Poster presentation: Neighborhoods and health

Neighborhoods and health: Development and validation of an experimental manipulation of neighborhood characteristics in a virtual reality environment. Presented at the 75th Annual Scientific Meeting at Sevilla, Spain, March 15-18, 2017. This represents a collaboration between ETH Zurich, the University of South California, and the University of Wisconsin-Madison.  

by Anita Schärer-Geser
Affluent
Affluent
Disadvantaged
Disadvantaged

DownloadPoster (PDF, 399 KB)


Daniel A. Hackman, Ph.D., USC Suzanne Dworak-Peck School of
Social Work, University of Southern California, Los Angeles, CA,
Stephanie A. Robert, Ph.D., School of Social Work, University of
Wisconsin-Madison, Madison, WI, Jascha Grübel, MSc, Raphael
Weibel, B.Sc., Christoph Hölscher, Ph.D., Victor R. Schinazi, Ph.D.,
Chair of Cognitive Science, ETH Zurich, Zurich, Zurich, Switzerland

Background: Neighborhood disadvantage is an independent
predictor of health that is thought to operate, in part, through acute
impacts on emotion and stress reactivity. Nevertheless, no studies
have measured the acute effect of neighborhood contexts on emotion
and stress reactivity. To address these issues, we used virtual reality
(VR) to develop an experimental model of neighborhood
disadvantage and affluence. This study (1) assesses the validity of
the VR neighborhoods by examining participant observations and (2)
tests the hypothesis that neighborhood disadvantage elicits greater
stress reactivity and emotion.

Methods: In a preliminary analysis of an ongoing study, 26
participants were randomly assigned to complete a simple navigation
task in the virtual affluent (VR-A) (n = 11) or disadvantaged (VR-D)
(n = 15) neighborhood. Participants were young adults (M = 22.8
years, SD = 3.1), 53.8% female, and undergraduate or graduate
(88.5%) students. Participants completed a systematic social
observation of the virtual neighborhood, and ratings of emotion and
arousal, after the task. Blood pressure (BP) was measured three
times during a baseline condition and at 3-minute intervals during
the task.

Results: The VR-D condition was rated as lower in a measure of
overall socioeconomic position (t = 10.2, p < .001). It was also rated
as less safe to live in, less desirable, in worse condition, and having
more garbage and fewer trees (all p < .001). The VR-D condition
also elicited more negative affect (t = 2.5, p = .02) but not arousal (t
= -.48, p = .64), and higher ratings of anger, disgust, and sadness (all
p ≤ .02). Systolic and diastolic BP were significantly higher than
baseline across both VR conditions (all p < .001). No significant
differences in BP were found in preliminary analyses between VR-D
and VR-A (all p > .55).

Conclusions: The validity of the VR-based models was supported
by participants’ differentiated perception of the neighborhood
environments. In addition, the disadvantaged condition elicited
more negative affect, consistent with hypotheses. Physiological and
psychological responses to the virtual environments indicate the
feasibility and utility of this approach for studying acute effects of
neighborhood conditions on stress reactivity and other pathways to
health. The final presentation will include complete data from this
ongoing study.

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