An Ipad App to Collect Social Network Data From High-Risk Populations

Background:  Social network data provides powerful insights into the impact of social environments on the behavioral health outcomes of homeless persons.  Collecting social network data is typically very expensive and labor intensive.  Social network studies are often perceived by participants to be tiring and frustrating, as the same set of questions is repeatedly asked about each social tie the participant nominates.  Most studies looking at survey burden in the context of network data collection are not conducted with high-risk populations, who often have co-occurring substance use and physical health and mental health issues. To collect social network data quickly, cheaply, and with high participant acceptability, we developed an iPad application to collect health-related social network data from high risk populations.

Methods:  We partnered with ELC Technologies to design an iPad app for in-field use.  The construction was a collaborative, four-month process.  The app was implemented for use with data collection beginning in January 2012. 

Results: A series of screen shots depicting this technology in action are available for download at: http://www.divshare.com/download/16705788-149.  This technology allows data collection to move beyond paper-and-pencil data collection, and even computer-assisted attribute charts.  With 3G capability, it eliminates the need for internet access and promotes immediate, on-site interviewing.  The app reduces post-data entry errors, participant burnout and boredom, and interview length.  We have successfully piloted this app with three different high-risk populations:  homeless adults with co-occurring mental health and/or substance abuse problems moving into permanent supportive housing (n=52 total interviews), runaway and homeless youth ages 13-25 years (n=606 total interviews), and HIV–positive women living in HIV-related housing (n=48 total interviews).

Conclusions: This technology appeals to our target populations and has been successfully deployed in a variety of field settings.  The app allows participants  have a more active role in the data collection process.  Moreover, for more sensitive questions, participants are able to privately indicate who in their network are current/former sex partners and who they share needles with.  Other app versions are foreseen, including for use on individuals’ smartphones.  We believe that this app enables researchers to easily and accurately collect social network data in challenging field settings, including shelters, drop-in centers, housing projects, and street locations.