This study investigated how framing threatening information influences subsequent threat perception of faces. Participants viewed either a neutral video, a negatively framed video about the Boston Marathon bombings, or a positively framed video. They then completed a face perception task where they judged faces as threatening or non-threatening. The researchers predicted lower sensitivity but higher bias towards threat for those who viewed threatening videos, especially with negative framing. Preliminary results found lower sensitivity for threat detection in the threat video conditions compared to control, and an even lower sensitivity with positive rather than negative framing. Contrary to predictions, bias was less conservative in the positive framing condition only in the baseline scenario. The study suggests framing of mass violence events can impact unrelated threat perception

1. Wormwood, J. B., Lynn, S. K., Barrett, L. F., & Quigley, K. S. (2015). Threat perception after the Boston Marathon bombings: The
effects of personal relevance and conceptual framing. Cognition and Emotion, 30(3), 539-549.
• In partial support of our predictions, we found that sensitivity was indeed lower in
the two threat conditions compared to the control condition. However, contrary to
predictions, this effect was most pronounced among participants in the positively-
framed threat condition and was present only in the low threat scenario.
• Contrary to predictions, we did not find that bias was more liberal in the negatively-
framed threat condition compared to the other two conditions. Instead we found
that bias was less conservative (more liberal) among participants in the positively-
framed threat condition compared to the other two conditions, but only in the
baseline scenario.
• These findings suggest that the impact of threat information, and the affective
framing of that information, differs for threat perception in person perception and
threat perception in a shooting task.
• Our findings suggest that how people think about mass violence events can impact
their perception of threat in scenarios that are unrelated to the original event. The
media plays an important role in how society thinks about mass violence events, so
if the media frames these events in a certain light, it can cause people to have
misconceptions regarding threat even in seemingly mundane everyday situations,
like judging whether or not you can trust someone you just met.
• For future research, it would be interesting to investigate the relationship between
these findings and the amount of exposure each participant had to the Boston
Marathon bombings. It might be that people who were more exposed to the
bombings have even lower threat sensitivity and an even more liberal bias than
those with less exposure to the event.
In this study, we investigated whether the framing of threatening information influenced how participants
make decisions about if a face is threatening during a face perception task. Participants were first shown either
a neutral video, a “negative” threat video which contained photos of the Boston Marathon bombings with
negative news headlines (e.g., “Terror strikes Boston”) or a “positive” threat video which contained the same
images but with optimistic news headlines (e.g., “Boston Strong”). Following the video, participants completed
a face perception task in which they were shown a single face and then asked if the face was threatening or
not. As the task continued, the proportion of threatening versus non-threatening faces that participants were
shown decreased. We predict that participants in the negatively-framed threat condition will have the greatest
bias towards finding the faces threatening, while the positively-framed threat condition will have only a slight
bias towards finding the faces threatening, and the neutral condition will have no bias. We predict that
sensitivity (or a person’s ability to distinguish between threatening and non-threatening faces) will be lower in
the neutral condition compared to both the positively- and negatively-framed threat conditions. That is, we
predicted that participants who saw videos related to the bombings would be more sensitive to threats.
Preliminary results partially confirm our hypotheses. Our study suggests that how the media frames mass
violence events, like the Boston Marathon bombings, can influence how people perceive threat in faces.
Undergraduate
Category: Social Sciences, Business, and Law
Degree Level: Bachelor of Science in Psychology
Abstract ID# 1205
Abstract
Introduction
Methods Results
Conclusion
References
Acknowledgements
This research was supported by a grant from the National Science Foundation, BCS-1422327.
Face This: The Effect of Framing Information on Threat Perception of Faces
Dan McDonald, Sara Petro, Samantha DiChiara, Jolie Wormwood, Julia Senft, Spencer Lynn, Lisa Barrett, Karen Quigley
• Previous research has shown that whether threat-relevant information
is framed in a positive or negative way can influence how exposure to
that threat information influences subsequent threat perception
performance (Wormwood et al., 2015).
• For example, Wormwood and colleagues (2015) paired images of the
Boston Marathon bombings with more positive (e.g., “Boston Strong”)
or more negative (e.g., “Terror Strikes Boston”) new headlines to
examine whether these different framings of the same threat would
impact behavior in a subsequent shooting task. Findings revealed that
exposure to threat information decreased threat sensitivity (i.e.,
participants ability to distinguish armed from unarmed targets), but
only in the negatively-framed threat condition. They did not find any
influence of the different framings on threat bias (i.e., the tendency to
favor the “shoot” response).
• However, this previous research focused on shooting behavior and so
whether or how the framing of threat information will influence more
basic threat perception processes, like person perception, is not yet
understood.
• In the present study, we examine how negatively or positively framing
threat information impacts an individual’s ability to perceive faces as
threatening or not.
• Similar to Wormwood et al. (2015), we predict that there will be lower
sensitivity for detecting threat for individuals exposed to threat
information, but particularly for participants who are in the negatively-
framed threat condition.
• In addition, although Wormwood et al. (2015) found no effect of the
framings on threat perception bias, we predict that we will see
differences in bias in the present study because there are less severe
implications for judging faces compared to shooting someone.
Specifically, we predict that participants in the negatively-framed
threat condition will have the greatest bias towards finding the faces
threatening, followed by those in the positively-framed threat
condition, and then those in the control condition.
Threat Induction Conditions:
Participants (N=183) from the Boston community were randomly
assigned to watch 1 of 3 induction videos:
• “Negative” Threat Video: Photos of the Boston Marathon
bombings accompanied by negative news headlines (e.g.,
“Terror Strikes Boston”) and music designed to elicit negative
affect (See Fig 1).
• “Positive” Threat Video: Photos of the Boston Marathon
bombings accompanied by optimistic news headlines (e.g.,
“Boston Strong”) and music designed to elicit more positive
affect (See Fig 2).
• Control Video: Photos containing neutral content from the
International Affective Picture System accompanied by music
designed to not have any impact on emotions.
Face Perception Task:
• On each trial, participants viewed a face for 500 ms, and
indicated whether it was threatening or not.
• Faces were CGI-generated and ranged from having more non-
threatening physiognomy (i.e., baby-face features) to more
threatening physiognomy (i.e., strong jaw/brow). See Fig 3.
• Participants earned points for correctly detecting whether or
not each face was threatening and lost points for incorrect
decisions. Participants were instructed to try to maximize
points earned.
• In the first half of the task, the baseline scenario, participants
judged 200 faces (50% threatening/50% non-threatening).
• In the second half of the task, the low threat scenario, the
number of threatening faces was reduced: participants judged
200 more faces (25% threatening/75% non-threatening).
Figure 3: Sample Faces Ranging in Physiognomy
Data were analyzed in 2X3 repeated-measures ANOVAs with threat induction
condition as a between-subjects variable and face perception scenario as a within-
subjects variable.
1.2
1.25
1.3
1.35
1.4
1.45
1.5
1.55
1.6
1.65
1.7
Control
Video
Negative
Threat Video
Positive
Threat Video
Sensitivity
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Control
Video
Negative
Threat Video
Positive
Threat Video
Bias
Figure 1 Figure 2
Baseline Scenario Low Threat Scenario
References and Funding