Psychological Science21(12) 1770 –1776© The Author(s) 2010.docx

Psychological Science
21(12) 1770 –1776
© The Author(s) 2010
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DOI: 10.1177/0956797610387441
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A well-established finding is that mood interacts with cogni-
tive processing (for a review, see Isen, 1999), with executive
functioning implicated as a possible source of the effects of
this interaction (Mitchell & Phillips, 2007). Positive mood
leads to enhanced cognitive flexibility,1 whereas negative
mood may reduce (or may not affect) cognitive flexibility (for
a review, see Ashby, Isen, & Turken, 1999). Category learning
has also been associated with cognitive flexibility (Ashby
et al., 1999; Maddox, Baldwin, & Markman, 2006), making cat-
egory learning well suited to the study of the effects of mood
on cognition. For example, Ashby, Alfonso-Reese, Turken,
and Waldron (1998) predicted that depressed subjects should
be impaired in learning rule-described (RD) category sets.
Smith, Tracy, and Murray (1993) supported this prediction and
also found that depressed subjects were not impaired when
learning non-RD categories. However, the more general ques-
tion of how induced positive and negative mood states influ-
ence category learning remains unanswered. We addressed
this question by using two kinds of categories, one in which
learning is thought to be enhanced by cognitive flexibility and
one in which learning is not thought to be enhanced by cogni-
tive flexibility (Maddox et al., 2006).
Our starting point was the competition between verbal and

implicit systems (COVIS) theory, which posits the existence
of separate explicit and implicit category-learning systems
(Ashby et al., 1998). The explicit system enables people to
learn RD categories and is associated with the prefrontal cor-
tex (PFC) and the anterior cingulate cortex (ACC). RD cate-
gory learning uses hypothesis testing, rule selection, and
inhibition to find and apply rules that can be verbalized, and it
is influenced by cognitive flexibility. The implicit system
enables people to learn non-RD categories, relies on connec-
tions between visual cortical areas and the basal ganglia, and
is not affected by cognitive flexibility. This system is likely
procedural in nature and dependent on a dopamine-mediated
reward signal (Maddox, Ashby, Ing, & Pickering, 2004). RD
and non-RD category sets have been dissociated behaviorally
(for a review, see Maddox & Ashby, 2004) and neurobiologi-
cally (Nomura et al., 2007), making them appropriate for the
study of mood effects.
We argue that positive mood increases cognitive flexibility,
and this effect enhances the explicit category-learning system
Corresponding Author:
Ruby T. Nadler, The University of Western Ontario, Department
of
Psychology, Social Science Centre, Room 7418, 1151 Richmond
St., London,
Ontario, Canada N6A 5C2
E-mail: [email protected]
Better Mood and Better Performance:
Learning Rule-Described Categories Is
Enhanced by Positive Mood
Ruby T. Nadler, Rahel Rabi, and John Paul Minda
The University of Western Ontario

Abstract
Theories of mood and its effect on cognitive processing suggest
that positive mood may allow for increased cognitive flexibility.
This increased flexibility is associated with the prefrontal
cortex and the anterior cingulate cortex, both of which play
crucial
roles in hypothesis testing and rule selection. Thus, cognitive
tasks that rely on behaviors such as hypothesis testing and rule
selection may benefit from positive mood, whereas tasks that do
not rely on such behaviors should not be affected by positive
mood. We explored this idea within a category-learning
framework. Positive, neutral, and negative moods were induced
in
our subjects, and they learned either a rule-described or a non-
rule-described category set. Subjects in the positive-mood
condition performed better than subjects in the neutral- or
negative-mood conditions in classifying stimuli from rule-
described
categories. Positive mood also affected the strategy of subjects
who classified stimuli from non-rule-described categories.
Keywords
frontal lobe, emotions, hypothesis testing, selective attention,
response inhibition
Received 4/7/10; Revision accepted 6/28/10
Research Report
Better Mood and Better Performance 1771
mediated by the PFC (Ashby et al., 1999; Ashby & Ell, 2001;

Minda & Miles, 2010). We base our predictions on two lines
of research. First, Ashby et al. (1999) hypothesized that posi-
tive affect is associated with enhanced cognitive flexibility as
a result of increased dopamine in the frontal cortical areas of
the brain. Second, the COVIS theory predicts that increased
dopamine in the PFC and ACC should enhance learning on
RD tasks, and reduced dopamine should impair learning on
RD tasks (Ashby et al., 1998). Thus, positive mood should be
associated with enhanced RD category learning, an important
prediction that has not to our knowledge been tested directly.
We induced a positive, neutral, or negative mood in sub-
jects and presented them with one of two kinds of category
sets that have been widely used in the category-learning litera-
ture (Ashby & Maddox, 2005). These sets consisted of sine-
wave gratings (Gabor patches) that varied in spatial frequency
and orientation. The RD set of Gabor patches required learners
to find a single-dimensional rule in order to correctly classify
the stimuli on the basis of frequency but not orientation, and
the non-RD, information-integration (II) set of Gabor patches
required learners to assess both orientation and frequency.
Subjects in the RD condition were able to formulate a verbal
rule to ensure optimal performance, but subjects in the II con-
dition were not able to form a rule that could be easily
verbalized.
We predicted that subjects in a positive mood, compared
with those in a neutral or negative mood, would perform better
when learning RD categories. It was unclear whether a nega-
tive mood would impair RD learning relative to a neutral
mood, as the effects of negative mood on cognitive processing
are variable and difficult to predict (for a review, see Isen,
1990). Because the PFC and the ACC do not mediate the
implicit system, we did not expect mood to affect II category
learning.

Method
Subjects
Subjects were 87 university students (61 females and 26
males), who received $10.00 or course credit for participation.
Subjects were randomly assigned to one of the three mood-
induction conditions and one of the two category sets. Six sub-
jects who scored below 50% on the categorization task were
excluded from data analysis.
Materials
We used a series of music clips and video clips from YouTube2
to establish affective states. We verified that these clips evoked
the intended emotions by conducting a pilot study. After each
viewing or listening, subjects in the pilot study (7 graduate
students, who did not participate in the main experiment) rated
how the clip made them feel on a 7-point scale, which ranged
from 1 (very sad) to 4 (neutral) to 7 (very happy). Table 1
shows the complete list of clip selections and the average rat-
ings by pilot subjects; it also denotes the clips selected for the
main experiment. As a manipulation check during the main
experiment, we queried subjects with the Positive and Nega-
tive Affect Schedule (PANAS) after using the selected clips to
induce moods. The PANAS assesses positive and negative
affective dimensions (Watson, Clark, & Tellegen, 1988).
The Gabor patches used in the main experiment were gen-
erated according to established methodologies (see Ashby &
Gott, 1988; Zeithamova & Maddox, 2006). For each category
(RD and II), we randomly sampled 40 values from a multivari-
ate normal distribution described by that category’s parame-
ters (shown in Table 2). The resulting structures for the RD
and II category sets are illustrated in Figure 1.3 We used the
PsychoPy software package (Pierce, 2007) to generate a Gabor
patch corresponding to each coordinate sampled from the mul-

tivariate distributions.
Procedure
In the main experiment, subjects were assigned randomly to
one of three mood-induction conditions (positive, neutral, or
negative), as well as to one of two category sets (RD or II).
Table 1. Music and Video Clips Used in the Pilot Study
Selection
Average subject
rating
Positive music
Mozart: “Eine Kleine Nachtmusik—Allegro”* 6.57
Handel: “The Arrival of the Queen of Sheba” 5.00
Vivaldi: “Spring” 6.14
Neutral music
Mark Salona: “One Angel’s Hands”* 3.86
Linkin Park: “In the End (Instrumental)” 4.14
Stephen Rhodes: “Voice of Compassion” 3.29
Negative music
Schindler’s List Soundtrack: “Main Theme”* 2.00
I Am Legend Movie Theme Song 2.71
Distant Everyday Memories 2.57
Positive video
Laughing Baby* 6.57
Whose Line Is It Anyway: Sound Effects 6.43
Where the Hell Is Matt? 6.00
Neutral video
Antiques Roadshow Television Show* 4.14
Facebook on 60 Minutes 3.71
Report About the Importance of Sleep 4.29
Negative video
Chinese Earthquake News Report* 1.43

Madison’s Story (About Child With Cancer) 1.71
Death Scene From the Film The Champ 1.86
Note: Clips were taken from the YouTube Web site. Asterisks
denote clips
that were used in the main experiment.
1772 Nadler et al.
Subjects were presented with the clips (music first, then video)
from their assigned mood condition and then completed the
PANAS so we could ensure that the mood induction was
successful.
After receiving instructions, subjects performed a category-
learning task on a computer. On each trial, a Gabor patch
appeared in the center of the screen, and subjects pressed the
“A” or the “B” key to classify the stimulus. Subjects who
viewed the RD category set (Fig. 1a) had to find a single-
dimensional rule to correctly classify the stimuli on the basis
of the frequency of the grating, while ignoring the more salient
dimension of orientation. The optimal verbal rule for such
classification could be phrased as follows: “Press ‘A’ if the
stimulus has three or more stripes; otherwise, press ‘B.’” The
non-RD, II category set (Fig. 1b) required learners to assess
both orientation and frequency. There was no rule for this set
that could be easily verbalized to allow for optimal perfor-
mance. In both conditions, feedback (“CORRECT” or
“INCORRECT”) was presented after each response. Subjects
completed four unbroken blocks of 80 trials each (320 total).
The presentation order of the 80 stimuli was randomly gener-
ated within each block for each subject.

Results
PANAS
Scores on the Positive Affect scale were as follows—positive-
mood condition: 2.89; neutral-mood condition: 2.45; and neg-
ative-mood condition: 2.42. A significant effect of mood on
positive affect was found, F(2, 78) = 3.98, p < .05, η2 = .093.
Positive-mood subjects showed only marginally more positive
Table 2. Distribution Parameters for the Rule-Described and
Non-Rule-
Described Category Sets
Category set and category µ
f
µ
o
σ
f
2 σ
o
2 cov
f,o
Rule-described
Category A 280 125 75 9,000 0
Category B 320 125 75 9,000 0
Non-rule-described
Category A 268 157 4,538 4,538 435
Category B 332 93 4,538 4,538 4,351
Note: Dimensions are in arbitrary units; see Figure 1 for scaling

factors. The sub-
scripted letters o and f refer to orientation and frequency,
respectively.
–200
–100
0
100
200
300
400
500
–100 0 100 200 300 400 500 600
O
rie
nt
at
io
n
Frequency
Rule-Described
–200

–100
0
100
200
300
400
500
–100 0 100 200 300 400 500 600
O
rie
nt
at
io
n
Frequency
Non-Rule-Described
ba
Fig. 1. Structures used in the (a) rule-described category set and
(b) non-rule-described, information-integration category set.
Category A stimuli are
represented by light circles, and Category B stimuli are
represented by dark circles. The solid lines show the optimal

decision boundaries between
the stimuli. The values of the stimulus dimensions are arbitrary
units. Each stimulus was created by converting the value of
these arbitrary units into
a frequency value (cycles per stimulus) and an orientation value
(degree of tilt). For both category sets, the grating frequency (f)
was calculated as
0.25 + (x
f
/50) cycles per stimulus, and the grating orientation (o) was
calculated as xo × (π/20)°. The Gabor patches are examples of
the actual stimuli
seen by subjects.
affect than neutral-mood subjects did (p < .06), but they
showed significantly more positive affect than negative-mood
subjects did (p < .05). These scores indicate that the mood-
induction procedures were effective. Scores on the Negative
Affect scale were as follows—positive-mood condition: 1.15;
neutral-mood condition: 1.18; and negative-mood condition:
2.13. A significant effect of mood on negative affect was
found, F(2, 78) = 30.36, p < .001, η2 = .438, with negative-
mood subjects showing significantly more negative affect than
positive- and neutral-mood subjects did (p < .0001 in both
cases). These results again indicate that the mood-induction
procedures were effective.
Category learning
Figure 2 shows the learning curve (average proportion of cor-
rect responses in Blocks 1–4) for each condition and each cat-

egory set. A mixed analysis of variance revealed main effects
of category set, F(1, 75) = 31.94, p < .001, η2 = .257; mood,
F(2, 75) = 4.40, p < .05, η2 = .071; and block, F(3, 225) =
41.33, p < .001, η2 = .322. It also revealed a significant interac-
tion between mood and category set, F(2, 75) = 4.17, p < .05,
η2 = .067. We conducted two separate analyses of variance
(one for the RD category and one for the II category) to exam-
ine this interaction.
A main effect of mood on overall performance was found
for the RD category set, F(2, 35) = 6.28, p < .001, η2 = .264. A
Tukey’s honestly significant difference test showed that over-
all performance by subjects in the positive-mood condition
(M = .85) was higher than performance by subjects in the neg-
ative-mood condition (M = .73, p < .0001) and subjects in the
neutral-mood condition (M = .73, p < .0001). Performance did
not differ between subjects in the neutral- and negative-mood
conditions (p = .69). No effect of mood on overall perfor-
mance was found for the II category set (p = .71). Overall pro-
portions correct were as follows—positive-mood condition:
.64; negative-mood condition: .66; and neutral-mood condi-
tion: .64.
Computational modeling
For insight into the response strategies used by our subjects,
we fit decision-bound models to the first block of each sub-
ject’s data (for details, see Ashby, 1992a; Maddox & Ashby,
1993). We analyzed the first block of trials because that is
when mood-induction effects are likely to be strongest, and it
is also when cognitive flexibility is most needed. One class of
models assumed that each subject’s performance was based on
a single-dimensional rule (we used an optimal version with a
fixed intercept and a version with the intercept as a free param-
eter). Another class of models assumed that each subject’s per-
formance was based on the two-dimensional II boundary (we

used an optimal version with a fixed intercept and slope, a ver-
sion with a fixed slope, and a version with a freely varying
P
ro
po
rt
io
n
C
or
re
ct
RD Category Set II Category Set
.0
.2
.4
.6
.8
1.0
P
ro
po

rt
io
n
C
or
re
ct
.0
.2
.4
.6
.8
1.0
Block Block
Positive Mood Neutral Mood
Negative Mood
Positive Mood Neutral Mood
Negative Mood
1 2 3 4 1 2 3 4
Fig. 2. Average proportion of correct responses to stimuli in the
three mood conditions as a function of trial block. Subjects
were tested on either the

rule-described (RD) category set (left graph) or the non-RD,
information-integration (II) category set (right graph). Error
bars denote standard errors
of the mean.
1774 Nadler et al.
slope and intercept). We fit these models to each subject’s data
by maximizing the log likelihood. Model comparisons were
carried out using Akaike’s information criterion, which penal-
izes a model for the number of free parameters (Ashby, 1992b).
The proportion of subjects whose responses were best fit by
their respective optimal model is shown in Figure 3. For the
RD categories, .83 of positive-mood subjects, .62 of neutral-
mood subjects, and .54 of negative-mood subjects were fit best
by a model that assumed a single-dimensional rule. For the II
categories, .71 of positive-mood subjects, .40 of neutral-mood
subjects, and .43 of negative-mood subjects were fit best by
one of the II models.
Discussion
In this experiment, positive, neutral, and negative moods were
induced before subjects learned either an RD or a non-RD, II
category set. The RD set required subjects to use hypothesis
testing, rule selection, and response inhibition to achieve opti-
mal performance, and the II set was best learned by associat-
ing regions of perceptual space with responses (Ashby & Gott,
1988). We found that positive mood enhanced RD learning com-
pared with neutral and negative moods. Mood did not seem to
affect II learning. However, a comparison of decision-bound
models suggested that positive-mood subjects displayed a
greater degree of cognitive flexibility compared with neutral-
and negative-mood subjects by adopting an optimal strategy

early in both RD and II learning.
The COVIS theory suggests that people learn categories
using an explicit, rule-based system or an implicit, similarity-
based system (Ashby et al., 1998; Ashby & Maddox, 2005;
Minda & Miles, 2010). The brain areas that mediate these sys-
tems have been well studied, linking the PFC, ACC, and
medial temporal lobes to the explicit system but not to the
implicit system. Our experiment highlights a variable that
facilitates the learning of RD categories using the explicit
system.
The finding that positive mood enhances performance of
the explicit system posited by the COVIS theory corresponds
with the dopamine hypothesis of positive affect (Ashby et al.,
1999). Our results connect this research with existing work on
category learning, and we view this connection as a substan-
tial step forward in the study of cognition and mood. We sus-
pect that our positive-mood subjects experienced increased
cognitive flexibility, which allowed them to find the optimal
verbal rule faster than negative-mood subjects and neutral-
mood subjects did. Performance on the II category set did not
differ strongly across the different mood conditions. This
result is also in line with the dopamine hypothesis, as positive
mood is not theorized to affect the same brain regions
P
ro
po
rt
io
n
F

it
by
O
pt
im
al
M
od
el
.0
.2
.4
.6
.8
1.0
P
ro
po
rt
io
n
F

it
by
O
pt
im
al
M
od
el
.0
.2
.4
.6
.8
1.0
Positive Neutral Negative
Mood-Induction Condition
Positive Neutral Negative
Mood-Induction Condition
RD Category Set II Category Set

Fig. 3. Proportion of subjects in each mood-induction condition
whose responses best fit the optimal model for the category set
to which they
were assigned. Subjects learned either the rule-described (RD)
category set (left graph) or the non-RD, information-integration
(II) category set
(right graph).
hypothesized by the COVIS theory to be involved with the
learning of non-RD category sets. However, our modeling
results suggest that the cognitive flexibility associated with
positive mood may affect the strategies used in II category
learning. This cognitive flexibility could allow the explicit
system to exhaust rule searches more effectively, even though
performance levels may remain unchanged between the
conditions.
We failed to find an effect of negative mood in RD learn-
ing. This is in line with previous research that reported no dif-
ferences between negative- and neutral-mood subjects on
measures of cognitive flexibility (Isen, Daubman, & Nowicki,
1987). It may be that negative mood does not affect RD cate-
gory learning, although we think it could, given the right cir-
cumstances. One possible explanation of why we did not find
such an effect is that the induced negative mood may not have
been sustained long enough to interfere with performance. We
suspect that subjects in certain negative states will be impaired
in RD category learning. Future work should examine ways of
sustaining mood states and should explore a wider range of
negative mood states.
An intriguing possibility that was not observed is that nega-

tive mood could enhance II category learning. Recent research
suggests that affective states low in motivational intensity
(e.g., amusement, sadness) are associated with broadened
attention, and affective states high in motivational intensity
(e.g., desire, disgust) are associated with narrowed attention
(Gable & Harmon-Jones, 2008, 2010). Thus, for example, sad-
ness may facilitate performance when broadened attention is
beneficial for category learning. We did not find this effect,
either because learning of the II category set used did not ben-
efit from broadened attention or because the induced negative
mood was high in motivational intensity. These interesting
ideas require further research.
Smith et al. (1993) showed that clinically depressed sub-
jects were impaired in RD category learning and unimpaired
in II category learning, but our research is the first to investi-
gate how experimentally induced mood states influence cate-
gory learning. We have shown that positive mood enhanced
the learning of an RD category set, an advantage that was
strong and sustained throughout the task. Positive mood did
not improve the learning of II categories, though there was
evidence that positive mood enhanced selection of the optimal
strategy. By connecting theories of multiple-system category
learning and positive affect, our research suggests that positive
affect enhances performance when category learning benefits
from cognitive flexibility. Future work should examine the
interaction between mood states (motivationally weak com-
pared with intense), valence (positive compared with nega-
tive), and category type (explicit compared with implicit) in
category learning.
Acknowledgments
We thank E. Hayden for many valuable insights on this project.
Declaration of Conflicting Interests

The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
Funding
This research was supported by Natural Sciences and
Engineering
Research Council (NSERC) Grant R3507A03 to J.P.M., an
Ontario
Graduate Scholarship award to R.T.N., and an NSERC
fellowship to
R.R.
Notes
1. We define cognitive flexibility as the ability to seek out and
apply
alternate strategies to problems (Maddox, Baldwin, & Markman,
2006) and to find unusual relationships between items (Isen,
Johnson,
Mertz, & Robinson, 1985).
2. The clips can be found by searching for their titles on
YouTube
(http://www.youtube.com/), or URLs can be obtained from the
first
author.
3. Stimulus parameters and generation were the same as those
used
by Zeithamova and Maddox (2006).
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Running head: DO WEAPONS MAKE PEOPLE AGGRESSIVE?
1
DO WEAPONS MAKE PEOPLE AGGRESSIVE
7
Weapons as Aggression-Eliciting Stimuli
Jane Doe
Florida International University
Weapons as Aggression-Eliciting Stimuli

Summary:
Berkowitz and Lepage (1967) designed a study to test the
hypothesis that individuals who are in a state of anger are more
likely to act out their aggression if cues associated with
violence and aggression are present. The sample consisted of
100 male students from the University of Wisconsin who were
all enrolled in an introductory level psychology course.
This study used an experimental research method because it
manipulated the independent variable and presumably involved
random assignment (although this was not stated in the text).
There were two main independent variables. The first one was
the subject’s level of anger and this was determined by whether
the subject was shocked once or seven times. The second
independent variable was the kind of cue present near the shock
button when it was the subject’s turn to evaluate the
confederate. For one group there was no object, in the control
group there was a neutral object (a badminton racquet), and for
the last group there was a gun that was supposedly part of a
different study. This last group was further separated into 2
subgroups with some being told that the gun belonged to the
confederate while others were told that it was left behind by
someone else. These independent variables were then combined
to see how they affected the dependent variable, which was the
level of aggression the subject displayed. The dependent
variable was measured by how many shocks the subject
delivered to the confederate.
The procedure ran as follows: volunteers were told that they
were participating in a study to test the physiological effects of
stress. To do this the subject and the other participant (who
was actually a confederate) were both given a social problem
and they had to think up ways to solve it. After they completed
this task (in separate rooms) their problem solving ideas were
then exchanged so they could evaluate each other. The
evaluation was done by pushing a button that was supposed to
shock the person in the other room (although they still could not
see each other); 1 shock represented the best rating while a

lesser evaluation was communicated through a higher number of
shocks. The confederate was the first to do the evaluation. The
number of shocks given to the actual volunteer was already
determined as 1 or 7 though (depending on the random
assignment) and was not based on a real rating. After this came
the volunteer’s turn to do the same evaluation, but the number
of shocks was not predetermined. Next to the shock button was
one of the previously stated objects, and the gun was the only
cue hypothesized to elicit increased aggression.
The results of this study confirmed the hypothesis. Those
participants who were more angered (given 7 shocks) and were
cued by the violent object (a gun) and told that it belonged to
the person they were rating, outwardly expressed their
aggression the most by giving the confederate a higher number
of shocks. The next highest number of shocks was by the group
in the presence of a gun, but had been told the gun was left
behind by someone else. Those who did not see any objects
gave on average one less shock and the least number of shocks
were given by those in the presence of the badminton racquets.
On the other hand, when the volunteer was not as angered (only
shocked once by the confederate), outward expression of
aggression was relatively low and stable regardless of what type
of cue was present. The researchers used these results to
theorize that a person who is already aroused and is then cued
by a violent object is more likely to have an impulsive reaction
to act more aggressively.
Critique:
Overall this study was well designed in order to test the given
hypothesis that weapons are aggression-eliciting stimuli. The
method of using different objects to induce a given response is
very similar to the proven phenomenon of priming. Priming is
where certain information is more attended to when related cues
are presented. Therefore the results of Berkowitz and Lepage
(1967) make sense because weapons are connected to

aggression, which increases the person’s awareness of his or her
aggressive feelings, and consequently makes the outward act of
aggression more likely.
Based on the results, chances are high that these men would
always act in this way when in a similar situation, so this study
can be considered reliable (that is, it is repeatable). Validity is
not as strong, though. Validity refers to whether the study is
measuring what it purports to measure. When the participant
was already aroused (given 7 shocks) there was a significant
difference in the amount of retaliation depending on which cue
was present. However, this retaliation did not depend on the
cues if the participant was not as initially aroused (only given 1
shock). So how can they be measuring the impact of a priming
mechanism like the gun in the room if they need participants to
already be aroused? I am not sure they are measuring their
variables correctly. That being said, it did show that although
the cues do have an effect on aggressive behavior, initial
aggression level plays a much larger role in the causal
relationship. The ethicalness of this study is also questionable.
Receiving and delivering shocks could potentially cause
physical pain and also have a negative effect on one’s emotional
well-being. Nonetheless, most participants probably did not
suffer any serious consequences. Also, due to the nature of this
specific research question it does not seem like there is another
way to measure aggression that would be anymore ethical.
One major methodological problem that should have been
addressed is the sample that was obtained. The sample used in
this experiment is not a good representation of humans in
general, because it only involved college-aged men. It is
possible that women or people of different ages may respond
differently to the cues. Women are often thought of as less
violent, so their reaction to a negative stimulus might cause
them to deliver fewer shocks. A weapon makes the seriousness
of the situation salient and may cause some people to think
rationally about their behavior in the near future. Clearly this
proposal requires actual testing before making further

assumptions, but it does show the need for a more diverse
sample of participants.
Along the same line as the previous issue, a follow-up study
could more carefully look at the relationship between peoples’
attitudes towards guns (or other weapons) and their
corresponding level of aggressive behavior when given the
chance to retaliate. This would be more of a quasi-experiment
because in order to test the independent variable of attitudes
towards weapons the groups could not be randomly assigned.
Three existing groups would be used; those who support
weapons, those who are against them, and those who feel
neutral (the control group). The hypothesis would predict that
if prior arousal level was high, participants who support
weapons would show increased aggression when cued by the
gun, but the group of participants with negative attitudes
towards guns would not be as aggressive. If the subjects did not
receive prior arousal (if they were only shocked once by their
“evaluator”), then neither group would be significantly affected
by the cues.
Even if initial aggression is a greater cause in inducing violent
behavior than the existence of weapon-related cues, this study
has serious implications for social policies related to gun
control. It is apparent from the results that if someone is angry
and is near a gun, then that person will likely act more
aggressively than he or she typically would. Since the guns in
the experiment were not loaded and the situation was
controlled, the heightened aggression was not transferred over
to actually using the guns. In a private home though, arguments
occurring with a gun nearby might make it more likely that a
gun will be used. Knowing that the mere presence of a weapon
increases violence should urge lawmakers to consider adopting
stricter gun laws.
Brief summary
Berkowitz and Lepage (1967) conducted a study in which they

hypothesized that priming people with an aggressive object (a
gun) would lead them to act aggressively. The authors gave
electrical shocks (from 1 to 7 of them) to 100 male
undergraduates. They told them that one of their peers had
delivered the shock. The participant could then retaliate, but
they did so in the presence of either a gun or a tennis racket
(which was supposedly left in the researcher room from a
different study). Participants given the highest number of
shocks (7) gave higher retaliation shocks to the peer, but this
was more likely when they were in the presence of a gun
(compared to a tennis racket). The authors concluded that the
guns increased aggressive responses from male participants who
were highly aroused.
References
Berkowitz, L., & Lepage, A. (1967). Weapons as aggression-
eliciting stimuli. Journal of Personality and Social Psychology,
7, 202-207. doi: 10.1037/h0025008
Running head: ARTICLE CRITIQUE INSTRUCTIONS 1
ARTICLE CRITIQUE INSTRUCTIONS 2
Article Critique Instructions (60 points possible)
Ryan J. Winter
Florida International University

Purpose of The Article Critique Paper
1). Psychological Purpose
This paper serves several purposes, the first of which is helping
you gain insight into research papers in psychology. As this
may be your first time reading and writing papers in
psychology, one goal of Paper I is to give you insight into what
goes into such papers. This article critique paper will help you
learn about the various sections of an empirical research report
by reading at least one peer-reviewed articles (articles that have
a Title Page, Abstract*, Literature Review, Methods Section,
Results Section, and References Page—I have already selected
some articles for you to critique, so make sure you only critique
one in the folder provided on Canvas) This paper will also give
you some insights into how the results sections are written in
APA formatted research articles. Pay close attention to those
sections, as throughout this course you’ll be writing up some
results of your own!
In this relatively short paper, you will read one of five articles
posted on Canvas and summarize what the authors did and what
they found. The first part of the paper should focus on
summarizing the design the authors used for their project. That
is, you will identify the independent and dependent variables,
talk about how the authors carried out their study, and then
summarize the results (you don’t need to fully understand the
statistics in the results, but try to get a sense of what the
authors did in their analyses). In the second part of the paper,
you will critique the article for its methodological strengths and
weaknesses. Finally, in part three, you will provide your
references for the Article Critique Paper in APA format.
2). APA Formatting Purpose
The second purpose of the Article Critique paper is to teach you
proper American Psychological Association (APA) formatting.
In the instructions below, I tell you how to format your paper
using APA style. There are a lot of very specific requirements
in APA papers, so pay attention to the instructions below as
well as Chapter 14 in your textbook! I highly recommend using

the Paper I Checklist before submitting your paper, as it will
help walk you through the picky nuances of APA formatting.
3). Writing Purpose
Finally, this paper is intended to help you grow as a writer. Few
psychology classes give you the chance to write papers and
receive feedback on your work. This class will! We will give
you feedback on this paper in terms of content, spelling, and
grammar.
Article Critique Paper (60 points possible)
Each student is required to write an article critique paper based
on one of the research articles present on Canvas only those
articles listed on Canvas can be critiqued – if you critique a
different article, it will not be graded). If you are unclear about
any of this information, please ask.
What is an article critique paper?
An article critique is a written communication that conveys your
understanding of a research article and how it relates to the
conceptual issues of interest to this course.
This article critique paper will include 5 things:
1. Title page: 1 page (4 points)
· Use APA style to present the appropriate information:
· A Running head must be included and formatted APA style
· The phrase “Running head” is at the top of the title page
followed by a short title of your creation (no more than 50
characters) that is in ALL CAPS. This running head is left-
justified (flush left on the page). Note that the “h” in head is all
lower case! Look at the first page of these instructions, and you
will see how to set up your Running head.
· There must be a page number on the title page that is right
justified. It is included in the header

· Your paper title appears on the title page. This is usually 12
words or less, and the first letter of each word is capitalized. It
should be descriptive of the paper (For this paper, you should
use the title of the article you are critiquing. The paper title can
be the same title as in the Running head or it can differ – your
choice)
· Your name will appear on the title page
· Your institution will appear on the title page as well
· For all papers, make sure to double-space EVERYTHING and
use Times New Roman font. This includes everything from the
title page through the references.
· This is standard APA format. ALL of your future papers will
include a similar title page
2. Summary of the Article: 1 ½ page minimum, 3 pages
maximum - 14 points)
An article critique should briefly summarize, in your own
words, the article research question and how it was addressed in
the article. Below are some things to include in your summary.
· The summary itself will include the following: (Note – if the
article involved more than one experiment, you can either
choose to focus on one of the studies specifically or summarize
the general design for all of the studies)
1. Type of study (Was it experimental or correlational? How do
you know?)
2. Variables (What were the independent and dependent
variables? How did they manipulate the IV? How did they
operationally define the DV? Be specific with these. Define the
terms independent and dependent variable and make sure to
identify how they are operationally defined in the article)
3. Method (What did the participants do in the study? How was
it set up? Was there a random sample of participants? Was there
random assignment to groups?). How was data collected (online,
in person, in a laboratory?).
4. Summary of findings (What were their findings?)
· Make sure that:

1. The CAPS portion of your running head should also appear
on the first page of your paper, but it will NOT include the
phrase “Running head” this time, only the same title as the
running head from the first paper in ALL CAPS. Again, see the
example paper. There is a powerpoint presentation on using
Microsoft Word that can help you figure out how to have a
different header on the title page (where “Running head” is
present) and other pages in the paper (where “Running head” is
NOT present). You can also find how-to information like this
using youtube!
2. If you look at the header in pages 2 through 5 (including
THIS current page 4 that you are reading right now!), you will
see “Running head” omitted. It simply has the short title
(ARTICLE CRITIQUE PAPER INSTRUCTIONS) all in caps,
followed by the page number.
3. The same title used on the title page should be at the top of
the page on the first actual line of the paper, centered.
4. For this paper, add the word “Summary” below the title, and
have it flush left. Then write your summary of the article below
that.
3. Critique of the study: 1 ½ pages minimum - 3 pages
maximum - 16 points)
1. This portion of the article critique assignment focuses on
your own thoughts about the content of the article (i.e. your
own ideas in your own words). For this section, please use the
word “Critique” below the last sentence in your summary, and
have the word “Critique” flush left.
1. This section is a bit harder, but there are a number of ways to
demonstrate critical thinking in your writing. Address at least
four of the following elements. You can address more than four,
but four is the minimum.
· 1). In your opinion, are there any confounding variables in the
study (these could be extraneous variables or nuisance
variables)? If so, explain what the confound is and specifically

how it is impacting the results of the study. A sufficient
explanation of this will include at least one paragraph of
writing.
· 2). Is the sample used in the study an appropriate sample? Is
the sample representative of the population? Could the study be
replicated if it were done again? Why or why not?
· 3). Did they measure the dependent variable in a way that is
valid? Be sure to explain what validity is, and why you believe
the dependent variable was or was not measured in a way that
was valid.
· 4). Did the study authors correctly interpret their findings, or
are there any alternative interpretations you can think of?
· 5). Did the authors of the study employ appropriate ethical
safeguards?
· 6). Briefly describe a follow-up study you might design that
builds on the findings of the study you read how the research
presented in the article relates to research, articles or material
covered in other sections of the course
· 7). Describe whether you feel the results presented in the
article are weaker or stronger than the authors claim (and why);
or discuss alternative interpretations of the results (i.e.
something not mentioned by the authors) and/or what research
might provide a test between the proposed and alternate
interpretations
· 8). Mention additional implications of the findings not
mentioned in the article (either theoretical or practical/applied)
· 9). Identify specific problems in the theory, discussion or
empirical research presented in the article and how these
problems could be corrected. If the problems you discuss are
methodological in nature, then they must be issues that are
substantial enough to affect the interpretations of the findings
or arguments presented in the article. Furthermore, for
methodological problems, you must justify not only why
something is problematic but also how it could be resolved and
why your proposed solution would be preferable.
· 10). Describe how/why the method used in the article is either

better or worse for addressing a particular issue than other
methods
4. Brief summary of the article: One or paragraphs (6 points)
· Write the words “Brief Summary”, and then begin the brief
summary below this
· In ONE or TWO paragraphs maximum, summarize the article
again, but this time I want it to be very short. In other words,
take all of the information that you talked about in the summary
portion of this assignment and write it again, but this time in
only a few sentences.
· The reason for this section is that I want to make sure you can
understand the whole study but that you can also write about it
in a shorter paragraph that still emphasizes the main points of
the article. Pretend that you are writing your own literature
review for a research study, and you need to get the gist of an
article that you read that helps support your own research across
to your reader. Make sure to cite the original study (the article
you are critiquing).
5. References – 1 page (4 points)
· Provide the reference for this article in proper APA format
(see the book Chapter 14 for appropriate referencing guidelines
or the Chapter 14 powerpoint).
· If you cited other sources during either your critique or
summary, reference them as well (though you do not need to
cite other sources in this assignment – this is merely optional IF
you happen to bring in other sources). Formatting counts here,
so make sure to italicize where appropriate and watch which
words you are capitalizing!
6. Grammar and Writing Quality (6 points)
· Few psychology courses are as writing intensive as Research
Methods (especially Research Methods Two next semester!). As
such, I want to make sure that you develop writing skills early.
This is something that needs special attention, so make sure to

proofread your papers carefully.
· Avoid run-on sentences, sentence fragments, spelling errors,
and grammar errors. Writing quality will become more
important in future papers, but this is where you should start to
hone your writing skills.
· We will give you feedback on your papers, but I recommend
seeking some help from the FIU writing center to make sure
your paper is clear, precise, and covers all needed material. I
also recommend asking a few of your group members to read
over your paper and make suggestions. You can do the same for
them!
· If your paper lacks originality and contains too much overlap
with the paper you are summarizing (i.e. you do not paraphrase
appropriately or cite your sources properly), you will lose some
or all of the points from writing quality, depending on the
extent of the overlap with the paper. For example, if sentences
contain only one or two words changed from a sentence in the
original paper, you will lose points from writing quality.
Please note that you do not need to refer to any other sources
other than the article on which you have chosen to write your
paper. However, you are welcome to refer to additional sources
if you choose.
7. Self-Rating Rubric (10 points). On canvas, you will find a
self-rating rubric. This rubric contains a summary of all the
points available to you in this paper. You must submit your
ratings for your own paper, using this rubric (essentially, you’ll
grade your own paper before you hand it in). You will upload
your completed rubric to the “article critique rubric” assignment
on Canvas.
· Please put effort into your ratings. Do not simply give
yourself a 50/50. Really reflect on the quality of your paper and
whether you meet all the criteria listed.
1. If it is clear that you have not reflected sufficiently on your
paper (e.g., you give a rating of 2/2 for something that is not

included in your paper), you will lose points.
· This does not mean that you are guaranteed whatever grade
you give to yourself. Instead, this will help you to 1) make sure
that you have included everything you need to include, and 2)
help you to reflect on your own writing.
· In fact, we will use this very same rubric when we grade your
paper, so you should know exactly what to expect for your
grade!
Other guidelines for the article critique papers
1. 1). Pay attention to the page length requirements – 1 page for
the title page, 1.5 pages to 3 pages for the summary, 1.5 pages
to 3 pages for the critique, one or two paragraphs for the brief
summary, and 1 page for the references page. If you are under
the minimum, we will deduct points. If you go over the
maximum, we are a little more flexible (you can go over by half
page or so), but we want you to try to keep it to the maximum
page.
1. 2). Page size is 8 1/2 X 11” with all 4 margins set one inch
on all sides. You must use 12-point Times New Roman font.
1. 3). As a general rule, ALL paragraphs and sentences are
double spaced in APA papers. It even includes the references,
so make sure to double space EVERYTHING
1. 4). When summarizing the article in your own words, you
need not continually cite the article throughout the rest of your
critique. Nonetheless, you should follow proper referencing
procedures, which means that:
3. If you are inserting a direct quote from any source, it must be
enclosed in quotations and followed by a parenthetical reference
to the source. “Let’s say I am directly quoting this current
sentence and the next. I would then cite it with the author name,
date of publication, and the page number for the direct quote”
(Winter, 2013, p . 4).
0. Note: We will deduct points if you quote more than once per
page, so keep quotes to a minimum. Paraphrase instead, but

make sure you still give the original author credit for the
material by citing him or using the author’s name (“In this
article, Smith noted that …” or “In this article, the authors
noted that…”)
3. If you choose to reference any source other than your chosen
article, it must be listed in a reference list.
1. 5). Proofread everything you write. I actually recommend
reading some sentences aloud to see if they flow well, or getting
family or friends to read your work. Writing quality will
become more important in future papers, so you should start
working on that now!
If you have any questions about the articles, your ideas, or your
writing, please ask. Although we won’t be able to review entire
drafts of papers before they are handed in, we are very willing
to discuss problems, concerns or issues that you might have.

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