We propose a solution for discovering at-risk veterans using online network surveys. Our approach combines 1) Facebook ad targeting for efficient recruitment of veterans and friends of veterans with 2) a survey that asks about veteran friends and acquaintances we can analyze using a network "scale-up" methodology. We accessed 400 respondents in 4 hours using only $240 (60 cents per respondent) and found preliminary evidence for self-reporting bias for PTSD.

1. Learning About At-Risk
Veterans Using
Online Network Surveys
#TeamFacebook
Carlos Greg Diuk
Akos Lada
Alex Peysakhovich
Sean J. Taylor

2. How can we identify more at-risk
veterans to gather more survey
data or connect them to help?

3. Problem 1:
At-risk veterans might not
survey answer truthfully.

4. Problem 2:
How can we find them to
survey them in the first place?

5. Combine:
1. targeted recruitment
2. online surveys
3. network survey methods
Key Idea

6. Facebook Ads Targeting
Target using FB ads both
generally and using
criteria:
• location = near the 5
largest military bases
• job = employed by the
US Army
• interest = US Army

7. 400 responses
in 4 hours
for $240
(all today)

8. Survey Methodology:
“Network Scale-Up Method”
• Ask about self:
“have you had symptoms of depression?”
• Ask about friends:
“think of a person who you know that has served in
the US Armed Forces” and then
“has this person had symptoms of depression?”

10. Age

11. Possible Biases Uncovered:
Friends vs Self Reports

12. Extensions
• This modern approach improves our ability to
survey hidden populations.
• Accessing hidden populations could allow for
interventions!
• Survey continuously for longitudinal measurements,
detect trends and effects of policy changes.

13. Appendix

14. MTurk vs. Facebook

15. Results:
Age
Distribution

16. Gender

17. Two Types of Recruitment
• Create Facebook page + target using Facebook
ads
• Use crowdsourcing (Amazon Mechanical Turk)