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Conflicts between avoiding feared stimuli versus approaching them for competing rewards are essential for functional behavior and anxious psychopathology. Yet, little is known about the underlying decision process. We examined approach-avoidance decisions and their temporal dynamics when avoiding Pavlovian fear stimuli conflicted with gaining rewards. First, a formerly neutral stimulus (CS+) was repeatedly paired with an aversive stimulus (US) to establish Pavlovian fear. Another stimulus (CS−) was never paired with the US. A control group received neutral tones instead of aversive USs. Next, in each of 324 trials, participants chose between a CS−/low reward and a CS+/high reward option. For the latter, probability of CS+ presentation (Pavlovian fear information) and reward magnitude (reward information) varied. Computer mouse movements were tracked to capture the decision dynamics. Although no more USs occurred, pronounced and persistent costly avoidance of the Pavlovian fear CS+ was found. Time-continuous multiple regression of movement trajectories revealed a stronger and faster impact of Pavlovian fear compared to reward information during decision-making. The impact of fear information, but not reward information, modestly decreased across trials. These findings suggest a persistently stronger weighting of fear compared to reward information during approach-avoidance decisions, which may facilitate the development of pathological avoidance.

PurposeExamine the effects of an 8-week yoga therapy on fatigue in patients with different types of cancer.MethodsA total of 173 cancer patients suffering from mild to severe fatigue were randomly allocated to yoga intervention (n = 84) (IG) versus waitlist control group (CG) (n = 88). Yoga therapy consisted of eight weekly sessions with 60 min each. The primary outcome was self-reported fatigue symptoms. Secondary outcomes were symptoms of depression and quality of life (QoL). Data were assessed using questionnaires before (T0) and after yoga therapy for IG versus waiting period for CG (T1).ResultsA stronger reduction of general fatigue (P = .033), physical fatigue (P = .048), and depression (P < .001) as well as a stronger increase in QoL (P = .002) was found for patients who attended 7 or 8 sessions compared with controls. Within the yoga group, both higher attendance rate and lower T0-fatigue were significant predictors of lower T1-fatigue (P ≤ .001). Exploratory results revealed that women with breast cancer report a higher reduction of fatigue than women with other types of cancer (P = .016) after yoga therapy.ConclusionThe findings support the assumption that yoga therapy is useful to reduce cancer-related fatigue, especially for the physical aspects of fatigue. Women with breast cancer seem to benefit most, and higher attendance rate results in greater reduction of fatigue.Trial registrationGerman Clinical Trials Register DRKS00016034

Safety behavior prevents the occurrence of threat, thus it is typically considered adaptive. However, safety behavior in anxiety-related disorders is often costly, and persists even the situation does not entail realistic threat. Individuals can engage in safety behavior to varying extents, however, these behaviors are typically measured dichotomously (i.e., to execute or not). To better understand the nuances of safety behavior, this study developed a dimensional measure of safety behavior that had a negative linear relationship with the admission of an aversive outcome. In two experiments, a Reward group receiving fixed or individually calibrated incentives competing with safety behavior showed reduced safety behavior than a Control group receiving no incentives. This allowed extinction learning to a previously learnt warning signal in the Reward group (i.e., updating the belief that this stimulus no longer signals threat). Despite the Reward group exhibited extinction learning, both groups showed a similar increase in fear to the warning signal once safety behavior was no longer available. This null group difference was due to some participants in the Reward group not incentivized enough to disengage from safety behavior. Dimensional assessment revealed a dissociation between low fear but substantial safety behavior to a safety signal in the Control group. This suggests that low-cost safety behavior does not accurately reflect the fear-driven processes, but also other non-fear-driven processes, such as cost (i.e., engage in safety behavior merely because it bears little to no cost). Pinpointing both processes is important for furthering the understanding of safety behavior.

Enhancing the reduction of avoidance may optimize treatment for anxiety disorders. Past research focused on boosting fear extinction to reduce avoidance, however, with limited success. Directly extinguishing avoidance may be more promising. This preregistered study tested the impact of incentives and instruction for non-avoidance compared to passive fear extinction on long-term avoidance and fear reduction. On Day 1, participants acquired conditioned fear and avoidance to a conditioned stimulus (CS) paired with an aversive outcome. Next, incentives or instructions encouraged non-avoidance to the CS, which was no longer reinforced by a US regardless of avoidance (Incentives and Instruction group). In a third group, avoidance was unavailable and the CS was passively presented in absence of the US (Passive Fear Extinction group). On Day 2, avoidance retention and reinstatement and return of fear were tested. In the short term, incentives and instruction strongly reduced avoidance with similar fear reduction compared to passive fear extinction. Importantly, incentives and instruction were linked to lower long-term avoidance retention. Avoidance reinstatement was evident in all groups, but avoidance remained higher after passive fear extinction. Finally, incentives yielded a lower return of threat expectancies. Thus, targeting avoidance instead of fear better reduced long-term avoidance and, for incentives, the return of fear. Especially, incentives could be a promising add-on to exposure.

ObjectiveTo examine the efficacy of reminder e-mails to continue yoga therapy on practice frequency and fatigue in cancer patients and long-term effects of yoga on fatigue, depression, and quality of life.MethodologyOne hundred two cancer patients who completed an 8-week yoga therapy were randomly allocated to two groups: reminder (N = 51) vs. no-reminder group (N = 51). After completing yoga therapy, the reminder group received weekly e-mails for 24 weeks, which reminded them of practicing yoga, whereas the no-reminder group did not. Primary outcomes were fatigue and practice frequency, and long-term outcomes were fatigue, depression, and quality of life. Data were assessed using questionnaires after yoga therapy (T1) and 6 months after completing yoga therapy (T2).ResultA significantly stronger reduction of general (p = 0.038, d = 0.42) and emotional fatigue (p = 0.004, d = 0.59) and a higher increase of practice frequency (p = 0.015, d = 0.52) between T1 and T2 were found for the reminder group compared to the no-reminder group. In the mediation model, practice frequency as a mediator partially explained the changes in emotional fatigue (indirect effect B =  − 0.10). Long-term effects of yoga therapy regarding fatigue, depression, and quality of life were found (F > 7.46, p < 0.001, d > 0.54).ConclusionWeekly reminder e-mails after yoga therapy can positively affect general and emotional fatigue and help cancer patients with fatigue establish a regular yoga practice at home. However, higher practice frequency did not lead to higher physical or cognitive fatigue improvement, suggesting other factors that mediate efficacy on physical or cognitive fatigue, such as mindfulness or side effects of therapy.

In the interplay of fear and avoidance, not only imminent threat signals that directly predict potential threat evoke avoidance, but also distal threat signals that predict these imminent threat signals. Avoidance of learnt fear refers to avoidance to a distal threat signal that prevents the occurrence of an imminent threat signal. In clinical anxiety, it is often pathological given its persistence in the absence of threat and the impairments it inflicts. The current study examined whether fear extinction to an imminent threat signal would effectively reduce avoidance of learnt fear in a sensory preconditioning procedure. Three neutral preconditioning stimuli (PSs), serving as distal threat or safety signals, were paired with three neutral to-be conditioned stimuli (CSs), serving as imminent threat or safety signals. After assessing baseline levels of costly avoidance to the PSs, two CSs were paired with threat. One of these CSs then ceased to predict threat during extinction training. In test, participants showed limited avoidance to the PS that signaled the extinguished CS, however, the level of avoidance was still stronger compared to a PS that signaled a safety CS. Results suggest that exposure to an imminent threat signal partly reduces avoidance to a distal threat.

Background and objectivesTypicality asymmetry in generalization refers to enhanced fear generalization when trained with typical compared to atypical exemplars. Typical exemplars are highly representative of their category, whereas atypical exemplars are less representative. Individual risk factors, such as trait anxiety, attenuate this effect, due to the high level of threat ambiguity of atypical exemplars. Although recent research provided evidence for generalization of safety behavior, it is unclear whether this generalization also follows typicality asymmetry. This study examined (1) whether participants exhibited typicality asymmetry in the generalization of safety behavior and (2) whether this effect would be attenuated by individual risk factors, such as intolerance of uncertainty and trait anxiety.MethodsParticipants were trained with either typical (Typical group, n = 53) or atypical (Atypical group, n = 55) exemplars in a fear and avoidance conditioning procedure. Participants acquired differential conditioned fear and costly safety behavior to the threat- and safety-related exemplars. In a following Generalization Test, the degree of safety behavior to novel exemplars of the same categories was tested.ResultsThe Atypical group showed greater differential safety behavior responses compared to the Typical group. Higher trait anxiety was associated with lower differential safety behavior generalization, driven by an increase in generalized responding to novel safety-related exemplars. Limitations: This study used hypothetical cost instead of real cost.ConclusionsTraining with atypical exemplars led to greater safety behavior generalization. Moreover, individuals with high trait anxiety show impaired safety behavior generalization.

•Precision medicine needs reliable, replicable response predictions.•Studies suggest neuroimaging data as good input to predict treatment response.•We failed to replicate this in two big samples with state-of-the-art methodology.•The use of independent samples and several processing methods corroborates this. Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Background:Blended cognitive behavioral therapy (bCBT)—the combination of cognitive behavioral therapy and digital mental health applications—has been increasingly used to treat depression and anxiety disorders. As a resource-efficient treatment approach, bCBT appears promising for addressing the growing need for mental health care services, for example, as an early intervention before the chronification of symptoms. However, further research on the efficacy and feasibility of integrated bCBT interventions is needed.Objective:This study aimed to evaluate the efficacy of a novel bCBT program comprising short (25 min), weekly face-to-face therapy sessions combined with a smartphone-based digital health app for treating mild to moderate symptoms of depression or anxiety.Methods:This prospective uncontrolled trial comprised 2 measurement points (before and after treatment) and 2 intervention groups. We recruited university students with mild to moderate symptoms of depression or anxiety. On the basis of the primary symptoms, participants were assigned to either a depression intervention group (n=67 completers) or an anxiety intervention group (n=33 completers). Participants in each group received 6 weekly individual psychotherapy sessions via videoconference and completed modules tailored to their respective symptoms in the smartphone-based digital health app.Results:The depression group displayed medium to large improvements in the symptoms of depression (Cohen d=−0.70 to −0.90; P<.001). The anxiety group experienced significant improvements in the symptoms of generalized anxiety assessed with the Generalized Anxiety Disorder-7 scale with a large effect size (Cohen d=−0.80; P<.001) but not in symptoms of anxiety assessed with the Beck Anxiety Inventory (Cohen d=−0.35; P=.06). In addition, both groups experienced significant improvements in their perceived self-efficacy (Cohen d=0.50; P<.001 in the depression group and Cohen d=0.71; P<.001 in the anxiety group) and quality of life related to psychological health (Cohen d=0.87; P<.001 in the depression group and Cohen d=0.40; P=.03 in the anxiety group). Work and social adjustment of patients improved significantly in the depression group (Cohen d=−0.49; P<.001) but not in the anxiety group (Cohen d=−0.06; P=.72). Patients’ mental health literacy improved in the anxiety group (Cohen d=0.45; P=.02) but not in the depression group (Cohen d=0.21; P=.10). Patient satisfaction with the bCBT program and ratings of the usability of the digital app were high in both treatment groups.Conclusions:This study provides preliminary evidence for the feasibility and efficacy of a novel brief bCBT intervention. The intervention effects were generalized across a broad spectrum of patient-reported outcomes. Hence, the newly developed bCBT intervention appears promising for treating mild to moderate depression and anxiety in young adults.

This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.