THE RELATIONSHIP AMONG CAUSAL UNCERTAINTY, REASSURANCE SEEKING, AND DYSPHORIA

Transcription

1 JACOBSON CAUSAL UNCERTAINTY Journal of Social and Clinical Psychology, Vol. 26, No. 8, 2007, pp THE RELATIONSHIP AMONG CAUSAL UNCERTAINTY, REASSURANCE SEEKING, AND DYSPHORIA JILL A. JACOBSON Queen s University Two hypotheses have been proposed for the relationship among causal uncertainty, reassurance seeking, and dysphoria. According to one prediction, reassurance seeking should mediate the relationship between causal uncertainty and dysphoria, but according to the other prediction, causal uncertainty is expected to mediate the relationship between reassurance seeking and dysphoria. One study has investigated the relationship between all three constructs, but it assessed the scales only concurrently. In the current study, participants completed measures of the three constructs at two sessions held 4 to 8 weeks apart. Causal uncertainty was found to be a mediator of the longitudinal relationship between reassurance seeking and depressive symptoms. However, reassurance seeking did not mediate the longitudinal relationship between causal uncertainty and depressive symptoms. Depression has a high relapse rate (Gotlib & Hammen, 2002), suggesting that specific risk factors exist, and researchers typically have examined biological as well as psychological or situational factors that may make people more susceptible to this disorder. Although all of these factors are important, Joiner, Coyne, and Blalock (1999) have called for greater focus on the interpersonal context of depression because social factors should be more amenable to change than genetic and some other factors. Jill A. Jacobson, Department of Psychology. This research was supported in part by a Queen s University Advisory Research Committee grant and a Canadian Foundation for Innovation grant awarded to Jill A. Jacobson. I would like to thank Nina Rytwinski, Jorden Cummings, and Jennifer Passey for their assistance with the data collection. Correspondence concerning this article should be addressed to Jill A. Jacobson, Department of Psychology, Queen s University, 318 Craine Hall, Kingston, Ontario, Canada K7L 3N6. jill.jacobson@queensu.ca 922

2 CAUSAL UNCERTAINTY 923 In addition, because dysphoric individuals are highly likely to become clinically depressed (e.g., Fergusson, Horwood, Ridder, & Beautrais, 2005; Horwath, Johnson, Klerman, & Weissman, 1992; Pine, Cohen, Cohen, & Brook, 1999), exploring the interpersonal factors with individuals who have subclinical levels of depressive symptoms may be particularly important. Indeed, if we can better understand the social phenomena that exacerbate dysphoric individuals depressive symptoms, we should be able to use this information to design means of intervening and preventing them from becoming clinically depressed. Coyne s (1976b) interpersonal theory of depression focused on the context of social interactions between people experiencing depressive symptoms and their significant others. Because depressed individuals are likely to be socially rejected, Coyne (1976a) proposed a cycle in which social interactions exacerbate a person s depressive symptomatology. The cycle begins when a person who is experiencing symptoms of depression seeks support and validation from friends and family members. After repeatedly reassuring the dysphoric individual, these significant others become frustrated and distance themselves. Alternatively, they may avoid confrontation out of the fear of causing the dysphoric person to become more distressed. Over time, however, these situations and frustrations accumulate. Eventually they result in built-up emotional exchanges that can be upsetting to both parties (Coyne, Burchill, & Stiles, 1991). These unpleasant social interactions worsen the individual s depressive symptoms, motivating the person to seek further support and reassurance, thereby continuing the cycle. Living with a person who suffers from depressive symptomatology can be extremely distressing. Indeed, not only may family members develop depressive symptoms of their own, but they also are likely to develop feelings of hostility toward the depressed person (Coyne et al., 1987). Moreover, the progression of interactions that Coyne (1976b) describes may not be limited to family members and friends. For example, men are more likely to reject dysphoric than nondysphoric strangers (Tan & Stoppard, 1994). In addition, individuals with low positive affect, a key symptom of depression that also may be among the most visible indicators, are rated more negatively by observers than are targets with high positive affect (Joiner, 1996). Observer ratings did not correlate with targets overall depression scores, so the meaningfulness of this finding for understanding depression and social relationships is less clear. Still, interpersonal difficulties associated with depressive symptomatology exist at least to some degree across a number of social relationships and are worth better understanding.

3 924 JACOBSON REASSURANCE SEEKING One aspect of Coyne s theory that has received a great deal of research attention is the excessive reassurance seeking pursued by dysphoric individuals (e.g., Davila, 2001; Joiner, 1994; Joiner & Metalsky, 2001). According to Coyne (1976b), reassurance seeking starts the interactional cycle that leads to increased dysphoria, and Joiner and Metalsky s (2001) longitudinal studies provided evidence that excessive reassurance seeking is, indeed, an antecedent for the development of depressive symptomatology (but see Shahar, Joiner, Zuroff, & Blatt, 2004). Furthermore, reassurance seeking s effects are specific to symptoms of depression as opposed to other disorders such as anxiety (Joiner, 1994; Joiner, Metalsky, Gencoz, & Gencoz, 2001; Joiner & Schmidt, 1998). Also, excessive reassurance seeking is related to interpersonal difficulties such as shyness (Joiner, 1997) and social rejection (e.g., Joiner, Alfano, & Metalsky, 1992; Katz & Beach, 1997). Does excessive reassurance seeking lead directly to depressive symptomatology, or could some third variable account for this relationship? Davila (1999) proposed that personality factors may serve as such a third variable. To test this idea, Davila (2001) looked at anxiety about abandonment, sociotropy, and preoccupied attachment style, but none were significant mediators of the link between excessive reassurance seeking and dysphoria. Furthermore, Joiner and Metalsky (2001) have ruled out general dependency and doubt about the sincerity of others. However, one individual difference factor that appears to play a role in the reassurance seeking dysphoria relationship is causal uncertainty (Jacobson & Weary, 1999). CAUSAL UNCERTAINTY For some people, other individuals are chronically perplexing. Weary and Edwards (1994, 1996) have termed such uncertainty about one s understanding of other people and social events causal uncertainty. People who are causally uncertain engage in a more extensive search for and processing of social information to satisfy a goal of subjective accuracy and to gain control (Weary & Edwards, 1996). For example, compared to people who are not causally uncertain, individuals who are causally uncertain seek more diagnostic information (Weary & Jacobson, 1997), spend more time gathering information to form an impression of another person (Jacobson, Weary, & Lin, 2006), and are less likely to use stereotypes when making judgments about others (Weary, Jacobson, Edwards, & Tobin, 2001). Like reassurance seeking, causal uncertainty also has been linked to interpersonal difficulties such as shyness and

4 CAUSAL UNCERTAINTY 925 loneliness (Jacobson, Weary, & Chakraborti, 1997) and related to depressive symptoms (Edwards & Weary, 1998; Jacobson, Weary, & Edwards, 1999). Why would causal uncertainty and dysphoria be associated? Both constructs have been related to perceptions of uncontrollability (e.g., Edwards & Weary, 1998; Jacobson et al., 1999). People who are uncertain that they understand the causes of events also are likely to feel they do not have control over these outcomes, and such uncontrollability perceptions may, in turn, increase symptoms of depression like dejection and hopelessness. Alternatively, causal uncertainty and dysphoria may be related because they both are associated with interpersonal difficulties like loneliness and shyness (Jacobson et al., 1997). THE RELATIONSHIP BETWEEN REASSURANCE SEEKING AND CAUSAL UNCERTAINTY In their review of the reassurance seeking research, Joiner, Metalsky, Katz, and Beach (1999b) proposed that excessive reassurance seeking might mediate the relationship between causal uncertainty and dysphoria. People who are causally uncertain tend to seek additional social information to render their worlds more understandable (Edwards, Weary, von Hippel, & Jacobson, 2000), and Joiner et al. (1999b) proposed that reassurance seeking might be one of the ways they accomplish this goal. That is, causally uncertain people may seek reassurance from friends and family members to determine the validity of their perceptions and judgments (i.e., to get feedback on their accuracy to attain the attributional confidence that they lack). Thus their need to resolve their causal uncertainty motivates their reassurance seeking behavior, starting Coyne s cycle of depression and rejection. In response to Joiner et al. s (1999b) hypothesis, Jacobson and Weary (1999) proposed that causal uncertainty might, instead, be a mediator of the relationship between excessive reassurance seeking and dysphoria. According to Coyne (1976b), an individual who has been excessively seeking reassurance to the point that it has driven significant others away may be confused about why this distancing has occurred. Potentially, the individual may conclude that something is wrong with him or her, which could lead to doubt about his or her understanding of social relations. Furthermore, individuals who engage in excessive reassurance seeking likely elicit conflicting responses from friends and family members such that other people s words of support are at odds with their tone of voice and distancing behavior (Coyne, 1976b; Joiner & Metalsky, 2001; Joiner, Metalsky, Katz, & Beach, 1999a). As a result, people who engage in excessive reassurance seeking may become causally

5 926 JACOBSON uncertain about which social cues are genuine. In turn, this confusion about the actions of close others may lead a person to be uncertain about his or her understanding of other aspects of their social world. In their study, Jacobson and Weary (1999) found significant positive correlations between causal uncertainty and reassurance seeking. However, excessive reassurance seeking did not mediate the relationship between causal uncertainty and depressive symptoms as Joiner et al. (1999b) hypothesized. Instead, Jacobson and Weary s counterproposal was supported, and causal uncertainty was a significant mediator of the relationship between reassurance seeking and depressive symptoms. Unfortunately, Jacobson and Weary assessed only concurrent relationships between the variables. A longitudinal investigation would provide more compelling evidence about the relationships between the constructs. Indeed, Joiner et al. (1999a) focused on such a study as one of two important extensions of their research program because Jacobson and Weary s premise also would be supportive of Coyne s theory. Thus the current study was conducted to gather this additional information and potentially resolve the conflict between the competing hypotheses about the relationship between excessive reassurance seeking, causal uncertainty, and dysphoria. THE CURRENT STUDY In the current study, I used a longitudinal design to reexamine the contrasting hypotheses about the mediating roles of causal uncertainty and excessive reassurance seeking in the other construct s relationship to depressive symptomatology. I predicted that causal uncertainty, reassurance seeking, and dysphoria would be concurrently related. However, consistent with Jacobson and Weary (1999), I expected that reassurance seeking would not be a mediator of the longitudinal relationship between causal uncertainty and depressive symptoms, but causal uncertainty would again be shown to mediate the relationship between excessive reassurance seeking and dysphoria. METHOD PARTICIPANTS Two hundred students (170 women, 30 men) from an introductory psychology class at Queen s University participated in this study and received 0.5% toward their final grade. They ranged in age from 17 to 21 years, with a mean age of years (SD = 0.62).

6 CAUSAL UNCERTAINTY 927 MATERIALS Beck Depression Inventory II. The Beck Depression Inventory II (BDI; Beck, 1996) is a self report inventory that measures an individual s level of depressive symptomatology; however, it is not adequate for a clinical diagnosis of depression. This scale is composed of 21 items that are scored on a scale ranging from 0 to 3. A total score was calculated by summing across the items, and higher scores indicated greater depressive symptoms. The BDI has high internal consistency, Cronbach s alpha =.81, and good test retest reliability, rs =.67 to.90 (Andersen & Schwartz, 1992; Beck, Steer, & Garbin, 1988; Lightfoot & Oliver, 1985; Oliver & Burkham, 1979; Oliver & Simmons, 1984). Beck Anxiety Inventory. Due to the comorbidity between depression and anxiety (Ingram & Hamilton, 1999) and the significant relationship between causal uncertainty and anxiety (Weary & Edwards, 1994), I also included a measure of anxiety so that I could control for its effects. The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988) is a self report questionnaire that assesses the frequency of anxious symptoms over a 2 week time period. The scale is composed of 21 items that are scored on a scale ranging from 0 to 3. A total score was calculated by summing across the items, and higher scores indicated greater anxious symptoms. It has a coefficient α of.92, indicating high internal consistency, and it has good test retest reliability of.75 (Beck et al., 1988). This measure was chosen because it primarily measures physiological manifestations of anxiety (e.g., sweating and heart pounding) that distinguish anxiety from depression (Clark & Watson, 1991). Causal Uncertainty Scale. The Causal Uncertainty Scale (CUS; Weary & Edwards, 1994) assesses individual differences in the strength and frequency of causal uncertainty beliefs. It is composed of 14 items (e.g., When things go right, I generally do not know what to do to keep them that way and I do not know what it takes to get along well with others ). Participants responded to each item using a scale ranging from strongly disagree (1) to strongly agree (6). A total score was calculated by summing across the items, and higher scores indicated greater causal uncertainty. This scale has high internal consistency (Cronbach s α =.83) and six week test retest reliability ranging from.62 to.80 (Edwards & Weary, 1998; Jacobson et al., 1999). Reassurance Seeking Scale. The Reassurance Seeking Scale (RSS; Joiner & Metalsky, 2001) is a self report measure of an individual s level of reassurance seeking. It is made up of four items (e.g., In general, do you find yourself often asking the people you feel close to how they truly feel about you? ) that are scored on a 7 point scale from 1 (no, not at all)to7 (yes, very much). Thus higher scores indicated greater reassurance seek-

7 928 JACOBSON ing. The RSS has shown good internal consistency, Cronbach s α =.85 to.95 (Joiner et al., 1999b). Joiner, Katz, and Lew (1999) found that the 3 week test retest reliability for the RSS was statistically significant, but relatively low, r =.39, p <.01; thus they concluded that reassurance seeking is as much statelike as traitlike (p. 635). PROCEDURE At a prescreening session held at the beginning of the term, introductory psychology students at Queen s University completed several questionnaires, including the BDI, the BAI, the CUS, and the RSS. Between 4 and 8 weeks after the prescreening session, students who completed the prescreening materials were contacted by telephone and given the opportunity to participate in a study regarding their personal views, feelings, and attitudes. Upon arrival at the laboratory, participants were separated into individual rooms to complete the BDI, the BAI, the CUS, and the RSS on a computer. The questionnaires were presented in a random order except for the BDI, which was always presented last to avoid mood effects (Mark, Sinclair, & Wellens, 1991). When the participants were finished, they were debriefed and thanked for their time. RESULTS CORRELATION ANALYSIS The means, standard deviations, and zero order correlations between the participants scale scores from Times 1 and 2 are shown in Table 1. The means for the participants CUS scores are consistent with other studies using similar populations, but the BDI, BAI, and RSS 1 scores are slightly higher than some of Joiner and his colleagues previous research as well as both of Davila s (2001) studies. Consistent with previous research, the participants BDI, BAI, CUS, and RSS scores were significantly and positively correlated, rs >.19, ps < In addition to slightly higher mean RSS scores, my test-retest correlation (r =.66) for RSS was substantially larger than that obtained by Joiner, Katz, and Lew (1999). Consequently, reassurance seeking appears to be more traitlike than statelike in my sample. One potential explanation for these discrepancies could be cultural. That is, my sample comprised Canadians, whereas Joiner and his colleagues participants were Americans. Although the two cultures are highly similar and, in fact, are often treated as interchangeable in cross-cultural research, differences do exist. Perhaps reassurance seeking is one behavior that is more often or at least more consistently over time performed by people in Canada than in the United States.

8 CAUSAL UNCERTAINTY 929 MEDIATION ANALYSES To test the competing mediation hypotheses, a series of path analyses were conducted using LISREL 8.30 and maximum likelihood estimation. In accordance with the recommendations of Hoyle and Panter (1995), the assessment of model fit was based on three indexes: one absolute fit index, the Root Mean Square Error of Approximation (RMSEA; Browne & Cudek, 1993); and two incremental fit indexes, the Tucker Lewis (TLI; Tucker & Lewis, 1973) or Non Normed Fit Index (NNFI; Bentler & Bonett, 1980) and the Comparative Fit Index (CFI, 1990). The following heuristics for each index are used for interpreting fit: (1) the RMSEA should be less than.05 for good fit or less than.10 for acceptable fit (Browne & Cudek, 1993), and (2) the TLI/NNFI and CFI should be greater than.90 (Bentler & Bonett, 1980; Hu & Bentler, 1995), although more recent reviews recommend that they be greater than.95 for good fit (Hu & Bentler, 1999). For each proposed mediator, three models were tested. All of the models included the appropriate errors and variances as well as the covariance paths between all of the participants Time 1 scores to account for their significant, positive interrelationships. In addition, for the mediator (either Time 2 CUS or RSS) and the dependent measure (Time 2 BDI), a directional path was included between participants scores on that variable at Time 1 to that same variable at Time 2. Consequently, the mediators and dependent measure should be interpreted as changes in those constructs at Time 2 rather than just static levels. Also, participants Time 1 BAI scores were included to partial out their longitudinal effects on Time 2 BDI. 2 In the first model, I examined the direct effects of the predictor variable (either Time 1 CUS or RSS) and the mediator (either Time 2 RSS or CUS) as separate predictors of Time 2 BDI. The difference between this model and the other two is that no path was included between the predictor variable and the mediator, but a path from each of those variables to Time 2 BDI was assessed. In the second model, the separate paths to Time 2 BDI still were included, but a path linking the predictor variable to the mediator was added. This model could be considered a test of partial mediation because both an indirect effect through the mediator and a direct effect from the predictor were examined simultaneously. In the third model, the path between the Time 1 predictor variable and Time 2 BDI was eliminated. Thus this model was a test of full mediation or that 2. The same results were obtained when participants Time 2 BAI scores were controlled either in addition to or in place of their Time 1 BAI scores.

9 TABLE 1. Cronbach s Alphas, Zero Order Correlations, Means, and Standard Deviations for the Variables Time 1 Time 2 BDI BAI CUS RSS BDI BAI CUS RSS Time 1 BDI.87 BAI.47***.87 CUS.38***.34***.88 RSS.36***.32***.29***.86 Time 2 BDI.65***.39***.38***.35***.96 BAI.36***.49***.26***.33***.52***.95 CUS.40***.37***.73***.31***.48***.38***.88 RSS.39***.20**.21**.66***.37***.28***.26***.84 Mean SD Note. Cronbach s alphas are reported along the diagonal. BDI = Beck Depression Inventory II score; BAI = Beck Anxiety Inventory score; CUS = Causal Uncertainty Scale score; RSS = Reassurance Seeking Scale score; SD = Standard deviation. *p <.05, **p <.01, ***p <

10 CAUSAL UNCERTAINTY 931 Time 1 Reassurance Seeking.65***.02 Time 2 Reassurance Seeking.13* Time 1 Causal Uncertainty.13* Time 2 Dysphoria.52***.08 Time 1 Dysphoria Time 1 Anxiety * p <.05 ** p <.01 *** p <.001 FIGURE 1. Path diagram for Time 2 reassurance seeking as a partial mediator of the relationship between Time 1 causal uncertainty and Time 2 depressive symptoms. the predictor variable s relationship to Time 2 BDI operates entirely through the mediator. Reassurance Seeking as a Mediator. In the direct effects model, both Time 1 CUS and changes in Time 2 RSS were significantly related to changes in Time 2 BDI, both βs =.13, ts 2.25, ps.01. In the partial mediation model, the path coefficients for the direct paths did not change; however, Time 1 CUS was not significantly related to changes in Time 2 RSS, β =.02, t =.31, p >.75 (see Figure 1). Hence, because the two variables were not related, changes in Time 2 RSS cannot be a mediator of CUS s longitudinal relationship to changes in Time 2 BDI as Joiner et al. (1999b) proposed. The longitudinal CUS RSS relationship also was not significant in the full mediation model. Because the direct effects and full mediation models are nested within the partial mediation model (i.e., their parameters are a subset of those in the partial mediation model), they each can be separately compared to the partial mediation model using the χ 2 difference test. Because the direct effects and full mediation models have the same degrees of freedom, however, they cannot be directly compared to each other using this quantitative analysis. The partial mediation model would be preferred to the full mediation model because the partial mediation model, which had more parameters, accounted for the data significantly better, χ 2 (4 3

11 932 JACOBSON = 1) = = 5.13, p <.05. In contrast, the direct effects model would be preferred to the partial mediation model because they were not significantly different, χ 2 (4 3 = 1) = = 0.10, and the direct effects model, which had fewer parameters, was more parsimonious. As further evidence against RSS as a mediator of the CUS BDI relationship, the only model that evidenced acceptable fit according to all three indexes was the direct effects model. Causal Uncertainty as a Mediator. In the direct effects model, changes in Time 2 CUS were significantly related to changes in Time 2 BDI, β =.25, t = 4.56, p <.001; however, Time 1 RSS was not related to changes in Time 2 BDI, β =.08, t = 1.44, p >.14. Consequently, according to Baron and Kenny s (1986) guidelines, there was no effect to be mediated, so running the other two models would be unnecessary. However, if the effects of changes in Time 2 CUS on changes in Time 2 BDI are not controlled, which more closely approximates Baron and Kenny s regression steps, then Time 1 RSS is significantly related to changes in Time 2 BDI, β =.12, t = 2.05, p =.04. On the basis of this result, I chose to examine the other two models. In the partial mediation model, Time 1 RSS was significantly related to changes in Time 2 CUS, β =.11, t = 2.19, p <.03, but only changes in Time 2 CUS were significantly related to changes in Time 2 BDI, β =.25, t = 4.43, p <.001 (see Figure 2). In the full mediation model, Time 1 RSS also was significantly related to changes in Time 2 CUS, which were, in turn, significantly related to changes in Time 2 BDI, βs =.11 and.26, ts = 2.19 and 4.75, ps <.03 and <.001, respectively. Thus, consistent with the cross sectional results obtained by Jacobson and Weary (1999), causal uncertainty mediated the longitudinal relationship between reassurance seeking and dysphoria. This conclusion also was supported by the χ 2 difference tests. The partial mediation model would be preferred to the direct effects model because the partial mediation model with its additional parameter accounted for the data significantly better, χ 2 (4 3=1)= =4.83,p <.05. Furthermore, the full mediation model would be preferred to the partial mediation model because the full mediation model, which had fewer parameters and thus was more parsimonious, accounted for the data equally well, χ 2 (4 3= 1) = = 2.76, p >.10. In addition, although all of these models had acceptable fit according to at least two of the three indexes, the full mediation model did perform the best (TLI and CFI.95, RMSEA <.09). GENDER ANALYSES Gender has been differentially associated with some of my variables (e.g., greater depressive symptomatology among women than men),

12 CAUSAL UNCERTAINTY 933 Time 1 Causal Uncertainty.69***.11* Time 2 Causal Uncertainty.25*** Time 1 Reassurance Seeking.08 Time 2 Dysphoria.51***.03 Time 1 Dysphoria Time 1 Anxiety * p <.05 **p <.01 ***p <.001 FIGURE 2. Standardized path coefficients for changes in Time 2 causal uncertainty as a partial mediator of the relationship between Time 1 reassurance seeking and changes in Time 2 depressive symptoms. and I had a much larger proportion of women than men in my study. Therefore, I conducted multiple groups analyses in LISREL to determine if the preferred model (i.e., CUS as a full mediator of the longitudinal relationship between RSS and BDI) differed according to the gender of the participants. I tested and compared four models. One model forced the parameter estimates for women and men to be equal for the two key relationships: Time 1 RSS to changes in Time 2 CUS and changes in Time 2 CUS to changes in Time 2 BDI. The second model constrained all of the Time 1 to Time 2 variable paths to be equal across genders, and the third model forced just the changes in Time 2 CUS to changes in Time 2 BDI path to be equal for women and men. The fourth model had no constraints (i.e., all paths were free to vary), and the other three models were nested within this unconstrained model and statistically compared to it. If the fourth model, which allows for different estimates for women and men, accounts for the data significantly better than any of the other models, then I would conclude that the pattern of relationships differed significantly by gender. However, none of the χ 2 difference tests were significant. Specifically, Model 1, in which the two key directional paths were forced to be equal across genders, did not differ significantly from

13 934 JACOBSON the unconstrained model, χ 2 (8 6 = 2) = = 5.08, p <.10. Similarly, the second and third models that constrained either all of the longitudinal paths or just the Time 2 CUS to Time 2 BDI path to be equal also accounted for the data equally as well as the unconstrained model, χ 2 (11 6 = 5) = = 8.37, p <.20, and χ 2 (7 6 = 1) = = 0.49, p >.20. In sum, the pattern of relationships obtained in the original analyses appears to apply equally to women and men. DISCUSSION In their review of the reassurance seeking research, Joiner et al. (1999b) proposed that causal uncertainty s relationship to dysphoria might be mediated by reassurance seeking. That is, reassurance seeking may be one action plan that causally uncertain people pursue to reduce their confusion, and because reassurance seeking leads to subsequent rejection, causally uncertaint people become more dysphoric over time. Drawing upon Coyne (1976b), Jacobson and Weary (1999) hypothesized instead that reassurance seeking likely elicits ambiguous responses from others that could make one causally uncertain and subsequently dysphoric because of these feelings of confusion and lack of control. In other words, Jacobson and Weary postulated that causal uncertainty mediated the relationship between reassurance seeking and depressive symptoms, and their data supported this contention. Jacobson and Weary s (1999) study, however, was limited in that all the constructs were assessed concurrently, and different relationships potentially could occur longitudinally. Indeed, Joiner et al. (1999a) focused on such a prospective study as one of only two areas that they felt would extend their research in important ways. In the current study, I was able to readdress this issue and test the two mediation hypotheses by examining the relationships between the constructs over two time periods. Counter to Joiner et al. s (1999b) hypothesis, reassurance seeking did not mediate the relationship between causal uncertainty and dysphoria. That is, even controlling for changes in reassurance seeking at Time 2, causal uncertainty at Time 1 still predicted significant increases in dysphoria at Time 2. Instead, my results supported Jacobson and Weary s (1999) postulate and cross sectional results. In the current study, causal uncertainty mediated the longitudinal relationship between reassurance seeking and depressive symptomatology. More specifically, controlling for changes in causal uncertainty at Time 2, reassurance seeking at Time 1 was no longer related to changes in dysphoria at Time 2. Furthermore, these associations did not differ by gender. Thus, I have now obtained additional support that Jacobson and Weary s hypothesis more accurately

14 CAUSAL UNCERTAINTY 935 reflects the relationships among these variables than does Joiner et al. s (1999b) proposal. However, even Joiner et al. (1999a) were intrigued by such a possible association among the three constructs because establishing that reassurance seeking leads to causal uncertainty provides additional support for Coyne s interpersonal theory of depression (1976a,1976b), which has guided much of their research. Hence, my results do not undermine Joiner and his colleagues previous work, but rather introduce another mechanism that links reassurance seeking to increases in depressive symptoms. Indeed, identifying third variables like causal uncertainty is important to their research program because it can lead to better understanding of reassurance seeking behavior and its consequences, thereby generating new areas for investigation. For example, causal uncertainty also has been associated with interpersonal problems (Jacobson et al., 1997) and social rejection (Jacobson, Rytwinski, & Passey, 2006). Future research should explore whether or not causal uncertainty also mediates the relationship between reassurance seeking and these outcomes and if causal uncertainty links reassurance seeking to dysphoria because causal uncertainty elicits the stress of social rejection. In addition, clearly not everyone who engaged in reassurance seeking became more causally uncertain. Therefore, the approach individuals take to seeking reassurance and the responses they elicit from other people should be examined to enhance our understanding of the relationship between reassurance seeking and causal uncertainty. For instance, if someone s excessive reassurance seeking yields clear and unambiguous validation from close others, then this person should not become more causally uncertain and experience greater depressive symptomatology. The current study also yields benefits more generally by increasing our knowledge about the interpersonal factors associated with depression and by pinpointing particular areas for prevention programs. Although my effects were not large, 3 identifying such cognitions and behaviors that can be modified in therapy is still quite valuable (cf. Davila, 2001). My study indicates that focusing on people s certainty about their 3. In the models, causal uncertainty accounted for about 14% of the variance in participants dysphoria levels if you consider the zero-order relationships or an additional 5% of the variance over and above participants Time 1 dysphoria and reassurance seeking. Participants Time 1 depressive symptomatology was by far the strongest predictor of their Time 2 dysphoria. Specifically, along with their Time 1 anxiety, participants Time 1 dysphoria accounted for about 43% of the variance in their Time 2 dysphoria levels. Overall the models with all of the predictors accounted for 46% 49% of the variance in participants Time 2 depressive symptoms.

15 936 JACOBSON ability to understand social events may be a useful area to address. Causally uncertain individuals are not only less susceptible to biases in their social judgments (Weary et al., 2001), but they actually are more accurate at least in determining other people s emotions (Harkness, Sabbagh, Jacobson, Chowdrey, & Chen, 2002) as well as their thoughts and feelings (Jacobson, Currie, Bondy, & Boucher, 2006). Thus, if these individuals can become more confident in their social perceptions, perhaps they can regain feelings of control and hopefully avoid becoming depressed. Finally, these data are correlational, so conclusions about causality cannot yet be made. Cohen, Cohen, West, and Aiken (2003) propose three conditions for causality: relationship, temporal precedence, and nonspuriousness. A relationship clearly was established among the constructs as was the temporal precedence of causal uncertainty and reassurance seeking in predicting increases in depressive symptoms. For some correlations, my mediation analyses can be used to support nonspuriousness. Unfortunately, I can rule out only the other variables measured in this study, which were neither extensive nor exhaustive, but almost all personality and psychopathology research suffers from this limitation. Still, further replications and extensions of the current study should help bolster the case for nonspuriousness and start to build the case for causality. REFERENCES Andersen, S. M., & Schwartz, A. H. (1992). Intolerance of ambiguity and depression: A cognitive vulnerability factor linked to hopelessness. Social Cognition, 10, Baron, R. M., & Kenny, D. A. (1986). The moderator mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, Beck, A. T. (1996). Beck Depression Inventory II. San Antonio, TX: Psychological Corporation. Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety psychometric properties. Journal of Consulting and Clinical Psychology, 56, Beck, A. T., Steer, R. A., & Garbin, M.G. (1988). Psychometric properties of the Beck Depression Inventory: Twenty five years of evaluation. Clinical Psychology Review, 8, Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, Browne, M. W., & Cudek, R. (1993). Alternative ways of assessing model fit. In K.A. Bollen & J.S. Long (Eds.), Testing structural equation models (pp ). Newbury Park, CA: Sage. Clark, L. A., & Watson, D. (1991). Theoretical and empirical issues in differentiating depression

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