Neighborhood Disadvantage and Birth Weight: The Role of Perceived Danger and Substance Abuse

In this analysis we connect structural neighborhood conditions to birth outcomes through their intermediate effects on mothers’ perceptions of neighborhood danger and their tendency to abuse substances during pregnancy. We hypothesize that neighborhood poverty and racial/ethnic concentration combine to produce environments that mothers perceive as unsafe, thereby increasing the likelihood of negative coping behaviors (substance abuse). We expect these behaviors, in turn, to produce lower birth weights. Using data from the Fragile Families and Child Wellbeing Study, a survey of a cohort mothers and children born between 1998 and 2000 in large cities in the United States, we find little evidence to suggest that neighborhood circumstances have strong, direct effects on birth weight. Living in a neighborhood with more foreigners had a positive effect on birth weight. To the extent that neighborhood conditions influence birth weight, the effect mainly occurs through an association with perceived neighborhood danger and subsequent negative coping behaviors. Poverty and racial/ethnic concentration increase a mother’s sense that her neighborhood is unsafe. The perception of an unsafe neighborhood, in turn, associates with a greater likelihood of smoking cigarettes and using illegal drugs, and these behaviors have strong and significant effects in reducing birth weight. However, demographic characteristics, rather than perceived danger or substance abuse, mediate the influence of neighborhood characteristics on birth weight.

Impact Study of Nonverbal Facial Cues on Spontaneous Chatting with Virtual Humans

Non-verbal communication (NVC) is considered to represent more than 90 percent of everyday communication. In virtual world, this important aspect of interaction between virtual humans (VH) is strongly neglected. This paper presents a user-test study to demonstrate the impact of automatically generated graphics-based NVC expression on the dialog quality: first, we wanted to compare impassive and emotion facial expression simulation for impact on the chatting. Second, we wanted to see whether people like chatting within a 3D graphical environment. Our model only proposes facial expressions and head movements induced from spontaneous chatting between VHs. Only subtle facial expressions are being used as nonverbal cues - i.e. related to the emotional model. Motion capture animations related to hand gestures, such as cleaning glasses, were randomly used to make the virtual human lively. After briefly introducing the technical architecture of the 3D-chatting system, we focus on two aspects of chatting through VHs. First, what is the influence of facial expressions that are induced from text dialog? For this purpose, we exploited an emotion engine extracting an emotional content from a text and depicting it into a virtual character developed previously [GAS11]. Second, as our goal was not addressing automatic generation of text, we compared the impact of nonverbal cues in conversation with a chatbot or with a human operator with a wizard of oz approach. Among main results, the within group study -involving 40 subjects- suggests that subtle facial expressions impact significantly not only on the quality of experience but also on dialog understanding.