Visser P Thesis Final

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

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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.

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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!

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CONTENTS

PageABSTRACT………………………………………………………………………………. 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……………………………… 41

5

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

6

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—


7. Negative Life Events, Organizational Religiousness, and Depressive Symptoms—


8. Negative Life Events, Positive Religious Coping, and Depressive Symptoms—


9. Negative Life Events, Negative Religious Coping, and Depressive Symptoms—


7

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)…................................................................................ 62

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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,

9

& 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

10

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 12-

month 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).

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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, &

12

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

13

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

14

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

15

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), self-

esteem 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,

16

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, Tusaie-

Mumford, & 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

17

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).

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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

19

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

20

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

21

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 self-

regulate 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

22

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

23

(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

24

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

25

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

26

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

27

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 meta-

analysis of 147 studies, ethnicity did not appear to moderate the relationship between depression

28

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 community-

based 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.

29

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.

30

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

31

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 item-

total correlations suggest good internal consistency, with r ranging from .41 to .64, except for the

32

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.,

33

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

34

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

35

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

36

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

37

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.


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.


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

38

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.

39

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. Self-

reports 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).

40

Table 1

Levels of Demographic, Predictor, and Criterion Variables across Ethnic Groups

Variable Total SampleM SD

BlacksM SD

HispanicsM SD

WhitesM SD

AsiansM 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 [3.82] 5.80 [3.62] 6.76 [3.67] 6.11 [3.71] 7.24 [5.34]

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] 11.35 [8.75]

Organizational Religiousness 4.33 [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 [2.27] 5.38 [2.38] 5.70 [2.30] 5.35 [1.83] 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 [.71] 1.56 [.72] 1.44 [.70] 1.42 [.71] 1.73 [.63]

% Female 69.17% 70.41% 75.62% 53.52% 59.09%

Religious Affiliation

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%

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;

41

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

42

Table 2

Bivariate Correlations of Study Variables, with Demographics Included

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.

Negative Life Events

Trait Hope

Optimism Spiritual Experiences

Religious Practices

Organizational Religiousness

PositiveCoping

Negative Coping

Gender Age Year in School

Depressive Symptoms

.39*** -.52*** -.55*** -.16** -.09 -.08 -.10 .35*** .28*** -.04.04


- -.23*** -.31*** -.12* -.04 .02 -.08 .21*** -.01 -.17**.00

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 .07.07

ReligiousPractices

- - - - - .64*** .65*** -.08 .04 .16**.13*

OrganizationalReligiousness

- - - - - - .50*** .02 -.07 .04.05

Positive Coping - - - - - - - -.04 .07 .08 .03

Negative Coping - - - - - - - - .07 -.13* .08

Gender - - - - - - - - - -.09 -.02

Age - - - - - - - - - - .32***

43

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).

44

Table 3

Negative Life Events, Hope, and Depressive Symptoms—Multivariate Linear Regression

Total Sample Blacks Hispanics Whites Asians

Step 1 R2

Step 2 ΔR2

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]Step OneConstant 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]

Trait Hope -10.04‡ -.98 [.10] -5.03‡ -1.00 [.20] -6.63‡ -1.08 [.16] -5.01‡ -.99 [.19] -1.43 -.73 [.51]

Negative Life Events 7.22‡ .73 [.10] 3.88‡ .80 [.21] 3.96‡ .71 [.18] 2.80+ .56 [.20] 2.54* 1.03 [.41]

Step Two

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]

Trait Hope -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


-2.17* -.06 [.03] -1.44 -.07 [.05] -.40 -.02 [.05] -1.60 -.07 [.05] -1.24 -.12 [.10]

* 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.

45

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.

46

Table 4

Negative Life Events, Optimism, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

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]T-

ValueUn.β [SE] T-Value Un.β [SE] T-Value Un.β [SE] T-Value Un.β [SE]

Step One

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]

Step Two

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]

Optimism X

Negative Life Events1.94 .04 [.02] 1.60 .07 [.04] .296 .01 [.04] 2.03* .06 [.03] .94 .16 [.17]

* 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.

47

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

48

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.

49

Table 5

Negative Life Events, Daily Spiritual Experiences, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

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]Step One

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]

Step Two

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]

Spiritual Experiences X

Negative Life Events-.78 -.01 [.01] -.89 -.03 [.03] 1.05 .03 [.03] -2.62* -.07 [.03] -.25 -.01 [.05]

* 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.

50

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

51

Table 6

Negative Life Events, Private Religious Practices, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

R2 = .239

ΔR2 = .005

R2 = .288

ΔR2 = .034

R2 = .213

ΔR2 = .005

R2 = .302

ΔR2 = .083

R2 = .534

ΔR2 = .002


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]

Step Two

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]

Religious Practices X

Negative Life Events-1.57 -.03 [.02] -.211* -.07 [.03] 1.00 .04 [.04] -2.94+ -.10 [.03] -.23 -.01 [.05]

* 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.

52

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

53

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.

54

Table 7

Negative Life Events, Organizational Religiousness, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

R2 = .236

ΔR2 = .004

R2 = .287

ΔR2 = .031

R2 = .212

ΔR2 = .001

R2 = .320

ΔR2 = .093

R2 = .435

ΔR2 = .010


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]

Step Two

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]

Organizational Religiousness

X Negative Life Events-1.35 -.06 [.05] -.202* -.20 [.10] .46 .04 [.09] -3.19+ -.28 [.09] .53 .15 [.29]

* 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.

55

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.

56

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.

57

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.

58

Table 8

Negative Life Events, Positive Religious Coping, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

R2 = .238

ΔR2 = .003

R2 = .295

ΔR2 = .023

R2 = .212

ΔR2 = .002

R2 = .279

ΔR2 = .048

R2 = .408

ΔR2 = .002


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]

Step Two

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]

Positive Religious Coping

X Negative Life Events-1.29 -.04 [.03] -1.76 -.12 [.07] .63 .04 [.07] -2.13* -.16 [.07] -.25 -.03 [.13]

* 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.

59

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

60

Table 9

Negative Life Events, Negative Religious Coping, and Depressive Symptoms—Multivariate Linear Regression


Step 1 R2

Step 2 ΔR2

R2 = .302

ΔR2 = .002

R2 = .393

ΔR2 = .003

R2 = .292

ΔR2 = .014

R2 = .248

ΔR2 = .000

R2 = .434

ΔR2 = .162


Constant1.97*

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]

Step Two

Constant2.04*

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]

Negative Religious Coping

X Negative Life Events.92 .04 [.04] -.68 -.05 [.07] 1.73 .15 [.09] .05 .01 [.12] 2.45* .28 [.11]

* 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.

61

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.

62

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.

63

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

64

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

65

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

66

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

67

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.

68

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).

69

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.

70

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).

71

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.

72

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.

73

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

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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 (Toth-

Cohen, 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

75

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

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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.,

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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

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(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.

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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 (Lewis-

Coles & 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 (Lewis-

Coles & 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

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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

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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

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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

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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

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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

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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 over-

encouraging 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.

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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

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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

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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

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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

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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

92

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 racism-

related 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.

93

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

94

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.

95

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.

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VITA

PRESTON L. VISSER

Personal Data: Date of Birth: June 4, 1985Place of Birth: Johnson City, TennesseeMarital 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, 2003-2007East Tennessee State University’s Outstanding Psychology

Sophomore, awarded by Psi ChiEast Tennessee State University’s Outstanding Psychology Senior,

awarded by Psi ChiRecipient of James H. Quillen Scholarship, 2007-20101st 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

Visser P Thesis Final

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