My research on neighborhoods and health investigates the effect of neighborhood condition (i.e., disadvantage versus affluence) on behavior, emotion and physiological reactivity. In collaboration with Professor Daniel Hackman at the University of South California (USC), we developed a virtual reality experimental model of neighborhood disadvantage and affluence to examine the effects of exposure on stress reactivity and emotion. Specifically, participants in the study navigated one of two neighborhoods that differed in terms of social and physical characteristics (e.g., garbage, graffiti, condition of the buildings and sidewalks, types of shops) while we measured changes in blood pressure, electrodermal activity and heart rate. Participants were also asked to appraise the experienced neighborhood by completing a systematic social observation (Odgers et al., 2009) and questionnaires on emotion. This experiment was implemented using EVE and has now been accepted in Nature Scientific reports.

Currently, we are developing a follow up study in which we investigate the effect of specific neighborhood characteristics (i.e., nature, deterioration and disorder, and the presence of community members) on physiological stress response. Here, we developed a “pixel count” technique in which we replayed each participants trajectories through the virtual neighborhoods and quantified (per minute) the percentage of the virtual scene that was composed of pixels from nature, deterioration / disorder and avatars. This work will be presented at the next Interdisciplinary Association for Population Health Science (IAPHS) conference. This project is only a reality because of the superhuman efforts from my colleagues Raphael Weibel, Jascha Grübel and Eirini Anagnostou.

The “pixel extraction” algorithm for the trajectory of a participant in the disadvantaged route. The algorithm calculates the percentage of visible pixels for nature (green), deterioration (red) and avatar (blue) for every navigation minute.