Depression and generalized anxiety disorders (GAD) are the two most frequent types of mental illness worldwide, with a steadily rising incidence (especially among younger adults). It is thus not surprising that there is an enormous literature on the risk factors involved. A recent umbrella review of evidence from 134 meta-analyses spanning 1,283 studies revealed convincing evidence for six risk factors: widowhood, physical abuse during childhood, obesity, having 4–5 metabolic risk factors, sexual dysfunction, and job strain (Köhler et al., 2018). In addition to stressful life events and interpersonal problems (see also, Hettema et al., 2006; Hammen, 2018), psychologists have underlined the important role of personality, in particular neuroticism (Kotov et al., 2010; Sutton et al., 2011; Vittengl, 2017), and negative versus positive trait affect (Watson and Clark, 1984; Watson et al., 1988; Clark and Watson, 1991; Dejonckheere et al., 2018). A central research domain addresses individual differences in the form of various cognitive vulnerabilities (Teasdale, 1988; Murphy et al., 1999; Mathews and MacLeod, 2005; Everaert et al., 2012). Among the major theoretical models proposed in this domain are the following: the helplessness model (Seligman, 1975; Abramson et al., 1978), the hopelessness theory (Abramson et al., 1989), the response styles theory (Nolen-Hoeksema, 1991), self-serving attributional bias (Sweeney et al., 1986; Greenberg et al., 1992; Haidt and Rodin, 1999; Sanjuán and Magallares, 2009), and self-efficacy beliefs (Bandura et al., 1999; Muris, 2002). Recent reviews of empirical studies in this domain show the relative prevalence of pessimistic inferential style, dysfunctional attitudes, and rumination for depression and of anxiety sensitivity, intolerance of uncertainty, and fear of negative evaluation for anxiety (Hong and Cheung, 2015) as well as high neuroticism, low self-esteem, and negative repetitive thinking (Struijs et al., 2021).

Most of these models for emotion disorders have been developed and empirically studied in the domains of psychiatry and personality or clinical psychology, with little input from emotion psychology. Thus, one important issue that remains to be explored is the mediating role of specific “normal” emotions such as sadness and worry in the underlying mechanism. As part of the debate about the criteria in the new guidelines of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, DSM-5 Task Force, 2013), it has been argued that emotion theory and research can provide major input into a better understanding of the transition from normal to abnormal emotions that potentially result in severe emotional disorders (see the special issue of Emotion Review, Scherer and Mehu, 2015; Table of Contents listed in Appendix 4 of the online supplemental materials). After all, it seems reasonable to assume that in order to study disorders and dysfunctions of psychosomatic dysfunctions, it would be helpful to understand functioning under “normal” conditions, that is, in everyday life, in a random sample population (e.g., a household panel) so that the factors that can be considered risk factors for abnormality may be examined.

Appraisal theories of emotion (Smith and Lazarus, 1993; Roseman, 2001; Scherer, 2001, 2009; Scherer et al., 2001; Ellsworth and Scherer, 2003; Moors et al., 2013) can provide a major contribution to such efforts. Appraisal theorists assume that emotions are elicited and differentiated by the subjective evaluation, based on a number of appraisal criteria, of the personal significance of events and one’s ability to deal with the consequences. Apart from the central issue of whether the consequences of an event are good or bad for reaching one’s goal, two major appraisal criteria are control (Can human agency control the consequences?) and power (Do I have sufficient power to change the consequences?). If the results of these appraisals are realistic, the resulting emotion is likely to be functional (e.g., with respect to producing appropriate action tendencies). If this is not the case, the emotion is likely to be dysfunctional and maladaptive. If there is a tendency or bias toward repeatedly making unrealistic appraisals, for example, by over- or underestimating one’s coping potential, a more enduring emotional disorder may develop (see also Kuppens and Tong, 2010). Thus, Scherer (1987, p. 77) proposed the following hypotheses:

On the basis of this early proposal, Scherer and his collaborators have suggested that cognitive appraisal biases may be responsible for the development of dysfunctional emotion dispositions, that is, the tendency to experience certain emotions more frequently than warranted, constituting major risk factors for emotional disorders (Scherer, 1989, 2015; Scherer and Brosch, 2009; see also Roseman and Kaiser, 2001). It should be noted that the appraisal bias concept differs from the more general term “cognitive bias” in that it focuses specifically on very concrete appraisal steps such as valence, coping/control, causation, etc. in the judgment process. In contrast, general cognitive bias includes attention biases, working memory difficulties, and long-term memory biases (Everaert et al., 2020). Similarly, the widely studied domain of cognitive vulnerabilities covers many different types of maladaptive beliefs and attitudes, processing and thinking styles, as well as self-image (Hong and Cheung, 2015; Struijs et al., 2021). Clearly, all of these may be affected by appraisal bias or, in turn, affect appraisal bias. Thus, low self-esteem may be due to low control/coping beliefs or be partly responsible for low coping/control appraisal bias. Sander et al. (2005, p. 321–322) have discussed some of these bidirectional effects between appraisal and other cognitive functions such as stored schemata, representations in memory and self-concept, and expectations. However, the etiology of appraisal biases needs to be clarified by further research in this domain. Here we assume the existence of appraisal biases as a dispositional concept, which is expected to have a direct impact on the nature of the ensuing emotion and on emotion dispositions as well as emotion disorders.

Appraisal researchers have developed a theoretical framework that proposes concrete predictions on the type of appraisal bias likely to produce a particular form of emotional disorder (for further details, see Scherer and Brosch, 2009, and Supplementary Table S1). Specifically, they hypothesize that an appraisal bias of consistently underestimating one’s ability to control and cope with the consequences of adverse events across many different situations increases the frequency of experiences of worry and sadness and thus facilitates the development of depression and GAD.

These suggestions, developed from the theoretical framework of appraisal theory of emotion, are highly compatible with the large number of approaches, cited earlier, that highlight cognitive vulnerability as a major risk factor for affective disorders. Mehu and Scherer (2015) provide a brief overview and discussion of the relationship of these theories to the appraisal bias model. They argue that the main difference between the appraisal bias model and other models lies in the temporal position—within the flow of events leading from life challenges to depressive symptoms—of the respective cognitive processes. Whereas earlier models emphasize the role of individual differences in information processing after the negative emotional experience is initiated, the appraisal model argues that consistent appraisal biases in the way that events are processed in the first place increase the tendency to experience episodes of sadness and despair and thus increase the risk of developing clinically relevant depression. In other words, there is a slow buildup of an ever-increasing tendency toward “sadness orientation,” progressing from normal to pathological. Thus, the major difference is that the predictions concerning the risk for depression and anxiety mood disorders based on an appraisal bias model assume a mediating role for stable emotion dispositions. The assumption is that individuals for whom a low coping potential appraisal bias (underestimating both control and power potential) has created a stable emotion disposition to experience sadness and/or worry more frequently and more strongly will be at greater risk of suffering clinically relevant depression or anxiety disorders.

The first step in examining this mediation hypothesis is to establish the existence of emotion dispositions that can be reasonably attributed to appraisal bias. The first evidence for the existence of emotion dispositions was obtained in a semi-representative survey of emotion experiences in the population living in Switzerland (N = 1,242; Scherer et al., 2004). It corroborated the notion that an emotion disposition may induce a tendency to experience certain emotions more frequently. To assess emotion dispositions, respondents rated the relative frequency with which they had experienced each of 14 emotions in the past months. Respondents then reported an event that had elicited an emotion on the previous day. Those who frequently experienced a particular emotion in their daily life were three times more likely (odds ratio) to have experienced the corresponding emotion yesterday. Furthermore, respondents scoring high on the eating disorder, depression, and anxiety disorder scales in a self-report version of the Primary Care Evaluation of Mental Disorders questionnaire (Spitzer et al., 1999) also showed increased odds ratios of having experienced anxiety yesterday. The strength of the emotion disposition effect is surprising, as a major emotion experienced “yesterday” can generally be accounted for by a large number of different factors (see Epstein, 1979). Even though these results are not surprising, they underline the need to better understand the nature and origin of emotion dispositions as separate from trait emotionality (see also Tangney, 1990; Reisenzein and Weber, 2009).

More recently, Scherer (2021) reported two large-scale studies on emotion dispositions and appraisal bias that used a scenario imagination assessment method. Study 1, with 3,052 professionals in assessment sessions, confirmed the existence of stable emotion dispositions and showed important correlations with several personality traits. Concerning the central role of appraisal bias, in Study 2, representatively selected participants in a US web panel (N = 190) were asked to indicate how they would most likely appraise the events in nine realistic scenarios, in addition to the emotions they would most likely experience in the respective situations. The scenario measurement allows a more fine-grained determination of emotion dispositions and appraisals by focusing on the frequent reoccurrence of certain appraisal and emotion responses across different scenarios, rather than on simple self-report of the estimated frequency with which one experiences certain emotions or makes certain types of evaluations. The results confirmed the theoretical prediction that specific appraisal biases do in fact account for a large percentage of the variance in the expected emotion responses. In particular, the reporting of worry and sadness as emotions anticipated to be felt by the individual in several of the realistic scenarios generally coincided with a conjectured appraisal of low coping potential (see Supplementary Table S1).

In this article, we are extending this approach to the area of affective disorders by examining whether appraisal bias and related emotion dispositions should be considered risk factors for developing depression or GAD. From the theoretical framework outlined earlier, we specifically predict that an appraisal bias resulting in habitual underestimation of one’s capacity to cope with negative events increases the tendency to frequently experience sadness or worry. In turn, these emotions generated by inappropriate appraisal may give rise to a clinically relevant increase in feelings typical of depression and anxiety. We further predict that a number of background variables (such as biographical factors, personality, motivation, and negative life events in critical phases) can affect both emotion dispositions and (directly or mediated via these dispositions) the tendency to frequently experience a state of depression or anxiety.

For both ethical and practical reasons, these hypotheses cannot be tested in experimental studies by using systematic manipulations. Realistically, we are limited to a self-report approach. Most earlier work used self-report scales to study clinically relevant groups. Although this approach produces important insights, it needs to be complemented by studies on large, randomized, representative samples of the general population. Such studies are even more indicated because it is important to understand the mechanism involved in a “normal” sample (i.e., a random sample from a general population) before the first indicators are detected.

In this article, we present first empirical evidence for the hypothesis that appraisal bias and associated emotion dispositions of sadness and worry can be potential risk factors for the development of depression and general anxiety obtained in two successive studies. In Study 1, we used data from a single survey wave of an official Swiss nationwide household panel survey (based on telephone interviews) with a large representative group of participants. To obtain the first cross-sectional evidence for the theoretical predictions outlined earlier, we based our analyses on short forms of established psychometric instruments. The inherent limitations of scales with a limited number of items is compensated by the possibility of obtaining data from a very large representative sample of the population. In order to test the replicability of the results with standard multi-item scales, we ran a second study, Study 2, where we measured the major variables via established psychometric instruments and a recently validated scenario-based assessment instrument, using a sample of young adults.

Obviously, these cross-sectional studies do not allow to test the causal mechanism suggested by the theoretical assumptions. To firmly establish proof of causality, experimental manipulation or intervention is required. Longitudinal designs help but cannot provide absolute certainty, either. In many cases, as in the current one, experimental manipulation or intervention is impossible for ethical reasons and low feasibility. The latter is also a major issue for longitudinal designs. Most longitudinal studies in the domain of emotional disorders concern therapeutic interventions. The proposed causal path from appraisal bias to emotion dispositions to risk for emotion disorders is most likely a very complex process, probably involving recursive influences, that extends over many years. At present, we know very little about the factors involved, their interaction, and the temporal unfolding. This is why any longitudinal design needs input about the important factors to measure and the time frames to be chosen. Given that there is insufficient information on these factors so far, input from cross-sectional data that establishes solid, replicated statistical associations can help to identify effect sizes for potential parameters and their interdependencies. This is how we understand the contribution of the research reported here.

The multidisciplinary longitudinal Swiss Household Panel (SHP) survey (Tillmann et al., 2016; SHP Group, 2022) is ideal for our purposes, as the regular interview schedule already contains questions for many psychological constructs involved in the theoretical framework, such as questions on moods, beliefs, and suffering from life events, as well as motivation and personality traits. Notably, at an early stage of the development of the survey, we had the chance to include four items that measure the frequency of experiencing sadness, worry, anger, and joy (with standard self-report questions, as a scenario measurement cannot be used in lengthy multidisciplinary and generalist telephone interviews). The analysis of the survey data was structured in such a way that different classes of variables could be differentiated with respect to their position in a causal path model that combined several classes of variables with differential proximality to the major dependent variable, risk for mood disorder (see Figure 1). These classes are, in descending order of proximality, as follows: (1) mental predispositions (emotion dispositions, severity of suffering), (2) cognitive appraisal bias (coping potential), and (3) background factors (socio-demographic, personality, motivation, and past experience). We decided to include severity of suffering from life events as a mental predisposition factor separate from emotion dispositions as it is more directly tied to eliciting events. The goal was to examine, in an exploratory manner, the theoretical framework outlined earlier with respect to direct effects and mediation effects in a large sample of the population. Given the aim of identifying particular risk factors for emotion disorders, it is of particular importance to rely on panel data in order to have access to a large, representative, randomized sample living in a specific country.

Given the limitations of a nationwide representative household survey, we wanted to examine the predictions of the appraisal bias/emotion disposition model presented in the introduction, using established instruments in a specially recruited sample of participants. We chose young adolescents as the target population, as there have been several reports of the high incidence of depression and general anxiety in younger adults (Mojtabai et al., 2016; Hawes et al., 2021; see also https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health).

To measure the risk for developing these emotion disorders, we chose two of the most widely used instruments in this domain, the PHQ-8 (Kroenke et al., 2009) and the GAD-7 (Spitzer et al., 2006). Appraisal bias and resulting emotion dispositions are measured by two new instruments, the Emotion Index (EI), measuring the self-reported frequency of different types of emotional experiences, and the Emotion Disposition Index (EmoDis), measuring the respondent’s projected appraisal pattern and emotional reaction in a number of typical emotion-eliciting scenarios. These instruments were recently validated in two large-scale studies cited earlier (Scherer, 2021): (1) The EmoDis was administered to several thousand adults from many cultural backgrounds in personnel assessment contexts (N = 3,012), demonstrating the existence and intensity of emotion dispositions, as well as identifying potential individual difference correlates; and (2) the EmoDis was used in a representative survey panel study of US citizens (N = 190), assessing both appraisal biases and emotion dispositions, allowing an in-depth analysis of their relationships (in addition to examining the effect of correlates).

There are two major questions to be investigated in this study: (1) Can the important effect of specific appraisal biases on emotion dispositions be replicated in a sample of participants drawn from another culture and language, and (2) can the effects of appraisal bias and emotion dispositions on the risk for depression and generalized anxiety, found in Study 1, be replicated in a study with a group of young adults by using validated assessment scales in a web-based survey?

As to (1), Scherer (2021) investigated the following predictions on the effect of appraisal biases on emotion disposition (see also Supplementary Table S1):

Using the same EmoDis instrument in the current study, we will investigate these same hypotheses and compare the results to those reported by Scherer (2021).

As to (2), the predictions on the effects of appraisal biases and emotion dispositions on potential risk factors for emotional disorders, published in Scherer (2021), are shown in Supplementary Table S1. Of particular importance for the replication of the results in Study 1 is the prediction concerning risk for depression and anxiety, considered to be caused by an underestimation bias for control and power and frequent experiences of pessimism, sadness, and worry. To test these predictions, we used both self-report measures and the scenario-based instrument EmoDis.

In this article, based on two complementary samples, one random nationwide sample and one selected sample based on a student population, we attempt to demonstrate the well-foundedness of a nomological network of interrelated variables based on a theory of emotional functioning—appraisal theory—that is generally considered the most comprehensive attempt to map out this domain (Moors et al., 2013). In particular, we hope to build bridges between the communities of researchers studying emotion, personality, and individual differences on the one hand, and clinical psychologists and psychiatrists on the other, by demonstrating the utility of using theories and findings on “normal” emotionality in order to better understand abnormal affective disorders (Scherer and Mehu, 2015). In this way, we hope to contribute to the development of an emotion-focused clinical approach in the spirit of L. S. Greenberg's (2019) theory of functioning.

We consider the results of the two studies reported here, summarized in Table 2 for Study 1 and Figure 2 for Study 2, to provide important empirical evidence for appraisal bias theory according to which habitual biases in event evaluation can potentially lead to stable emotion dispositions, which, in some cases, may develop into mood disorders, in particular depression and generalized anxiety. Our findings confirm and extend a recent empirical study that demonstrated the close link between habitual underestimation of one’s coping potential and emotion dispositions such as worry and sadness (Scherer, 2021). We were also able to examine the effect of some background factors. Although age and gender have little effect in our samples, the number of life events and the degree of suffering caused is clearly a very important contributing factor in both studies, as was to be expected. In addition, Study 1 showed important effects of personality (neuroticism) and motivation (achievement). Thus, the current study suggests leads for further research on background factors that play a major role in the nomological network, in particular personality, motivation, and the experience of major life events.

Future work on the effects of appraisal bias and emotion dispositions on mood disorder should also examine relationships of this approach to the established traditions of linking locus of control, internalizing/externalizing, and attributional style with depression and anxiety (Sweeney et al., 1986; Cheng et al., 2013; Huang, 2015; Galvin et al., 2018). The major difference is that the appraisal-based emotion-focused approach does not privilege the habitual attribution of cause (external-internal) as a central determinant, but postulates a strong link between control and coping potential appraisal and an established emotion disposition as an imbalance between positive emotions on the one hand and a prevalence of sadness and worry on the other. The results of the current study show that the combination of these two predictors provides a promising estimation of potential risk for depression and anxiety. Interestingly, a similar combination of the two common temperament components of high Negative Emotionality and low Effortful Control were also strongly associated with increased psychopathology symptoms in a study by Snyder et al. (2015) with adolescents.

As mentioned with respect to the limitations of Study 1, the causal path model underlying the current investigation cannot be validated by cross-sectional studies of household panels or web surveys. Further work in this direction by using longitudinal time series approaches is urgently needed. Major efforts will be required to get appropriate longitudinal studies, which will be time- and cost-intensive, on the way. We hope that the results of the present study can help determine the priorities for the measurement of the many factors involved.

However, at this point, the evidence in the literature, confirmed by the current results, certainly encourages the urgency of developing intervention programs to minimize the adverse effects of the risk factors described here. In particular, the feasibility of health intervention activities such as increasing emotional competence and augmenting control beliefs in an effort to reduce the risk of emotional disturbances needs to be examined closely. Further work should examine in more detail which determinants are particularly valuable in reducing risk in order to better understand the underlying mechanisms and to fine-tune interventions. It would also be of interest to examine existing intervention programs for their utility in this respect. As to boosting control/coping skills, there is a plethora of programs on stress management and coping available that could be more closely evaluated in terms of the model developed here. Such projects, for example, in the framework of currently existing attempts to improve control beliefs and coping capacity (see Compas et al., 2017), should focus on promising techniques to prevent or reduce appraisal biases likely to produce dysfunctional and maladaptive emotion dispositions. Rapid development in this area is particularly urgent, given the rising incidence of depression and anxiety disorders among the young, particularly during periods of economic or health crises. This problem has become particularly salient in the enduring COVID pandemic (see Debowska et al., 2020; Kujawa et al., 2020).

The study’s design and its analysis were not preregistered. Study 1 was performed by using the data collected by the SHP, which is based at the FORS and supported by the Swiss National Science Foundation. The authors do not have any financial interest or benefit arising from the direct applications of this research.

The data files of the Swiss Household Panel (SHP; financed by the Swiss National Science Foundation) are available upon application to SwissUbase (https://www.swissubase.ch/en/catalogue/studies/6097/16588/overview). The Swiss Centre of Expertise in the Social Sciences (FORS) oversees the SHP. The SHP data are freely available to scientists who sign a contract agreeing to legal and ethical conditions that apply to the use of the data for research purposes (Tillmann et al., 2016). Other data files are available from the corresponding author upon reasonable request. The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Study 1—Swiss Household Panel, Study 2—University of Bologna. The patients/participants provided their written informed consent to participate in this study.

KS has furnished the theoretical background, designed both studies, contributed to the data analysis, and wrote the first draft. V-AR has developed the control scales and performed the data analyses for the Swiss Household Survey data. PR-B and MC have designed and run the Italian survey study. All authors contributed to the article and approved the submitted version.

This work was supported by funds granted to KS under a Swiss National Science Foundation grant (100014-122491) and a European Research Council (ERC) Advanced grant PROPEREMO (230331).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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