1) The study investigated how the context of faces presented alongside a target face can influence perceptions of threat posed by the target face.
2) Participants completed a task in two runs where they judged faces on a spectrum from non-threatening to threatening. In run 1, the target face was paired with a young face, while in run 2 it was paired with an older face.
3) Results showed the target face was perceived as more threatening in run 1 when paired with the young face, compared to run 2 when it was paired with the older face. This demonstrates that threat judgments can be context-sensitive based on the other faces in the evaluation set.
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
A Structural Equation Modeling among Stress, Fear of Negative Evaluation and ...inventionjournals
The objective of this study is to examine the relations of the stress, fear of negative evaluation, avoidant decision making and dependent decision making among a group of university students that have moderate economic status. The study group consists of 330 participants who are students of public university. Our study was based on voluntary participation. 56% of participants were female and 44% participants were male. We used Structural Equation Modeling for the data analysis. The results were X2 /df=1.564; GFI=0.88; CFI=0.94; RMSEA=0.04; SRMR=0.05. The goodness of fit provided evidence that the hypothesized model was stable. All estimated path coefficients were significant. We found that the avoidant decision making and the dependent decision making have a positive impact on the fear of negative evaluation and the fear of negative evaluation has positive impact on the stress. The avoidant decision making style and the dependent decision making style explained %10 of the variation in the fear of negative evaluation. All these tree variables explained %20 of the variation in the stress. The fear of negative evaluation plays a mediating role for avoidant decision making style and the dependent decision making style on the stress.
Research ArticleDomain Specificity inExperimental Measur.docxrgladys1
Research Article
Domain Specificity in
Experimental Measures and
Participant Recruitment
An Application to Risk-Taking Behavior
Yaniv Hanoch,1,2 Joseph G. Johnson,3 and Andreas Wilke4
1
UCLA School of Public Health;
2
Max Planck Institute for Human Development, Berlin, Germany;
3
Miami University;
and
4
International Max Planck Research School LIFE, Max Planck Institute for Human Development, Berlin, Germany
ABSTRACT—We challenge the prevailing notion that risk
taking is a stable trait, such that individuals show con-
sistent risk-taking/aversive behavior across domains. We
subscribe to an alternative approach that appreciates the
domain-specific nature of risk taking. More important, we
recognize heterogeneity of risk profiles among experi-
mental samples and introduce a new methodology that
takes this heterogeneity into account. Rather than using
a convenient subject pool (i.e., university students), as is
typically done, we specifically targeted relevant subsam-
ples to provide further validation of the domain-specific
nature of risk taking. Our research shows that individuals
who exhibit high levels of risk-taking behavior in one
content area (e.g., bungee jumpers taking recreational
risks) can exhibit moderate levels in other risky domains
(e.g., financial). Furthermore, our results indicate that
risk taking among targeted subsamples can be explained
within a cost-benefit framework and is largely mediated by
the perceived benefit of the activity, and to a lesser extent
by the perceived risk.
How should researchers study a psychological construct such as
risk-taking propensity? Answering this question might not be as
easy as it seems at first glance. First, an individual might exhibit
risk-taking tendencies in one domain (e.g., financial) but display
more conservative behavior in another (e.g., recreational).
Second, different methodological designs—for example, the
pool of subjects used or the type of analysis conducted—can
yield contradicting results (e.g., Huber, Wider, & Huber, 1997).
In the present study, our methodological focus on the ecological
validity of the experimental design (e.g., Huber, 1997), domain-
specific risk-taking measures, and recruitment of participants in
targeted groups yielded results that allow us to challenge the
tendency to cluster individuals globally as either risk takers or
risk avoiders—thus offering a richer perspective on the psy-
chology of risk taking.
The psychological literature has been largely dominated by
the assumption that risk taking is a stable personality trait, and
thus individuals can be clustered into groups having risk-taking
or risk-aversive styles (e.g., Eysenck & Eysenck, 1977; Lejuez
et al., 2002; for a review, see Bromiley & Curley, 1992). This
simplistic, though appealing, conceptualization has proven to be
inadequate. Researchers have responded by examining sub-
traits and, therefore, the relation between risk taking and con-
struc.
1
AFFECTIVE FORECASTING
AFFECTIVE FORECASTING
Isaac Estrada
Florida International University
AFFECTIVE FORECASTING
Affective Forecasting is also known as hedonic forecasting, which refers to “implicit or explicit forecasts of utility that will be experienced at a later time” (Polyportis, Kokkinaki, Horváth, & Christopoulos, 2020), in this context, ‘utility’ refers to “the quality and intensity of the hedonic experience associated with [an] outcome” (Kahneman & Snell, 1992, p. 188). In other words, it refers to the prediction of emotions and feelings in the future, regarding an specific situation. Human beings tend to forecasting how they are going to feel about situations we consider are important, this is done unconsciously in the daily life. Following this definition Wilson and Gilbert identified four specific components of emotional experience that one may make predictions of Valence (whether the emotions will be positive or negative), specific emotions experience, intensity of the emotions, and duration of the emotions. For example, a college student is about to take a final exam, and he start getting his hands sweaty, and he start feeling nervous. He is predicting to feel fearful to fail the exam.
Affective Forecasting plays an important role in the daily life because it drives decision and behaviors (Dunn and Laham Affective forecasting: a user’s guide to emotional time travel, Psychology Press, London, 2006). Every decision requires a prediction (Barry Schwartz and R. Sommers, 2013). If we think about how we are going to feel about an event, we are going to make decisions to try to obtain desired outcomes, or to change our behavior towards the situation. For example, a woman makes an appointment to see the doctor because she is not feeling good, however, she is afraid of getting examined, so she decides to cancel her doctor appointment, as a result of this bad decision she starts feeling worse. Most of the times we engage in Affective Forecasting we predict wrongly, and we make mistakes.
Researchers suggest that when predicting our future emotions, affecting forecasting error are frequent (Wilson and Gilbert in Adv Exp Soc Psychol 35:345-411,2003). There are several reasons why we may find ourselves making seemingly basic errors when it comes to affective forecasting (Wilson & Gilbert, 2003). For better understanding here an example, a person heads to work and it seems that the day is going to be smooth, not busy, but it ends up being stressful, and very tiring day. The Target of error and Nature of bias are valence, specific emotions, intensity, and duration. In the study we are going to conduct, we can also see how participants report their feelings before the study, expecting good results about their participation in the study, and their target error, after completing the anagrams exercise.
Now that Affective Forecasting was exposed and explained, I am going to present details about the study. Solving ana ...
Vlastos, D., Kyritsis, M., Papaioannou-Spiroulia, A., & Varela V.-A. (2017). ...Dimitris Vlastos
Oral Presentation, 22nd International Conference of the Association of Psychology & Psychiatry for Adults & Children (A.P.P.A.C.): Recent Advances in Neuropsychiatric, Psychological and Social Sciences in Psychological Research, 16th – 19th May 2017, Athens, Greece.
Coping with Teasing and Name-Calling Scale for Children............................................................................................. 1
Ümit Sahranç
Assessment for Learning: How Plagiarism can be used as an Efficient Learning Tool............................................... 17
Lucía Morales and Amparo Soler-Domínguez
The use of Technology to Support the Innovative Teaching of Mathematics to Students with SEBD: A Debate
Related to the use of Technology in the Classroom to Promote Inclusion.................................................................... 35
Jonathan Camenzuli
An Effective Approach for Teaching Database ................................................................................................................ 53
K. S. Sastry, Musti
Circuit Analysis Tools: Integrating Smartphone and Tablet Applications and Simulation Software into Circuit
Analysis Instruction and Laboratories ............................................................................................................................... 64
John Ulrich, Charles Feldhaus, Elaine Cooney and David Nickolich
Efficacy of Cognitive Instruction in Teaching Deictic Motion Verbs in EFL Classrooms .......................................... 84
Hu, Ying-hsueh
Teaching in Interactive Pedagogical Perspective at Primary Schools in Northern Mountainous Provinces of
Vietnam ............................................................................................................................................................................... 105
Associate Prof. Dr. Duc-Hoa Pho
Discussion Forums in MOOCs.......................................................................................................................................... 119
Afsaneh Sharif and Barry Magrill
An Empirical Research on the Use of Mobile Phones to Support Students’ Mathematics Learning ...................... 133
Nguyen Danh Nam and Trinh Thi Phuong Thao
As the importance of promoting college student mental health increases and campuses work to prevent suicide, resident assistants (RAs) are called upon to serve as gatekeepers to facilitate professional help as a part of suicide prevention initiatives on campuses. However, assessing the efficacy of suicide prevention training is lacking. This study develops and validates the Gatekeepers Self-Efficacy Scale among resident assistants (RAs) based on the Question, Persuade, Response suicide prevention model. Exploratory Factor Analysis (EFA), Parallel Analysis, and Multidimensional Graded Response model (MGRM) were used with 302 RAs sample. Two factors were found, (1) Communicating about Crisis and (2) Knowledge of Resources, with appropriate item fit and parameter estimates. The response patterns of the two factors and their correlations with objective suicide prevention knowledge were estimated and discussed. The implications of these findings for practical application are discussed, along with suggestions for future studies.
Running head COLOR PRIMING AND FOREWARNING 1 .docxtodd271
Running head: COLOR PRIMING AND FOREWARNING 1
The Influence of Color Priming and Forewarning on Anagram Performance
A. Student
Florida International University
COLOR PRIMING AND FOREWARNING 2
Abstract
Methods One Students: Typically, authors add their abstract for the paper here on the second
page. As you can see, the abstract for this paper is missing. Your job is to supply that abstract!
Read over the following paper, which is an actual paper turned in by a former student taking
Research Methods and Design II at FIU. This is similar to a paper you will write next semester.
Review the studies in this paper, and spot the hypotheses, independent and dependent variables,
participants, results, and implications, and write it up in one paragraph (no more than 200 words
maximum). Make sure to include keywords as well (keywords are words or short phrases that
researchers use when searching through online databases like PsycInfo – they need to be
descriptive of the paper, so come up with three or four that seem to suit this paper). Good luck!
Keywords: Methods II Paper, Abstract Assignment, Methods II Preview
COLOR PRIMING AND FOREWARNING 3
The Influence of Color Priming and Forewarning on Anagram Performance
Colors are an essential part of life, from warning us of poisonous creatures to describing
our emotions, they have proven their worth. Certain colors can be perceived in specific situations
or attributed to a particular emotion. For instance, priming of sadness can lead to perception of
the color blue, whereas priming of anger can lead to perception of the color red (Fetterman,
Robinson, Gordon, & Elliot, 2011). The central aim of our study is to explore the effect priming
with a specific color has on anagram performance.
Priming is defined as the unconscious influence that a stimulus has on the agility or
accuracy in performing a task (Schacter & Rajendra, 2001). According to Jefferis and Fazio
(2008), priming impacts behaviors by informing the person if they have met the demands of the
situation. The influence priming has on behavior is shaped by what one perceives in a particular
situation. For example, priming the color red in the context of romantic attraction would have a
different response than priming the color red in an achievement situation, situations in which
there is a possibility for success or failure and competence is measured (Elliot, Maier, Binser,
Friedman, & Pekrun, 2009). In the context of romantic attraction, the color red unconsciously
increases perceived attractiveness of another person (Elliot & Niesta, 2008). With regards to
achievement, the color red elicits avoidance behavior due to its association with factors such as
the red in alarms that suggest danger (Elliot, Maier, Moller, Friedman, & Meinhardt, 2007; Elliot
et al., 2009).
To study the influence that red has on achievement, Elliot et al. (2007) .
More Related Content
Similar to McDonald & Asi 2015 threat perception consext sensitivity
A Structural Equation Modeling among Stress, Fear of Negative Evaluation and ...inventionjournals
The objective of this study is to examine the relations of the stress, fear of negative evaluation, avoidant decision making and dependent decision making among a group of university students that have moderate economic status. The study group consists of 330 participants who are students of public university. Our study was based on voluntary participation. 56% of participants were female and 44% participants were male. We used Structural Equation Modeling for the data analysis. The results were X2 /df=1.564; GFI=0.88; CFI=0.94; RMSEA=0.04; SRMR=0.05. The goodness of fit provided evidence that the hypothesized model was stable. All estimated path coefficients were significant. We found that the avoidant decision making and the dependent decision making have a positive impact on the fear of negative evaluation and the fear of negative evaluation has positive impact on the stress. The avoidant decision making style and the dependent decision making style explained %10 of the variation in the fear of negative evaluation. All these tree variables explained %20 of the variation in the stress. The fear of negative evaluation plays a mediating role for avoidant decision making style and the dependent decision making style on the stress.
Research ArticleDomain Specificity inExperimental Measur.docxrgladys1
Research Article
Domain Specificity in
Experimental Measures and
Participant Recruitment
An Application to Risk-Taking Behavior
Yaniv Hanoch,1,2 Joseph G. Johnson,3 and Andreas Wilke4
1
UCLA School of Public Health;
2
Max Planck Institute for Human Development, Berlin, Germany;
3
Miami University;
and
4
International Max Planck Research School LIFE, Max Planck Institute for Human Development, Berlin, Germany
ABSTRACT—We challenge the prevailing notion that risk
taking is a stable trait, such that individuals show con-
sistent risk-taking/aversive behavior across domains. We
subscribe to an alternative approach that appreciates the
domain-specific nature of risk taking. More important, we
recognize heterogeneity of risk profiles among experi-
mental samples and introduce a new methodology that
takes this heterogeneity into account. Rather than using
a convenient subject pool (i.e., university students), as is
typically done, we specifically targeted relevant subsam-
ples to provide further validation of the domain-specific
nature of risk taking. Our research shows that individuals
who exhibit high levels of risk-taking behavior in one
content area (e.g., bungee jumpers taking recreational
risks) can exhibit moderate levels in other risky domains
(e.g., financial). Furthermore, our results indicate that
risk taking among targeted subsamples can be explained
within a cost-benefit framework and is largely mediated by
the perceived benefit of the activity, and to a lesser extent
by the perceived risk.
How should researchers study a psychological construct such as
risk-taking propensity? Answering this question might not be as
easy as it seems at first glance. First, an individual might exhibit
risk-taking tendencies in one domain (e.g., financial) but display
more conservative behavior in another (e.g., recreational).
Second, different methodological designs—for example, the
pool of subjects used or the type of analysis conducted—can
yield contradicting results (e.g., Huber, Wider, & Huber, 1997).
In the present study, our methodological focus on the ecological
validity of the experimental design (e.g., Huber, 1997), domain-
specific risk-taking measures, and recruitment of participants in
targeted groups yielded results that allow us to challenge the
tendency to cluster individuals globally as either risk takers or
risk avoiders—thus offering a richer perspective on the psy-
chology of risk taking.
The psychological literature has been largely dominated by
the assumption that risk taking is a stable personality trait, and
thus individuals can be clustered into groups having risk-taking
or risk-aversive styles (e.g., Eysenck & Eysenck, 1977; Lejuez
et al., 2002; for a review, see Bromiley & Curley, 1992). This
simplistic, though appealing, conceptualization has proven to be
inadequate. Researchers have responded by examining sub-
traits and, therefore, the relation between risk taking and con-
struc.
1
AFFECTIVE FORECASTING
AFFECTIVE FORECASTING
Isaac Estrada
Florida International University
AFFECTIVE FORECASTING
Affective Forecasting is also known as hedonic forecasting, which refers to “implicit or explicit forecasts of utility that will be experienced at a later time” (Polyportis, Kokkinaki, Horváth, & Christopoulos, 2020), in this context, ‘utility’ refers to “the quality and intensity of the hedonic experience associated with [an] outcome” (Kahneman & Snell, 1992, p. 188). In other words, it refers to the prediction of emotions and feelings in the future, regarding an specific situation. Human beings tend to forecasting how they are going to feel about situations we consider are important, this is done unconsciously in the daily life. Following this definition Wilson and Gilbert identified four specific components of emotional experience that one may make predictions of Valence (whether the emotions will be positive or negative), specific emotions experience, intensity of the emotions, and duration of the emotions. For example, a college student is about to take a final exam, and he start getting his hands sweaty, and he start feeling nervous. He is predicting to feel fearful to fail the exam.
Affective Forecasting plays an important role in the daily life because it drives decision and behaviors (Dunn and Laham Affective forecasting: a user’s guide to emotional time travel, Psychology Press, London, 2006). Every decision requires a prediction (Barry Schwartz and R. Sommers, 2013). If we think about how we are going to feel about an event, we are going to make decisions to try to obtain desired outcomes, or to change our behavior towards the situation. For example, a woman makes an appointment to see the doctor because she is not feeling good, however, she is afraid of getting examined, so she decides to cancel her doctor appointment, as a result of this bad decision she starts feeling worse. Most of the times we engage in Affective Forecasting we predict wrongly, and we make mistakes.
Researchers suggest that when predicting our future emotions, affecting forecasting error are frequent (Wilson and Gilbert in Adv Exp Soc Psychol 35:345-411,2003). There are several reasons why we may find ourselves making seemingly basic errors when it comes to affective forecasting (Wilson & Gilbert, 2003). For better understanding here an example, a person heads to work and it seems that the day is going to be smooth, not busy, but it ends up being stressful, and very tiring day. The Target of error and Nature of bias are valence, specific emotions, intensity, and duration. In the study we are going to conduct, we can also see how participants report their feelings before the study, expecting good results about their participation in the study, and their target error, after completing the anagrams exercise.
Now that Affective Forecasting was exposed and explained, I am going to present details about the study. Solving ana ...
Vlastos, D., Kyritsis, M., Papaioannou-Spiroulia, A., & Varela V.-A. (2017). ...Dimitris Vlastos
Oral Presentation, 22nd International Conference of the Association of Psychology & Psychiatry for Adults & Children (A.P.P.A.C.): Recent Advances in Neuropsychiatric, Psychological and Social Sciences in Psychological Research, 16th – 19th May 2017, Athens, Greece.
Coping with Teasing and Name-Calling Scale for Children............................................................................................. 1
Ümit Sahranç
Assessment for Learning: How Plagiarism can be used as an Efficient Learning Tool............................................... 17
Lucía Morales and Amparo Soler-Domínguez
The use of Technology to Support the Innovative Teaching of Mathematics to Students with SEBD: A Debate
Related to the use of Technology in the Classroom to Promote Inclusion.................................................................... 35
Jonathan Camenzuli
An Effective Approach for Teaching Database ................................................................................................................ 53
K. S. Sastry, Musti
Circuit Analysis Tools: Integrating Smartphone and Tablet Applications and Simulation Software into Circuit
Analysis Instruction and Laboratories ............................................................................................................................... 64
John Ulrich, Charles Feldhaus, Elaine Cooney and David Nickolich
Efficacy of Cognitive Instruction in Teaching Deictic Motion Verbs in EFL Classrooms .......................................... 84
Hu, Ying-hsueh
Teaching in Interactive Pedagogical Perspective at Primary Schools in Northern Mountainous Provinces of
Vietnam ............................................................................................................................................................................... 105
Associate Prof. Dr. Duc-Hoa Pho
Discussion Forums in MOOCs.......................................................................................................................................... 119
Afsaneh Sharif and Barry Magrill
An Empirical Research on the Use of Mobile Phones to Support Students’ Mathematics Learning ...................... 133
Nguyen Danh Nam and Trinh Thi Phuong Thao
As the importance of promoting college student mental health increases and campuses work to prevent suicide, resident assistants (RAs) are called upon to serve as gatekeepers to facilitate professional help as a part of suicide prevention initiatives on campuses. However, assessing the efficacy of suicide prevention training is lacking. This study develops and validates the Gatekeepers Self-Efficacy Scale among resident assistants (RAs) based on the Question, Persuade, Response suicide prevention model. Exploratory Factor Analysis (EFA), Parallel Analysis, and Multidimensional Graded Response model (MGRM) were used with 302 RAs sample. Two factors were found, (1) Communicating about Crisis and (2) Knowledge of Resources, with appropriate item fit and parameter estimates. The response patterns of the two factors and their correlations with objective suicide prevention knowledge were estimated and discussed. The implications of these findings for practical application are discussed, along with suggestions for future studies.
Running head COLOR PRIMING AND FOREWARNING 1 .docxtodd271
Running head: COLOR PRIMING AND FOREWARNING 1
The Influence of Color Priming and Forewarning on Anagram Performance
A. Student
Florida International University
COLOR PRIMING AND FOREWARNING 2
Abstract
Methods One Students: Typically, authors add their abstract for the paper here on the second
page. As you can see, the abstract for this paper is missing. Your job is to supply that abstract!
Read over the following paper, which is an actual paper turned in by a former student taking
Research Methods and Design II at FIU. This is similar to a paper you will write next semester.
Review the studies in this paper, and spot the hypotheses, independent and dependent variables,
participants, results, and implications, and write it up in one paragraph (no more than 200 words
maximum). Make sure to include keywords as well (keywords are words or short phrases that
researchers use when searching through online databases like PsycInfo – they need to be
descriptive of the paper, so come up with three or four that seem to suit this paper). Good luck!
Keywords: Methods II Paper, Abstract Assignment, Methods II Preview
COLOR PRIMING AND FOREWARNING 3
The Influence of Color Priming and Forewarning on Anagram Performance
Colors are an essential part of life, from warning us of poisonous creatures to describing
our emotions, they have proven their worth. Certain colors can be perceived in specific situations
or attributed to a particular emotion. For instance, priming of sadness can lead to perception of
the color blue, whereas priming of anger can lead to perception of the color red (Fetterman,
Robinson, Gordon, & Elliot, 2011). The central aim of our study is to explore the effect priming
with a specific color has on anagram performance.
Priming is defined as the unconscious influence that a stimulus has on the agility or
accuracy in performing a task (Schacter & Rajendra, 2001). According to Jefferis and Fazio
(2008), priming impacts behaviors by informing the person if they have met the demands of the
situation. The influence priming has on behavior is shaped by what one perceives in a particular
situation. For example, priming the color red in the context of romantic attraction would have a
different response than priming the color red in an achievement situation, situations in which
there is a possibility for success or failure and competence is measured (Elliot, Maier, Binser,
Friedman, & Pekrun, 2009). In the context of romantic attraction, the color red unconsciously
increases perceived attractiveness of another person (Elliot & Niesta, 2008). With regards to
achievement, the color red elicits avoidance behavior due to its association with factors such as
the red in alarms that suggest danger (Elliot, Maier, Moller, Friedman, & Meinhardt, 2007; Elliot
et al., 2009).
To study the influence that red has on achievement, Elliot et al. (2007) .
Similar to McDonald & Asi 2015 threat perception consext sensitivity (20)
Running head COLOR PRIMING AND FOREWARNING 1 .docx
McDonald & Asi 2015 threat perception consext sensitivity
1. Results
Threat Perception and Context Sensitivity Relation
Dan McDonald, Suhair Asi, and Spencer Lynn
Introduction
An individual’s judgment of how
threatening a face looks could be
altered by the context surrounding
that face. The idea of “context
sensitivity” has been studied as a
key aspect to the decision making
process. Context sensitivity argues
that when there is a collection of
options from which the decision
maker must choose then the
alternative options within the
collection compromise a unique
context (Busemeyer, 1993).
In Busemeyer's study, he noticed
this issue when studying economic
decision making. Subjects were
asked to choose between a gamble
and a certain value. Option A was
win or lose 5 cents with equal
probability. Option B was the win or
lose 50 cents with equal probability.
Option C was a certain loss of 1
cent. Option D was a certain gain of
1 cent. The probabilities of choosing
A over C, B over C, A over D, and B
over D were found: the probability
was higher to choose A over C than
B over C. These results would imply
that the probability to pick A is
always greater than B. However,
this was not the case; the pattern
was reversed for the A vs. D and B
vs. D choices. This meant that the
participants made the decision
based on the pairings rather than
on a preference for a specific
option.
From Busemeyer’s findings, we
hypothesized that a person’s
judgment of a face being
threatening would be influenced by
the other faces that one was also
judging. The set of faces under
consideration might form a context
that can influence one’s perception
of a target face.
References
Busemeyer, Jerome R., and James T.
Townsend. "Decision Field Theory: A
Dynamic-cognitive Approach to
Decision Making in an Uncertain
Environment." Psychological Review
100.3 (1993): 432-59.
Olivola, C. Y., Funk, F., & Todorov, A.
(2014). Social attributions from faces
bias human choices. Trends in
Cognitive Sciences, 18(11), 566-570.
Methods
Our study examines participants’
ability to effectively categorize two
different faces during a threat
perception task. We recruited 28
participants from the Northeastern
University student-body population.
Participants saw two different series
of faces that ranged from non-
threatening physiognomy (i.e., the
shape of facial features) to
threatening physiognomy.
According to previous research,
certain facial features create a more
threatening look than others, for
example, a stronger jaw line is more
threatening than a rounded or
weaker one (Olivola, 2014). Faces
were constructed using FaceGen
Modeler software. Each face series
comprised 11 “morphs” of a “base”
face. With each morph, facial
features changed very slightly, in
almost unnoticeable distinctions.
For example, the size of the
individual’s nostrils went from very
small to very large. The faces
ranged from 1-11, one being the
most non-threatening and 11 being
most threatening.
In run 1 of the experiment the face
series were created from two young
base faces. In run 2 of the
experiment an old base face was
used in place of one of the young
base faces. The two young faces
were approximately 20-30 years of
age while the old face was
approximately 50-60 years of age.
During the perception task,
participants viewed one face at a
time for 500 ms. Participants
earned or lost points by correctly
detecting whether or not the face
was threatening. They were
instructed to earn as many points
as they could over 300 trials. The
point values favored a conservative
bias, which means a tendency to
categorize the faces as not
threatening. Therefore, participants
with a more conservative bias
earned more points during the
study.
Conclusion &
Discussion
The threat physiognomy’s
dependency on a stimulus’
surroundings upholds Busemyer’s
(1993) findings of context sensitivity
because the choices surrounding
each stimulus influence the
participant’s perception and
ultimately his or her decision. While
conducting the threat physiognomy
study, a person’s threat perception
was affected by other options
present. Threat perception
experiences this phenomenon
because an individual is affected by
context sensitivity when analyzing a
threat, making Busemyer’s (1993)
findings applicable.
Though successful in identifying
context sensitivity, our experiment
is limited by the demographics of
the participants (solely Northeastern
Students with an average age of
18-22 years) and the type of stimuli
(only white males). Future studies
would ideally study faces of both
genders and different races, and
the studies should select a larger
variety for the demographic of
participants.
Currently, we are investigating how
adding an additional stimulus to the
face perception task would intensify
or hinder a person’s threat
perception. Context sensitivity is
applicable to a person’s threat
perception and would need further
investigation to determine if the
relation can be applied to all
settings.
Abstract
Social threat perception is the ability
to effectively identify person as a
threat or not. We investigated
whether or not people’s evaluation
of a face as threatening is biased by
other faces they are also
evaluating. Over two runs of the
experiment, participants had to
judge three faces that were similar
in features and state “yes” or “no”
when asked if they were
threatening. Participants earned
and lost points for correct and
incorrect categorization of the
faces, and were instructed to earn
as many points as they could. With
the points as motivation, a slight
bias to categorize faces as not
threatening would maximize
earnings. We hypothesized that the
participants would not judge the
target face, which was present in
both runs, any differently when it
was paired with another face, which
differed on the two runs. However,
participants judged the target face
to be more threatening when it was
paired with a young face (run 1)
than when paired with an old face
(run 2). These results show that the
participants were judging the two
faces in relation to each other rather
than separately. We conclude that
context sensitivity, meaning people
use everything in the situation to
form judgments, altered how people
perceived the target face.
We created the graph using the results from each participant (n=14). The data collected is
averaged to display the function of the participants' behavioral response to the target face
series. The calculations were determined by calculating the participants’ average portion of
times they said the target face was threatening. The graph displays the participants’
responses to the the target face (blue) and alternative face (green). A line’s inflection point is
the participants’ threshold of threat detection
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ProbabilityofperceivedThreat
Range of faces from non-threatening to threatening
Run 1
Target Face, Run1
Altered Face, Run 1
We created an aged version the target face series to see if an aged version would stimulate a
different response. Initially, we thought the aged face would be seen as less threatening due
to its age (50-60 years old), but the aged face was perceived as more threatening in
comparison to the target face. The graph represents the participants’ responses when
stimulated with the target face (red) and the aged alternative face (green) (n=14).
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ProbabilityofPerceivedthreat
Range of faces from non-threatening to threatening
Run 2
Target Face, Run2
Aged Target Face, Run2
By comparing both target face graphs side by side, we were able to conclude that the threat
perception of the target face was context sensitive, which makes the stimulus dependent on
the other stimuli surrounding the target face. The threshold determines where the participant’s
perception of the faces shifts from non-threatening to threatening. When comparing the two
data sets, the target face’s threshold location increased during Run 2. Participants found the
target face to be significantly less threatening when it was paired with the aged face in Run 2
than when it was paired with the young face in Run 1 (t25=-5.2, P<0.001).
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ProbabilityofperceivedThreat
Range of faces from non-threatening to threatening
Run 1 and Run 2 Results
Mean Target Face, Run 1
Mean Target Face, Run 2
McDonald, D., Asi, S., and Lynn, S. K. 2015. Threat perception and context sensitivity relation. Presented at the Fall
Symposium of the Interdisciplinary Affective Science Laboratory, Northeastern University, Boston, Massachusetts.