International Journal of Behavioral Medicine, 15: 194–200, 2008
Taylor & Francis Group, LLC
ISSN: 1070-5503 print / 1532-7558 online
The Brief Resilience Scale: Assessing the Ability to Bounce Back
Bruce W. Smith, Jeanne Dalen, Kathryn Wiggins, Erin Tooley, Paulette Christopher,
and Jennifer Bernard
Background: While resilience has been deﬁned as resistance to illness, adaptation,
and thriving, the ability to bounce back or recover from stress is closest to its original
meaning. Previous resilience measures assess resources that may promote resilience
rather than recovery, resistance, adaptation, or thriving. Purpose: To te st a ne w
brief resilience scale. Method: The brief resilience scale (BRS) was created to assess
the ability to bounce back or recover from stress. Its psychometric characteristics
were examined in four samples, including two student samples and samples with
cardiac and chronic pain patients. Results: The BRS was reliable and measured as
a unitary construct. It was predictably related to personal characteristics, social
relations, coping, and health in all samples. It was negatively related to anxiety,
depression, negative affect, and physical symptoms when other resilience measures
and optimism, social support, and Type D personality (high negative affect and
high social inhibition) were controlled. There were large differences in BRS scores
between cardiac patients with and without Type D and women with and without
ﬁbromyalgia. Conclusion: The BRS is a reliable means of assessing resilience as the
ability to bounce back or recover from stress and may provide unique and important
information about people coping with health-related stressors.
Key words: brief resilience scale, stress, recovery, pain, cardiac
During the past decade, resilience has increasingly
become a focus of research in the behavioral and medi-
cal sciences (Charney, 2004; Masten, 2001). However,
“resilience” has been deﬁned in a variety of ways, in-
cluding the ability to bounce back or recover from
stress, to adapt to stressful circumstances, to not be-
come ill despite signiﬁcant adversity, and to function
above the norm in spite of stress or adversity (Carver,
1998; Tusaie & Dyer, 2004). In addition, the measures
that have been developed to assess “resilience” have
not focused on these qualities but on the factors and
All of the authors (Bruce W. Smith, Jeanne Dalen, Kathy
Wiggins, Erin Tooley, Paulette Christopher, and Jennifer Bernard)
are afﬁliated with the Department of Psychology, University of New
Mexico, Albuquerque, New Mexico.
The authors gratefully acknowledge Dr. Richard D. Lueker and
the staff of New Heart, Inc., Albuquerque, New Mexico, for pro-
viding the opportunity to study patients in their cardiac rehabilita-
tion program. We also gratefully acknowledge Dr. Paul Mullins, Dr.
Wilmer Sibbitt, and Erica Montague for their help and support in
the study of women with ﬁbromyalgia and healthy controls. Finally,
we are grateful to the University of New Mexico for providing a
Research Allocation Committee Grant (#06-17) to support the study
with women with ﬁbromyalgia and healthy controls.
Correspondence concerning this article should be addressed
to Bruce W. Smith, Ph.D., Department of Psychology, Univer-
sity of New Mexico, Albuquerque, NM 87131-1161. E-mail: bw-
resources that make them possible (Ahern, Kiehl, Sole,
& Byers, 2006).
Resilience as Bouncing Back
The purpose of this article is to clarify the study
of resilience by presenting a scale for assessing the
original and most basic meaning of the word resilience.
The root for the English word “resilience” is the word
“resile,” which means “to bounce or spring back” (from
re- “back” +salire- “to jump, leap”; Agnes, 2005).
While recognizing that words evolve in meaning over
time, the ability to bounce back or recover from stress
may be important to assess and study in its own right. In
addition, this ability may be particularly important for
people who are already ill or are dealing with ongoing
In distinguishing between the other meanings as-
sociated with resilience, it may be useful to use dif-
ferent words for resistance to illness, adaptation to
stress, and functioning above the norm in spite of stress.
Carver (1998) provided a clear distinction between “re-
silience” as returning to the previous level of function-
ing (e.g., bouncing back or recovery) and “thriving”
as moving to a superior level of functioning following
a stressful event. In addition, “adaptation” (or “stress
adaptation”) could be used for changing to adjust to
a new situation. Finally, it may be preferable to use
BRIEF RESILIENCE SCALE
a word like “resistance” (as in “stress resistance” or
“resistance to illness”) to refer to not becoming ill or
showing a decrease in functioning during stress.
Previous Measures of Resilience
Even though several meanings have been associated
with resilience, it is striking that measures of resilience
have not directly targeted them. Ahern et al. (2006)
have recently reviewed the instruments that were de-
signed to measure resilience. They focused on six mea-
sures, and the range of constructs measured included
“protective factors that support resiliency,” “success-
ful stress-coping ability,” “central protective resources
of health adjustment,” “resilient coping behavior,” and
“resilience as a positive personality characteristic that
enhances individual adaptation” (p. 110).
Rather than speciﬁcally assessing resilience as the
ability to bounce back, resist illness, adapt to stress,
or thrive in the face of adversity, previous mea-
sures have generally assessed protective factors or re-
sources that involve personal characteristics and cop-
ing styles. For example, the Resilience Scale (Wagnild
& Young, 1993) aimed to assess equanimity, perse-
verance, self-reliance, meaningfulness, and existential
aloneness. Similarly, the Connor Davidson Resilience
Scale (Connor & Davidson, 2003) aimed to assess
characteristics such as self-efﬁcacy, sense of humor,
patience, optimism, and faith.
In understanding people faced with health prob-
lems, it is undoubtedly important to identify the char-
acteristics or factors that may promote resilience, such
as optimism, active coping, and social support. While
measures have been developed to assess these char-
acteristics individually, the current “resilience” mea-
sures appear to provide a useful summary score of the
resources that generally support positive adaptation.
However, it may be more semantically accurate and
clear to refer to characteristics that may increase the
likelihood of resilience as “resilience resources.”
The Current Studies
The authors developed a brief resilience scale to
determine whether it is possible to reliably assess re-
silience as bouncing back from stress, whether it is
related to resilience resources, and whether it is related
to important health outcomes. Our strategy was to use
as few items as necessary to develop a reliable scale for
a unitary construct. We selected the ﬁnal items from
a list of potential items based on the feedback of re-
search team members and piloting with undergraduate
students. We included an equal number of positive and
negatively worded items to reduce the effects of social
desirability and positive response bias.
We tested the BRS on four separate samples to de-
termine whether it is reliable and demonstrates conver-
gent and predictive discriminate validity. We expected
that the ability to bounce back or recover from stress
would be valuable in coping with health-related stres-
sors. We included cardiac rehabilitation and chronic
pain patients because resilience may be particularly
important for them (Chan, Lai, & Wong, 2006; Zautra,
Johnson, & Davis, 2005). Our hypotheses were that the
BRS would represent one factor, would be related to
resilience resources and health-related outcomes, and
would predict health outcomes when controlling for
The BRS was tested on four samples. Sample 1
consisted of 128 undergraduate students. Sample 2
consisted of 64 undergraduate students. Sample 3
consisted of 112 cardiac rehabilitation patients. Sam-
ple 4 consisted of 50 women who either had ﬁ-
bromyalgia (n=20) or were healthy controls (n=
30). All four samples were recruited from a medium-
sized metropolitan area in the southwestern U.S.
(Albuquerque, New Mexico).
The BRS was administered to each of these four
samples in questionnaires. The questionnaires for each
sample were not identical but measured many of the
same constructs. These questionnaires assessed a range
of resilience-related constructs, other personal charac-
teristics, coping styles, social relationships, and health-
related outcomes. The list of measures below indicates
which measures were included for each sample.
The Brief Resilience Scale
The six items of the brief resilience scale (BRS)
are presented in Table 1. Items 1, 3, and 5 are pos-
itively worded, and items 2, 4, and 6 are negatively
worded. The BRS is scored by reverse coding items
2, 4, and 6 and ﬁnding the mean of the six items. The
following instructions are used to administer the scale:
“Please indicate the extent to which you agree with
each of the following statements by using the following
scale: 1 =strongly disagree, 2 =disagree, 3 =neutral,
4=agree, 5 =strongly agree.”
1. Resilience-Related Constructs
Connor-Davidson Resilience Scale (CD-RISC;
Connor & Davidson, 2003). The CD-RISC was de-
signed to assess the personal characteristics that em-
body resilience. It contains 25 items responded to
SMITH ET AL.
Tabl e 1. The Brief Resilience Scale: Items and Factor Loadings
Items Sample 1 Sample 2 Sample 3 Sample 4
1. I tend to bounce back quickly after hard times .77 .79 .70 .89
2. I have a hard time making it through stressful events (R) .73 .78 .68 .91
3. It does not take me long to recover from a stressful event .78 .78 .71 .71
4. It is hard for me to snap back when something bad happens (R) .85 .90 .70 .85
5. I usually come through difﬁcult times with little trouble .69 .69 .71 .68
6. I tend to take a long time to get over set-backs in my life (R) .84 .81 .67 .68
Note. Sample 1 =128 undergraduate students; Sample 2 =64 undergraduate students; Sample 3 =112 cardiac
rehabilitation patients; Sample 4 =50 women with ﬁbromyalgia or healthy controls. R =reverse coded items.
on a 5-point scale. The CD-RISC was included in
Ego Resiliency Scale (Block & Kremen, 1996). This
was designed to assess “the ability to change from
and also return to the individual’s characteristics level
of ego-control after the temporary, accommodation-
requiring, stressing inﬂuence is no longer acutely
present” (Block & Kremen, 1996; p. 351). It contains
14 items responded to on a 4-point scale and was in-
cluded in Sample 1.
2. Other Personal Characteristics
Life Orientation Test-Revised (LOT-R; Scheier,
Carver, & Bridges, 1994). The LOT-R included three
items assessing optimism and three items assessing
pessimism. The items are responded to on a 5-point
scale. The optimism items were in all samples and the
pessimism items were in Samples, 1, 2, and 4.
Purpose in Life (Ryff & Keyes, 1995). This assesses
the belief that one’s life has meaning and purpose. The
items are scored on a 6-point scale. The 9-item version
was in Samples 1 and 4 and the 3-item version was in
Toronto Alexithymia Scale (TAS-20; Bagby, Parker,
& Taylor, 1994). The TAS-20 was designed to assess
difﬁculty ﬁnding words for feelings. The 20 items are
scored on a 5-point scale and were included in Samples
1 and 4.
Type D Personality (DS14; Denollet, 2005). The
DS14 assesses for Type D personality. Type D is a
joint tendency toward negative affectivity and social
inhibition and has been related to poor cardiac prog-
nosis (Denollet, 2005). Fourteen items are scored on a
5-point scale. Seven items assess negative affectivity
and seven items assess social inhibition. It was included
in Sample 3.
3. Coping Styles
Brief COPE (Carver, 1997). The Brief COPE con-
sists of 28 items to assess 14 coping strategies. The
items are scores on a 4-point scale. All of the items
were included in Samples 1 and 4, and items for se-
lected strategies were included in Samples 2 and 3.
4. Social Relationships
Interpersonal Support Evaluation List (ISEL;
Cohen, Mermelstein, Karmarck, & Hoberman, 1985).
The ISEL consists of 12 items to assess social support
using a 4-point scale. It was included in Samples 1 and
MOS Social Support Survey (MOS-SSS; Sherbourne
& Stewart, 1991). This consists of 20 items assessing
social support using a 5-point scale. An 8-item short
version was in Sample 3, and the full 20-item version
was in Sample 4.
Negative Social Interactions (Finch, Okun, Barrera,
Zautra, & Reich, 1989). This measure includes four
items to assess negative social interactions. These items
were included in Samples 1, 2, and 4.
5. Health-Related Outcomes
Brief Health-Related Measures. Sample 3 also in-
cluded one 7-point item assessing the number of ex-
ercise days per week. Samples 3 and 4 included a 10-
point item measuring fatigue. Sample 4 included three
visual analogue scales assessing current, worse, and
average pain that were summed to form an overall in-
dex of pain.
Hospital Anxiety and Depression Scale (HADS;
Zigmond & Snaith, 1983). There are 7 items each to
assess anxiety and depression. The items are scored on
a 4-point scale. The HADS was included in Samples 3
Mental Health Inventory (Veit & Ware, 1983). This
consists of 9 items to assess anxiety and 9 items to
assess depression. The items are scored on 5- or 6-point
scales. These items were included in Samples 1 and 2.
Mood Adjective Checklist (Larsen & Diener, 1992).
Six items were included to assess negative affect and
six items were included to assess positive affect. They
were scored on a 6-point scale and were included in
Physical Symptoms Index (Moos, Cronkite, &
Finney, 1986). This measure includes 12 items to as-
sess physical symptoms such as headaches and consti-
pation. It was included in Samples 1, 3, and 4.
BRIEF RESILIENCE SCALE
Perceived Stress Scale (PSS; Cohen, Kamarck, &
Mermelstein, 1983). The PSS consists of 10 items that
assess perceived stress. The items are scored on a 4-
point scale. The PSS was included in all four samples.
Positive and Negative Affect Schedule (PANAS; Wat-
son, Clark, & Tellegen, 1988). The PANAS includes
20 items to assess positive and negative affect. It was
scored on a 5-point scale and included in Samples 1,
2, and 4.
The primary analyses assessed the factor structure,
reliability, and validity of the BRS. The factor struc-
ture was examined by principal components analyses
(PCA) with a varimax rotation retaining eigenvalues >
1. Internal consistency was examined using Cronbach’s
alpha, and test-retest reliability was examined using the
intra-class correlation (ICC) for absolute agreement.
Convergent validity was assessed by zero-order corre-
lations between the BRS and the other measures. Dis-
criminant predictive validity was assessed by partial
correlations, with health-related outcomes controlling
for other predictors. In addition, we compared mean
BRS scores across samples and subgroups using inde-
pendent samples t-tests.
Table 2 displays the descriptive statistics for age,
gender, and the BRS for each sample. Samples 1 and
2 were young and primarily female. Sample 3 was rel-
atively old and primarily male. Sample 4 was middle-
aged and all female. The mean BRS scores ranged from
3.53 in Sample 1 to 3.98 in Sample 3. BRS scores were
signiﬁcantly higher in Sample 3 than in Samples 1, 2,
and 4 combined (3.98 vs. 3.56, t =5.053, df =352,
p<.001), which did not differ from each other.
Factor Structure and Reliability
Table 1 shows the PCA loadings of the BRS items
for each of the four samples. The results for each sam-
ple revealed a one-factor solution accounting for 55–
67% of the variance (Samples 1–4 =61%, 61%, 57%,
67%, respectively). The loadings ranged from .68 to
.91. Internal consistency was good, with Cronbach’s
alpha ranging from .80–.91(Samples 1–4 =.84, .87,
Tabl e 2. Descriptive Statistics for the Four Samples
Sample 1 Sample 2 Sample 3 Sample 4
Sample size 128 64 112 50
Age (years) 20.4 (4.0) 19.8 (3.0) 62.8 (10.5) 47.3 (8.2)
Gender(% female) 76 67 24 100
BRS scores 3.53 (0.68) 3.57 (0.76) 3.98 (0.68) 3.61 (0.85)
Note. Standard deviations are listed in parentheses.
.80, .91, respectively). The BRS was given twice in
two samples with a test-retest reliability (ICC) of .69
for one month in 48 participants from Sample 2 and
.62 for three months in 61 participants from Sample 3.
Table 3 shows the zero-order correlations between
the BRS and personal characteristics, social relations,
coping, and health outcomes for each sample. The BRS
was positively correlated with the resilience measures,
optimism, and purpose in life, and negatively correlated
with pessimism and alexithymia. In addition, it was
positively correlated with social support and negatively
correlated with negative interactions. Finally, it was
consistently positively correlated with active coping
and positive reframing and negatively correlated with
behavioral disengagement, denial, and self-blame.
With regard to health-related outcomes, the BRS
was consistently negatively correlated with perceived
stress, anxiety, depression, negative affect, and physi-
cal symptoms. In addition, it was positively correlated
with positive affect in three of the four samples and
with exercise days per week in the cardiac rehabilita-
tion sample. It was negatively correlated with fatigue
in the cardiac sample and negatively correlated with
fatigue and pain in the sample of middle-aged women.
Discriminant Predictive Validity
We examined discriminant predictive validity in the
two larger samples. Table 4 shows the zero-order and
partial correlations between each of the BRS, CD-
RISC, ego resiliency, and the health outcomes in the
ﬁrst undergraduate sample. The zero-order correlations
revealed that the “resilience” measures were almost
always related in the expected direction with the out-
comes, with the exception that ego resiliency was only
marginally related to less negative affect.
The partial correlations were obtained by correlat-
ing each resilience measure with each outcome, while
controlling for both of the other “resilience” mea-
sures. The BRS was still negatively related to perceived
stress, anxiety, depression, negative affect, and physi-
cal symptoms. The CD-RISC was still negatively re-
lated to perceived stress and still positively related to
positive affect. The ego resiliency scale was still posi-
tively related to positive affect.
Table 5 shows the zero-order and partial correlations
between the BRS, optimism, social support, and Type
D and the health outcomes in the cardiac sample. The
zero-order correlations revealed that the BRS was cor-
related with all seven outcomes and that optimism, so-
cial support, and Type D were correlated with ﬁve out-
comes. The partial correlations showed that the BRS
was still related to perceived stress, anxiety, depres-
sion, negative affect, fatigue, and marginally to exercise
days. Optimism was still related to perceived stress,
SMITH ET AL.
Tabl e 3. Correlations Between the Brief Resilience Scale and Other
Sample 1 Sample 2 Sample 3 Sample 4
Alexithymia −.47∗∗ ——−.44∗∗
CD-RISC .59∗∗ ———
Ego resiliency .51∗∗ —— 49
Optimism .45∗∗ .63∗∗ .69∗∗ .55∗∗
Pessimism −.40∗∗ −.56∗∗ —−.32∗
Purpose in life .46∗∗ —.47∗∗ .67∗∗
Negative interactions −.25∗∗ −.47∗∗ —−.46∗∗
Social support .28∗∗ .27∗.30∗∗ .40∗∗
Acceptance .43∗∗ .42∗∗ .18+.22
Active coping .40∗∗ .41∗∗ .38∗∗ .31∗
Behavioral disengagement −.39∗∗ ——−.52∗∗
Denial −.37∗∗ −.33∗−.32∗∗ −.53∗∗
Humor .32∗∗ .18 .09 .08
Planning .27∗∗ —— .42∗∗
Positive reframing .40∗∗ .41∗∗ .38∗∗ .31∗
Religion .16+—— .08
Self-blame −.27∗∗ −.47∗∗ −.36∗∗ −.35∗
Self-distraction .07 — — −.26+
Substance use −.06 −.45∗∗ −.22∗−.32∗
Using emotional support .16+.10 — .13
Using instrumental support .15+.33∗—−.12
Venting −.14 — .04 .16
Anxiety −.46∗∗ −.56∗∗ −.53∗∗ −.60∗∗
Depression −.41∗∗ −.49∗∗ −.50∗∗ −.66∗∗
Exercise days — — .23∗—
Fatigue — — −.32∗∗ −.55∗∗
Negative affect −.34∗∗ −.53∗∗ −.51∗∗ −.68∗∗
Pain — — — −.59∗∗
Perceived stress −.60∗∗ −.71∗∗ −.61∗∗ −.64∗∗
Physical symptoms −.39∗∗ −.28∗—−.50∗∗
Positive affect .46∗∗ .17 .45∗∗ .63∗∗
Note. Sample 1 =128 students; Sample 2 =64 students; Sample 3 =112 cardiac
patients; Sample 4 =50 women with ﬁbromyalgia or healthy controls. +p<.10,
anxiety, and positive affect, and marginally to nega-
tive affect. Social support was still related to positive
affect and marginally to anxiety. Type D was still re-
lated to depression and negative affect and marginally
to positive affect.
Subgroup Differences in BRS Scores
Finally, we wanted to determine whether there were
subgroup differences in mean BRS scores between men
and women within samples, between participants with
Tabl e 4. Zero-Order and Partial Correlations between Resilience Measures and Outcomes for
Zero-Order Correlations Partial Correlations
BRS CD-RISC Ego Resiliency BRS CD-RISC Ego Resiliency
Perceived stress –.60** –.53** –.40** –.38** –.26* .04
Anxiety –.46** –.40** –.33** –.29** –.15 –.02
Depression –.41** –.35** .28** –.21* –.14 –.04
Negative affect –.34** –.25** –.16+–.24* –.14 .12
Positive affect .46** .68** .69** .09 .40** .26**
Physical symptoms –.39** –.35** –.25* –.23* –.15 .04
aSample 1 (128 undergraduates students). +p<.10, *p<.05, **p<.01.
BRIEF RESILIENCE SCALE
Tabl e 5. Zero-Order and Partial Correlations of the Brief Resilience Scale, Optimism, Social Support, and Type D
for Cardiac Patientsa
Zero-Order Correlations Partial Correlations
BRS Optimism Social Support Type D BRS Optimism Social Support Type D
Perceived stress −.61∗∗ −.38∗∗ −.29∗∗ .35∗∗ −.46∗∗ −.30∗∗ −.12 .05
Anxiety −.53∗∗ −.34∗∗ −.35∗∗ .36∗∗ −.33∗∗ −.24∗−.20+.01
Depression −.50∗∗ −.25∗∗ −.26∗∗ .46∗∗ −.37∗∗ −.08 −.17 .32∗∗
Negative affect −.51∗∗ −.39∗∗ −.19+.43∗∗ −.35∗∗ −.22+.01 .20∗
Positive affect .45∗∗ .40∗∗ .25∗∗ −.36∗∗ .20+.28∗.23∗−.19+
Fatigue −.32∗∗ −.18+−.19∗.13 −.28∗∗ −.07 −.17 .00
Exercise days .23∗.06 .11 −.08 .19+−.07 −.06 .06
aSample 3 (112 cardiac rehabilitation patients). +p<.10, ∗p<.05, ∗∗p<.01.
Type D and without Type D in Sample 3, and between
women with and without ﬁbromyalgia in Sample 4.
There were no differences between men and women in
Samples 1 and 2, but BRS scores were higher in men
(M=4.07, SD =0.66) than for women (M=3.67,
SD =0.70) in Sample 3 (t =2.673, df =110, p<.01,
d=.60). Gender differences could not be examined in
Sample 4 because it only included women. In Sample 3,
the BRS scores were higher for the 93 cardiac patients
without Type D (M=4.11, SD =0.60) than for the 19
cardiac patients with Type D (M=3.27, SD =0.67;
t=5.318, df =110, p<.001, d=1.32). Finally, in
Sample 4, BRS scores were higher for the 30 women
without ﬁbromyalgia (M=3.96, SD =0.58) than for
the 20 women with ﬁbromyalgia (M=3.09, SD =
0.93; t =4.074, df =48, p<.001; d=1.12).
The purpose of this study was to test a new brief
resilience scale to assess the ability to bounce back or
recover from stress. We examined the BRS in two stu-
dent and two behavioral medicine samples. We found
that the BRS demonstrated good internal consistency
and test-retest reliability. In addition, our hypotheses
that it would represent one factor, would be related to
resilience resources and health-outcomes, and would
predict health outcomes beyond resilience resources
were supported. Finally, there were BRS score dif-
ferences between those with and without Type D and
those with and without ﬁbromyalgia.
The results suggest that the BRS may have a unique
place in behavioral medicine research. First, previous
measures of resilience target the personal character-
istics that may promote positive adaptation and not
resilience itself. The BRS is the only measure that
speciﬁcally assesses resilience in its original and most
basic meaning: to bounce back or recover from stress
(Agnes, 2005). When studying people who are already
ill, assessing the speciﬁc ability to recover may be more
important than assessing the ability to resist illness.
Second, the BRS may be uniquely related to health
when controlling for previous resilience measures and
measures of individual resilience resources (e.g., op-
timism and social support). Since the BRS is framed
with regard to negative events (“stressful events,” “hard
times,” “difﬁcult times,” “set-backs”), it is not surpris-
ing that its unique effects were speciﬁc to reducing
negative outcomes (anxiety, depression, negative af-
fect, physical symptoms).
Third, the relationship that we found between the
BRS and resilience resources suggests it may medi-
ate the effects of resilience resources on health out-
comes. Resources such as optimism, social support,
active coping, and the range of those assessed by pre-
vious resilience measures may facilitate the ability to
recover from stress or adversity. The ability to recover
itself may, in turn, have a more direct relationship with
Finally, these studies have limitations which lay the
groundwork for future studies using the BRS. The
BRS needs to be used in longitudinal studies to de-
termine whether it predicts recovery from important
health stressors. In addition, the BRS needs to be com-
pared with physiological indicators of bouncing back
or recovery from stress and illness (Charney, 2004).
Last, the relationship between the BRS and other forms
of positive adaptation, such as thriving and posttrau-
matic growth, and their effects on health needs to be
Agnes, M. (Ed.). (2005). Webster’s new college dictionary.
Cleveland, OH: Wiley.
Ahern, N. R., Kiehl, E. M., Sole, M. L., & Byers, J. (2006). A review
of instruments measuring resilience. Issues in Comprehensive
Pediatric Nursing, 29, 103–125.
Bagby, M. R., Parker, J. D. A., & Taylor, G. J. (1994). The twenty-
item Toronto Alexithymia Scale-I item selection and cross-
validation of the factor structure. Journal of Personality and
Social Psychology, 38,23–32.
Block, J., & Kremen, A. M. (1996). IQ and ego-resiliency: Con-
ceptual and empirical connections and separateness. Journal of
Personality and Social Psychology, 70, 349–361.
SMITH ET AL.
Carver, C. S. (1997). You want to measure coping but your protocol’s
too long: Consider the Brief COPE. International Journal of
Behavioral Medicine, 4, 92–100.
Carver, C. S. (1998). Resilience and thriving: Issues, models, and
linkages. Journal of Social Issues, 54, 245–266.
Chan, I. W. S., Lai, J. C. L., & Wong, K. W. N. (2006). Resilience
is associated with better recovery in Chinese people diagnosed
with coronary heart disease. Psychology and Health, 21(3),
Charney, D. S. (2004). Psychobiological mechanisms of resilience
and vulnerability: Implications for successful adaptation to ex-
treme stress. American Journal of Psychiatry, 161, 195–216.
Cohen, S., Kamarck, T.,& Mermelstein, R. (1983). A global measure
of perceived stress. Journal of Health and Social Behavior, 24,
Cohen, S., Mermelstein, R., Karmarck, T., & Hoberman, H. (1985).
Measuring the functional components of social support. In I.
G. Sarason & B. R. Sarason (Eds.), Social support: Theory,
research, and application. The Hague, Holland: Martinus Ni-
Connor, K. M., & Davidson, J. R. T. (2003). Development of a
new resilience scale: The Connor-Davidson Resilience Scale
(CD-RISC). Depression and Anxiety, 18, 76–82.
Denollet, J. (2005). DS14: Standard assessment of negative affec-
tivity, social inhibition, and Type D personality. Psychosomatic
Medicine, 67, 89–97.
Finch, J. F., Okun, M. A., Barrera, M., Zautra, A. J., & Reich, J.
W. (1989). Positive and negative social ties among older adults:
Measurement models and the prediction of psychological stress
and well-being. American Journal of Community Psychology,
Larsen, R., & Diener, E. (1992). Promises and problems with the
circumplex model of emotion. In M. S. Clarke (Ed.), Emotion
(pp. 25–59). Newbury Park, CA: Sage.
Masten, A. S. (2001). Ordinary magic: Resilience processes in de-
velopment. American Psychologist, 56, 227–238.
Moos, R. H., Cronkite, R. C., & Finney, J. W. (1986). Health and
Daily Living Manual (2nd ed.).Palo Alto, CA: Center for Health
Care Evaluation, Stanford University Medical Centers.
Ryff, C. D., & Keyes, C. L. M. (1995). The structure of psycho-
logical well-being revisited. Journal of Personality and Social
Psychology, 69, 719–727.
Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguish-
ing optimism from neuroticism (and trait anxiety, self-mastery,
and self-esteem): A reevaluation of the Life Orientation Test.
Journal of Personality and Social Psychology, 67, 1063–
Sherbourne, C. D., & Stewart, A. L. (1991). The MOS social support
survey. Social Science and Medicine, 32, 705–714.
Tusaie, K., & Dyer, J. (2004). Resilience: A historical review of the
construct. Holistic Nursing Practice, 18, 3–8.
Veit, C. T., & Ware, J. E. (1983). The structure of psychological
distress and well-being in general populations. Journal of Con-
sulting and Clinical Psychology, 51, 730–742.
Wagnild, G. M., & Young, H. M. (1993). Development and psy-
chometric evaluation of the resilience scale. Journal of Nursing
Measurement, 1, 165–178.
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and
validation of brief measures of positive and negative affect: The
PANAS Scales. Journal of Personality and Social Psychology,
Zautra, A. J., Johnson, L. M., & Davis, M. C. (2005). Posi-
tive affect as a source for resilience for women in chronic
pain. Journal of Consulting and Clinical Psychology, 73, 212–
Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and
Depression Scale. Acta Psychiatrica Scandinavica, 67, 361–