Psychology, 2010, 1, 80-87
doi:10.4236/psych.2010.12011 Published Online June 2010 (
Copyright © 2010 SciRes. PSYCH
The Effect of Gender on Cognitive Structuring:
Who are More Biased, Men or Women?
Yoram Bar-Tal1, Maria Jarymowicz2
1Department of Nursing, School of Health Professions, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; 2Faculty
of Psychology, Warsaw University, Warsaw, Poland.
Received May 6th, 2010; revised May 25th, 2010; accepted June 3rd, 2010.
The effect of gender on the use of cognitive structuring (CS) is examined in three studies (n = 356). Study 1 showed that
Israeli men use less diagnostic information (display more confirmation bias) than Israeli women. Study 2 demonstrated
that Polish adolescent male but not female were influenced by implicit cues in a judgment task a Study 3 showed that
the correlation between trait anxiety and the state anxiety measures, in first degree relatives of patients in a cardiac
intensive care unit in Israel, was significantly higher for Israeli men than for women. According to the findings of the
three studies, women use cognitive structuring to a lesser degree than men do.
Keywords: Gender, Cognitive Structuring, Confirmation Bias, TSAI, Self Reference Effect
1. Introduction
Ample evidence demonstrates the existence stereotypes
about gender differences: men are more rational than
women, while women are more emotional, intuitive and
biased [1]. Meyers-Levy [2] has hypothesized that indeed
men and women use different information processing
strategies. However, the direction of the difference she
hypothesizes is quite contrary to the stereotypes. In her
Selectivity Hypothesis Meyers-Levy [2] theorizes that
men are considered to be “selective processors” who
often do not engage in comprehensive processing of all
available information before rendering judgment. Instead,
they seem to rely on various heuristics in place of detailed
information processing. These heuristics involve a cue or
cues that are highly available and salient and conver-
gently imply a particular inference. Women, on the other
hand, are considered to be “comprehensive processors”
who attempt to assimilate all available information be-
fore rendering judgment.
Despite the importance of the issue and the general in-
terest in gender differences, very limited effort has been
made to examine the validity of the Meyers-Levy [2]
hypothesis. Among the few studies that have examined
this question is Martin’s [3] study, which showed that
men and women are affected differently by promotional
messages. Women were found to process promotional
information more comprehensively than men, while men
focused on more peripheral information. This implies
that men use schema based heuristic strategies to process
information. Hayes, Allinson and Armstrong [4] found,
similarly, that women use more analytical (less intuitive)
information processing than men. Since the relevant studies
are so few and mostly performed in English speaking
countries, however, one can criticize their conclusions as
representing specific content areas, cultures, or method-
ologies rather than the general phenomenon they purport
to validate. For example, it is possible that shopping be-
havior are more related to the female role and that
women are therefore more motivated to invest the addi-
tional effort necessary for piecemeal processing. A more
effective examination of the validity of the Meyers-Levy
[2] hypothesis would center on examining the general
processing strategies characteristic of each gender and
would deploy multiple methods and content areas and in
different countries.
The present paper is designed to examine the effect of
gender on the use of cognitive structuring (CS) versus
piecemeal processing. Piecemeal processing involves
vigilant behavior, consisting of a bottom-up, systematic
and effortful search for relevant information, and the
evaluation and unbiased assimilation of that information.
CS has been defined as “the creation and use of abstract
mental representations (e.g., schemata, prototypes, scripts,
attitudes, and stereotypes)representations that are sim-
plified generalizations of previous experience” [5]. (The
conceptualization of the contrast between CS and piece-
meal is also described in terms of heuristic thinking and
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women 81
systematic processing [6]).
CS allows individuals to attain certainty most effi-
ciently because it is relatively automatic, effort-free and
faster than piecemeal processing [7,8]. It helps reach
certainty by filtering out inconsistent and/or irrelevant
information [9] and may make use of previously stored
information if needed to attain certainty as to the validity
of the inference [9,10]. CS is often identified with holis-
tic and top-down processing. These characteristics make
CS very effective. In this vein, Macrae and Bodenhausen
[11] suggested that using CS helps the perceiver to make
the world a meaningful, orderly, and predictable place.
In addition, however, to the very functional characteris-
tics of CS it also characterized with the use of crudely
differentiated categories, stereotypical thinking, and heu-
ristic, and biased cognition [12,13]. The association be-
tween CS and the use of biases is explained by the lower
utilization of the relevant information as well as the re-
lying on previously stored information that might be in
form of stereotypes or other schema [14].
This paper presents three studies designed to examine
the effect of gender on the use of CS in information proc-
essing, utilizing different methodologies and participants
from different age groups, cultures, and level of educa-
tion. The first study examines the preference for utilizing
available diagnostic information (rather than schema-
consistent information). Specifically, participants were
requested to judge the informative value of behavioral
cues that were either schema consistent or inconsistent. It
is assumed that the extent of relative importance attrib-
uted to schema consistent and inconsistent information
represents CS. The second study examines the extent
participants used the self-schema to interpret neutral
stimulus, using implicit (rather than explicit measure-
ment). It is assumed that CS processing is manifested in
greater utilization of self-schema information in the
judgment task. Finally, the third study explores the effect
of gender on the relationship between state and trait
anxiety. It is assumed that trait-state relationship repre-
sents CS if the trait (self-schema) is used to interpret the
situation (the state characteristics). The authors hypothe-
size that in all operationalizations of CS in this paper,
men will exhibit a higher level of CS use than women
2. Study 1
Study 1 was designed to demonstrate that gender affects
the use of schema-inconsistent but diagnostic informa-
tion. The tendency to use or to avoid this type of infor-
mation has been studied extensively within the phe-
nomenon of confirmation bias. Confirmation bias is de-
fined as the tendency, when examining the validity of a
hypothesis, to prefer to corroborative rather than refuting
evidence [15]. Several types of confirmation bias have
been identified [15,16]. Study 1 focuses on only one, the
tendency to avoid examining rival hypotheses. The phe-
nomenon of confirmation strategies has been validated
[17-20] but other researchers claim that people use a di-
agnostic rather than a confirmation strategy in hypothesis
testing [16,21-24]. Thus, people are capable of using
both confirmatory and diagnostic strategies. We suggest
that confirmation bias is the result of a CS process that
allows people to achieve certainty with a low expenditure
of effort by mainly attending to schema-consistent in-
formation and ignoring schema-inconsistent or irrelevant
information. This theoretical reasoning is similar to that
of Kruglanski and Mayseless [25], that is, people who are
motivated to use CS tend to search for prototypical rather
than diagnostic (schema-inconsistent) information, where-
as people who are motivated to use piecemeal processing
do the opposite. Our hypothesis, therefore, is that women
will show greater preference for schema inconsistent and
diagnostic information than men show and so show less
confirmation bias.
2.1 Method
2.1.1 Participants
One hundred women and 136 men Israelis, all with uni-
versity education participated in the study. Their average
age was 39.05 years (SD = 10.03). There was no signifi-
cant difference between genders in terms of age or edu-
2.1.2 Measurements
Stimuli: Participants were presented, in random order,
with written impressions of two persons they had sup-
posedly just met, one honest, the other friendly. These
impressions functioned to create a hypothesis about the
target person. Each impression was followed by 15 in-
formation segments regarding the target person’s behav-
iors. Participants were requested to imagine that they
wanted to check whether their first impression was cor-
rect. They could do so by examining the list of behaviors
and rating each behavior on a six-point scale (from “In-
formation not important at all” (1) to “Very important
information” (6)). The list of behaviors consisted of five
prototypical items, i.e., items consistent with the impres-
sion, five diagnostic items, i.e., items inconsistent with
the impression, and five items irrelevant to the impres-
sion (distraction items). In the case of the honest person,
an example of a prototypical item might be “Delivered to
the police station money he/she found in the street”. An
inconsistent item was “Has an extramarital love affair
while repeatedly telling the spouse that he/she is faithful”.
An irrelevant item was “Lives in Ramat Hasharon” (a
town in Israel). In the case of the friendly target person,
an example of a prototypical item might be “Volunteered
to care for lonely older people”, an inconsistent item was
“Refused to talk with other participants on an organized
trip”, and an irrelevant item was “Reads Ma’ariv” (an
Israeli daily newspaper). Five judges had to validate the
Copyright © 2010 SciRes. PSYCH
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women
items by sorting them into one of three categories: rele-
vant and consistent with the hypothesis, relevant but di-
rectly refuting the hypothesis, and completely irrelevant
to the hypothesis. For each item to be included, at least
80% of the judges had to agree.
Based on the study participants’ responses to the items
regarding the two target persons, two indices were created
by averaging the 10 items in each category. The Cron-
bach’s alpha reliability of the hypothesis-consistent index
was α = 0.88, and of the hypothesis-inconsistent index α
= 0.86.
2.1.3 Procedure
Participants were approached at their place of employ-
ment by the researcher and asked to volunteer for a
decision-making study. The response rate was 84%. Upon
completion, participants were debriefed.
2.2 Results and Discussion
To examine the hypothesis that men use more CS and
therefore, will demonstrate more confirmation bias, a
confirmation bias index was created by subtracting the
inconsistent information index from the consistent infor-
mation index. Lower values on this new index implied a
lower showing of confirmation bias, i.e., the informative
value of inconsistent items is considered to be closer to
that of consistent items. A t-test showed that men’s con-
firmation bias (M = 1.43 SD = 1.09) was significantly
higher than women’s (M = 1.09 SD = 0.96) (t(234) =
2.52, p < 0.01), which supported the study hypothesis
that women tended to use cognitive structuring less than
The conclusion of this study contradicts other studies
that reported lack of effect of gender on confirmation
bias. Marsh and Hanlon [26], for example, reported that
man do not differ in the extent of searching information
consistent with a given hypothesis. In contrast, Chung
and Monroe [27] found that female participants rated
inconsistent information as more important than male
participants did. It is possible that the explanation for the
contradicting results is in the method of operationaliza-
tion of the concept of confirmation bias. In the present
study, by virtue of using the confirmation bias index that
reflects both schema consistent as well as schema incon-
sistent information preference, we can conclude that the
results of Study 1 demonstrate that women use less con-
firmation bias (and therefore, less CS) than men do.
3. Study 2
Study 1 demonstrated that women are more sensitive to
schema-inconsistent information than men and so use CS
less. However, the authors noted that Study 1’s outcome
variables consisted of an explicit measure that could have
influenced the results. For example, Skov and Sherman
[23] suggest that asking participants about the utility of
various kinds of available information (exactly what was
done in Study 1) focuses the participants’ attention on the
diagnosticity of that information. Perhaps the women
complied more with the instructions than the men. To
cover this possibility, a more implicit and non-obtrusive
method was needed. In Study 2, therefore, we tested our
hypothesis examining the Self Reference Effect (SRE)
[28] on the implicit level of information processing. Studies
on the SRE show specific, universal rules of information
processing about the self [29,30]. One of them leads to
positivity bias [31] which may displayed in overestimation
of positive traits, one possess, and under- estimation of
negative ones.
In the present study, to measure SRE effect, we used
the implicit priming paradigm of Murphy and Zajonc
[32]. The original method consist neutral, novel, unfa-
miliar targets (like Chinese ideograms or hexagrams) sub-
liminally primed with the affective stimulus – partici-
pants have to interpret meaning of targets and they are
not aware of the influence of implicit cues on their
judgments. Błaszczak [33,34] made a modification using
affective primes, and requesting participants to guess if a
given Chinese represents a trait characteristic for the self.
Because the self is more accessible in memory than
other cognitive structures it is an important source for the
interpretation of ambiguous cues. For example, Candinu
and Rothbart [35] have demonstrated that participants
used self-knowledge to give meaning to their novel and
unfamiliar situation (for similar results, see Otten &
Bar-Tal [36]). Study 2 referred to the fact that valence is
represented as an attribute of the self-schema. The study
was designed, therefore, to examine the extent to which
gender affects the tendency of respondents to associate
the self with implicit signals of valence. We hypothesized
an interaction effect in which since men use CS more
than women do, the prime valence would be connected
with the self more among them (stronger effect of the
valance of the implicit traits) than among women.
3.1 Method
3.1.1 General Design
The study had two phases. The first aimed to provoke
activation of the self-schema. Participants were requested
to describe themselves using 20 positive and negative
traits on a seven-point scale. In the second, a Blaszczak
[33] modification of the implicit priming paradigm [32]
was introduced. We presented participants with neutral
stimuli—hexagrams—as symbols of human different
traits. Each hexagram was primed on a subliminal level
with positive and negative words—the same 20 traits
used earlier. Participants were requested to make judg-
ments as to what extent each target stimuli represented
trait relevant to the self. Thus, the independent variables
in the study were the valance of the priming and the
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The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women 83
gender of the participant.
3.1.2 Participants
The participants were Polish high-school junior year
students, 16 boys and 14 girls who volunteered for the
3.1.3 Instruments
Self-descriptive adjectives: The self-descriptive ques- tion-
naire comprised 20 adjectives, 10 positive (e.g., “loyal”,
“creative”, “efficient”) and 10 negative (“lazy”, “naïve”,
“quarrelsome”), selected from a representative list of per-
sonal descriptions, constructed and validated in Polish by
Lewicka [37]. We selected adjectives to achieve a small
variance of valence within each category (negative and
positive) and a number of letters between six and eight.
For each adjective, participants had to rate themselves
from “Much less than others” (1) to “Much more than
others” (7).
Priming procedure: Using a PC with Pentium 750
MHZ processor with a 17” monitor and the SuperLab Pro
v.1.04 program, each adjective was presented to partici-
pants subliminally with 75 ms exposure time.
Target stimuli: After each adjective had been presented
subliminally, participants were presented with a neutral
stimulus (Chinese hexagrams) for 1000 ms. Before start-
ing, participants were told “Hexagrams are symbols from
the Chinese philosophy of nature. You will be presented
with hexagrams representing different human traits. Your
task is to assess to what extent the hexagram presented
on the screen symbolizes a trait that you possess”. To
mask primes, hexagrams appeared in the same location
on the screen as the primed adjective. Primes and hexa-
grams were presented in random and counter-balanced
order. Participants responded by pressing a number key
on a keyboard, ranging from 1 (“definitely NOT ME”) to
5 (“definitely ME”). Two variables were calculated
based on participants’ responses: the average of the re-
latedness to the self of 10 estimates of the hexagrams
primed with positive traits (α = 0.87) and 10 with nega-
tive ones (α = 0.85).
3.1.4 Procedure
After obtaining the approval of the high school authori-
ties to conduct the study, it was presented to the junior
year students as research into impression formation and
human intuition. Students were assured that participation
is strictly anonymous. Volunteers were tested individu-
ally. All students that were requested agreed to partici-
pant in the study.
The first stage was for participants to complete a self-
descriptive questionnaire. Then they were presented with
two pictures of groups of young people of both genders.
In the first picture, participants had to guess, from their
posture of the people, who were in romantic relationships.
In the second picture, participants had to guess who earned
the most money. The point of these two tasks was to
convince participants that the study was designed to ex-
amine human intuition. After the priming procedure, the
target stimuli appeared on the screen. The following se-
quence was followed in each trial: a fixation dot ap-
peared on the screen accompanied by a sound; the posi-
tive or negative priming trait appeared subliminally, fol-
lowed by hexagrams; participants responded to the ques-
tion that appeared on the screen asking how characteris-
tic the trait, symbolized by a given hexagram, was of
them. The initial eight trials consisted of hexagrams
without priming and were used for training. The actual
data stage consisted of 20 trials. Upon completion, par-
ticipants were debriefed.
3.2 Results and Discussion
To test the study hypothesis of which women will be less
influenced by the primed valance, a 2 × 2 within-between
ANOVA was performed, with gender as a ‘between’
factor and the valence of the priming word as a ‘within’
factor. A significant main effect of the valence of the
priming words was found: hexagrams in positively
primed words were rated as more relevant to self (M =
3.04 SD = 0.49) than those in negatively primed words
(M = 2.82 SD = 0.58) (F(1,28) = 4.01, p = 0.05). In addi-
tion, the analysis yielded a significant interaction (F(1,28)
= 4.02, p = 0.05). Table 1 presents the cell means and
shows that priming had a greater effect on men than on
women. The a posteriori Tukey/b test showed a signifi-
cant priming effect on men but not on women. These
results can be interpreted as supporting the study hy-
pothesis. However, the lower impact of the priming on
women may also be attributable to the women’s lower
self-esteem, that is, to a stronger association between self
and negative valence in women than in men. To test this
possibility another 2 × 2 within-between ANOVA was
performed on the positive and negative traits participants
ranked themselves at the beginning of the study. Results
showed only a main valence effect for the adjectives:
positive adjectives (M = 4.45, SD = 0.81) were judged as
more relevant to the self than negative traits (M = 3.63,
SD = 0.59) (F(1,28) = 14.82, p < 0.01). Since neither
gender nor gender-by-valence interaction achieved sig-
nificance, it indicates that the men in this experiment did
not differ a priori from the women in their self-esteem.
Therefore, the second explanation, women’s lower self-
esteem, can be discounted.
Table 1. Implicit self reference effect as a function of
Positive Negative
M 3.01 (± 0.55) 2.58 (± 0.58)
F 3.07 (± 0.44) 3.07 (± 0.48)
1The full range of the scale is 1-5.
Copyright © 2010 SciRes. PSYCH
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women
Similar results were obtained using different manipu
lations of the independent variables (i.e. visual ratherse-
mantic implicit priming) and different operationalization
of the dependent variable (use of RT) (for review see
Jarymowicz [38]). In all studies reviewed by her, there
were significant differences between the positive and
negative conditions for men but not for women.
Study 2 provides further evidence for the validity of
Levi-Mayers hypothesis. It adds to the findings of study
1 by using completely different research paradigm (explicit
in Study 1, versus implicit-in Study 2), with participants
of different age (adults vs. adolescents), and nationality
(Israeli vs. Polish) groups.
4. Study 3
One implication of women using CS less than men is that
a woman’s reaction to, and interpretation of, situations is
less affected by her personality traits. This is because
personality traits can be viewed as knowledge structures
(schema) which predispose individuals to use them in
interpreting new information. As with other types of
pre-existing schema (e.g., expectations, attitudes, and
stereotypes [39-42], personality traits can be viewed as
cognitive structures [29,43-45]. For example, when com-
paring attitudes and traits, Sherman and Fazio [44] re-
viewed research regarding how one’s character traits
affect perception of and expectations about others and
how these perceptions guide behavior in a trait-consistent
manner. It can be argued, therefore, that the extent to
which people are affected by their personality traits repre-
sents different degrees of use of cognitive structuring. To
demonstrate this claim we chose to examine the relation-
ship between trait and state anxiety. The choice of anxi-
ety is based on the fact that state and trait anxiety are
used more often than any other state-trait characteristic.
Thus, we suggest that the relationship between trait and
state anxiety represent CS because trait anxiety creates a
negative bias in the processing of social information,
especially in highly self-relevant situations where the self
feels threatened. Similarly, it can be suggested that cog-
nitive structuring is related to the effect of trait anxiety
on a person’s emotional distress in a fear-arousing situa-
Study 3 examined the effect of gender on relationships
between state and trait anxiety, psychological distress and
well-being among the first-degree relatives of patients in a
cardiac intensive care unit. On the assumption that men use
CS more than women, it was hypothesized that trait anxiety
in men is a better predictor of state anxiety, psychological
distress and well-being than in women.
4.1 Method
4.1.1 Participants
The sample comprised 44 male and 46 female first-degree
relatives (spouse, sibling, child) of patients in a cardiac
intensive care unit in Israel, who agreed to volunteer for
the study (The response rate of the participants was 70%).
Participants’ mean age was 43.04 years (SD = 13.57) and
mean years of schooling was 14.72 (SD = 3.50). The
patients’ state of health, assessed by a physician in the
Unit and ranked on a scale ranging from 1 “very mild” to
6 “very severe”, averaged 3.59 (SD = 1.35). There were
no significant relationships between participants’ gender
and their characteristics (age, schooling, and category of
kinship with the patient).
4.1.2 Instruments
State and trait anxiety: The Hebrew version [46] of the
State-Trait Anxiety Inventory (STAI) [47] consists of 40
items: 20 measure trait anxiety and 20 state anxiety. The
instructions preceding the trait measure direct partici-
pants to describe their feelings in general, while those of
the state measure direct participants to describe their
present feelings. In Study 3, the reliability scores for the
state and trait anxiety scales were α = 0.93 and α = 0.88,
Psychological distress and well-being. Were measured
by the Mental Health Inventory [48], comprising 38 items:
14 measure psychological well-being and 24 measure
psychological distress. Questions refer to the participant’s
life during the past week. Responses to the items are
given on a six-point scale from 1 “complete approval” to
6 “complete disapproval” of the item. The reliability
scores for psychological distress and well- being were α
= 0.91 and α = 0.90, respectively.
4.1.3 Procedure
The study was conducted in a large university hospital in
Israel. The study was approved by the Helsinki committee
of the hospital. Participants were told that the study ex-
amined factors relating to the coping of individuals with
the hospitalization of their first degree relatives in a car-
diac intensive care unit. Participants were interviewed
individually on the second or third day of their relative’s
admission to the Unit. Participants were assured that the
data would serve research purposes only and that their
participation or completion of the study would not affect
the patient’s treatment. Upon completion, participants
were debriefed.
4.2 Results and Discussion
To test the study hypothesis that the correlations coeffi-
cients between trait anxiety and the participants’ reports
of their state are higher for men than for women, we cal-
culated the correlation coefficients for each gender. Ta-
ble 2 presents the correlation matrix of the study vari-
ables separately for each gender. The correlation between
trait anxiety and the measures of state anxiety, distress,
and well-being was significantly higher for men than
women (U = 2.08, p < 0.05; U = 2.57, p = 0.01; and U =
.82, p < 0.07, respectively). Thus, this study validates the 1
Copyright © 2010 SciRes. PSYCH
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women 85
Copyright © 2010 SciRes. PSYCH
Table 2. Correlation matrix of variables in study 3 as a function of gender
Men Women
1 2 3 4 1 2 3 4
1. State Anxiety
2. Trait Anxiety 0.61** 0.25
3. Psychological Distress 0.60** 0.63** 0.55** 0.36*
4. Well Being –0.37* –0.74** –0.83** –0.33* –0.31* –0.72**
1 2.34 1.73 2.30 4.43 2.64 1.76 2.57 4.07
SD 0.66 0.44 0.75 0.87 0.67 0.40 0.81 0.92
* = p < 0.05 ** = p < 0.01; 1) The full range of both STAI scales is 1-4 and that of the other scales is 1-6
hypothesis that men use schematic thinking more than
women do.
Few studies demonstrated similar effects. For example,
Bar-Tal Gardosh, and Barnoy [49] demonstrated that the
traits of negative affectivity and perception of control,
measured before a coronary artery bypass graft, predicted
significantly better symptom reporting after surgery for
men than for women. Also, Eli, Bar-Tal, Fuss and Korff
[50] found that pain tolerance of men is more affected by
their trait anxiety than that of women (for similar results,
see also, Edwards, Auguston and Fillings [51]) Similarly,
Shepperd and Kashani [52] found that the components of
hardiness (commitment and control) moderated the effect
of stress on both physical and psychological symptoms in
men. In women, hardiness components did not interact
with stress in the prediction of health outcomes. However,
Although the STAI is frequently used, little research has
been done on the effect of gender on the state-trait rela-
tionship. Novy, Nelson, Goodwin and Rowzee [53] are
among the very few whose results are related to the ques-
tion. They found that the correlation among Caucasian in
the US men was higher (r = 0.85) than among women (r
= 0.65). Although the authors did not report whether the
difference was significant, it nevertheless is consistent
with our results.
5. General Discussion
The focus of this article has been gender differences in
the use of cognitive structuring. The three studies, de-
ploying very different methods, showed that women tend
to use less CS than men do. The studies not only func-
tioned as theoretical replications of each other but were
also supported by studies with more or less similar
methodologies. The data and findings of the three studies
clearly support the idea that men tend to use more CS
(and therefore use more cognitive biases) than women
Whether there is a difference between genders in their
accuracies or biases has been much researched but the
results are equivocal. Some studies report greater accuracy
and less bias in men than in women [54,55]. Other stud-
ies show men less accurate than women [56,57]. Yet
other studies show no gender difference in accuracy or
bias [58,59]. The common denominator of these diverse
studies is the use of outcomes to assess gender differences
in accuracy and bias. That is, the judgment of the par-
ticipant was compared to a given criteria (supposedly the
truth) and the greater the discrepancy between the judg-
ment and the criteria, the less accurate and more biased
the judgment was judged to be. It is possible that the di-
versity of answers to the question of gender differences
stem from this common feature. Accuracy of judgment
may be related to different skills or motivations rather
than to distortions of reality or biases [60-62].
Departing from this prescriptional approach, the present
study takes a descriptive approach to the question. It
examines whether there are gender differences in the
cognitive processes men and women tend to use. More
specifically, to what extent do men and women differ in
their use of piecemeal vs. CS. Its results indicate that
women tend to react more to the objective characteristics
of a stimulus, while men react more to pertinent pre-
existing schema, which influence their perception.
Before concluding, it is necessary to consider the possi-
bility that the gender differences reported in this paper
are the results of specific contents involved in the studies
(e.g., self-esteem), motivation and attention toward spe-
cific contents (interpersonal interaction). However, the
diversity of the contents and experimental paradigms in
this paper should be a reasonable answer to such threats.
The contents in Study 1 and Study 3 were not related to
self-esteem. Thus, in spite of the fact that participants’
self esteem was part of Study 2, it is not reasonable to
attribute the results of all three studies to the difference
in self esteem between men and women. Similarly it is
not reasonable to attribute the results mainly to differ-
ence between genders in the salience of health related
issues (that are in the base of Study 3), because the other
two studies do not utilize these contents. Likewise, it is
not reasonable to attribute the results to the specific age
or level of education of the participants because of the
diversity of these characteristic in the three studies.
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women
[1] S. Nemecek, “The Furor over Feminist Science,” Scien-
tific American, Vol. 276, No. 62, January 1997, pp.
[2] J. Meyers-Levy, “Gender Differences in Information
Processing: A Selectivity Interpretation,” In: P. Cafferata
and A. Tybout, Eds., Cognitive and Affective Responses
to Advertising, Lexington Press, Lexington, MA, 1989,
pp. 219-260.
[3] B. A. Martin, “The influence of gender on mood effects
in advertising,” Psychology and Marketing, Vol. 20, No.
3, 2003, pp. 249-273.
[4] J. Hayes, C. W. Allinson and S. J. Armstrong, “Intuition,
Women Managers and Gendered Stereotypes,” Personnel
Review, Vol. 33, No. 4, 2004, pp. 403-417.
[5] S. L. Neuberg and J. T. Newsom, “Personal need for
Structure: Individual Differences in the Desire for Simple
Structure,” Journal of Personality and Social Psychology,
Vol. 65, No. 1, 1993, pp. 113-131.
[6] A. W. Kruglanski and E. P. Thompson, “Persuasion by a
Single Route: A View from the Unimodel,” Psychologi-
cal Inquiry, Vol. 10, No. 2, 1999, pp. 83-109.
[7] M. B. Brewer, “A Dual Process Model of Impression
Formation,” In: T. K. Srull and R. S. Wyer, Eds., Ad-
vances in Social Cognition, Lawrence Erlbaum, New Jer-
sey, 1988, pp. 1-36.
[8] R. M. Shiffrin and W. Schneider, “Controlled and Auto-
matic Human Information Processing: II. Perceptual
Learning, Automatic Attending, and a General Theory,”
Psychological Review, Vol. 84, No. 1, 1977, pp. 127-190.
[9] S. T. Fiske and P. W. Linville, “What does the Schema
Concept Buy us?” Personality and Social Psychology
Bulletin, Vol. 6, No. 4, 1980, pp. 543-557.
[10] J. R. Anderson, “The Adaptive Nature of Human Cate-
gorization,” Psychological Review, Vol. 98, No. 3, 1991,
pp. 409-429.
[11] C. N. Macrae and G. V. Bodenhausen, “Social Cognition:
Thinking Categorically about Others,” Annual Review,
Vol. 51, No. 1, 2000, pp. 93-120.
[12] S. T. Fiske and S. E. Taylor, “Social Cognition,”
McGraw-Hill, Inc., New York, 1991.
[13] A. W. Kruglanski and D. M. Webster, “Motivated Closing
of the Mind: ‘Seizing’ and ‘freezing’,” Psychological Re-
view, Vol. 103, No. 2, 1996, pp. 263-283.
[14] A. W. Kruglanski and I. Ajzen, “Bias and Error in Human
Judgment,” European Journal of Social Psychology, Vol.
13, No. 1, 1983, pp. 1-44.
[15] J. Beattie and J. Baron, “Confirmation and Matching
Biases in Hypothesis Testing,” The Quarterly Journal of
Experimental Psychology, Vol. 40, No. 2, 1988, pp. 269-
[16] S. R. Evett, P. G. Devine, E. R. Hirt and J. Price, “The
role of the Hypothesis and the Evidence tn the Trait Hy-
pothesis Testing Process,” Journal of Experimental Social
Psychology, Vol. 30, No. 5, 1994, pp. 456-481.
[17] J. Baron, J. Beattie and J. C. Hershey, “Heuristics and
Biases in Diagnostic Reasoning: II. Congruence, Infor-
mation, and Certainty,” Organizational Behavior and
Human Decision Processes, Vol. 42, No. 1, 1988, pp. 88-
[18] R. B. Marom and B. Fischhoff, “Diagnosticity and Pseu-
dodiagnosticity,” Journal of Personality and Social Psy-
chology, Vol. 45, No. 6, 1983, pp. 1185-1195.
[19] J. Klayman and Y. Ha, “Hypothesis Testing in Rule Dis-
covery: Strategy, Structure, and Content,” Journal of Ex-
perimental Psychology: Learning Memory, and Cognition,
Vol. 15, No. 4, 1989, pp. 596-604.
[20] M. Snyder and W. B. Swann, “Hypothesis-Testing Proc-
esses in Social Interaction,” Journal of Personality and
Social Psychology, Vol. 36, No. 11, 1978, pp. 1202-1212.
[21] M. Bassok and Y. Trope, “People’s Strategies for Testing
Hypothesis about Another’S Personality: Confirmatory of
Diagnostic?” Social Cognition, Vol. 2, No. 12, 1984, pp.
[22] P. G. Devine, E. R. Hirt, and E. M. Gehrke, “Diagnostic
and Confirmation Strategies in Trait Hypothesis Testing,”
Journal of Personality and Social Psychology, Vol. 58,
No. 6, 1990, pp. 952-963.
[23] R. B. Skov and S. J. Sherman, “Information-Gathering
Processes: Diagnosticity, Hypothesis-Confirmatory Stra-
tegies, and Perceived Hypothesis Confirmation,” Journal
of Experimental Social Psychology, Vol. 22, No. 1, 1986,
pp. 93-121.
[24] Y. Trope and M. Bassok, “Information-Gathering Strate-
gies in Hypothesis-Testing,” Journal of Experimental So-
cial Psychology, Vol. 19, No. 6, 1983, pp. 560-576.
[25] A. W. Kruglanski and O. Mayseless, “Contextual Effects
in Hypothesis Testing: The Role of Competing Alternatives
and Epistemic Motivations,” Social Cognition, Vol. 6, No.
1, 1988, pp. 1-21.
[26] D. M. Marsh and T. J. Hanlon, “Seeing What We Want to
See: Confirmation Bias in Animal Behavior Research,”
Ethology, Vol. 113, No. 11, 2007, pp. 1089-1098.
[27] J. Chung and G. Monroe, “Gender Differences in Informa-
tion Processing: An Empirical Test of the Hypothe-
sis-Confirming Strategy an Audit Context,” Accounting
and Finance, Vol. 38, No. 2, 1998, pp. 265-79.
[28] T. B. Rogers, N. A Kuiper and W. S. Kirker, “Self-
Reference and the Encoding of Personal Information,”
Journal of Personality and Social Psychology, Vol. 35,
1977, pp. 677-688.
[29] H. Markus, “Self-Schemata and Processing Information
about the Self,” Journal of Personality and Social Psy-
chology, Vol. 35, No. 1, 1977, pp. 63-78.
[30] A. G. Greenwald and A. R. Pratkanis, “The Self,” In: R.S.
Wyer Jr. and T. K. Srull, Eds., Handbook of Social Cogni-
tion, Lawrence Erlbaum, Hillsdale, 1984, pp. 129-177.
[31] M. H. Kernis (Ed.), “Self-Esteem Issues and Answers: A
Sourcebook of Current Perspectives,” Psychology Press,
New York, 2006.
[32] S. T. Murphy and R. B. Zajonc, “Affect, Cognition and
Awareness: Affective Priming with Optimal and Sub op-
timal Stimulus Exposures,” Journal of Personality and
Social Psychology, Vol. 64, No. 5, 1993, pp. 723-739.
[33] W. Blaszczak, “W Poszukiwaniu Specyfiki Utajonego
Copyright © 2010 SciRes. PSYCH
The Effect of Gender on Cognitive Structuring: Who are More Biased, Men or Women 87
Copyright © 2010 SciRes. PSYCH
Ja,” Studia Psychologiczne, Vol. 39, No. 2, 2001, pp.
[34] W. Blaszczak, “O efektach odnoszenia do Ja afektu
wzbudzanego poza świadomością,” In: R. K. Ohme, Ed.,
Nieuświa-domiony afekt, Gdańskie Wydawnictwo Psy-
chologiczne, Gdańsk, 2007, pp. 157-163.
[35] M. R. Cadinu and M. Rothbart, “Self-Anchoring and
Differentiation Processes in the Minimal Group Setting,”
Journal of Personality and Social Psychology, Vol. 70,
No. 4, 1996, pp. 661-677.
[36] S. Otten and Y. Bar-Tal, “Self-Anchoring in The Minimal
Group Paradigm: The Impact of Need and Ability to
Achieve Cognitive Structure,” Group Processes and Inter-
group Relations, Vol. 5, No. 4, 2002, pp. 267-284.
[37] M. Lewicka, “Lista określeń do opisu właściwości czło-
wieka,” Przegl ąd Psychologiczny, Vol. 26, No. 6, 1983, pp.
[38] M. Jarymowicz, “O roznicach plciowych w prze- twarzaniu
informacji w warunkach wzbudzania afektu,” Czasopismo
Psychologiczne, Vol. 9, No. 3, 2003, pp. 231-242.
[39] J. Friedrich, “Primary Error Detection and Minimization
(PEDMIN) Strategies in Social Cognition: A Reinterpreta-
tion of Confirmation Bias Phenomena,” Psychological Re-
view, 1993, pp. 298-319.
[40] J. L. Hilton and W. von Hippel, “Stereotypes,” Annual
Review of Psychology, Vol. 47, No. 1, 1996, pp. 237-271.
[41] S. L. Neuberg, “Expectancy-Confirmation Processes in
Stereotype-Tinged Social Encounters: The Moderating
Role of Social Goals,” In: M. P. Zanna and J. M. Olson,
Eds., The Psychology of Prejudice: The Ontario Sympo-
sium, Lawrence Erlbaum, Hilsdale, 1994, pp. 103-130.
[42] Stangor and D. McMillan, “Memory for Expectancy-
Congruent and Expectancy-Incongruent Information: A
Review of the Social and Social Developmental Litera-
tures,” Psychological Bulletin, Vol. 111, No. 1, 1992, pp.
[43] Sedikides and J. J. Skowronski, “The Law of Cognitive
Structure Activation,” Psychological Inquiry, Vol. 2, No.
2, 1991, pp. 169-184.
[44] S. J. Sherman, and R. H. Fazio, “Parallels between Atti-
tudes and Traits as Predictors of Behavior,” Journal of
Personality, Vol. 51, No. 3, 1983, pp. 308-345.
[45] S. S. Smith, and J. F. Kihlstrom, “When is a Schema not a
Schema? The “big five’ Traits as Cognitive Structures,”
Social Cognition, Vol. 5, No. 1, 1987, pp. 26-57.
[46] Y. Y. Teichman and C. Melinak, “State-Trait Anxiety
Questionnaire: Hebrew-Language Guide for Testers,” 2nd
Edition, Psychology Department, Tel Aviv University,
Tel-Aviv, Israel, [In Hebrew], 1979.
[47] C. C. Spielberger, “Preliminary Manual for the State-Trait
Personality Inventory,” Human Resources Institute, Uni-
versity of South Florida, Tampa, 1980.
[48] C. T. Veit and J. E. Ware, “The Structure of Psychological
Distress and Well-Being in General Populations,” Journal
of Consulting and Clinical Psychology, Vol. 51, No. 5,
October 1983, pp. 730-42.
[49] Y. Bar-Tal, H. Gardosh and S. Barnoy, “The Differential
Effect of Perceived Control and Negative Affectivity as a
Function of Gender after Coronary Artery Bypass Graft
Surgery,” Sex Roles, Vol. 55, No. 11, 2006, pp. 853-859.
[50] I. Eli, Y. Bar-Tal, Z. Fuss and E. Korff, “Effect of Bio-
logical Sex Differences on the Perception of Acute Pain
Stimulation in The Dental Setting,” Pain and Research
Management, Vol. 1, No. 4, 1996, pp. 201-206.
[51] R. Edwards, E. M. Auguston and R. Fillingim, “Sex Spe-
cific Effects of Pain Related Anxiety on Adjustment to
Chronic Pain,” Clinical Journal of Pain, Vol. 16, No. 1,
2000, pp. 46-53.
[52] J. A. Shepperd and J. H. Kashani, “The Relationship of
Hardiness, Gender, and Stress to Health Outcomes in
Adolescents,” Journal of Personality, Vol. 59, No. 4,
1991, pp. 747-768.
[53] D. M. Novy, D. V. Nelson, J. Goodwin and R. D. Rowzee,
“Psychometric Comparability of the State-Trait Anxiety
Inventory for Different Ethnic Subpopulations,” Psycho-
logical Assessment, Vol. 5, No. 3, 1993, pp. 343-349.
[54] S. Mann, “Who Killed my Relative? Police Officers’
Ability to Detect Real-Life High-Stake Lies,” Psychology,
Crime and Law, Vol. 7, No. 2, 2001, pp. 119-132.
[55] Y. Bar-Tal, S. Barnoy and B. Zisser, “Whose Informational
Needs are Considered? A Comparison between Cancer Pa-
tients and Their Spouses’ Perception of their Own and
their Partners’ Knowledge and Informational Needs,” So-
cial Science and Medicine, Vol. 60, No. 7, 2005, pp. 1459-
[56] J. A. Hall, “Nonverbal Sex Differences: Communication
Accuracy and Expressive Style,” John Hopkins University
Press, Baltimore, 1984.
[57] S. Beyer, “Gender Differences in the Accuracy of Grade
Expectancies and Evaluations,” Sex Roles, Vol. 41, No. 3,
1999, pp. 279-296.
[58] H. Holling and F. Preckel, “Self-Estimates of Intelligence-
Methodological Approaches and Gender Differences,”
Personality and Individual Differences, Vol. 38, No. 3,
2005, pp. 503-517.
[59] D. A. Kenny and L. K. Acitelli, “Accuracy and Bias in
the Perception of the Partner in a Close Relationship,”
Journal of Personality and Social Psychology, Vol. 80,
No. 3, 2001, pp. 439-448.
[60] K. J. Klein, and S. D. Hodges, “Gender Differences, Mo-
tivation, and Empathic Accuracy: When it Pays to Under-
stand,” Personality and Social Psychology Bulletin, Vol.
27, No. 6, 2001, pp. 720-730.
[61] C. Lewin, G. Wolgers and A. Herlitz, “Sex Differences
Favoring Women in Verbal But Not in Visuospatial Epi-
sodic Memory,” Neuropsychology, Vol. 15, No. 2, 2001,
pp. 165-173.
[62] P. L. Ackerman, K. R. Bowen, M. E. Beier and R. Kanfer,
“Determinants of Individual Differences and Gender Dif-
ferences in Knowledge,” Journal of Educational Psy-
chology, Vol. 93, No. 4, 2001, pp. 797-825.