East Tennessee State University
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Electronic Theses and Dissertations
12-2009
Positive Psychological and Religious
Characteristics as Moderators of Negative Life
Events and Depressive Symptoms: A Multiethnic
Comparison.
Preston Lee Visser
East Tennessee State University
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Recommended Citation
Visser, Preston Lee, "Positive Psychological and Religious Characteristics as Moderators of Negative Life Events and Depressive
Symptoms: A Multiethnic Comparison." (2009). Electronic Theses and Dissertations. Paper 1884. http://dc.etsu.edu/etd/1884
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Positive Psychological and Religious Characteristics as Moderators of Negative Life Events and
Depressive Symptoms: A Multiethnic Comparison
____________________________________
A thesis
presented to
the faculty of the Department of Psychology
East Tennessee State University
____________________________________
In partial fulfillment
of the requirements for the degree
Master of Arts in Psychology
___________________________________
by
Preston Lee Visser
December 2009
___________________________________
Jameson Kenneth Hirsch, Ph.D., Chair
Jon R. Webb, Ph.D.
Andrea D. Clements, Ph.D.
Keywords: Depressive Symptoms, Ethnicity, Life Events, Spirituality, Optimism, Hope
ABSTRACT
Positive Psychological and Religious Characteristics as Moderators of Negative Life Events and
Depressive Symptoms: A Multiethnic Comparison
by
Preston Lee Visser
Hope, optimism, and several markers of religiosity and spirituality were examined as potential
moderators of the association between negative life events and depressive symptoms in a
secondary data analysis of an ethnically diverse sample. Participants (267 female, 119 male)
were college students enrolled at an urban Northeastern university. It was hypothesized that
negative life events would be associated with increased depressive symptoms and that higher
levels of hope, optimism, and religious and spiritual variables would attenuate this relationship.
Ethnically-stratified moderation analyses were conducted to assess for differences in moderation
between Blacks, Hispanics, Whites, and Asians. Hypotheses were generally supported, with
some ethnic variation in findings. Although hope and optimism predicted decreased depressive
symptoms in Blacks, Hispanics, and Whites, optimism was a significant moderator in Whites
only. Measures of religiosity were significant moderators among Blacks as well as Whites.
Clinical and research implications are explored based on the extant literature.
2
ACKNOWLEDGEMENTS
A valuable practice that I, regrettably, often neglect is reflecting upon the countless
blessings I experience. In taking one step closer to my educational goals, I am reminded of the
many people who have been instrumental in fostering personal and academic success in my life.
I would be a lesser person without their unconditional support and persistent encouragement.
First, I would like to express gratitude to my Thesis Chair, Dr. Jameson Hirsch, who,
because of his patience and commitment over the past two years has also become my mentor.
Thank you for the numerous late nights of email communication; I hope that your wife has
forgiven me. I am also grateful to my committee members, Drs. Andrea Clements and Jon
Webb, who always provided excellent feedback as well as timely encouragement. Because of
their support, I have developed a greater appreciation of the value of positive reinforcement. I
thank Dr. Stacey Williams, who contributed needed statistical direction, Dr. Chad Lakey, who
generously spent several afternoons discussing ideas with me and offering guidance in statistical
procedures, and Dr. Elizabeth Jeglic, who graciously allowed me to use her data for this project.
My debt of gratitude for my family could never be repaid, for it is only because of their
nurturance and training that I achieve any success. Presently, I am grateful for my mother’s
undying interest and encouragement in my work, my father’s priceless counsel in all areas of
life, my sister’s exceptional work in blazing the trail to college for me to follow, and my
brothers’ commitment to helping me remember more important things in life such as creating a
home and cheering on the Steelers. Also, any success I have had in college is due largely to the
immeasurable love and generosity of my grandparents who took me in as a son for four great
years. Lastly, my wife and best friend, Krystal Jo, thank you for your selflessness and support. I
pray that accomplishments such as these help me to better serve you with the love of our Lord!
3
CONTENTS
Page
ABSTRACT………………………………………………………………………………. 2
ACKNOWLEDGEMENTS……………………………………………………………….
3
LIST OF TABLES………………………………………………………………………...
6
LIST OF FIGURES……………………………………………………………………….
7
Chapter
1. INTRODUCTION………………………………………………………………….
8
Depression……………………………………………………………………..
9
Epidemiology of Depression……………………………………… 10
Ethnic Differences in Depression…………………………………
11
Etiological Influences on Depression……………………………..
13
Psychological and Religious or Spiritual Moderators of Depression.……….. 18
Trait Hope…………………………………………………............
18
Dispositional Optimism…………………….……………………..
21
Religiosity and Spirituality………………………………………..
24
Statement of the Problem……………………..……………………………….
28
Hypotheses…………………………………………………………………….
28
2. METHODS..……………………………………………………………………….
30
Procedures.…………………………………………………………………….
30
Measures………………………………………………………………………
30
Beck Depression Inventory-II……………………………………..
30
Life Events Scale………………………………………………….
32
Trait Hope Scale…………………………………………………... 32
Life Orientation Test-Revised..…………………………………… 33
Brief Multidimensional Measure of Religiousness/Spirituality…... 34
Statistical Analyses……………………………………………………………
36
3. RESULTS………………………………………………………………………….
39
Descriptive Results……………………………………………………………
39
Mean Differences Across Ethnic Groups……………………………………... 40
Bivariate Associations Among Study Variables………………………………
4
41
Moderation Analyses of Study Variables and Depressive Symptoms………..
43
Trait Hope as a Moderator………………………………………...
43
Optimism as a Moderator…………………………………………. 45
Daily Spiritual Experiences as a Moderator………………………. 47
Private Religious Practices as a Moderator……………………….
47
Organizational Religiousness as a Moderator…………………….
52
Positive Religious Coping as a Moderator………………………... 55
Negative Religious Coping as a Moderator……………………….
59
4. DISCUSSION……………………………………………………………………...
63
Hypotheses……………………………………………………………….……
63
Hypothesis 1: Negative Life Events and Depressive Symptoms….
63
Hypothesis 2: Trait Hope, Dispositional Optimism, and
Depressive Symptoms ……………………………………………. 64
Hypothesis 3: Daily Spiritual Experiences, Private Religious
Practices, Organizational Religiousness, and Depressive Symptoms..
66
Hypothesis 4: Religious Coping and Depressive Symptoms……... 68
Hypothesis 5: Study Variables as Moderators…………………….
70
Hypothesis 6: Prevalence of Outcome and Predictor Variables by
Ethnic Group………………………………………………………
76
Hypothesis 7: Study Variables as Moderators in Analyses
Stratified by Ethnicity……………………………………………..
80
Limitations and Future Research……………………………………………...
89
Conclusions……………………………………………………………………
93
REFERENCES……………………………………………………………………. 96
VITA……………………………………………………………………………… 123
5
LIST OF TABLES
Table
Page
1. Levels of Demographic, Predictor, and Criterion Variables Across Ethnic Groups.
40
2. Bivariate Correlations of Study Variables with Demographics Included…………….
42
3. Negative Life Events, Hope, and Depressive Symptoms—Multivariate Linear
Regression………………………………………………………………………..
44
4. Negative Life Events, Optimism, and Depressive Symptoms—Multivariate Linear
Regression………………………………………………………………………..
46
5. Negative Life Events, Daily Spiritual Experiences, and Depressive Symptoms—
Multivariate Linear Regression…………………………………………………..
49
6. Negative Life Events, Private Religious Practices, and Depressive Symptoms—
Multivariate Linear Regression…………………………………………………..
51
7. Negative Life Events, Organizational Religiousness, and Depressive Symptoms—
Multivariate Linear Regression…………………………………………………..
54
8. Negative Life Events, Positive Religious Coping, and Depressive Symptoms—
Multivariate Linear Regression…………………………………………………..
58
9. Negative Life Events, Negative Religious Coping, and Depressive Symptoms—
Multivariate Linear Regression…………………………………………………..
6
60
LIST OF FIGURES
Figure
Page
1. Regression of Depressive Symptoms on Negative Life Events for High Trait Hope
(1 SD above) and Low Trait Hope (1 SD below) for the Total Sample (N =
386)….....................................................................................................................
45
2. Regression of Depressive Symptoms on Negative Life Events for High Optimism
(1 SD above) and Low Optimism (1 SD below) for Whites (N = 71)…….…......
48
3. Regression of Depressive Symptoms on Negative Life Events for High Daily
Spiritual Experiences (1 SD above) and Low Daily Spiritual Experiences (1 SD
below) for Whites (N = 71)……............................................................................
50
4. Regression of Depressive Symptoms on Negative Life Events for High Private
Religious Practices (1 SD above) and Low Private Religious Practices (1 SD
below) for Blacks (N = 98)…................................................................................
52
5. Regression of Depressive Symptoms on Negative Life Events for High Private
Religious Practices (1 SD above) and Low Private Religious Practices (1 SD
below) for Whites (N = 71)…................................................................................
53
6. Regression of Depressive Symptoms on Negative Life Events for High
Organizational Religiousness (1 SD above) and Low Organizational
Religiousness (1 SD below) for Blacks (N = 98)…...............................................
56
7. Regression of Depressive Symptoms on Negative Life Events for High
Organizational Religiousness (1 SD above) and Low Organizational
Religiousness (1 SD below) for Whites (N = 71)…..............................................
57
8. Regression of Depressive Symptoms on Negative Life Events for High Positive
Religious Coping (1 SD above) and Low Positive Religious Coping (1 SD
below) for Whites (N = 71)…................................................................................
59
9. Regression of Depressive Symptoms on Negative Life Events for High Negative
Religious Coping (1 SD above) and Low Negative Religious Coping (1 SD
below) for Asians (N = 21)…................................................................................
7
62
CHAPTER 1
INTRODUCTION
Depression is one of the most pervasive and costly psychological disorders in the United
States (Greenberg et al., 2003), and it is predictive of increased risk for numerous negative
outcomes such as physical disease, premature death, and loss of quality of life (Gallegos-Carrillo
et al., 2009; Gutierrez, Osman, Kopper, Barrios, & Bagge, 2000; Insel & Charney, 2003; Wulsin,
Vaillant, & Wells, 1999). Of particular concern, depression is a growing problem among college
students, for whom the prevalence of major depressive disorder (MDD) increased from
approximately 10.0% in 2000 to 14.5% in 2006 (ACHA, 2000; ACHA, 2006). Some ethnic and
racial groups in the United States such as Mexican Americans and Blacks may also be at
increased risk for depression compared with non-Hispanic Whites (Hasin, Goodwin, Stinson, &
Grant, 2005; Oquendo, Lizardi, Greenwald, Weissman, & Mann, 2004; Roberts, Roberts, &
Chen, 1997). Factors that may play a role in the etiology of depression such as levels of
spirituality and life stress have been found to differ across ethnic groups (Mangold, Veraza,
Kinkler, & Kinney, 2007; Perez, 2002; Ramos, 2005).
Consistently, the experience of stressful life events is strongly predictive of depression
(Kessler, 1997), yet stress alone is not sufficient to precipitate a depressive episode (Kendler,
Karkowski, & Prescott, 1999). The study of characteristics that decrease individuals’ probability
of becoming depressed even when they have experienced stressful life events has recently gained
momentum in the empirical literature (Grote, Bledsoe, Larkin, Lemay, & Brown, 2007).
Researchers have observed a need to better understand the role of positive psychological
characteristics that may buffer against depression (Seligman, Rashid, & Parks, 2006) and, in
particular, how such protective effects might differ across ethnic groups (Burke, Joyner, Czech,
8
& Wilson, 2000; Chang & Banks, 2007). The development of targeted, effective treatments for
depression depends on thorough investigation of risk and protective factors and how they might
differ across cultural groups.
Depression
In lay terms, depression can simply refer to an affective state (as in a depressed mood);
whereas for research purposes depression most often indicates the presence of symptoms
associated with clinical disorders such as major depressive disorder (MDD) (American
Psychiatric Association [APA], 2000). These symptoms include feelings of sadness or
worthlessness, loss of energy, agitation, diminished pleasure in previously enjoyable activities,
empty or sad mood most of the time, loss of appetite, insomnia, fatigue, inability to concentrate,
feelings of worthlessness, and preoccupation with death (APA). According to the Diagnostic and
Statistical Manual of Mental Disorders Fourth Edition Text Revision (DSM-IV-TR; APA), an
individual diagnosed with MDD must have experienced at least one major depressive episode
(MDE) that is not attributable to other psychological or physical disorders, and the individual
must have never experienced a manic, mixed, or hypomanic episode (APA). An MDE is
characterized by, “at least 2 weeks during which there is either depressed mood or the loss of
interest or pleasure in nearly all activities” (APA, p. 349).
Research on depression often uses only MDD as an outcome; however, not all individuals
experiencing depressive symptomatology reach the level of MDD. Similar to MDD, elevated
depressive symptoms are highly associated with poor outcomes (Kubik, Lytle, Birnbaum,
Murray, & Perry, 2003). In a longitudinal study of 1,698 randomly selected high school students,
Gotlib, Lewinsohn, and Seeley (1995) found that 33 participants (1.9%) were clinically
depressed, and 283 (16.7%) displayed elevated depressive symptoms but fell short of the
9
threshold for diagnosis of MDD. Both groups were significantly more likely than nondepressed
participants to experience negative psychosocial outcomes such as poor social support and low
self-esteem. Additionally, over the course of the study both groups were at greater risk for
developing other psychological disorders such as anxiety. Statistical comparisons of the two
groups revealed significant differences on only 4 of 20 psychosocial outcomes assessed,
suggesting that both clinical and subclinical levels of depression contribute to risk for poor
psychosocial functioning (Gotlib et al., 1995). Because elevated but subthreshold depressive
symptoms and MDD share similar symptoms and correlates, a comprehensive literature review
may consider studies in both areas to develop an overall understanding of depression
(Vredenburg, Flett, & Krames, 1993).
Epidemiology of Depression
In the United States, MDD is one of the most frequently occurring mental disorders
(Kessler et al., 2003). At least four large epidemiological studies using face-to-face structured
interviews to collect data on the prevalence of depression in the United States have been
conducted in the past 30 years: The Epidemiological Catchment Area (ECA) study, The National
Comorbidity Study (NCS), the National Comorbidity Study-Revised (NCS-R), and the National
Epidemiological Survey on Alcoholism and Related Conditions (NESARC) (Hasin et al., 2005).
The ECA study was conducted between 1980 and 1984, and it found the lifetime and 12-month
prevalence of MDD to be approximately 4.5% and 2.5% respectively (Kessler et al.). Lifetime
prevalence refers to individuals who have experienced MDD at least once in their lives, and 12month prevalence refers to the percentage of people experiencing MDD in the previous year.
Eight years after completion of the ECA study, the NCS found MDD prevalence to be
considerably higher at 14.9% for lifetime and 8.6% for the previous 12 months (Kessler et al).
10
The ECA used the National Institute of Mental Health’s Diagnostic Interview Schedule (DIS),
whereas the NCS used an expanded version of the DIS, the Composite International Diagnostic
Interview. Previous research has found general agreement between these two scales (Semler et
al., 1987), indicating that other methodological variables such as interviewer experience or
sampling (Semler et al.) or prevalence changes over time may explain discrepant findings.
Conducted from 2001-2002, the NCS-R found similar results to the original NCS, with lifetime
and 12-month prevalence estimates of MDD at 16.2% and 6.6% respectively (Kessler et al.). The
NESARC was conducted during the same time frame as the NCS-R by a different research
group, and it found lifetime and 12-month estimates of 13.2% and 5.3% respectively, which was
more consistent with the relatively high prevalence found in the national comorbidity studies as
opposed to the original ECA study (Hasin et al.). Prevalence estimates for individuals attending
college have been tracked with the American College Health Assessment study, which found the
lifetime prevalence of MDD to be 14.5 % in 2006 (ACHA, 2006). This rate has grown
substantially from 10.3% in 2000 (ACHA, 2000). Increased risk for depression may be reflective
of a cohort effect rather than an effect unique to only young adults who attend college; evidence
suggests that depression rates do not differ significantly between college and noncollege 18-24
year olds (Chadwick, 1999).
Ethnic Differences in Depression
Some studies suggest that minority groups in the United States are at increased risk for
depression (Jones-Webb & Snowden, 1993; Wight et al., 2005), while other studies indicate
lower prevalence among minority groups (Breslau et al., 2006; Hasin et al., 2005). When
depression is operationalized as MDD, ethnic minorities tend to not differ or to be at decreased
risk compared to Whites (Breslau et al., 2006; Hasin et al., 2005; Mendelson, Rehkopf, &
11
Kubzansky, 2008). Conversely, when depression is operationalized as elevated depressive
symptomology, ethnic minorities tend to be at increased risk (Cuella & Roberts, 1997; Locke,
Newcomb, Duclos, & Goodyear, 2007; Riolo, Nguyen, Greden, & King, 2005; Mendelson,
Rehkopf, & Kubzansky, 2008); however, not all studies agree (Saluja et al., 2004; Mendelson et
al., 2008).
The NCS-R, conducted from 2001-2002, used face-to-face interviews of a nationally
representative sample of 5,554 participants to assess the prevalence of mental disorders in the
United States based upon DSM-IV criteria (Breslau et al,. 2006). Data from the NCS-R showed
that Blacks regardless of age and younger (age< 43 years) but not older (age >43 years)
Hispanics had significantly lower risk for MDD than Whites. Using a larger sample size (N=
43,093), the NESARC found the lifetime prevalence of MDD to be 8.9% for Blacks, 9.6% for
Hispanics, 8.8% for Asian Americans, 19.2% for Native Americans, and 14.6% for Whites
(Hasin et al., 2005). These results, like those from the NCS-R, indicate lower risk of depression
for Blacks, Hispanics, and Asian Americans in comparison with Whites. Some studies, however,
do suggest that Blacks and Hispanics are at higher risk for depressive symptoms than Whites as
opposed to actual diagnosis of MDD (Jones-Webb & Snowden, 1993; Mendelson et al., 2008;
Ramos, 2005). Increased risk for depressive symptomology in Blacks and Hispanics may be
partially explained by risk factors associated with lower socioeconomic status (SES) such as
financial pressure and disparate access to resources as well as problems associated with being in
a minority group like feeling pressure to acculturate to mainstream society (Jones-Webb &
Snowden; Oquendo et al., 2004; Ramos; Wight et al., 2005). Nonetheless, even when examining
individual and contextual differences such as the ethnic status of the surrounding community
researchers have been unable to pinpoint all of the factors associated with being a member of a
12
minority group that may explain the relationship between minority status and depressive
symptoms, leading some to speculate that membership in an ethnic group that is in the minority
may be “fundamentally related to depressive symptoms” via differences in feelings of power,
prestige, and connectedness (Wight et al., p. 2081).
In conclusion, non-White groups in the United States may be at decreased risk for MDD
compared with Whites, but a greater proportion of individuals within those minority groups may
consistently experience elevated depressive symptomology, and when they do suffer from MDD,
it is more severe and persistent than it is for Whites (Breslau et al., 2006; Williams et al., 2007).
Etiological Influences on Depression
Etiological models of depression vary considerably. Some are exclusive in the factors
that they propose lead to depression yet increasingly more integrate an eclectic selection of
biological, environmental, psychological, and religious or spiritual characteristics that are
thought to interact to contribute to risk or protection from depression (Zuess, 2003).
Biological Influences. Potential biological influences on depression include genetic
structure (Kendler, Walters, Truett, & Heath, 1994; Lyons et al., 1998; Zubenko et al. 2002,
2003), problematic hormonal and endocrine fluctuation such as dysregulation of the
hypothalamic-pituitary-adrenal axis (Bloch, Daly, & Rubinow, 2003; Ehlert, Gaab, & Heinrichs,
2001), and neurotransmitter imbalances (Fava & Kendler, 2000). However, it can be difficult to
determine direction of causality between biological correlates and depression as well as account
for potential confounds such as life stress that may influence both biology and depression (Wyatt
& Midkiff, 2006). Assessing biological factors requires special instrumentation or research
design, and such factors are, therefore, outside of the scope of this study. For a comprehensive
13
list of biological and other factors associated with depression, please see Parker and Roy (2001)
and Vink, Aartsen, and Schoevers (2008).
Life Events. Life stressors, particularly negative life events, are significantly positively
associated with depressive symptoms, and depressed individuals report substantially more life
stress in the previous year than nondepressed individuals (Kessler, 1997). Although positive life
events can contribute to overall life stress, which may increase risk for depression, life events
considered to be negative typically have a stronger association with depression (Holmes & Rahe,
1967; Kessler, 1997). Common life stressors that can have a significant impact on the etiology of
depression include interpersonal relationships (Barnett & Gotlib, 1988), socioeconomic status
(Hudson, 2005), and life events (Kendler et al., 1999). Negative and potentially traumatic life
events include trouble with a boss, death of a family member, pregnancy, troubles with the law,
major change in financial status, and separation from a mate (Holmes & Rahe, 1967). Results
from a year-long twin study suggest that negative life events account for the majority of variance
in depression (Kendler et al.); however, potential bidirectionality prohibits such a strong claim
because it is difficult to determine the extent to which psychopathology increases the experience
and recall of negative life events (Kessler, 1997). Nonetheless, research indicates that negative
life events often precipitate the onset of depression (Kendler et al.).
Religion and Spirituality. Religiosity and spirituality refer to a multidimensional set of
psychological and social factors such as systems of belief, values, rituals, interpersonal
relationships, and social norms (King & Dein, 1998). Because of their ubiquity in nearly every
human culture and their unique role in the drive for purpose and meaning, religiosity and
spirituality are often considered as distinct from other psychological or social factors (Zuess,
2003). The multifaceted nature of religiosity and spirituality has created challenges in identifying
14
their role in the development of depression that have resulted in conflicting outcomes (George,
Larson, Koenig, & McCullough, 2000; McCullough & Larson, 1999). Therefore, it is necessary
to specify which dimension is being considered (Mofidi et al., 2006). For example, the religious
social support received during times of stress may protect an individual from the development of
depressive symptoms, but blaming God for negative life situations may increase risk (Smith,
McCullough, & Poll, 2003). Beliefs about God and a higher purpose in life may protect from
feelings of hopelessness, which in turn reduces risk for depression (Murphy et al., 2000).
Individual Differences. Psychological characteristics that may play a role in the
development of depression include personality traits (Bagby, Quilty, & Ryder, 2008), selfesteem and self-concept (Orth, Robins, & Roberts, 2008; Sheppes, Meiran, Schechtman, &
Shahar, 2008), cognitions and beliefs (Beck, 1963; Kleinman, 2004), and the manner in which an
individual assigns causation and meaning to life events (Abramson, Metalsky, & Alloy, 1989).
Although the potential psychological variables involved in depression are vast, this project
emphasizes the role of cognitive processes, particularly those which may be associated with
decreased risk for depressive symptoms. Two influential theories highlighting the significance of
cognition in affecting depressive symptoms include Abramson’s learned helplessness model,
which later became known as the hopelessness model (Abramson, Seligman, & Teasdale, 1978),
and Beck’s (1963) cognitive theory. The learned helplessness and hopelessness models
emphasize the psychological effects of uncontrollable stressful situations. The extent to which
the stressful situation confers risk for depression may depend on a person’s attributional style,
which indicates how individuals explain the causes of their stressors. Individuals who believe
prior stressful life events are caused by internal (their fault), stable (will endure), and global
(affects many situations) factors are said to have a pessimistic explanatory style. Conversely,
15
those with optimistic explanatory style attribute stressful situations to external, transient, and
specific factors (Abramson et al.). Empirical support indicates that pessimistic explanatory style
is associated with increased depressive symptomology and optimistic explanatory style is
associated with lower risk of depression (Abramson et al., 1989; Puskar, Sereika, Lamb, TusaieMumford, & McGuinness 1999).
Over 40 years ago, Aaron Beck introduced his theory of depression that posits that
depressed individuals demonstrate a triad of pervasive cognitive patterns: negative views of
one’s self, the world, and the future (Beck, 2002). Beck’s approach emphasizes the etiological
role of dysfunctional beliefs that cause individuals to have unrealistic expectations about their
environments. These underlying dysfunctional beliefs are thought to be relatively latent until
activated by a specific stressor that targets the individuals’ cognitive susceptibility (Haaga, Dyck,
& Ernst, 1991). Once activated, the beliefs lead to distorted thinking that directly negatively
affects mood and predisposes the individual to selectively perceive environmental cues that
concur with the distorted cognitions. The process can quickly become a vicious cycle, leading to
increased depressive symptomology (Beck, 1963). Empirical investigations indicate support for
the main components of Beck’s cognitive theory such as the negative triad (Haaga et al.).
Grigsby (1994) has extended this support to college students, and Hammack (2003) supported its
main components among Blacks.
Beck’s model of depression and Abramson’s learned helplessness model are, however,
limited in their ability to fully explain causes of depression; therefore, they incorporate other
etiological factors into an integrated diathesis-stress model (Abramson et al., 1989; Haaga et al.,
1991). Diathesis-stress models take into consideration the possibility that different etiological
mechanisms contributing to depression may not be simply additive; they can interact in unique
16
ways. Variables that make a person more susceptible to depression such as maladaptive cognitive
patterns are referred to as diatheses, and those that precipitate depression such as acute life
events are stressors. The use of diathesis-stress models increases the flexibility and applicability
of cognitive models of depression by allowing researchers to take into consideration other
variables that may play a role in etiology (Abramson et al.; Haaga et al., 1991). Recently,
increasing attention has been given to more positive variables that may prevent depression in
spite of life stressors (Joseph & Linley, 2005; Schueller & Seligman, 2008; Seligman &
Csikszentmihalyi, 2000). More positive characteristics such as hope and optimism may directly
lead to decreased depressive symptoms as well as mitigate or undermine the negative influence
of diathesis variables such as hopelessness and pessimism (Fredrickson & Losada, 2005;
Seligman et al., 2005). According to diathesis-stress models of depression, even if cognitive or
behavioral vulnerabilities for depression exist, symptoms will not surface unless sufficient stress
from outside the person is present. Therefore, one would expect the differences between
individuals with and without positive or protective characteristics to be relatively small at low
levels of life stress and increasingly larger as life stress increases. Indeed, the mitigating effects
of hope and optimism on depressive symptoms have been found to be stronger among
individuals who have experienced elevated levels of life stress versus those who reported little
life stress (Chang, 1996 & 2002; Reff, Kwon, & Campbell, 2005; Scheier & Carver, 1985;
Snyder et al., 1991). A similar pattern has been found for measures of religiosity and religious
coping particularly when life stress is judged to be severe (Bjorck & Thurman, 2007; Pargament,
Smith, Koenig, & Perez, 1998; Smith et al., 2003; Walsh et al., 2002).
17
Psychological and Religious or Spiritual Moderators of Depression
Negative life events increase risk for depressive symptoms (Kendler et al., 1999);
however, the potential deleterious impact of a given event may vary between individuals based,
in part, upon their unique set of psychological and religious or spiritual characteristics (Zuess,
2003). Such individual-level characteristics that might influence the association between
negative life events and depressive symptoms are referred to as moderators (Baron & Kenny,
1986). Studying variables that may buffer or attenuate the relationship between negative life
events and depressive symptoms may give insight into how depression develops and is
manifested.
Trait Hope
The concept of hope has been around for millennia. In an ancient Greek myth, Pandora
inadvertently released all kinds of creatures into the world. Almost all of them were types of evil
and disease except for the creature hope that promised to make the burdens that humans
experience less troublesome as they pursue life goals (Smith, 1983). The construct of hope was
neglected in scientific research for many years, possibly because of disagreement about
operationalization and assessment (Snyder et al., 1991). Generally, researchers agreed that
hopefulness referred to an overall perception that a person can achieve his or her goals, but it was
not until Snyder et al. empirically investigated the construct that a unified definition of hope was
developed.
According to Snyder’s model, trait hope is differentiated from state-hope, with the former
considered a more enduring cognitive disposition and the latter a context-dependent appraisal.
Trait hope is a cognitive-motivational construct composed of two distinct yet related elements
that influence one’s perception that his or her goals can be achieved. Agency refers to a “…sense
18
of successful determination in meeting goals in the past, present, and the future,” and pathways
refers to a “…sense of being able to generate successful plans to meet goals” (Snyder et al.,
1991, p. 570). People with high agency believe that they have the personal efficacy required to
achieve goals, and people with high pathways perceive that they have the resources necessary to
achieve goals. Adequate amounts of both must be present for individuals to believe that they can
and will achieve their goals. Hence, they are both necessary, but neither is sufficient.
The essential aspects of Snyder’s hope theory have received support from the literature.
Chang and DeSimone (2001) found that the scores obtained on Snyder’s Trait Hope Scale (THS)
(Snyder et al., 1991) were predictive of higher levels of engaged coping behavior and negatively
associated with disengaged coping behavior, which fits well with trait hope’s theoretical
relationship to goal attainment. Another study found amount of trait hope to be positively related
to level of adaptive problem solving behavior (Chang, 1998b). These correlates of hope may
serve to buffer against psychopathology by enabling individuals who experience life stressors to
effectively deal with them.
Trait Hope and Depression. Using a university sample of 241 students, Snyder et al.
(1991) found that the THS was significantly negatively correlated (-.42, p<.005) with the Beck
Depression Inventory. No data regarding ethnic background were available for the study, which
limits its generalizability. Using data collected from 341 college students, Chang and DeSimone
(2001) found a negative relationship between the THS and BDI even when controlling for the
effects of coping style and secondary appraisals. Using a sample of 159 undergraduate students,
Kwon (2000) tested the hypothesis that hope would only predict decreased depressive
symptomology for individuals with adaptive defense styles, but he found that trait hope was
associated with lower levels of depression regardless of an individual’s defense style. A
19
longitudinal study of 522 college students found that higher THS scores at baseline were
predictive of decreased levels of depression 1 month and 2 months later and that THS scores
were unaffected at 1 and 2 month intervals by prior depression scores, supporting hope’s
dispositional nature (Arnau, Rosen, Finch, Rhudy, & Fortunato, 2007). The relationship,
however, was explained by the agency rather than the pathways component, which conflicts with
the assertion made by Snyder et al. that both aspects of trait hope contribute unique variance to
the activation of hope.
Trait Hope and Negative Life Events. Levels of hope have been found to moderate the
relationship between life stressors and psychological outcomes (Reff, Kwon, & Campbell, 2005;
Snyder et al., 1991). In one study, after collecting baseline THS scores students were given a
negative exam grade; individuals who were high in trait hope responded to the negative grade by
demonstrating higher goal-directed determination, whereas those low in trait hope demonstrated
lower goal-directed determination (Snyder et al.). In a similar study, after participants were
assessed for trait hope and depressive symptoms, they were asked to indicate what score they
would consider a failure on an upcoming exam. After taking the exam, those who scored at or
below their failure range and were low in trait hope experienced an increase in depressive
symptoms, whereas those high in hope were protected from the negative effect of failing to reach
their goal, indicating that trait hope may buffer the negative effect of academic stress on
depressive symptoms (Reff et al.).
Trait Hope and Ethnicity. To date, little research has examined how trait hope may differ
across ethnic groups. In a diverse college sample of 374 students, Chang and Banks (2007) found
that Hispanics scored higher on agency than Whites and Blacks but not Asian Americans. On the
pathways component, Blacks and Hispanics scored significantly higher than Whites and Asian
20
Americans. These different levels of trait hope contradicted predictions, as the authors expected
ethnic minorities, because of their relatively greater exposure to psychosocial stressors, to score
lower than Whites. The higher rates of trait hope in Blacks and Hispanics may be due to a
selection bias because ethnic minorities who are enrolled in college may be those who are likely
to have more adaptive problem solving skills (Chang & Banks). Although it is not clear from the
study why these ethnic differences were found, it highlights the fact that the causes and effects of
trait hope may vary as a function of one’s ethnic identity (Chang & Banks).
Dispositional Optimism
In a broad sense, dispositional optimism is a general expectancy that good things will
occur in the future (Scheier & Carver, 1985). The foundation for the theoretical framework of
dispositional optimism that is widely used today stems from Carver and Scheier’s (1982)
description of control theory and their model of behavioral self-regulation. Control theory posits
that humans perceive their present condition through a feedback system and then compare it to a
standard reference. If a discrepancy exists between their present condition and the standard, they
activate behavior in order to draw closer to the standard of reference; however, they will only do
so if they have an expectation of success (Carver & Scheier). In other words, humans only selfregulate when they believe that their efforts will succeed. Success can be very specific such as
receiving a high grade on one exam or general such as becoming a successful person. Scheier
and Carver’s conceptualization of optimism emphasizes more general expectancies that are less
susceptible to change when environmental circumstances fluctuate. Therefore, in this sense,
optimism is considered a trait. The Life Orientation Test (LOT) (Scheier & Carver) and the Life
Orientation Test - Revised (LOT-R) (Scheier, Carver, & Bridges, 1994) were designed to
measure optimism as a trait. Supporting optimism’s dispositional nature, Scheier et al. found a
21
test-retest reliability coefficient of r = .79 across 28 months in a sample of 2,055 college students
using the LOT-R. In summary, optimistic individuals are more likely to consistently exhibit
behaviors that stem from positive, general expectancies about the future even when they are
confronted with life stressors that may be perceived as threats to achieving certain general goals
(Scheier et al., 1994).
Dispositional Optimism and Depression. Scheier et al. (1994) administered the LOT-R
and a variant of the BDI (a shorter version with 13 questions) to 2,055 college students between
1988 and 1990. They found that the LOT-R was significantly negatively correlated (r = -.42;
p<.001) with the BDI short form. The relationship between the LOT-R and BDI short form was
still significant after controlling for the effects of self-mastery, trait anxiety, self-esteem, or
neuroticism. In a meta-analysis of the LOT, Andersson (1996) concluded that the relationship
between the LOT and BDI is highly reliable. He found that the LOT and BDI had been
correlated in five studies, and the weighted combined r was -.45. A recent study found that the
LOT-R and the BDI-II were significantly negatively correlated (r = -.53) in a sample of college
students (Hirsch, Wolford, Lalonde, Brunk, & Parker-Morris, 2007).
Dispositional Optimism and Negative Life Events. Scheier and Carver (1985) conducted a
longitudinal study in which college students completed the LOT and a physical symptoms
checklist 4 weeks before the end of the semester (a potentially stressful time) and again at the
end of the semester. Scores reflecting higher levels of dispositional optimism at Time 1 were
significantly predictive of fewer subjective physical complaints at Time 2 even when controlling
for Time 1 differences in physical symptoms. These results indicate that higher dispositional
optimism may protect individuals who experience life stress from physical problems (Scheier &
Carver). In samples of 388 college students, 340 younger adults, and 316 older adults, Chang
22
(1998a, 2002) found that individuals who perceived high levels of life stress yet scored high in
dispositional optimism reported significantly fewer depressive symptoms than those with high
life stress and low optimism. These results support dispositional optimism as a moderator of life
stress and depressive symptoms. A recent study found that dispositional optimism moderated the
relationship between negative life events and suicidal thoughts and behaviors in a college sample
of 138 students (Hirsch, Wolford, et al., 2007). Negative life events predicted increased suicidal
ideation and attempts, but higher levels of optimism buffered the relationship.
Styles of coping with negative life situations are significantly related to levels of
dispositional optimism (Scheier, Weintraub, & Carver, 1986). In a sample of 291
undergraduates, higher levels of optimism predicted more adaptive coping strategies such as
problem focused coping and positive reinterpretation of events, and lower levels of optimism
predicted maladaptive coping strategies like disengagement and emotion focused coping.
Optimists’ more adaptive responses to adversity may limit the negative effects of stressful life
events (Scheier, Weintraub, & Carver, 1986). Additionally, Khoo and Bishop (1996) suggest that
optimists may simply experience less subjective stress than pessimists even in the same
circumstances, and this difference may be due to the cognitive biases of pessimists to recognize
and dwell on negative components of a situation.
Increased optimism, however, may not always predict more positive outcomes. Elevated
optimism may decrease one’s sense of vulnerability to injury or disease and lead to risky
behavior (Gerrard, Gibbons, & Bushman, 1996; Weinstein, 1980) or poor health outcomes. For
instance, Hirsch, Wolford, et al. (2007) found that although the relationship between negative
life events and suicide ideation was weakened in individuals with high versus low levels of
23
optimism, the association was exacerbated for individuals with especially high levels of
optimism.
Optimism and Ethnicity. Some evidence suggests that the effects of optimism may differ
across ethnic groups (Hardin & Leong, 2005). Chang (1996) conducted a study of Asian
Americans and Whites and found that levels of optimism were not significantly different
between the two ethnicities; however, optimism significantly predicted physical symptoms in
Asian Americans but not Whites (Chang). Using a variant of the LOT (extended scale including
20 questions), Hardin and Leong (2005) found that optimism and pessimism mediated the
relationship between undesired self-discrepancy and depressive symptoms differently in Asian
Americans than Whites, with pessimism mediating more of the effect in Whites than Asian
Americans. More research is necessary to understand how levels and functions of optimism may
vary across ethnic groups (Chambers, 2006).
Religiosity and Spirituality
The relationship between religion and the field of psychology has been marked with
ambivalence. Religion was treated as more of a nuisance or detriment by researchers like
Sigmund Freud (Koenig & Larson, 2001) and Albert Ellis, who implied that religious tendencies
are at the core of psychopathology (Dryden & Ellis, 2001). Yet, increasing numbers of academic
researchers have begun to specialize in the study of the positive and negative effects of religion
and spirituality on psychological and physical variables such as depression or mortality rates
(King & Crowther, 2004; McCullough & Larson, 1999). In research the constructs of religiosity
and spirituality have often been interchanged, but evidence demonstrates that in practice people
consider them different constructs (Zinnbauer et al., 1997). Both religiosity and spirituality can
refer to the search for a higher power (George et al., 2000), but religiosity is associated more
24
with institutions and traditions, whereas spirituality emphasizes personal experiences with the
supernatural (Zinnbauer et al.). Members of religious organizations who participate in
organizational traditions may be considered religious, but this does not guarantee that members
actively pursue knowledge of or experience with a higher power (George et al., 2000). Findings
from surveyed members of religious and social groups suggest that religiousness may be divided
into two components: 1) personal beliefs about God or a higher power and 2) organizational
beliefs and practices such as church attendance and commitment to belief systems. Definitions of
spirituality also included belief in God or a higher power, but they emphasize broader
experiential terms such as having a relationship with God or a connection with a supernatural
force (Zinnbauer et al.).
Research on religiosity and spirituality has advanced in recent decades as investigators
have focused on which dimensions of religion and spirituality are associated with physical and
mental health outcomes (Neff, 2006; Zinnbauer et al., 1997). A panel convened by the National
Institute of Healthcare Research identified 10 domains of religiosity and spirituality that have
been studied in empirical research: 1) Preference or affiliation, 2) History, 3) Participation, 4)
Private Practices, 5) Support, 6) Coping, 7) Beliefs and values, 8) Commitment, 9) Motivation
for regulating and reconciling relationships, and 10) Experiences (George et al., 2000).
Religiosity, Spirituality, and Depression. A review of the literature on the association
between religion and depression revealed that two thirds of relevant observational (60/93) and
prospective (15/22) studies found a significantly negative relationship between levels of religion
and depression (Koenig & Larson, 2001). Because of the lack of consensus on the operational
definition of religiosity, a wide variety of religious measures were represented in the study. A
recent meta-analysis found that the relationship between religion and depressive symptoms
25
across 147 studies (N= 98,975) was relatively weak (r = -.10; p = .003) (Smith et al., 2003).
When religiosity was defined in terms of intrinsic motivation, which is the motivation to engage
in religious practices that stems from actual belief in a higher power or force, the correlation
strengthened (r = -.18; p<.001). The relationship between measures of spirituality and depression
is less certain (Zinnbauer et al., 1997). Self-perception of one’s level of spirituality may be
related to higher depressive symptoms (Baetz et al., 2004), but some evidence also suggests that
higher spirituality is associated with less depression (George et al., 2000; Mofidi et al., 2007).
The direction of influence between religiosity or spirituality and depression is still not
clear. Religious or spiritual practices may have an ameliorative effect on depressive
symptomology. Conversely, individuals prone to depression may be more or less likely to seek
out religious or spiritual experiences (Smith et al., 2003). Smith et al. found that the most
researched hypothesis is that religiosity buffers depressive symptoms. There are a variety of
reasons that religiosity is suspected to have this effect. Religious individuals may be less likely to
abuse substances, may receive social support from their congregation, may have an increased
activity level, and may be more likely to experience high-quality relationships especially in
marriage (Smith et al.). From a cognitive perspective, religious and spiritual beliefs may counter
dysfunctional hopeless beliefs by providing a sense of eternal meaning and higher purpose
(Murphy et al., 2000).
Religiosity, Spirituality, and Negative Life Events. The relationship that religiosity or
spirituality have with depression may be strongest in times of great distress, suggesting an
interaction effect (Smith et al., 2003; Walsh, King, Jones, Tookman, & Blizard, 2002). In a
literature review, Smith et al. found support for religiosity as a buffer against the effect of stress
on depression especially when the stress was judged to be severe. For example, one study found
26
that the buffering effect of religiosity was strongest in individuals with cancer versus those with
a lesser or no illness (Musick et al., 1998). A prospective study of the close family and friends of
dying patients in London found that those with higher reported spirituality completed the
grieving process sooner than those with low spirituality, supporting the idea that spirituality may
buffer against the potentially negative effects of serious stressors (Walsh et al.).
In response to stressful situations religious or spiritual individuals may employ beneficial
coping strategies that subsequently protect them from psychological distress (Bjorck & Thurman,
2007). Using positive religious coping involves searching for a religious or spiritual
understanding of a stressful situation and maintaining a secure connection with God in spite of
distress. Negative religious coping may involve denial of meaning, feeling an insecure
relationship with God, and adopting a threatening view of the world and may exacerbate
symptomology related to life stress (Pargament, Koenig, & Perez, 2000). Religious coping
strategies have been found to moderate the relationship between acute stressors and
psychological distress as well as the aggregate impact of life stress and psychological distress
(Bjorck & Thurman, 2007).
Religiosity, Spirituality, Ethnicity, and Depression. The associations between religiosity
or spirituality and depression may differ across ethnic groups. The negative relationship between
religiosity and depression may be stronger in Blacks than Whites (McCullough & Larson, 1999).
In a study of community-dwelling adults living with cancer, religiosity buffered depressive
symptoms, and there was a significantly stronger effect in Blacks than in Whites (Musick et al.,
1998). Most research investigating how ethnicity affects the relationship between religiosity or
spirituality and depression has, however, been unable to find a moderating effect. In a metaanalysis of 147 studies, ethnicity did not appear to moderate the relationship between depression
27
and religiosity, but because of limitations comparisons were only conducted among Blacks,
American Whites, and Northern Europeans (Smith et al., 2003). A study involving a communitybased sample of 630 adults 45 years and older found that ethnicity did not moderate the
relationship between spiritual experiences and depressive symptoms; however, this study only
assessed Blacks and Whites (Mofidi et al. 2006). A recent study involving 615 Black, White,
Hispanic, and Asian American adolescents of diverse religious backgrounds did not find a
moderating effect of ethnicity in the relationship between various daily spiritual experiences and
BDI scores (Desrosiers & Miller, 2007). In summary, some evidence suggests that religiosity and
spirituality affect depression regardless of ethnicity, but more research needs to be done.
Statement of the Problem
Depression is a serious and potentially growing problem among college students.
Negative life events are predictive of higher depression; however, not everyone who experiences
negative events becomes depressed. Psychological factors such as trait hope, optimism, and
religiosity and spirituality may buffer against depressive symptomology even in individuals who
have experienced elevated life stress. Little is known about how these factors vary across
different ethnic groups. This study examines the role of trait hope, optimism, and religiosity and
spirituality in the relationship between negative life events and depressive symptoms in an
ethnically diverse college sample. To date, such a study has not been published.
Hypotheses
1. The number of negative life events reported on the LES are significantly
positively associated with the number and degree of depressive symptoms
reported on the BDI-II.
28
2. The levels of trait hope reported on the THS and dispositional optimism reported
on the LOT-R are significantly negatively associated with scores on the BDI-II.
3. The levels of religious involvement and belief and daily spiritual experiences
reported on the BMMRS are significantly negatively associated with scores on
the BDI-II.
4. Positive religious coping as measured with the BMMRS is significantly
negatively associated with scores on the BDI-II, while negative religious coping
as measured with the BMMRS is significantly positively associated scores on the
BDI-II.
5. Scores on the THS, LOT-R, and daily spiritual experiences scale, organizational
religiousness scale, private religious practices scale, positive religious coping
scale, and negative religious coping scale moderate the relationship between
scores on the LES and BDI-II.
6. Differences in scores on the LES, THS, LOT-R, BMMRS, and BDI-II are
explored among ethnic groups.
7. Ethnic differences in the moderating effects of the THS, LOT-R, and daily
spiritual experiences scale, organizational religiousness scale, private religious
practices scale, positive religious coping scale, and negative religious coping
scale, in the relationship between scores on the LES and BDI-II are explored by
conducting ethnically-stratified moderator analyses.
29
CHAPTER 2
METHODS
Procedures
Participants in this study were recruited from an urban, Northeastern university in the
United States. The sample consisted of 386 students, 267 females and 119 males. After obtaining
IRB approval, undergraduate students in an introductory psychology course who were 18 years
of age or older were invited to participate in a study examining the relationship between stress,
resiliency, and psychological functioning in college undergraduates. Students who agreed to
participate completed a series of questionnaires assessing mood, levels of depression, ethnic
identification, negative life events, spirituality, positive psychological characteristics including
hope and optimism, and demographic characteristics in a group setting. After review by a
research assistant, any student identified as at-risk for suicide was scheduled to meet with the
principal investigator for a clinical assessment. All participating students received 2 credits
toward their course research requirement. All introductory psychology students who volunteered
were selected for participation. Data collection took place during the spring and fall semesters of
2005. The present study is a secondary analysis of data gathered for a separate project.
Measures
Beck Depression Inventory-II (BDI-II).
The BDI-II (Beck, Steer, Ball, & Ranieri, 1996) is a 21-item self-report measure of the
presence and severity of cognitive, affective, somatic, and motivational symptoms of depression.
Beck et al. found evidence in a college sample for a two-factor structure of the BDI-II composed
of cognitive-affective and somatic factors, and other researchers have found evidence for various
two and three factor solutions emphasizing negative attitudes, performance difficulty, and
30
somatic dimensions (Arnau, Meagher, Norris, & Bramson, 2001; Carmody, 2005; Storch,
Roberti, & Roth, 2004).
The BDI-II is scored using a 4-point Likert scale ranging from 0-3, with 0 representing
the absence of a symptom and 3 representing severe presence of a symptom; however, two items
(16 and 18) allow the participant to select 1a or 1b, 2a or 2b, and 3a or 3b in order to determine if
sleep or appetite has increased or decreased. Items are summed to derive a total depressive
symptoms score. Cutoff scores recommended by Beck et al. (1996) indicate that minimal
depressive symptoms range from 0-13, mild depressive symptoms range from 14-19, moderate
depressive symptoms range from 20-28, and severe depressive symptoms range from 29-63.
Running a series of analyses testing for optimal sensitivity and specificity, Dozois, Dobson and
Ahnberg (1998) recommended the following cutoffs for undergraduate students: nondepressed =
0-12, dysphoric = 13-19, dysphoric or depressed = 20-63. The BDI-II predicted major depressive
disorder in a clinical sample and a collegiate sample (Beck et al.) and has exhibited adequate
test-retest reliability using Pearson’s Correlation coefficient (r = .93 in Beck et al., 1996; r = .92
in Carmody, 2005). Using Cronbach’s alpha, a measure of how well the items of a construct
reflect an underlying factor (Cronbach, 1951), the BDI-II demonstrated good internal
consistency (α = .91) in a sample of 1,022 undergraduates, and corrected item-total correlations,
calculations of an individual item’s relationship with the sum of the other items in the scale,
ranged from .18 (suicidal thoughts) to .88 (changes in sleep; Dozois et al., 1998). Convergent
validity of the BDI-II has been supported with significant relationships with the State-Trait
Anxiety Inventory depression (r = .77) and anxiety (r = .70) factors in a sample of 414
undergraduates (Storch et al., 2004). In the current study α = .88. For the entire sample, the itemtotal correlations suggest good internal consistency, with r ranging from .41 to .64, except for the
31
item “loss of interest in sex” (r = .23), which has been found to be less reliable in other college
samples as well (Carmody, 2005; Osman et al., 1997). Consistent with previous research (e.g.,
Nolen-Hoeksema & Girgus, 1994), females in the present sample reported significantly more
depressive symptoms than males [Mean BDI-II (SD) = 14.44 (9.22) and 9.20 (6.30),
respectively, p<.001].
Life Events Scale (LES).
The LES (Tomoda, 1997) is a checklist of 43 positive and negative life events that
college students may be more likely than others to experience. Respondents are asked to check
all life events that they experienced at least once in the previous 12 months. The LES includes
items such as, “I had financial difficulties” and “I made a financial profit.” Items assessing
positive and negative life events can be summed separately to create positive and negative
subscales, and all 43 items can be summed to determine an overall life adjustment score. Holmes
and Rahe (1967) found that the social readjustment resulting from experiencing both positive and
negative life events can lead to higher life stress that may increase risk of stress-related
problems. The current study, however, focuses only on negative and potentially traumatic life
events that research suggests are more strongly associated with increased depression than
positive, yet stressful, life events (Kendler et al., 1999). There are 23 items from the LES that
assess negative and potentially traumatic life experiences. No gender differences were found in
mean number of reported negative life events.
Trait Hope Scale (THS).
The THS (Snyder et al., 1991) is a 12-item scale designed to measure dispositional hope.
This scale contrasts with the state hope scale later developed by Snyder and colleagues in that it
conceptualizes hope as an enduring trait rather than as dependent upon situations (Snyder et al.,
32
1996). The THS is composed of two factors - agency assesses one’s belief in his or her own
ability to achieve goals and pathways assesses the extent to which one has the necessary
resources to achieve his or her goals (Roesch & Vaughn, 2006; Snyder et al., 1991). Items 2, 9,
10, and 12 comprise the agency component, items 1, 4, 6, and 8 comprise the pathways
component, and the other items are fillers. In this study, the THS was scored using a 4-point
Likert scale allowing a possible range of 8-32 with higher values indicating stronger hope. The
THS has been shown to be negatively related to depression; for example, Snyder et al. (1991)
found a significant negative correlation between the THS and the original BDI (r = -.42). Snyder
et al. (1991) found convergent validity support for the THS, in a pair of studies, with significant
positive associations with the Life Orientation Test (r = .50 & .60) and divergent validity
support, in a single study, with a negative association with the Beck Hopelessness Scale (r = .51). In six college samples and two outpatient samples of people seeking psychological
treatment, the THS has demonstrated adequate internal consistency (α = .63-.84) and test-retest
reliability (r = .73-.85; Snyder et al.). In the current study, α = .81. The corrected item-total
correlations suggest adequate internal consistency, with r ranging from .34 (“I can think of many
ways to get out of a jam”) to .61 (“Even when others get discouraged, I know I can find a way to
solve the problem”). In the current sample, males (M = 25.50, SD = 3.69) scored significantly
higher than females (M = 24.33, SD = 3.75) on reported trait hope, (p<.05).
Life Orientation Test-Revised. (LOT-R).
Scheier and Carver (1985) developed the Life Orientation Test (LOT), which was later
reduced from 12 to 10 items by Scheier, Carver, and Bridges (1994). The LOT-R measures
dispositional optimism via general outcome expectancies of the respondent. It consists of three
positively worded, three negatively worded, and four filler items and requires participants to
33
indicate how strongly they agree with each statement using a 5-point Likert scale. For scoring,
items 1, 4, and 10 are reverse-scored and added to items 3, 7, and 9 to create a total score,
ranging from 0-24, with higher values indicating greater optimism. In a German epidemiological
study (n = 46,133), the optimism subfactor comprised of the 3 positively worded items and the
pessimism subfactor comprised of the 3 negatively worded items significantly predicted
depression when both were included in a regression analysis (βs = -.47 and .24, respectively)
(Herzberg, Glaesmer, & Hoyer, 2006). The LOT-R demonstrated acceptable internal consistency
(α = .84), and it was associated with decreased depressive symptoms (r = -.53) and hopelessness
(r = -.55) in a college sample of 138 students, supporting its discriminant validity (Hirsch,
Wolford, et al., 2007). However, in a sample of individuals receiving treatment for opiate
dependence in a methadone maintenance program, unacceptable internal consistency was found
in Blacks and Hispanics, and 2-week test-retest reliability was low in Blacks, (Hirsch, Britton, &
Conner, in press). In the present study, convergent validity was supported by significant modest
correlations between the LOT-R and self-mastery (r = .48) and self-esteem (r = .50) in a sample
of 4,309 college students (Scheier et al., 1994). For the current sample α = .76. The corrected
item-total correlations suggest adequate internal consistency with r ranging from .32 (“In
uncertain times, I usually expect the best”) to .61 (“Overall, I expect more good things to happen
to me than bad”). In the current sample, females (M = 11.72, SD = 5.18) scored significantly
higher (p<.05) than males (M = 10.72, SD = 5.07) on reported dispositional optimism.
Brief Multidimensional Measure of Religiousness and Spirituality (BMMRS).
The BMMRS (Fetzer Institute, 1999) is a 38-item scale designed to assess 11 core
dimensions of religiosity and spirituality identified by the Fetzer Institute to be theoretically and
empirically related to physical and mental health. The core dimensions include daily spiritual
34
experiences, values and beliefs, forgiveness, private religious practices, religious and spiritual
coping, religious support, religious and spiritual history, commitment, organizational
religiousness, religious preference, and self-assessed rankings of global religiosity and
spirituality. Scales are intended to be scored and analyzed independently of each other (Fetzer
Institute). For the current study, the scales assessing daily spiritual experiences, private religious
practices, organizational religiousness, and religious and spiritual coping were used. Daily
spiritual experiences items directly assess the impact of religion and spirituality on one’s
everyday life; private religious practices refer to a subset of religious behaviors occurring outside
of the context of organized religion; organizational religiousness refers to one’s attendance of
worship services as well as involvement in other church-related activities; religious coping refers
to the religious responses individuals are likely to use in stressful life situations, with positive
religious coping tapping into beneficent religious involvement and search for meaning and
negative coping reflecting religious struggle and doubting (Fetzer Institute).
Researchers have investigated the psychometric properties of the BMMRS. Internal
consistency estimates were derived from a sample of 1,145 participants for daily spiritual
experiences (α = .91), private religious practices (α = .72), organizational religiousness (α =
.82), positive religious coping (α = .81), and negative religious coping (α = .54) (Fetzer Institute).
In a sample of 122 patients with chronic pain, daily spiritual experiences significantly predicted
better mental health status (r = .27) as measured by the SF-36, while negative religious coping
negatively predicted mental health status (r = -.31) (Rippentrop, Altmaier, Chen, Found, &
Keffala, 2005).
In the current sample, the internal consistency estimates were obtained. For daily spiritual
experiences, α = .89, and the corrected item-total correlations suggested good internal
35
consistency, with r ranging from .54 (“I feel deep inner peace or harmony”) to .79 (“I feel God’s
presence”). For private religious practices, α = .75, and corrected item-total correlations
indicated adequate internal consistency, with r ranging from .46 (“How often do you pray
privately in places other than at church of synagogue?”) to .68 (“How often do you read the
Bible or other religious literature?”). For organizational religiousness, α = .72, and no inter-item
correlations were assessed because the scale is composed of only two items. For positive
religious coping, α = .82, and the corrected item-total correlations suggested adequate internal
consistency, with r ranging from .61 (“I think about how my life is part of a larger spiritual
force”) to .69 (“I look to God for strength, support, and guidance”). Lastly, for negative religious
coping, α = .65, and the corrected item-total correlations suggested acceptable internal
consistency, with r ranging from .32 (“I try to make sense of the situation and decide what to do
without relying on God”) to .56 (“I wonder whether God has abandoned me”). The fairly low
internal consistency estimate for negative religious coping is similar to that found by Desrosiers
and Miller (2007) in a sample of 615 adolescents and in other research by the Fetzer Institute
(1999). No gender differences were found on any of the subscales of the BMMRS.
Statistical Analyses
Prior to analysis, a statistical and visual review of the data was conducted to determine
the presence of any outliers or missing data and to verify normality of data. None of the statistics
for skewness and kurtosis exceeded an absolute value of 1.25 and 3.00, respectively; therefore,
data were not transformed (Norris & Aroian, 2004). In the moderator regression models,
predictor and moderator variables were centered prior to analyses to reduce multicollinearity
(Aiken & West, 1991). Pearson’s product-moment correlation coefficient was used to determine
independence of study variables. Excessive multicollinearity was determined by a conservative
36
coefficient of r = .70 or higher (Field, 2005). Only positive religious coping and daily spiritual
experiences exceeded this cutoff, but they were not included in regression analyses together.
Specific hypotheses were tested using the following methods:
Hypothesis 1: Pearson’s product moment correlation tested for a positive relationship
between scores on the LES and BDI-II.
Hypothesis 2: Pearson’s product moment correlation tested for a negative
relationship between the THS and BDI-II as well as the LOT-R and BDI-II.
Hypothesis 3: Pearson’s product moment correlation tested for a positive relationship
between the daily spiritual experiences scale and BDI-II, the private religious
practices scale and BDI-II, and the organizational religiousness scale and BDI-II.
Hypothesis 4: Pearson’s product moment correlation tested for a positive relationship
between the negative religious coping scale and BDI-II, and a negative relationship
between the positive religious coping scale and BDI-II.
Hypothesis 5: To test for moderators in the relationship between the LES and BDI-II,
hierarchical, multivariate linear regressions were used, according to accepted
guidelines (Baron & Kenny, 1986). The THS and LES were centered to reduce
multicollinearity (Aiken & West, 1991) and then entered into the first step of a linear
regression along with covariates of age and gender; the BDI-II total score was the
dependent variable. The interaction term created by multiplying the centered
variables of the THS and LES was entered into the second step of the regression. A
moderation effect was found if the ΔR2 value for the second step significantly
accounted for additional variance. The same steps were followed in subsequent
regressions with the LOT-R, the daily spiritual experiences scale, the private
37
religious practices scale, the organizational religiousness scale, the positive religious
coping scale, and the negative religious coping scale as the moderators.
Hypothesis 6: A series of analysis of variance (ANOVA) tests were used to explore
differences in mean levels of the THS, LOT-R, daily spiritual experiences scale,
private religious practices scale, organizational religiousness scale, positive religious
coping scale, negative religious coping scale, and BDI-II across gender and ethnic
groups.
Hypothesis 7: Moderation analyses following the same steps as those described in
step 5 were conducted within each ethnic group separately for the THS, LOT-R,
daily spiritual experiences scale, private religious practices scale, organizational
religiousness scale, positive religious coping scale, and negative religious coping
scale. Ethnicity was used as a point of stratification rather than as a moderating
variable.
To produce graphic illustrations of significant moderator effects using simple slopes
regression lines, data were split based on values falling at or above one standard deviation
greater than the mean and values falling at or below one standard deviation less than the mean
(Aiken & West, 1991). To determine the unique effects of variables in moderation analyses, it is
important to statistically control for some variables (Baron & Kenny, 1986), a procedure that
assesses the effect of the independent variable on the dependent variable over and above the
effects of control variables. With regard to depression, females are approximately twice as likely
as males to have subclinical and diagnosable MDD (Nolen-Hoeksema & Girgus, 1994) and
higher age is often predictive of increased levels of depression (Hasin et al., 2005). Therefore,
gender and age were controlled in moderation analyses.
38
CHAPTER 3
RESULTS
Descriptive Results
Demographic variables assessed included age, gender, religious affiliation, and education
level (see Table 1). Although income levels were assessed in the original study, excessive
missing data (30.30%) of this item precluded its use as in any analyses. The total sample
consisted of 386 (69.17% female) undergraduate students from an urban, Northeastern
university. Ages ranged from 18 to 46 years with a mean age of 19.60 (SD=3.12) years. Selfreports found that 41.45% (n= 160) of individuals were Hispanic, 25.39% (n= 98) were Black,
18.39% (n= 71) were White, 5.70% (n= 22) were Asian, less than 1% (n=3) were Native
American, and, of the remaining, 7.25% (n= 28) selected “Other” and 1.04% (n= 4) did not
respond to the question. No significant differences for the age of participants or year in college
were found across ethnic groups. Whites were significantly more likely to be male than were
Hispanics (p<.01).
Descriptive statistics were generated for each of the scales being used in the study (see
Table 1). Analysis of depressive symptoms, the outcome variable, revealed that the mean BDI-II
total score for the entire sample was 12.76 (SD = 8.53), which is similar to that reported by other
studies using college samples (Beck et al., 1996; Carmody, 2005). Using the cut-off scores
reported by Beck et al. (1996) in the original manual, 219 (60.0%) participants scored within the
minimal range of depressive symptoms (0-13); 80 (21.9%) scored in the mild range (14-19); 42
(11.5%) scored in the moderate range (20-28); and 24 (6.6%) scored in the severe range. Using
cutoff scores recommended by Dozois et al. (1998), 212 (56.8%) were nondepressed (0-12), 89
(23.9%) were dysphoric (13-19), and 72 (19.3%) were dysphoric or depressed (20-63).
39
Table 1
Levels of Demographic, Predictor, and Criterion Variables across Ethnic Groups
Variable
Total Sample
M
SD
Blacks
M
SD
Hispanics
M
SD
Whites
M
SD
Asians
M
SD
Depressive Symptoms
12.76 [8.53]
11.84 [8.36]
13.84
[9.18] 11.65 [7.33]
12.20 [10.32]
Negative Life Events
6.50
5.80
[3.62]
6.76
[3.67]
7.24
Trait Hope
24.68 [3.77]
25.92 [3.55]
24.54
[3.84] 24.93 [3.71]
23.09 [4.24]
Optimism
11.41 [5.15] 10.17a [5.01] 12.17b [5.26] 11.34 [5.30]
11.95 [3.84]
Spiritual Experiences
20.19 [7.84] 22.64a [7.18] 19.90b [7.45] 17.51b [8.46] 16.90b [8.02]
Religious Practices
12.89 [6.59] 15.26a [6.65] 11.98b [5.67] 10.70b [6.31]
Organizational Religiousness 4.33
[3.82]
6.11
[3.71]
[5.34]
11.35 [8.75]
[2.44]
5.00a [2.58]
4.10b
[2.28]
4.15
[2.48]
3.43
[2.46]
Positive Religious Coping
10.61 [2.02]
7.63 a [2.42]
6.82
[2.44]
6.11b [2.45]
6.62
[2.52]
Negative Religious Coping
5.62
5.38
[2.38]
5.70
[2.30]
5.35
6.76
[2.88]
Age
19.60 [3.12]
19.89 [3.48]
19.78
[3.70] 19.10 [1.65]
19.64 [2.30]
Year in college
1.49
1.56
1.44
[.70]
1.73
% Female
[2.27]
[.71]
[.72]
1.42
[1.83]
[.71]
[.63]
69.17%
70.41%
75.62%
53.52%
59.09%
Catholic
49.22%
23.47%
75.63%
54.93%
4.54%
Jewish
2.59%
0%
0.62%
8.45%
0%
Muslim
3.89%
3.06%
0%
5.63%
9.09%
Protestant
3.67%
6.12%
1.25%
2.82%
9.09%
Buddhist
2.59%
1.02%
0.62%
0%
27.27%
Other
23.32%
47.69%
13.75%
9.86%
18.18%
None
12.69%
16.33%
6.25%
18.31%
27.27%
Religious Affiliation
Note: a and b are significantly different from each other at p<.05.
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Trait Hope = Trait Hope Scale
total score; Optimism = Life Orientation Test-Revised total score; Religion and Spirituality variables =
subscales of Fetzer Brief Multidimensional Measure of Religiousness / Spirituality.
Note: Year in college based on values of 1= Freshman, 2= Sophomore, 3= Junior, and 4= Senior.
Mean Differences Across Ethnic Groups
Using the analysis of variance (ANOVA) test, mean levels of each study variable were
assessed to see if they differed by ethnic status. Significant ethnic differences were found for
optimism, F(3, 341) = 3.45, p = .017; daily spiritual experiences, F(3, 341) = 7.35, p<.001;
40
private religious practices, F(3, 341) = 8.09, p<.001; organizational religiousness, F(3, 341) =
4.06, p = .007; and positive religious coping, F(3, 341) = 5.27, p = .001 (see Table 1). Bonferroni
post-hoc analyses revealed that Hispanics reported significantly higher levels of optimism than
Blacks (Mdiff = 2.10, p = .010). Blacks reported significantly higher levels of daily spiritual
experiences than Hispanics (Mdiff = 2.76, p = .032), Whites (Mdiff = 5.00, p<.001), and Asians
(Mdiff = 5.58, p = .009). For private religious practices, Blacks again reported significantly higher
levels than Hispanics (Mdiff = 3.31, p<.001) and Whites (Mdiff = 4.29, p<.001) but not Asians
(Mdiff = 3.87, p = .067). For organizational religiousness, Blacks reported significantly higher
levels than Hispanics (Mdiff = 0.91, p = .022) but not Whites (Mdiff = 0.86, p = .133) nor Asians
(Mdiff = 1.53, p = .052). Blacks reported significantly higher levels of positive religious coping
than Whites (Mdiff = 1.93, p = .001) but not Hispanics (Mdiff = 0.81, p = .065) nor Asians (Mdiff =
1.00, p = .527).
Bivariate Associations Among Study Variables
An analysis using Pearson’s Product Moment Correlation supported the first hypothesis,
which stated that negative life events would be significantly positively associated with
depressive symptoms (r = .39, p<.001) (see Table 2). In support of the second hypothesis, which
predicted a significant negative relationship between positive psychological characteristics and
depressive symptoms, trait hope (r = -.52, p<.001) as well as optimism (r = -.55, p<.001) were
significantly associated with decreased total score on the BDI-II. The third hypothesis, which
anticipated a significant negative relationship between measures of religious and spiritual
characteristics and depressive symptoms, was partially supported. Daily spiritual experiences
were significantly negatively related to depressive symptoms (r = -.16, p<.01); however, private
religious practices (r = -.09, p = .09) and organizational religiousness (r = -.08, p = .11) were not
41
Table 2
Bivariate Correlations of Study Variables, with Demographics Included
Negative
Life Events
Trait
Hope
Optimism
Spiritual
Experiences
Religious
Practices
Organizational
Religiousness
Positive
Coping
Negative
Coping
Gender
Age
.39***
-.52***
-.55***
-.16**
-.09
-.08
-.10
.35***
.28***
-.04
Negative Life
Events
-
-.23***
-.31***
-.12*
-.04
.02
-.08
.21***
-.01
-.17**
Trait Hope
-
-
.57***
.21***
.12*
.03
.15**
-.20**
-.14**
.13*
.05
Optimism
-
-
-
.23***
.15**
.05
.15**
-.30***
-.10*
-.15**
-.10
Spiritual
Experiences
-
-
-
-
.66***
.48***
.77***
-.16**
.05
.07
Religious
Practices
-
-
-
-
-
.64***
.65***
-.08
.04
.16**
Organizational
Religiousness
-
-
-
-
-
-
.50***
.02
-.07
.04
Positive Coping
-
-
-
-
-
-
-
-.04
.07
.08
.03
Negative Coping
-
-
-
-
-
-
-
-
.07
-.13*
.08
Gender
-
-
-
-
-
-
-
-
-
-.09
-.02
Age
-
-
-
-
-
-
-
-
-
-
.32***
Depressive
Symptoms
Year in
School
.04
.00
.07
.13*
.05
Note: *p<.05, **p<.01, ***p<.001.
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Trait Hope = Trait Hope Scale total score; Optimism = Life Orientation
Test-Revised total score; Religion and spirituality variables = subscales of Fetzer Brief Multidimensional Measure of Religiousness / Spirituality.
42
significantly associated with depressive symptoms. Lastly, the fourth hypothesis predicting
contrasting relationships between two aspects of religious coping and depressive symptoms was
partially supported; negative religious coping (r = .35, p<.001) was positively associated with
depressive symptoms, but the relationship between positive religious coping and depressive
symptoms did not reach significance although it did show a clinically meaningful trend (r = -.10,
p = .057).
Moderation Analyses of Study Variables and Depressive Symptoms
Trait Hope as a Moderator
For the total sample, trait hope (standardized β = -.42, p<.001) was associated with
decreased depressive symptoms, and negative life events (β = .30, p<.001) predicted increased
depressive symptoms (see Table 3). The addition of the interaction term in Step 2 significantly
improved the predictability of the model, F (1, 371) = 4.69, p = .031, thereby supporting hope as
a moderator. The negative valence of the interaction term (β = -.09) suggests that the relationship
between negative life events and depressive symptoms is weakened as levels of trait hope
increase. In simple slopes testing, both high trait hope (t = 3.37, p<.001) and low trait hope (t =
6.69, p<.001) were significantly different from zero, suggesting that negative life events are
positively related to depressive symptoms regardless of the level of trait hope (see Figure 1).
Negative life events were positively related to depressive symptoms for each ethnic
group. Hope was associated with fewer depressive symptoms in Blacks, Hispanics, and Whites
but not Asians. Although hope significantly moderated life events and depressive symptoms for
the entire sample, it did not reach significance as a moderator in any of the individual ethnic
groups (see Table 3).
43
Table 3
Negative Life Events, Hope, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .395
ΔR2 = .008
R2 = .440
ΔR2 = .013
R2 = .389
ΔR2 = .001
R2 = .460
ΔR2 = .021
R2 = .454
ΔR2 = .051
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
2.23*
5.41[2.38]
.19
.75 [4.02]
2.00*
7.31 [3.66]
.99
7.72 [7.84]
.39
7.78 [19.98]
Gender
5.44‡
4.25 [.78]
2.56*
3.70 [1.45]
3.06+
4.41 [1.44]
2.41*
3.25 [1.35]
1.71
7.93 [4.64]
Age
1.99*
.23 [.12]
2.17*
.41 [.19]
1.01
.17 [.16]
.24
.10 [.41]
.08
.07 [.95]
-10.04‡
-.98 [.10]
-5.03‡
-1.00 [.20]
-6.63‡
-1.08 [.16]
-5.01‡
-.99 [.19]
-1.43
-.73 [.51]
7.22‡
.73 [.10]
3.88‡
.80 [.21]
3.96‡
.71 [.18]
2.80+
.56 [.20]
2.54*
1.03 [.41]
Constant
2.44*
5.80 [2.38]
.39
1.58 [4.04]
2.02*
7.41 [3.67]
.69
5.43 [7.88]
.70
14.15 [20.32]
Gender
5.48‡
4.25 [.78]
2.37*
3.44 [1.45]
3.08+
4.46 [1.45]
2.52*
3.36 [1.33]
1.36
6.44 [4.72]
Age
1.73
.20 [.12]
1.90
.37 [.19]
.94
.16 [.17]
.48
.20 [.41]
-.21
-.20 [.96]
-10.04‡
-.98 [.10]
-5.22‡
-1.04 [.20]
-6.57‡
-1.08 [.16]
-5.00‡
-.96 [.19]
-1.28
-.65 [.51]
Negative Life Events
7.12‡
.71 [.10]
3.44+
.72 [.21]
3.97‡
.71 [.18]
2.36*
.48 [.214]
2.84*
1.20 [.42]
Trait Hope X
Negative Life Events
-2.17*
-.06 [.03]
-1.44
-.07 [.05]
-.40
-.02 [.05]
-1.60
-.07 [.05]
-1.24
-.12 [.10]
Step One
Trait Hope
Negative Life Events
Step Two
Trait Hope
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Trait Hope = Trait Hope Scale total score; Depressive Symptoms = Beck
Depression Inventory-II total score.
44
Figure 1. Regression of Depressive Symptoms on Negative Life Events for High Trait Hope (1
SD above) and Low Trait Hope (1 SD below) for the Total Sample (N = 386).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Hope = Trait Hope Scale total
score; Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative Life Events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
Optimism as a Moderator
For the total sample, optimism (β = -.46, p<.001) and negative life events (β = .26,
p<.001) were significantly related to decreased and increased depressive symptoms, respectively
(see Table 4). The inclusion of the interaction term in Step 2 did not statistically support
optimism as a moderator although it did show a clinically significant trend F (1, 371) = 3.77, p =
.053.
Separate moderator analyses were conducted for each ethnic group. Negative life events
significantly predicted increased depressive symptoms for each ethnic group, and optimism
predicted decreased depressive symptoms in Blacks, Hispanics, and Whites but not Asians.
45
Table 4
Negative Life Events, Optimism, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .414
ΔR2 = .006
R2 = .485
ΔR2 = .014
R2 = .374
ΔR2 = .000
R2 = .552
ΔR2 = .027
R2 = .406
ΔR2 = .033
T-Value
Un.β [SE]
TValue
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
1.975*
4.64 [2.35]
.27
1.06 [3.86]
1.25*
4.65 [3.72]
1.59
11.36 [7.15]
-.022
-.47 [20.95]
Gender
5.93‡
4.53 [.76]
2.79+
3.86 [1.38]
3.96‡
5.66 [1.43]
2.44*
2.98 [1.22]
2.02
9.42 [4.66]
Age
2.28*
.26 [.11]
2.14*
.39 [.20]
1.45
.25 [.17]
-.23
-.08 [.38]
.44
.45 [1.02]
Optimism
10.80‡
.77 [.07]
5.94‡
.80 [.14]
6.27‡
.75 [.12]
6.69‡
.83 [.12]
.77
.51 [.66]
Negative Life Events
6.24‡
.63 [.10]
3.96‡
.77 [.20]
3.84‡
.70 [.18]
2.45*
.45 [.19]
1.76
.83 [.47]
Constant
2.14*
5.03 [2.35]
..45
1.74 [3.85]
1.28
4.87 [3.80]
1.43
10.03 [7.01]
-.44
-10.33 [23.47]
Gender
5.88‡
4.48 [.76]
2.86+
3.93 [1.37]
3.89‡
5.61 [1.44]
2.34*
2.81 [1.20]
2.02
9.45 [4.68]
Age
2.00*
.23 [.11]
1.82
.34 [.19]
1.38
.24 [.17]
-.09
-.03 [.37]
.79
.88 [.18]
Optimism
10.67‡
.76 [.07]
6.11‡
.82 [.13]
6.08‡
.74 [.12]
6.30‡
.78 [.12]
1.21
1.09 [.90]
Negative Life Events
6.03‡
.61 [.10]
3.25+
.67 [.20]
3.84‡
.70 [.18]
2.10*
.39 [.18]
.78
.47 [.61]
1.94
.04 [.02]
1.60
.07 [.04]
.296
.01 [.04]
2.03*
.06 [.03]
.94
.16 [.17]
Step One
Step Two
Optimism X
Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Optimism = Life Orientation Test- Revised total score; Depressive
Symptoms = Beck Depression Inventory-II total score.
46
In Whites only optimism significantly moderated the relationship between negative life
events and depressive symptoms, F (1, 68) = 4.12, p = .047 (see Table 4). In simple slopes
testing, the regression line for low levels of optimism was significantly different from zero (t =
2.80, p = .007), but there was not a significant slope for those with high levels of optimism (t =
0.28, p = .78) (see Figure 2). The relationship between negative life events and depressive
symptoms was significant for Whites with low optimism, but nonsignificant for those with high
levels of optimism.
Daily Spiritual Experiences as a Moderator
In the entire sample daily spiritual experiences (β = -.13, p = .007) was associated with
decreased depressive symptoms and negative life events (β = .39, p<.001) was related to
increased depressive symptoms. The inclusion of the interaction term in Step 2 did not support
daily spiritual experiences as a moderator, F (1, 371) = 0.61, p = .43 (see Table 5).
Negative life events significantly predicted increased depressive symptoms for each
ethnic group. Daily Spiritual Experiences were a significant predictor of decreased depressive
symptoms in Whites only. Similarly, daily spiritual experiences moderated negative life events
and depressive symptoms in only Whites, F (1, 68) = 6.87, p = .011 (see Table 5). The
relationship between negative life events and depressive symptoms was significantly weaker at
higher rather than lower levels of daily spiritual experiences. The simple slopes regression lines
reveal that at low (t = 4.04, p<.001) but not high (t = 0.74, p = .46) levels of daily spiritual
experiences, negative life events predict increased depressive symptoms (see Figure 3).
Private Religious Practices as a Moderator
For the entire sample private religious practices (β = -.09, p = .049) were related to
decreased depressive symptoms, and negative life events (β = .39, p<.001) were associated with
47
Figure 2. Regression of Depressive Symptoms on Negative Life Events for High Optimism (1
SD above) and Low Optimism (1 SD below) for Whites (N =71).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Optimism = Life Orientation
Test-Revised total score; Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative Life Events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
48
Table 5
Negative Life Events, Daily Spiritual Experiences, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .246
ΔR2 = .001
R2 = .295
ΔR2 = .006
R2 = .214
ΔR2 = .006
R2 = .304
ΔR2 = .067
R2 = .417
ΔR2 = .002
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
2.16*
5.77 [2.67]
.20
.91 [4.52]
1.69
6.99 [4.15]
.34
3.16 [9.16]
.02
.48 [20.48]
Gender
6.36‡
5.49 [.86]
2.97+
4.77 [1.61]
4.07‡
6.50 [1.60]
1.83
2.79 [1.53]
2.40*
11.07 [4.62]
Age
1.29
.17 [.13]
1.72
.37 [.21]
.54
.10 [.19]
.73
.35 [.48]
.36
.35 [.98]
Spiritual Experiences
-2.74+
-.14 [.05]
-1.14
-.12 [.10]
-.57
-.05 [.09]
-2.36*
-.22 [.09]
-.95
-.27 [.28]
Negative Life Events
8.37‡
.92 [.11]
5.13‡
1.12 [.22]
4.94‡
.98 [.20]
4.06‡
.87 [.22]
2.12*
.91 [.43]
Constant
2.15*
5.73 [2.67]
.19
.87 [4.52]
1.70
7.04 [4.15]
.53
4.68 [8.79]
.01
.25 [21.13]
Gender
6.37‡
5.50 [.86]
3.00+
4.83 [1.61]
4.17‡
6.71 [1.61]
2.17*
3.18 [1.47]
2.34*
11.26 [4.82]
Age
1.29
.17 [.13]
1.70
.36 [.21]
.50
.09 [.19]
.53
.25 [.46]
.35
.35 [1.01]
Spiritual Experiences
-2.75+
-.14 [.05]
-1.23
-.13 [.10]
-.44
-.04 [.09]
-2.53*
-.23 [.09]
-.92
-.27 [.29]
Negative Life Events
8.25‡
.91 [.11]
4.94‡
1.09 [.22]
5.05‡
1.02 [.20]
3.92‡
.81 [.21]
2.07
.93 [.45]
-.78
-.01 [.01]
-.89
-.03 [.03]
1.05
.03 [.03]
-2.62*
-.07 [.03]
-.25
-.01 [.05]
Step One
Step Two
Spiritual Experiences X
Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Spiritual Experiences = Daily Spiritual Experiences total score (Fetzer);
Depressive Symptoms = Beck Depression Inventory-II total score.
49
Figure 3. Regression of Depressive Symptoms on Negative Life Events for high Daily Spiritual
Experiences (1 SD above) and low Daily Spiritual Experiences (1 SD below) for Whites (N =
71).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Daily Spiritual Experiences =
Daily Spiritual Experiences total score (Fetzer); Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative life events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
increased symptoms of depression. Including the interaction term in Step 2 did not support
private religious practices as a moderator, F (1, 371) = 2.47, p = .12 (see Table 6).
In ethnically stratified analyses, negative life events significantly predicted increased
depressive symptoms, and private religious practices significantly predicted decreased depressive
symptoms in both Whites and Asians. The interaction term, however, was significant in only
Blacks, F (1, 94) = 4.45, p = .038 and Whites, F (1, 68) = 8.65, p<.005 (see Table 6). In both
cases as levels of private religious practices increased, the relationship between negative life
events and depressive symptoms weakened. In simple slopes regression analyses for Blacks there
was a significant effect of negative life events on depressive symptoms at low (t = 5.64, p<.001)
but not high (t = 1.85, p = .068) levels of private religious practices (see Figure 4). Similarly, in
50
Table 6
Negative Life Events, Private Religious Practices, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .239
ΔR2 = .005
R2 = .288
ΔR2 = .034
R2 = .213
ΔR2 = .005
R2 = .302
ΔR2 = .083
R2 = .534
ΔR2 = .002
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
1.99*
5.38 [2.71]
.13
.61 [4.57]
1.64
6.88 [4.22]
-.02
-.24 [9.64]
-.15
-2.77 [18.34]
Gender
6.30‡
5.47 [.87]
2.91+
4.71 [1.62]
4.11‡
6.56 [1.60]
1.81
2.76 [1.53]
2.87*
11.77 [4.10]
Age
1.43
.19 [.13]
1.77
.39 [.22]
.55
.10 [.19]
1.05
.53 [.51]
.57
.50 [.88]
Religious Practices
-1.97*
-.12 [.06]
-.69
-.08 [.11]
-.17
-.02 [.12]
-2.32*
-.30 [.13]
-2.27*
-.52 [.23]
Negative Life Events
8.68‡
.95 [.11]
5.26‡
1.14 [.22]
5.05‡
.99 [.20]
4.40‡
.94 [21]
2.85*
1.07 [.38]
Constant
2.05*
5.56 [2.71]
.07
.33 [4.49]
1.59
6.69 [4.20]
.36
3.30 [9.20]
-.11
-2.16 [19.10]
Gender
6.28‡
5.44 [.87]
3.12+
4.98 [1.59]
4.20‡
6.74 [1.61]
1.98
2.86 [1.45]
2.70*
11.60 [4.30]
Age
1.36
.18 [.13]
1.81
.39 [.21]
.58
.11 [.19]
.70
.34 [.48]
.52
.47 [.91]
Religious Practices
-1.99*
-.12 [.06]
-1.04
-.12 [.11]
-.02
.00 [.12]
-2.25*
-.28 [.12]
-2.04
.51 [.25]
Negative Life Events
8.58‡
.94 [.11]
4.82‡
1.05 [.22]
5.14‡
1.03 [.20]
4.89‡
.99 [.20]
2.77*
1.08 [.39]
-1.57
-.03 [.02]
-.211*
-.07 [.03]
1.00
.04 [.04]
-2.94+
-.10 [.03]
-.23
-.01 [.05]
Step One
Step Two
Religious Practices X
Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Religious Practices = Private Religious Practices total score (Fetzer);
Depressive Symptoms = Beck Depression Inventory-II total score.
51
Figure 4. Regression of Depressive Symptoms on Negative Life Events for high Private
Religious Practices (1 SD above) and low Private Religious Practices (1 SD below) for Blacks
(N = 98).
Note: Depressive symptoms = Beck Depression Inventory-II total score; Optimism = Life Orientation
Test-Revised total score; Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative Life Events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
Whites negative life events significantly predicted increased depressive symptoms at low (t =
5.59, p<.001) but not high (t = 1.35, p>.05) levels of private religious practices (see Figure 5).
Organizational Religiousness as a Moderator
Organizational religiousness (β = -.07, p = .14) did not significantly predict depressive
symptoms beyond the effects of covariates for the entire sample (see Table 7). As in other
analyses, negative life events (β = .40, p<.001) were significantly associated with increased
depressive symptoms. The interaction term in Step 2 did not support organizational religiousness
as a moderator, F (1, 371) = 1.83, p = .18.
In ethnically stratified analyses, negative life events significantly predicted increased
depressive symptoms for each ethnic group. Organizational religiousness significantly predicted
52
Figure 5. Regression of Depressive Symptoms on Negative Life Events for high Private
Religious Practices (1 SD above) and low Private Religious Practices (1 SD below) for Whites
(N = 70).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Private Religious
Practices = Private Religious Practices total score (Fetzer); Negative Life Events = Life Events
Scale total score.
Note: Low Negative Life Events = Negative life events 1 SD below mean; High Negative Life
Events = Negative Life Events 1 SD above mean.
53
Table 7
Negative Life Events, Organizational Religiousness, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .236
ΔR2 = .004
R2 = .287
ΔR2 = .031
R2 = .212
ΔR2 = .001
R2 = .320
ΔR2 = .093
R2 = .435
ΔR2 = .010
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
2.60*
6.15 [2.68]
.25
1.13 [4.55]
1.68
6.98 [4.15]
.69
6.07 [8.83]
-.22
-4.62 [20.95]
Gender
6.08‡
5.29 [.87]
2.90+
4.71 [1.62]
4.07‡
6.57 [1.62]
1.54
2.33 [1.51]
2.55*
11.97 [4.70]
Age
1.19
.15 [.13]
1.67
.36 [.22]
.52
.10 [.19]
.46
.21 [.46]
.59
.59 [1.00]
Organizational Religiousness
-1.48
-.24 [.16]
-.49
-.14 [.29]
.06
.02 [.30]
-2.70+
-.84 [.31]
-1.20
-1.17 [.98]
Negative Life Events
8.72‡
.96 [.11]
5.28‡
1.15 [.22]
5.07‡
.99 [.20]
4.36‡
.92 [.21]
2.68*
1.19 [.45]
Constant
2.31*
6.19 [2.68]
.17
.75 [4.47]
1.62
6.76 [4.19]
.88
7.31 [8.28]
-.42
-10.09 [23.82]
Gender
6.00‡
5.23 [.87]
2.83+
4.53 [1.60]
4.05‡
6.74 [1.67]
1.70
2.40 [1.41]
2.54*
12.40 [4.88]
Age
1.20
.15 [.13]
1.83
.39 [.21]
.55
.10 [.19]
.32
.14 [.43]
.74
.82 [1.12]
Organizational Religiousness
-1.47
-.24 [.16]
-.96
-.28 [.29]
.09
.03 [.30]
-2.40*
-.71 [.29]
-1.10
-1.93 [1.76]
Negative Life Events
8.65‡
-95 [.11]
5.00‡
1.08 [.22]
5.08‡
1.00 [.20]
4.97‡
.99 [.20]
2.55*
1.32 [.52]
-1.35
-.06 [.05]
-.202*
-.20 [.10]
.46
.04 [.09]
-3.19+
-.28 [.09]
.53
.15 [.29]
Step One
Step Two
Organizational Religiousness
X Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Organizational Religiousness = Organizational Religiousness total score
(Fetzer); Depressive Symptoms = Beck Depression Inventory-II total score.
54
decreased depressive symptoms in Whites only. The interaction term, although, was significant
in Blacks, F (1, 94) = 4.07, p = .047 and Whites, F (1, 68) = 10.18, p = .002. Both terms
indicated that increasing levels of organizational religiousness were associated with a weakened
relationship between negative life events and depressive symptoms. For Blacks a significant
relationship between life events and depressive symptoms was found at low levels of
organizational religiousness (t = 5.10, p<.001); however, the slope (see Figure 6) was
nonsignificant for individuals scoring high in organizational religiousness (t = 1.61, p = .11). The
same pattern was found in Whites at low (t = 5.36, p<.001) and high (t = 1.11, p = .27)
organizational religiousness (see Figure 7).
Positive Religious Coping as a Moderator
Positive religious coping (β = -.09, p = .06) did not contribute unique variance to BDI-II
scores, but negative life events (β = .39, p<.001) were positively associated with depressive
symptoms for the entire sample. The inclusion of the interaction term in Step 2 did not
significantly account for additional variance, F (1, 371) = 1.67, p = .20 (see Table 8), indicating
that positive religious coping does not moderate negative life events and depressive symptoms.
Negative life events significantly predicted depressive symptoms for each ethnic group.
Positive religious coping was not significantly associated with depressive symptoms in any of
the ethnic groups. The interaction of positive religious coping and negative life events
contributed significant unique variance to BDI-II scores among Whites, F (1, 68) = 4.53, p =
.037. In this case increasing levels of positive religious coping weakened the relationship
between negative life events and depressive symptoms. Simple slopes regression lines (see
Figure 8) show that negative life events significantly predicted increased depressive symptoms at
low (t = 4.17, p<.001) but not high (t = 1.26, p = .21) levels of positive religious coping.
55
Figure 6. Regression of Depressive Symptoms on Negative Life Events for High Organizational
Religiousness (1 SD above) and Low Organizational Religiousness (1 SD below) for Blacks (N
= 98).
Note: Depressive symptoms = Beck Depression Inventory-II total score; Organizational Religiousness =
Organizational Religiousness total score (Fetzer); Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative life events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
56
Figure 7. Regression of Depressive Symptoms on Negative Life Events for high Organizational
Religiousness (1 SD above) and low Organizational Religiousness (1 SD below) for Whites (N =
70).
Note: Depressive symptoms = Beck Depression Inventory-II total score; Organizational Religiousness =
Organizational Religiousness total score (Fetzer); Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative life events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
57
Table 8
Negative Life Events, Positive Religious Coping, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .238
ΔR2 = .003
R2 = .295
ΔR2 = .023
R2 = .212
ΔR2 = .002
R2 = .279
ΔR2 = .048
R2 = .408
ΔR2 = .002
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
Constant
2.18*
5.85 [2.68]
.28
1.28 [4.52]
1.67
6.97 [4.17]
.63
5.78 [9.17]
.00
-.06 [20.78]
Gender
6.32‡
5.49 [.87]
2.94+
4.73 [1.91]
4.11‡
6.55 [1.60]
1.82
2.83 [1.56]
2.38*
11.56 [4.87]
Age
1.25
.16 [.13]
1.64
.35 [.21]
.52
.10 [.19]
.44
.21 [.48]
.37
.37 [.99]
Positive Religious Coping
-1.88
-.23 [.12]
-1.16
-.28 [.24]
-.03
-.01 [.22]
-1.78
-.43 [.24]
-.81
-.57 [.71]
Negative Life Events
8.54‡
.94 [.11]
5.16‡
1.12 [.22]
5.03‡
.99 [.20]
4.30‡
.93 [.22]
2.20*
.94 [.43]
Constant
2.14*
5.74 [2.68]
.17
.75 [4.48]
1.68
7.01 [4.18]
.80
7.15 [8.95]
-.02
-.40 [21.47]
Gender
6.31‡
5.48 [.87]
2.90+
4.62 [1.59]
4.14‡
6.67 [1.61]
1.91
2.90 [1.52]
2.32*
11.69 [5.04]
Age
1.28
.17 [.13]
1.77
.38 [.21]
.51
.10 [.19]
.29
.14 [.47]
.37
.38 [1.02]
Positive Religious Coping
-2.01*
-.25 [.13]
-1.57
-.38 [.24]
.13
.03 [.23]
-1.61
-.38 [.24]
-.79
-.58 [.73]
Negative Life Events
8.32‡
.92 [.11]
5.08‡
1.10 [.22]
5.02‡
1.03 [.20]
4.13‡
.88 [.21]
2.14*
.94 [.44]
-1.29
-.04 [.03]
-1.76
-.12 [.07]
.63
.04 [.07]
-2.13*
-.16 [.07]
-.25
-.03 [.13]
Step One
Step Two
Positive Religious Coping
X Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Positive Religious Coping = Positive Religious Coping total score (Fetzer);
Depressive Symptoms = Beck Depression Inventory-II total score.
58
Figure 8. Regression of Depressive Symptoms on Negative Life Events for high Positive
Religious Coping (1 SD above) and low Positive Religious Coping (1 SD below) for Whites (N
= 71).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Positive Religious Coping =
Positive Religious Coping total score (Fetzer); Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative Life Events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
Negative Religious Coping as a Moderator
For the entire sample negative religious coping (β = .27, p<.001) and negative life events
(β = .35, p<.001) were both associated with increased depressive symptoms. The inclusion of the
interaction term in Step 2 did not support negative religious coping as a moderator, F (1, 371) =
0.85, p = .36 (see Table 9).
Negative life events were positively associated with depressive symptoms in each ethnic
group except for Asians. Negative religious coping was a significant predictor of depressive
symptoms in Blacks and Hispanics. In Asians only negative religious coping significantly
moderated the relationship between life events and depressive symptoms, F (1, 19) = 6.02, p .027. The positive valence of the interaction term (β = .41) indicates that higher levels of
59
Table 9
Negative Life Events, Negative Religious Coping, and Depressive Symptoms—Multivariate Linear Regression
Step 1 R2
Step 2 ΔR2
Total Sample
Blacks
Hispanics
Whites
Asians
R2 = .302
ΔR2 = .002
R2 = .393
ΔR2 = .003
R2 = .292
ΔR2 = .014
R2 = .248
ΔR2 = .000
R2 = .434
ΔR2 = .162
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
T-Value
Un.β [SE]
1.97*
5.06
[2.57]
-.28
-1.18 [4.22]
1.44
5.68 [3.65]
.91
8.38 [9.25]
.43
8.97 [20.68]
Gender
6.05‡
5.03 [.83]
3.50+
5.25 [1.50]
3.66‡
5.59 [1.53]
1.70
2.71 [1.59]
1.75
8.28 [4.73]
Age
1.77
.22 [.12]
2.28*
.46 [.20]
1.12
.20 [.18]
.16
.08 [.49]
.00
.00 [.99]
Negative Religious Coping
6.14‡
1.06 [.17]
4.03‡
1.23 [.31]
4.13‡
1.17 [.28]
.61
.27 [.44]
1.19
.95 [.80]
Negative Life Events
7.77‡
.83 [.11]
4.28‡
.90 [.21]
4.92‡
.92 [.19]
4.00‡
.90 [.23]
2.10
.89 [.42]
2.04*
5.26
[2.58]
-.31
-1.31 [4.24]
1.61
6.36 [3.94]
.90
8.41 [9.34]
.60
10.77 [18.06]
Gender
6.02‡
5.01 [.83]
3.52+
5.29 [1.50]
3.73‡
5.67 [1.52]
1.69
2.71 [1.60]
1.72
7.11 [4.15]
Age
1.65
.21 [.12]
2.32*
.47 [.20]
.87
.16 [.18]
.16
.08 [.49]
-.10
-.09 [.86]
Negative Religious Coping
6.04‡
1.04 [.17]
4.06‡
1.25 [.31]
4.34‡
1.23 [.28]
.55
.26 [.48]
1.09
.76 [.70]
Negative Life Events
7.64‡
.82 [.11]
4.25‡
.95 [.22]
5.10‡
.95 [.19]
3.91‡
.90 [.23]
2.65*
.98 [.37]
.92
.04 [.04]
-.68
-.05 [.07]
1.73
.15 [.09]
.05
.01 [.12]
2.45*
.28 [.11]
Step One
Constant
Step Two
Constant
Negative Religious Coping
X Negative Life Events
* p<.05, +p<.01, ‡p<.001.
Note: Negative Life Events = Life Events Scale total score; Negative Religious Coping = Negative Religious Coping total score
(Fetzer); Depressive Symptoms = Beck Depression Inventory-II total score.
60
negative religious coping amplified the relationship between negative life events and depressive
symptoms. Simple slopes testing (see Figure 9) demonstrated that the relationship between
negative life events and depressive symptoms is significantly different from zero for individuals
scoring high (t = 3.72, p<.001) but not low (t = -0.23, p = .82) in negative religious coping.
61
Figure 9. Regression of Depressive Symptoms on Negative Life Events for high Negative
Religious Coping (1 SD above) and low Negative Religious Coping (1 SD below) for Asians (N
= 21).
Note: Depressive Symptoms = Beck Depression Inventory-II total score; Negative Religious Coping =
Negative Religious Coping total score (Fetzer); Negative Life Events = Life Events Scale total score.
Note: Low Negative Life Events = Negative Life events 1 SD below mean; High Negative Life Events =
Negative Life Events 1 SD above mean.
62
CHAPTER 4
DISCUSSION
The current study investigated the relationship between negative and potentially
traumatic life events and depressive symptoms in an ethnically diverse sample. The potential
moderating role of positive psychological characteristics including trait hope and optimism and
spiritual or religious characteristics including daily spiritual experiences, private religious
practices, organizational religiousness, positive religious coping, and negative religious coping
was also examined including differences in main and moderating effects among ethnic groups.
Current results support previous research indicating a significant negative relationship
between depressive symptoms and trait hope (Arnau, Rosen, Finch, Rhudy, & Fortunato, 2007;
Chang & DeSimone; 2001; Kwon, 2000; Snyder et al., 1991), and between depressive symptoms
and dispositional optimism (Andersson, 1996; Hirsch, Wolford, et al., 2007; Scheier et al.,
1994). These relationships were expected and contribute support to the growing body of
literature positing hope and optimism as important variables in depression research. This study
also concurs with literature suggesting a negative relationship between symptoms of depression
and various aspects of religiosity (Koenig & Larson, 2001). The current study, however, extends
previous research by examining the moderator status of positive psychological and religious and
spiritual variables across ethnicities.
Hypotheses
Hypothesis 1: Negative Life Events and Depressive Symptoms
As hypothesized, negative and potentially traumatic life events experienced by college
students were significantly associated with depressive symptoms in the entire sample. This
finding is consistent with decades of research on the deleterious effects of experiencing stressful
63
and potentially traumatic life events (Kendler et al., 1999; Kessler, 1997; Tennant, 2002). The
moderate association between the life events scale and the BDI-II is consonant with correlation
coefficients found in studies with similar samples and instruments (Dixon & Reid, 2000; Gencoz
& Dinc, 2006; Konick & Gutierrez, 2005). Yet, much of the variance in depressive symptoms is
left unexplained, which may indicate that more detailed analysis of life stress is needed to
accurately assess the relationship between negative life events and depressive symptoms
(Kessler, 1997), or that factors other than life stress account for the majority of variance in
symptoms of depression. These other factors may include biological variables such as endocrine
and neurotransmitter levels, dysregulation in brain functioning, genetic structure, and cognitive
impairment (Bloch, Daly, & Rubinow, 2003; Fava & Kendler, 2000; Kato, 2007; Vink et al.,
2008); environmental circumstances such as familial structure, SES, social networks, and living
conditions (Hammen, Rudolph, Weisz, & Burge, 1999; Vink et al., 2008); or psychological and
behavioral characteristics such as neuroticism, self-image, comorbid psychopathology, health
habits, coping styles, mastery, locus of control, self-efficacy, and those included in the present
study (McCullough & Larson, 1999; Reff et al., 2005; Scheier et al., 1994; Vink et al., 2008).
Hypothesis 2: Trait Hope, Dispositional Optimism, and Depressive Symptoms
As expected, trait hope and dispositional optimism were significantly negatively
correlated with depressive symptoms in the entire sample. This corroborates previous research
indicating a salutary effect of positive psychological characteristics such as hope and optimism
on depressive symptoms (Andersson, 1996; Arnau et al., 2007; Chang, 1997; Chang &
DeSimone, 2001; Chang & Sanna, 2003; Hirsch, Conner, & Duberstein, 2007; Kwon, 2000;
Scheier et al., 1994; Snyder et al., 1991). The relatively strong negative relationships of
optimism and hope with depressive symptoms in the current study support the potential value of
64
these constructs in treatment and intervention efforts by suggesting that moderate increases in
hope and optimism levels may be associated with decreases in depressive symptoms.
In a review of the literature, Schueller and Seligman (2008) concluded that optimism
appears to prevent and mitigate depression perhaps via promotion of positive emotions and a
sense of life meaning. Similarly, Needles and Abramson (1990) concluded that optimism may
play a critical role in recovery from depression. Interventions for bolstering optimism have been
recently designed and tested in group and individual settings with empirical studies
demonstrating efficacy using modified cognitive-behavioral strategies (Seligman, Schulman, &
Tryon, 2007; Seligman & Csikszentmihalyi, 2000; Seligman, Schulman, DeRubeis, & Hollon,
1999) and techniques such as visualizing one’s best future and regularly counting and thinking
about one’s blessings (Joseph & Linley, 2005; Seligman et al., 2005; Sheldon & Lyubomirsky,
2006).
Clinical efforts for strengthening hope have also been made. Snyder (1995) delineated
several steps for enhancing hope in clients including identifying goals, imagining success,
identifying potential pathways to achieving goals, and positively interpreting failures; Snyder et
al. (2002) expanded these recommendations to include formulation of and mentally acting out
ways to address barriers to goal attainment. Empirical support exists for interventions that
increase hope via the use of positive self-statements, identifying and enhancing personal
strengths, psychoeducation regarding effective goal-setting, and discussing personal narratives of
successful hope (Pedrotti, Edwards, & Lopez, 2008; Ripley & Worthington, 2002; ; Snyder,
Lehman, Kluck, & Monsson, 2006). Hope interventions have resulted in higher confidence in
one’s ability to achieve goals and increased capacity for identifying environmental resources for
goal accomplishment (Snyder et al., 2006). In addition to specialized interventions to promote
65
hope and optimism, clinicians are increasingly augmenting traditional treatments focused on
symptom reduction with strategies aimed at preventing relapse and improving quality of life, via
hope and optimism enhancement (Schueller & Seligman, 2008). Little is known, however, about
the effectiveness of hope and optimism interventions in different ethnic groups (Chang & Banks,
2007); research in this area is needed.
Hypothesis 3: Daily Spiritual Experiences, Private Religious Practices, Organizational
Religiousness, and Depressive Symptoms
As hypothesized, reporting higher levels of daily spiritual experiences represented by
items such as feeling God’s presence, being touched by the beauty of creation, and feeling deep
inner peace and harmony was associated with lower levels of depressive symptoms in this
ethnically diverse sample. The small correlation found in the present study concurs with other
research on daily spiritual experiences that indicates a weak negative relationship between
spiritual experiences and depressive symptoms (George et al., 2000; Mofidi et al., 2006, 2007;
Rippentrop et al., 2007). Spiritual experiences may indirectly influence depressive symptoms via
a stronger a sense of direction and purpose in life, increased confidence that God will intervene
on one’s behalf in times of difficulty, and reductions in feelings of loneliness (Mofidi et al.,
2007).
Contrary to the hypothesis, neither private religious practices nor organizational
religiousness were significantly negatively associated with depressive symptoms in the entire
sample. The literature on private religious practices reveals that its relationship with depressive
symptoms is tenuous at best (McCullough & Larson, 1999). Although some researchers have
found that private religious practices such as prayer and viewing religious programs are
predictive of better mental health (Musick, Koenig, Hays, & Cohen, 1998), other research has
66
found that private practices such as praying are unrelated or positively related to depressive
symptoms (McCullough & Larson, 1999). Salutary effects of private religious practices on
mental health may involve increased use of adaptive or less threatening cognitive appraisal as
individuals deal with life stress in the context of their religious beliefs (Musick et al., 1998).
Positive relationships between private religious practices and depressive symptoms may be due
to a bidirectional relationship in which those with increased physical and psychological distress
engage in more private religious practices as coping tools (McCullough & Larson, 1999;
Pargament et al., 1998). Longitudinal research is needed to determine if private religious
practices exert a causal influence on depressive symptoms over time.
The lack of a significant negative relationship between organizational religiousness and
depressive symptoms is surprising as there is a substantial literature support indicating a negative
association with depression (McCullough & Larson, 1999). It should be noted, however, that the
correlation coefficient between organizational religiousness and depressive symptoms in the
present study corresponds to reported ranges from other studies that reached significance using
larger sample sizes (Smith et al., 2003), suggesting that the present results support rather than
contradict a weak negative relationship between organizational religiousness and depressive
symptoms. Organizational religiousness may benefit psychological health by promoting a
decrease in risky behaviors such as substance abuse that can cause significant distress (Swendsen
et al., 1998) and by increasing social support that can provide a sense of cohesion and
belongingness (Moreiera-Almeida et al., 2006). Clinicians working with religious clients may
identify ways to use the beneficial aspects of their clients’ participation in a religious
organization to accomplish treatment goals (McCullough, 1999) such as increased social activity.
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The association of organizational religiousness and depressive symptoms in the present
study is not statistically significant; cultural background may be an important moderator of this
relationship (Ellison, 1995). In a diverse sample as in the present study it is possible that,
because of ethnic influences on the meaning of religiosity, the strength of the association
between organizational religiousness and depressive symptoms is not reflective of the
association that would be found in individual ethnic groups. Indeed, the present study supported
such differences across ethnicity, and these results are discussed shortly.
Hypothesis 4: Religious Coping and Depressive Symptoms
Contrary to the hypothesis, positive religious coping was not significantly associated with
fewer depressive symptoms in the entire sample, but there was a clinically meaningful trend (p =
.057). Additionally, the strength of the relationship found in the current study corresponds with
other research on positive religious coping and depressive symptoms (see Smith et al., 2003),
indicating a weak negative association with depressive symptoms. Focusing on God and
potential meaning after experiencing life stress may decrease a negative attentional bias that can
lead to or exacerbate depressive symptoms (Macleod, Mathews, & Tata, 1986). Considering how
one’s stress fits into a larger spiritual framework may increase positive affect by shifting focus to
more favorable aspects of life circumstances (Pargament et al., 1998). Individuals high in
positive religious coping also tend to have more supportive social relationships, perhaps as a
result of seeking assistance from others in their faith (Ano & Vasconcelles, 2005; Toth-Cohen,
2004). In a clinical setting, reinforcing religious clients’ use of positive religious coping
strategies can be effective for enhancing a therapeutic alliance by supporting rather than ignoring
or demeaning an important aspect of clients’ lives (Worthington, Kurusu, McCullough, &
Sandage, 1996).
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Consistent with the hypothesis, negative religious coping did significantly predict
increased depressive symptoms in the entire sample. When asked how they respond to stressful
situations, participants who reported that they are likely to question whether God had abandoned
them, feel punished by God, and attempt to solve problems without God also reported greater
amounts of depressive symptoms. This positive association between negative religious coping
and depressive symptoms corroborates other research (Fitchett, Rybarczyk, DeMarco, &
Nicholas, 1999; Pargament et al., 1998). Rejecting and feeling judged or abandoned by God
because one is experiencing life stressors may increase the salience of the negative aspects of a
situation by increasing one’s fear of punishment and negating meaning that may result from a
supportive relationship with God or personal growth that may result from viewing life stress as
an opportunity rather than a threat (Ano & Vasconcelles, 2005; Maltby et al., 2003; Murphy et
al., 2000; Park et al., 1990). Although religious beliefs may be a source of meaning and comfort
for many people, they may also be a source of distress particularly when life stress is interpreted
in a threatening manner (Pargament et al., 1998). Some people may unrealistically expect that
God will not let bad things happen to them, leading to increased anger and feelings of rejection
when challenges arise (Pargament et al., 1998). Clinicians working with clients high in negative
religious coping may wish to promote a more favorable view of life stress, but they should be
cautious to not directly challenge religious beliefs, which can jeopardize a therapeutic alliance
(Worthington et al., 1998). Because of the difficulty and danger in attempting to directly change
a client’s negative religious coping style that may be contributing to clinically significant
distress, research on how to indirectly encourage a more adaptive religious response to life stress
is needed.
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Hypothesis 5: Study Variables as Moderators
Trait Hope. As expected, trait hope significantly moderated the relationship between life
stress and depressive symptoms in the entire sample. Although the interaction term was
significant, negative life events were significantly associated with increased depression at both
low and high levels of trait hope, indicating that the deleterious effects of experiencing life
stressors may still exist even if a person has high hope. Previous research has also found trait
hope to be a significant moderator of the association between depressive symptoms and stress,
but stress was defined as failure to reach particular self-made goals such as scoring below a
desired exam score (Reff et al., 2005; Snyder et al., 1991). The effects of acute and cumulative
stressors may differ (Bjorck & Thurman, 2007), but the current results indicate that hope remains
a significant moderator when stress is defined as an accumulation of life events.
Students in college may perceive excessive stress as a result of academic and vocational
requirements, preparation for graduate school or careers, financial challenges, as well as changes
in interpersonal relationships and support systems (Misra & McKean, 2000). Maintaining hope
during times of stress may increase motivation to adaptively address demands and stressors by
enhancing one’s self-confidence and ability to foresee a path to goal achievement (Snyder et al.,
1991); in turn, this may reduce some of the distress arising from the experience of negative life
events (Snyder et al., 1991) and ultimately may decrease symptoms of depression. Chang
(1998b) found that college students high in hope tend to solve problems more effectively than
those in low hope in part because they avoid maladaptive coping strategies that can exacerbate
depressive symptoms such as social withdrawal and self-criticism. The long-term effectiveness
of cognitive-behavioral therapies targeting maladaptive thoughts and behaviors may be increased
if hope is concomitantly bolstered (Snyder, 1995).
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Dispositional Optimism. Surprisingly, optimism was not a significant moderator of
negative and potentially traumatic life events and depressive symptoms in the entire sample
although there was a clinically significant trend toward significance (p = .053). Previous research
on the moderating effect of optimism on the relationship between life stress and psychological
distress has been found to be significant in past studies. Using a sample of high school students,
Chang and Sanna (2003) reported a significant interaction in which the relationship between life
hassles and depressive symptoms was significantly weaker for students high in optimism. A
similar moderating effect of optimism in the relationship between perceived stress and
depressive symptoms was found in college students, but the interaction did not achieve
significance among a convenience sample of older adults (Chang, 2002). In a college sample,
Hirsch, Wolford, et al. (2007) found that the association of negative life events and suicidal
ideation and attempts was significantly weaker for students with high optimism. The variance
explained by the interactions in each of these studies was relatively small as in the present
research. As with trait hope, this may suggest that despite high levels of optimism experiencing
negative life events is likely to lead to increased depressive symptoms. It should be noted,
however, that in the present sample a relatively strong negative correlation between optimism
and depressive symptoms exists, indicating optimism’s potential importance in clinical practice;
bolstering optimism may benefit most patients regardless of the amount of life stressors they
experience (Joseph & Linley, 2005; Seligman et al., 2005; Schueller & Seligman, 2008).
Daily Spiritual Experiences. Contrary to the hypothesis, daily spiritual experiences did
not moderate the association between negative life events and depressive symptoms in the entire
sample. Little research has looked at the role of daily spiritual experiences in psychological
health or its role as a moderator of the relationship between life stress and depressive symptoms.
71
Mofidi et al. (2006) reported evidence of a stress-buffering model in which acute stress
interacted with daily spiritual experiences to explain variance in depressive symptoms in a
sample of ethnically diverse adults from the community. The present findings, however, do not
support daily spiritual experiences as a buffer of stress and depressive symptoms. One
explanation for the different findings may stem from the assessment of stress: the present study
quantified life stress by the number of negative life events reported for the previous year,
whereas Mofidi et al. dichotomized life stress based on experience of “…significant losses or
really terrible things” during the past 2 years (pp. 976). Having daily spiritual experiences can
reinforce a person’s identity as a spiritual being and foster interpretation of life events as being a
meaningful part of a spiritual journey (Gall et al., 2005). Assigning spiritual meaning in
situations involving trauma and death may have a greater effect than attempting to integrate less
severe stressors such as those assessed in the current study whose long-term consequences are
not readily apparent into a spiritual journey.
Demographic differences between samples may also help explain differences in results:
the present research recruited undergraduates from a Northeastern university, whereas Mofidi et
al. used a sample of community-dwelling adults from a Southeastern state. Older individuals
tend to be more religious and spiritual than younger people (Markides, 1983). Additionally, the
level and function of spirituality may be contingent upon the religious climate that might vary
based on geography (Hoge & Carroll, 1973). Lastly, college students may differ from
community samples in religiosity or spirituality (White, Fleming, Kim, Catalona, & McMorris,
2008). Future research among different populations will need to be done to determine the
influence of demographic variables on a potential moderating effect of daily spiritual experiences
in the relationship between negative life events and depressive symptoms.
72
Private Religious Practices. In the current study, frequency of private religious practices
was assessed and did not significantly moderate the association between negative life events and
depressive symptoms for the whole sample. This finding is contrary to some research that
indicates that private religious practices mitigate the negative effects of life stress on depressive
symptoms perhaps by providing a sense of emotional support and enhancing self-efficacy (Gall
et al., 2005; Stolley, Buckwalter, & Koenig, 1999). Merely engaging more frequently in private
religious practices, as was assessed in the current study, may not be sufficient to mitigate the
negative effects of life stress (Baetz, Larson, Marcoux, Brown, & Griffin, 2002; Gall et al.). As
an example, prayer style (e.g., conversational, meditational, ritualistic, or petitionary) but not
prayer frequency predicted increased life satisfaction among randomly sampled community
adults (Gall et al.). Some individuals receiving psychotherapy may wish to explore during
session the use of religious and spiritual practices as potential coping mechanisms (McCullough,
1999; Worthington, Kurusu, McCullough, & Sandage, 1996). The present results suggest that
among college students only encouraging increased frequency of private religious practices
during times of distress may not be an effective technique for reducing depressive symptoms; the
quality of and motivation for the practice may be important (Gall et al.).
Organizational Religiousness. Organizational religiousness did not moderate the
relationship between negative life events and depressive symptoms for the whole sample. This
finding is contrary to research indicating a stress-buffering effect of organizational religiousness
on the association between life stress and depressive symptoms (Moreira-Almeida et al., 2006;
Smith et al., 2003; Strawbridge, Shema, Cohen, Roberts, & Kaplan, 1998; Williams, Larson,
Buckler, & Heckmann, 1991), although some research has also found no effect (Smith et al.,
2003). Organizational religiousness may buffer the negative effects of life stressors by increasing
73
emotional and instrumental social support (Moreira-Almeida et al., 2006; Musick et al., 1998),
reinforcing comforting belief systems such as those regarding God’s grace and power (Fetzer
Institute, 1999; Musick et al., 1998) and by deterring individuals from certain behaviors deemed
inappropriate that are often used as maladaptive coping techniques such as substance abuse
(Ellison et al., 2001; Martens et al., 2008).
One possible explanation for why the current study did not find a significant moderating
effect of organizational religiousness is that the type of stressor is important. Strawbridge et al.
(1998) found that organizational religiousness buffered the effect of financial difficulties and
poor health on depressive symptoms, but it amplified relationships between family-related
problems such as marital struggles and abuse and depressive symptoms. Experiencing life
stressors that are viewed negatively by one’s church may increase feelings of guilt,
stigmatization, and shame (Ellison et al., 2001); for instance, some churches may expect
congregation members to have their “house in order” and may express disapproval of families
that appear to have particular difficulty in this area (Strawbridge et al., 1998). The present study
assessed organizational religiousness as a potential buffer of the quantity of reported negative
life events and did not distinguish between family and nonfamily stressors.
Positive Religious Coping. In the entire sample positive religious coping did not
moderate the relationship between negative life events and depressive symptoms contrary to the
hypothesis. This nonsignificant finding is inconsistent with the coping literature (Ano &
Vasconcelles, 2005; Bjorck & Thurman, 2007; Kolchakian & Sears, 2004; Lee, 2007). Positive
religious coping can enhance one’s sense of instrumental support during times of stress (TothCohen, 2004) and increase the probability that negative life events will be interpreted as
opportunities for growth, potentially reducing the negative impact of life stress on psychological
74
well-being (Maltby et al., 2003). The current study differs from most previous research on
positive religious coping and stress in that it investigated cumulative, rather than acute, life
stressors. Religious coping responses to life stressors may be most effective when individuals are
able to use their existing religious belief systems to attribute positive meaning to stressors (Park,
Cohen, & Herb, 1990), yet finding meaning in stress may be easier in instances of a single severe
stressor than multiple moderate stressors (Bjorck & Thurman, 2007).
In one study that did examine the effect of cumulative life stress on depressive
symptoms, Bjorck and Thurman (2007) found that positive religious coping was a significant
moderator in a sample of adult members of a conservative Protestant congregation. This sample
may differ from the sample used in the current study in their view of life stressors. Cohen and
Hill (2007) found that Protestants tend to report higher levels of intrinsic religious motivation
than other religions, and Park et al. (1990) reported that individuals with higher intrinsic
religious motivation are more likely to view life stressors as challenges from God and
opportunities to grow in one’s faith. Viewing challenges as opportunities may facilitate effective
religious coping for multiple stressors by increasing hopefulness and positive expectancies about
the future (Bjorck & Thurman, 2007; Fitchett et al., 1999). Individuals in the present sample
represent diverse religious backgrounds that may contribute to differences in how participants
make meaning out of stressful situations. For example, Catholics may be more likely than other
religious groups to respond to stress by engaging in rituals such as confession intended to reduce
guilt associated with being responsible for the stress (Tix & Frazier, 1998). Jewish individuals
may be more likely to find meaning in stress based on how stressors relate to their community or
ethnic group; whereas, Protestants may be more likely to relate the stressor to a personal spiritual
journey (Cohen & Hill, 2005). Accounting for degree of intrinsic religious motivation in future
75
research may help specify when positive religious coping moderates negative life events and
depressive symptoms.
Negative Religious Coping. For the entire sample negative religious coping did not
significantly moderate negative life events and depressive symptoms. This was inconsistent with
the hypothesis; however, little research exists on this subject (Bjorck & Thurman, 2007), so it is
not clear if these findings represent a unique effect. The tendency to view God as a harsh judge
who will abandon individuals in distress is substantially less common than more benign or
benevolent views of God (Moreira-Almeida et al., 2006; Pargament et al., 1998), and, as
supported in the current study, is significantly independently associated with increased
depressive symptoms (Smith et al., 2003). Individuals frequently employing negative religious
coping might maintain elevated levels of perceived stress even in the absence of objective
stressors because they are psychologically burdened with fear of punishment and abandonment
(Ano & Vasconcelles, 2005). It may be interesting to assess how negative religious coping
moderates the association between perceived rather than objective stress and depressive
symptoms. If an amplifying effect were found, clinicians working with clients high in negative
religious coping may reduce depressive symptoms substantially by focusing efforts on reducing
perceived stress.
Hypothesis 6: Prevalence of Outcome and Predictor Variables by Ethnic Group
Due to higher likelihood of exposure to risk factors relative to Whites, some research has
found ethnic minorities to be at increased risk for depressive symptoms (Cuella & Roberts, 1997;
Riolo, Nguyen, Greden, & King, 2005; Wight et al., 2005); however, some studies have also
indicated little to no ethnic differences in depressive symptoms (Saluja et al., 2004; Mendelson et
al., 2008), and measurement bias does not appear to explain these noneffects (Breslau et al.,
76
2008). The present study found no significant differences among ethnic groups in their level of
depressive symptoms. This may indicate that the particular minority students used in the present
sample do not experience increased risk factors for depressive symptoms relative to Whites, or
that they have higher levels of factors that protect from depressive symptoms that counteract
relatively higher exposure to risk factors. For example, factors that may protect from depressive
symptoms in a minority individual more so than for a nonminority include family cohesiveness
and emotional and instrumental support from the community (Breslau et al., 2006; Lewis-Coles
& Constantine, 2006; Locke et al., 2007). It is also possible that the findings are influenced by
the overall demographics of the sample. Specifically, for minority students being successfully
enrolled in college and attending a university comprised primarily of members of ethnic
minorities may be predictive of increased psychological health (Goldsmith, 2004; Lewinsohn,
Hoberman, & Rosenbaum, 1988; Morenoff et al., 2007).
Similar to this study’s findings on depressive symptoms, no ethnic differences were
found for negative life events, trait hope, or negative religious coping. Based on studies of
minority groups showing relatively higher exposure to life stressors such as racism (Lewis-Coles
& Constantine, 2006) and acculturation (Ramos, 2005; Torres & Rollock, 2007) and fewer
resources available for achieving goals (Cuella & Roberts, 1997; Plant & Sachs-Ericsson, 2004),
it is surprising that ethnic minorities did not differ from Whites in trait hope and negative life
events. Despite expectations that race-related barriers to goal achievement would hinder the
development of hope (Snyder, 1995), Chang and Banks (2007) found, similar to the present
study, that minority college students were as hopeful as or more hopeful than White students.
Early exposure to race-related barriers may enhance some children’s ability to identify and use
available resources to address obstacles and to anticipate and prevent race-related stressors
77
(Chang & Banks, 2007). Successfully overcoming race-related obstacles may reinforce agentic
thinking by increasing belief in one’s ability to achieve goals despite barriers. Minority students
in the present sample, because they have successfully completed secondary education and
enrolled in college, may represent a greater proportion of those who, at some point during their
lives, learned to use race-related barriers as opportunities for hope enhancement (Chang &
Banks, 2007). In order to design more effective interventions for hope, it may be important to
identify developmental variables or conditions that predict when individuals are most likely to
increase their level of hope as a response to racism-related stress; prospective and longitudinal
research may be the most appropriate way to accomplish this task.
Little research has investigated ethnic differences in optimism (Burke et al., 2000); in the
current study, Hispanics reported significantly higher levels of dispositional optimism than
Blacks but not Whites or Asians. Chambers (2006) found that Black undergraduate students did
not significantly differ from Hispanic students on the Life Orientation Test; other studies have
also failed to find significant ethnic differences in optimism levels (Chang, 1996; Grote et al.,
2007). Hence, it is not clear why Hispanics in this sample reported higher optimism than Blacks.
Potentially, the fact that Hispanics represent the largest ethnic group in the sample impacts
optimism; indeed, Goldsmith (2004) found that the ethnic makeup of other students and teachers
significantly predicted levels of optimism among 24,599 eighth-graders. Because of their high
representation in the present sample, Hispanics’ optimism may have been bolstered by a stronger
sense of ethnic identity (Beiser & Hou, 2006; Phinney, 1990, 1992), a construct related to better
mental health and beliefs about the future (Mossakowski, 2003; Adelabu, 2008). Future research
should investigate the impact of ethnic composition and ethnic identity on levels of optimism.
78
No differences in optimism were found between Hispanics and Whites or Asians, which
suggests that other factors specific to Blacks may explain their lower level of optimism. For
example, in addition to individual racism Blacks have been exposed to high rates of institutional
and cultural racism for decades despite prevention policies and social change efforts (LewisColes & Constantine, 2006). Continual disappointment in the effectiveness of these efforts in
spite of optimistic expectations may lead to more pessimistic attitudes regarding the elimination
of race-related obstacles (Milam et al., 2004; Petersen, 2000). More research is needed to
determine if racism and failure of efforts to reduce racism negatively affects optimism.
In this study, Blacks reported higher levels of daily spiritual experiences than Hispanics,
Whites, and Asians. Additionally, for private religious practices Blacks reported significantly
higher levels than Hispanics and Whites; for organizational religiousness Blacks reported
significantly higher levels than Hispanics; and for positive religious coping Blacks reported
significantly higher levels than Whites. This strong tendency for Blacks to report greater
amounts of religiosity and spirituality is consistent with other research supporting the centrality
of religion to the Black community (Ellison, 1995; Mattis, Fontenot, & Hatcher-Kay, 2003;
Utsey, Adams, & Bolden, 2000).
During the 19th and 20th centuries in response to widespread racism the Black church
became very influential in providing coping resources and strategies to its congregations (LewisColes & Constantine, 2006). Across a wide variety of samples spanning age and socioeconomic
status, and using varied indicators including religious service attendance, daily prayer, church
membership status and endorsing self-reported spirituality and religiosity items Blacks tend to
score significantly higher in levels of religiosity and spirituality than Whites (Taylor, Chatters,
Jayakody, & Levin, 1996).
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The current results suggest that cultural differences in the degree of reported religiosity
and spirituality exist among college students, potentially influencing how clinicians working
with these particular populations should approach treatment. Manualized cognitive therapies
using standard techniques such as challenging cognitive distortions have been adapted to include
religious language and have been found to be as or more effective than original treatments in
treating depression among religious clients (McCullough, 1999). Such approaches may be
particularly beneficial within the Black community (Worthington et al., 1996).
Hypothesis 7: Study Variables as Moderators in Analyses Stratified by Ethnicity
Trait Hope. Although trait hope was a significant moderator of negative life events and
depressive symptoms for the entire sample, it did not reach significance in any of the individual
ethnic groups, which is inconsistent with previous research (Reff et al., 2005; Snyder et al.,
1991). Sample size within individual ethnic groups may not have provided sufficient power to
detect a somewhat weak effect. The absence of a possible stress-buffering effect in any group,
however, does not negate the potential importance of trait hope for psychological health. In the
present study significant main effects occurred; trait hope was significantly predictive of reduced
depressive symptoms for Blacks, Hispanics, and Whites over and above the effects of age,
gender, and negative life events. Main effects may be due to increased cognitive flexibility,
positive affect, and motivation in dealing with life stress (Roesch & Vaughn, 2006; Snyder et al.,
1991). Interventions that increase hope can lead to greater positive emotions and a sense of
meaning in life (Seligman et al., 2006). Although hope theory suggests that hope may play an
important role in coping with distress (Lazarus, 1999; Snyder et al., 1991), stratified analyses did
not support hope as a moderator of cumulative stress and depressive symptoms. A larger sample
size may be needed to detect significant differences. Alternatively, differentiating between
80
different types of life stressors may specify the variables for which hope moderates the influence
of life stress on depressive symptoms (Maton, 1989).
Dispositional Optimism. A significant moderating effect of optimism on the relationship
between negative life events and depressive symptoms was only found in Whites. This concurs
with previous research on the potential stress-buffering effect of optimism conducted in
predominately White samples (Chang, 1998a; Chang, 2002; Chang & Sanna, 2003; Hirsch,
Wolford, et al., 2007; Scheier & Carver, 1985). Individuals with high levels of optimism may be
more likely to view life stressors as challenges and opportunities for growth and to perceive
greater resources for dealing with challenges (Chang, 1998a). Such appraisals can lead to more
adaptive coping such as direct engagement and persistence (Scheier & Carver, 1992), possibly
protecting from depressive symptoms during times of distress via effective problem-solving
(Chang, 1998a).
The moderating effect of optimism, however, was not found in non-White individuals.
Potentially important variables not considered in this study are racism-related stress and
challenges particular to being an ethnic-minority group member. If members of ethnic minority
groups perceive life stress to be race-related, they may be more likely to appraise stressors as
threatening, increasing maladaptive coping responses such as emotion-focused coping (Ong &
Edwards, 2008). It is also likely that despite having an optimistic view of the future an individual
would be subject to the detrimental effects of stress resulting from racism (Lewis-Coles &
Constantine, 2006). Members of minority groups may also have witnessed family members and
peers unsuccessfully attempt to combat the negative effects of racism-related stress, possibly
reducing their belief that challenging circumstances will turn out well (Goldsmith, 2004). The
role of racism-related stress in the development of optimism or pessimism needs to be further
81
explored to identify possible interventions that could foster optimistic beliefs for minorities
facing challenging circumstances such as discussing narratives of successful optimism under
similar circumstances (Snyder et al., 2006).
Concurrent with previous research on optimism and depressive symptoms (Andersson,
1996; Chang, 1996; Scheier et al., 1994), in the present study optimism was significantly
predictive of reduced depressive symptoms for Blacks, Hispanics, and Whites after controlling
age, gender, and negative life events. Efforts to increase optimism have been promising.
Individuals identified as at risk for depression have participated in group interventions delivered
in live settings or via the Internet, and results have shown increased optimism and decreased
depressive symptoms compared to placebo-controlled groups (Schueller & Seligman, 2008). The
robust negative relationship between optimism and depressive symptoms in the present sample
suggests that most college students despite their level of life stress may benefit from increased
optimism. Current results also suggest that for Whites in particular optimism may be especially
beneficial in the context of multiple life stressors. For members of ethnic minority groups, it may
be important to assess for the tendency to minimize one’s own positive expectancies during
times of stress based upon observing negative experiences of others within one’s ethnic group
(Goldsmith, 2004).
Daily Spiritual Experiences. Although daily spiritual experiences did not moderate
negative life events and depressive symptoms for the entire sample, ethnically stratified analyses
revealed a significant moderation effect among Whites. Additionally, a main effect of daily
spiritual experiences predicting decreased depressive symptoms when controlling for age,
gender, and negative life events was found only in Whites. These results suggest that daily
having experiences such as inner peace, closeness with God, and admiration of natural beauty
82
may play a salutary role in psychological health for Whites more so than for other ethnic groups.
This is somewhat surprising given recent research that was unable to detect a significant
moderating effect of ethnicity in the relationship between spirituality and depressive symptoms
(Desrosiers & Miller, 2007; Mofidi et al., 2006, 2007). It should be noted, however, that the
present study assessed for moderating effects within separate ethnic groups individually but did
not directly test for a moderating effect of ethnicity; therefore, the current study may not be
statistically comparable to past research (Desrosiers & Miller, 2007; Mofidi et al., 2006, 2007).
It is possible that spirituality can serve as a beneficial coping tool for members of
minority groups under stress (Perez, 2002), but minority groups’ decreased use of mental health
resources may counteract any reductions in depressive symptoms attributable to spirituality
(Baez & Hernandez, 2001). Specifically, more spiritual minorities may avoid mental health
services because of a belief that their faith should be sufficient to treat emotional distress
(Mahan, 2005), or that they will be stigmatized for unusual spiritual practices such as visiting
with deceased loved ones during times of distress (Constantine et al., 2005; Mahan, 2005).
Clinicians working with minority clients high in spirituality should be wary of culture-specific
hindrances to engaging in and following through with treatment, and clinicians should be ready
to use creative solutions to barriers such as including clergy or family in treatment (Baez &
Hernandez, 2001). Future research is needed to assess how spirituality may influence minority
college students’ perceptions of mental health treatments and how this might impact depressive
symptoms.
Private Religious Practices. In Blacks and Whites private religious practices significantly
moderated the association between negative life events and depressive symptoms. In these ethnic
groups the relationship between negative life events and depressive symptoms is weakened at
83
higher levels of private religious practices including praying, meditating, scripture reading,
saying grace before meals, and consuming religious media (Fetzer Institute, 1999). In Whites and
Asians only a significant main effect was found; private religious practices significantly
predicted decreased depressive symptoms after controlling for age, gender, and negative life
events. The variation in results across ethnic groups highlights the possible role of cultural
factors in the function of religiosity.
For Blacks and Whites in the present sample engaging in private religious practices when
facing multiple life stressors may mitigate the negative effects of stress by decreasing the
probability that stressors will be judged as threatening, by providing a sense of meaning and
emotional support, and by increasing optimism and motivation to deal with problems (Gall et al.,
2005; Mattis et al., 2003; Stolley, Buckwalter, & Koenig, 1999). The lack of effect in Hispanics
and Asians may be explained by considering the type of religious practices. Poloma and
Pendleton (1990) found that conversational and meditational praying was related to enhanced
well-being, whereas ritualistic and petitionary praying was related to decreased well-being.
Hispanics who have a strong connection to the Catholic Church, which is known for its traditions
and rituals (Christiano, 1993), and Asians with a heritage of Eastern religions emphasizing
formality, tradition, and hierarchy (Carnes & Fenggang, 2004) may tend to engage in more
ritualistic practices than Blacks or Whites. More research assessing for type of private religious
practice is needed to test this possibility.
In addition to the potential importance of the type of religious practice, the type of
stressor may be important to understanding the moderating effect of private religious practices.
For example, in a large community sample, the negative effects of family problems were
exacerbated by private religious practices, perhaps by increasing the shame and dissonance
84
individuals feel for failing in their family life, an area that many religious belief systems
(Strawbridge et al., 2003) as well as the Hispanic and Asian cultures in particular (Chang &
Subramaniam, 2008; Fuligni, 2001) assign strong spiritual meaning. Further, Hispanics and
Asians may be exposed to challenges that increase familial stress such as generational
differences in acculturation, which can lead to parent-child values gaps and elevate family
conflict (Park, Vo, & Tsong, 2009; Torres & Rollock, 2007). Clinicians working with religious
or spiritual clients, particularly Hispanics and Asians who report the use of private religious
practices to cope with stress, may wish to assess for familial conflict and potential feelings of
guilt or shame.
Organizational Religiousness. In the current study, organizational religiousness
moderated the relationship between negative life events and depressive symptoms for Whites and
Blacks but not Hispanics nor Asians. In significant moderation models the relationship between
negative life events and depressive symptoms was weakened at higher levels of organizational
religiousness. After controlling for age, gender, and negative life events, organizational
religiousness significantly predicted decreased depressive symptoms in Whites only.
The significant moderating effect of organizational religiousness in Blacks and Whites
may indicate that involvement in a religious group provides access to beneficial emotional and
instrumental social support when a person experiences elevated stress (Moreira-Almeida et al.,
2006; Musick et al., 1998). Additionally, consistent religious involvement may reinforce belief
systems regarding one’s spiritual or religious identity and promote faith that God will intervene
or give the strength needed to deal with the stress (Fetzer Institute, 1999; Musick et al., 1998).
It is not entirely clear why organizational religiousness does not appear to function
similarly in Hispanics or Asians. For Asians, a heavy cultural influence on “saving face” may
85
prevent them from accessing the social resources available in an organized religion because they
attempt to keep their problems hidden from others (Chang & Subramaniam, 2008). Clinicians
working with religious Asians should be careful not to create cultural distress by overencouraging them to seek help for problems that others in their congregation may consider
shameful (Berg & Jaya, 1993). It may be important for future research to focus on examination
of the association between “saving face” and the use of organized religious support among
religious Asian college students who may share different values and customs than their parents
(Fuligni, 2001).
For Hispanics a potentially important variable that was not assessed in the current study
is motivation (i.e., intrinsic or extrinsic) for religious involvement, which can be important to
understanding the relationship between religiosity and depressive symptoms (Smith et al., 2003).
Since Spain colonized Latin America over 500 years ago, the Hispanic culture has developed a
very strong tie to the Catholic Church (Christiano, 1993). Indeed, a large majority of Hispanics
in the present sample identified themselves as being Catholic, a religion rich in tradition and
rituals (Christiano, 1993). Catholic undergraduates scored significantly higher in extrinsic and
lower in intrinsic religious motivation than Protestant students (Cohen & Hill, 2007). Hispanic
students in the present sample high in organizational religiousness may be motivated by cultural
or other extrinsic factors and may not benefit from possessing a strong religious or spiritual
identification (Smith et al., 2003). Clinicians working with religious or spiritual clients should be
careful not to use religious involvement as a marker for religiosity or religious identification;
rather, motivation for attendance may be beneficial to explore. Future studies investigating the
role of organizational religiousness in depressive symptoms should control for extrinsic and
intrinsic motivation.
86
Positive Religious Coping. Although positive religious coping did not significantly
moderate negative and potentially traumatic life events and depressive symptoms in the entire
sample, it was a significant moderator in Whites, and there was a clinically meaningful trend in
Blacks. In both cases the relationship between negative life events and depressive symptoms was
weaker at high versus low levels of positive religious coping. This relationship is consistent with
the limited research on positive religious coping as a moderator of cumulative life stress and
depressive symptoms (Bjorck & Thurman, 2007). Individuals who attempt to understand life
stress within the context of a spiritual world, who look to God for emotional and instrumental
support, and who work proactively with God to address life stressors may be protected from the
negative effects of stress via adaptive cognitive appraisals (Bjorck & Thurman, 2007; Maltby &
Liza, 2003; Musick et al., 1998). Specifically, people who use positive religious coping are more
likely to view life stressors as opportunities for spiritual growth and development (Maltby &
Liza, 2003; Park et al., 1990) and to perceive greater religious or spiritual resources for
addressing difficult circumstances (Bjorck & Thurman, 2007; Musick et al., 1998). This may be
particularly true in the Black community because of a heavy emphasis on showing faith in God,
particularly when someone is in need (Mattis et al., 2002). Many religious Whites also focus on
faith rather than works as being necessary for identification as a child of God (Ward, 2008), and
a consistent emphasis of faith facilitates trusting God during times of higher stress (Park et al.,
1990).
Positive religious coping did not moderate life stressors and depressive symptoms among
Hispanics and Asians. Although it was not tested in this study, the relationships between the
Hispanic community and Catholic Church (Christiano, 1993) and between the Asian community
and Eastern religious philosophies (Carnes & Fenggang, 2004) may impact Hispanics’ and
87
Asians’ motivation for religious behaviors. Intrinsic religiousness may be an important condition
for positive religious coping to have a salutary impact (Park et al., 1990), and attempting to
employ religious coping strategies in times of high stress may be ineffective if one does not
possess a strong religious or spiritual identification. Before drawing conclusions, however, future
research is needed to assess for the role of extrinsic religious motivation in the relationship of
positive religious coping and depressive symptoms.
Negative Religious Coping. In the current sample, negative religious coping significantly
moderated negative life events and depressive symptoms in only Asians, such that the
relationship between negative life events and depressive symptoms was significantly stronger at
higher levels of negative religious coping. After controlling for age, gender, and negative life
events, there was a significant main effect in which negative religious coping was related to
increased depressive symptoms in Blacks, Hispanics, and Whites, but not Asians.
Among Asians, the group with the least statistical power in the current sample, an
interaction was observed. For Asians who believe that they have failed and are, consequently,
being punished for their mistakes or abandoned by God, the relationship between negative life
events and depressive symptoms was significantly exacerbated. Asians may be more sensitive to
failure and punishment than members of other ethnic groups. Castro and Rice (2003) found that
Asians worry more about making mistakes, report higher expectations from authority figures,
and expect to be criticized more when they make a mistake. These maladaptive patterns are
related to perceptions of God as a harsh judge who is ready to punish those who sin (Corrigan,
1998). This punitive image of God may lead some Asian students to live in fear of sinning
(Castro & Rice, 2003), and this fear can increase the negative impact of life stressors,
particularly if stressors are interpreted as a result of personal failure. Clinicians working with
88
Asian students who are open to discussing their religious beliefs may wish to assess for negative
perceptions of God as a harsh judge in order to understand their clients’ interpretation of life
stressors and to help foster a more adaptive view of life stress. Caution should be used in
challenging clients’ negative views of God (Worthington et al., 1996).
Limitations and Future Research
The current study has several strengths including the use of an ethnically diverse sample
and psychometrically supported instrumentation, but results must also be viewed in the context
of limitations. As an example, use of cross-sectional data precludes the examination of causal
inferences; however, hypotheses for this study were not causal in nature and analyses were
limited to moderation models that are appropriate for cross-sectional data (Finney, Mitchell,
Croncite, & Moos, 1984). Investigation of causality may be particularly important for
associations between variables that are bidirectional in nature. For instance, although negative
life events exert an influence on depressive symptoms, the reverse may also be true (Kendler et
al., 1999). Similarly, hopeful thinking may reduce depressive symptoms, but depressive
symptoms may also reduce hopeful thinking (Gum, Snyder, & Duncan, 2006).
Although use of a diverse sample is a strength of this study, small sample size precluded
examination of ethnicity as a potential moderator (Aiken & West, 1991); the present study
assessed for moderating effects of psychological and religious variables among four separate
groups that differed by ethnicity. Future research on depressive symptoms would benefit from
the examination of possible three-way interactions between ethnic status, negative life events,
and potential positive psychological and religious moderators (Dawson & Richter, 2006).
Further, sample size for Asian respondents was small enough to limit interpretability and
generalizability. Although the majority of the main and interaction effects tested within Asians
89
were nonsignificant, an examination of the unstandardized beta coefficients indicates that a
relationship comparable to or stronger than the other ethnic groups was often found within
Asians but may have simply lacked the power to achieve significance. In general, psychosocial
research should always strive to incorporate diversity into research samples. It should also be
noted that some ethnic differences in the main and moderating effects of the religious and
spiritual variables may be explained by differences in religious affiliation. Although controlling
for religious affiliation when conducting ethnically stratified analyses would have significantly
reduced power because of overrepresentation in certain religions (e.g., over three fourths of
Hispanics reported Catholicism) (Monroe, 2000), examining main and moderating effects within
separate religious groups may be an important extension of this research.
It is not clear how well the findings from the present study may generalize to other
collegiate or ethnically-diverse samples or to community or clinical samples. Although the use
of undergraduate students is often cited as a general limitation of social sciences research,
studying depressive symptoms within college samples is important due to the potentially
increasing prevalence of major depressive disorder among this group (ACHA, 2000; ACHA,
2006) and the increased risk of lifetime recurrence for earlier onset depressive disorders (APA,
2000). In addition, selection bias may exist in the ethnically-diverse participants of the current
study because those minority-group members with fewer risk factors or more adaptive patterns
of resiliency may be more likely to pursue and attend college (Chang & Banks, 2007).
Use of self-report measures may be problematic, as this methodology is subject to recall
bias and there may be a lack of assurance that a respondent understands the meaning of a
question (Howard, 1994; Patten, 2003; Spector, 1994). Further, the Life Events Scale used in the
present study (Tomoda, 1997) has limited reliability and validity data to support it and, although
90
the cumulative checklist method of assessing negative life events can be convenient, this
approach neglects significant information regarding the subjective impact of a negative life event
(Horowitz, Schaefer, Hiroto, Wilner, & Levin, 1977). Negative life events vary in the degree to
which they are actually stressful (Horowitz et al.); one method of capturing this variability in
future research may be to use weighted checklists that assign values to each stressor based on
normative reporting (e.g., Holmes & Rahe, 1967). Another, simpler method is to assess one’s
level of perceived stress (e.g., Chang, 1998a), but this method may lack objectivity (Lewinsohn,
Rohde, & Gau, 2003). Despite their shortcomings, life events checklists provide a relatively
objective and accurate assessment of the experience of life stress (Lewinsohn et al., 2003).
In somewhat stark contrast to the lack of support for the Life Events Scale used in this
study, a strength of the present research is the use of additional instrumentation that has adequate
to excellent reliability and validity in use with college students and ethnically diverse
populations. For example, the BDI-II (Beck et al., 1996) has been successfully used and found to
be psychometrically sound in several ethnically diverse groups (Dutton et al., 2004; Carmody,
2005; Van Voorhis & Blumentritt, 2007) as has the THS (Roesch & Vaughn, 2006) and LOT-R
(Burke et al., 2000). The BMMRS was created to address decades of methodological
inconsistency in the study of religion and spirituality (George et al., 2000; McCullough &
Larson, 1999; Mofidi et al., 2007; Smith et al., 2003), and it also has adequate psychometric
properties in Blacks and Whites (Neff, 2006). Even though research supports use of these
instruments in non-Whites, an interesting finding of the current study is that moderation effects
were most often significant among Whites; the BDI-II (Beck et al., 1996), THS (Snyder et al.,
1991), LOT-R (Scheier & Carver, 1994), and subscales of the BMMRS (see Fetzer Institute,
1999) were developed using primarily White samples. Failing to consider minority groups when
91
developing instruments may neglect their unique contribution to the meaning of measured
constructs (Helms, 2006). It may be possible however, that factors related to ethnicity such as
income level influenced the relatively stronger associations among Whites.
Because the present study is a secondary analysis of data collected for a larger project,
potentially important variables were not assessed thoroughly or at all. For instance, although
income was assessed in the original study, substantial missing data (30.3%) prevented its use in
analyses. Income levels have a significant association with levels of depressive symptoms, with
lower income increasing risk for depressive symptoms (Lorant et al., 2003) and with income
disparities greater among ethnic minority groups than Whites (Hudson, 2005). Future research in
this area should control for the effects of income. Another neglected variable is racism-related
stress, which can be a significant source of distress for members of ethnic minority groups and is
positively related to depressive symptomology (Clark, Anderson, Clark, & Williams, 1999;
Lewis-Coles & Constantine, 2006; Yip, Gee, & Takeuchi, 2008). Further, variables examined for
moderator status in the present study such as optimism may differ in their association with
racism-related stress as compared to stress not related to racism (Ong & Edwards, 2008). To
more fully understand the association of buffering variables in ethnic minorities, both racismrelated and non-racism-related stress should be examined.
Finally, the ethnic classification used in the current study may be a taxonomical
limitation. Although Hispanics may share a common Spanish ancestry, they vary widely in their
cultural background based on country and region (Hunt, Schneider, & Comer, 2004). Indeed,
research distinguishing between Mexican-Americans, Puerto Ricans, and Cuban Americans has
found substantial differences in risk factors for and prevalence of depression (Oquendo et al.,
2004). This classification approach may have affected the results of the current research.
92
Hispanics were the only ethnic group in which none of the potential moderators were significant.
If the sample of Hispanics used in the current study represented diverse cultural backgrounds,
associations between variables may have been harder to detect because of lack of consistency
within the broadly-defined ethnic group (Hunt et al., 2004). Future research examining potential
stress-buffering effects of positive psychological and religious or spiritual variables should use
more specific labels of race, ethnicity and culture.
Conclusions
The current study extends research on positive psychological and religious and spiritual
variables by examining their association with depressive symptoms and their role as moderators
of the relationship between negative and potentially traumatic life events and depressive
symptoms across different ethnic groups. Results generally supported a salutary relationship
between the study variables and depressive symptoms; however, these relationships differed by
ethnicity.
Negative life events were moderately predictive of increased depressive symptoms
regardless of ethnicity. This relationship, however, is not inevitable. Increased hope weakened
the association of negative life events and depressive symptoms, yet this moderating effect of
hope did not appear to be statistically significant within any individual ethnic group. Optimism,
on the other hand, significantly weakened the effect of negative life events among White
participants only, suggesting that cultural factors such as exposure to race-related stressors may
affect the potentially stress-buffering effect of optimism when facing multiple life stressors.
Accounting for ethnicity was especially important in understanding the role of religious
and spiritual variables in the relationship between negative life events and depressive symptoms.
In this diverse sample overall none of the religious and spiritual variables weakened the
93
association of negative life events and depressive symptoms. A closer look at each ethnic group,
however, revealed that religious and spiritual variables tended to be associated, albeit weakly,
with fewer depressive symptoms in Blacks and Whites and were unrelated in Hispanics and
Asians. Among Blacks and Whites private religious practices, organizational religiousness, and
positive religious coping, in addition to daily spiritual experiences for Whites, significantly
moderated the effect of negative life events. Negative religious coping predicted increased
depressive symptoms in each ethnic group and also exacerbated the relationship between
negative life events and depressive symptoms in Asians.
In clinical practice the variables from the present study may be directly or indirectly
related to treatment goals. Hope and optimism, which tended to be moderately to strongly
associated with fewer depressive symptoms in each ethnic group, may be enhanced with
dedicated interventions or by incorporating specific exercises such as positive self-statements
and expressing gratitude, into existing treatments. The present results suggest that optimism may
be particularly beneficial for White college students who are exposed to several life stressors by
enabling them to see positive aspects of stressful situations and remain engaged in efforts to
overcome the stress. Although religious and spiritual variables tend to be related to decreased
depressive symptoms in Blacks and Whites particularly those reporting high levels of negative
life events, the current results found no such effect for Hispanics and Asians. It may be important
for clinicians to consider culturally-influenced factors such as the degree of extrinsic versus
intrinsic motivation for being religious or spiritual. Some clients may wish to incorporate their
religiosity and spirituality into treatment sessions; in this case, clinicians should be aware of the
potential implications of ethnic and cultural background.
94
Although previous studies have investigated the potentially moderating effects of several
of the variables used in the current research such as hope, optimism, and positive and negative
religious coping, this is the first study that has employed the same methodology and
instrumentation to simultaneously assess negative life events, potential moderators, and
depressive symptoms across four different ethnic groups. The current findings are at least a first
step toward gaining a more comprehensive understanding of the role that ethnic differences
might play in the mechanisms contributing to the development or prevention of
psychopathology, and it is hoped that they might be used to inform the design of targeted and
effective, culturally-specific interventions that increase hope and optimism and that incorporate
elements of religiosity and spirituality. The current results do not provide a definitive analysis of
the topic, but they do support the potential utility of positive psychological and religious and
spiritual variables in the treatment of depressive symptoms occurring as a result of the
experience of negative and potentially traumatic life events.
95
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VITA
PRESTON L. VISSER
Personal Data:
Date of Birth: June 4, 1985
Place of Birth: Johnson City, Tennessee
Marital Status: Married
Education:
Gateway Christian Schools, Home school Umbrella Organization,
Memphis, Tennessee
B.S. Psychology, East Tennessee State University, Johnson City,
Tennessee, 2007
M.A. Psychology, Clinical Concentration, East Tennessee State
University, Johnson City, Tennessee, 2009
Professional Experience:
Research Assistant, Skin Cancer Prevention Laboratory; Johnson
City, Tennessee, 2005-2007
Graduate Assistant, East Tennessee State University, College of
Arts and Sciences, 2007-2009
Honors and Awards:
Dean’s List, East Tennessee State University, 2003-2007
East Tennessee State University’s Outstanding Psychology
Sophomore, awarded by Psi Chi
East Tennessee State University’s Outstanding Psychology Senior,
awarded by Psi Chi
Recipient of James H. Quillen Scholarship, 2007-2010
1st Place for Oral Presentation in Graduate Division of 2009
Appalachian Student Research Forum
Conference Presentations:
4 First Author Oral Presentations at Local and National
Conferences
13 First Author Oral Presentations at Local and National
Conferences
123