1. Alan Nochenson
IST 597J Method Implementation
10/24/2012

2.  Is it possible to prime participants so that
they ask in a less risky way in security user
studies?

3.  Pennstate.qualtrics.com
 Let me randomize viewing order and other
advanced options
 Timing
 Browser statistics
 Number of clicks

6.  Based on Meertens and Lion (2008)
 Had to reverse-score the appropriate questions
(typo in original paper)
 Then, add up the answers to get a score (higher is
more risk-seeking)
 Change to percentage

7.  H1: The order in which the warning message
is displayed has an impact on risk propensity
 H2: Demographic factors have an impact on
risk propensity
 H3: Demographic factors have an impact on
knowledge about phishing

8.  Remove unused variables
 Timing
 Browser information
 Change variables to usable categorical forms
 Change to binary yes/no
▪ Phishing question correct?
▪ Country of origin is US?
 Change to low/high around median
▪ Education, Income, RPS, Age

9.  Order does not have an effect
Median: 40%
Mean: 43%

10.  Gender almost has an effect (males higher)

11.  Country of origin has no effect
U.S. – 14
India – 5
China – 3
Other – 1 (Israel)

12.  Income almost has an effect
Median: $80-90k
Mode: Over $100k (9 of 23)

13.  Education has no effect
Median: completed 4 year degree
Mode: same (11 of 23)

14.  Gender has a weak effect

15.  Recruitment is difficult
 Difficult to see effects with small n
 Important to use not only crosstabs
 Important to go in with specific
hypothesis, otherwise too many options

17.  Meertens, R. M. and R. Lion. 2008.
“Measuring and Individual’s Tendency to Take
Risks: the Risk Propensity Scale” Journal of
Applied Social Psychology. 38(6): 1506-1520.

18. 