1. Effects of Content and Speed of Thought on Risk Taking
Sarah Hogan and Katherine Holloway
Department of Psychology
Abstract
Research shows that speed of thought alters both mood and the likelihood to engage in risk
seeking behavior. This study replicates and explores not only the effects of speed of thought,
but of content being shown as well. 28 subjects were asked to watch one of four videos. Each
either showing neutral content or illicit content and shown with either long average shot
lengths or short average shot lengths. Subjects were then asked to fill out the Domain-
Specific Risk-Taking (DOSPERT). Although there was not a significant difference in each of the
conditions, the results comparing illicit fast and illicit slow are in the predicted direction. Also,
males had a greater likelihood overall of engaging in risk seeking behavior.
Introduction
Based on previous research and the current study, Fast Thought Speed Induces Risk Taking,
Chandler and Pronin claim that the speed of thought has a greater effect on the tendency to
engage in risky behaviors than the actual content of thought. In our research, we would like
to further explore this idea by directly comparing these three variables (thought speed,
content, and gender) with respect to their effects on mood and likelihood to engage in risk
seeking behavior.
Goals of the Study
• Replicate Chandler and Pronin’s study while manipulating the variable of content, not
just speed of thought.
• Determine if content, gender, thought speed, or a combination of the three effect mood
and likelihood to engage in risk seeking behavior.
Predictions
• Content along with speed of thought will increase the likelihood to engage in a risk
seeking behavior.
• Fast thinking paired up with illicit content will lead to stronger risk taking than slow
thinking paired with illicit content.
• When shown neutral content risk seeking behavior is less likely.
Methods
Subjects
Twenty-eight undergraduates (22 female and 6 male) were recruited from sections of PSY 100.
Subjects were recruited using a convenience sampling method with flyers, a bulletin board,
and a signup sheet posted in the hallway of the psychology building on the Ohio Dominican
University campus.
Materials and Procedure
Subjects were asked to watch to one of four videos. Next, they completed the Domain-Specific
Risk-Taking (DOSPERT) survey. Results were then analyzed by researchers using independent t-
tests and a 2 Sex X 4 Condition ANOVA.
Results
Likelihood of Risk Taking
The 2 x 4 ANOVA revealed a significant main effect of sex, F(1,20)= 5.52, p<.05. Overall, males
reported a greater likelihood of engaging in risky behavior than did females, Ms = 112 and 90,
respectively.
Perceived Risk
Viewing the various films did not affect participants’ perception of risk for various behaviors.
However, the means for the Illicit-slow versus Illicit-fast conditions are in the predicted direction
(see Table below).
Perceived Benefits
Viewing the various films did not affect participants’ expectation for benefits following various risky
behaviors. However, the means for the Illicit-slow versus Illicit-fast conditions are in the predicted
direction (see Table below).
Table 1. Average DOSPERT scores as a function of viewing condition (SD’s in parentheses)
Discussion
Subjects were asked to rate situations on the likelihood of engaging, the perceived risk, and the
perceived benefit. Major findings have proven that males have a higher likelihood of engaging in
engaging in risk seeking behavior. Results for perceived risk and perceived benefits of each
situation were in the predicted direction when comparing illicit slow versus illicit fast. This
suggests that content may play a role in all three domains. Results also showed that the
likelihood of engaging in risky behavior lowers as the perceived risk raises. The likelihood of
engaging in risky behavior also raises as the perceived benefit of the behavior raises. There was
also a correlation found between the perceived risk of behavior and the perceived benefit of the
behavior. As the perceived risk raises, the perceived benefit decreases.
Limitations
• More participants may have caused more significance when comparing the different
domains.
• Subjects were homogenous: males (n=6), females (n=22)
Conclusions
The hypothesis of this study was that both speed of thought and content alter the likelihood that
a person will engage in a risky behavior. It also predicted that both the perception of the risk and
the benefit of the risk are also altered. Subjects viewed one of four videos and were asked to fill
out the DOSPERT. Which provided them with thirty situations. The situations each were rated on
likelihood of participating, perceived risk, and perceived benefits. The major results suggested
that both speed of thought and the viewing content altered these domains. Results also proved
that males are more likely to engage in risky behavior than females.
Future Studies
•More participants
•Equality among the sex of the participants
References
Blais, A., & Weber, E. (2006). A domain-specific risk-taking (dospert) scale for adult populations. Judgment
and decision making, 1(1), 33-47.
Bushman, B. J., & Anderson, C. A. (2009). Comfortably numb: Desensitizing effects of violent media on
helping others. Association for psychological sciences, 20(3), 273-277.
Chandler, J.J., & Pronin, E. (2012). Fast thought speed induces risk taking. Psychological science, 23, 370-
374.
Chong, Y., Teng, K., Siew, S., & Skoric, M. (2012). Cultivation effects of video games: A longer-term
experimental test of first- and second-order effects. Journal of social and clinical psychology, 31(9),
952-971.
Harris, C., Jenkins, M., & Glaser, D. (2006). Gender differences in risk assessment: Why do women take
fewer risks than men?. Judgment and Decision Making, 1(1), 48-63.
Pronin, E., & Jacobs, E. (2008). Thought speed, mood, and the experience of mental motion. Perspectives on
psychological science, 3(6), 461-485.
Pronin, E., & Wegner, D. (2006). Manic thinking: Independent effects of thought speed and thought content
on mood. Association for psychological sciences, 17(9), 807-813.
Szrek, H., Chao, L., Ramlagan, S., & Peltzer, K. (2012). Predicting (un)healthy behavior: A comparison of risk-
taking propensity measures. Judgment and decision making, 7(6), 716-727.
Poster presented at the 3rd Annual Ohio Dominican University Research Symposium, April 26, 2013
Neutral Content
Slow ASL
Neutral Content
Fast ASL
Illicit Content
Slow ASL
Illicit Content
Fast ASL
Average Shot Length:
20 Seconds
Average Shot Length:
5 Seconds
Average Shot Length:
20 Seconds
Average Shot Length:
5 Seconds
Y
Content Speed Risk Taking Likelihood Perceived Risk Perceived Benefit
Neutral Slow 100.17 (13.00) 142.50 (22.12) 93.50 (20.80)
Fast 88.25 (18.25) 143.00 (3.40) 79.13 (11.05)
Illicit Slow 92.50 (30.70) 150.00 (26.00) 87.50 (23.23)
Fast 99.38 (17.52) 143.00 (19.75) 99.13 (21.56)
Perceived Risk Of
Behavior
Perceived Benefit
of Behavior
Likelihood of Engaging in Risky Behavior -.43* .48*
Perceived Risk of Behavior -- -.42*
Scale Intercorrelations
• A negative correlation was found between the likelihood of engaging in risk seeking behavior
and the perceived risk of the behavior.
• A positive correlation was found between the likelihood of engaging in risk and the
perceived benefit of the risk.
• A negative correlation was found between the perceived risk of a behavior and the
perceived benefits of the behavior.
*p < .05.