2012. Vol.3, No.6, 441-446
Published Online June 2012 in SciRes (http://www.SciRP.org/journal/psych) http://dx.doi.org/10.4236/psych.2012.36062
Copyright © 2012 SciRes. 441
Confidence Appraisals Protect against Anxiety in Response
to a Transient Stressor
Alyson K. Zalta, Dianne L. Chambless
Department of Psychology, University of Pennsylvania, Philadelphia, USA
Received March 16th, 2012; revised April 10th, 2012; accepted May 12th, 2012
Research suggests that cognitive appraisals regarding personal control and existential beliefs are impor-
tant factors in the development of anxiety. These include mastery, generalized self-efficacy, locus of con-
trol, self-esteem, attributional style, and optimism. It remains unclear, however, whether these appraisals
add to the prediction of anxiety beyond what can be determined by individuals’ generalized tendency to
respond with anxiety in stressful situations. Moreover, researchers have begun to question whether meas-
ures of these appraisals represent truly distinct constructs or whether they are merely redundant aspects of
a broad higher order construct. We sought to determine the empirical overlap of these six cognitive ap-
praisals known to correlate with anxiety and whether identified factor(s) prospectively predicted anxiety
in response to an ecologically valid stressor. The appraisals loaded onto one factor reflecting confidence
in one’s coping ability. This confidence factor significantly predicted future state anxiety after controlling
for baseline levels of trait anxiety and other possible confounds. Results suggest that these cognitive ap-
praisals may be causally linked to anxiety and used to identify those at risk.
Keywords: Anxiety; Prospective; Longitudinal; Risk Factor; Cognitive Appraisal
Anxiety disorders pose a substantial burden to both individu-
als and society, affecting approximately 29% of individuals in
their lifetime (Kessler et al., 2005) and costing an estimated
$42.3 billion annually in 1990 (Greenberg et al., 1999). Con-
sidering the significant public health and economic burden
posed by anxiety disorders, researchers have called for greater
research efforts to elucidate etiological risk processes that can
inform intervention strategies (Zvolensky, Schmidt, Bernstein,
& Keough, 2006). Historically, behavioral learning approaches
served as the predominant etiological model for anxiety disor-
ders; however, these theories suffered criticism as it became
clear that this model could not account for the large degree of
individual variation in anxiety after fearful learning experiences
(Mineka, 1985). To resolve these concerns, contemporary
learning approaches incorporate the concept of diatheses that
make individuals more or less susceptible to stressful experi-
ences (Mineka & Zinbarg, 2006). These diatheses could repre-
sent a wide range of risk factors from genetic vulnerability to
experiential learning history.
Cognitive appraisals1 have been identified as a potentially
important factor in determining how individuals respond to
stress and the subsequent development of anxiety. According to
the stress-appraisal-coping framework proposed by Lazarus and
Folkman (1984), when an individual is faced with a stressor,
they make primary appraisals as to whether the stressor is a
negative threat or a positive challenge and secondary appraisals
regarding their ability to cope with the stressor. Anxiety is
thought to occur when primary appraisals of the significance of
a stressful event exceed secondary appraisals of one’s coping
ability. According to this theory, both person factors and situa-
tion factors influence individuals’ appraisals. Person factors
include individual’s beliefs about their personal control (i.e.,
the extent to which people are confident that they can control
the environment and important outcomes in their lives) and
existential beliefs (i.e., beliefs that enable people to create
meaning out of life and maintain hope). Individuals who per-
ceive themselves as having control over their outcomes and
who generally believe that their outcomes will be positive are
less likely to experience anxiety because they are more likely to
be confident in their copi ng ability and are less likely to view a
stressor as threatening.
Studies examining various populations have shown that indi-
viduals with a sense of control and optimism are less likely to
experience anxiety (e.g., Archer, 1979; Scheier, Carver, & Bri-
dges, 2001). Moreover, evidence suggests that measures of
perceived control and optimism prospectively predict psycholo-
gical distress following major life stressors (Bárez, Blasco,
Fernández-Castro, & Viladrich, 2009; Ben-Zur & Zeidner,
1988; Dew et al., 1997; Dew et al., 2004; Dew et al., 1994;
Gurung, Dunkel-Schetter, Collins, Rini, & Hobel, 2005; Sch-
eier, Carver, & Bridges, 2001; van Jaarsveld, Ranchor, Sander-
man, Ormel, & Kempen, 2005; Windsor, Anstey, Butterworth,
Luszcz, & Andrews, 2007). These studies indicate that cogni-
tive appraisals assessing one’s personal sense of control and
hope for the future may be important causal diatheses for anxi-
ety. However, the majority of longitudinal studies have exam-
ined these appraisals as predictors of anxiety without control-
ling for preexisting levels of trait anxiety. It is possible that
these appraisals do not add any predictive value beyond what is
accounted for by individuals’ general tendency to respond with
anxiety in stressful situations. If this is the case, then the as-
1We use the term cognitive appraisals to refer to constructs that represent
stable ways of thinking about oneself, the world, and the future that affect
esponding (Clark & Beck, 2010).
A. K. ZALTA, D. L. CHAMBLESS
sessment of cognitive appraisals would not provide incremental
information as to who is likely to develop anxiety, even though
they might still contribute to the development of the chronic
tendency to be anxious.
Researchers have also begun to question whether different
cognitive appraisal measures that assess personal control and
optimism are truly distinct or whether they are redundant as-
pects of a broad higher order construct (cf. Judge, Locke, &
Durham, 1997). Although it appears at face value that measures
assessing a sense of control (e.g., mastery, self-efficacy),
self-worth (e.g., self-esteem), and positive hope for the future
(e.g., optimism) are separate constructs, it is possible that these
traits may be empirically indistinguishable. For example, Judge
and colleages (2002) showed that self-esteem, neuroticism,
locus of control, and generalized self-efficacy form a single
latent factor and reveal poor discriminant validity. By contrast,
Scheier and colleagues (1994) showed that optimism continues
to predict depression after controlling for the effects of self-
esteem and self-mastery. Using different terminology to iden-
tify the same construct within various domains can be detri-
mental because researchers fail to consider these alternate lite-
ratures to inform their research and may engage in redundant
efforts. However, it is equally problematic to combine seem-
ingly similar traits that are in fact distinct constructs because
this adds error to data analysis and obscures accurate interpreta-
tion. For example, investigators may conclude that findings in
the field are inconsistent when in fact the target variable reflects
multiple unique concepts.
To address these concerns, we sought examine the latent
structure underlying six cognitive appraisals known to predict
anxiety including measures that assess personal control and
positive expectancies: mastery, generalized self-efficacy, locus
of control, attributional style, self-esteem and optimism. Al-
though it is true that other appraisals may fit into the stress-
appraisal-coping framework, these six constructs were selected
for investigation because they all have well-validated measures
that have been widely used in research on anxiety. We then
sought to examine whether any identified factor(s) predicted
future anxiety after controlling for individuals’ general ten-
dency to respond to stressors with anxiety (i.e., trait anxiety).
According to Lazarus and Folkman’s theory (1984), cogni-
tive appraisals not only impact individuals who experience a
major life stressor, but also influence how people respond to the
hassles that they experience in their daily life. Moreover, re-
search suggests that measures of hassles, or more minor daily
stressors, are better predictors of psychological symptoms than
measures of life events (Monroe, 1983). Thus, we sought to
examine whether cognitive appraisals play an important role in
determining how individuals respond to the common stressors
they are likely to face. Evidence suggests that for college stu-
dents, testing situations are an important source of stress and
anxiety (Souza, Samaraweera, & Frye, 2009). We measured
levels of state anxiety among college undergraduates in the 24
hours prior to a psychology exam to determine the role of cog-
nitive appraisals in predicting anxiety in this salient and ecolo-
gically valid context. The longitudinal design of this study en-
abled us to control for preexisting levels of trait anxiety to es-
tablish whether cognitive appraisals create vulnerability for
future anxiety independent of the general tendency to be an-
xious. Because it is plausible that actual (as opposed to per-
ceived) lack of ability contributes to students’ concerns about
their performance and thereby their anxiety, we also examined
the contribution of Scholastic Aptitude Test (SAT) scores as a
potentially confounding variable.
Participants and Procedure
Participants were undergraduates enrolled in Introduction to
Psychology, Abnormal Psychology, or Social Psychology at the
University of Pennsylvania during the Spring and Fall semes-
ters of 2008. The overall sample (N = 337) included 132 men
and 205 women ranging in age from 18 to 28 years old (M =
19.3, SD = 1.4). The racial composition of the sample was
58.5% White, 25.2% Asian, 5.9% Latino, 5.3% African Ame-
rican, 0.3% American Indian or Alaskan Native, 0.3% Native
Hawaiian or Pacific Islander, and 4.5% Other or unknown.
After providing informed consent, participants completed
two sets of online computer questionnaires. Those who com-
pleted both surveys received research credit to meet require-
ments for their undergraduate psychology course. At Time 1,
students completed the six cognitive measures as well as a mea-
sure of trait anxiety and provided their SAT scores. This initial
survey was completed at least two weeks prior to the students’
scheduled psychology exam for the class in which they were
enrolled. Students were re-contacted 24 hours prior to their
scheduled psychology exam to complete the Time 2 survey,
which included a measure of state anxiety. Only students who
completed the Time 2 survey before their scheduled exam time
were included in the final sample so as to capture their anxiety
about a future event. Of the 337 students included in the base-
line sample, 38 were lost to follow-up. This study was ap-
proved by the Human Subjects Committee of the University of
Pennsylvania’s Institutional Review Board.
Demographic and Course Information. At baseline, partici-
pants were asked to report their year in school, undergraduate
major, SAT scores, parents’ educational level, and how moti-
vated they were to do well in their psychology course on a
7-point Likert-type scale (from not at all motivated to extremely
motivated). At follow-up, students were asked to use the same
scale to indicate how motivated they were to do well on the
exam and to report how many other exams they had that week.
On average, students reported being highly motivated to do
well in their psychology course (M = 5.91, SD = 1.12) and
highly motivated to do well on their psychology exam (M =
5.86, SD = 1.21); on both motivation questions, over two-thirds
of students reported either a 6 or 7.
Attributional Style Questionnaire (ASQ; Peterson et al., 1982).
The ASQ is composed of 12 different hypothetical situations,
consisting of 6 good events and 6 bad events. Individuals are
asked to rate whether they see each event as caused by internal
versus external, stable versus unstable, and global versus spe-
cific causes. Composites of internal, stable, and global attribu-
tions are created separately for positive and negative events,
and the final summary score represents the difference between
the composite scores for positive and negative events. High
scores represent more beneficial attributional styles. Internal,
stable, and global attributions for negative events are associated
with anxiety (e.g., Ahrens & Haaga, 1993). Cronbach’s alpha in
the current sample was .80 for positive events and .75 for nega-
Copyright © 2012 SciRes.
A. K. ZALTA, D. L. CHAMBLESS
Generalized Self Efficacy Scale (GSE; Schwarzer & Jeru-
salem, 1995). The GSE is a 10-item scale designed to assess
“the belief in one’s competence to cope with a broad range of
stressful or challenging demands” (Luszczynska, Scholz, &
Schwarzer, 2005: p. 439). Studies have consistently demon-
strated a relationship between higher levels of generalized self-
efficacy and better physical and mental health (Luszczynska et
al., 2005). Cronbach’s alpha was .87.
Life Orientation Test-Revised (LOT-R; Scheier et al., 1994).
The Life Orienta tion Test was de veloped to assess individual dif-
ferences in dispositiona l optimism or the gene ralized expecta ncies
of good versus bad outcomes. The revised version (LOT-R) in-
cludes 10 items with 6 scored questions and 4 filler items. This
measure is consistently correlated with measures of physical and
psychological well-being (Scheier & Carver, 1992). Cronbach’s
alpha in the current sample was .80.
Rosenberg Self-Esteem Scale (RSE; Rosenberg, 1965). This
scale is the most commonly used measure of self-esteem, designed
to assess an individual’s global positive or negative attitude to-
wards the self. Respondents are asked to rate themselves on 10
items, such as “I feel that I have a number of good qualities” on a
scale from 1 (strongly disagree) to 5 (strongly agree). There are
considerable data to support the validity of this scale (e.g., Gray-
Little, Williams, & Hancock, 1997). Research indicates that low
self-esteem prospectively predicts anxiety (Lee & Hankin, 2009).
Cronbach’s alpha in the current sample was .90.
Rotter’s Locus of Control Scale (LOC; Rotter, 1966). The
LOC is a 29-item forced-choice scale in which individuals are
asked to select from two options reflecting internal or external
locus of control. Individuals with a high internal locus of con-
trol believe that events result primarily from their own behavior
and actions. Those with a high external locus of control believe
that powerful others, fate, or chance primarily determine events.
High scores represent high levels of externality. External con-
trol scores have been found to correlate with higher levels of
anxiety in a variety of sample populations (Archer, 1979).
Kuder-Richardson 20 coefficient in this sample was .73.
Self-Mastery Scale (SMS; Pearlin & Schooler, 1978). The
SMS is a widely used measure that assesses “the extent to
which people see themselves as being in control of the forces
that importantly affect their lives” (Pearlin, Menaghan, Lieber-
man, & Mullen, 1981: p. 340). The scale contains 7 items rated
on a 4-point scale from 1 (strongly disagree) to 4 (strongly
agree). The measure has demonstrated the ability to longitudi-
nally predict treatment outcome for patients with panic disorder
and agoraphobia (Bowen, South, Fischer, & Looman, 1994).
Cronbach’s alpha in the current sample was .80.
State-Trait Anxiety Invent ory (Spielberger, Gorsuch, Lushene,
Vagg, & Jacobs, 1983). Trait anxiety refers to a stable tendency
to experience anxiety in anticipation of seemingly threatening
situations. State anxiety refers to transient emotional arousal and
apprehension. These constructs are measured separately with 20
statements each. The trait anxiety scale (STAI-T), measured at
baseline, asks participants to report how they generally feel.
The state anxiety scale (STAI-S), measured at follow-up, asks
respondents how they feel “right now, at this moment.” Re-
search has demonstrated that the STA I - T i s u s e f u l f o r i d en t i fyi n g
individuals with clinical levels of anxiety and the STAI-S is a
sensitive indicator of changes in transitory anxiety (Spielberger et
al., 1983). The STAI-T is also a strong predictor of state levels
of anxiety (e.g., r = .46 in the present sample). In the current
sample, Cronbach’s alpha was .92 for the STAI-T and .94 for
Before conducting the primary analyses, we first examined
whether demographic variables and potential confounds were
associated with state anxiety at Time 2. Correlations were cal-
culated for continuous variables, independent samples t-tests
were calculated for binary variables, and regressions using
dummy variables were calculated for nominal variables with
more than two categories. The following variables were unre-
lated to state anxiety: age, year in school, semester the data
were collected, which psychology course students were en-
rolled in, whether they were a psychology major, father’s edu-
cational status, mother’s educational status, motivation to do
well in the course, motivation to do well on the test, and the
number of days between baseline and follow-up assessments.
All effects were small. Notably, total SAT scores were unre-
lated to state anxiety in the 24 hours prior to a psychology exam
(r = .05, p = .50).
Several other variables demonstrated significant relationships
with state anxiety at follow-up. Women reported higher state
anxiety (t(293) = –2.66, p = .008, d = –.31) compared to men,
and Asians reported higher state anxiety (t(291) = –2.96, p
= .003, d = –.39) compared to Whites. The number of other
tests that participants had in the same week was also associated
with state anxiety (r = .12, p = .04). These three variables were
controlled in prediction analyses.
Additional tests demonstrated that those who were lost to
follow-up did not differ from those who participated in the
follow-up assessment on any demographic variables.
The six measures were assessed using Bartlett’s chi-square
criteria (Geweke & Singleton, 1980); this test was significant (p
< .001), rejecting the likelihood that the variables are uncorre-
lated and indicating that factor analysis is appropriate with this
dataset. A principal factor analysis was then conducted to de-
termine the latent structure of these cognitive appraisal vari-
ables. This analysis resulted in a single factor (eigenvalue =
2.56) with all scales loading onto the first factor (all factor
loadings .40). No scales loaded on any additional factors (all
factor loadings < .20) and the eigenvalue for the second factor
was 0.06. Thus a single common factor was determined to be
the best solution. This factor appears to represent general con-
fidence in oneself and the future, that one is worthy and capable
of achieving success and that good things will come from life.
To capture this factor in a single measurement, a factor score
was calculated using a regression scoring method with a single
factor solution. The means, standard deviations, correlation
matrix, and factor structure are presented in Table 1.
Longitudinal Prediction of State Anxiety
We then sought to determine whether this confidence con-
struct is an important prospective predictor of anxiety. The
correlation between the factor score and Time 2 state anxiety
revealed a medium to large effect (r = –.43, p < .0001). A mul-
tiple regression was then conducted predicting Time 2 state
anxiety from the following predictors: Time 1 trait anxiety, sex,
Copyright © 2012 SciRes. 443
A. K. ZALTA, D. L. CHAMBLESS
Copyright © 2012 SciRes.
Descriptive statistics, correlations, and factor structure of six cognitive appraisal measures.
Mean SD SMS GSE LOC ASQ RSE LOT-R Factor loading Communality
SMS 21.97 3.11 .67 –.48 .38 .65 .68 .72 .54
GSE 31.48 4.27 .56 –.43 .49 .57 .55 .69 .48
LOC 12.05 4.07 –.37 –.34 –.41 –.33 –.44 –.47 .25
ASQ 3.04 2.87 .30 .40 –.31 .49 .52 .54 .32
RSE 21.17 5.11 .55 .50 –.27 .41 .71 .73 .55
LOT-R 14.62 4.05 .54 .46 –.34 .41 .60 .73 .54
Notes: SMS = Self-Mastery Scale; GSE = Generalized Self-Efficacy Scale; LOC = Locus of Control; ASQ = Attributional Style Questionnaire; RSE = Rosenberg
Self-Esteem Scale; LOT-R = Life Orientation Test-Revised. Zero-order correlations are reported below the diagonal. Disattenuated correlations are reported above the diagonal.
Asian ethnicity, the number of other tests participants had in the
same week at Time 2, and the factor score. Trait anxiety and
other covariates were first entered in the model, the factor sc ore
was then entered in the model in a second block to determine
the incremental predictive validity of this factor. The results of
these analyses are presented in Table 2. The overall regression
model was significant (p < .0001), explaining 26.7% of the
variance in Time 2 state anxiety. The confidence factor score2
significantly added to the prediction of state anxiety after con-
trolling for Time 1 trait anxiety and other possible confounds.
Hierarchical multiple regression of Time 1 variables predicting state
anxiety at Time 2.
Block 1 Sex .135** .257***
Other tests .139**
Trait anxiety .318***
Block 2 Factor score –.171* .011*
Discussion Notes: N = 293. For sex, male = 0, female = 1. represents the standardized betas
with all variables entered into the model. R2 represents the amount of incre-
mental variance explained by each block of variables. Other tests = number of
other tests students had that week; †p < .10, *p < . 05, **p < .01, ***p < .001.
Results indicated that the six cognitive appraisals assessed in
this study were all indicators of a single higher order factor
which we describe as confidence in one’s coping ability and the
future based on the framework proposed by Lazarus and Folk-
man (1984). The latent association among these measures sug-
gests that researchers should consider these alternate research
literatures to aid in the accumulation of findings and avoid re-
dundant research efforts. Investigators should especially look to
these other literatures when a paucity of studies exists using a
given construct. Although investigators may be wary of inte-
grating studies that utilize different terms, our data suggest that
empirically, this may be no different from integrating studies
that use different measures of the same construct. Judge and
colleagues (2002) reported that meta-analytic correlations be-
tween self-esteem and generalized self-efficacy were similar to
or even exceeded typical correlations between different mea-
sures of the same construct. Thus, investigators should consider
building off of rather than replicating research conducted with
one of these cognitive appraisals.
that individuals’ intellectual ability is less important in deter-
mining anxiety than a subjective sense of one’s ability to cope.
These findings suggest that cognitive appraisals not only play
an important role in emotional responses to major life events,
but also predict more transient daily anxiety. Our findings also
indicate that these cognitive appraisals are not merely a reflec-
tion of chronic anxiety, but rather make a unique contribution
to the prediction of future anxiety in response to minor stress.
The factor score only predicted a small incremental portion
of the variance in state anxiety (1.1%) after controlling for trait
anxiety and other predictors, bringing into question whether
this factor makes a meaningful contribution even though it is
statistically significant. Our stringent analytic approach gives
priority to trait anxiety and the other predictors in accounting
for the variance in state anxiety. It is also likely that our analy-
sis underestimates the importance of the confidence factor, be-
cause these cognitive appraisals should contribute to develop-
ment of chronic levels of trait anxiety. Given that this factor
predicts transient state anxiety responses under these rigorous
testing conditions with trait anxiety statistically controlled, it is
likely that confidence appraisals are not only significant but
also meaningful as predictors of responses to stress.
Having established this latent factor, we then sought to de-
termine whether these variables prospectively predicted state
anxiety in the 24 hours prior to an undergraduate psychology
exam, a salient and common stressor for college students. Re-
sults showed that the factor score had a moderate to large asso-
ciation with later state anxiety and prospectively predicted state
anxiety above and beyond the contribution of prior levels of
trait anxiety and potential confounds. Examination of the stan-
dardized betas indicates that the confidence factor was the se-
cond largest predictor of state anxiety after trait anxiety and
provided a greater contribution to the prediction of state anxiety
than biological sex, a well known risk factor for anxiety. By
contrast, SAT scores were unassociated with anxiety, indicating
An important question to consider is how the cognitive ap-
praisals represented in the confidence factor may reduce risk
for anxiety. According to the framework proposed by Lazarus
and Folkman (1984), these appraisals ultimately influence an
individual’s psychological resilience to threat through the en-
gagement of coping strategies. For example, if one expects bad
things to happen, then the only way to reduce negative emo-
tions in response to a threat is to engage in avoidance, whereas
if one has a general sense that things will turn out well, one will
2The factor scor e was al so a sig nif ican t pred ict or of anxi ety i n th e reg res sion
model when calculated with unit weighting of th e six mea sur es.
A. K. ZALTA, D. L. CHAMBLESS
be able to approach threats and engage in active coping strate-
gies. Taylor and colleagues (2008) showed that psychosocial
resources (which include optimism, mastery, and self-esteem)
did not influence individuals’ detection of threat, but enhanced
individuals’ ability to inhibit threat responses. Thus, it is possi-
ble that individuals with confidence are able to more effectively
manage threats once they are detected by promoting effective
Our findings suggest that the cognitive appraisals assessed in
this study may be used to identify those at risk for future anxi-
ety and that improving these cognitive appraisals through in-
terventions may be an effective strategy for enhancing indi-
viduals’ coping responses and decreasing anxiety. That is,
knowing that a person is chronically anxious is an effective
predictor of response to a specific threat, but it does not point to
preventive psychosocial interventions for anxiety. Previous re-
search showed that increases in control-related beliefs signifi-
cantly mediated anxiety and depressive symptom prevention for
at-risk undergraduates randomly assigned to an 8-week cogni-
tive-behavioral workshop (Seligman, Schulman, & Tryon,
2007). Our findings suggest that early intervention with at-risk
individuals may be beneficial given that these appraisals have
an impact on emotional responses to life’s hassles, which are
known to be important predictors of psychological well-being
(Monroe, 1983). The empirical overlap among the six cognitive
measures also suggests that interventions targeting any of these
appraisals should help to buffer against anxiety, whether bol-
stering optimism or self-esteem through cognitive restructuring
or increasing a sense of mastery or self-efficacy through expo-
A number of limitations should be considered when inter-
preting the results of this study. First, our results are consistent
with a causal model in which cognitive appraisals lead to the
development of anxiety; however, this does not rule out the
possibility of a bi-directional relationship between these con-
structs or third variables that may account for this relationship.
More extended prospective research and experimental studies
are needed to increase confidence in these findings. Second, we
also cannot establish whether state anxiety reported at Time 2
was necessarily provoked by the psychology exam, although
the correlation between the number of exams and state anxiety
suggests that the anxiety was exam-related. Certainly this is a
disadvantage of using a more naturalistic stressor; however, it is
likely that this would weaken rather than enhance our chances
of finding systematic variance in state anxiety. Third, because
we assessed responses to a single, relatively mild stressor, it
remains unclear whether these cognitive dispositions represent
risk factors for clinical levels of pathology. Fourth, we have
discounted the role of intellectual ability, as measured by the
SATs, as a predictor of exam anxiety. However, the SAT range
in a sample of Ivy League students is limited, and these results
might differ in a more heterogeneous population. Finally, it is
possible that additional cognitive measures not assessed in the
current study should be included as part of this latent confi-
Despite these limitations, the current study has several im-
portant strengths. We examined anxiety in the context of a sa-
lient and ecologically valid stressor, which helps to increase our
understanding of how these cognitive dispositions function to
predict individuals’ anxiety in response to more common
stressors in daily life. The prospective nature of these data also
suggests that this latent construct can be used to identify those
at risk for anxiety and may be a viable target for intervention.
Future studies should test the boundaries and meaning of this
latent factor by examining more disparate cognitive appraisals
and determining how this factor is associated with the engage-
ment of coping strategies. Better understanding of the mecha-
nisms that contribute to anxiety should enhance our ability to
intervene effectively. The current study represents one step to-
wards this goal, demonstrating that cognitive appraisals are not
only associated with anxiety, but also likely play a role in the
development of anxiety in daily real-world settings.
The authors wish to thank Paul McDermott for statistical
Ahrens , A. H., & Haaga, D. A. F. (1993). The specificity of attribu-
tional style and expectations to positive and negative affectivity, de-
pression, and anxiety. Cognitive Therapy and Research, 17, 83-98.
Archer, R. P. (1979). Relationships between locus of control and anxi-
ety. Journal of Personality Assessment, 43, 617-626.
Bárez, M., Blasco, T., Fernández-Castro, J., & Viladrich, C. (2009).
Perceived control and psychological distress in women with breast
cancer: A longitudinal study. Journal of Behavioral Medicine, 32,
Ben-Zur, H., & Zeidner, M. (1988). Sex differences in anxiety, curios-
ity, and anger: A cross-cultural study. Sex Roles, 19, 335-347.
Bowen, R., South, M., Fischer, D., & Looman, T. (1994). Depression,
mastery and number of group sessions attended predict outcome of
patients with panic and agoraphobia in a behavioural/medication pro-
gram. Canadian Journal of Psychiatry, 39, 283-288.
Clark, D. A., & Beck, A. T. (2010). Cognitive therapy of anxiety disor-
ders: Science and practice. New York: Guilford Press.
Dew, M. A., Becker, J. T., Sanchez, J., Caldararo, R., Lopez, O. L.,
Wess, J. et al. (1997). Prevalence and predictors of depressive, anxi-
ety and substance use disorders in HIV-infected and uninfected men:
A longitudinal evaluati o n . Psychological Medic in e , 27, 395-409.
Geweke, J. F., & Singleton, K. I. (1980). Interpreting the likelihood of
ratio statistic in factor models when sample size is small. Journal of
American Statistical Associatio n, 75, 133-137.
Gray-Little, B., Williams, V. S. L., & Hancock, T. D. (1997). An item
response theory analysis of the Rosenberg self-esteem scale. Person-
ality and Social Psychology Bulletin, 23, 443-451.
Gurung, R. A. R., Dunkel-Schetter, C., Collins, N. J., Rini, C., & Hobel,
C. J. (2005). Psychosocial predictors of prenatal anxiety. Journal of
Social and Clinical P s ych olo gy , 24, 497-519.
Judge, T. A., Erez, A., Bono, J. E., & Thoresen, C. J. (2002). Are
measures of self-esteem, neuroticism, locus of control, and general-
ized self-efficacy indicators of a common core construct? Journal of
Personality and Social P s y chology, 83, 693-710.
Judge, T. A., Locke, E. A., & Durham, C. C. (1997). The dispositional
causes of job satisfaction: A core evaluations approach. Research in
Organizational Behavior, 19, 151-188.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping.
New York: Springer.
Lee, A., & Hankin, B. L. (2009). Insecure attachment, dysfunctional
attitudes, and low self-esteem predicting prospective symptoms of
depression and anxiety during adolescence. Journal of Clinical Child
Copyright © 2012 SciRes. 445
A. K. ZALTA, D. L. CHAMBLESS
Copyright © 2012 SciRes.
and Adolescent Psychology, 38, 219-231.
Luszczynska, A., Scholz, U., & Schwarzer, R. (2005). The general
self-efficacy scale: Multicultural validation studies. The Journal of
Psychology, 139, 439-457. doi:10.3200/JRLP.139.5.439-457
Monroe, S. M. (1983). Major and minor life events as predictors of
psychological distress: Further issues and findings. Journal of Be-
havioral Medicine, 6, 189-205. doi:10.1007/BF00845380
Pearlin, L. I., Menaghan, E. G., Lieberman, M. A., & Mullen, J. T.
(1981). The stress process. Journal of Health and Social Behavior,
22, 337-356. doi:10.2307/2136676
Pearlin, L. I., & Schooler, C. (1978). The structure of coping. Journal
of Health and Social Behavior, 19 , 2-21. doi:10.2307/2136319
Peterson, C., Semmel, A., von Baeyer, C., Abramson, L. Y., Metalsky,
G. I., & Seligman, M. E. P. (1982). The attributional style question-
naire. Cognitive Therapy and R esearch, 6, 287-299.
Rosenberg, M. (1965). Society and the adolescent self-image. Princeton,
NJ: Princeton University Press.
Rotter, J. B. (1966). Generalized expectancies for internal versus ex-
ternal control of reinforcement. Psychological Monographs, 80.
Sanderson, W. C., Rapee, R. M., & Barlow, D. H. (1989). The influ-
ence of an illusion of control on panic attacks induced via inhalation
of 5.5% carbon dioxide-enriched air. Archives of General Psychiatry,
46, 157-162. doi:10.1001/archpsyc.1989.01810020059010
Scheier, M. F., & Carver, C. S. (1992). Effects of optimism on psycho-
logical and physical well-being: Theoretical overview and empirical
update. Cognitive Therapy and Re s ear ch , 16, 201-228.
Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguishing
optimism from neuroticism (and trait anxiety, self-mastery, and
self-esteem): A reevaluation of the Life Orientation Test. Journal of
Personality and Social P s y chology, 67, 1063-1078.
Scheier, M. F., Carver, C. S., & Bridges, M. W. (2001). Optimism,
pessimism, and psychological well-being. In E. C. Chang (Ed.), Op-
timism and pessimism: Implications for theory, research, and prac-
tice (pp. 189-215). Washington, DC: American Psychological Asso-
Schwarzer, R., & Jerusalem, M. (1995). Generalized self-efficacy scale.
In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures in health
psychology: A user’s portfolio. Causal and control beliefs (pp.
35-37). Windsor , UK: NFER-NELSON.
Seligman, M. E., Schulman, P., & Tryon, A. M. (2007). Group preven-
tion of depression and anxiety symptoms. Behaviour Research and
Therapy, 45, 1111-1126. doi:10.1016/j.brat.2006.09.010
Souza, T. M., Samaraweera, N., & Frye, L. A. (2009). Anxiety and
PTSD in the 2009-2010 college population. Anxiety Disorders: A
Tri-Annual Report, 6, 1-6.
Spielberger, C. D., Gorsuch, R. L., L ushene, R. E., V a gg, P. R. , & Jac obs,
G. A. (1983). Manual for the state-trait anxiety inventory. Palo Alto,
CA: Consulting Psych o l og i st s Press.
Taylor, S. E., Burklund, L. J., Eisenberger, N. I., Lehman, B. J., Hil-
mert, C. J., & Lieberman, M. D. (2008). Neural bases of moderation
of cortisol stress responses by psychosocial resources. Journal of
Personality and Social P s y chology, 95, 197-211.
van Jaarsveld, C. H., Ranchor, A. V., Sanderman, R., Ormel, J., &
Kempen, G. I. (2005). The role of premorbid psychological attributes
in short- and long-term adjustment after cardiac disease. A prospec-
tive study in the elderly in The Netherlands. Social Science & Medi-
cine, 60, 1035-1045. doi:10.1016/j.socscimed.2004.06.037
Windsor, T. D., Anstey, K. J., Butterworth, P., Luszcz, M. A., & An-
drews, G. R. (2007). The role of perceived control in explaining de-
pressive symptoms associated with driving cessation in a longitudi-
nal study. The Gerontolo gist, 47, 215-223.