2 page article review psychology

2 page review… I have attached Both the Article and the page review instructions.

Article Review Assignments

The purpose of this assignment is to get you comfortable with reading and understanding scientific research articles. For this assignment, you will need to access the articles electronically through Blackboard Vista. On the main content page, you should see a folder labeled “Articles for Review.” Inside this folder are two or three articles. These are the ONLY articles that you may use for this assignment. Select ONE of these articles to review.

Read the article through once, to get the idea of what it is about. Then read it again, keeping in mind the review sections described below. Article reviews should be typed in 12pt Times New Roman Font, single-spaced. Your review should be between 2-3 pages, stapled. Each section should be clearly labeled as below and must be in outline format (follow this handout). Be sure to proofread for spelling and grammar.

Your review needs to include the following sections:

Reference

The reference of the article needs to be in APA style.

Study Design

For this portion of the article review, you need to specify what type of study was conducted.

a. State the type of study (correlational, experimental, longitudinal, etc).

b. Also include a brief overview of the purpose of the study (why did they do it).

Variables

Independent variables are things like the conditions participants are assigned to in an experimental study; predictor variables are the things the researchers use to predict an outcome but that can’t necessarily be manipulated (like self-esteem or education level) and are in a correlational or longitudinal study. Dependent or criterion variables are outcome variables; the term “dependent variable” refers specifically to outcomes in experimental studies whereas the term “criterion variable” refers to outcomes in correlational studies.

a. Specify whether it was an independent/predictor variable and/or a dependent/criterion variable in the study (correct labels).

b. Identify the independent/predictor and dependent/criterion variables in the study (name them).

Operational Definitions of Variables

These involve defining any terms or concepts that are central variables in the study. For example, if in the article you reviewed, stereotype threat was a predictor variable, it would be one term you would need to provide an operational definition for.

a. Operational definition of independent/predictor variable(s)

b. Operational definition of dependent/criterion variable(s)

Hypotheses

What did the researchers predict? What did they expect to happen? All studies have at least 1 hypothesis, and many have quite a few more than that. Remember that the study hypothesis will involve predictions about the variables.

a. Identify the hypotheses for the study.

Results

What are the main findings? You should have at least 1 result for each hypothesis. You also need to indicate whether the result supports or disconfirms a hypothesis.

a. What were the results/main findings?

b. Were these results consistent with the hypotheses?

c. Were these results consistent with past research?

Conclusions

A good place to look for conclusions is in the discussion section, usually toward the end of the article.

a. Interpretation of the results: What do these results mean in a broader sense? (In other words, what do the findings mean in the big picture? What do they imply about life in the real world?)

b. Briefly describe future directions for the line of research studied in the article.

Critique

Typically researchers acknowledge limitations to their own work (in the discussion section), but there may be some things that you notice that could be a problem for the study. For example, were the participants mostly women (so we don’t know if men would respond the same way)?

a. What are some of the limitations of the study identified by the researcher(s)? What could the researchers have done that would have made the study better?

b. What limitations did you find with the study? Identify and describe at least 2 limitations that are not mentioned by the researchers.

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Bulletin
Personality and Social Psychology

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782

The online version of this article can be found at:

DOI: 10.1177/014616720302900601

0

2003 29: 782Pers Soc Psychol Bull
Laurie T. O’Brien and Christian S. Crandall

Stereotype Threat and Arousal: Effects on Women’s Math Performan

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10.1177/0146167203252810 ARTICLE
PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN
O’Brien, Crandall / STEREOTYPE THREAT AND AROUSAL

Stereotype Threat and Arousal: Effects
on Women’s Math Performance

Laurie T. O’Brien
Christian S. Crandall
University of Kansas

Theories of arousal suggest that arousal should decrease perfor-
mance on difficult tasks and increase performance on easy tasks.
An experiment tested the hypothesis that the effects of stereotype
threat on performance are due to heightened arousal. The
authors hypothesized that telling participants that a math test
they are about to take is known to have gender differences would
cause stereotype threat in women but not in men. In the experi-
ment, each participant took two tests—a difficult math test and
an easy math test. Compared to women in a “no differences” con-
dition, women in the “gender differences” condition scored better
on the easy math test and worse on the difficult math test. Men’s
performance was unaffected by the manipulation. These data
are consistent with an arousal-based explanation of stereotype
threat effects. Data were inconsistent with expectancy, evalua-
tion apprehension, and persistence explanations of the stereotype
threat phenomenon.

Keywords: stereotype threat; arousal; gender; math

When people are members of a group that can be neg-
atively stereotyped in a social situation, they carry an
extra burden: their performance might well be inter-
preted in terms of the stereotype. Should the perfor-
mance be consistent with the stereotype (e.g., a woman
scoring poorly on a math test, an upper-class White man
being clumsy on the dance floor), the behavior serves to
confirm the stereotype in the eyes of the beholders; this
phenomenon has been labeled stereotype threat
(Spencer, Steele, & Quinn, 1999; Steele & Aronson,
1995). Stereotype threat has proven to be a robust phe-
nomenon, applying to a diverse set of groups, including
African Americans, White men, women, and people with
low socioeconomic status and social class (Aronson et al.,
1999; Leyens, Desert, Croizet, & Darcis, 2000; Quinn &
Spencer, 2001; Spencer et al., 1999; Steele & Aronson,

1995; Walsh, Hickey, & Duffy, 1999. See Steele, Spencer, &
Aronson, 2002, for a review.).

For a person to experience stereotype threat, she or
he need only to have knowledge that some people hold a
negative stereotype about their group. This knowledge
can make a person worried about being viewed
stereotypically, even when she or he does not endorse
the stereotype. Although the psychological state of ste-
reotype threat is an important issue (e.g., Aronson,
Quinn, & Spencer, 1998; Croizet & Claire, 1998; Lee &
Ottati, 1995; Oswald & Harvey, 2000-2001; Spencer et al.,
1999; Steele & Aronson, 1995), much of the research has
focused on the demonstration of the behavioral effects
of stereotype threat and the range of conditions when it
might occur (Aronson et al., 1999; Inzlicht & Ben-Zeev,
2000; Marx, Brown, & Steele, 1999; Quinn & Spencer,
2001; Stangor, Carr, & Kiang, 1998; Steele, 1997; Steele &
Aronson, 1998; Stone, Lynch, Sjomeling, & Darley,
1999).

In a typical stereotype threat experiment, participants
who are aware of being at risk for behaving consistently
with a negative stereotype (e.g., being poor at math, ath-
letics, academics, etc.) perform significantly more
poorly than participants who do not feel that they are
threatened by the stereotype. Removing stereotype
threat can have a large effect; Spencer et al. (1999)
erased gender differences in complex mathematics per-
formance by describing their math test as one that did
not produce gender differences, and Aronson et al.
(1998) eliminated racial differences in math perfor-
mance by presenting the test as “nondiagnostic.” In

782

Authors’ Note: Please address correspondence to Laurie T. O’Brien,
Department of Psychology, University of California, Santa Barbara, CA
93106; e-mail: obrien@psych.ucsb.edu.

PSPB, Vol. 29 No. 6, June 2003 782-789
DOI: 10.1177/0146167203252810
© 2003 by the Society for Personality and Social Psychology, Inc.

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these experiments, the removal of stereotype threat
completely removed group differences, suggesting that
many of the racial or gender group differences that
appear to characterize groups are in fact the result of ste-
reotype threat—an environmental challenge rather
than an essential difference.

The fact that stereotype threat harms task perfor-
mance on difficult tasks is well established (Aronson
et al., 1999; Croizet & Claire, 1998; Spencer et al., 1999;
Steele & Aronson, 1995). Although Steele and Aronson
(1995) argue that stereotype threat is most likely to
occur when the test is difficult, they acknowledge that in
the case of African Americans and the stereotype of intel-
lectual inferiority, the mere “act of taking a test pur-
ported to measure intellectual ability may be enough to
induce this threat” (p. 798). Thus, difficult tasks may not
be an essential component to the experience of stereo-
type threat.

Researchers have also argued that stereotype threat
can occur even when the task is not difficult.

A test need not be difficult for stereotype threat to occur.
Simply being in a situation where one can confirm a neg-
ative stereotype about one’s group—women simply sit-
ting down to the math test, for example, could be
enough to cause this self-evaluative threat. (Spencer
et al., 1999, p. 7)

Even when the task is easy, members of negatively stereo-
typed groups are in a predicament not faced by others.
“In situations where math skills are exposed to judg-
ment—be it a formal test, classroom participation, or
simply computing the waiter’s tip—women bear the ex-
tra burden of having a stereotype that alleges a sex-based
inability” (Spencer et al., 1999, p. 6).

Members of negatively stereotyped groups are fre-
quently in situations where the difficulty of the task is
unknown. Although it is certainly possible that threat is
attenuated once people learn that the task they are to
perform is easy, this knowledge may not completely
negate the early effects of the threat (e.g., Zillman,
1972).

How does stereotype threat lead to decreased perfor-
mance on difficult tasks? Steele and Aronson (1995)
found that African American participants under condi-
tions of stereotype threat showed increased activation of
stereotypes about African Americans and more self-
doubt than African Americans who were not under stereo-
type threat and White Americans. Steele and Aronson
argue that these findings are evidence of a disruptive
evaluation apprehension in stereotype-threatened par-
ticipants. Spencer et al. (1999) showed that stereotype
threat increased anxiety, but they did not find conclusive
evidence that anxiety, self-efficacy, or evaluation appre-

hension mediated the link between stereotype threat
and performance in spite of the fact that anxiety, self-effi-
cacy, and evaluation apprehension have been clearly
linked to decreased performance in other literatures
(e.g., Ashcraft, 2002).

Stereotype threat is not limited to low-status groups;
Aronson et al. (1999) showed that the performance of
White men on math was harmed when threatened with
stereotypes of Asian superiority in math, and Leyens
et al. (2000) showed that men experienced stereotype
threat on a task that involved affective processing. Steele
and Aronson (1995) suggested that stereotype threat
might be mediated by low performance expectations
(which could affect dominant and subordinate groups
equally) but Brown and Steele (1999, cited in Marx et al.,
1999) found that increasing performance expectations
of African Americans did not remove the effects of ste-
reotype threat.

The active ingredient in stereotype threat has not
been definitively identified. Because of the importance
of the phenomenon, and the complexity of social inter-
actions between groups in conflict, we suggest that ste-
reotype threat’s effect works through a variety of path-
ways. Any explanation of the phenomenon should
parsimoniously appeal to psychological processes that
are common to women and men, Blacks, Whites, and
Asians in the domain of mathematics, language, and
sports—in short, it should be based in fundamental and
common psychological processes. We suggest that one
common and powerful psychological process that might
contribute substantially to stereotype threat’s effects on
performance is heightened arousal. High levels of
arousal have been widely shown to interfere with com-
plex and difficult tasks (e.g., Davis & Harvey, 1992;
Markus, 1978; Spence, 1956; Zajonc, 1965, 1969) and
operating under the fear and anxiety of confirming a
negative stereotype, or being categorized as an exemplar
of a negative stereotype, is sufficient to create arousal.
High arousal should interfere with performance.

Does the arousal caused by stereotype threat impact perfor-
mance? In our view, arousal is heightened activity, primar-
ily in the sympathetic nervous system (SNS), that ener-
gizes behavior. Arousal, through activation of the SNS,
increases heart rate, systolic blood pressure, sweating,
and causes the release of epinephrine. Arousal is non-
specific and serves to energize behavior in a nondirective
way. For this reason, arousal enhances the emission of
dominant responses. When the task is complex or diffi-
cult, arousal will lead to an increased number of inap-
propriate responses, thereby creating a decrement in
overall performance. On the other hand, when the task
is simple, or well learned, arousal will lead to an
increased number of appropriate responses thereby
increasing overall performance (Bolles, 1967; Markus,

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1978; Spence, 1956; Weiner, 1985; Wright, Murray,
Storey, & Williams, 1997; Zajonc, 1965; Zillman, 1972).

Much of the research on stereotype threat is consis-
tent with an arousal explanation for stereotype threat
effects. Most research involving stereotype threat has uti-
lized difficult tasks (e.g., GRE verbal and math tests and
GMAT math tests). This research has shown that people
experiencing stereotype threat (and are presumably in a
higher state of arousal) do more poorly on difficult tests
(e.g., Aronson et al., 1999; Croizet & Claire, 1998;
Spencer et al., 1999; Steele & Aronson, 1995).

A study by Blascovich, Spencer, Quinn, and Steele
(2001) found that stereotype threat elevated blood pres-
sure in American Blacks. Black and White Americans
took an “intelligence test” while researchers measured
their cardiovascular activity. To enhance stereotype
threat, participants first watched a video of a White pro-
fessor who presented the test as “an intelligence test
developed at Stanford.” To reduce threat, a video with a
Black professor presented the test as racially unbiased.
Under conditions of stereotype threat, Blacks’ blood
pressure rose more quickly and to a higher level than
Whites, but under conditions of reduced threat, Blacks
did not have higher blood pressure than Whites. These
data suggest that stereotype threat creates arousal (see
Wright et al., 1997, for a similar finding).

One important implication of an arousal theory of ste-
reotype threat is that although performance on difficult
tasks should be harmed by arousal, performance on easy
or well-learned tasks should be enhanced. To date, only
Spencer et al. (1999) have paid close attention to the
relationship between task difficulty and stereotype
threat. They gave male and female participants an
extremely difficult test taken from the advanced GRE
exam in mathematics and a moderately difficult test
taken from the quantitative section of the GRE general
exam. Whereas threat reduced women’s performance
on the extremely difficult test, there was no difference
between women in the two conditions on performance
on the moderately difficult test. Unfortunately, this study
does not offer a good test of the arousal hypothesis
because it does not include a truly easy test. However, the
results from Spencer et al.’s (1999) Study 1 are consis-
tent with the arousal hypothesis; whereas arousal should
increase performance on easy tasks and decrease perfor-
mance on difficult tasks, it should not affect perfor-
mance on tasks of moderate difficulty such as the test
used in the Spencer et al. (1999) research.

Although there has not been a direct test of how ste-
reotype threat affects performance on easy tasks, there is
some research that is consistent with the arousal hypoth-
esis that threat should lead to increased performance on
easy tasks. Bielinski and Davidson (1998) analyzed math
competency tests of more than 10,000 eighth-grade stu-

dents and more than 5,000 ninth-grade students; they
found that men tended to perform better on the most
difficult items, whereas women tended to perform better
on the easiest items. This is the exact pattern of results an
arousal explanation would predict for women under
conditions of stereotype threat if one assumes that ste-
reotype threat is “in the air” (Steele, 1997).

Overview and hypotheses. We suggest that a substantial
active component of stereotype threat is increased
arousal. Because arousal harms performance on diffi-
cult tasks but improves performance on easy tasks, we
predict that when compared to conditions of no stereo-
type threat, people under stereotype threat will perform
more poorly on difficult tasks but they will improve on
easy tasks.

We conducted a study in which women were put in
conditions of stereotype threat or were put in conditions
that attenuated stereotype threat and then presented
them both difficult and easy math problems. We pre-
dicted that the stereotype of male superiority on math
would create stereotype threat for women only, and for
them only in the presence of purported gender differ-
ences. Arousal from this threat would decrease math
performance on difficult items and increase math per-
formance on easy items for women. Because men are not
at risk for confirming a negative stereotype about their
math ability, we predicted that the stereotype threat
manipulation would have no discernable effect on men’s
math performance, regardless of test difficulty. Statis-
tically, we predicted a three-way interaction between the
stereotype threat manipulation, participant gender, and
test difficulty.

Method

Participants. Participants in the experiment were 164
students (59 women, 105 men) enrolled in an introduc-
tory psychology class who participated in exchange for
partial course credit. The ethnic background of the par-
ticipants included 7 African Americans, 6 Asian Ameri-
cans, 4 Hispanics/Latinos, 2 Indians/Central Asians, 4
Native Americans, 137 Whites, and 4 people who indi-
cated that they were of mixed ethnicity.1 Participants
took part throughout two semesters in the spring and fall
of 1999.

Procedure. After participants arrived at the laboratory
and consented to participate in the study, the experi-
menter handed participants a packet of materials that
included tests of math ability. The cover sheet informed
the participants that the researchers were evaluating a
series of tests; the participants would be working on
mathematical tests.

The participants read that previous research had
sometimes “shown gender differences and sometimes

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shown no gender differences.” In the gender differences
condition, we used the same manipulation adopted in
previous studies (e.g., Spencer et al., 1999); participants
were told, “The test you are about to take has been shown
to produce gender differences.” Participants in the no
differences conditions were told, “The test you are about
to take has NOT been shown to produce gender differ-
ences.” Spencer et al. (1999) argued that participants
interpret information about gender differences in math
tests to mean that men outperform women—informa-
tion from debriefing suggested that our participants had
the same interpretation.

Participants then filled out a brief questionnaire
regarding their feelings prior to taking the tests. For the
last 94 participants, we added a self-report measure of
motivation and a five-item measure of evaluation appre-
hension (taken from Spencer et al., 1999). After filling
out this questionnaire, the experimenter told partici-
pants how much time that they would have to complete
the first test. One minute prior to the end of the test, the
experimenter informed participants that they had 1
minute left to complete the test. When time was up, the
experimenter asked the participants to stop working on
the test.

The same procedure followed for the subsequent
tests. All participants took three tests: a fairly easy test, a
fairly difficult test, and a very simple math test to mea-
sure effort and persistence (Biernat, 1989).2 The order
of the tests was counterbalanced between participants.
After completing the tests, participants were debriefed
and dismissed.

Materials. Participants in the study completed three
tests: an easy math test, a difficult math test, and a test to
measure math persistence. The easy test consisted of
three-digit multiplication problems; for example, multi-
plying 143 by 495. Participants were not allowed to use
calculators and were given 10 min to complete 20
problems.

The difficult test was 15 items from the quantitative
SAT. Questions were given in a five-option, multiple-
choice format and participants had 11 min to complete
the questions. An example is as follows:

If x2 + y2 = 2xy, the x must equal:

A. –1 B. 0 C. 1 D. –y E. y

The correct answer is E. Three items had more than
90% of the sample answering correctly across condition;
because the test was designed to be difficult, these items
were deleted. Scores were calculated by giving partici-
pants one point for each correct answer and correcting
for guessing by subtracting one fifth of a point for each
incorrect answer (Spencer et al., 1999).

The test to measure math persistence employs mental
math. Participants were instructed to answer addition
and subtraction problems in their head and write down
the answer. Participants were allotted 8 min to complete
24 questions. The mental math test requires some con-
centration and effort but is mathematically very easy,
involving only addition and subtraction. Previous
researchers (e.g., Biernat, 1989) have used the number
of answers that participants get correct on this test as a
measure of motivation, effort, and persistence.

Ninety-four participants also filled out measures of
motivation and evaluation apprehension prior to com-
pleting the tests. The motivation item asked participants
how motivated they were to perform well on the test. Par-
ticipants responded on a 100-point scale with 0 labeled
not at all motivated and 100 labeled extremely motivated. The
evaluation apprehension measure included five items
taken from Spencer et al. (1999). Items include: “If I do
poorly on this test, people will look down on me” and “If I
don’t do well on this test, others may question my ability”
(α = .75).

Results

Order effects. A mixed-model ANOVA with test-diffi-
culty as a within-subjects factor (easy vs. hard) and order,
sex, and condition as between-subjects factors found no
significant main effects or interactions of test order on
test performance. Order was deleted from further
analyses.

Effects of threat manipulation and gender on performance.
The main hypothesis test is the three-way interaction
between gender, threat manipulation, and math diffi-
culty. Characterizing a test as sensitive to gender differ-
ences should increase women’s performance on an easy
test, decrease women’s performance on a difficult test,
and leave men unaffected by test difficulty. To make test
scores comparable across test difficulty, we z transformed
participants’ test scores by subtracting the overall sample
mean from each participants’ score and dividing this
amount by the sample standard deviation (see Johnson,
2000).3 The data were submitted to a mixed-model
ANOVA; math difficulty (easy vs. hard) was a within-
subjects factor and gender and threat manipulation
(gender differences vs. no differences) were between-
subjects factors. This analysis revealed the predicted
three-way interaction between gender, threat, and test
difficulty, F(1, 160) = 5.46, p < .05. The pattern of means is displayed in Figure 1; it supports the arousal hypothe- sis. Compared to the no threat conditions, stereotype threat lowered difficult math per formance but improved easy math performance among women.

To investigate the nature of the interaction, we car-
ried out planned comparisons that offered a proper,
direct test of the hypothesis. On the easy test, women in

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the gender differences condition performed better (M =
+.20) than did women in the no differences condition
(M = –.25), t(57) = 1.82, p < .05, one-tailed, d = .47. Men’s performance on the easy test did not vary as a function of condition; men in the gender differences condition (M = .05) did not perform significantly different from men in the no differences condition (M = .00), |t| < 1, ns. No other relevant pairwise comparisons on the easy test were significant.

On the difficult math test, women in gender differ-
ences performed worse than women in no differences
(Ms = –.64, –.17, respectively), t(57) = 1.79, p < .05, one- tailed, d = .46. Men showed no difference by condition, |t| < 1. These results mimic the standard stereotype threat result; removal of threat improves performance on diffi- cult tasks for the stereotyped group but does not touch the unstereotyped.

Men outperformed women in the gender differences
condition on the difficult math test, t(160) = –3.81, p < .001, d = .82, and performed slightly better than women in no differences condition, t(80) = –1.85, p < .10, two- tailed, d = .39. The difference between men and women in the gender differences condition was more than twice the size of the difference between men and women in the no differences condition.

The ANOVA also revealed a significant main effect of
sex, F(1, 160) = 6.69, p < .05, a Sex × Test Difficulty inter- action, F(1, 160) = 10.02, p < .01, and a Condition × Test Difficulty interaction, F(1, 160) = 7.61, p < .05. The pat- tern of these effects is subsumed by the three-way interac- tion, and these effects are visible in Figure 1.

Subsidiary Analyses

Problems attempted versus accuracy. The manipulation
increased women’s scores on the easy math test and

decreased their scores on the difficult math test while
leaving the men unaffected. Is it possible that the manip-
ulation affected test scores simply because women under
threat attempted greater problems on the easy test and
fewer problems on the difficult test, or did the manipula-
tion affect participants’ accuracy? We planned and con-
ducted further analyses on the women’s data to deter-
mine whether accuracy or the number of problems
attempted contributed to differences in overall test
scores. To create a measure of accuracy for each partici-
pant, for the easy and the difficult tests we divided the
number of problems correct by the number of problems
attempted; this proportion score was transformed by tak-
ing the arcsine of participants’ proportion score (Cohen
& Cohen, 1975). To equate accuracy on both tests, the
analyses employed z scores. Because only female partici-
pants’ scores are examined in the subsidiary analyses,
participants’ accuracy scores were transformed by sub-
tracting the sample mean for women from each partici-
pant’s accuracy score and dividing this amount by the
sample standard deviation for women. Separate analyses
performed on accuracy scores without the arcsign trans-
formation and on accuracy scores transformed using the
overall sample means and standard deviations yielded
nearly identical results.

If arousal affects accuracy directly, rather than indi-
rectly, through greater effort and persistence (measured
by speed), then women in the gender differences condi-
tion should perform more accurately on the easy test
and less accurately on the difficult test, resulting in a two-
way interaction between test difficulty and threat manip-
ulation. The test of this hypothesis, a Test Difficulty ×
Threat Manipulation mixed-model ANOVA, yielded the
predicted two-way interaction, F(1, 57) = 11.27, p < .01. As expected, when the test was easy, women in the gen- der differences (M = +.21) condition were more accurate than women in the no differences condition (M = –.19). When the test was difficult, however, women in the gen- der differences condition (M = –.27) were less accurate than women in the no differences condition (M = +.25). To further explore these results, we tested the signifi- cance of the differences between the conditions; when the test was difficult, the difference between the two con- ditions was significant, t(57) = 2.04, p < .05, one-tailed, and when the test was easy, the difference between the two conditions was nearly significant, t(57) = 1.58, p = .06, one-tailed. Threat directly affected accuracy.

To test whether improved performance might be due
to enhanced effort due merely to greater numbers of
problems attempted, we analyzed the number of prob-
lems attempted using a Test Difficulty × Threat Manipu-
lation mixed-model ANOVA. This analysis did not yield
any significant effects, ps > .42. These results suggest that
stereotype threat enhances accuracy on easy problems,

786 PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN

-1

-0.75

–

0.5

–

0.25

0
0.25
0.5

Women
Gender

Difference

Women
No Difference

Men
Gender

Difference

Men
No Difference

Easy Test Hard Test

T
es

t
P

er
fo

rm
an

ce

Figure 1 Math performance of women and men on easy and difficult
math problems by stereotype threat condition.

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harms accuracy on difficult problems, and that these dif-
ferences are not a function of the number of problems
attempted but rather on improved performance.

Problem difficulty and effect size. All the problems on the
easy math test involved multiplication of three-digit
numbers and were of comparable difficulty. The prob-
lems on the difficult math test, however, were algebra
problems of varying difficulty. The percentage of partici-
pants answering a question correctly ranged from 28%
(difficult problem) to 93% (relatively easy problem).
Previous analyses have show that women in the no differ-
ences condition outperform women in the gender dif-
ferences condition on the difficult math test; the arousal
hypothesis suggests that this difference should grow
larger as problem difficulty increases. For men, any dif-
ferences between conditions should be unrelated to
problem difficulty.

To test this hypothesis, we examined “problem” as the
unit of analysis for all 15 problems included in the alge-
bra test. Problem difficulty was calculated by taking the
arcsine of the sample mean for each problem. To aid in
interpretation, scores were reverse-coded so that
increasing numbers reflect increasing difficulty; a prob-
lem difficulty score of “0” would indicate that all partici-
pants answered a problem correctly. Next, the effect of
the manipulation on each problem was calculated as the
effect size “d” such that positive scores indicated partici-
pants in the no differences condition were outperform-
ing participants in the gender differences condition and
negative scores indicated the reverse.

As predicted, the correlation between problem diffi-
culty and effect size for women was significant and posi-
tive, r = +.59, p < .03, whereas the correlation for men was nonsignificantly negative, r = –.03, p > .90. As Figure 2
shows, on the most difficult problems, female partici-
pants in the no difference condition far outscored
female participants in the gender differences. It is also
worthwhile to note that consistent with arousal predic-
tions, female participants in the gender differences con-
dition outperformed female participants in the no dif-
ferences condition on some of the easiest problems.4

Self-reports of motivation. Participants’ self-reports of
motivation measured prior to beginning the math tests
were submitted to a Sex × Manipulation ANOVA. This
analysis yielded no significant effects of self-reported
motivation on performance.

Ruling Out Nonarousal Explanations

Math persistence test. We tested whether the manipula-
tion had an effect on math persistence. Five participants
were deleted from this analysis for failure to follow direc-
tions. A Sex × Condition ANOVA performed on math
persistence test revealed no main effect of condition,

F(1, 155) = 1.08, ns. There was, however, a main effect of
sex, F(1, 155) = 12.42, p < .01, with men correctly answer- ing more items (M = 19.1) than women (M = 15.8). The interaction between sex and condition was not signifi- cant, F < 1. These data suggest that sheer persistence does not explain the improvement on easy items for women in the no differences condition.

Evaluation apprehension. We submitted the evaluation
apprehension scale to a Sex × Condition ANOVA. We
found a main effect of sex, F(1, 90) = 5.29, p < .05, with women (M = 3.0) showing higher levels of evaluation apprehension than men (M = 2.5). There was no effect of condition and no interaction, both Fs < 1. Evaluation apprehension was uncorrelated with performance on the difficult test, performance on the easy test, and the measure of persistence.

DISCUSSION

Women under stereotype threat performed better on
an easy math test and worse on a difficult math test than
women who were not exposed to stereotype threat.
These effects on women’s performance affected accu-
racy (performance) but not the number of problems
attempted (effort).

Research on arousal suggests that arousal enhances
performance on easy tasks and harms performance on
difficult tasks (Zajonc, 1965). Stereotype threat research
has reliably demonstrated that the threat of confirming a
negative stereotype harms performance on difficult
tasks. We replicated this effect but also showed that ste-
reotype threat can enhance performance on an easy task.
We have argued that the possibility of confirming a nega-
tive stereotype can cause arousal and that this arousal
accounts for stereotype threat effects on performance.
This hypothesis suggests that in addition to the well-

O’Brien, Crandall / STEREOTYPE THREAT AND AROUSAL 787

–

0.05

0
0.05

0.1

0.15

0.2

0.25

0.3

0.35

Problem Difficulty

P
er

fo
rm

an
ce

i
n

N
o

D
if

fe
re

nc
es

–
P

er
fo
rm
an

ce
i

n
G

en
de

r
D

if
fe

re
nc

es

Females Males

– 1 SD + 1 SD

Figure 2 Predicting effect size (d) for men and women as a function
of problem difficulty.

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established decrements in difficult tasks, stereotype
threat should improve performance on easy tasks. The
data supported the hypothesis. The present research
provides empirical support for Steele and Aronson’s
(1995) suggestion that arousal may be one causal mecha-
nism for stereotype threat effects (Easterbrook, 1959).

How does stereotype threat lead to decreased perfor-
mance on difficult tasks? Some have suggested that lower
self-confidence and performance expectancies can be
triggered by situationally relevant negative stereotypes
(e.g., Stangor et al., 1998). Past stereotype threat
researchers have been unable to effectively rule out the
possibility that stereotype threat is caused by reduced
expectancies. These data suggest that negative expectan-
cies are not solely responsible for stereotype threat
effects—negative expectancies should not elevate the
performance of stereotype-threatened individuals on
easy tasks; they should reduce them.

The current study also lends further evidence to the
notion that stereotype threat effects are not mediated by
evaluation apprehension. Evaluation apprehension was
unaffected by the manipulation—instead, we found only
that women had greater evaluation apprehension than
men. In addition, evaluation apprehension was
uncorrelated with performance in either condition.
Consistent with research reported by Marx et al. (1999),
the present research also suggests that the effects of ste-
reotype threat on performance are not due to differ-
ences in persistence; women’s math persistence did not
vary by condition.

Recent theorizing on motivation might explain why
women would perform poorly on difficult tasks and well
on easier tasks. According to Brehm’s theory of motiva-
tional intensity (Brehm, 1999; Brehm & Self, 1989),
when a woman encounters a math task she perceives as
manageable and expects success (such as multiplication
problems), she will have approximately as much motiva-
tion as needed to do well on the test. However, if the test
is perceived as difficult enough that she is unwilling or
unable to invest the effort required to succeed, then the
motivation levels created by the stereotype threat manip-
ulation will suffer sharp declines along with her perfor-
mance. Thus, motivation is affected by the difficulty of
the task. In the current study, participants’ self-reports of
motivation were measured before participants had
viewed the math test and when they had no knowledge of
the test difficulty. Therefore, the present research does
not offer a proper test of Brehm’s model—future
research should measure participants’ motivation after
learning of the task’s difficulty in order to examine a
motivational explanation of stereotype threat effects on
performance.

Stereotype researchers have raised the issue of
whether participants must be consciously aware of nega-

tive stereotypes and their relevance to a performance sit-
uation for stereotype threat effects to occur (Wheeler &
Petty, 2001). For example, the results of Levy’s (1996)
research with subliminal priming and older adults sug-
gest that negative stereotypes can affect behavior with-
out participants’ conscious awareness. Levy, Hausdorff,
Hencke, and Wei (2000) showed that priming negative
stereotype of aging can increase heart rate in older par-
ticipants even when participants are unaware that nega-
tive stereotypes have been primed. An arousal-based
explanation for the effects of stereotype threat on behav-
ior can parsimoniously account for circumstances under
which people are aware of negative stereotypes and situa-
tions in which stereotypes have been primed without
people’s conscious awareness.

Early thinking on stereotype threat was groundbreak-
ing because it suggested a situational explanation for
gender differences in mathematics abilities and racial
differences in standardized test scores—two findings
that have frequently been chalked up to genetic or other
biological bases. Stereotype threat research, including
the current investigation, suggests that the situation mat-
ters. Men and women may take math tests in the same
room but they are not in the same situation.

In an atmosphere laden with stereotypes of incompe-
tence, the present research suggests that people who are
members of negatively stereotyped groups are likely to
feel increased arousal. This arousal can interfere with
people’s ability to succeed at difficult tasks. Teaching
people skills to cope with arousal (e.g., relaxation tech-
niques, planning) may prove an effective weapon against
the detrimental effects of stereotype threat.

NOTES

1. Excluding participants who are not White had no effect on the
pattern of results.

2. Originally, a fourth, very difficult test was included with the items
from the math portion of the GMAT used by Spencer, Steele, and
Quinn (1999). When preliminary data analyses were run on the first 71
participants, we discovered that participants of both genders in both
conditions were scoring at a level no different from chance. Therefore,
we eliminated this test from the procedure for the subsequent 94 par-
ticipants. Spencer et al.’s participants were preselected for having
above-average ability in math, whereas the participants in the current
study were from general psychology classes. This fact most likely
explains why Spencer et al. found differences between conditions
using this test while we found all participants scoring near a chance
level.

3. Analyses using untransformed test scores yielded a nearly identi-
cal analysis. Transforming test scores for female participants using
females’ sample mean and standard deviation and for male partici-
pants using males’ sample mean and standard deviation also yielded a
nearly identical analysis, but by definition, eliminated any main effect
of sex. To compare men’s and women’s scores, we opted to transform
test scores using the overall mean and standard deviation.

4. We also calculated the correlations using only the 12 problems
that were retained in the final analysis of the test. The correlations were
nearly identical, r = +.57 for women, r = –.04 for men. Finally, we also cal-
culated separate problem difficulty scores for men and women. Again,
this had little effect on the analyses; the correlation between effect size

788 PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN

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and problem difficulty for female participants was r = +.58, for men, r =
–.03.

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Received October 15, 2002
Revision accepted November 7, 2002

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