How negative mood hinders belief updating in depression: results from two experimental studies

Test-retest reliability of reinforcement learning parameters

It has recently been suggested that parameter estimates of computational models can be used to understand individual differences at the process level. One area of research in which this approach, called computational phenotyping, has taken hold is computational psychiatry. One requirement for successful computational phenotyping is that behavior and parameters are stable over time. Surprisingly, the test-retest reliability of behavior and model parameters remains unknown for most experimental tasks and models. The present study seeks to close this gap by investigating the test-retest reliability of canonical reinforcement learning models in the context of two often-used learning paradigms: a two-armed bandit and a reversal learning task. We tested independent cohorts for the two tasks (N = 69 and N = 47) via an online testing platform with a between-test interval of five weeks. Whereas reliability was high for personality and cognitive measures (with ICCs ranging from .67 to .93), it was generally poor for the parameter estimates of the reinforcement learning models (with ICCs ranging from .02 to .52 for the bandit task and from .01 to .71 for the reversal learning task). Given that simulations indicated that our procedures could detect high test-retest reliability, this suggests that a significant proportion of the variability must be ascribed to the participants themselves. In support of that hypothesis, we show that mood (stress and happiness) can partly explain within-participant variability. Taken together, these results are critical for current practices in computational phenotyping and suggest that individual variability should be taken into account in the future development of the field.

Anti-saccades reveal impaired attention control over negative social evaluation in individuals with depressive symptoms

Depressed individuals are excessively sensitive to negative information but blunt to positive information, which has been considered as vulnerability to depression. Here, we focused on inhibitory control over attentional bias on social evaluation in individuals with depression. We engaged individuals with and without depressive symptoms (categorized by Beck Depression Inventory-II) in a novel attention control task using positive and negative evaluative adjectives as self-referential feedback given by social others. Participants were instructed to look at sudden onset feedback targets (pro-saccade) or the mirror location of the targets (anti-saccade) when correct saccade latencies and saccade errors were collected. The two indices showed that while both groups displayed longer latencies and more errors for anti-saccade relative to pro-saccade responses depressed individuals spent more time reacting correctly and made more errors than non-depressed individuals in the anti-saccade trials and such group differences were not observed in the pro-saccade trials. Although group differences in correct anti-saccade latencies were found for both positive and negative stimuli, depressed individuals spent more time making correct anti-saccade responses to negative social feedback than to positive ones whereas non-depressed individuals featured longer correct anti-saccade latencies for positive relative to negative evaluations. Our results suggest that depressed individuals feature an impaired ability in attention control for self-referential evaluations, notably those of negative valence, shedding new light on depression-distorted self-schema and corresponding social dysfunctions.

Investigating Relationships Among Self-Efficacy, Mood, and Anxiety Using Digital Technologies: Randomized Controlled Trial

BACKGROUND

Digital tools assessing momentary parameters and offering interventions in people's daily lives play an increasingly important role in mental health research and treatment. Ecological momentary assessment (EMA) makes it possible to assess transient mental health states and their parameters. Ecological momentary interventions (EMIs) offer mental health interventions that fit well into individuals' daily lives and routines. Self-efficacy is a transdiagnostic construct that is commonly associated with positive mental health outcomes.

OBJECTIVE

The aim of our study assessing mood, specific self-efficacy, and other parameters using EMA was 2-fold. First, we wanted to determine the effects of daily assessed moods and dissatisfaction with social contacts as well as the effects of baseline variables, such as depression, on specific self-efficacy in the training group (TG). Second, we aimed to explore which variables influenced both groups' positive and negative moods during the 7-day study period.

METHODS

In this randomized controlled trial, we applied digital self-efficacy training (EMI) to 93 university students with elevated self-reported stress levels and daily collected different parameters, such as mood, dissatisfaction with social contacts, and specific self-efficacy, using EMA. Participants were randomized to either the TG, where they completed the self-efficacy training combined with EMA, or the control group, where they completed EMA only.

RESULTS

In total, 93 university students participated in the trial. Positive momentary mood was associated with higher specific self-efficacy in the evening of the same day (b=0.15, SE 0.05, P=.005). Higher self-efficacy at baseline was associated with reduced negative mood during study participation (b=-0.61, SE 0.30, P=.04), while we could not determine an effect on positive mood. Baseline depression severity was significantly associated with lower specific self-efficacy over the week of the training (b=-0.92, SE 0.35, P=.004). Associations between higher baseline anxiety with higher mean negative mood (state anxiety: b=0.78, SE 0.38, P=.04; trait anxiety: b=0.73, SE 0.33, P=.03) and lower mean positive mood (b=-0.64, SE 0.28, P=.02) during study participation were found. Emotional flexibility was significantly enhanced in the TG. Additionally, dissatisfaction with social contacts was associated with both a decreased positive mood (b=-0.56, SE 0.15, P<.001) and an increased negative mood (b=0.45, SE 0.12, P<.001).

CONCLUSIONS

This study showed several significant associations between mood and self-efficacy as well as those between mood and anxiety in students with elevated stress levels, for example, suggesting that improving mood in people with low mood could enhance the effects of digital self-efficacy training. In addition, engaging in 1-week self-efficacy training was associated with increased emotional flexibility. Future work is needed to replicate and investigate the training's effects in other groups and settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05617248; https://clinicaltrials.gov/study/NCT05617248.

Biased belief updating in depression

Cognitive approaches to depression have benefitted from recent research on belief updating, examining how new information is used to alter beliefs. This review presents recent advances in understanding various sources of bias in belief updating in depression. Specifically, research has demonstrated that people with depression have difficulty revising negative beliefs in response to novel positive information, whereas belief updating in depression is not related to an enhanced integration of negative information. In terms of mechanisms underlying the deficient processing of positive information, research has shown that people with depression use defensive cognitive strategies to devalue novel positive information. Furthermore, the disregard of novel positive information can be amplified by the presence of state negative affect, and the resulting persistence of negative beliefs in turn perpetuates chronically low mood, contributing to a self-reinforcing negative feedback loop of beliefs and affect. Synthesising previous research, this review proposes a coherent framework of when belief change is likely to occur, and argues that future research also needs to elucidate why people with depression hesitate to abandon negative beliefs. Recent insights from belief updating have not only improved the understanding of the psychopathology of depression, but also have the potential to improve its cognitive-behavioural treatment.

Using expectation violation models to improve the outcome of psychological treatments

Expectations are a central maintaining mechanism in mental disorders and most psychological treatments aim to directly or indirectly modify clinically relevant expectations. Therefore, it is crucial to examine why patients with mental disorders maintain dysfunctional expectations, even in light of disconfirming evidence, and how expectation-violating situations should be created in treatment settings to optimize treatment outcome and reduce the risk of treatment failures. The different psychological subdisciplines offer various approaches for understanding the underlying mechanisms of expectation development, persistence, and change. Here, we convey recommendations on how to improve psychological treatments by considering these different perspectives. Based on our expectation violation model, we argue that the outcome of expectation violation depends on several characteristics: features of the expectation-violating situation; the dynamics between the magnitude of expectation violation and cognitive immunization processes; dealing with uncertainties during and after expectation change; controlled and automatic attention processes; and the costs of expectation changes. Personality factors further add to predict outcomes and may offer a basis for personalized treatment planning. We conclude with a list of recommendations derived from basic psychology that could contribute to improved treatment outcome and to reduced risks of treatment failures.