The social transmission of empathy relies on observational reinforcement learning.

Theories of moral development propose that empathy is transmitted across individuals. However, the mechanisms through which empathy is socially transmitted remain unclear. Here, we combine computational learning models and functional MRI to investigate whether, and if so, how empathic and non-empathic responses observed in others affect the empathy of female observers. The results of three independent studies showed that watching empathic or non-empathic responses generates a learning signal that respectively increases or decreases empathy ratings of the observer. A fourth study revealed that the learning-related transmission of empathy is stronger when observing human rather than computer demonstrators. Finally, we show that the social transmission of empathy alters empathy-related responses in the anterior insula, i.e., the same region that correlated with empathy baseline ratings, as well as its functional connectivity with the temporoparietal junction. Together, our findings provide a computational and neural mechanism for the social transmission of empathy that accounts for changes in individual empathic responses in empathic and non-empathic social environments.

Connected in Bad Times and in Good Times: Empathy Induces Stable Social Closeness.

Humans need social closeness to prosper. There is evidence that empathy can induce social closeness. However, it remains unclear how empathy-related social closeness is formed and how stable it is as time passes. We applied an acquisition-extinction paradigm combined with computational modeling and fMRI, to investigate the formation and stability of empathy-related social closeness. Female participants observed painful stimulation of another person with high probability (acquisition) and low probability (extinction) and rated their closeness to that person. The results of two independent studies showed increased social closeness in the acquisition block that resisted extinction in the extinction block. Providing insights into underlying mechanisms, reinforcement learning modeling revealed that the formation of social closeness is based on a learning signal (prediction error) generated from observing another's pain, whereas maintaining social closeness is based on a learning signal generated from observing another's pain relief. The results of a reciprocity control study indicate that this feedback recalibration is specific to learning of empathy-related social closeness. On the neural level, the recalibration of the feedback signal was associated with neural responses in anterior insula and adjacent inferior frontal gyrus and the bilateral superior temporal sulcus/temporoparietal junction. Together, these findings show that empathy-related social closeness generated in bad times, that is, empathy with the misfortune of another person, transfers to good times and thus may form one important basis for stable social relationships.

Empathy incites a stable prosocial decision bias.

Empathy toward suffering individuals serves as potent driver for prosocial behavior. However, it remains unclear whether prosociality induced by empathy for another person's pain persists once that person's suffering diminishes. To test this, participants underwent functional magnetic resonance imaging while performing a binary social decision task that involved allocation of points to themselves and another person. In block one, participants completed the task after witnessing frequent painful stimulation of the other person, and in block two, after observing low frequency of painful stimulation. Drift-diffusion modeling revealed an increased initial bias toward making prosocial decisions in the first block compared with baseline that persisted in the second block. These results were replicated in an independent behavioral study. An additional control study showed that this effect may be specific to empathy as stability was not evident when prosocial decisions were driven by a social norm such as reciprocity. Increased neural activation in dorsomedial prefrontal cortex was linked to empathic concern after witnessing frequent pain and to a general prosocial decision bias after witnessing rare pain. Altogether, our findings show that empathy for pain elicits a stable inclination toward making prosocial decisions even as their suffering diminishes.

EEG evidence for racial ingroup bias in collective empathy for pain.

Previous research on racial ingroup bias in empathy for pain focused on neural responses to a single person's suffering. It is unclear whether empathy for simultaneously perceived multiple individuals' pain (denoted as collective empathy in this study) is also sensitive to perceived racial identities of empathy targets. We addressed this issue by recording electroencephalography from Chinese adults who responded to racial identities of 2 × 2 arrays of Asian or White faces in which 4 faces, 1 face, or no face showed painful expressions. Participants reported greater feelings of others' pain and their own unpleasantness when viewing 4 compared to 1 (or no) painful faces. Behavioral responses to racial identities of faces revealed decreased speeds of information acquisition when responding to the face arrays with 4 (vs. 1 or no) painful expressions of Asian (but not White) faces. Moreover, Asian compared to White face arrays with 4 (vs. 1 or no) painful expressions elicited a larger positive neural response at 160-190 ms (P2) at the frontal/central electrodes and enhanced alpha synchronizations at 288-1,000 ms at the central electrodes. Our findings provide evidence for racial ingroup biases in collective empathy for pain and unravel its relevant neural underpinnings.

Electrophysiological correlates of why humans deviate from rational decision-making: A registered replication study.

In contrast to rational choice theory predicting humans to optimize expected utilities of choices, humans deviate from rational behavior in decision-making paradigms. Hewig et al. (2011) explored affective correlates of decision-making in the ultimatum game (UG) and the dictator game (DG). They found that feedback-related negativity (FRN), subjective valence ratings, and autonomic nervous system activity predicted rejection of monetary offers. This registered replication aimed to validate and extend these findings. Although behavioral patterns and results of subjective ratings closely matched the original study, not all psychophysiological effects were successfully replicated. Firstly, we could not replicate the reported effects of autonomic nervous system activity. Secondly, a quadratic instead of the originally proposed linear relation between the offer and the FRN emerged, possibly driven by the offer evaluation in economic games and the rewarding anticipation of successful punishment for low offers. Thirdly, P3 amplitudes mirrored the quadratic offer response pattern, generally peaking for the lowest offer. In contrast to the original study, P3 responses were larger in the UG compared with the DG. Finally, our findings indicate that participant-related higher midfrontal theta activation predicted lower acceptance behavior in the UG, with a systematic dampening effect for fairer offers. This highlights cognitive control as a crucial mechanism in economic decision-making to overcome behavioral defaults. Overall, our results conceptually support the original conclusion that decision-making in economic games is non-rational and dependent on the objective situation as well as emotional and neural markers, though not precisely as suggested by Hewig et al. (2011).

Differential effects of everyday-life social support on chronic pain.

BACKGROUND: Social support is a multidimensional construct encompassing emotional support as well as pain-focused care and attention, also known as solicitous support. One the one hand, social support is widely believed to positively influence pain symptoms, their intensity, and the ability to cope and influence pain. On the other hand, social support can be negative if it conflicts with the patient's needs or even causes discomfort. How different types of social support influence pain is not very well understood especially because most of the present research originates from laboratory studies, raising uncertainties about its generalizability to the everyday life of individuals with chronic pain. METHODS: Here, we tested the effects of emotional, solicitous, and negative social support on pain intensity cross-sectionally in everyday life. We collected data from 20 patients with acute complex regional pain syndrome using a smartphone-based Ecological Momentary Assessment with up to 30 survey prompts over a period of five consecutive days. RESULTS: Our results showed that solicitous social support decreased pain, in particular in male patients. Emotional support was beneficial on pain in women but not in men. CONCLUSIONS: Taken together, these findings highlight the differential effects of social support in every-day life on chronic pain.

The Effect of Everyday-Life Social Contact on Pain.

Pain is a biopsychosocial phenomenon, resulting from the interplay between physiological and psychological processes and social factors. Given that humans constantly interact with others, the effect of social factors is particularly relevant. Documenting the significance of the social modulation of pain, an increasing number of studies have investigated the effect of social contact on subjective pain intensity and pain-related physiological changes. While evidence suggests that social contact can alleviate pain, contradictory findings indicate an increase in pain intensity and a deterioration of pain coping strategies. This evidence primarily stems from studies examining the effect of social contact on pain within highly controlled laboratory conditions. Moreover, pain assessments often rely on one-time subjective reports of average pain intensity across a predefined period. Ecological momentary assessments (EMAs) can circumvent these problems, as they can capture diverse aspects of behavior and experiences multiple times a day, in real time, with high resolution, and within naturalistic and ecologically valid settings. These multiple measures allow for the examination of fluctuations of pain symptoms throughout the day in relation to affective, cognitive, behavioral, and social factors. In this opinion paper, we review the current state and future relevance of EMA-based social pain research in daily life. Specifically, we examine whether everyday-life social support reduces or enhances pain. The first part of the paper provides a comprehensive overview of the use of EMA in pain research and summarizes the main findings. The review of the relatively limited number of existing EMA studies shows that the association between pain and social contact in everyday life depends on numerous factors, including pain syndromes, temporal dynamics, the nature of social interactions, and characteristics of the interaction partners. In line with laboratory research, there is evidence that everyday-life social contact can alleviate, but also intensify pain, depending on the type of social support. Everyday-life emotional support seems to reduce pain, while extensive solicitous support was found to have opposite effects. Moreover, positive short-term effects of social support can be overshadowed by other symptoms such as fatigue. Overall, gathering and integrating experiences from a patient's social environment can offer valuable insights. These insights can help interpret dynamics in pain intensity and accompanying symptoms such as depression or fatigue. We conclude that factors determining the reducing versus enhancing effects of social contact on pain need to be investigated more thoroughly. We advocate EMA as the assessment method of the future and highlight open questions that should be addressed in future EMA studies on pain and the potential of ecological momentary interventions for pain treatment.

Learning from Ingroup Experiences Changes Intergroup Impressions.

Humans form impressions toward individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Outgroup-focused theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals, while ingroup-focused theories predict that ingroup experiences play a dominant role. Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. While undergoing fMRI, male participants had identical experiences with different ingroup or outgroup members and rated their social closeness and impressions toward the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning, with larger effects in individuals with stronger ingroup identification. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. Neurally, the individual weight for ingroup prediction errors was related to the coupling between the left inferior parietal lobule and the left anterior insula, which, in turn, predicted learning-related changes in intergroup impressions. Our findings provide computational and neural evidence for ingroup-focused theories, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings.Significance Statement:Living in multicultural societies, humans interact with individuals of their own social groups (ingroup members) and of different social groups (outgroup members). However, little is known about how people learn from the mixture of ingroup and outgroup interactions, the most natural experiences in current societies. Here, participants had identical, intermixed experiences with different ingroup and outgroup individuals and rated their closeness and impressions toward the ingroup and the outgroup. Combining computational models and fMRI, we find that the weight given to ingroup experiences (ingroup prediction errors) is the main source of intergroup impression change, captured by changes in connectivity between the parietal lobe and insula. These findings highlight the importance of ingroup experiences in shaping intergroup impressions in complex social environments.

Why We Learn Less from Observing Outgroups.

Humans are less likely to learn from individuals belonging to a different group (outgroup) than from individuals of their own group (ingroup), yet the source of this societally relevant deficit has remained unclear. Here we used neuroimaging and computational modeling to investigate how people learn from observing the actions and outcomes of ingroup and outgroup demonstrators. Politically left-wing male and female participants performed worse when observing computer-simulated actions they believed were from a right-wing outgroup member compared with those from a left-wing ingroup member. A control experiment in which participants observed choices from a nonhuman agent confirmed that this performance difference reflected an outgroup deficit, rather than an ingroup gain. Accounting for the outgroup deficit, a computational model showed that participants relied less on information from outgroup actions compared with ingroup actions, while learning from outgroup outcomes was not impaired. At the neural level, the differences in observational ingroup versus outgroup learning were reflected in lateral prefrontal activity. The stronger the activity in this region, the more strongly participants weighed ingroup compared with outgroup learning signals (action prediction errors), which formally captured deficits in outgroup learning. Together, our work provides a computational and neural account of why people learn less from observing outgroups.SIGNIFICANCE STATEMENT Learning from observing others is an efficient way to acquire knowledge. In our globalized world, "the others" often are people from a different social group (outgroup). There is evidence that people learn less from observing outgroup individuals compared with individuals from their own group (ingroup). However, the source of this outgroup deficit in observational learning remained unknown, which limits our chances to improve intergroup learning. Our results showed that participants rely less on observed outgroup actions compared with ingroup actions, while learning from outgroup outcomes is not impaired. On the neural level, this outgroup deficit was reflected in the activation of the inferior frontal gyrus. These findings imply that intergroup learning should rely on observing outcomes, rather than actions.

The neural computation of human prosocial choices in complex motivational states.

Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modeling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants' choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors.

The impact of the COVID-19 pandemic on stress and other psychological factors in pregnant women giving birth during the first wave of the pandemic.

BACKGROUND: The onset of mental illness such as depression and anxiety disorders in pregnancy and postpartum period is common. The coronavirus induced disease 2019 (COVID-19) pandemic and the resulting public policy responses represent an exceptional situation worldwide and there are hints for adverse psychosocial impact, hence, the study of psychological effects of the pandemic in women during hospitalization for delivery and in the postpartum period is highly relevant. METHODS: Patients who gave birth during the first wave of the COVID-19 pandemic in Germany (March to June 2020) at the Department of Obstetrics and Gynecology, University of Würzburg, Germany, were recruited at hospital admission for delivery. Biosamples were collected for analysis of SARS-CoV-2 infection and various stress hormones and interleukin-6 (IL-6). In addition to sociodemographic and medical obstetric data, survey questionnaires in relation to concerns about and fear of COVID-19, depression, stress, anxiety, loneliness, maternal self-efficacy and the mother-child bonding were administered at T1 (delivery stay) and T2 (3-6 months postpartum). RESULTS: In total, all 94 recruited patients had a moderate concern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at T1 with a significant rise at T2. This concern correlated with low to low-medium general psychosocial stress levels and stress symptoms, and the women showed a significant increase of active coping from T1 to T2. Anxiety levels were low and the Edinburgh Postnatal Depression Scale showed a medium score of 5 with a significant (T1), but only week correlation with the concerns about SARS-CoV-2. In contrast to the overall good maternal bonding without correlation to SARS-CoV-2 concern, the maternal self-efficiency correlated negatively with the obstetric impairment caused by the COVID-19 pandemic. CONCLUSION: Obstetric patients` concerns regarding SARS-CoV-2 and the accompanying pandemic increased during the course of the pandemic correlating positively with stress and depression. Of note is the increase in active coping over time and the overall good mother-child-bonding. Maternal self-efficacy was affected in part by the restrictions of the pandemic. Clinical trial registration DRKS00022506.

The global pandemic of COVID-19 (coronavirus induced disease 2019) is challenging our society in many ways. Especially pregnant women are facing extraordinary conditions and worries, like uncertain risks for mother and fetus in case of infection, restricted prenatal classes or restricted visitor regulations in hospitals. Particularly it is known that pregnancy and the postnatal period are presenting a more psychologically vulnerable time in a woman's life. Developing the GeZeCO study, we aimed to focus on the pandemic's effects on mental health of pregnant women during this time. Women giving birth in the department of obstetrics of the University Hospital Würzburg were asked to participate in the study. In total, 94 women completed several questionnaires concerning their mental health postpartum and again after 3 to 6 months. Further, we took blood samples of the women during the delivery stay and registered sociodemographic and obstetric data. Our results showed, that the women's concern relating to COVID-19, as well as the level of depression and anxiety raised during the pandemic. In addition, the self-efficacy of the mothers was affected by the restriction measures. Despite this, the women had at large a good mother­child-bonding and their competence of active coping increased during time. In summary, we did find that the mental health of obstetric patients is impaired by the COVID-19 pandemic. This points out the importance of not only attending to physical health but also taking care of psychological stress and mental health problems of obstetric patients during this exceptional time.

[Seroprevalence of COVID-19 and Psychosocial Effects in the General Population: Results of the STAAB-COVID-One Program]. / Seroprävalenz von COVID-19 und psychosoziale Auswirkungen in der Allgemeinbevölkerung: Ergebnisse des STAAB-COVID-One Programms.

BACKGROUND: Research of SARS-CoV-2 has so far largely focused on symptomatic cases. The STAAB-COVID study therefore examined the seroprevalence of COVID-19 in the general population and the psychosocial effects of the pandemic. METHODS: From June-October 2020, a sub-study was conducted within the "Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression (STAAB)" cohort study. 4,860 study participants identified from a representative age-stratified sample of Würzburg residents were asked to provide a blood sample and to fill in a questionnaire. All participants also received an offer to take part in a point prevalence assessment (nasal swab taken from the participant at the beginning of November 2020). RESULTS: A total of 3,034 subjects took part in the STAAB-COVID program (response rate 62%). Antibodies against SARS-CoV-2 were detected in 33 participants (1.1%; 95% confidence interval 0.7-1.5%). Higher values on the GAD-7 anxiety scale were associated with lower rates of SARS-CoV-2 antibodies (Odds Ratio=0.78 for each+1 point in GAD-7; 95% confidence interval 0.65-0.95). Within this rather anxious group of subjects, however, the rate of cancellation of medical appointments was also increased (Odds Ratio=1.13 for each+1 point in GAD-7; 95% confidence interval 1.10-1.16). An acute infection was detected in six of a total of 2,451 participants in the point prevalence assessment (0.24%; 95% confidence interval 0.09-0.53%). CONCLUSION: Between the first and second COVID-19 waves in Germany, we found a low level of SARS-CoV-2 contamination in the city of Würzburg. A more anxious personality was associated with a lower seroprevalence. Conducting the study was largely facilitated by the existing cohort study.

The mere physical presence of another person reduces human autonomic responses to aversive sounds.

Social animals show reduced physiological responses to aversive events if a conspecific is physically present. Although humans are innately social, it is unclear whether the mere physical presence of another person is sufficient to reduce human autonomic responses to aversive events. In our study, participants experienced aversive and neutral sounds alone (alone treatment) or with an unknown person that was physically present without providing active support. The present person was a member of the participants' ethnical group (ingroup treatment) or a different ethnical group (outgroup treatment), inspired by studies that have found an impact of similarity on social modulation effects. We measured skin conductance responses (SCRs) and collected subjective similarity and affect ratings. The mere presence of an ingroup or outgroup person significantly reduced SCRs to the aversive sounds compared with the alone condition, in particular in participants with high situational anxiety. Moreover, the effect was stronger if participants perceived the ingroup or outgroup person as dissimilar to themselves. Our results indicate that the mere presence of another person was sufficient to diminish autonomic responses to aversive events in humans, and thus verify the translational validity of basic social modulation effects across different species.

How learning shapes the empathic brain.

Deficits in empathy enhance conflicts and human suffering. Thus, it is crucial to understand how empathy can be learned and how learning experiences shape empathy-related processes in the human brain. As a model of empathy deficits, we used the well-established suppression of empathy-related brain responses for the suffering of out-groups and tested whether and how out-group empathy is boosted by a learning intervention. During this intervention, participants received costly help equally often from an out-group member (experimental group) or an in-group member (control group). We show that receiving help from an out-group member elicits a classical learning signal (prediction error) in the anterior insular cortex. This signal in turn predicts a subsequent increase of empathy for a different out-group member (generalization). The enhancement of empathy-related insula responses by the neural prediction error signal was mediated by an establishment of positive emotions toward the out-group member. Finally, we show that surprisingly few positive learning experiences are sufficient to increase empathy. Our results specify the neural and psychological mechanisms through which learning interacts with empathy, and thus provide a neurobiological account for the plasticity of empathic reactions.

Pain relief provided by an outgroup member enhances analgesia.

Pain feels different in different social contexts, yet the mechanisms behind social pain modulation remain poorly understood. To elucidate the impact of social context on pain processing, we investigated how group membership, one of the most important social context factors, shapes pain relief behaviourally and neurally in humans undergoing functional neuroimaging. Participants repeatedly received pain relief from a member of their own group (ingroup treatment) or a member of a disliked outgroup (outgroup treatment). We observed a decrease in pain ratings and anterior insula (AI) pain responses after outgroup treatment, but not after ingroup treatment. Moreover, path analyses revealed that the outgroup treatment induced a stronger relief learning in the AI, which in turn altered pain processing, in particular if the participant entered the treatment with a negative impression toward the outgroup individual. The finding of enhanced analgesia after outgroup treatment is relevant for intergroup clinical settings. More generally, we found that group membership affects pain responses through neural learning and we thus elucidate one possible mechanism through which social context impacts pain processing.

Spatial gradient in value representation along the medial prefrontal cortex reflects individual differences in prosociality.

Despite the importance of valuing another person's welfare for prosocial behavior, currently we have only a limited understanding of how these values are represented in the brain and, more importantly, how they give rise to individual variability in prosociality. In the present study, participants underwent functional magnetic resonance imaging while performing a prosocial learning task in which they could choose to benefit themselves and/or another person. Choice behavior indicated that participants valued the welfare of another person, although less so than they valued their own welfare. Neural data revealed a spatial gradient in activity within the medial prefrontal cortex (MPFC), such that ventral parts predominantly represented self-regarding values and dorsal parts predominantly represented other-regarding values. Importantly, compared with selfish individuals, prosocial individuals showed a more gradual transition from self-regarding to other-regarding value signals in the MPFC and stronger MPFC-striatum coupling when they made choices for another person rather than for themselves. The present study provides evidence of neural markers reflecting individual differences in human prosociality.

Common and differential variables of anxiety and depression in adolescence: a nation-wide smartphone-based survey.

BACKGROUND: Mental health in adolescence is critical in its own right and a predictor of later symptoms of anxiety and depression. To address these mental health challenges, it is crucial to understand the variables linked to anxiety and depression in adolescence. METHODS: Here, we analyzed data of 278 adolescents that were collected in a nation-wide survey provided via a smartphone-based application during the COVID-19 pandemic. We used an elastic net regression machine-learning approach to classify individuals with clinically relevant self-reported symptoms of depression or anxiety. We then identified the most important variables with a combination of permutation feature importance calculation and sequential logistic regressions. RESULTS: 40.30% of participants reported clinically relevant anxiety symptoms, and 37.69% reported depressive symptoms. Both machine-learning models performed well in classifying participants with depressive (AUROC = 0.77) or anxiety (AUROC = 0.83) symptoms and were significantly better than the no-information rate. Feature importance analyses revealed that anxiety and depression in adolescence are commonly related to sleep disturbances (anxiety OR = 2.12, depression OR = 1.80). Differentiating between symptoms, self-reported depression increased with decreasing life satisfaction (OR = 0.43), whereas self-reported anxiety was related to worries about the health of family and friends (OR = 1.98) as well as impulsivity (OR = 2.01). CONCLUSION: Our results show that app-based self-reports provide information that can classify symptoms of anxiety and depression in adolescence and thus offer new insights into symptom patterns related to adolescent mental health issues. These findings underscore the potentials of health apps in reaching large cohorts of adolescence and optimize diagnostic and treatment.

Exposure traced in daily life: improvements in ecologically assessed social and physical activity following exposure-based psychotherapy for anxiety disorders.

BACKGROUND: Although exposure-based cognitive-behavioral therapy for anxiety disorders has frequently been proven effective, only few studies examined whether it improves everyday behavioral outcomes such as social and physical activity. METHODS: 126 participants (85 patients with panic disorder, agoraphobia, social anxiety disorder, or specific phobias, and 41 controls without mental disorders) completed smartphone-based ambulatory ratings (activities, social interactions, mood, physical symptoms) and motion sensor-based indices of physical activity (steps, time spent moving, metabolic activity) at baseline, during, and after exposure-based treatment. RESULTS: Prior to treatment, patients showed reduced mood and physical activity relative to healthy controls. Over the course of therapy, mood ratings, interactions with strangers and indices of physical activity improved, while reported physical symptoms decreased. Overall results did not differ between patients with primary panic disorder/agoraphobia and social anxiety disorder. Higher depression scores at baseline were associated with larger changes in reported symptoms and mood ratings, but smaller changes in physical activity CONCLUSIONS: Exposure-based treatment initiates increased physical activity, more frequent interaction with strangers, and improvements in everyday mood. The current approach provides objective and fine-graded process and outcome measures that may help to further improve treatments and possibly reduce relapse.

Mental health improvement after the COVID-19 pandemic in individuals with psychological distress.

The COVID-19 pandemic and associated countermeasures had an immensely disruptive impact on people's lives. Due to the lack of systematic pre-pandemic data, however, it is still unclear how individuals' psychological health has been affected across this incisive event. In this study, we analyze longitudinal data from two healthy samples (N = 307) to provide quasi-longitudinal insight into the full trajectory of psychological burden before (baseline), during the first peak, and at a relative downturn of the COVID-19 pandemic. Our data indicated a medium rise in psychological strain from baseline to the first peak of the pandemic (d = 0.40). Surprisingly, this was overcompensated by a large decrease of perceived burden until downturn (d = - 0.93), resulting in a positive overall effect of the COVID-19 pandemic on mental health (d = 0.44). Accounting for this paradoxical positive effect, our results reveal that the post-pandemic increase in mental health is driven by individuals that were already facing psychological challenges before the pandemic. These findings suggest that coping with acute challenges such as the COVID-19 pandemic can stabilize previously impaired mental health through reframing processes.

Depression and fatigue six months post-COVID-19 disease are associated with overlapping symptom constellations: A prospective, multi-center, population-based cohort study.

BACKGROUND: Depression and fatigue are commonly observed sequelae following viral diseases such as COVID-19. Identifying symptom constellations that differentially classify post-COVID depression and fatigue may be helpful to individualize treatment strategies. Here, we investigated whether self-reported post-COVID depression and post-COVID fatigue are associated with the same or different symptom constellations. METHODS: To address this question, we used data from COVIDOM, a population-based cohort study conducted as part of the NAPKON-POP platform. Data were collected in three different German regions (Kiel, Berlin, Würzburg). We analyzed data from >2000 individuals at least six months past a PCR-confirmed COVID-19 disease, using elastic net regression and cluster analysis. The regression model was developed in the Kiel data set, and externally validated using data sets from Berlin and Würzburg. RESULTS: Our results revealed that post-COVID depression and fatigue are associated with overlapping symptom constellations consisting of difficulties with daily activities, perceived health-related quality of life, chronic exhaustion, unrestful sleep, and impaired concentration. Confirming the overlap in symptom constellations, a follow-up cluster analysis could categorize individuals as scoring high or low on depression and fatigue but could not differentiate between both dimensions. LIMITATIONS: The data presented are cross-sectional, consisting primarily of self-reported questionnaire or medical records rather than biometric data. CONCLUSIONS: In summary, our results suggest a strong link between post-COVID depression and fatigue, highlighting the need for integrative treatment approaches.