Articulo de Depresion y Ansiedad Para Seminario

8/2/2019 Articulo de Depresion y Ansiedad Para Seminario

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Intolerance of Uncertai nty, Depression, and Anxiety: The Moderating andMediati ng Roles of Rumination

Kelly Yu-Hsin Liao

1

and Meifen Wei

2

1University of Missouri - St. Louis2Iowa State University

Objectives: This study examined rumination as a moderator and mediator between intolerance of

uncertainty (IU) and depression and anxiety symptoms. Designs: The study was a cross sectional

study. Survey data were collected from 332 undergraduate students at a large Midwestern university.

Results: The results from hierarchical analyses supported the moderator role of rumination. A high level

of rumination enhanced the association between IU and depression symptoms. In addition, both high

and low levels of rumination strengthened the relation between IU and anxiety symptoms. Results

from structural equation modeling analyses indicated that rumination fully mediated the relation

between IU and depression symptoms, but only partially mediated the association between IU and

anxiety symptoms. Conclusions: The results supported rumination as a moderator and mediator in the

association between IU and depression and anxiety symptoms. Future research and practical

implications are discussed. & 2011 Wiley Periodicals, Inc. J Clin Psychol 67:12201239, 2011.

Keywords: intolerance of uncertainty; rumination; moderation; mediation; depression; anxiety

Feelings of uncertainty can be experienced in different stages and domains of life. For

example, college students might be uncertain of future goals, career choices, and romantic

partners. Uncertainty can be overwhelming for individuals and can become a source of stress,

anxiety, and negative mood, especially for those who are intolerant of uncertainty. Individuals

who cannot tolerate uncertainty are likely to find the inevitability of ambiguity in life

unbearable and stressful. Intolerance of uncertainty (IU) is defined as the tendency to react

negatively on an emotional, cognitive, and behavioral level to uncertain situations and events

(Dugas, Buhr, & Ladouceur, 2004). That is, individuals who are intolerant of uncertainty tend

to find uncertain situations upsetting, believe uncertainty is negative and should be avoided,

and have trouble functioning in uncertain situations (Buhr & Dugas, 2002). IU is considered

as a cognitive bias that influences how a person perceives, interprets, and responds to

uncertain situations (Buhr & Dugas, 2002; Dugas, Schwartz, & Francis, 2004). Research has

shown that individuals with high levels of IU were more likely to impose a more threatening

interpretation on ambiguous information than those with low levels of IU (Dugas et al., 2005).

IU is thus considered maladaptive (Buhr & Dugas, 2006) and it can result in negative

emotional outcomes. Empirical studies have demonstrated that IU was positively associated

with depression symptoms (Dugas et al., 2004; Norton, Sexton, Walker, & Norton, 2005) and

anxiety symptoms (Buhr & Dugas, 2002).

IU and Rumination

Rumination is broadly defined as experiencing intrusive or recursive thoughts (e.g., Nolen-

Hoeksema, 1991). It has been viewed as thinking repetitively and passively about negative

This research was initiated while the first author was affiliated with the Psychology Department, IowaState University. The authors thank Zlatan Krizan and Chih-Yuan Weng for their insightful comments onthis paper.

Correspondence concerning this article should be addressed to: Kelly Yu-Hsin Liao, University ofMissouri - St. Louis. Division of Counseling and Family Therapy, College of Education, 413 MarillacHall, 1 University Blvd. St. Louis, MO, 63146; e-mail: [email protected]


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emotions (Nolen-Hoeksema, 2000; Ward, Lyubomirsky, & Nolen-Hoeksema, 2003).

Rumination is also viewed as a form of self-focus or self-attention that involves recurrent

thinking about the self, prompted by not only negative mood but also perceived threats, losses,

or injustices to the self (Trapnell & Campbell, 1999). It can be conceptualized as an emotional

regulation strategy wherein people ruminate to cope with the distress stemming from stressful

life events or losses (Gross, 1999; Pyszczynski & Greenberg, 1987; Spasojevic & Alloy, 2001).However, when one ruminates in response to distress, the recurrent thoughts tend to be self-

relevant negative thoughts (Papageorgiou & Wells, 2001). In addition, rumination does not

motivate individuals to take action to minimize their distress (Lyubomirsky & Nolen-

Hoeksema, 1993); instead, its repetitive nature worsens individuals level of stress by creating a

vicious cycle between negative thoughts and mood (e.g., Lyubomirsky & Tkach, 2004).

When individuals experience a sense of uncertainty, they might engage in rumination.

Watkins and Baracaia (2001) investigated why people ruminate despite its negative

consequences and found that many individuals believed rumination could improve under-

standing, facilitate insight, and increase problem-solving ability. This suggests that uncertainty

might prompt individuals to ruminate because they think that it might minimize ambiguities

and feelings of uncertainty. In addition, Nolen-Hoeksema (2000) found that the content ofindividuals ruminations reflected uncertainty about whether they will be able to control their

current situations. Also, Ward et al. (2003) argued that uncertainty might be aversive to

ruminators (i.e., individuals who tend to ruminate), who then engage in rumination rather

than taking an action to lessen the negative feelings associated with uncertainty. Moreover,

these authors maintained that feelings of uncertainty would keep individuals locked in

continued rumination, perhaps as a way to manage these uncertain feelings. Empirically,

Ward et al. (2003) demonstrated that ruminators are likely to feel uncertain in ambiguous

situations and these feelings of uncertainty are likely to perpetuate ruminative thoughts. Thus,

uncertainty is linked with the initiation of rumination episodes, the maintenance of these

episodes, and the tendency to ruminate as a response style. In the literature, IU has been

shown to correlate positively with rumination (Gervais & Dugas, 2006).

Rumination and Symptoms of Depression and Anxiety

When individuals engage in prolonged rumination, they might be at risk of experiencing poor

psychological outcomes such as depression symptoms. Rumination is a process of thinking

perserveratively about ones distress that leads individuals to remain fixated on their problems

(Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008). In addition to its repetitive focus on

distress, rumination appears to prompt people to think negatively. For example, rumination is

reported to contribute to increased recall of negative memories, negative evaluations of the

present, and pessimistic predictions about the future (e.g., Lyubomirsky, Caldwell, & Nolen-

Hoeksema, 1998; Lyubomirsky & Nolen-Hoeksema, 1995; Teasdale, 1983). Rumination alsonegatively biases ones thoughts through maladaptive cognitive mechanisms including

negative attributional styles, hopelessness, and self-criticism (Robinson & Alloy, 2003;

Spasojevic & Alloy, 2001). The negative bias of rumination is likely to lead people to blame

themselves for their current problems, be more self-critical, and overgeneralize from their

failures. Moreover, experimental studies have shown that rumination can lead people to

appraise their problems as unsolvable (Lyubomirsky et al., 1999) and to come up with poor

problem solutions. This might generate greater stressful events in ones life. With these

negative consequences of rumination on thoughts and problem solving, it is not surprising that

rumination is associated with depression symptoms. Empirically, several naturalistic studies

have shown that rumination is associated with prolonged negative mood (e.g., Nolen-

Hoeksema & Davis, 1999). One longitudinal study also demonstrated that ruminationpredicted depression over a 9-week period (Nolen-Hoeksema & Morrow, 1991).

Rumination is also associated with anxiety symptoms Ruminative thoughts mostly reflect

1221Intolerance of Uncertainty


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Because anxiety can stem from feeling out of control as well as thinking about

uncontrollability of events (e.g., Alloy, Kelly, Mineka, & Clements, 1990; Barlow, 1988),

one might expect rumination to be related to symptoms of anxiety. Individuals also perceive

the act of rumination as uncontrollable (e.g., ruminating about my problems is uncontrollable)

(Papageorgiou & Wells, 2004). Accordingly, engaging in rumination is likely to be associated

with anxious feelings. Research studies have shown that rumination predicted participantsself-report ratings of anxiety (Nolen-Hoeksema, 2000; Watkins, 2004).

Moderation

A moderator is conceptualized as a variable that alters the direction or the strength of the

relation between a predictor and an outcome (Baron & Kenny, 1986; Frazier, Tix, & Barron,

2004; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). In this study, rumination might serve

as a moderator that alters the strength of the associations between IU and symptoms of

depression and anxiety. Robinson and Alloy (2003) provided the evidence that rumination

interacted with a cognitive risk factor/vulnerability to predict prospective depression and

hopelessness. In addition, Ciesla and Roberts (2002) demonstrated that rumination interactedwith a negative cognitive vulnerability to predict changes in the severity of depressive

symptom. A cognitive risk factor/vulnerability refers to a cognitive pattern that shapes and

biases the persons attention and information processing (Riskind & Alloy, 2006; Clark, Beck,

& Alford, 1999) in a direction that increases a persons vulnerability to negative emotion such

as depressed mood. Because IU negatively biases information processing of ambiguous events

(Dugas et al., 2005), it can be considered as a cognitive vulnerability to depression and anxiety

symptoms. Thus, based on previous empirical studies, the current study hypothesized that

rumination would interact with IU to predict depression and anxiety symptoms.

More specifically, individuals who are inclined to ruminate often are not motivated to

conceive solutions to problems. They tend to take a long time to decide on a plan of action and

are inadequate at problem solving (e.g., Lyubomirsky & Nolen-Hoeksema, 1993, 1995;Lyubomirsky et al., 1999; Ward et al., 2003). When individuals with a high level of rumination

face uncertainty, rumination is likely to hinder them from actively confronting the uncertainty

they face, resulting in prolonged feelings of uncertainty and negative mood. Moreover, as

mentioned previously, rumination is associated with decreased social support because friends

of people who tend to ruminate might eventually become tired of or irritated by their repetitive

pessimistic thoughts (Spasojevic , Alloy, Abramson, Maccoon, & Robinson, 2004). When

confronted with uncertainty, individuals with high rumination might feel alone, alienated, and

receive little support and few constructive ideas from others to cope with the uncertainty.

Accordingly, we expected that high levels of rumination would strengthen the associations

between IU and symptoms of depression and anxiety. Conversely, individuals with a low level

of rumination are likely to actively seek information or find solutions to manage and reducethe uncertainty they face. These proactive strategies might increase their level of tolerance for

uncertain situations, thereby lessening the association between IU and emotional distress.

Therefore, it was expected that a low level of rumination would buffer the associations

between IU and symptoms of depression and anxiety.

Mediation

Conceptually, a mediator is defined as a variable or a mechanism (e.g., rumination) that explains

the process of how a predictor (e.g., IU) is associated with an outcome variable (e.g., depression

symptoms; Baron & Kenny, 1986; Frazier et al., 2004; Kraemer et al., 2001). Spasojevic and

Alloy (2001) theorized rumination as a mediator between cognitive risk factors/vulnerabilitiesand negative psychological outcomes (e.g., depression). Spasojevic and Alloy indicated that

people with cognitive risk factors/vulnerabilities for depression (e g IU self-criticism) are likely

1222 Journal of Clinical Psychology, December 2011


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outcomes. Thus, these authors conceptualized rumination as the underlying link (i.e., mediator)

between cognitive vulnerability (e.g., IU) and adverse psychological outcomes. Other studies

have also confirmed rumination as a mediator between vulnerability factors (e.g., including

neuroticism, self-criticism, neediness, low perceived social support) and depression (Roberts,

Gilboa, & Gotlib, 1998; Nolen-Hoeksema, Parker, & Larson, 1994; Spasojevic & Alloy, 2001).

Based on Spasojevic and Alloys (2001) theoretical framework and the above-mentionedliterature support for the associations among IU, rumination, symptoms of depression, and

anxiety, it is postulated that rumination might be acting as a mediator in the relations between

IU and symptoms of depression and anxiety. It is reasoned that individuals with high levels of

IU might ruminate in the hope of gaining an increased understanding of the situation to

minimize their feelings of uncertainty. However, engaging in rumination to cope with and

manage the stress associated with IU might worsen it rather than alleviate it (Nolen-Hoeksema,

1991), which in turn is associated with greater depressive and anxious mood. Thus, IU might be

linked to symptoms of depression and anxiety through its association with rumination.

Current Study

In summary, the purpose of the present study was to examine whether rumination serves as a

moderator, as a mediator, or as both in the relations between IU and symptoms of depression

and anxiety. First, we hypothesized that the relations between IU and symptoms of depression

and anxiety would vary at different levels of rumination. That is, the association between IU

and symptoms of depression and anxiety at high levels of rumination would be stronger than

that at low levels of rumination. Second, it was expected that rumination would mediate the

relations between IU and symptoms of depression and anxiety.

METHOD

ParticipantsData were collected from 332 students enrolled in psychology classes in a large Midwest

university. There were 160 men (48%), 171 women (52%), and one person who did not indicate

gender (0.3%). Their ages ranged from 18 to 42 (mean [M]519.88, standard deviation

[SD]52.61). Half of participants were 163 freshmen (49%), followed by 80 sophomores (24%),

45 juniors (14%), and 42 seniors (13%). Regarding participants ethnicity, 87% were Caucasian,

5% were Asian Americans, 1% were African Americans, 1% were Hispanic Americans, 1%

were Multi-racial Americans, 3% were international students, and 1% reported Other for

their ethnicity. In terms of marital status, 195 (59%) were single, 118 (36%) were in a committed

relationship, 7 (2%) were married, and 12 (4%) indicated Other for their marital status.

Instruments

Intolerance of uncertainty. The construct of intolerance of uncertainty was measuredby the Intolerance of Uncertainty Scale (IUS; Original French version: Freeston, Rhe aume,

Letarte, Dugas, & Ladouceur, 1994; English translation: Buhr & Dugas, 2002). The IUS was

used in the present study to assess emotional, cognitive, and behavioral reactions to

ambiguous situations, the implications of being uncertain, and attempts to control the future

(Freeston et al.). The scale asks participants to rate how they react to uncertainties in life. The

27-item IUS comprises four subscales: Desire for Predictability, Uncertainty Paralysis,

Uncertainty Distress, and Inflexible Uncertainty Beliefs. Coefficient alphas for desire for

predictability, uncertainty paralysis, uncertainty distress, and inflexible uncertainty belief were

.83, .84, .81, and .70, respectively, in the present study. The coefficient alpha for the total scoreof IUS was.94 in the current study. Construct validity for the subscales has been established,

as follows: desire for predictability was associated with neuroticism; uncertainty paralysis was



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Rumination. Two different rumination scales were used in the current study as twoindicators to measure the latent construct of rumination. The first scale was the Rumination

subscale from the Rumination-Reflection Questionnaire (RRQ; Trapnell & Campbell, 1999).

The RRQ is a 28-item measure comprised of two subscales that assess individuals rumination

and reflection tendencies. Only the Rumination subscale (RRQ-R; 12 items) was used in the

present study. RRQ-R assesses recurrent thinking or rumination about the self, prompted bythreats, losses, or injustices to the self. Participants are asked to indicate their level of

agreement with each of the items. A high score suggests greater ruminative tendencies or the

tendency to pay more attention to the negative aspects of the self. The scales coefficient alpha

was.91 in the current study. The construct validity of the scale was shown by its positive

correlation with neuroticism in college students (Trapnell & Campbell).

The second rumination scale was the Short Response Styles Questionnaire (Short-RSQ;

Nolen-Hoeksema & Morrow, 1991). Short-RSQ is a 10 item scale designed to measure

individuals responses to depressed mood that are self-focused (e.g., a sample item states Why

cant I get going?) and symptom-focused (e.g., I think about how hard it is to concentrate).

Participants are asked to answer each question based on what they generally do when they are

feeling depressed, down, or sad. A high score on the scale reflects greater ruminativetendencies. In the present study, the coefficient alpha of the scale was.91. The predictive

validity of the scale was based on a positive association with depression among college

students (Nolen-Hoeksema & Morrow, 1991). The RRQ and the Short-RSQ were used as

indicators because they both tap into repetitive thoughts and recurrent self-focused thinking

found in the construct of rumination.

Depression. Two depression scales were used as two indicators for measuring the latentconstruct of depression. The first scale was the Depression subscale from the Depression,

Anxiety, and Stress Scale-short version (DASS-D-short version; Lovibond & Lovibond, 1995).

The Depression subscale (DASS-D-short version; seven items) assesses the individuals level of

depressive symptoms during the past week. A high score indicates more depressive symptoms.The coefficient alpha was .88 in the present study. Criterion validity of the DASS-D-short

version was supported by a positive correlation with another measure of depression in college

students (Antony, Bieling, Cox, Enns, & Swinson, 1998).

The second depression scale was the short version of the Center for Epidemiological

Studies-Depression Scale (CES-D-short version; Kohout, Berkman, Evans, & Cornoni-

Huntley, 1993), which comprised 11 items and assessed the frequency of depressive symptoms

the participants experienced during the past week. A high score indicates greater depressive

symptoms. The coefficient alpha was.85 in the current study. Wei, Russell, Mallinckrodt, and

Vogel (2007) provided evidence for the scales construct validity by demonstrating positive

associations with attachment avoidance and anxiety for college students.

Anxiety. Two scales were employed as two indicators to measure the latent construct ofanxiety. The first scale was the Anxiety subscale from the Depression, Anxiety, and Stress

Scale-short form (DASS-A-short version; Lovibond & Lovibond, 1995). The Anxiety subscale

(DASS-A-short form; seven items) measures the level of anxiety participants experienced.

Participants are asked to rate the extent to which each anxiety symptom applies to them in the

last week. A high score suggests higher level of anxiety. The coefficient alpha of the short

version was .74 in the present study. Wei, Vogel, Ku, and Zakalik (2005) provided evidence for

the concurrent validity of the scale by reporting positive correlations with interpersonal

problems and loneliness in college students.

The second anxiety scale was the Self-Rating Anxiety Scale (SRAS; Zung, 1971). The SRAS

contains 20-items that represent commonly found anxiety symptoms (Zung). Sample itemsinclude I feel more nervous and anxious than usual and I get feelings of numbness and

tingling in my fingers toes Participants are asked to respond to the items according to how



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evaluation, and depression (Olatunji, Deacon, Abramowitz, & Tolin, 2006) in a college

student sample.

Procedure

Psychology undergraduate students were told that the purpose of the study was to examine

mood regulation and reactions to uncertainty. Interested students would sign up for the study

and participate in the study at a designated classroom. These students were asked to read and

sign the informed consent document before they filled out paper copies of the questionnaire,

which took them approximately 30-45 minutes to complete. At the end of the study, they were

debriefed about the purpose of the study and rewarded with an extra course credit for their

participation.

RESULTS

Preliminary AnalysesMeans, standard deviations, and zero-order correlations for the studys variables are shown in

Table 1. All of the observed variables were significantly correlated with each other. Further, a

Mardia multivariate normality test (see Bollen, 1989) was conducted and the result indicated

that the data did not meet the assumption of multivariate normality, w2 (2, N 5 332) 5

496.16, p o.001. Therefore, the scaled chi-square statistics (Satorra & Bentler, 1988), which

adjust the influence of non-normality, were reported.

Data Analytic Strategy

The data analytic strategy involved first examining the hypothesized moderator role ofrumination between IU and symptoms of depression and anxiety. A hierarchical regression

(Baron & Kenny, 1986; Cohen, Cohen, West, & Aiken, 2003) was conducted using SPSS 13. If

a moderation effect existed, simple effect analyses were conducted to test the significant levels

of simple slopes.

Table 1Means, Standard Deviations, and Correlations among the Variables

Variable M SD 2 3 4 5 6 7 8 9 10 11

1. IUS 2.10 .69 .84 .89 .89 .81 .39 .54 .42 .49 .41 .49

2. DP 2.44 .79 .65 .60 .57 .34 .38 .26 .30 .29 .323. UP 1.96 .77 .81 .65 .35 .55 .45 .51 .41 .46

4. UD 1.95 .81 .70 .40 .55 .44 .53 .41 .53

5. IUB 1.99 .76 .26 .41 .33 .41 .28 .40

6. RRQ-R 3.18 .79 .54 .38 .44 .29 .39

7. Short-RSQ 2.07 .67 .62 .64 .41 .57

8. DASS-D-Short .54 .55 .71 .53 .54

9. CES-D-Short 1.74 .55 .52 .66

10. DASS-A-Short .43 .42 .63

11. SRAS 1.74 .42

Note: M5mean; SD5 standard deviation; IUS5 Intolerance of Uncertainty Scale; DP5Desire for

Predictability subscale; UP5Uncertainty Paralysis subscale; UD5Uncertainty Distress subscale;

IUB5 Inflexible Uncertainty Beliefs subscale; RRQ-R5 the Rumination Scale from the Rumination-

Reflection Questionnaire; Short-RSQ5 the Short Response Styles Questionnaire; DASS-D-Short5 the

D i b l f D i A i t d St S l h t i CES D Sh t C t f



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We then tested the hypothesized mediator role of rumination between IU and symptoms of

depression and anxiety using structural equation modeling (SEM) in LISREL program

(Version 8.80; Jo reskog, & So rbom, 2006). Following the SEM framework, we tested the

measurement model for an acceptable fit to the data through a confirmatory factor analysis

(Anderson & Gerbing, 1988). When a satisfactory fitting measurement model was obtained,

the structural model was tested for the mediation hypotheses (Bollen, 1989). Next, followingShrout and Bolgers (2002) suggestions, a bootstrapping method was used to test the

significance level of the indirect (mediated) effects.

Test for Moderation

To test the moderating role of rumination (see Panel A in Figure 1), we followed Aiken and

Wests (1991) suggestion by standardizing the predictors (including moderators) before the

analysis to control for possible multicollinearitiy among predictors and moderators. Following

this, IU was standardized. Because there are multiple scales for the construct of rumination, a

composite score of rumination was created by summing the standardized scores of RRQ-R

and Short-RSQ. Similarly, because of the multiple scales for depression and anxiety, acomposite score of depression was created by summing the standardized scores of the CES-D-

Short version and DASS-D-Short form; a composite score of anxiety was created by summing

the standardized scores of the DASS-A-Short form and SRAS. The interaction term was

created by multiplying the predictor (IU) and the moderator (rumination). The interaction

term is thus IU Rumination. Moderation effect exists when the regression coefficient for

the interaction variable (e.g., IU Rumination) in predicting the dependent variable (e.g.,

depression) is significant (Baron & Kenny, 1986).

Depression as a dependent variable. In Step 1, IU and the composite rumination wereentered into the first block of regression (see Table 2 and Panel A in Figure 1). The result

indicated that IU and rumination accounted for 44% of the variance in depression, F(2, 329)5 129.99, p o.001. The main effects of IU and rumination were significant. In Step 2, the



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interaction variable (IURumination) was entered into the second block of regression. There

was a moderation effect because the regression coefficient for the interaction of IU and

rumination was significant in predicting depression (po.001, see Table 2). Moreover, the two-way interaction significantly added incremental variance in depression over and beyond the

main effects, DR25 .03, DF (1, 328)516.92, po.001. This suggests that the relation between

IU and depression symptoms was moderated by the level of rumination.

Based on Cohen et al.s (2003) recommendation, we used one standard deviation below and

above the mean for the variables to plot the nature of the above two-way interaction. We also

tested the statistical significance for each of the simple slopes (see Aiken & West, 1991; Cohen

et al., 2003; Frazier et al., 2004). As seen in Figure 2 (Panel A), the results from a simple effect

analysis supported the moderation hypotheses for depression symptoms. It indicated that the

relation between IU and depression symptoms was significant at the high level of rumination

(b5 .49, X5 .27, po.001, sr25 .05). However, at the low level of rumination, the association

between IU and depression symptoms was not statistically significant ( b5 .16, X5 .09, p5 .14,sr25 .00).

Anxiety as a dependent variable. We repeated the above procedure for anxiety. Thus,in Step 1, IU and the composite rumination were entered into the first block of the regression

equation. Results showed that IU and rumination accounted for 34% of the variance in

anxiety, F (2, 329)584.71, po.001. The main effects of rumination and IU were both

significant. Next, the interaction variable (IURumination) was entered into the second

block of regression. A moderation effect was found; the regression coefficient for the

interaction of IU and Rumination was significant in predicting anxiety (po.05, see Table 2).

Moreover, the two-way interaction significantly added incremental variance in anxiety over

and beyond the main effect, DR2

5 .01, DF(1, 328)54.01, p5 .05, suggesting that ruminationmoderated the relation between IU and anxiety.

Because of the presence of a moderation effect a simple effect analysis was conducted

Table 2A Hierarchical Multiple Regression Analysis Testing Moderating Effects of Intolerance ofUncertainty and Rumination on Depression and Anxiety Symptoms

Variable B SE B b sr2

Depression symptoms

Step 1

Intolerance of uncertainty 0.4 0.09 .21 0.03

Rumination 0.55 0.05 .52 0.19

Step 2

Intolerance of uncertainty 0.32 0.09 0.18 0.02

Rumination 0.57 0.05 .54 0.21

Intolerance of uncertainty rumination 0.17 0.04 .17 0.03

Anxiety symptoms

Step 1

Intolerance of uncertainty 0.56 0.1 .31 0.07

Rumination 0.37 0.06 .36 0.09

Step 2Intolerance of uncertainty 0.52 0.1 .29 0.06

Rumination 0.38 0.06 .37 0.09

Intolerance of uncertainty rumination 0.09 0.04 .09 0.01

Note: SE5 standard error.

N5332.po.05. po.01. po.001.



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results supported the moderation hypotheses for anxiety. Specifically, the hypothesis that high

rumination would strengthen the association between IU and anxiety was supported. Low

levels of rumination still strengthened the association between IU and anxiety; however, the

strength of the association at low rumination was significantly weaker than that at high

rumination.

Testing Mediated Structural Models

Measurement model. The maximum likelihood method in LISREL (Version 8.80;Jo reskog & So rbom, 2006) was used to evaluate the fit of the measurement model. Two fit

indices were employed to determine the goodness of fit for the model (Hu & Bentler, 1999): the

comparative fit index (CFI; values of.95 or greater indicate that the model adequately fits the

data) and the root mean square error approximation (RMSEA; values of.06 or less indicate

that the model adequately fits the data). The corrected scaled chi-square difference test

(Satorra & Bentler, 2001) was used to compare the nested models.

The results of the measurement model suggested a good fit to the data, scaled w2 (29,

N5332)570.38, po.001, CFI5 .99, RMSEA5 .06 (90% confidence interval [CI], .04.08).All of the loadings of the 10 observed variables on the latent variables were statistically

significant (po 001; see Table 3) This result indicated each measure in the measurement

Figure 2. Relationships between IU and Depression Symptoms at High and Low Levels of Rumination(Panel A). Relationships between IU and Anxiety Symptoms at High and Low Levels of Rumination (Panel B).



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Structural equation model. Holmbeck (1997) has recommended using three steps to teststructural mediated models in SEM. The first step is to test the significance level of the direct

effects of independent variables (i.e., IU) on the dependent variables (i.e., symptoms of

depression and anxiety). If these direct effects are significant, we can then test the mediation

effects. The second step is to examine the model fit of the partially mediated structural model

(i.e., our hypothesized model; Panel B in Figure 1). The third step is to compare our

hypothesized partially mediated model with different fully mediated models to see which

model fits the data best.

With regard to the first step, we found significant direct effects of IU on depression andanxiety symptoms. Specifically, the path from IU to depression (X5 .61, Z5 6.86, po.001)

and the path from IU to anxiety (X5 .61, Z57.02, po.001) were significant. In the second

Table 3Factor Loadings of the Measurement Model

Variable and measure Unstandardized factor loading SE Z Standardized factor loading

Intolerance of uncertainty

DP 3.84 .26 15.36 .69

UP 4.14 .19 21.99 .89

UD 3.70 .16 22.63 .91

IUB 2.31 .15 15.04 .76

Rumination

RRQ-R 5.90 .49 12.02 .60

Short-RSQ 6.02 .34 17.84 .90

Depression

DASS-D-short version 3.09 .23 13.29 .80

CES-D-short version 5.42 .34 16.00 .89

Anxiety

DASS-A-short version 2.13 .20 10.73 .72

SRAS 7.32 .53 13.78 .88

Note: SE5 standard error; DP5Desire for Predictability subscale; UP5Uncertainty Paralysis subscale;

UD5Uncertainty Distress subscale; IUB5 Inflexible Uncertainty Beliefs subscale; RRQ-R5 the

Rumination subscale from the Rumination-Reflection Questionnaire; Short-RSQ5 the Short Response

Styles Questionnaire; DASS-D-short version5 the Depression subscale of Depression, Anxiety, and Stress

Scale-short form; CES-D-short version5 the short version of the Center for Epidemiological Studies-

Depression Scale; DASS-A-short version5 the Anxiety subscale of Depression, Anxiety, and Stress Scale-

short version; SRAS5 the Self-Rating Anxiety Scale.

N5332.po.001.

Table 4Correlations Among Latent Variables for the Measurement Model

Latent variable 2 3 4

1. Intolerance of Uncertainty .66 .62 .61

2. Rumination .82 .70

3. Depression .82

4. Anxiety

Note: N5332.

po

.001.



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pAnalysesoftheMagnitudeandStatisticalSignificanceofIndirectEffects

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12/21

compared the hypothesized partially mediated model with different fully mediated models (see

Models B-D in Table 5). As described above, the corrected scaled chi-square difference test

(Satorra & Bentler, 2001) was used to compare these nested models.

The first fully mediated model (i.e., a fully mediated model for both depression and anxiety

symptoms; Model B) constrained two direct paths to zero (i.e., the paths from IU to

depression symptoms and from IU to anxiety symptoms). The results indicated that Model Bprovided an acceptable fit to the data (see Table 5). However, the result of the scaled chi-

square difference test showed a significant difference between Model A and Model B, D scaled

w2 (2, N5332)57.37, p5 .03. This implies that the two direct paths still contribute to the

model and need to be retained in the model. Thus, Model A with these two direct paths was a

better model compared with Model B.

The second model (Model C) is a fully mediated model for anxiety symptoms but a partially

mediated model for depression symptoms. That is, in Model C, one direct path (i.e., the path

from IU to anxiety symptoms) was constrained to zero. The result indicated that Model C

provided an acceptable fit for the data. The scaled chi-square difference test showed that

Model A was significantly different from Model C, D scaled w2 (1, N5332)57.70, p5 .006.

Again, this suggests that the direct path from IU to anxiety symptoms still contributes to themodel and needs to be kept in the model. Therefore, Model A with this direct path was a better

fit model.

The third model (Model D) is a fully mediated model for depression symptoms but a

partially mediated model for anxiety symptoms. In Model D, one direct path (i.e., the path

from IU to depression symptoms) was constrained to zero. The result indicated that Model D

also provided an acceptable fit for the data. The scaled chi-square difference test showed that

Model A was not significantly different from Model D, D scaled w2 (1, N5332)51.93,

p5 .16. Based on the parsimony principle, Model D without this direct path was a better fit

model. Therefore, Model D (see Figure 3 and Table 5; a fully mediated model for depression

symptoms but a partially mediated model for anxiety symptoms) was the best fit model and

was used in the following bootstrap procedure for testing the significance levels of indirecteffects.

Before testing the significance levels of indirect effects, we examined three alternative

models in addition to the hypothesized model. The first alternative model consisted of

rumination as the predictor, IU as the mediator, and depression and anxiety symptoms as the

dependent variables. The LISREL results indicated that the path from IU to depression was

not significant (X5 .13, Z51.36, p5 .18); therefore, there was not a significant mediation (or

indirect) effect from rumination through IU to depression. Next, we examined a second

alternative model in which depression and anxiety symptoms were the predictors, IU was the

mediator, and rumination was the dependent variable. Results from LISREL showed that in

this second model, the paths from depression to IU was significant (X5 .34, Z5 2.36, p5 .03),

the path from anxiety to IU was significant (X5 .33, Z52.27, p5 .03), and the path from IUto rumination was significant (X5 .26, Z53.67, po.01). This suggests that there was

mediation effect from depression and anxiety through IU to rumination. Future studies might

further explore this model. Last, we tested the third alternative model in which the depression



13/21

and anxiety symptoms were the predictors, rumination was the mediator, and IU was the

dependent variable. The results indicated that the path from anxiety to rumination was not

significant (X5 .08, Z5 .69, p5 .50), indicating that there was no mediation effect from

anxiety through rumination to IU.

Significance levels of indirect effects. In the literature on testing mediation effects, thebootstrap procedure was recommended to test the significance level of the indirect effects

(Mallinckrodt, Abraham, Wei, & Russell, 2006; Shrout & Bolger, 2002). The results from the

bootstrap procedure indicated that the indirect effect from IU through rumination to

depression symptoms was significant, b 5 .47 (95% CI, .36.64), b5 .70 .855 .60. The

identical procedure was used for testing the indirect effect from IU through rumination to

anxiety. The result was also significant, b5 .23 (95% CI, .15.34), b5 .70 .605 .42.

Moreover, in the final best model (see Figure 3), about 48% of variance in rumination was

explained by IU; 72% of the variance in depression and 55% of variance in anxiety were

explained by rumination and/or IU.

Post hoc analysis. A previous study demonstrated that women ruminated more abouttheir emotions than men did (Nolen-Hoeksema, Morrow, & Fredrickson, 1993). In addition,

Butler and Nolen-Hoeksema (1994) found that women were more likely than men to ruminate

in response to naturally occurring negative mood and that womens tendency to ruminate

contributed to more depressive symptoms in women compared to men. Because of the sex

differences in rumination, post hoc analysis was conducted to explore whether the moderation

effect of rumination would be more salient for women than for men. To test this, we examined

a three-way interaction of IURuminationSex. The results indicated a significant three-

way interaction, b5 .17, b5 .32, p5 .02, sr25 .01, for depression but not for anxiety

symptoms (b5.04, b5.08, p5 .59, sr25 .00). Next, a simple effect analysis revealed only

one significant finding; the relation between IU and depression symptoms was significant

among women with high levels of rumination (b5 .54, b5 .29, po.001, sr25 .04). There were

no significant associations between IU and depression symptoms for women with a low level

of rumination (b5 .001, b5 .00, p5 .99, sr25 .00) or men with either a high (b5 .27,

b5 .15, p5 .07, sr25 .005) or a low level of rumination (b5 .23, b5 .12, p5 .12,

sr25 .004).

DISCUSSION

Two significant findings were found in this study that can extend the current literature. First,

the results confirmed our first hypothesis of rumination as a moderator in the association

between IU and depression symptoms. Specifically, a high level of rumination enhanced the

association between IU and depression symptoms. Perhaps, those with high rumination have

negatively biased thoughts (e.g., Nolen-Hoeksema, 1991) as well as pessimistic thoughts andpredictions (Lyubomirsky & Nolen-Hoeksema, 1995) about uncertain events. These

individuals might also have quick access to negative memories (Lyubomirsky et al., 1998;

McFarland & Buehler, 1998) associated with uncertain situations. Moreover, rumination

involves perseverative focus on ones negative emotion, which might decrease the likelihood of

generating potential solutions or alternative ways of coping (Davis & Nolen-Hoeksema, 2000)

for uncertain situations. Based on these negative consequences of rumination, perhaps

rumination enhanced the association between IU and depression symptoms through

magnifying the negative aspects of an uncertain situation, maintaining ones distress

associated with uncertainty, and strengthening the belief that negative outcomes will occur

in uncertain situations. Furthermore, individuals with high levels of rumination might not

have social resources (Nolen-Hoeksema & Davis, 1999) to provide them with comfort andhelpful advice when they encounter situations that are uncertain. This might also increase

these individuals vulnerability to the negative impact of IU



14/21

negative mood (Butler & Nolen-Hoeksema, 1994). Our result shows that as women face

situations that are uncertain in nature, high levels of rumination might place women in a more

vulnerable position than men for depression symptoms. This result underscores the

importance of considering the degree of rumination as a critical dimension in explaining

womens vulnerability to depressive symptoms. Nolen-Hoeksema and Jackson (2001) studied

factors that contribute to sex differences in rumination. They found that women were morelikely than men to report feeling little control over important events in their lives and to

endorse the belief that negative emotions are difficult to control. Perhaps, as women encounter

uncertainty in their lives, in addition to experiencing the stress associated with IU, their

perceived low mastery and difficulty in overcoming negative emotions might also adversely

impact the way they manage uncertainty. These factors might together enhance the association

between IU and depression symptoms among women.

Our results revealed that low rumination buffered the association between IU and

symptoms of depression. This result might help to explain why uncertainty does not place

everyone in a vulnerable position for depression, even though it is aversive to most people.

Ward et al. (2003) reported that when presented with a task fraught with uncertainty,

nonruminators could quickly attend to the task at hand and engage in problem solving. In thecurrent study, instead of spending their time focusing on the stress associated with uncertainty,

thinking about it, and letting it affect their thinking about how to manage the uncertain

situation, individuals with low levels of rumination might actively manage the distress related

to uncertainty by using adaptive coping strategies. For example, individuals with low

rumination might actively seek social support to cope with uncertainty. Because people who

ruminate less have more social resources available to them than people with high levels of

rumination (Spasojevic et al., 2004), they are likely to receive the support they need. The

strategies used by individuals with low rumination might effectively lessen the negative affect

associated with uncertainty, thereby decreasing the strength of the association between IU and

symptoms of depression.

Regarding the hypothesis of rumination as a moderator for anxiety symptoms, this studyfound a significant association between IU and anxiety symptoms for those who were either

high or low on rumination. A previous study has demonstrated that rumination is associated

with reluctance to commit to a plan of action and decreased confidence as well as satisfaction

toward ones self-generated solutions in an ambiguous situation (Ward et al., 2003). This

suggests that rumination might delay ones active coping responses and lessen the likelihood

that one will remain committed to a solution during uncertain circumstances. As a result,

rumination might maintain or increase the level of uncertainty. Moreover, because ruminative

thinking has been found to impair problem solving (Lyubomirsky, Kasri, & Zehm, 2003), it

might prolong ones preoccupation with the unresolved problems and maintain a high level of

uncertainty of a given situation. Thus, high rumination might increase the association

between IU and anxiety through aggravating the distress associated with uncertainty.However, it is important to note that although both high and low levels of rumination

enhanced the association between IU and anxiety, the magnitude of the slope for low levels of

rumination (b5 .43, X5 .24, po.001) was significantly smaller than that for high levels of

rumination (b5 .61, X5 .34, po.001). This suggests that those with low rumination might be

more willing than those with high rumination to actively cope with uncertainty and to accept

uncertainties in life as inevitable rather than ruminating about them, thus resulting in less

anxiety.

The second significant result in the study was the finding that rumination also acted as a

mediator. Thus, the studys second research hypothesis was supported. Specifically, the results

showed that rumination completely mediated the association between IU and depression

symptoms and partially mediated the association between IU and anxiety symptoms.Theoretically, the studys findings provide support for Spasojevic and Alloys (2001)

conceptual framework of rumination as a mediator linking cognitive vulnerability and



15/21

The study advances the literature on IU by identifying IU as a cognitive vulnerability for

depression and anxiety symptoms through the mechanism of rumination.

The current finding of rumination as a mediator indicates that individuals with high levels

of IU tend to ruminate on distress, which in turn is associated with greater symptoms of

depression and anxiety. Rumination thus appears to be a maladaptive coping strategy for

managing the distress associated with IU. In particular, rumination appears to be a passivecoping strategy that refers to attempts to escape or disengage from the stressor (Billings &

Moos, 1984). Passive coping is considered maladaptive especially in the long run as it prevents

individuals from dealing with the situation that causes distress (Nolen-Hoeksema, Wisco, &

Lyubomirsky, 2008). Rumination is positively related to suppression or avoidance of

distressing feelings and thoughts (Moulds, Kandris, Starr, & Wong, 2007; Nolen-Hoeksema &

Morrow, 1991; Wenzlaff & Luxton, 2003), suggesting rumination constitutes a form of passing

coping. Marroquin, Fontes, Scilletta, and Miranda (2010) found a positive association

between rumination and passive coping strategy. Moreover, they demonstrated that it is the

passive nature of rumination (i.e., the brooding component of rumination) characterized by

repetitive processing of negative content that links rumination to symptoms of depression

(Marroquin et al.). In the current study, IU might have resulted in negative outcomes, (e.g.,symptoms of depression and anxiety) through ruminations passive focus on negative

experience, which prolongs, instead of actively manages, the stress related to IU.

Perhaps, individuals high in IU think rumination might help them understand their feelings

better, gain insights, and find solutions to the uncertain situations they face (Watkins &

Baracaia, 2001). Unfortunately, as mentioned above, rumination is a passive coping strategy

that involves avoidance of problems or stressors. It is also associated with a weak problem-

solving orientation, poor decision making, and high levels of mental and behavioral

disengagement (e.g., Lyubomirsky et al., 1999). As such, during uncertain situations,

rumination might inhibit individuals from using instrumental behaviors, which might assist

them to acquire a sense of control and in turn shield them from negative emotions in these

situations (Nolen-Hoeksema, 1991; Sarin, Abela, & Auerbach, 2005). As a result, theseindividuals might be more vulnerable to depressed mood.

Several limitations can be found in the present study. The sample of the study consisted of

nonclinical participants. Thus, it is not known whether the current findings can be generalized to

clinical samples. Although the reliance on self-report measures for the studys variables might be

construed as another limitation of the present study, self-report measure of rumination is an

appropriate assessment of individuals perceptions of their own tendency to ruminate in response

to negative mood. Moreover, the study comprises mostly Caucasian participants, and thus it is

unclear whether the current results can be generalized to other ethnic populations.

The current studys findings point to some future research directions. First of all, some

theorists proposed that rumination comprises two factors; brooding and reflection (Trapnell &

Campbell, 1999; Treynor, Gonzalez, & Nolen-Hoeksema, 2003). A longitudinal study byTreynor et al. (2003) found that the reflection factor is associated with decreased depression

over time, while brooding is associated with increased depression. Future studies might

investigate the unique components of rumination and examine which of them should be

strengthened and which of them should be weakened to alleviate stress for individuals who are

intolerant of uncertainty. Second, the finding that rumination only partially mediated the

relation between IU and anxiety suggests that other mediators need to be explored in this

association. One such mediator might be the concept of mindfulness, which refers to paying

attention in a particular way: on purpose, in the present moment, and non-judgmentally

(Kabat-Zinn, 1994, p.4). The nonjudgmental acceptance feature of mindfulness allows one to

observe cognitions, emotions, or perceptions entering ones mind without evaluating them as

good or bad or engage in elaborative processing such as rumination (Baer, 2003). Mindfulnesshas been suggested as a way to counter or interfere with rumination (Segal, Williams, &

Teasdale 2002; Teasdale Segal & Williams 1995) In addition mindfulness allows one to



16/21

temporary events in the mind. The present focus of mindfulness also disengages individuals

from thinking about future uncertainties. Thus, future research might explore how IU is

related to this potential mediator (i.e., mindfulness) and how this in turn is associated with

symptoms of anxiety. Last, it is important to note that the correlational nature of our study

does not allow us to infer causality. Future studies might conduct experimental research to

manipulate IU (Ladouceur, Gosselin, & Dugas, 2000) and rumination (e.g., Lyubomirsky &Nolen-Hoeksema, 1995) to determine causal relationships among the variables. Moreover, the

current study found IU to be a predictor of rumination. Future study using longitudinal

designs could focus on examining IUs potential role in the etiology of rumination.

The current results might imply at least two practical implications. First, as we mentioned

earlier, college students might experience uncertainty in several life domains (e.g., deciding on

a future career or searching for a romantic partner). Those who are intolerant of uncertainty

are likely to experience depression and anxiety symptoms, which are two of the main

presenting concerns among college students who seek help from counseling services (Benton,

Robertson, Tseng, Newton, & Benton, 2003). It is likely that these students are aware of these

symptoms; however, they might have little understanding of the factors associated with these

symptoms. Those who work with college students might help increase their awareness aboutthe role of rumination in the association between IU and these negative psychological

symptoms. Furthermore, in the rumination literature, researchers consistently found that

individuals who participate in benign distracting responses are less likely to experience

depressed mood compared with those who engage in ruminative responses (e.g., Lyubomirsky

et al., 1998). Therefore, students who ruminate frequently might be suggested to engage in

benign distracting activities. Second, those who work with college students might educate

them that when faced with uncertain situations, high frequency of rumination might actually

enhance their depressed mood and anxiety symptoms. Because rumination is a passive form of

coping, replacing it with more active problem-solving strategies (e.g., planning ahead of time,

seeking clarifications, and gathering information) to cope with uncertainty might be useful

(Greco & Roger, 2001) in lessening depressed mood and anxiety.Moreover, the finding that women with high rumination reported more symptoms of

depression suggests that womens proneness to ruminate when facing lifes uncertainties

deserves attention. This also stresses the importance of educating women regarding the negative

psychological outcomes of engaging in rumination to cope with uncertainty. Perhaps, it might

be beneficial if women can focus their attention on aspects of their life that they can control.

This might increase their sense of mastery and guide them to different ways of managing

uncertainty so that they free themselves from rumination (Nolen-Hoeksema et al., 1999).

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