usually include data on household food consumption, but their applicability to nutrition research is limited by their collection at the household level. Using data from Mongolia, this study evaluated four approaches for estimating diet from household surveys: direct inference from per-capita household consumption; disaggregation of household consumption using a statistical method and the “adult male equivalent” method, and direct prediction of dietary intake. Per-capita household consumption overestimated dietary energy in single- and multi-person households by factors of 2.63 and 1.89, respectively. Performance of disaggregation methods was variable across two household surveys analyzed, while the statistical method exhibited less bias in estimating intake densities (per 100 kcal) of most dietary components in both of the surveys. Increasingly complex prediction models explained 54% to 72% of in-sample variation in dietary energy, with consistent benefits incurred by inclusion of basic dietary measurements. In conclusion, in Mongolia and elsewhere, differences in how household and dietary measurements are recorded make their comparison challenging. Validity of disaggregation methods depends on household survey characteristics and the dietary components that are considered. Relatively precise prediction models of dietary intake can be achieved by integrating basic dietary assessment into household surveys.

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This study assessed awareness and attitudes regarding industrial food fortification among adults in urban and rural Mongolia, and the city of Harbin, China. Between 2014 and 2017, surveys were collected from healthy men and women aged ≥18 years (182 Harbin residents and 129 urban and rural Mongolians participating in a nationwide nutrition survey in Mongolia). Survey reproducibility was assessed among 69 Mongolian participants to whom it was administered twice (summer and winter). Findings revealed that only 19% of rural and 30% of urban Mongolians, and 48% of Harbin residents were aware that industrial fortification is practiced in their countries. For most food groups evaluated, at least half of Mongolians and less than half of Harbin residents thought fortification was government-mandated (only the addition of iodine with salt is actually mandated in both countries). Fifty-five percent of rural and urban Mongolians favored mandatory fortification of foods, 14% disapproved of it, and 31% were uncertain (compared with 25%, 38%, and 37% respectively in Harbin). Upon learning that the primary purpose of adding vitamin D to milk is to prevent rickets, 75% of Mongolians but only 18% of Harbin residents favored mandatory fortification, while 42% of Harbin residents favored voluntary fortification (compared with <10% of Mongolians). In conclusion, in Mongolia and Harbin, awareness and understanding of food fortification is low, as is receptivity toward mandatory fortification. Health promotion and social marketing should be designed to create an enabling environment for increasing supply and demand of fortified foods, in support of upcoming program implementation in Mongolia and potential future legislation in northeern China.

We investigated the household-level social network correlates of acceptance of intimate partner violence (IPV) in rural, agrarian settings of Honduras and Uganda, two low-income countries with unequal access to resources based upon gender. We collected complete social network data in each location (Honduras in 2014 and Uganda in 2012), across a diverse range of relationships, and then created a measure of household cohesion by calculating the degree to which members of a household nominated each other as important social connections. Our measure of IPV acceptance was based on 4 questions from the Demographic Health Survey to assess the conditions under which a person believes that it is acceptable for a man to perpetrate physical violence against his wife or partner and we coded a person as positive on IPV acceptance if they answered positively to any of the four questions. We used logistic regression to calculate the odds that an individual accepted IPV given (1) household level cohesion and (2) the proportion of the household that accepts IPV. We found individuals from more cohesive households were less likely to accept IPV controlling for the overall level of IPV acceptance in the household. Nevertheless, those in households more accepting of IPV were more likely to personally accept IPV. In stratified analyses, when household IPV acceptance was especially high, the benefit of household cohesion with respect to IPV was attenuated. The design and implementation of interventions to prevent IPV should consider household structure and norms rather than focusing only on individuals or couples.