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Basic psychological needs theory postulates that a social environment that satisfies individuals’ three basic psychological needs of autonomy, competence, and relatedness leads to optimal growth and well-being. On the other hand, the frustration of these needs is associated with ill-being and depressive symptoms foremost investigated in non-clinical samples; yet, there is a paucity of research on need frustration in clinical samples. Survey data were compared between adult individuals with major depressive disorder (MDD; n = 115; 48.69% female; 38.46 years, SD = 10.46) with those of a non-depressed comparison sample (n = 201; 53.23% female; 30.16 years, SD = 12.81). Need profiles were examined with a linear mixed model (LMM). Individuals with depression reported higher levels of frustration and lower levels of satisfaction in relation to the three basic psychological needs when compared to non-depressed adults. The difference between depressed and non-depressed groups was significantly larger for frustration than satisfaction regarding the needs for relatedness and competence. LMM correlation parameters confirmed the expected positive correlation between the three needs. This is the first study showing substantial differences in need-based experiences between depressed and non-depressed adults. The results confirm basic assumptions of the self-determination theory and have preliminary implications in tailoring therapy for depression., Zweitveröffentlichungen der Universität Potsdam : Gesundheitswissenschaftliche Reihe; 8

SP8 is a subproject of the DFG-funded research unit 5187 "Towards precision psychotherapy for non-respondent patients: From signatures to predictions to clinical utility" (see more information here: https://forschungsgruppe5187.de/en). The general aim of the unit is to foster precision psychotherapy by i) investigating clinical and bio-behavioral signatures of nonresponse to cognitive-behavioral therapy (CBT) to improve our understanding of this phenomenon, ii) applying state-of-the-art machine learning technology for single-case predictions, and iii) validating these for clinical utility in an ecologically valid treatment setting. SP1 (see preregistration https://osf.io/bcgax) describes the set-up of the prospective-longitudinal observational cohort of n = 500 patients with mental disorders from the internalizing spectrum who are treated with cognitive behavioral therapy (CBT). SP8 focuses on the task-based analyses of the fMRI data of the prospective sample, including dynamic causal modelling. Impairment of adaptive emotion regulation represents a central psychopathological characteristic of psychological disorders from the internalizing spectrum. There are first indications that cognitive behavioral therapy - which uses techniques to train and improve emotion regulation – also influences neurofunctional patterns and that, in fact, appropriate functioning of these neural patterns is required for successful psychotherapy. They might therefore be considered as an important transdiagnostic marker for treatment response. More specifically, data from connectivity studies suggest that deficient fronto-limbic connectivity underlies impairments in emotion regulation. Ineffective top-down control is believed to prevent adaptive regulation of negative emotions. Detecting these malfunctioning neural patterns and, in turn, the resulting vulnerability to therapy non-response at an early stage, could allow for the development of individualized treatment and/or augmentation strategies. Adapting and individualizing treatment strategies will likely improve overall therapeutic results. In Sub-project 8, we will therefore develop and validate neurofunctional markers of emotion regulation as predictors for therapy non-response in a transdiagnostic sample of patients with internalizing disorders. In a first step, we will model effective connectivity of fronto-limbic modulation during three different emotion regulation strategies in retrospective data sets on depression, obsessive-compulsive disorder and social anxiety disorder. In a second step, we will validate those models with the best predictive values in a transdiagnostic prospective data set newly collected within the DFG (German Research Foundation) research group, testing them with respect to their generalizability and specificity across tasks (strategies) and diagnoses. By including bio-behavioral markers (SP5 and SP6), psychophysiological data (SP4) and findings from resting state connectivity (SP7), results will be further enhanced and refined. In addition, data from this sub-project will be contributing to single case prediction (SP2).

Background: The COVID-19 pandemic and its associated lockdown measures impacted mental health worldwide. However, the temporal dynamics of causal factors that modulate mental health during lockdown are not well understood. Objective: We aimed to understand how a COVID-19 lockdown changes the temporal dynamics of loneliness and other factors affecting mental health. This is the first study that compares network characteristics between lockdown stages to prioritize mental health intervention targets. Methods: We combined ecological momentary assessments with wrist-worn motion tracking to investigate the mechanism and changes in network centrality of symptoms and behaviors before and during lockdown. A total of 258 participants who reported at least mild loneliness and distress were assessed 8 times a day for 7 consecutive days over a 213-day period from August 8, 2020, through March 9, 2021, in Germany, covering a “no-lockdown” and a “lockdown” stage. COVID-19–related worry, information-seeking, perceived restriction, and loneliness were assessed by digital visual analog scales ranging from 0 to 100. Social activity was assessed on a 7-point Likert scale, while physical activity was recorded from wrist-worn actigraphy devices. Results: We built a multilevel vector autoregressive model to estimate dynamic networks. To compare network characteristics between a no-lockdown stage and a lockdown stage, we performed permutation tests. During lockdown, loneliness had the highest impact within the network, as indicated by its centrality index (ie, an index to identify variables that have a strong influence on the other variables). Moreover, during lockdown, the centrality of loneliness significantly increased. Physical activity contributed to a decrease in loneliness amid the lockdown stage. Conclusions: The COVID-19 lockdown increased the central role of loneliness in triggering stress-related behaviors and cognition. Our study indicates that loneliness should be prioritized in mental health interventions during lockdown. Moreover, physical activity can serve as a buffer for loneliness amid social restrictions.

The COVID-19 pandemic may have caused people to feel isolated, left out, and in need of companionship. Effective strategies to cope with such unrelenting feelings of loneliness are needed. In times of COVID-19, we conducted a smartphone-based ecological momentary assessment (EMA) study with 280 lonely participants in Germany over 7 months, where a long and hard second national lockdown was in place. Each participant reported their daily loneliness and coping strategies for loneliness once in the evening for 7 consecutive days. We found that managing emotions and social relationships were associated with decreased feelings of loneliness, while using a problem-focused coping strategy was associated with increased feelings of loneliness amid COVID-19. Interestingly, managing emotions was particularly effective for easing loneliness during the second lockdown. Females tend to use more emotion-focused coping strategies to overcome their loneliness compared to males. Our study highlights the importance of managing emotions against loneliness throughout the COVID-19 pandemic in Germany. Designing technology that provides emotional support to people may be one of the keys to easing loneliness and promoting well-being.