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ORIGINAL RESEARCH article

Front. Psychiatry, 11 March 2022
Sec. Social Neuroscience
https://doi.org/10.3389/fpsyt.2022.804763

Exploring the Structure and Interrelations of Time-Stable Psychological Resilience, Psychological Vulnerability, and Social Cohesion

  • 1Social Neuroscience Lab, Max Planck Society, Berlin, Germany
  • 2Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Germany
  • 3Department of Psychiatry and Psychotherapy, Charité Campus Mitte (CCM), Charité – Universitätsmedizin Berlin, Berlin, Germany
  • 4Fliedner Klinik Berlin, Center for Psychiatry, Psychotherapy and Psychosomatic Medicine, Berlin, Germany
  • 5Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany

The current study explores the relationship between three constructs of high relevance in the context of adversities which have, however, not yet been systematically linked on the level of psychological dispositions: psychological vulnerability, psychological resilience, and social cohesion. Based on previous theoretical and empirical frameworks, a collection of trait questionnaires was assessed in a Berlin sample of 3,522 subjects between 18 and 65 years of age. Using a confirmatory factor analytical approach, we found no support for a simple three-factor structure. Results from exploratory structural analyses suggest that instead of psychological resilience and psychological vulnerability constituting two separate factors, respective indicators load on one bipolar latent factor. Interestingly, some psychological resilience indicators contributed to an additional specific latent factor, which may be interpreted as adaptive capacities, that is, abilities to adapt to changes or adjust to consequences of adversities. Furthermore, instead of evidence for one single social cohesion factor on the psychological level, indicators of perceived social support and loneliness formed another specific factor of social belonging, while indicators of prosocial competencies were found to form yet another distinct factor, which was positively associated to the other social factors, adaptive capacities and social belonging. Our results suggest that social cohesion is composed of different independent psychological components, such as trust, social belonging, and social skills. Furthermore, our findings highlight the importance of social capacities and belonging for psychological resilience and suggest that decreasing loneliness and increasing social skills should therefore represent a valuable intervention strategy to foster adaptive capacities.

Introduction

In light of the exacerbated global mental health challenges in the context of the COVID-19 pandemic, there is enduring and increasing interest in the various and complex accounts for the maintenance and recovery of mental health and psychological wellbeing. In the face of adversities, individuals show a variety of skills and abilities that are dispositional to the mitigation of negative impacts and potential long term mental health sequelae. In the psychological sciences, the two constructs that have prominently emerged and commonly been used to describe such individual dispositions are psychological vulnerability and psychological resilience, which will hereinafter be called vulnerability and resilience for the sake of brevity. While vulnerability involves a set of individual characteristics that promote susceptibility to harm (1, 2), resilience describes a general ability to bounce back in the aftermath of adversities (35). Over the past decades, conceptualizations of vulnerability and resilience have increasingly moved away from a mere focus on these individual characteristics, highlighting the role of socio-ecological systems for developmental outcomes when exposed to adversity (6, 7). Despite these process-oriented notions, dispositional vulnerability and resilience remain conceptually and empirically largely detached from social aspects.

While the concepts of vulnerability and resilience are mostly rooted in psychology and the clinical sciences, in more recent years, the concept of social cohesion emerged in the political and social sciences. It describes multidimensional and multilevel core mechanisms that unite individuals in social networks, and has also frequently been discussed to be relevant to fostering resilience, thereby expanding the focus of stress recovery to the level of communities and societies (811). Also on the individual level, social cohesion may be crucial for maintaining mental health in the face of severe stress, which is supported by the growing body of resilience research with focus on multisystemic dynamic processes to overcome adversity (6, 7, 12). Yet, given the heterogeneous origins of these different concepts on the individual level, so far, it remains unclear whether they can all be measured with existing time-stable psychometric indicators and how exactly the concept of social cohesion relates to the more established constructs of vulnerability and resilience. Using trait-based self-report measures as indicators for these individual characteristics and a factor analytical approach, the current study aims to integrate these three constructs in a unifying conceptual framework of psychological dispositions. More specifically, we focus on the questions whether different person-based aspects of social cohesion discussed in the literature can be conceptualized as a single social cohesion factor and whether this factor is indeed positively related to the concept of resilience or rather reflects a distinct capacity, which is also differentially related to aspects of vulnerability. To this end, we first review the psychological core constructs vulnerability and resilience and their existing integrative frameworks. Second, we review individual aspects of social cohesion as discussed in the literature, current social accounts in vulnerability and resilience frameworks and gaps thereof. Third, we outline our methodological approach toward an integrative psychological framework.

Vulnerability

Despite a variety of definitions of vulnerability, stemming from different research traditions, previous literature highlights a few core characteristics across disciplines that relate to exposure to external stressors or adversity, sensitivity to those stressors and response capacity (1, 13). In most contemporary studies, vulnerability is primarily measured in relation to aspects of exposure to risk or adversity, such as exposure to adverse childhood experiences, natural disasters or poverty. While exposure to severe and chronic stress is undoubtedly a postulated precursor of adverse outcomes, the degree to which individuals are negatively impacted varies in association with individual factors, as suggested by various diathesis-stress models (14). Trait vulnerability comprises psychological and genetic risk factors, which predispose people to a heightened stress sensitivity and maladaptive response capacity (15). A considerable amount of research has emphasized the role of neuroticism in stress vulnerability (16). Neuroticism is a major dimension of personality that is characterized by negative affectivity and maladjustment (17), as well as by quick and disproportional arousal when exposed to emotional stimuli (18). The association between neuroticism and exposure to stress is 2 fold, in that neuroticism may both predict the exposure to and amplify the impact of adversities (19). Similar to neuroticism, also trait anxiety is associated with negative affect and stress sensitivity, and has been suggested as a marker of vulnerability to distress and psychological disorders (20). It was suggested that a transdiagnostic underlying mechanism of this association between personality and vulnerability may be attributed to biased metacognitive beliefs and related coping styles (21). Research has shown that particularly dysfunctional cognitive strategies of emotion regulation such as self-blaming or catastrophizing play a crucial role in the relationship between adversity and maladjustment (22). Another cognitive bias relevant to the ability to adjust to negative life events is pessimism, a trait that describes generalized negative outcome expectancies (23). According to the control theory of self-regulation (24), such negative expectations about the likelihood of coping success may lead pessimists to withdraw goal-oriented coping efforts and thus increase the risk of suffering from adverse consequences of a stressful situation (25). A growing body of literature further highlights the role of loneliness, that is, perceived social isolation, in psychological vulnerability based on its impact on a variety of cognitive, physiological and biobehavioral processes (26). It is accompanied by a diminished capacity for self-regulation and increased feeling of stress, pessimism and anxiety (27). Based on this literature on psychological vulnerability, we thus chose to use single trait-based indicators of neuroticism, anxiety, stress, pessimism and loneliness to reflect the concept of vulnerability.

Resilience

Within the field of psychology, research on resilience represents a paradigm shift from a focus on risk factors of vulnerability to individual factors that promote adaptive responses to adversities (3, 28). However, as for the concept of vulnerability, several different frameworks have been suggested to describe resilience, and operationalization and measurement of this construct continues to be a challenge (29). In this sense, the term resilience is used to describe different phenomena, including resilient personality traits (3, 4), processes of dynamic adaptation and underlying mechanisms (3033), or developmental outcomes (34, 35).

While empirical resilience research has increasingly shifted focus toward complex and dynamic multisystem mechanisms and developmental progressions, the notion of resilience as an individual disposition on psychological level, which is adopted in the current study, has persisted over decades despite criticism (36, 37). These internal person-based characteristics are historically linked to the concept of ego-resiliency (38), and have also been referred to as resilience factors, a term subsuming individual aspects on genetic, biological, psychological or social levels that predict resilient outcomes (39).

Similar to vulnerability, resilience is generally viewed to unfold in the context of challenges, threats, adversity or potentially traumatic events, which is thus empirically fundamental to process-oriented resilience research on successful adaptation to perturbations (33, 4043). The current study was conducted in the context of the COVID-19 pandemic. However, the relationship between vulnerable and resilient trait characteristics, outcome trajectories and past or current adversity are not part of this paper and will be investigated in future studies of the ongoing CovSocial project. In sum, the current study focuses only on a subpart of resilience, that is, person-based psychological resilience, refraining from adversity exposure and underlying mechanisms of developmental resilience processes.

In its most basic meaning, trait resilience refers to the ability to bounce back or recover from adversities (4). Individual cognitive, affective and behavioral patterns that are aimed to reduce the negative impact of stressors, so called coping styles, are closely linked to this concept (44). While these patterns vary between individuals, theoretical and empirical attempts have been made to cluster phenotypes of coping styles with regards to their adaptive or maladaptive function or their likelihood of positive or negative outcomes (45). The likelihood to cope successfully is further related to dispositional optimism. As such, optimism is not only associated with resilient processes of adaptive self-regulation, but notions of resilience also convey optimistic expectations of overcoming adversities (46, 47). On a similar note, resilient adaptation to stress further goes along with satisfaction with life (48, 49). Even though life satisfaction is frequently used as a resilient outcome variable, it is fairly stable over time, and entails a general cognitive-judgmental tendency of comparing one's life circumstances with ideas of an ideal standard (50). Positive emotions in general are ascribed a crucial role in building resilient resources (3, 51). Another dispositional tendency to adaptively face adversities is self-compassion (52). Self-compassion describes a mindset of care, understanding and forgiveness toward oneself, as well as a felt connection with humanity and an ability to anchor an experience in the present moment instead of the past or the future (53). In sum, the psychological literature suggests that personality characteristics such as quick and effortless stress recovery, adaptive coping styles, optimism, satisfaction with life and self-compassion constitute important aspects of a resilient personality.

Integrative Frameworks for Vulnerability and Resilience

Several frameworks have been formulated to integrate dispositional vulnerability and resilience concepts. At the most fundamental level, vulnerability and resilience encompass different but complementary individual characteristics. Accordingly, resilience has early on be conceptualized as the positive counterpart to vulnerability (54), and as such on a continuum with vulnerability (55). Since phenomena that have been ascribed to the concept of resilience increasingly included good developmental outcomes and stress recovery in a high-risk population, this conceptual view is empirically supported by follow-up studies on the better-than-expected developmental course from childhood to adulthood in individuals, who had been identified as at-risk children due to unfavorable contexts like economic burdens, childhood adversity or parental mental illness (35, 54). However, these linkages are based on a view of resilience as developmental outcome and of vulnerability as exposure to risk and adversity. In contrast, empirical findings also point to unique aspects of resilience in the prediction of stress recovery and mental health (56, 57), supporting the notion that resilience is more than the mere absence of vulnerability. Drawing from socio-ecological frameworks, particularly the notion of adaptive capacity, that is, the ability to adapt to changes or adjust to consequences of adversities, has been considered pivotal for the distinction between vulnerability and resilience (13, 58, 59). Accordingly, adaptive capacity—though related to a general capacity of response entailed in the vulnerability concept—has been ascribed only to resilience. In biology, an adaptive trait indicates a feature of an organism, which allows the organism to secure adaptiveness, that is, to live and reproduce given environmental contingencies (60). In contrast to merely reactive responses to perturbations in biological systems, adaptive capacity in humans involves both reactive and proactive components. A “successful” adaptation is thereby biased toward growth and improvement, and thus goes beyond the capacity to cope and maintain a status quo (13, 61). While adaptive capacities are fundamental to conceptualizations of resilience as dynamic processes (33, 37, 41), there is a lack of conceptual clarity and differentiation with regards to adaptive trait dispositions entailed in resilience as compared to vulnerability.

Social Cohesion

The third concept of interest, the concept of social cohesion, is currently not so much discussed in the field of psychology than in the social sciences such as in sociology, political sciences and economics [although it has its roots also in early psychology, see (6264)], and has frequently been used in the public discourse by policymakers (65). Social cohesion includes micro, meso and macro systems of a society that refer to individuals, institutions and communities, respectively (66). In a nutshell, social cohesion can be defined as “indicator of the quality of social togetherness” [(67), p. 595]. On the individual level, it entails a subjective component that relates to subjective experiences, cognition and emotion, and an objective component that takes into account manifestations thereof in behaviors (65, 68).

Despite the concept of social cohesion not being discussed only in psychology and also being measured by objective systemic and macroscopic indicators such as inequality or network size, the focus of social cohesion in the present study is on the psychological individual dimensions, which can be measured through subjective self-report measures referring to person characteristics. This allows linking aspects of the broader construct of social cohesion to the well-known psychological constructs of resilience and vulnerability.

While a uniform conceptualization and operationalization of social cohesion remains a challenge (9, 69), literature reviews revealed reoccurring dimensions which can be operationalized within the means of psychology, specifically social engagement, trust, a sense of belonging and social interaction (6567).

More specifically, individual aspects of social cohesion empirically relate to patterns of social engagement and cooperation, the willingness to participate and help, which in terms of time-stable person characteristics (trait-measures) can be related to dispositions of prosocial motivation and tendencies (70). Prosocial tendencies play a crucial role in shaping group processes by contributing to inclusion or exclusion of group members and promoting social norms (71).

The quality of social relations is further proposed to relate to, or even be based upon trust (72). Trust describes an individual's expectancy of the predictability of others' behavior as well as good intentions thereof, which is promoted by time-stable individual characteristics and can be measured in attitudes about the trustworthiness of others (73). General trust as a response to social uncertainty enables individuals to take risks in the pursuit of opportunities (74). In line with this, feelings of trust have been related to the neuropeptide oxytocin, which beyond its involvement in social affiliation and attachment has been found to promote risk taking in social interactions (75). The notion of trust between individuals as a resource that enables social cohesion is related to implicit beliefs of shared norms and values (76). Together with social engagement and participation, social trust forms the basis of social capital by promoting collective resources and health (77).

Furthermore, an individual's sense of belonging positively impacts the quality of social interactions and social participation (65). A sense of belonging has been defined as “the experience of personal involvement in a system or environment so that the persons feel themselves to be an integral part of that system or environment” [(78), p. 173]. Social belonging can be considered a fundamental human need and motive, which guides human emotion and cognition (79). Feelings of belonging to a society thereby depend on a multitude of factors, including feelings of appreciation or receiving help from others (80). Measures of a sense of belonging thus reflect an individual's encoding of social experiences and social integration, including perceptions of the availability of social resources and support (78).

Finally, another aspect crucial for social cohesion is human sociality and social interaction. In psychology and the social neurosciences, human interaction and sociality have been extensively studied in terms of the underlying skill set needed for successful social interaction. Accordingly, individuals are equipped with different social abilities allowing to understand the affective (empathy) and mental states of others (cognitive perspective taking), which in turn influence the degree to which people show cooperative and prosocial behaviors (81, 82). Corroborated by neurobiological findings, a distinction can be made between a more cognitive understanding of others' thoughts and intentions, which can be referred to as mentalizing, Theory of Mind or perspective taking, and an affective resonance or affect sharing that is conceived of as empathy [for reviews see (83, 84)]. These socio-emotional and socio-cognitive processes are fundamental to effective and beneficial social interactions (85, 86). Indeed, they enable individuals not only to form individual relationships, but also to build solidarity and foster morality in communities (87, 88). Several trait-like scales such as the Interpersonal Reactivity Index (89) used here as a time-stable person disposition for social capacities have been developed to capture individual differences in the propensity of a person to react empathically or take the perspective of others in social interactions.

In sum, the review of the literature on social cohesion suggests an important role of following core aspects of social cohesion that can be captured on the subjective individual and psychological level as person-specific characteristics: prosocial engagement and tendencies, trust, social belonging and sociality reflected in social competencies of empathy and perspective taking.

Integrative Frameworks for Vulnerability, Resilience and Social Cohesion

Since resilience research has increasingly emphasized that a conceptualization of resilience with focus on the individual is not sufficient, the recognition of social resources like social support and attachment in resilience frameworks has a long tradition (29, 37). In this sense, social aspects like a caring family and skilled parenting, close relationships or social connections with community-members have been proclaimed as protective resilience factors (34). Besides, the existence of social justice, social identity and adherence to cultural values, practices and beliefs are associated with better developmental outcomes when facing adversity (90). In light of dynamic multisystemic approaches to resilience, successful adaptation is thus increasingly viewed as a process of complex interactions across several systems, including the socio-ecological contexts of an individual (7, 12). This also suggests that adaptation is only sustainable with the support of social systems (91).

Despite these advances in resilience research, a systematic investigation of the relationship between the psychological concepts of time-stable vulnerability and resilience, and the social science concept of social cohesion on the individual level is so far lacking. However, previous findings suggest a resilience promoting role of social cohesion on the level of communities, particularly in the context of disaster relief and prevention. In this regard, not only were indices of community resilience and social cohesion found to be positively related to each other (9294), yet predisaster levels of community social cohesion could even predict lower risk of mental disorders and psychological distress (11, 95). While these frameworks refer to the system-level of human-environment-interaction, it remains unclear whether similar associations between social cohesion and resilience also apply to the level of individual-based psychological personality dispositions.

To fill this gap and systematically explore the relationship between resilience, vulnerability and social cohesion on the individual psychological and subjective level, we conducted an in-depth investigation of how a variety of relevant psychological personality indicators of vulnerability, resilience and social cohesion assessed with well-known and validated psychological trait-questionnaires are empirically related based on factor analyses. At present, there are inconsistent conceptual and empirical links between pervasive and enduring psychological aspects of vulnerability and resilience, as well as a lack of systematic investigations of the empirical link between psychological aspects of social cohesion on the one hand and vulnerability and resilience on the other hand. We therefore tested whether there is indeed empirical evidence to propose three distinct yet interrelated factors of psychological dispositions, whereby the vulnerability factor should be negatively associated with the resilience and social cohesion factors, and the social cohesion and resilience factors are positively related to each other.

Methods

Sample

The current study was conducted as part of the longitudinal CovSocial project that aims to investigate the impact of the COVID-19 pandemic-related lockdown on a variety of biopsychosocial factors related to vulnerability, resilience and social cohesion in the Berlin population using a multi-measurement approach (for more details about the whole project see Supplementary Material 1). In addition to assessing the trait questionnaires reported in the current paper, the CovSocial project also included repeated assessment of state-like questionnaires with focus on pandemic specific questions throughout the years of 2020 and 2021. This longitudinal data is beyond the scope of this paper.

The target population for our study were residents of Berlin, Germany, between 18 and 65 years of age. The majority of prospective participants, that is, 56,000 people were invited to participate in this study via letters, with postal addresses randomly selected by the residents' registration office in Berlin. Additional outreach was attempted using e-mail lists of academic and research institutions, flyers at churches, and sports clubs, as well as posts on social media, and advertisement in newspapers and public transportation. A total of 7,214 participants signed up for the study (see Supplementary Material 1, Figure 5), 4,448 of which completed the first block of trait questionnaires, 3,868 completed the second, and 3,681 participants completed all three blocks of trait questionnaires relevant to this study (see Supplementary Material 1, Figure 6). Individuals who did not meet the inclusion criteria, that is, non-Berlin residents (n = 44) and people who were not between 18 and 65 years of age (n = 81) were excluded from the final sample. As all data were assessed online and in self-report, we further excluded participants due to response times which were deemed too fast to be reliable. A pilot trial with 5 staff members (mean age 23.8, SD = 2.77 years) that was conducted to evaluate technical feasibility of the implemented survey platform, was used to determine thresholds of maximal speed, that is, the fastest response time in each of the seven blocks of questionnaires was used as a threshold for the respective block. Participants with response times below the thresholds in at least two blocks of questionnaires (n = 30) were excluded from the analyses. Data from three participants were excluded due to technical issues with file saving, and data of one participant was deleted according to the participant's request. Demographic characteristics of the final study sample of n = 3,522 participants (mean age = 43.95, SD = 12.69, age range = 18–65 years, 65.11% female, 34.89% male) are presented in Supplementary Material 1, Section 4.

This study is in accordance with the Declaration of Helsinki and was approved by the Ethical Committee of the Charité – Universitätsmedizin Berlin, Germany (#EA4/172/20 and #EA1/345/20). All study participants provided written informed consent. No direct financial compensation was offered, yet five tablets were raffled using random selection among all participants who completed the questionnaires.

Study Design

The current study reports on validated trait measures assessed at study baseline of the CovSocial project. Data was assessed using online surveys that were implemented on the project-related web application (www.covsocial.de). Questionnaires were presented in seven blocks, using the same order of questionnaires and blocks for all subjects. Trait questionnaires were presented in block 3, 5 and 7, with median block process times between 5 (block 3) and 9 min (block 7). Other blocks included demographic assessments (block 1) and retrospective assessments of subjective experiences during the pandemic. The assessment period lasted from 11 September 2020 to 7 December 2020.

Measures

In the following, the trait-level questionnaires used in the current study are described (for full information about all other measures used in the CovSocial project, see Supplementary Material 1, Section 5). The trait-level questionnaires include six vulnerability indicators, five resilience indicators and 4 social cohesion indicators, which are listed in successive order.

Vulnerability

Chronic Stress

The short form of the Trier Inventory for Chronic Stress [TICS; (96)] was used to assess chronic exposure to stress. The 12 items refer to five distinct domains of stress, including social overload, work overload, lack of social recognition, excessive demands from work, chronic worrying. Items describe the experience of stress, e.g., “Sometimes I feel overburdened by my responsibilities toward others” that are rated on a five-point rating scale from “never” (=0) to “very often” (=4).

Neuroticism

The personality trait neuroticism was assessed using the NEO personality inventory [NEO-FFI; (17, 97)]. The neuroticism scale comprises 12 items that refer to the frequency of negative affectivity, e.g., “At times I have felt bitter and resentful” and are rated on a five-point rating scale from “strongly disagree” (=0) to “strongly agree” (=4).

Pessimism

Pessimism was assessed using the Revised Life Orientation Test [LOT-R; (98, 99)]. The scale comprises 3 negatively worded pessimistic statements, e.g., “I hardly ever expect things to go my way,” which are rated on a five-point rating scale ranging from “strongly disagree” (=0) to “strongly agree” (=4).

Trait Anxiety

To assess trait anxiety, the State-Trait-Anxiety-Inventory form X [STAI-X; (100, 101)] was used. This scale consists of 20 items (“I worry too much over something that really doesn't matter,” some of which are reverse coded. Items are rated on a four-point rating scale ranging from “almost never” (=1) to “almost always” (=4).

Loneliness

Trait loneliness was assessed using the UCLA Loneliness Scale (102, 103). Half of the 20 items reflect satisfaction, and the others reflect dissatisfaction with social relationships (e.g., “There is no one I can turn to”). Statements are rated on a four-point rating scale, ranging from “never” (=1) to “often” (=4).

Maladaptive Emotion Regulation Strategies

Three maladaptive emotion regulation strategies were assessed using the subscales self-blame (e.g., “I feel that I am the one who is responsible for what has happened”), catastrophizing (e.g., “I continually think about how horrible the situation has been”), and blaming others (e.g., “I feel that basically the cause lies with others”) from the short version of the Cognitive Emotion Regulation Questionnaire [CERQ; (22, 104)]. Each subscale consists of 3 items which can be answered on a five-point rating scale, ranging from “(almost) never” (=0) to “(almost) always” (=4).

Resilience

Stress Recovery

The ability to bounce back after stressful life events, which is assumed to be at the core of resilience, was assessed using the Brief Resilience Scale [BRS; (4)]. The scale consists of six items, three of which are reverse coded, that capture ease (e.g., “It is hard for me to snap back when something bad happens”) and speed (e.g., “I tend to bounce back quickly after hard times”) of recovery after a stressful life event. Items are rated on a five-point rating scale from “strongly disagree” (=1) to “strongly agree” (=5).

Optimism

Similarly to pessimism, optimism was assessed using the Revised Life Orientation Test [LOT-R; (98, 99)]. The optimism scale comprises 3 items, which are rated on a five-point rating scale ranging from “strongly disagree” (=0) to “strongly agree” (=4). Optimistic statements are worded positively, e.g., “I'm always optimistic about my future.” Several studies suggest that pessimism and optimism as measured with the LOT-R are independent constructs with orthogonal factor loadings (98, 105).

Satisfaction With Life

Satisfaction with life was assessed using the Satisfaction With Life Scale [SWLS; [48, (106)]. The SWLS consists of five items, e.g., “In most ways my life is close to my ideal,” each rated on a seven-point rating scale from “strongly disagree” (=1) to “strongly agree” (=7).

Self-Compassion

Self-compassion was assessed using the short form of the Self-Compassion Scale [SCS-SF; (107)]. The SCS-SF consists of six subscales and two items per subscale, respectively. Half of the subscales reflect a positive mindset, and half of them reflect a negative mindset. The three positive subscales of self-kindness (e.g., “I try to be understanding and patient toward those aspects of my personality I don't like”), common humanity (e.g., “I try to see my failings as part of the human condition”) and mindfulness (e.g., “When something painful happens I try to take a balanced view of the situation”) were selected. Items are rated on a five-point rating scale ranging from “almost never” (=1) to “almost always (=5).

Adaptive Coping

To assess coping strategies with relevance to resilient capacities, we employed selected subscales of the Brief-COPE (108). The Brief-COPE assesses each coping style in two items on a four-point rating scale from “not at all” (=1) to “very much” (=4). While no explicit recommendation is made by the author regarding an adaptive composite score of specific Brief-COPE subscales, several studies have found such a composite to be useful (109, 110). In a four-factor model, coping styles have been grouped into (1) problem-focused (active coping, e.g., “I've been taking action to try to make the situation better”; planning, e.g., “I've been trying to come up with a strategy about what to do”), (2) emotion-focused (positive reframing, e.g., “I've been looking for something good in what is happening”; acceptance, e.g., “I've been learning to live with it”; humor, e.g., “I've been making jokes about it”; religion, e.g., “I've been praying or meditating”), (3) socially supported (emotional support, e.g., “I've been getting emotional support from others”; instrumental support, e.g., “I've been getting help and advice from other people”; venting, e.g., “I've been expressing my negative feelings”) and (4) avoidant coping (behavioral disengagement, denial, substance use), and all coping styles except of avoidant coping have been found to correlate positively with quality of life in individuals exposed to chronic stress (111). In the current study, we therefore focus on coping styles apart from avoidant coping.

Social Cohesion

Trust

An inclination toward trust in other people was assessed using the General Trust Scale [GTS; (74)]. The GTS measures general levels of trust in the form of beliefs about other peoples' trustworthiness (e.g., “Most people are basically honest”). It consists of six items, which are rated on a five-point rating scale from “completely disagree” (=1) to “completely agree” (=5). The GTS was translated into German for the purpose of this study using Brislin's back-translation method (112). Accordingly, a bilingual person who was blinded to the original scale backtranslated the items to ensure equivalence of the translated scale.

Prosocialness

To measure prosocialness as a trait, the Prosocialness Scale for Adults [PSA; (113)] was used. It consists of 16 items that describe behavioral tendencies to help, take care of, assist or comfort others (e.g., “I help immediately those who are in need”). Items are rated on a five-point rating scale from “(almost) never true” (=1) to “(almost) always true” (=5).

Social Support

The Berlin Social Support Scales [BSSS; (114)] were used as an instrument to measure social support. The BSSS comprises 6 subscales that assess various dimensions of social support, categorizing support into two distinct types, namely perceived support and received support. Perceived support refers to the future oriented expectation that others will be available to provide assistance if needed. It was found to be more relevant to coping with stress than actually received support (115). In this study, we therefore only included items of the perceived support scale. This scale comprises four items that assess emotional, e.g., “Whenever I am sad, there are people who cheer me up.” and instrumental support, e.g., “There are people who offer me help when I need it.”, on a four-point rating scale from “strongly disagree” (=1) to “strongly agree” (=4).

Social Cognition and Emotion

The ability to empathize with another human being was assessed using the empathic concern subscale (e.g., “I feel sad when I see a lonely stranger in a group”), and the ability to take a cognitive perspective of others with the perspective taking subscale (e.g., “When I'm upset at someone, I usually try to put myself in his shoes for a while”) from the Interpersonal Reactivity Index [IRI; (89, 116)]. Selection of subscales was based on comparative measurement model analyses (117). The IRI subscales comprise four items concerning interpersonal thoughts and feeling that are rated in their frequency on a five-point rating scale from “never” (=1) to “always” (=5).

Data Analysis

Data statistical analyses were performed in R [version 3.6.3; (118)] using the lavaan package [version 0.6-9; (119)]. Confirmatory factor analyses (CFA) were conducted to test the proposed model with three distinct latent factors for vulnerability, resilience and social cohesion. Univariate and multivariate normal distributions were tested using Shapiro-Wilk tests and Mardia's test for multivariate normality (120). Since no missing data was given, composites for scales and subscales were computed as recommended by the respective questionnaire guidelines. Thus, averages were computed for the UCLA, BRS, GTS, BSSS, and PSA, and sums for the TICS, LOT-R subscales, NEO-FFI, STAI-X, CERQ subscales, SCS-SF subscales, Brief-COPE subscales, SWLS, and IRI subscales. Internal consistencies were determined using Cronbach's Alpha and compared to the norm samples of respective questionnaires (see Supplementary Table 3). For subscales of the CERQ, SCS-SF, Brief-COPE and IRI, scale-level composites were computed by averaging subscale scores.

In the CFA analyses, the variances of the latent factors were constrained to 1 and the means of the latent factors were constrained to 0 for identification purposes. All factor loadings, residual variances and intercepts of the manifest indicators were estimated. We used robust maximum likelihood estimation which provides more robust inferences in case of non-normality (121). Standard fit indices were computed, including the root mean square error of approximation (RMSEA), comparative fit index (CFI) and Tucker-Lewis index (TLI). Chi-square (χ2) statistics and degrees of freedom (df) are reported for each factor model. A model is considered acceptable with RMSEA <0.10 (122), CFI and TLI >0.90 (123). Manifest indicators with factor loadings <0.2 were removed from the factor models (124). Factor loadings >0.4 were considered sufficiently relevant. In case of insufficient model fit for the hypothesized three factor structure (see the project's Open Science Framework page at https://osf.io/jvb98), further analyses will be conducted with an exploratory approach. To explore possible reasons for model misfit, model modification indices based on the Lagrange Multiplier test were considered. If theoretically plausible, cross-loadings of factor indicators were allowed. Chi-square difference tests were used for comparing nested models. For all exploratory models, we used hold-out cross validation with a hold-out sample of 20% (n = 704], which was randomly selected from the study sample. Results were considered significant if p < 0.05.

Results

Scale Statistics

All unidimensional scales showed good internal consistencies ranging from Cronbach's Alpha of α = 0.73 (LOT-R pessimism) to 0.93 (BSSS; STAI-X) that were comparable to norm samples (Supplementary Table 3). Reliability was further assessed on scale-level for subscales of the CERQ, SCS-SF, Brief-COPE and IRI. Cronbach's Alpha for the SCS-SF showed good internal consistency with α = 0.77, 90% confidence interval (CI) [0.75, 0.78]. For the CERQ with α = 0.46, 90% CI [0.44, 0.49] and IRI with α = 0.62, 90% CI [0.59, 0.64] internal consistencies were below the defined cut-off score of 0.70 (125). Respective constructs of different emotion regulation strategies and empathic functioning were thus considered to be better represented by the subscales on those measures, which showed high internal consistencies (see Supplementary Table 3). The Brief-COPE showed good internal consistency when items of coping with religion were excluded from scale-level composites, α = 0.73, 90% CI [0.72, 0.75]. Neither univariate nor multivariate normality was given, p < 0.001.

Factor Analyses

A CFA was conducted to test the proposed three-dimensional factor structure (Model 1; Figure 1). Thereby, TICS, LOT-R pessimism, NEO-FFI neuroticism, STAI-X, CERQ subscales self-blame, blaming others and catastrophizing were modeled as the first latent factor (i.e., vulnerability), BRS, LOT-R optimism, SCS-SF, Brief-COPE and SWLS were modeled as the second latent factor (i.e., resilience) and GTS, BSSS, PSA and IRI subscales empathic concern and perspective taking were modeled as the third factor (i.e., social cohesion). While indicators had significant positive loadings on respective latent factors (p < 0.001), the overall model had a poor fit, χ2 = 6473.50, df = 132, CFI = 0.74, TLI = 0.70, RMSEA = 0.117, 90% CI [0.115, 0.120]. Strikingly, the expected negative correlation between the latent vulnerability and resilience factor was close to perfect with r = −0.93, p < 0.001. For this reason and for theoretical reasons regarding the association between resilience and vulnerability outlined above, an alternative factor model was considered.

FIGURE 1
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Figure 1. Proposed three-factor model of vulnerability, resilience and social cohesion with standardized factor loadings and correlations. Shapes represent following structural components: box = manifest indicator, circle = latent factor, arrow = factor loading of reflective indicators, bi-directional arrow = variance or covariance. Mean structure related elements are omitted for clarity.

In the alternative model (Model 2; Figure 2), the BRS, LOT-R optimism, SCS-SF, Brief-COPE and SWLS scales were modeled together with the TICS, LOT-R pessimism, NEO-FFI neuroticism, STAI-X, and CERQ scales as one general latent factor in the main sample. All scales that had been proposed as resilience indicators were found to have significant negative factor loadings on this general factor, while scales that were proposed as vulnerability indicators had significant positive factor loadings (p < 0.001). We therefore call this factor resilience-vulnerability. An additional factor was formed based on the residual variances of the BRS, LOT-R optimism, SCS-SF, Brief-COPE and SWLS scales. The scales that were proposed to indicate resilience were allowed to have cross-loadings on both the general factor and the specific factor, which are orthogonal to each other. All of the scales that were proposed as resilience indicators except for the BRS had significant positive loadings on the specific factor (p < 0.001). In accordance with conceptual distinctions between vulnerability and resilience in the literature (13), we call this specific latent factor adaptive capacities. Even though Model 2 performed better than the first model with three distinct latent factors, with χdiff2 = 736.29, dfdiff = 4, p < 0.001, the overall model fit was also poor, χ2 = 4456.59, df = 128, CFI = 0.78, TLI = 0.74, RMSEA = 0.111, 90% CI [0.107, 0.112].

FIGURE 2
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Figure 2. Three-factor model of resilience-vulnerability, adaptive capacities and social cohesion with standardized factor loadings and correlations. Shapes represent following structural components: box = manifest indicator, circle = latent factor, arrow = factor loading of reflective indicators, bi-directional arrow = variance or covariance. Mean structure related elements are omitted for clarity.

In a next step, Model 2 was further modified under consideration of factor loadings, modification indices and theoretical plausibility (Figure 3A). Due to its consistently low factor loading across all models (b < 0.2) and thus low consistency with other vulnerability indicators, the CERQ blaming others scale was dropped from the model. Similarly, GTS and BSSS consistently showed factor loadings below b = 0.4, and modification indices suggested that those scales load on the general factor, which may correspond to the role of perceived social support and general trust or a lack thereof in vulnerability. Modification indices suggested a strong residual correlation of BSSS and UCLA loneliness scales. This was considered theoretically plausible due to an association of measured constructs, namely perceived social support and perceived loneliness, which we represent by an additional specific factor. We call this factor social belonging. Residual variance of the GTS was further modeled as an additional indicator of the adaptive capacities factor. Besides, residual variance of the LOT-R pessimism scale was included as an indicator of the adaptive capacities factor, according to the notion that pessimism and optimism can be conceptualized as two poles of the same dimension (126). The PSA and IRI subscales empathic concern and perspective taking formed a stable latent factor without cross-loadings. We call this factor social capacities. Correlations between the specific factors and the general resilience-vulnerability factor were constrained to 0, correlations between the specific factors, between the specific factors and social capacities, and between the general factor and social capacities were estimated. The model was found to have an acceptable model fit with χ2 = 1592.44, df = 106, CFI = 0.93, TLI = 0.90, RMSEA = 0.071, 90% CI [0.068, 0.073]. Factor loadings on the resilience-vulnerability factor were significantly positive for scales that were proposed as vulnerability indicators. Scales that were proposed as resilience indicators and the GTS had consistently negative factor loadings on the resilience-vulnerability factor (Figure 3B). However, these scales had consistently positive factor loadings on the adaptive capacities factor, while the loading of LOT-R pessimism was negative on this factor. The social belonging factor was characterized by a positive factor loading of the BSSS and a negative factor loading of the UCLA loneliness scale. Correlations between the adaptive capacities and social belonging factor and between those factors and the social capacities factor were significantly positive (Figure 3A). The correlation between the resilience-vulnerability factor and the social capacities factor was not significant. This factor model could be validated in the hold-out sample of n = 704 with an acceptable model fit, χ2 = 547.59, df = 106, CFI = 0.92, TLI = 0.90, RMSEA = 0.073, 90% CI [0.067, 0.079] (Supplementary Table 4).

FIGURE 3
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Figure 3. (A) Empirical factor model of vulnerability, adaptive capacities, social belonging and social capacities in n = 2,818 subjects. Shapes represent following structural components: box = manifest indicator, circle = latent factor, circle with dashed line = specific latent factor, arrow = factor loading of reflective indicators, bi-directional arrow = variance or covariance. Blaming others was dropped as an indicator in this model. Standardized correlations with significance level *α = 0.001. (B) Significant standardized factor loadings of all indicators on the latent factors.

Discussion

The main goal of the current study was to systematically investigate the relationship between the three theoretical concepts of psychological vulnerability, psychological resilience and social cohesion using psychological trait-questionnaire indicators and a factor analytical approach. A literature review revealed inconclusive theoretical and empirical support for the relationship between the two widely used psychological constructs of vulnerability and resilience on the level of personality dispositions. Besides, despite increasing evidence of multisystemic dynamic resilience processes (6, 7), there is a lack of conceptual and empirical person-based links to the construct of social cohesion—originating in political and social sciences. Therefore, in a first step, we tested whether there is empirical evidence for a three-factor model with three distinctive yet intercorrelated factors of time-stable psychological dispositions with negative relationships between vulnerability and both resilience and social cohesion, and a positive correlation between social cohesion and resilience.

Bipolar Resilience-Vulnerability Factor

In contrast to the proposed three-factor model, dispositional scales that had been selected as key resilience and vulnerability indicators formed one general bipolar latent factor, with consistently positive factor loadings for vulnerability scales and negative loadings for resilience scales. Accordingly, this large vulnerability/resilience factor supports the notion of complementarity between vulnerable and protective individual dispositions (54, 55). Resilience and vulnerability have often been viewed as opposite poles of a continuum reflecting higher or lower susceptibility to adverse consequences when exposed to high-risk conditions of severe and/or chronic stress (35, 55). Under a unipolar perspective, resilience has initially even been termed invulnerability (127) and vulnerability has at times been termed non-resilience (128). However, in light of many contemporary conceptualizations of resilience as dynamic process or outcome trajectory (30) and of vulnerability in the context of exposure to risk or adversity, this result naturally depends on the operationalization of vulnerability and resilience that was chosen in this study. Using a large sample and multiple measures, our study thus confirms that a mere focus on time-stable trait constructions of vulnerability and resilience might be conceptually problematic. Contemporary approaches to vulnerability and resilience, which highlight the complex dynamic interplay of genetic, biological, psychological, social and ecological systems in the context of exposure to risk, challenges, adversity and potential traumatic events (6, 7, 12), might be more accurate and robust.

With regards to cognitive emotion regulation strategies, a disposition to blaming others was found to have a low factor loading on the vulnerability/resilience factor (<0.2) and was removed from the model (124). In accordance with this, previous research has similarly found high correlations between the CERQ subscales of self-blame and catastrophizing, and anxiety sensitivity, while the subscale of blaming others was found to correlate only moderately (104).

Furthermore, two trait scales that had been proposed as indicators of social cohesion, namely general trust and perceived social support, were found to significantly load on the latent vulnerability/resilience factor in a reversed manner, that is, lower levels of perceived social support and trust indicated higher levels of psychological vulnerability. This might not come as a surprise, considering that the mere definition of trust across various disciplines has been related to vulnerability at its core. Scholars have referred to trust as “willingness to be vulnerable” (129) or an “intention to accept vulnerability based upon positive expectations” (130). While some theoretical discourse revolves around the role of trust in acceptance, precaution or cause of vulnerability (131), there is only limited empirical evidence for a relationship between trust and vulnerability, particularly on the individual level. Yet, trust and breach thereof has been proposed to be of crucial value in various moments of crises (132, 133). Particularly, trust-related motifs of affiliation and attachment (75), as well as of commitment in times of social uncertainty (74), can be seen as resilience promoting.

Adaptive Capacities Factor

Beyond this general resilience-vulnerability factor, which captures vulnerability and resilience aspects in a bipolar manner, we found that residual variances of those scales that had been considered indicative of resilient dispositions form another specific latent factor with consistent positive factor loadings. The residuals thus share common variance that is unexplained by the resilience-vulnerability factor. This additional factor may capture specific adaptive capacities present in the concept of resilience, which are not covered by the general resilience-vulnerability factor. Drawing from socio-ecological frameworks (13, 58, 59), both resilience and vulnerability have been related to a general ability to respond in the face of adversities, yet this response or reactive capacity differs from the more active capacity of long-term adaptation that has been proposed to be a unique feature of the concept of resilience (59). Adaptation thereby refers to long-term adjustments, while response capacity is considered rather short-term (61). Adaptive capacities of resilience have thus been conceptualized as dynamic capacities in a state space, enabling individuals not only to recover from adversities but also to improve conditions and achieve personal growth (134, 135). As such, in contemporary frameworks of resilience as a dynamic process, adaptive capacities are seen as resilience enablers that mediate impacts of adversity on adaptive or better-than-expected outcomes (6, 7). On a similar note, a concept to capture positive psychological change after suffering from adversity or a traumatic event is post-traumatic growth (136). Post-traumatic growth describes developmental transformations that go beyond an ability to resist or bounce back. Despite conceptual relatedness, there are crucial distinctions between the concepts of resilience and post-traumatic growth, particularly with regards to suffering as a prerequisite of growth. Indeed, highly resilient individuals might only experience relatively little growth (137). On the other hand, post-traumatic growth is enabled by adaptive cognitive abilities and processes such as positive reappraisal (136). Therefore, the factor of adaptive capacities in contrast to the resilience-vulnerability factor might be relevant to such developmental growth trajectories.

Consistent with such views, the Brief Resilience Scale showed a low factor loading (<0.20) and was not found to significantly relate to the adaptive capacities factor in the hold-out sample. The BRS assesses resilience in its original and most basic meaning, that is, as the ability to bounce back and recover from stress (4). It has previously been argued that the BRS may be unique in this respect and that other measures of resilience target individual characteristics that may promote positive adaptation (138). Most pronounced, the coping strategies that were assessed as indicators for resilience, namely problem-focused, emotion-focused and socially supported coping can be seen as indicative of adaptive capacities. These coping strategies showed highest factor loading on the adaptive capacities factor. While maladaptive coping strategies may also reduce stress in the short term, adaptive coping strategies that promote active engagement with the stressor or with one's own reaction to it are proposed to promote long-term stress reduction and wellbeing and are thus perceived as more effective (139). Yet, it should be kept in mind that even though we are referring to these coping strategies as adaptive, the Brief-COPE does not offer a clear rationale for the grouping of coping strategies into adaptive and maladaptive strategies (108). It is further important to note that coping with religious or spiritual belief was not included in the composite score of Brief-COPE due to a lack of scale consistency with the other coping strategies, a finding that has occurred repeatedly in previous literature (140). Other indicators of the adaptive capacities factor include the scales of self-compassion, satisfaction with life, optimism—and pessimism in a reversed manner—and trust. In light of adaptation, these individual dispositions are all characterized by a set of positive beliefs and expectations in overcoming uncertainty, ambiguity and contingencies. These anticipations may signal safety in the face of adversities and thus promote motivation and behavior toward improvement and growth.

Interrelation of Social Cohesion, Resilience-Vulnerability and Adaptive Capacities

In contrast to the original three-factor model, we did not find a distinct factor of psychological trait indicators of social cohesion. On the contrary, the trait-based scales chosen to be relevant to the four chosen core dimensions of social cohesion (social engagement, trust, belonging, social interaction) were found to load on three different factors. As discussed before, the scale of general trust or a lack thereof was found to relate to adaptive capacities and resilience-vulnerability, which highlights the role of trust in maintaining mental health and adaptive coping, going beyond its role in promoting social ties between individuals, societies and organizations (77). A sense of social belonging was reflected in a second distinct factor which entailed both perceived social support and perceived loneliness scales in a bipolar manner. The third distinct factor, social capacities, included the scales of empathy and perspective taking, which have been proposed as affective and cognitive routes of social understanding enabling successful social interactions (85, 86), together with prosocial tendencies. This is corroborated by findings that socio-emotional and socio-cognitive abilities may indeed be precursors of altruistic prosocial motivation and behavior (83, 141). Overall, the observation of the lack of an overarching factor for psychological dimensions of social cohesion, suggests that social cohesion on the individual level referring to person characteristics rather represents a heterogeneous concept with clearly distinguishable aspects such as social capacities, social belonging and adaptive capacities.

The understanding of this distinction in different dimensions for trust, social belonging and social capacities or skills, can further be enriched by adopting a network perspective of social capital. Social capital describes both the resources in a given social network and the processes by which those resources are obtained (142). From a network perspective, social capital is classified by three different types of network characteristics, that is, bonding, bridging and linking social capital (143). Bonding characterizes resources and processes within a social group that promote group membership and social identity. Bridging on the other hand describes resources and processes to overcome cleavages between social groups. As such, it promotes social relations between individuals despite a lack of shared social identity (144). Linking describes the extent to which individuals build social relations with others who have relative power or authority over them. Linking characterizes norms of respect and trusting relationships (143). In light of this, a sense of social belonging may be considered a precondition of bonding, social capacities like empathy, perspective taking and prosocial tendencies a precondition of bridging, and trust a precondition of linking social capital.

Interestingly, the two specific factors of adaptive capacities and social belonging, as well as the factor of social capacities were found to positively relate to each other. It can be argued that an underlying commonality of all three factors is their social nature, that is, that the indicators loading on these factors all include some social and intersubjective dimensions. Thus, even the less obvious factor of adaptive capacities is characterized by social indicators including trust and socially supported coping strategies. Interestingly, not only intersubjective qualities, also intra-subjective skills of self-compassion are indicative of the adaptive capacities factor; an observation in line with the notion that self-compassion requires creating a relationship to oneself (53). The positive interrelation of adaptive and social capacities further suggests that social skills like empathy and perspective taking may promote adaptive coping with stress and thus a maintenance of mental health. Similarly, social capacities and a sense of social belonging foster social support networks, the experience of more meaningful relationships and post-traumatic growth in the aftermath of adversity (136). This notion is supported by the hypothesis of social regulation, which argues that social relationships can mitigate adverse effects and promote health and wellbeing in the face of stressful life events (145). Social contact was found to attenuate stress responses on a neural systems level, which is related to the regulation of emotional and behavioral threat responses (146). In the light of evolution, phylogenetic development has led to neurophysiological responses associated with social behavior that are indeed linked to adaptive coping with stress (147). According to the social baseline theory (148), human brains are even more so prepared to expect an access to social relationships and the implicitly related abundance of beneficial outcomes. Social proximity is therefore considered to contribute to a baseline state of brain function, while an absence of those social resources increases physiological effort. Thus, social capacities and social belonging can be seen as dispositions that enable adaptation and rebound in the face of adversity. This corroborates notions of the social-ecological model of resilience (6, 7) that particularly highlight the resilience enabling properties of social networks and relationships. In future research, network analysis may be a suitable approach to further the exploratory results of our reflective measurement model and to gain an understanding of the causal relations between indicators of adaptive capacities, social belonging, social capacities and vulnerability or resilience (149).

Limitations

Since the current study is limited to a sample of Berlin residents, caution is advised regarding a generalization of findings to other populations. The study sample shows no normal distribution with regards to demographic data. Therefore, the assessment of trait indicators might have been biased. This is especially relevant in relation to an exposure to risk and adversity, since it is well-known that demographic variables such as education, gender or socio-economic status can represent protection or risk factors. Future analyses will be necessary to shed light on different outcome trajectories of resilience and vulnerability, and their prediction by demographic variables. Besides, online surveys bear a risk of response bias. This was addressed by the exclusion of participants based on critically low processing time.

Even though the scales that were employed in this study are assumed to measure fairly stable trait dispositions, the context of the COVID-19 pandemic, during which data was assessed, may have introduced some bias. This is particularly due to the fact that the measured characteristics relate to individual responses to stressors and adversities. Moreover, the majority of empirical support for a dichotomy of resilience and vulnerability focuses on the existence or absence of negative outcomes in the aftermath of severe stress [see for a review (150)], while the current study focuses on individual predispositions as indicators of vulnerability and resilience. Since these trait indicators are not empirically linked to individual outcomes in the context of adversity, their actual vulnerability- or resilience-enabling properties could not be measured by this study. In the broader context of the CovSocial project, a relationship between resilient trait characteristics, past and present adversity and outcome trajectories over the course of the pandemic will be investigated in more detail.

It is further important to notice that the selection of indicators for the concepts of vulnerability, resilience and social cohesion is non-exhaustive. The selection, however, is based on literature reviews with the attempt to capture key aspects of each construct as measurable through psychological trait scales. Particularly with regard to social cohesion indicators, a lack of adequate psychological trait measures to operationalize this construct, which did not originate in the field of psychology, might have led to a limited conceptual representation. The broad concept of social cohesion also includes objective facets reflecting for example economic inequality, social network size, and behavioral markers. Therefore, the present study only allows to draw conclusions about the individual subjective dimension of social cohesion. Lastly, questionnaires were presented in the same sequence for all subjects. This might have introduced a sequence effect to the self-report on measures.

Conclusion

This study shed light on the interrelationship between three widely used concepts on a level of psychological trait dispositions: psychological vulnerability, psychological resilience and social cohesion. In contrast to the assumption that these three concepts represent distinct factors, the pattern of results paints a more complex picture, furthering an understanding of dispositional risk and protective factors within the bounds of the study conceptualization, operationalization and scale selection. Whereas, the trait-scale indicators of vulnerability and resilience load on a single factor, thus representing two facets of the same coin, interestingly some unique residual variance in the resilience indicators form a specific factor reflecting adaptive coping capacities. In contrast, the identified social cohesion indicators of trust, belonging, social engagement and interaction did not load on a single social cohesion factor but rather two further factors emerged: social belonging and social capacities, which in turn were positively intercorrelated with the adaptive capacities factor. This study highlights the relevance of social capacities and social belonging for the capacity to resiliently cope with stressors and adversity, thereby confirming notions of resilience enabling properties of social systems entailed in process-oriented conceptualizations of resilience. It further provides novel empirical evidence of a relation between trust and psychological vulnerability. Strikingly, a sense of social belonging and not feeling lonely could be identified as a specific factor. Based on this finding, feelings of belonging can be conceptualized neither as only an inverse characteristic of psychological vulnerability nor as a part of other social capacities and skills but form a category on their own. In light of the increasing numbers of people feeling lonely, especially augmented in times of social isolation during the COVID-19 pandemic, intervention programs may specifically focus on how to help reduce loneliness and foster feelings of belonging. Furthermore, mental trainings that aim at increasing social skills such as empathy and perspective taking can also be considered valuable prevention and intervention targets to promote an increase in adaptive capacities in the face of stress and adversities.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethical Committee of the Charité – Universitätsmedizin Berlin, Germany (#EA4/172/20 and #EA1/345/20). The patients/participants provided their written informed consent to participate in this study.

Author Contributions

TS and MA initiated the project. TS as principal investigator, developed the main conceptual backbone for the covsocial project. TS and SS worked out the technical details including app development. SS performed data collection under the supervision of TS. SS and MH performed data analyses under supervision of MV and TS. SS wrote the paper with input from all authors. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

This study forms part of the CovSocial Project, headed by TS (principal investigator) and funded in majority by funds from the Social Neuroscience Lab of the Max Planck Society. Data for this project were collected between 2020 and 2021 at the Max Planck Social Neuroscience Lab in Berlin. TS together with MA and four other cooperation partners received a kick-off grant for the CovSocial Project in 2020 funded through the Berlin University Alliance (BUA) as part of the Excellence Strategy of the German federal and state governments [grant agreement number 114_GC_Pandemie_23]. We also thank Ella Heinz, Sarah Koop, Karen Joachim, Jessie Rademacher, Noemi Duroux, Eva Kellmann, Juliane Domke, and Thomas Feg for their help in organizing, preparing and collecting the data for this project.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2022.804763/full#supplementary-material

References

1. Adger WN. Vulnerability. Glob Environ Change. (2006) 16:268–81. doi: 10.1016/j.gloenvcha.2006.02.006

CrossRef Full Text | Google Scholar

2. Ingram R, Miranda J, Segal Z. Cognitive vulnerability to depression. In: Alloy LB, Riskind JH, editors. Cognitive Vulnerability to Emotional Disorders. New York: Lawrence Erlbaum Associates (2006). p. 63–91.

Google Scholar

3. Ong AD, Bergeman CS, Bisconti TL, Wallace KA. Psychological resilience, positive emotions, and successful adaptation to stress in later life. J Pers Soc Psychol. (2006) 91:730–49. doi: 10.1037/0022-3514.91.4.730

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Smith BW, Dalen J, Wiggins K, Tooley E, Christopher P, Bernard J. The brief resilience scale: assessing the ability to bounce back. Int J Behav Med. (2008) 15:194–200. doi: 10.1080/10705500802222972

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Tugade MM, Fredrickson BL. Resilient individuals use positive emotions to bounce back from negative emotional experiences. J Pers Soc Psychol. (2004) 86:320–33. doi: 10.1037/0022-3514.86.2.320

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Masten Ann S, Lucke CM, Nelson KM, Stallworthy IC. Resilience in development and psychopathology: multisystem perspectives. Annu Rev Clin Psychol. (2021) 17:521–49. doi: 10.1146/annurev-clinpsy-081219-120307

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Ungar M, Theron L. Resilience and mental health: how multisystemic processes contribute to positive outcomes. Lancet Psychiatry. (2020) 7:441–8. doi: 10.1016/S2215-0366(19)30434-1

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Fone D, Dunstan F, Lloyd K, Williams G, Watkins J, Palmer S. Does social cohesion modify the association between area income deprivation and mental health? A multilevel analysis. Int J Epidemiol. (2007) 36:338–45. doi: 10.1093/ije/dym004

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Friedkin NE. Social cohesion. Annu Rev Sociol. (2004) 30:409–25. doi: 10.1146/annurev.soc.30.012703.110625

CrossRef Full Text | Google Scholar

10. Gapen M, Cross D, Ortigo K, Graham A, Johnson E, Evces M, et al. Perceived neighborhood disorder, community cohesion, and PTSD symptoms among low-income African Americans in an Urban health setting. American Journal of Orthopsychiatry. (2011) 81:31–7. doi: 10.1111/j.1939-0025.2010.01069.x

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Greene G, Paranjothy S, Palmer SR. Resilience and vulnerability to the psychological harm from flooding: the role of social cohesion. Am J Public Health. (2015) 105:1792–5. doi: 10.2105/AJPH.2015.302709

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Panter-Brick C. Culture and resilience: next steps for theory and practice. In: Theron LC, Liebenberg L, Ungar M, editors. Youth Resilience and Culture: Commonalities and Complexities. Dordrecht: Springer (2015). p. 233–44. doi: 10.1007/978-94-017-9415-2_17

CrossRef Full Text | Google Scholar

13. Gallopín GC. Linkages between vulnerability, resilience, and adaptive capacity. Glob Environ Change. (2006) 16:293–303. doi: 10.1016/j.gloenvcha.2006.02.004

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Ingram R, Luxton DD. Vulnerability-stress models. In: Hankin BL , Abela JRZ, editors. Development of Psychopathology: A Vulnerability-Stress Perspective. New York: SAGE Publications (2005). p. 1–510.

Google Scholar

15. Bale TL. Stress sensitivity and the development of affective disorders. Horm Behav. (2006) 50:529–33. doi: 10.1016/j.yhbeh.2006.06.033

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Ormel J, Jeronimus BF, Kotov R, Riese H, Bos EH, Hankin B, et al. Neuroticism and common mental disorders: meaning and utility of a complex relationship. Clin Psychol Rev. (2013) 33:686–97. doi: 10.1016/j.cpr.2013.04.003

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Costa PT, McCrae RR. Neo Personality Inventory-Revised (NEO PI-R). Oxford: Psychological Assessment Resources (1992).

Google Scholar

18. Eysenck SBG, Eysenck HJ, Barrett P. A revised version of the psychoticism scale. Pers Individ Dif. (1985) 6:21–9. doi: 10.1016/0191-8869(85)90026-1

CrossRef Full Text | Google Scholar

19. Ormel J, Oldehinkel AJ, Brilman EI. The interplay and etiological continuity of neuroticism, difficulties, and life events in the etiology of major and subsyndromal, first and recurrent depressive episodes in later life. Am J Psychiatry. (2001) 158:885–91. doi: 10.1176/appi.ajp.158.6.885

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Mincic AM. Neuroanatomical correlates of negative emotionality-related traits: a systematic review and meta-analysis. Neuropsychologia. (2015) 77:97–118. doi: 10.1016/j.neuropsychologia.2015.08.007

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Nordahl H, Hjemdal O, Hagen R, Nordahl HM, Wells A. What lies beneath trait-anxiety? Testing the self-regulatory executive function model of vulnerability. Front Psychol. (2019) 10:122 doi: 10.3389/fpsyg.2019.00122

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Garnefski N, Kraaij V. Cognitive emotion regulation questionnaire - development of a short 18-item version (CERQ-short). Pers Individ Dif. (2006) 41:1045–53. doi: 10.1016/j.paid.2006.04.010

CrossRef Full Text | Google Scholar

23. Segerstrom SC, Evans DR, Eisenlohr-Moul TA. Optimism and pessimism dimensions in the Life Orientation Test-Revised: method and meaning. J Res Pers. (2011) 45:126–9. doi: 10.1016/j.jrp.2010.11.007

CrossRef Full Text | Google Scholar

24. Scheier MF, Carver CS. A model of behavioral self-regulation: translating intention into action. In: Advances in Experimental Social Psychology. Academic Press (1988). vol. 21. p. 303–46. doi: 10.1016/S0065-2601(08)60230-0

CrossRef Full Text | Google Scholar

25. Blanton H, Axsom D, McClive KP, Price S. Pessimistic bias in comparative evaluations: a case of perceived vulnerability to the effects of negative life events. Pers Soc Psychol Bull. (2001) 27:1627–36. doi: 10.1177/01461672012712006

CrossRef Full Text | Google Scholar

26. Hawkley LC, Cacioppo JT. Loneliness matters: a theoretical and empirical review of consequences and mechanisms. Ann Behav Med. (2010) 40:218–27. doi: 10.1007/s12160-010-9210-8

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Cacioppo JT, Hawkley LC, Ernst JM, Burleson M, Berntson GG, Nouriani B, et al. Loneliness within a nomological net: an evolutionary perspective. J Res Pers. (2006) 40:1054–85. doi: 10.1016/j.jrp.2005.11.007

CrossRef Full Text | Google Scholar

28. Vella S-L, Pai NB. A theoretical review of psychological resilience: defining resilience and resilience research over the decades. Arch Med Health Sci. (2019) 7:233. doi: 10.4103/amhs.amhs_119_19

CrossRef Full Text | Google Scholar

29. Fletcher D, Sarkar M. Psychological resilience: a review and critique of definitions, concepts and theory. Eur Psychol. (2013) 18:12–23. doi: 10.1027/1016-9040/a000124

CrossRef Full Text | Google Scholar

30. Bonanno GA. Clarifying and extending the construct of adult resilience. Am Psychol. (2005) 60:265–167. doi: 10.1037/0003-066X.60.3.265b

CrossRef Full Text | Google Scholar

31. Fergus S, Zimmerman MA. Adolescent resilience: a framework for understanding healthy development in the face of risk. Annu Rev Public Health. (2005) 26:399–419. doi: 10.1146/annurev.publhealth.26.021304.144357

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Luthar SS, Cicchetti D, Becker B. The construct of resilience: a critical evaluation and guidelines for future work. Child Dev. (2000) 71:543–62. doi: 10.1111/1467-8624.00164

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Ungar M. Systemic resilience: principles and processes for a science of change in contexts of adversity. Ecol Soc. (2018) 23:34. doi: 10.5751/ES-10385-230434

CrossRef Full Text | Google Scholar

34. Masten AS. Ordinary Magic: Resilience in Development. London: Guilford Press (2014).

PubMed Abstract | Google Scholar

35. Rutter M. Resilience as a dynamic concept. Dev Psychopathol. (2012) 24:335–44. doi: 10.1017/S0954579412000028

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Kalisch R, Cramer AOJ, Binder H, Fritz J, Leertouwer I, Lunansky G, et al. Deconstructing and reconstructing resilience: a dynamic network approach. Perspect Psychol Sci. (2019) 14:765–77. doi: 10.1177/1745691619855637

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Masten AS, Cicchetti D. Resilience in development: progress and transformation. In: Cicchetti D, editor. Risk, Resilience, and Intervention. 3rd ed. New Jersey: Wiley (2016). p. 271–333. doi: 10.1002/9781119125556.devpsy406

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Block JH, Block J. The role of ego-control and ego-resiliency in the organization of behavior. In: Development of Cognition, Affect, and Social Relations. New York: Psychology Press (2014). p. 49–112.

Google Scholar

39. Kalisch R, Müller MB, Tüscher O. A conceptual framework for the neurobiological study of resilience. Behav Brain Sci. (2015) 38:e92. doi: 10.1017/S0140525X1400082X

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Cicchetti D. Annual research review: resilient functioning in maltreated children - Past, present, and future perspectives. J Child Psychol Psychiatry Allied Discipl. (2013) 54:402–22. doi: 10.1111/j.1469-7610.2012.02608.x

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Folke C. Resilience. Ecol Soc. (2016) 21. doi: 10.5751/ES-09088-210444

CrossRef Full Text | Google Scholar

42. Luthar SS, Crossman EJ, Small PJ. Resilience and adversity. In: Lerner RM, Lamb ME, editors. Handbook of Child Psychology and Developmental Science. 7th ed. Wiley (2015). vol. 3, p. 247–86. doi: 10.1002/9781118963418.childpsy307

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Wright MO, Masten AS, Narayan AJ. Resilience processes in development: four waves of research on positive adaptation in the context of adversity. In: Goldstein S, Brooks RB, editors. Handbook of Resilience in Children. 2nd ed. Heidelberg: Springer (2013). p. 15–37. doi: 10.1007/978-1-4614-3661-4_2

CrossRef Full Text | Google Scholar

44. Leipold B, Greve W. Resilience: a conceptual bridge between coping and development. Eur Psychol. (2009) 14:40–50. doi: 10.1027/1016-9040.14.1.40

CrossRef Full Text | Google Scholar

45. Folkman S, Moskowitz JT. Coping: pitfalls and promise. Annu Rev Psychol. (2004) 55:745–74. doi: 10.1146/annurev.psych.55.090902.141456

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Carver C, Scheier MF, Segerstrom S. Optimism. Clin Psychol Rev. (2010) 30:879–89. doi: 10.1016/j.cpr.2010.01.006

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Rutter M. Implications of resilience concepts for scientific understanding. Ann N Y Acad Sci. (2006) 1094:1–12. doi: 10.1196/annals.1376.002

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Cohn MA, Fredrickson BL, Brown SL, Mikels JA, Conway AM. Happiness unpacked: positive emotions increase life satisfaction by building resilience. Emotion. (2009) 9:361–8. doi: 10.1037/a0015952

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Pavot W, Diener E. The Satisfaction With Life Scale and the emerging construct of life satisfaction. Journal of Positive Psychology. (2008) 3:137–52. doi: 10.1080/17439760701756946

CrossRef Full Text | Google Scholar

50. Glaesmer H, Grande G, Braehler E, Roth M. The German version of the satisfaction with life scale (SWLS) psychometric properties, validity, and population-based norms. Eur J Psychol Assess. (2011) 27:127–32. doi: 10.1027/1015-5759/a000058

CrossRef Full Text | Google Scholar

51. Fredrickson BL, Cohn MA, Coffey KA, Pek J, Finkel SM. Open hearts build lives: positive emotions, induced through loving-kindness meditation, build consequential personal resources. J Pers Soc Psychol. (2008) 95:1045–62. doi: 10.1037/a0013262

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Neff KD, McGehee P. Self-compassion and psychological resilience among adolescents and young adults. Self Identity. (2010) 9:225–40. doi: 10.1080/15298860902979307

CrossRef Full Text | Google Scholar

53. Neff KD. The role of self-compassion in development: a healthier way to relate to oneself. Hum Dev. (2009) 52:211–4. doi: 10.1159/000215071

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Werner EE, Smith RS. Journeys From Childhood to Midlife: Risk, Resilience, and Recovery. London: Cornell University Press (2001).

PubMed Abstract | Google Scholar

55. Ingram R, Price JM. Understanding psychopathology: the role of vulnerability. In: Vulnerability to Psychopathology: Risk across the Lifespan. New York: Guilford Press (2001). p. 3–17.

Google Scholar

56. Friborg O, Hjemdal O, Martinussen M, Rosenvinge JH. Empirical support for resilience as more than the counterpart and absence of vulnerability and symptoms of mental disorder. J Individ Diff. (2009) 30:138–51. doi: 10.1027/1614-0001.30.3.138

CrossRef Full Text | Google Scholar

57. Huta V, Hawley L. Psychological strengths and cognitive vulnerabilities: are they two ends of the same continuum or do they have independent relationships with well-being and ill-being? J Happiness Stud. (2010) 11:71–93. doi: 10.1007/s10902-008-9123-4

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, et al. A place-based model for understanding community resilience to natural disasters. Glob Environ Change. (2008) 18:598–606. doi: 10.1016/j.gloenvcha.2008.07.013

CrossRef Full Text | Google Scholar

59. Turner BL. Vulnerability and resilience: coalescing or paralleling approaches for sustainability science? Glob Environ Change. (2010) 20:570–6. doi: 10.1016/j.gloenvcha.2010.07.003

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Dobzhansky T. Adaptedness and fitness. In: Lewontin RC, editor. Population Biology and Evolution. New York: Syracuse University Press (1968). p. 109–21.

Google Scholar

61. Smit B, Wandel J. Adaptation, adaptive capacity and vulnerability. Glob Environ Change. (2006) 16:282–92. doi: 10.1016/j.gloenvcha.2006.03.008

CrossRef Full Text | Google Scholar

62. Festinger L, Schachter S, Back K. Social Pressures in Informal Groups; A Study of Human Factors in Housing. Harper. Stanford: Stanford University Press (1950). doi: 10.2307/3707362

CrossRef Full Text | Google Scholar

63. Freud S. Massenpsychologie und Ich-Analyse. Vienna: Internationaler Psychoanalytischer Verlag (1921).

Google Scholar

64. McDougall W. The Group Mind: A Sketch of the Principles of Collective Psychology. New Delhi: Prabhat Prakashan (1921).

Google Scholar

65. Chan J, To HP, Chan E. Reconsidering social cohesion: developing a definition and analytical framework for empirical research. Soc Indic Res. (2006) 75:273–302. doi: 10.1007/s11205-005-2118-1

CrossRef Full Text | Google Scholar

66. Fonseca X, Lukosch S, Brazier F. Social cohesion revisited: a new definition and how to characterize it. Innovation. (2019) 32:231–53. doi: 10.1080/13511610.2018.1497480

CrossRef Full Text | Google Scholar

67. Schiefer D, van der Noll J. The essentials of social cohesion: a literature review. Soc Indic Res. (2017) 132:579–603. doi: 10.1007/s11205-016-1314-5

CrossRef Full Text | Google Scholar

68. Bollen KA, Hoyle RH. Perceived cohesion: a conceptual and empirical examination. Social Forces. (1990) 69:479–504. doi: 10.2307/2579670

CrossRef Full Text | Google Scholar

69. Dickes P, Valentova M, Borsenberger M. construct validation and application of a common measure of social cohesion in 33 European countries. Soc Indic Res. (2010) 98:451–73. doi: 10.1007/s11205-009-9551-5

CrossRef Full Text | Google Scholar

70. Gilligan MJ, Pasquale BJ, Samii C. Civil war and social cohesion: lab-in-the-field evidence from Nepal. Am J Pol Sci. (2014) 58:604–19. doi: 10.1111/ajps.12067

CrossRef Full Text | Google Scholar

71. Thomas EF, McGarty C, Mavor KI. Transforming “apathy into movement”: the role of prosocial emotions in motivating action for social change. Pers Soc Psychol Rev. (2009) 13:310–33. doi: 10.1177/1088868309343290

PubMed Abstract | CrossRef Full Text | Google Scholar

72. Luhmann N. Familiarity, confidence, trust: problems and alterntives. In: Trust: Making and Breaking Cooperative Relations. Oxford: Oxford University Press (2000). p. 94–107.

Google Scholar

73. Glaeser EL, Laibson DI, Scheinkman JA, Soutter CL. Measuring trust. Quart J Econ. (2000) 115:811–46. doi: 10.1162/003355300554926

CrossRef Full Text | Google Scholar

74. Yamagishi T, Yamagishi M. Trust and commitment in the United States and Japan. Motiv Emot. (1994) 18:129–66. doi: 10.1007/BF02249397

CrossRef Full Text | Google Scholar

75. Kosfeld M, Heinrichs M, Zak PJ, Fischbacher U, Fehr E. University of Zurich Oxytocin increases trust in humans Oxytocin increases trust in humans. Nature. (2005) 435:673–6. doi: 10.1038/nature03701

PubMed Abstract | CrossRef Full Text | Google Scholar

76. Larsen CA. The Rise and Fall of Social Cohesion: The Construction and de-Construction of Social Trust in the US, UK, Sweden and Denmark. Oxford: Oxford University Press (2013). doi: 10.1093/acprof:oso/9780199681846.001.0001

CrossRef Full Text | Google Scholar

77. Putnam R. The prosperous community: social capital and public life. Am Prospect. (1993) 4:35–42.

Google Scholar

78. Hagerty BMK, Lynch-Sauer J, Patusky KL, Bouwsema M, Collier P. Sense of belonging: a vital mental health concept. Arch Psychiatr Nurs. (1992) 6:172–7. doi: 10.1016/0883-9417(92)90028-H

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Baumeister RF, Leary MR. The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychol Bull. (1995) 117:497–529. doi: 10.1037/0033-2909.117.3.497

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Bottoni G. A multilevel measurement model of social cohesion. Soc Indic Res. (2018) 136:835–57. doi: 10.1007/s11205-016-1470-7

CrossRef Full Text | Google Scholar

81. Böckler A, Tusche A, Singer T. The structure of human prosociality: differentiating altruistically motivated, norm motivated, strategically motivated, and self-reported prosocial behavior. Soc Psychol Personal Sci. (2016) 7:530–41. doi: 10.1177/1948550616639650

CrossRef Full Text | Google Scholar

82. Leiberg S, Klimecki O, Singer T. Short-term compassion training increases prosocial behavior in a newly developed prosocial game. PLoS ONE. (2011) 6:e17798. doi: 10.1371/journal.pone.0017798

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Singer T. The past, present and future of social neuroscience: a European perspective. Neuroimage. (2012) 61:437–49. doi: 10.1016/j.neuroimage.2012.01.109

PubMed Abstract | CrossRef Full Text | Google Scholar

84. Singer T. The neuronal basis and ontogeny of empathy and mind reading: review of literature and implications for future research. Neurosci Biobehav Rev. (2006) 30:855–63. doi: 10.1016/j.neubiorev.2006.06.011

PubMed Abstract | CrossRef Full Text | Google Scholar

85. Singer T, Lamm C. The social neuroscience of empathy. Ann N Y Acad Sci. (2009) 1156:81–96. doi: 10.1111/j.1749-6632.2009.04418.x

PubMed Abstract | CrossRef Full Text | Google Scholar

86. de Vignemont F, Singer T. The empathic brain: how, when and why? Trends Cogn Sci. (2006) 10:435–41. doi: 10.1016/j.tics.2006.08.008

PubMed Abstract | CrossRef Full Text | Google Scholar

87. Clohesy AM. Politics of Empathy: Ethics, Solidarity, Recognition. London: Routledge (2013). doi: 10.4324/9780203795989

CrossRef Full Text | Google Scholar

88. Decety J, Cowell JM. The complex relation between morality and empathy. Trends Cogn Sci. (2014) 18:337–9. doi: 10.1016/j.tics.2014.04.008

PubMed Abstract | CrossRef Full Text | Google Scholar

89. Davis MH. A mulitdimensional approach to individual differences in empathy. JSAS Catal Selected Doc Psychol. (1980) 10:85.

Google Scholar

90. Ungar M, Brown M, Liebenberg L, Othman R. Unique pathways to resilience across cultures. Adolescence. (2007) 42:287.

PubMed Abstract | Google Scholar

91. Oshri A, Duprey EB, Kogan SM, Carlson MW, Liu S. A prospective examination of the emergence of resilience. Dev Psychol. (2018) 54:1456–71. doi: 10.1037/dev0000528

PubMed Abstract | CrossRef Full Text | Google Scholar

92. Ludin SM, Rohaizat M, Arbon P. The association between social cohesion and community disaster resilience: a cross-sectional study. Health Soc Care Commun. (2019) 27:621–31. doi: 10.1111/hsc.12674

PubMed Abstract | CrossRef Full Text | Google Scholar

93. Mathbor GM. Enhancement of community preparedness for natural disasters: the role of social work in building social capital for sustainable disaster relief and management. Int Soc Work. (2007) 50:357–69. doi: 10.1177/0020872807076049

CrossRef Full Text | Google Scholar

94. Townshend I, Awosoga O, Kulig J, Fan H. Social cohesion and resilience across communities that have experienced a disaster. Natural Hazards. (2015) 76:913–38. doi: 10.1007/s11069-014-1526-4

CrossRef Full Text | Google Scholar

95. Hikichi H, Aida J, Tsuboya T, Kondo K, Kawachi I. Can community social cohesion prevent posttraumatic stress disorder in the aftermath of a disaster? A natural experiment from the 2011 Tohoku Earthquake and Tsunami. Am J Epidemiol. (2016) 183:902–10. doi: 10.1093/aje/kwv335

PubMed Abstract | CrossRef Full Text | Google Scholar

96. Schulz P, Schlotz W. Trierer Inventar zur Erfassung von chronischem Sre (TICS): skalenkonstruktion, teststatistische Überprüfung und Validierung der Skala Arbeitsüberlastung [The Trier Inventory for the Assessment of Chronic Stress (TICS). Scale Constr Stat Test Diagn. (1999) 45:8–19. doi: 10.1026//0012-1924.45.1.8

CrossRef Full Text | Google Scholar

97. Borkenau P, Ostendorf F. NEO-Fünf-Faktoren-Inventar (NEO-FFI) nach Costa und McCrae: Handanweisung. Göttingen: Hogrefe (1993).

Google Scholar

98. Glaesmer H, Hoyer J, Klotsche J, Herzberg PY. Die deutsche Version des Life-Orientation-Tests (LOT-R) zum dispositionellen Optimismus und Pessimismus. Zeitschrift Gesundheitspsychol. (2008) 16:26–31. doi: 10.1026/0943-8149.16.1.26

CrossRef Full Text | Google Scholar

99. Scheier MF, Carver CS, Bridges MW. Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the Life Orientation Test. J Pers Soc Psychol. (1994) 67:1063–78. doi: 10.1037/0022-3514.67.6.1063

PubMed Abstract | CrossRef Full Text | Google Scholar

100. Laux L Glanzmann P Schaffner P and Spielberger CD. (1981). STAI. State-Trait-Angstinventar. Beltz Test GmbH.

Google Scholar

101. Spielberger CD, Gorsuch RL, Lushene RE. Stai. Manual for the State-Trait Anxiety Inventory (Self Evaluation Questionnaire). Palo Alto Calif Consult Psychol. (1970) 22:1–24.

Google Scholar

102. Döring N, Bortz J. Psychometrische Einsamkeitsforschung: deutsche Neukonstruktion der UCLA Loneliness Scale [Psychometric research on loneliness: a new German version of the University of California at Los Angeles (UCLA) Loneliness Scale]. Diagnostica. (1993) 39:224–39.

Google Scholar

103. Russell D, Peplau LA, Cutrona CE. The revised UCLA Loneliness Scale: concurrent and discriminant validity evidence. J Pers Soc Psychol. (1980) 39:472–80. doi: 10.1037/0022-3514.39.3.472

PubMed Abstract | CrossRef Full Text | Google Scholar

104. Loch N, Hiller W, Witthöft M. Der cognitive emotion regulation questionnaire (CERQ) erste teststatistische überprüfung einer deutschen adaption. Z Klin Psychol Psychother. (2011) 40:94–106. doi: 10.1026/1616-3443/a000079

CrossRef Full Text | Google Scholar

105. Herzberg PY, Glaesmer H, Hoyer J. Separating optimism and pessimism: a robust psychometric analysis of the revised Life Orientation Test (LOT-R). Psychol Assess. (2006) 18:433–8. doi: 10.1037/1040-3590.18.4.433

PubMed Abstract | CrossRef Full Text | Google Scholar

106. Diener E, Emmons RA, Larsen RJ, Griffin S. The satisfaction with life scale. Routledge Companion Perform Philos. (1985) 49:71–5. doi: 10.1207/s15327752jpa4901_13

PubMed Abstract | CrossRef Full Text | Google Scholar

107. Raes F, Pommier E, Neff KD, Van Gucht D. Construction and factorial validation of a short form of the Self-Compassion Scale. Clin Psychol Psychother. (2011) 18:250–5. doi: 10.1002/cpp.702

PubMed Abstract | CrossRef Full Text | Google Scholar

108. Carver C. You want to measure coping but your protocol's too long: consider the Brief COPE. Int J Behav Med. (1997) 4:92–100. doi: 10.1207/s15327558ijbm0401_6

PubMed Abstract | CrossRef Full Text | Google Scholar

109. Cramer RJ, Braitman A, Bryson CN, Long MM, La Guardia AC. The brief COPE: factor structure and associations with self- and other-directed aggression among emerging adults. Eval Health Prof. (2020) 43:120–30. doi: 10.1177/0163278719873698

PubMed Abstract | CrossRef Full Text | Google Scholar

110. Meyer B. Coping with severe mental illness: relations of the Brief COPE with symptoms, functioning, and well-being. J Psychopathol Behav Assess. (2001) 23:265–77. doi: 10.1023/A:1012731520781

CrossRef Full Text | Google Scholar

111. Nahlen Bose C, Bjorling G, Elfstrom ML, Persson H, Saboonchi F. Assessment of coping strategies and their associations with health related quality of life in patients with chronic heart failure: the brief COPE restructured. Cardiol Res. (2015) 6:239–48. doi: 10.14740/cr385w

PubMed Abstract | CrossRef Full Text | Google Scholar

112. Brislin RW. Back-translation for cross-cultural research. J Cross Cult Psychol. (1970) 1:185–216. doi: 10.1177/135910457000100301

CrossRef Full Text | Google Scholar

113. Caprara GV, Steca P, Zelli A, Capanna C. A new scale for measuring adults' prosocialness. Eur J Psychol Assess. (2005) 21:77–89. doi: 10.1027/1015-5759.21.2.77

CrossRef Full Text | Google Scholar

114. Schulz U, Schwarzer R. Soziale unterstützung bei der krankheitsbewältigung: die Berliner Social Support Skalen (BSSS). Diagnostica. (2003) 49:73–82. doi: 10.1026//0012-1924.49.2.73

CrossRef Full Text | Google Scholar

115. Schwarzer R, Knoll N. Functional roles of social support within the stress and coping process: A theoretical and empirical overview. Int J Psychol. (2007) 42:243–52. doi: 10.1080/00207590701396641

CrossRef Full Text | Google Scholar

116. Paulus C,. Der Saarbrücker Persönlichkeitsfragebogen SPF (IRI) zur messung von empathie: psychometrische evaluation der deutschen version des interpersonal reactivity index. (2009). Available online at: http://psydok.sulb.uni-saarland.de/volltexte/2009/2363/ (accessed June 1, 2020).

Google Scholar

117. Wang Y, Li Y, Xiao W, Fu Y, Jie J. Investigation on the rationality of the extant ways of scoring the Interpersonal Reactivity Index based on confirmatory factor analysis. Front Psychol. (2020) 11:1086. doi: 10.3389/fpsyg.2020.01086

PubMed Abstract | CrossRef Full Text | Google Scholar

118. R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing (2020).

Google Scholar

119. Rosseel Y. Lavaan: an R package for structural equation modeling and more. J Stat Softw. (2012) 48:1–36. doi: 10.18637/jss.v048.i02

CrossRef Full Text | Google Scholar

120. Mardia KV. Measures of multivariate skewness and kurtosis with applications. Biometrika. (1970) 57:519–30. doi: 10.1093/biomet/57.3.519

CrossRef Full Text | Google Scholar

121. Lai K. Estimating standardized SEM parameters given nonnormal data and incorrect model: methods and comparison. Struct Equ Model. (2018) 25:600–20. doi: 10.1080/10705511.2017.1392248

CrossRef Full Text | Google Scholar

122. Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. (1992) 21:230–58. doi: 10.1177/0049124192021002005

CrossRef Full Text | Google Scholar

123. Bentler PM. On tests and indices for evaluating structural models. Pers Individ Dif. (2007) 42:825–9. doi: 10.1016/j.paid.2006.09.024

CrossRef Full Text | Google Scholar

124. Child D. The essentials of factor analysis. AandC Black. (2006).

Google Scholar

125. Nunnally JC. Psychometric Theory. New York: McGraw-Hill (1987).

Google Scholar

126. Burke KL, Joyner AB, Czech DR, Wilson MJ. An investigation of concurrent validity between two optimism/pessimism questionnaires: the life orientation test-revised and the optimism/pessimism scale. Curr Psychol. (2000) 19:129–36. doi: 10.1007/s12144-000-1009-5

CrossRef Full Text | Google Scholar

127. Egeland B, Farber E. Invulnerability among abused and neglected children. In: Anthony, Cohler BJ, editors. The Invulnerable Child. Guilford Publications (1987). p. 253–88.

Google Scholar

128. Radke-Yarrow M, Brown E. Resilience and vulnerability in children of multiple-risk families. Dev Psychopathol. (1993) 5:581–92. doi: 10.1017/S0954579400006179

CrossRef Full Text | Google Scholar

129. Mayer RC, Davis JH, Schoorman FD. An integrative model of organizational trust. Acad Manag Rev. (1995) 20:709–34. doi: 10.2307/258792

CrossRef Full Text | Google Scholar

130. Rousseau DM, Sitkin SB, Burt RS, Camerer C. Not so different after all: a cross-discipline view of trust. Acad Manag Rev. (1998) 23:393–404. doi: 10.5465/amr.1998.926617

CrossRef Full Text | Google Scholar

131. Misztal BA. Trust: acceptance of, precaution against and cause of vulnerability. In: Sasaki M, Marsh RM, editors. Trust. Boston: Brill (2012). p. 209–36. doi: 10.1163/9789004221383_010

CrossRef Full Text | Google Scholar

132. Longstaff PH, Yang SU. Communication management and trust: their role in building resilience to “surprises” such as natural disasters, pandemic flu, and terrorism. Ecol Soc. (2008) 13. doi: 10.5751/ES-02232-130103

CrossRef Full Text | Google Scholar

133. McQuaid RJ, McInnis OA, Stead JD, Matheson K, Anisman H. A paradoxical association of an oxytocin receptor gene polymorphism: Early-life adversity and vulnerability to depression. Front Neurosci. (2013) 7:128. doi: 10.3389/fnins.2013.00128

PubMed Abstract | CrossRef Full Text | Google Scholar

134. Bonanno GA. Resilience in the face of potential trauma. Curr Dir Psychol Sci. (2005) 14:135–8. doi: 10.1111/j.0963-7214.2005.00347.x

CrossRef Full Text | Google Scholar

135. Richardson GE. The metatheory of resilience and resiliency. J Clin Psychol. (2002) 58:307–21. doi: 10.1002/jclp.10020

PubMed Abstract | CrossRef Full Text | Google Scholar

136. Tedeschi RG, Calhoun LG. TARGET ARTICLE : “ posttraumatic growth: conceptual foundations and empirical evidence.” Psychol Inquiry. (2004) 15:1–18. doi: 10.1207/s15327965pli1501_01

CrossRef Full Text | Google Scholar

137. Westphal M, Bonanno GA. Posttraumatic growth and resilience to trauma: different sides of the same coin or different coins? Appl Psychol. (2007) 56:417–27. doi: 10.1111/j.1464-0597.2007.00298.x

CrossRef Full Text | Google Scholar

138. Salisu I, Hashim N. A critical review of scales used in resilience research. IOSR J Business Manag. (2017) 19:23–33. doi: 10.9790/487X-1904032333

CrossRef Full Text | Google Scholar

139. Skinner EA, Edge K, Altman J, Sherwood H. Searching for the structure of coping: A review and critique of category systems for classifying ways of coping. Psychol Bull. (2003) 129:216–69. doi: 10.1037/0033-2909.129.2.216

PubMed Abstract | CrossRef Full Text | Google Scholar

140. Krägeloh CU. A systematic review of studies using the Brief COPE: religious coping in factor analyses. Religions. (2011) 2:216–46. doi: 10.3390/rel2030216

CrossRef Full Text | Google Scholar

141. Tusche A, Böckler A, Kanske P, Trautwein FM, Singer T. Decoding the charitable brain: empathy, perspective taking, and attention shifts differentially predict altruistic giving. J Neurosci. (2016) 36:4719–32. doi: 10.1523/JNEUROSCI.3392-15.2016

PubMed Abstract | CrossRef Full Text | Google Scholar

142. Lin N. A network theory of social capital. In: Castiglione D, van Deth J, Wolleb G, editors. The Handbook of Social Capital. Oxford: Oxford University Press (2008). p. 50–9. doi: 10.4337/9781789907285.00009

CrossRef Full Text | Google Scholar

143. Szreter S, Woolcock M. Health by association? Social capital, social theory, and the political economy of public health. Int J Epidemiol. (2004) 33:650–67. doi: 10.1093/ije/dyh013

PubMed Abstract | CrossRef Full Text | Google Scholar

144. Pelling M, High C. Understanding adaptation: what can social capital offer assessments of adaptive capacity? Glob Environ Change. (2005) 15:308–19. doi: 10.1016/j.gloenvcha.2005.02.001

CrossRef Full Text | Google Scholar

145. Gunnar MR, Donzella B. Social regulation of the cortisol levels in early human development. Psychoneuroendocrinology. (2002) 27:199–220. doi: 10.1016/S0306-4530(01)00045-2

PubMed Abstract | CrossRef Full Text | Google Scholar

146. Coan JA, Schaefer HS, Davidson RJ. Lending a hand: social regulation of the neural response to threat. Psychol Sci. (2006) 17:1032–9. doi: 10.1111/j.1467-9280.2006.01832.x

PubMed Abstract | CrossRef Full Text | Google Scholar

147. Porges SW. The polyvagal theory: phylogenetic substrates of a social nervous system. Int J Psychophysiol. (2001) 42:123–46. doi: 10.1016/S0167-8760(01)00162-3

PubMed Abstract | CrossRef Full Text | Google Scholar

148. Coan JA, Sbarra DA. Social baseline theory: the social regulation of risk and effort. Curr Opin Psychol. (2015) 1:87–91. doi: 10.1016/j.copsyc.2014.12.021

PubMed Abstract | CrossRef Full Text | Google Scholar

149. Schmittmann VD, Cramer AOJ, Waldorp LJ, Epskamp S, Kievit RA, Borsboom D. Deconstructing the construct: a network perspective on psychological phenomena. New Ideas Psychol. (2013) 31:43–53. doi: 10.1016/j.newideapsych.2011.02.007

CrossRef Full Text | Google Scholar

150. Kaplan HB. Toward an understanding of resilience. In: Glantz MD, Johnson JL, editors. Resilience and Development. Boston: Springer (2002). p. 17–83. doi: 10.1007/0-306-47167-1_3

CrossRef Full Text | Google Scholar

Keywords: social cohesion, psychological vulnerability, psychological resilience, social skills, belonging

Citation: Silveira S, Hecht M, Adli M, Voelkle MC and Singer T (2022) Exploring the Structure and Interrelations of Time-Stable Psychological Resilience, Psychological Vulnerability, and Social Cohesion. Front. Psychiatry 13:804763. doi: 10.3389/fpsyt.2022.804763

Received: 29 October 2021; Accepted: 28 January 2022;
Published: 11 March 2022.

Edited by:

Giorgia Silani, University of Vienna, Austria

Reviewed by:

Dina Weindl, University of Vienna, Austria
Adrian Van Breda, University of Johannesburg, South Africa

Copyright © 2022 Silveira, Hecht, Adli, Voelkle and Singer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sarita Silveira, sarita.silveira@social.mpg.de

These authors share senior authorship

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