Differential effects of positive and negative expectations on depressive symptoms

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Differential effects of positive and negative expectations on depressive symptoms

https://doi.org/10.21203/rs.3.rs-1509694/v1

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Background

Recent research suggests that dysfunctional expectations are a particularly important subtype of cognitions in depression. However, it is unclear whether depressive symptoms are primarily related to the presence of negative expectations, the absence of positive expectations, or both.

Methods

Using hierarchical linear regression and mediation analyses, the present study examined the predictive value of positive situation-specific expectations, negative situation-specific expectations, and other cognitive factors on depressive symptoms eight weeks later in a non-clinical sample (N = 157).

Results

Cross-sectionally, depressive symptoms were more strongly associated with the presence of negative expectations than with the absence of positive expectations. In the regression analysis, negative expectations rather than positive expectations predicted depressive symptoms eight weeks later, but only if baseline depressive symptoms were not considered. Negative but not positive situation-specific expectations mediated the effects of both dispositional optimism and dysfunctional attitudes on depressive symptoms eight weeks later.

Conclusions

In non-clinical samples, the presence of negative expectations rather than the absence of positive expectations may be associated with depressive symptoms. The current results also provide further evidence for a cognitive mediational model, suggesting that the effects of dysfunctional global cognitions on depressive symptoms are mediated through dysfunctional situation-specific expectations.

depression

expectations

dispositional optimism

dysfunctional attitudes

cognitive model

Starting with Beck’s influential cognitive model of depression (Beck, 1963, 1964; Beck et al., 1979), numerous studies have provided evidence for the presence of dysfunctional cognitions in people with depressive symptoms (Everaert et al., 2021; Miranda et al., 2008; Perez & Rohan, 2021). Besides other types of cognitions, such as dysfunctional attitudes (Alloy et al., 2006; Burns & Spangler, 2001; Jarrett et al., 2012) and (a lack of) dispositional optimism (Strunk & Adler, 2009; Strunk et al., 2006; Thimm et al., 2013), a cumulative body of research has suggested that depression is particularly characterised by dysfunctional expectations (Kube et al., 2020; Rief & Joormann, 2019). Expectations have been defined as future-directed cognitions that refer to the incidence (or non-incidence) of certain events or experiences (Laferton et al., 2017; Olson et al., 1996; Rief et al., 2015). Whilst there is sound evidence that depression is linked to different types of dysfunctional expectations, such as such as low self-efficacy expectations (Gopinath et al., 2007; Gordon et al., 2011; Ludman et al., 2003), or negative global expectations about future events (Czyz et al., 2016; Strunk et al., 2006; Vilhauer et al., 2012), little is known about whether depression is related to the predominance of negative expectations, the absence of positive expectations, or both. The present study seeks to contribute to this question by examining the differential effects of negative and positive expectations on depressive symptoms. This would not only be informative for the theoretical understanding of depression, but also for cognitive-behavioural therapy, as it could give an indication of whether it is more important to reduce negative expectations or to build up positive expectations - which is not necessarily the same.

To our knowledge, only one previous study directly addressed the question of whether depression is predicted by a lack of positive future-oriented expectations rather than by the presence of overly negative future-oriented expectations (Horwitz et al., 2017). In this study, the authors used the Beck Hopelessness Scale (Beck, 1974) and divided it into the positive-expectation subscale and the negative-expectation subscale. In a sample of at-risk adolescents, they found that the lack of positive expectations, rather than the presence of negative expectations, predicted depressive symptoms and suicidal behaviour 2–4 years later (Horwitz et al., 2017). In line with this finding, evidence from experimental psychopathology research suggests that depression is related to difficulties in using novel positive information to revise established negative expectations, rather than by an increased sensitivity to novel negative information (Everaert et al., 2018; Korn et al., 2014; Kube, Kirchner, et al., 2019; Kube, Rief, et al., 2019). Drawing on this previous research, the first aim of the present study was to investigate whether depressive symptoms are predicted by a lack of positive expectations rather than by the presence of overly negative expectations.

The second aim of this study was to further examine the specific cognitive link through which expectations are related to depressive symptoms. Specifically, previous research has shown that dysfunctional global cognitions, such as dysfunctional attitudes and (the lack of) dispositional optimism, elicit dysfunctional situation-specific expectations, which are associated with depressive symptoms (Kube, Glombiewski, et al., 2018; Kube, Siebers, et al., 2018a). In other words, the effects of dysfunctional global cognitions on depressive symptoms were mediated through dysfunctional situational expectations. Here, we aimed to replicate and extend this prior work by delineating whether the effects of global cognitions on depressive symptoms are mediated through negative situational expectations, positive situational expectations, or both.

The study was approved by the local ethics committee of the Department of Psychology of the University of Koblenz-Landau (reference number LEK-303) and has been conducted in accordance with ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. The study design and the analysis plan were pre-registered on aspredicted.org: https://aspredicted.org/26B_T73.

Participants and Procedure

Participants were recruited via email lists and social networks. The inclusion criteria were: age ≥ 18 years and sufficient German language skills. The study was designed as an online longitudinal observational study with two measurement time points. Data collection at T1 took place between March 30, 2021 and April 14, 2021. After eight weeks, participants were contacted via email and were asked to complete the second assessment (T2), which took place between May 25, 2021 and June 14, 2021. Both at T1 and T2, the order of the questionnaires was randomised to prevent order effects. At baseline, 258 participants completed the questionnaires through the survey platform www.soscisurvey.de. Of these, 158 participants completed the follow-up survey eight weeks later. One person had to be excluded because the person’s age was below 18 years. As pre-registered, we only used data of people who completed both T1 and T2. Thus, all analyses are based on a sample of N = 157. As an incentive for participation, participants had the chance to take part in a lottery to win gift vouchers (20€).

The mean age of the participants was M = 26.84 years, SD = 10.07, and 73.2% of the participants were female (25.5% male, 0.6% diverse, and 0.6% not willing to provide data on gender). The majority of the sample (66.9%) had school leaving examination (“Abitur” in German) as the highest educational degree, 25.5% of the participants had a university degree, 7% had primary education (German “Hauptschulabschluss” or “Mittlere Reife”), and 0.6% had a PhD as the highest educational degree. Most participants were university students (62.4%), 23.6% were employed, 4.5% worked in civil service, 1.3% were self-employed, 3.8% were in training, 0.6% were unemployed, 1.3% were homemakers, and 0.6% were pensioners. The BDI II sum scores were M = 11.59, SD = 9.43, at baseline and M = 10.35, SD = 9.27, at follow-up, each reflecting minimal symptoms of depression (Beck et al., 1996).

Measures

Situational expectations. Situational expectations were assessed using the Depressive Expectations Scale (DES) developed by Kube et al. (2017). This 25-item scale was developed to measure depression-specific expectations with a high level of situational specificity. The DES assesses expectations concerning interpersonal situations, performance-related situations, and negative mood regulation. Each item is formulated in an “if-then” structure, such that the items of the DES reflect situation-specific predictions that could be tested empirically, for instance through a behavioural experiment. Fifteen items of the DES reflect negative expectations, in the sense that a negative outcome is anticipated (e.g., “If I ask someone for help, I will be rejected”). By contrast, 10 items represent positive expectations, meaning that a positive outcome is anticipated (e.g., “If I talk to someone about my problems, I will feel better afterwards”). All items are rated on a five-point Likert scale ranging from 1 (“I disagree”) to 5 (“I agree”). If researchers wish to use the DES total score, the items reflecting positive expectations have to be reversely scored. For the present analysis, we consideres positive and negative expectations as two separate subscales to examine their differential effects on depressive symptoms. In doing so, we report the original (not reversely scored) values of the positive expectations, in order to allow a more intuitive interpretation. That is, high values of the positive expectations subscale reflect positive expectations and high values in the negative expectations subscale reflect negative expectations. Participants completed the DES both at baseline and at follow-up.

In previous studies, the DES total score has shown excellent internal consistency as indicated by Cronbach’s α (Kube et al., 2017; Kube, Glombiewski, et al., 2018; Kube, Herzog, et al., 2019; Kube, Siebers, et al., 2018b). In the present sample, the internal consistency for the entire 25-item DES was Cronbach’s α = .86 at both T1 and T2. Separately for each subscale, the internal consistency of the positive expectations subscale was Cronbach’s α = .61 at T1 and Cronbach’s α = .73 at T2, and, respectively, Cronbach’s α = .84 at T1 and Cronbach’s α = .83 at T2 for the negative expectations subscale. The test-retest reliability with a time interval of eight weeks was r = .808 (p < .001) for the DES total score, r = .718 (p < .001) for the positive expectations subscale, and r = .751 (p < .001) for the negative expectations subscale.

Dispositional optimism. Dispositional optimism was assessed at baseline with the German version of the Life Orientation Test Revised (LOT-R, Scheier, Carver, & Bridges, 1994) by Glaesmer et al. (2011). The LOT-R is a 10-item self-report scale, of which four items are distractor items that are excluded when computing the sum scores. The items are rated on a five-point Likert scale, with higher values of the LOT-R total score indicating more optimistic outcome expectations. The LOT-R has shown good reliability and validity in previous research (Glaesmer et al., 2011; Reilley et al., 2005; Scheier et al., 1994). In the present study, internal consistency of the LOT-R was Cronbach’s α = .80.

Dysfunctional attitudes. Dysfunctional attitudes were assessed at baseline using the Dysfunctional Attitudes Scale (DAS), originally developed by Weissman and Beck (1978) and translated into German by Hautzinger, Joorman, and Keller (2005). Here, we used the 26-item version of the DAS, which comprises two factors: approval by others and performance evaluation. The DAS has shown good reliability and validity (Joormann, 2004; Nelson et al., 1992). Participants rated the items of the DAS using a five-point Likert scale, with higher values reflecting a greater endorsement of dysfunctional attitudes. Cronbach’s alpha in the current sample was Cronbach’s α = .91.

Depressive symptoms. Depressive symptoms were assessed both at baseline and at follow-up with the Beck Depression Inventory-II (Beck et al., 1996). This well-established 21-item scale assesses somatic, cognitive and affective symptoms of depression (sum scores ranging from 0 to 63) with higher scores reflecting more severe symptoms of depression. The BDI-II has shown good psychometric properties (Beck et al., 1996). In the present study, Cronbach’s alpha of the BDI-II was Cronbach’s α = .91 at baseline and Cronbach’s α = .92 at follow-up.

Statistical Analyses

Data screening was conducted according to the recommendations by Tabachnick and Fidell (2019). We first performed a Fisher-z test to examine whether the magnitudes of the correlations of positive and negative expectations with depressive symptoms differ. For the main analyses, we performed a hierarchical linear regression analysis with the BDI-II sum scores at T2 as the criterion. In the first block, we included BDI-II sum scores at baseline as the predictor. In the second block, we added the sum scores of the positive and negative expectations subscales of the DES as predictors. In the third block, we entered the sum scores of the DAS and the LOT-R as additional predictors. In order to test the mediation hypotheses, BDI-II sum scores at T2 were the dependent variable (Y). In the first mediational model, the LOT-R sum score was the independent variable (X), and in the second mediation model, the DAS sum scores were included as the independent variable. In both mediation models, negative expectations (M₁) and positive expectations (M₂) were the mediator variables. Using model 6 from the PROCESS macro for SPSS v4.0 by Andrew Hayes (Hayes, 2022), we examined the potential mediating effects of negative and positive expectations.[1] In order to test the statistical significance of the indirect effects, we used bias-corrected accelerated (BCa) bootstrapping confidence intervals (CI) with 10,000 bootstrapping samples. This bias-corrected bootstrapping procedure has been recommended by several authors for testing mediation effects (Cheung & Lau, 2008; Hayes, 2009; MacKinnon et al., 2004). To facilitate the comparison of the results across different studies, we provide standardised coefficients according to Preacher and Hayes (2008). For all analyses, IBM SPSS Statistics Version 27 was used.

Correlational Analyses

At baseline, depressive symptoms were significantly correlated with both positive (r = -.557, p < .001) and negative expectations (r = .734, p < .001) from the DES. However, comparing the magnitude of the two correlations in a Fisher-z test revealed that the correlation of depressive symptoms with negative expectations was significantly higher than the correlation with positive expectations, z(156) = -3.620, p < .001. At follow up, depressive symptoms were again more strongly correlated with negative expectations (r = .705, p < .001) than with positive expectations (r = -.514, p < .001), z(156) = -3.358, p < .001.

Regression Analyses

Depressive symptoms at baseline explained 72.2% of the variance in depressive symptoms eight weeks later (β = .850, p < .001). Including positive (β = -.021) and negative situational expectations (β = .061) as predictors in the second step added another 0.3% of the variance, which was not significant (p = .491). Including dispositional optimism (β = -.087) and dysfunctional attitudes (β = .026) as predictors in the third block non-significantly added another 0.3% of the variance (p = .396).

Given the extremely strong influence of baseline depressive symptoms on depressive symptoms at follow-up, we repeated the regression analysis for exploratory purposes without depressive symptoms at baseline to examine whether there is a difference in the predictive value of positive and negative expectations. When including positive and negative expectations in the first block of this analysis, 44.5% of the variance in depressive symptoms eight weeks later were explained, which was significant (p < .001). In this step, negative expectations (β = .563, p < .001), but not positive expectations (β = -.151, p = .051) were significantly associated with depressive symptoms. Adding dispositional optimism and dysfunctional attitudes as predictors in the second block significantly added another 5.6% of the variance (p < .001). At this step, dispositional optimism (β = -.325, p < .001) and negative situational expectations (β = .276, p = .010), but not dysfunctional attitudes (β = .119, p = .156) and positive expectations (β = -.088, p = .244) were significantly associated with depressive symptoms. Thus, the results suggest that negative expectations have a greater predictive value than (the lack of) positive expectations, but not beyond and above baseline depressive symptoms. The results of the regression analyses of both model 1 (including baseline depressive symptoms as a predictor) and model 2 (not including baseline depressive symptoms) are presented in Table 1.

Mediation Analyses

Dispositional optimism as the independent variable. Dispositional optimism had significant effects on negative situational expectations, b = -.740, t(155) = -13.679, p < .001, and positive situational expectations, b = .250, t(154) = 2.734, p = .007. Negative situational expectations had significant effects on positive situational expectations, b = -.436, t(154) = -4.765, p < .001. Negative situational expectations had significant effects on depressive symptoms eight weeks later, b = .351, t(153) = 3.841, p < .001, whereas positive situational expectations did not, b = -.088, t(153) = -1.171, p = .243. The total effect of dispositional optimism on depressive symptoms eight weeks later was significant, b = -.650, t(155) = -10.635, p < .001, and so was the direct effect, though the magnitude of the effect was smaller, b = -.339, t(153) = -3.884, p < .001. There was a significant indirect effect of dispositional optimism on depressive symptoms through negative situational expectations, b = .260, BCa 95% CI [-.400, -.124], but not through positive situational expectations, b = -.022, BCa 95% CI [-.075, .017]. Figure 1 illustrates the results of this mediation analysis.

Dysfunctional attitudes as the independent variable. Dysfunctional attitudes had significant effects on negative situational expectations, b = .724, t(155) = 13.078, p < .001, whereas it did not have significant effects on positive situational expectations, b = .032, t(154) = 0.353, p = .724. Negative situational expectations had significant effects on positive situational expectations, b = .598, t(154) = 6.535, p < .001. Negative situational expectations had significant effects on depressive symptoms eight weeks later, b = .454, t(153) = 4.644, p < .001, whereas positive situational expectations did not, b = .147, t(153) = 1.929, p = .056. The total effect of dysfunctional attitudes on depressive symptoms eight weeks later was significant, b = .552, t(155) = 8.231, p < .001, but the direct effect was not, b = .155, t(153) = 1.788, p = .076. There was a significant indirect effect of dysfunctional attitudes on depressive symptoms through negative situational expectations, b = .397, BCa 95% CI [.190, .471], but not through positive situational expectations, b = .005, BCa 95% CI [-.019, .040]. The results of this mediation analysis are displayed in Figure 2.

The aim of the present study was to examine the differential effects of positive and negative situation-specific expectations on depressive symptoms. Across different sets of analyses, we found that depressive symptoms in this non-clinical sample were more strongly associated with the presence of negative expectations than with the absence of positive expectations. Specifically, in cross-sectional correlational analyses, the results revealed that depressive symptoms were more strongly related to negative expectations than to positive expectations. Furthermore, in the longitudinal regression analyses, we found that depressive symptoms eight weeks later were predicted by negative rather than by positive expectations (only when not considering baseline depressive symptoms, though, see limitations below). Moreover, in the mediation analyses, we found that negative expectations, but not positive expectations mediated the effects of global cognitions on depressive symptoms. These results are at odds with a previous study examining a clinical sample, which found that depressive symptoms were predicted by the lack of positive expectations, rather than by the presence of negative expectations (Horwitz et al., 2017).

Three possible interpretations may account for these discrepant findings. First, and most plausibly, with reference to different sample characteristics of the previous (Horwitz et al., 2017) and the current study, it is possible that in a non-clinical sample, the presence of negative expectations (such as expectations of failure, expectations of social rejection, etc.) make people vulnerable to developing depressive symptoms. On the other hand, in a clinical sample, the presence of positive future-oriented expectations may serve as a protective factor by increasing people’s motivation to actively seek opportunities to have positive experiences and may thus be related to a better prognosis. Second, it might be that different assessment tools account for the discrepant results, since Horwitz et al. (2017) used the Beck Hopelessness Scale (BHS), whereas the present study used the Depressive Expectations Scale (DES). Third, it is conceivable that the discrepancy is related to different follow-up intervals (2-4 years vs. 8 weeks). The plausibility of the second and the third interpretation can be tested by using both the BHS and the DES in a future study with a longer follow-up interval, ideally also in a clinical sample.

The second aim of the present study was to replicate previous studies suggesting a cognitive mediational model, in which situational expectations mediate the effects of global cognitions on depressive symptoms (Kube, Glombiewski, et al., 2018; Kube, Siebers, et al., 2018a). In line with prior research, we found that the effects of dispositional optimism on depressive symptoms were mediated through situational expectations with a moderate effect size, while the effects of dysfunctional attitudes on depressive symptoms were strongly mediated via situational expectations. Extending the above-referenced previous work, we found that this mediational role is exerted only by negative expectations, but not by positive expectations.

Implications

The present study has some implications for theoretical models of depression. The cognitive model of depression (Beck, 1963, 1964; Beck & Haigh, 2014; Beck et al., 1979) highlights the importance of dysfunctional cognitions for the development and maintenance of depressive symptoms, and recent research has specified that dysfunctional expectations might be a particularly important subgroup of cognitions (Kube et al., 2020; Rief & Joormann, 2019). The current study contributes to a further specification of these models by examining whether “dysfunctional expectations” is the same as “negative expectations”. The results show that positive and negative expectations indeed have differential associations with depressive symptoms, and in our non-clinical sample, this association was stronger for negative expectations. In addition, the present study provides further evidence for the notion from previous research that situation-specific expectations are an important link between global cognitions and depressive symptoms (Kube, Glombiewski, et al., 2018; Kube, Siebers, et al., 2018a). Given their high degree of situational specificity, such situational expectations may also be a promising target for cognitive-behavioural interventions, such as behavioural experiments, aimed at providing patients with new positive information in order to promote cognitive restructuring (Craske et al., 2014; Dobson & Hamilton, 2003; Rief & Glombiewski, 2016).

Limitations

An important limitation of the present study is that its observational nature does not allow any conclusions about causality. Moreover, the examination of a non-clinical sample limits conclusions that can be drawn about clinical depression. Furthermore, the follow-up period of eight weeks is relatively short, limiting possible conclusions about long-term effects of cognitions on depressive symptoms. In terms of the interpretation of the results, an important limitation is that in the regression analysis, baseline depressive symptoms had such a strong effect on depressive symptoms at follow-up that all cognitive predictors had non-significant effects when entered after baseline depressive symptoms. The extremely high predictive value of baseline depressive symptoms might also be related to the relatively short follow-up interval, speaking to the importance of using longer intervals in future research. With respect to the interpretation of the results, it should also be noted that the positive expectations subscale of the DES had a relatively low internal consistency at baseline, which may have contributed to their weaker association with depressive symptoms compared to the negative expectations subscale. A further limitation regarding methodology is that depressive symptoms were assessed only via self-report with the BDI-II. In future studies, it might be useful to additionally use clinician-rated measures, such as the Hamilton Depression Rating Scale (Hamilton, 1960). Moreover, it should be noted that the present study examined only cognitions that referring to present or future events. However, depression is also often related to ruminating about past events, so future work may consider adding measures of these cognitions as well. In addition, future work may consider not only cognitive predictors of depressive symptoms, but also other vulnerability factors related to the psychopathology of depression.

The present study investigated the differential effects of positive and negative expectations on depressive symptoms. The results show that in a non-clinical sample, depressive symptoms were more strongly associated with the presence of negative expectations than with the absence of positive expectations. Our findings also provide further corroborative evidence for a cognitive mediation model by indicating that negative but not positive situation-specific expectations mediate the effects of global cognitions on depressive symptoms.

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Table 1 Results of the regression analyses for the prediction of depressive symptoms at follow-up

		Criterion: BDI-II T2
Model 1	Predictors	β	R²	*R² adj.*	*∆R²*	∆F
Block 1 Block 2 Block 3	BDI-II T1 BDI-II T1 DES Positive T1 DES Negative T1 BDI-II T1 DES Positive T1 DES Negative T1 LOT-R T1 DAS T1	.850* .793* -.021 .061 .761*** -.009 .009 -.087 .026	.722 .725 .728	.721 .720 .719	.722*** .003 .003	403.453*** .714 .932
Model 2
Block 1 Block 2	DES Positive T1 DES Negative T1 DES Positive T1 DES Negative T1 LOT-R T1 DAS T1	-.151 .563*** -.088 .276* -.325*** .119	.445 .502	.438 .489	.445* .056*	61.823* 8.609*

Note. T1= Baseline assessment; T2= Follow-up assessment eight weeks later; BDI-II = Beck’s Depression Inventory II; DES Positive= Depressive Expectations Scale: subscale positive expectations; DES Negative = Depressive Expectations Scale: subscale negative expectations; LOT-R = Life Orientation Test Revised; DAS = Dysfunctional Attitudes Scale; *p < .05, *** p < .001

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Differential effects of positive and negative expectations on depressive symptoms

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