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The pre-registration of this study is similar to the previous pre-registration of this study. More specifically, we only would like to change some aspects our data collection procedure as we encountered difficulties to obtain the necessary sample size. Further, we made the necessary adjustments in order to conduct the whole experiment online. This pre-registration, thus only differs slightly from the previous pre-registration. Negative self-referent processing (NSP) has been implicated in the occurrence and maintenance of emotional problems, but it is unclear how this NSP develop and why it starts. A learning theory of depression (Ramnerö, Folke, & Kanter, 2016) proposes that negative self-thoughts temporally increase when they are repeatedly paired with rewarding experiences; however, those negative self-thoughts are easily extinguished in the long term due to clear adverse consequences such as rejection of others. This theory further predicts that vulnerable people have, however, difficulty in disengaging from the acquired negative self-thoughts even when those thoughts are no longer being rewarded. This difficulty in disengaging from negative self-thoughts can be measured by an innovative lab-based paradigm, called the Emotional Reversal-Learning Task (ERLT). This negative self-referent processing could be a valuable target for prevention and treatment of emotional difficulties. (Watkins & Nolen Hoeksema, 2014). It is suggested that persistent NSP is difficult to treat as NSP tends to be a mental habit. NSP may become a mental habit after extended repetition and reinforcement. If this NSP is a mental habit, the key trick will be to replace it with a more adaptive response through the training of a new ‘counter-habit’ response. For example, in order to counteract NSP we suggest to enhance positive self-referent processing, which is incompatible with NSP. In this study, we will use the Positive self-referent Memory Specificity Training (PMST), in which participant are trained to increase the specificity with which they retrieve positive self-referent memories. PMST is a variant of Memory Specificity training, which has been found to significantly decrease depression in the past (Serrano, Latorre, Gatz, & Montanes, 2004). In the current study, we want to examine whether PMST can counteract persistent NSP. Specifically, we will randomly allocate participants to PMST and a bogus control condition, and test whether the PMST is associated with lower levels of persistent NSP measured by the ERLT after the training. The second aim of the present study is to investigate some secondary outcomes that are shown to be related to negative self-referent processing. We will focus on depressive symptoms, emotion regulation strategies and fear of positive emotions. First, depressive symptoms are shown to be related to negative self-referent processing (Belmans, Takano & Raes, in preparation; Takano, Iijima, Boddez, Raes, & Tanno, 2017; Takano, Van Grieken, & Raes, 2019; Wisco, Gilbert, & Marroquin, 2014). Second, for emotion regulation strategies, we will specifically examine two maladaptive types of regulation for negative (i.e., rumination) and positive emotions (i.e., dampening) (Aldoa, Nolen-Hoeksema,& Schweizer, 2010; Gilbert, Gruber, & Nolen-Hoeksema, 2013). Third, fear of positive emotions may play a role in persistent NSP. For instance, participants may not choose to retrieve positive memories by such a fear of positive emotions and will therefore be more persistent in NSP. As the PMST training will ask participants to retrieve several positive memories, it could be expected that this training will decrease the fear of positive emotions. Thus, we want to examine whether PMST is related to decreases in these secondary outcomes. Finally, if this is the case, we will check if NSP mediates these effects.

Depression is one of the most debilitating and prevalent mental disorders in the general population with more than 264 million people affected worldwide (World Health Organisation [WHO], 2020). Decades of research have gone into the exploration of the potential causes of depression and there seems to be a consensus that persistent Negative Self-Referent Processing (NSP) plays a central role in its development and maintenance (Beck, 2008). In a first step towards tackling this vulnerability factor in depression, there is a critical need to further understand how NSP exactly develops and why it is so difficult to extinguish over time. Indeed, learning psychology has repeatedly underlined the inflexible nature of NSP as it generally seems to be resistant to a changing environment – no longer eliciting the desired outcome that once installed it (Iijima, Takano, Boddez, Raes, & Tanno, 2017). In this regard, researchers have coined the term “mental habit” in conceptualizing the inflexibility and automaticity that characterizes NSP, as opposed to it being a form of volitional goal-driven behavior (Hertel, 2004). However, the question remains whether this conceptualization is justified and NSP is indeed habitual trait-like tendency that is responsible for prolonging and intensifying depression. If so, can we target this process in depressed individuals and thereby sharpen current treatment protocols? In order to answer these questions, we have developed the Emotional Reversal-Learning Task (ERLT), an innovative lab-based task measuring the putative habitual tendencies of NSP (Iijima, Takano, Boddez, Raes, & Tanno, 2017). In this project, we aim to systematically evaluate the validity (i.e., the diagnostic, construct, and predictive validity) of this new paradigm. The specific scope of the current study is to evaluate the predictive validity of the ERLT. Our aim is to establish whether individuals are less characterized by NSP (as measured by the ERLT) after taking part in a validated intervention for the treatment of symptoms of depression. Participants will take part in a mindfulness-based intervention (MBI), which has proven to be reliable and effective in reducing symptoms of depression in various populations. As a secondary aim we want to assess the impact of the MBI on symptoms of depression, levels of perseverative thinking and mindfulness skills.

A multitude of studies point towards the relevance of perfectionism in both the etiology and maintenance of various psychological disorders. Based on these observations, perfectionism has been proposed as a transdiagnostic process, that is to say, a process which exists across various disorders. Crucially, a transdiagnostic process must fulfil the criterion of causality by not only correlating with, but contributing to the etiology and maintenance of psychological disorders (Harvey et al., 2004). Transdiagnostic approaches aim to understand core processes underlying multiple psychopathologies and have gained increasing attention (Barlow et al., 2016; Ehring et al., 2008; Kring et al., 2010). They enable the development of models and treatments for processes instead of single disorders. Perfectionism has been found to be associated with different types of symptoms, including those indicative of Obsessive-Compulsive Disorder (OCD) and eating disorders (Egan et al., 2011; Limburg et al., 2017). The two conditions are frequently comorbid and assumed to share etiological relationships (Altman et al., 2009). However, the causality between perfectionism and these disorders is relatively understudied, as previous investigations have been conducted predominantly via cross-sectional studies. In order to approach an understanding of causality, temporal relations must be investigated. To this end, a longitudinal study design would be ideally suited. Additionally, previous research has tended to focus on one type of psychopathology, whereas simultaneous investigation of several different disorders is as of yet still lacking. So far, it is unclear (a) in which ways perfectionism increases a general risk for psychopathology, and (b) how perfectionism can lead to different specific disorders (e.g., OCD in one person and bulimia in another). To address these important questions, Nolen-Hoeksema and Watkins (2011) have suggested a heuristic for developing transdiagnostic models of psychopathology. Their heuristic proposes that transdiagnostic risk factors operate at different levels relative to the resulting psychopathology they cause. Within this model, so-called proximal risk factors such as perfectionism can lead to multiple types of disorders (multifinality). These proximal risk factors interact with moderating variables which can occur at the same time or after the proximal risk factor. Whether a specific type of symptomatology develops in the presence of this proximal risk factor (divergent trajectories) is assumed to depend on the presence of disorder-specific moderating variables. In the case of eating disorder and OCD symptoms, variables that have been suggested as possible moderators between perfectionism and symptomatology are body dissatisfaction (Boone et al., 2014, 2015) and inflated responsibility (Salkovskis et al., 2000), respectively. Thus, it is the aim of the current study to investigate the potential of perfectionism as a transdiagnostic risk factor. A longitudinal design will be employed to investigate the temporal relations between perfectionism and symptoms of more than one disorder at a time (multifinality), namely eating disorders and OCD. Additionally, the study will examine body dissatisfaction and responsibility as possible disorder-specific moderators between perfectionism and symptoms of eating disorders or OCD (divergent trajectories).

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Ecological Momentary Assessment (EMA) through mobile devices can provide new insights into the dynamic change of psychiatric disorders during the course of psychological treatments (Colombo et al., 2019; Shiffman, Stone, & Hufford, 2008; Vos et al., 2015). Especially affective or cognitive symptoms such as mood or Repetitive Negative Thoughts (RNT) (Ehring & Watkins, 2008) are characterized by high variability within days and across multiple days (McConville & Cooper, 1996; Peeters, Berkhof, Delespaul, Rottenberg, & Nicolson, 2006; Starr & Davila, 2012). It is therefore assumable that EMA allows for more reliable estimations of symptom change than standard questionnaires (SQs) that are collected less frequently and are currently the state of the art in psychological research. On the other side, EMA usually contains fewer items than SQs, because time and cognitive load on the respondent must be kept low, which in turn may lower the reliability and validity of a measuring instrument. So far, it is not clear whether outcome measures by EMA are more precise than SQs. To our knowledge, there is only one study (Moore, Depp, Wetherell, & Lenze, 2016) that has empirically investigated differences between EMA and SQs as measuring instruments for treatment response. The results indicate that treatment efficacy largely differs depending on which measurement method is used. Especially for depressive symptoms, EMA turned out to reveal higher effect sizes than SQs. When looking at the internal consistency of items, which is an indicator for the precision of a measure, EMA-items tended to show higher internal consistency than the same items measured with SQs, although this was not significant. Also, consistent with other studies, they found that correlations between EMA and SQ items were only of small to medium size. A possible explanation for these findings is that EMA is more sensitive to detect change in depressive symptoms than SQs, which are less frequently conducted and are known to be biased by recall. In this way, EMA can provide more precise estimations of treatment outcomes, which results in higher effect sizes. Besides the precision, the power to predict clinically relevant outcomes is an important evaluation criterion for measuring instruments. Therefore, building on Moores (2016) findings, we are interested in whether treatment outcomes measured by EMA can predict change in global functioning measured by clinical interviews better than SQs. Within an randomized clinical trial (RCT) investigating treatment efficacy of cognitive behavioral therapy (CBT), schema therapy (ST) and individual supportive therapy (IST) for depression, we assess self-reports about depressive symptoms and RNT three times daily with EMA in addition to weekly questionnaire assessments. RNT is a transdiagnostic factor with a central role in depression and is known to have a significant temporal fluctuation (Takano & Tanno, 2011). Further, we assess global functioning gobal functioning in a clinical interview pre- and posttreatment. Similar to Moore et al. (2016) we also calculate treatment effects separately for EMA and SQ data and compare the results.

Examining negative self-referent processing (NSP) as a key vulnerability process in depression.

Most research on depression has solely focused on negative affect even though depression is characterized by distortions on two independent dimensions, namely increased negative affect and decreased positive affect (Berrios, 1996; Vazquez, 2017). The role of positive emotions and cognitions has recently received increasing attention by researchers and clinicians (Vazquez, 2017). This is fortunate, as research showed that decreased positive affect is one of the most important predictors of depressive episodes (Dunn et al., 2016). But the solitary focus on only one of the two dimensions, negative affect or positive affect, may give an incomplete picture (Vazquez, 2017). Therefore, it is unfortunate that a one-sided focus on one of the valence dimensions (negative or positive) can also be found in the domain of self-referential information processing. Self-referential information processing is a process of how individuals perceive themselves. Previous research has shown that individuals who are vulnerable for depression tend to have excessive negative thoughts about themselves (Gotlib & Joormann, 2010). Furthermore, there is empirical evidence that depressive symptomatology is related to not only an excess of negative self-thoughts but also a lack of positive self-thoughts (Timbremont et al., 2004). These findings suggest that both a negativity bias and a lack of positivity bias are in play, but these two types of self-thoughts have been studied typically in isolation (Gotlib & Joormann, 2010; Timbremont et al., 204). Studying these biases together may give us a more complete picture of the mechanisms underlying depressive cognition as each of these biases seems to be related to different symptom dimensions. For instance, there is evidence that specifically lacking positive cognitions is related to anhedonia symptoms (Dunn et al., 2009). Therefore, the main focus of this study is on jointly examining the negative self-referent processing bias (NSP) and the positive self-referent processing bias (PSP) together, which allows us to tease the two processes apart and to assess the independent contribution of each of these processes to depressive symptomatology.

Most research on depression has solely focused on negative affect even though depression is characterized by distortions on two independent dimensions, namely increased negative affect and decreased positive affect (Berrios, 1996; Vazquez, 2017). The role of positive emotions and cognitions has recently received increasing attention by researchers and clinicians (Vazquez, 2017). This is fortunate, as research showed that decreased positive affect is one of the most important predictors of depressive episodes (Dunn et al., 2016). Though, the solitary focus on only one of the two dimensions, negative affect or positive affect, may give an incomplete picture (Vazquez, 2017). Therefore, it is unfortunate that a one-sided focus on one of the valence dimensions (negative or positive) can also be found in the domain of self-referential information processing. Self-referential information processing is a process of how individuals perceive themselves. Previous research has shown that individuals who are vulnerable for depression tend to have excessive negative thoughts about themselves (Gotlib & Joormann, 2010). Furthermore, there is empirical evidence that depressive symptomatology is related to not only an excess in negative self-thoughts but also a lack of positive self-thoughts (Timbremont et al., 2004). These findings suggest that both a negativity bias and a lack of positivity bias are in play, but these two types of self-thoughts have been studied typically in isolation (Gotlib & Joormann, 2010; Timbremont et al., 204). Studying these biases together may give us a complete picture of the mechanisms underlying depressive cognition as each of these biases seems to be related to different symptom dimensions. For instance, there is evidence that specifically lacking positive cognitions is related to anhedonia symptoms (Dunn et al., 2009). Therefore, the main focus of this study is on jointly examining the negative self-referent processing bias (NSP) and the positive self-referent processing bias (PSP) together, which allows us to tease the two processes apart and to assess the independent contribution of each of these processes to depressive symptomatology.

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019125992

Individuals who develop a mental disorder often present with not only one diagnosis, but high rates of comorbidities over the course of their lives. Therefore, research has developed an interest in identifying transdiagnostic processes that can help explain dysfunction across disorders. At the same time, this offers the possibility to target different clinical pictures with a more general intervention and thus to potentially improve the efficacy of treatments. One process that has received much attention as a possible transdiagnostic factor is emotion regulation (ER). There is evidence that deficits in ER are associated with increased levels of symptoms across a number of psychological disorders, including depression and anxiety (Brockmeyer et al., 2012; Joormann & Stanton, 2016; Mennin et al., 2009). However, studies investigating deficits in ER as a transdiagnostic process have provided mixed results: On the one hand, some results indeed support the transdiagnostic nature of ER; on the other hand, there is empirical evidence that particular ER difficulties are rather disorder-specific (Aldao et al., 2016; Im & Kahler, 2022; Lukas et al., 2018). Shukla and Pandey (2021) proposed a combination by suggesting, that only some ER difficulties may be transdiagnostic while other ER difficulties may be unique to specific disorders. They empirically tested their assumption by examining different components of ER deficits, based on the framework proposed by (Gratz & Roemer, 2004). Gratz and Roemer (2004) suggested that ER deficits can occur in the following domains: awareness and understanding of emotions, acceptance of emotional experiences, the ability to engage in goal-directed behaviors and control impulsive behaviors while facing negative emotions, and the use of strategies to modulate emotions in accordance with the situational demands. Shukla and Pandey (2021) included a subclinical sample with symptoms of either anxiety or both anxiety and depression in their study. They found that both subclinical groups showed a higher total score of ER deficits than the healthy sample, with the mixed group showing the highest level of deficits. When zooming in to the specific domains of ER difficulties, certain ER difficulties, namely non-acceptance of emotional response, impulse control difficulties, and limited access to ER strategies were only found in the anxious-depressed group, while difficulties engaging in goal-directed behavior, lack of emotional awareness and emotional clarity were found in both subclinical groups (Shukla & Pandey, 2021). In this study we aim to investigate which ER deficits can be found in individuals with a depression or an anxiety disorder. Thereby, we follow and extend the analogue study of Shukla and Pandey (2021) by recruiting a clinical sample with diagnosed disorders of a) depression, b) an anxiety disorder and c) depression and anxiety disorder. Note, the individuals may have additional comorbid diagnoses (e.g., nonorganic insomnia, obsessive-compulsive disorder, etc. for inclusion in this study. In this way, we hope to provide further evidence to clarify which deficits in ER are present in both depression and anxiety-related disorders, or if stronger degrees of difficulties are merely due to comorbidity between these two disorders. In order to further examine this possible dose-response relationship in more detail, we will also examine the extent of ER deficits depending on the number of disorders or comorbidities regardless of the type of disorder. Research has generally suggested that deficits in ER are linked to specific ER strategies, like repetitive negative thinking (RNT) that impede ER. For RNT, as for ER deficits, a transdiagnostic relationship is often assumed. Furthermore, it has also been shown for RNT that it increases as the number of comorbid diagnoses increases (McEvoy et al., 2013). Therefore, we will additionally investigate this particular ER strategy with respect to its occurrence in the different diagnostic groups as well as depending on the numbers of comorbid disorders.

This research question is a part of the ImPuls study. The study protocol of the ImPuls study is published at https://doi.org/10.1186/s12888-021-03541-3 and registered in the German Clinical Trial Register (ID: DRKS00024152, 05/02/2021).

Although there are many studies that clearly show a relationship between mental health and trait emotional intelligence (TEI), there have been only few studies that have examined clinical samples (Andrei et al., 2014; Hansen et al., 2009). Furthermore, it is particularly noticeable that most studies only looked at global TEI scores. But since TEI has many facets, it may also be important to look at the subdimensions of TEI and especially whether disorders differ in terms of the association with these dimensions. The aim of this study is, therefore, to investigate whether individuals with different mental disorders, differ significantly from healthy control groups on different TEI facets, measured with the TEIQue. For this purpose, a large patient sample, with different diagnoses (including depression, anxiety-related disorder, or insomnia) was recruited. Matched healthy control groups will be recruited. We expect that participants with a depression, participants with an anxiety-related disorder, and participants with insomnia will score lower on the global TEI score as well as on all subscales of the TEIQue compared to the healthy controls.

These research question is a part of the ImPuls study. The study protocol of the ImPuls study is published at https://doi.org/10.1186/s12888-021-03541-3 and registered in the German Clinical Trial Register (ID: DRKS00024152, 05/02/2021). We know from literature that there are a lot of variables that may have an impact on the symptom severity in a transdiagnostic sample of different mental disorders. In the following section we will shortly present possible impact factors that are also assumed to be mechanisms of change within the pragmatic randomized controlled trial (RCT). Physical activity (PA) and PA-related health competence (PAHCO). There is a body of evidence assuming that PA that is planned, structured and repeated, with the primary aim to improve or maintain physical fitness (Caspersen et al., 1985) might represent a preventive factor as well as an effective treatment in patients suffering from mental disorders. In a recently published RCT, an exercise intervention was efficacious in improving global symptom severity in a transdiagnostic sample (Zeibig et al., 2021). The results indicate that the reduction of global symptom severity was predicted by an increase in the amount of PA (Zeibig et al., 2021). Furthermore, exercise-specific affect regulation as part of PAHCO (Schmid et al., 2020) seemed to underly treatment effects (Zeibig et al., under review). Repetitive negative thinking (RNT). RNT defined as “a mode of responding to distress that involves repetitively and passively focusing on symptoms of distress and the possible causes and consequences of these symptoms” (Nolen-Hoeksema et al., 2008) might be a transdiagnostic risk factor for severity of depression and anxiety (Spinhoven et al., 2018). Sleep quality. Sleep disturbance is a symptom of many axis I disorders, e.g. in posttraumatic stress disorder or depressive disorders. In fact, depressed patients who also suffer from insomnia report higher levels of symptom severity compared to depressed patients without insomnia (Sunderajan et al., 2010). Evidence that extends these results to patients with other psychiatric disorders indicate that impaired sleep quality is strongly associated with higher levels of psychiatric symptom severity, assessed by patients themselves and clinicians (Kallestad et al., 2012). Health-related quality of life (HRQoL). HRQoL describes the perceived physical and mental health of an individual over time and includes correlates of HRQoL as health risks, functional status and social support (Centers for Disease Control and Prevention, 2000). A general population survey revealed that depressive and anxiety disorders are associated with the poorest outcome of HRQoL (Saarni et al., 2007). Regarding symptom severity, HRQoL seems to be negatively correlated among depressive patients (Cao et al., 2013) and patients suffering from post-traumatic stress disorder (Nachar et al., 2013) as well as from insomnia (Kyle et al., 2010). Perceived stress. Stress is defined as situations “in which environmental demands, internal demands, or both, tax or exceed the adaptive resources of an individual, social system, or tissue system” (Monat & Lazarus, 1991). Acute stressful life events or chronic levels of stress are a risk factor for a broad range of mental disorders such as posttraumatic stress disorder, depression, insomnia and anxiety disorders (Basta et al., 2007; Smoller, 2016). At the same time, people suffering from mental disorders are more sensitive to stress and experience higher levels of stress than healthy people (Connor et al., 2007; Zorn et al., 2017). However, research regarding symptom severity in a clinical sample is still pending. Fear of the corona virus (FoC). During the Covid-19 pandemic, people were confronted with a new, fast-spreading virus that was associated with high mortality rates, lack of treatment methods and overstrained health systems (Meyerowitz-Katz & Merone, 2020; Wiersinga et al., 2020). This situation was associated with high FoC in the population (Luo et al., 2021) and first results suggest that FoC is positively associated with symptom severity in depression and anxiety disorders (Belen, 2021; Fink et al., 2021; Rogers et al., 2021). Emotional regulation (ER). ER is defined as the “extrinsic and intrinsic processes responsible for monitoring, evaluating, and modifying emotional reactions, especially their intensive and temporal features, to accomplish one’s goal” (Thompson, 1994). Deficits in ER may favor the development of depression (Berking et al., 2014) and among patients suffering from depression deficits are seen as one key factor in the maintenance of symptoms (Ehring et al., 2010). In turn, enhancing ER skills using specific interventions may reduce symptom severity in depressive patients (Radkovsky et al., 2014). Emotional intelligence (EI). EI is defined as „the ability to process your emotions and others’ emotions to guide your thinking and behavior” (Ahmed Okasha et al., 2022) and impaired EI is seen as one principal component in depressive disorders (Fisher et al., 2010). Thus, research implies that impaired self-perceived EI is correlated with symptom severity among depressive patients (Ahmed Okasha et al., 2022). Sociodemographic data. Among a representative adult German sample, the prevalence of common mental disorders (e.g. depression or anxiety disorders) is higher among females, except for substance use disorders (Klose & Jacobi, 2004). Furthermore, being single, separated, divorced or widowed as well as being unemployed is associated with an increased risk of any mental disorder. Regarding the prevalence of depressive or anxiety disorders, no age effects were found (Klose & Jacobi, 2004) and higher education seems to yield lower rates of mood disorders (Alonso et al., 2004). However, research regarding symptom severity in a clinical sample is still pending. To summarize we can say that there are various variables associated with symptom severity of different mental disorders. However, they are mainly investigated in disorder-specific samples which is not in line with growing evidence supporting transdiagnostic treatments in patients with mental disorders (Dalgleish et al., 2020). Thus, research regarding impact factors on global symptom severity in a transdiagnostic sample is necessary. These results could provide important information that could be used to create transdiagnostic therapy approaches focusing on those impact factors with the highest impact on global symptom severity.

Everyday people are confronted with the perception of stress caused by several problems and challenges. These so-called stressors reach from long lists of tasks at work over the car traffic at rush hour up to social conflicts at home. Furthermore, crises of world affairs such as the Covid-19 pandemic are additional stressors, associated with a high prevalence of stress among the general population (Salari et al., 2020). Stress is defined as situation “in which environmental demands, internal demands, or both, tax or exceed the adaptive resources of an individual, social system, or tissue system,” (Monat & Lazarus, 1991). Acute stressful life events or chronic levels of stress are a risk factor for a broad range of mental disorders such as posttraumatic stress disorder (PTSD), major depressive disorder (MDD), Insomnia and anxiety disorders (Basta et al., 2007; Smoller, 2016). At the same time, people suffering from mental disorders are more sensitive to stress and experience higher levels of stress than healthy people (Connor et al., 2007; Zorn et al., 2017). Therefore, these mental disorders are also called stress-related disorder (Smoller, 2016). Stress does not necessarily lead to the development of a mental disorder, but it is generally associated with a lower quality of life (QOL) (Chaudhury et al., 2018). QOL is defined as the “individuals' perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” (WHOQOL, 1998, p. 1570). According to a systematic review the negative association between stress and QOL becomes even stronger if people also suffer from disorders such as sleep disorders, burnout or depression (Ribeiro et al., 2018). However, studies mainly compared stress and QOL from samples consisting of individuals with a specific mental disorder with healthy controls (Berghofer et al., 2020; Zorn et al., 2017). Although both constructs are shared relevant factors across all stress-related disorders, there is a gap in data from transdiagnostic analyses. One part of this study is therefore to fill this gap. Physical activity (PA), which is “any bodily movement produced by skeletal muscles that results in energy expenditure” (Caspersen et al., 1985, p. 128), has a contrary effect to stress on mental health in that it directly reduces the experience of stress but also elevates mood and increases QOL not only in healthy people but also in people suffering from mental disorders such as depression or anxiety disorder (Penedo & Dahn, 2005; White et al., 2017). The latter mechanism is attributed to the so-called stress-buffering hypothesis. According to this hypothesis, the increase, or a reduced decrease – compared to stronger decreases – in characteristics such as QOL is due to a reduction in the negative impact of stress (Gerber & Puhse, 2009). In one of the studies investigating the effect university students with more PA have been shown to be more satisfied in life and having higher positive affect than the group with lower levels of PA although they were confronted with the same academical stressors during this period (Wunsch et al., 2017). However, there is a lack of data on this hypothesis with regard to people suffering from mental disorders as – to our knowledge – it has only been tested on healthy people with provoked or naturally occurring stressors or people with physical diseases (Giessing et al., 2021; Klaperski & Fuchs, 2021; Schilling et al., 2020). Especially in terms of the underlying transdiagnostic mechanisms already mentioned, the idea of a stress buffer through PA does not seem to have been explored yet. Hence, this context gives rise to tow objectives for this study. In a first step we want to show that stress and QOL can be seen as underlying transdiagnostic factors in people with stress-related disorders. We expect higher levels of stress among the transdiagnostic sample and we also suspect that this group shows lower QOL due to the negative association of these two factors than the matched healthy sample. The second and also the main aim of this study is to shed light on the impact of PA on the association between stress and QOL in a transdiagnostic sample of people suffering from depression (mild, severe), insomnia, post-traumatic stress disorder and/or panic disorder (with or without agoraphobia).

The Approach-Avoidance Task (AAT) is a widely used instrument to measure approach and avoidance tendencies. In various psychological disorders (e.g., addictive disorders, eating disorders, anxiety disorders, etc.) approach or avoidance biases towards symptom related stimuli can be found. Furthermore, an AAT is frequently used as a method of training in cognitive bias modification studies, which aim to reduce these approach and avoidance biases in order to decrease symptom severity in psychological disorders. However, to the best of our knowledge, no systematic review regarding the reliability of an AAT across disorders exists so far. In addition, there are no consistent reports whether severity of symptoms is associated with a larger bias, as one would expect as evidence for validity. Therefore, the aim of the present systematic review and meta-analysis is to examine the reliability and validity of the AAT. Across studies which conducted the AAT in samples with (sub-)clinical symptoms of psychopathology, the mean bias score (i.e., AAT effect), its reliability, and its association with psychopathological symptoms are examined.

Additional file 2: Table S1. Counterbalancing of Instructions (AAT, IAT) and Order of IATs. Table S2. Ratings of Smoking-Related and Positive Pictures for Each Picture Set Used in the Approach-Avoidance Task (AAT). Table S3. Ratings of Smoking-Related and Positive Pictures Used in the Approach-Avoidance Task (AAT). Table S4. Design of the Single Target Implicit Association Test (ST-IAT) for the Order Compatible-Incompatible. Table S5. Design of the Single Target Implicit Association Test (ST-IAT) for the Order Incompatible-Compatible. Table S6. Picture Numbers (IAPS) of all Control Stimuli.

Additional file 1. SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents.

Background: Network analysis has gained increasing attention as a new framework to study complex associations between symptoms of post-traumatic stress disorder (PTSD). A number of studies have been published to investigate symptom networks on different sets of symptoms in different populations, and the findings have been inconsistent. Objective: We aimed to extend previous research by testing whether differences in PTSD symptom networks can be found in survivors of type I (single event; sudden and unexpected, high levels of acute threat) vs. type II (repeated and/or protracted; anticipated) trauma (with regard to their index trauma). Method: Participants were trauma-exposed individuals with elevated levels of PTSD symptomatology, most of whom (94%) were undergoing assessment in preparation for PTSD treatment in several treatment centres in Germany and Switzerland (n = 286 with type I and n = 187 with type II trauma). We estimated Bayesian Gaussian graphical models for each trauma group and explored group differences in the symptom network. Results: First, for both trauma types, our analyses identified the edges that were repeatedly reported in previous network studies. Second, there was decisive evidence that the two networks were generated from different multivariate normal distributions, i.e. the networks differed on a global level. Third, explorative edge-wise comparisons showed moderate or strong evidence for specific 12 edges. Edges which emerged as especially important in distinguishing the networks were between intrusions and flashbacks, highlighting the stronger positive association in the group of type II trauma survivors compared to type I survivors. Flashbacks showed a similar pattern of results in the associations with detachment and sleep problems (type II > type I). Conclusion: Our findings suggest that trauma type contributes to the heterogeneity in the symptom network. Future research on PTSD symptom networks should include this variable in the analyses to reduce heterogeneity. The current study aimed to investigate trauma type as a potential moderator of PTSD symptom networks, distinguishing between type I trauma (single event; sudden and unexpected, high level of acute threat) vs. type II trauma (repeated and/or protracted; anticipated) with regard to their index trauma.Findings suggest that the PTSD symptom network structure differs between type I and type II trauma survivors. Edges which emerged as especially important in distinguishing the networks were between intrusions and flashbacks, highlighting the stronger positive association in the group of type II trauma survivors compared to type I survivors. Flashbacks showed a similar pattern of results in the associations with detachment and sleep problems (type II > type I).Analysis revealed that trauma type contributes to the heterogeneity in the symptom network and it is important variable to consider in the future research. The current study aimed to investigate trauma type as a potential moderator of PTSD symptom networks, distinguishing between type I trauma (single event; sudden and unexpected, high level of acute threat) vs. type II trauma (repeated and/or protracted; anticipated) with regard to their index trauma. Findings suggest that the PTSD symptom network structure differs between type I and type II trauma survivors. Edges which emerged as especially important in distinguishing the networks were between intrusions and flashbacks, highlighting the stronger positive association in the group of type II trauma survivors compared to type I survivors. Flashbacks showed a similar pattern of results in the associations with detachment and sleep problems (type II > type I). Analysis revealed that trauma type contributes to the heterogeneity in the symptom network and it is important variable to consider in the future research.