Transdiagnostic Mechanisms of Mental Health During the COVID-19 Pandemic on Adults and Families in Germany: Study Protocol of a Cross-Sectional and 1-Year Longitudinal Study

Background: Since the outbreak of COVID-19 pandemic, psychological distress is increased. Transdiagnostic mechanisms, including trauma, personality functioning, mentalizing and emotion regulation are considered relevant to the development and maintenance of mental health problems and therefore may play a role in individuals’ reactions to the pandemic.

Aim: To identify moderating and mediating factors associated with pandemic-related distress and mental health problems in adults and families, we aim to investigate the interactions of interpersonal trauma (childhood trauma and domestic violence), psychological capacities (personality functioning, mentalizing and emotion regulation) and pandemic-related adversity on psychological distress during the COVID-19 pandemic. Furthermore, we aim to investigate behavioral and cognitive consequences of the pandemic (e.g., media consumption, vaccination status, conspiracy beliefs).

Methods: Using an online-based cross-sectional and longitudinal design, we will investigate a sample of adult participants recruited via online platforms in German-speaking countries over the course of 1 year with four measurements points via self-report instruments (personality functioning: PID5BF +; mentalizing: MentS, PRFQ; emotion regulation: DERS-SF; mental health problems: PHQ-9, GAD-7; a composite pandemic-related stress score). Structural equation and multi-level modeling will be performed for data analyses.

Implications: This study will provide data on the moderating and mediating effects of trauma, personality functioning and mentalizing during the pandemic in a large community sample, particularly on vulnerable groups like families. Identifying transdiagnostic mechanisms of psychopathology in the course of a pandemic crisis may provide valuable insight for the development of pre- and intervention measures for potential psychological distress during and post the pandemic.

Introduction

The current COVID-19 pandemic has a massive impact on all people’s life’s including individual, family related, societal, economic and financial hardship, social and cultural deprivation, and educational disadvantages (e.g., Kujawa et al., 2020).

A number of studies examined the psychological impact of the COVID-19 pandemic showing that psychological distress is generally increased across populations worldwide (e.g., Salari et al., 2020; Wu et al., 2020). In Europe, several studies have shown an increase in psychological distress related to the pandemic (Pierce et al., 2020; Rodríguez-Rey et al., 2020; Rossi et al., 2020). Studies from Germany, in particular, are also in line with international findings, showing for example significantly higher levels of depression, anxiety and increased psychological distress in the general population during the pandemic and specifically during lockdown phases (Bäuerle et al., 2020; Benke et al., 2020; Petzold et al., 2020). Studies have found a number of factors associated with psychological distress during the pandemic, namely being in quarantine, loneliness, worries about infections or death of important others, unemployment and housework, as well as social and financial consequences of the pandemic (Benke et al., 2020; Chandola et al., 2020; Rodríguez-Rey et al., 2020; Rossi et al., 2020).

Vulnerable populations, like families with young children are particularly affected during the pandemic (Pierce et al., 2020). Factors that have been identified to be associated with families’ psychological distress are their life circumstances (for example work- and learning spaces at home) (Pierce et al., 2020), financial anxiety and lack of social support. While the burden is higher in those families with younger children and those with two or more children (Mazza et al., 2020; Li et al., 2020), the impact on the mental health of young children, i.e., infants and toddlers, has been less investigated. Furthermore, several studies found an increase in intimate partner violence and child maltreatment since the COVID-19 pandemic (e.g., Brown et al., 2020; Jetelina et al., 2021). Decreased service utilization, other COVID-19 related stressful events, and increased parental psychological symptoms were also related to higher child abuse potential (Brown et al., 2020; Lawson et al., 2020). However, so far little is known about psychological risk and protective factors of families, which may amplify or buffer the potential effect from COVID-19 related adversities and parental distress on risk of child abuse.

Drawing on existing transdiagnostic models of childhood trauma and psychopathology (McLaughlin et al., 2020), and mentalizing (Luyten et al., 2020), we aim to expand this to the understanding of the psychosocial impact of the pandemic. Thereby, we aim to investigate the relationship of childhood trauma, psychological capacities including personality functioning, emotional awareness and regulation, and mentalizing abilities on the psychosocial impact of the pandemic. Social risk factors like younger age, female gender or unemployment, in addition to families with young children, have been shown to play an important role in experiencing increased psychological distress during the pandemic (Horesh and Brown, 2020; Xiong et al., 2020). Fewer studies have focused on factors such as a history of traumatic experiences or personality factors (e.g., Fernández et al., 2020). In the following, we briefly outline the evidence based on these hypothesized risk and protective factors with regard to mental health problems and summarize current findings on the pandemic impact:

A history of interpersonal childhood trauma (for example physical, sexual, and emotional abuse or neglect) is associated with a higher risk for a psychopathological development later in life (Felitti et al., 1998; Mandelli et al., 2015). With regard to pandemic-related impacts on mental health, Guo et al. (2020) found that adolescents with pre-pandemic traumatic experiences were associated with increased anxiety during the pandemic, and Kim et al. (2020) found a moderating effect of early childhood trauma on the association between the perceived risk from COVID-19 and depression. Hence, experiences of childhood trauma may be understood as a vulnerability factor for psychopathology during the pandemic.

Personality functioning, conceptualized as basic psychological capacities of a person have an understanding and regulation abilities of the self of relationships with others, is considered a key factor to develop and maintain mental health (Kernberg and Caligor, 2005; Bender et al., 2011). With regard to the pandemic, a disposition toward internalizing personality traits (including negative affectivity, detachment, closed-mindedness and psychoticism), were associated with increased levels of depression, anxiety and stress during the pandemic (Mazza et al., 2020; Biondi et al., 2021) and elevated levels of negative affectivity were found to contribute to lower resilience and reduced subjective well-being (Kocjan et al., 2021).

Mentalizing - the basic human capacity to conceive oneself and others as intentional beings whose actions are guided by feelings, thoughts, desires, attitudes, and goals (Fonagy et al., 2002) - is implicated in a number of mental health problems and disorders (Luyten et al., 2020) and can be understood as an adaptive psychological mechanism for coping with pandemic-related stressors. In a similar vein, parents’ ability to mentalize their child may be a protective factor against the adverse effects of pandemic-related stress on the child because parents are able to co-regulate their child more effectively according to its needs (Zeegers et al., 2017). So far, very few empirical studies have investigated pandemic-related effects on mentalizing abilities (Lassri and Desatnik, 2020; Ventura Wurman et al., 2020) and none of the studies focused on mentalizing as a risk or protective factor in the general population or families.

Furthermore, an individual’s ability to experience and regulate emotions is also considered highly relevant to develop and maintain mental health (e.g., Aldao et al., 2010; Hu et al., 2014). According to Gratz and Roemer (2004) the concept of emotional (dys-)regulation comprises (a) the ability to identify and understand emotions, (b) the acceptance of emotions, (c) the potential to exhibit goal-directed behavior and control impulsive behavior even while exposed to negative emotions or stress, and (d) the ability to flexibly use situationally appropriate emotion regulation strategies to achieve individual goals (Kaufman et al., 2016). A recent study examining emotional dysregulation during the pandemic found that having survived a Covid-19 infection was associated with a greater likelihood of psychological distress, and this in turn was associated with greater emotional dysregulation as well as elevated levels of depressive mood (Janiri et al., 2020). Moreover, the concept may be of particular relevance to family’s mental health during the pandemic, as parents’ emotional dysregulation problems have been shown to be related to children’s stress reactions (Shorer and Leibovich, 2020). Young children of parents with deficits in emotion regulation may be at a heightened risk during the pandemic to experience less adaptive co-regulation and thus may show more mental health problems (e.g., regulatory symptoms).

According to transdiagnostic models of the development of mental health problems, interactions between interpersonal trauma, psychological capacities and other factors exist and are to some extend supported by empirical data. For example, Abdi and Pak (2019) found that the effect of maladaptive personality traits and low personality functioning on mental health problems was mediated by emotion dysregulation. Moreover, emotion dysregulation (Cloitre et al., 2019) as well as mentalizing (Huang et al., 2020) are found to serve as mediating factors in the relationship between childhood trauma and psychopathology. These findings indicate the extent to which psychological capacities can have a mediating influence on a psychopathological development against the background of traumatic experiences in early childhood.

Furthermore, the behavioral and cognitive consequences of the pandemic such as increasing media consumption, authoritarianism, conspiracy beliefs, vaccination status and attitude, and posttraumatic growth need to be considered, if we want to advance our understanding about maintaining and losing mental health in a global crisis. Recent studies have shown a new rise in people’s vulnerability to conspiracy beliefs during the pandemic (Šrol et al., 2020; Leibovitz et al., 2021; Oleksy et al., 2021). Dyrendal et al. (2021) identified right-wing authoritarianism within their analysis as one predictor of conspiracy theories. Hartman et al. (2020) also showed a correlation between COVID-19-specific conspiracy beliefs (i.e., that the virus originated on a Chinese laboratory) and a political attitude toward right-wing authoritarianism. These results are also supported by Prichard and Christman (2020), who found that authoritarianism was not only a predictor of less concern about the COVID-19 virus and low compliance, but also associated with the belief that the virus had been produced in China. Moreover, this COVID-19 pandemic may also be regarded an infodemic, in which the overabundance of information, individuals’ increased media consumption and deliberate attempts to disseminate wrong information effects people’s psychological capacities and mental health (Cellini et al., 2020; Valdez et al., 2020; World Health Organization [WHO], 2020, September 23). At the same time, people may also be able to cope with the crisis in a positive way and develop posttraumatic growth as a result of the pandemic (e.g., Vazquez et al., 2021).

Rationale and Aim of This Study

Based on the research outlined above, we aim to investigate a multi-factorial and transdiagnostic model of risk and protective factors associated with pandemic-related distress and psychological impairments in adults and families in the general German-speaking population during the COVID-19 pandemic in a cross-sectional and 1-year longitudinal study. In particular, the effects and complex interactions of interpersonal trauma- namely childhood trauma and domestic violence- psychological capacities- namely personality functioning, mentalizing and emotion regulation- and pandemic-related adversity on psychological distress in adults and families will be investigated. Furthermore, we aim to exploratorily investigate behavioral and cognitive consequences of the pandemic including vaccination status and attitude, media consumption, authoritarianism and conspiracy beliefs, as well as violence, maltreatment and posttraumatic growth during the pandemic.

Research Questions

Main Research Questions Cross-Sectional Data

(1) Is there a relationship between pandemic-related adversity and psychological distress?

(1.1) Is pandemic-related adversity a predictor of psychological distress?

(2) Is there a relationship between childhood trauma, psychological capacities and pandemic-related adversity and psychological distress in adults and families?

(2.1) Is the relationship between pandemic-related adversity and psychological distress moderated by childhood trauma?

(2.2) Is the relationship between pandemic-related adversity and psychological distress mediated by psychological capacities (personality functioning, mentalizing, emotional experience and regulation)?

(2.3) Is the relationship between pandemic-related adversity and psychological distress as well as infant/toddler regulatory problems mediated by parental psychological capacities (parental mentalizing, emotional experience and regulation)?

(2.4) Is the relationship between pandemic-related adversity and psychological distress moderated by childhood trauma and mediated by psychological capacities (personality functioning, mentalizing, emotional experience and regulation)?

Main Research Questions Longitudinal Data

(3) Is there a relationship between changes in pandemic-related adversity and psychological distress in course of the 1-year longitudinal study?

(4) Is there a relationship between childhood trauma, changes in psychological capacities and pandemic-related adversity and changes in psychological distress over time?

(4.1) Is the relationship between changes in pandemic-related adversity and psychological distress predicted by childhood trauma?

(4.2) Is the relationship between changes in pandemic-related adversity and psychological distress mediated by changes in psychological capacities (personality functioning, mentalizing, emotional experience and regulation)?

(4.3) Is the relationship between changes in pandemic-related adversity and psychological distress as well as infant/toddler regulatory problem problems mediated by changes in parental psychological capacities (parental mentalizing, emotional experience and regulation)?

(4.4) Is the relationship between changes in pandemic-related adversity and psychological distress predicted by childhood trauma and mediated by changes in psychological capacities (personality functioning, mentalizing, emotional experience and regulation)?

(5) Is there a relationship between changes in parental psychological capacities, pandemic-related adversity and violence and maltreatment during the pandemic?

(5.1) Is the relationship between changes in pandemic-related adversity, violence and maltreatment during the pandemic mediated by changes in psychological capacities (parental reflective functioning, emotional experience and regulation)?

Additionally, further exploratory analyses with regard to the relationship between psychological capacities, pandemic-related adversity, psychological well-being and pandemic-related phenomena including conspiracy beliefs, media consumption, authoritarianism and vaccination status and attitudes will be conducted.

Method

A cross-sectional and longitudinal study of the relationship between childhood trauma, personality functioning, mentalizing ability, pandemic-related stressors, and psychological distress will be conducted. The survey will be conducted online using the SoSci Survey platform. Ethic approval has been obtained from the local ethics board (Heidelberg University; AZ Tau 2020 3/1). The first measurement period (t0) began in August 2020 and continued through February 2021. After the first survey period t0, three additional follow-up surveys will be conducted at 3-months intervals. The first follow-up survey (t1) started in November 2020 and ended in May 2021. The second follow-up survey (t2) started in February 2021 and will end in August 2021. The third follow-up survey (t3) started in May 2021 and will end in November 2021. Figure 1 illustrates the study design with time measurement points.

FIGURE 1

Figure 1. Design of the cross-sectional and 1-year longitudinal study on risk and protective factors of the psychosocial impact during the COVID-19 pandemic in Germany.

Sample

Adults over 18 years of age will be included. Aiming at a sample size of N = 800 at the last time point after 9 months and considering a drop-out rate of approx. 35% per time point (cf., Kujawa et al., 2020), appr. N = 3,000 adults (cross-sectional study) need to be included.

Participants will be recruited via the Institute for Psychosocial Prevention at Heidelberg University Hospital, via online and social media platforms (including Facebook, Instagram, Twitter, and Reddit), e-mails, and print flyers. Recruitment strategies are designed to reach a diverse population of German-speaking adults, with a focus on populations that may be particularly affected by the pandemic (including participants working in system-relevant occupations and families). Therefore, we particularly target respective groups on social media platforms (e.g., parent groups and forums) while we also recruit in more general groups/forums (e.g., COVID-19 related groups, sport clubs, and universities nationwide). Although our strategy aims at including a diverse population, participants’ characteristics will be analyzed for oversampling younger and better educated participants.

Measures

Table 1 includes an overview of all measures used in the study and their respective assessment time point.

TABLE 1

Table 1. Overview of PACE measures in cross-sectional and longitudinal surveys.

Predictors, Moderators and Mediators

Sociodemographic Characteristics

At baseline general sociodemographic data using a standardized questionnaire including information about age, gender, educational and occupational background, and socio-economic situation will be collected and data about changes in sociodemographic background is collected at all follow-up timepoints.

Childhood Trauma

The childhood trauma questionnaire (CTQ; German version: Wingenfeld et al., 2010) is a 28-item retrospective self-report measure that is divided into five subscales to assess different aspects of maltreatment experiences in childhood: emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect. Each subscale consists of five statements, which can be rated with a five- point Likert Scale (1 = not at all; 5 = very often). Three additional items measure the individual’s tendency to minimize and deny. The subscale-scores range from 5 to 25 and the total score ranges from 25 to 125, with higher points indicating a greater extent of maltreatment. For each subscale specific cutoffs indicate the frequency of exposure. Strong psychometric properties have been demonstrated for the CTQ in clinical as well as community samples (Scher et al., 2001). The German version showed similar properties to the original version and demonstrated to be reliable and valid (Wingenfeld et al., 2010).

Psychological Capacities

Personality functioning

The PID-5 Brief Form + (PID5BF +; Kerber et al., 2019) is a brief self-report measure for assessing the six pathological trait domains described in AMPD criterion B and the ICD-11: negative affectivity, detachment, antagonism/dissociality, disinhibition, anankastia and psychoticism. Items are rated on a four-point scale ranging from 0 (“very false or often false”) to 3 (“very true or often true”). The internal consistency of the domain scores in three large samples was high (mean McDonald’s ω = 0.81), and domain scores were substantially positively correlated with each other.

The Standardized Assessment of Severity of Personality Disorder (SASPD; Olajide et al., 2018; German version: Zimmermann and Leising, 2015) is a brief measure to assess the severity of a potential personality disorder (PD) according to ICD-11 (Olajide et al., 2018). It consists of a total of nine items relating to different life domains and skills such as friendships, self-control, or compassion. Respondents can choose between four statements, which can then be recoded into a four-point scale according to the severity of a potential personality disorder (0 = Non-existent, 1 = Mild, 2 = Moderate and 3 = Severe). However, studies that addressed the validation of the SASPD found that the SASPD total score may be more useful as an indicator of a complex and heterogeneous mix of PD characteristics rather than actually representing severity (Rek et al., 2020). The SASPD nonetheless shows acceptable internal consistency in both clinical (ω = 0.78) and non-clinical (ω = 0.70) samples (Rek et al., 2020).

Mentalizing Abilities

The Mentalization Ability Assessment Questionnaire (MentS; Dimitrijević et al., 2018; German version: D-MentS by Dimitrijević et al., 2017) is a self-report questionnaire with 28 items to assess mentalization in clinical and healthy populations. Items are rated on a five-point scale (1 = “strongly disagree” to 5 “strongly agree”). The questionnaire consists of three subscales: MentS-A (10 items) captures mentalizing in relation to the other; MentS-S (8 items) captures mentalizing in relation to the self; and MentS-M (10 items) captures motivation to mentalize. A sum score maps the total mentalizing abilities score. Internal consistencies are acceptable in clinical and healthy populations and validity is adequately ensured (Dimitrijević et al., 2017).

Parental Reflective Functioning

We used the interest and curiosity in mental states scale of the German version of the Parental Reflective Functioning Questionnaire [PRFQ by Ramsauer et al. (2014); Luyten et al. (2017)] to assess parental reflective functioning. The scale consists of six items and assesses a parents’ proclivity to be interested in the child’s mental states. Items are rated on a seven-point Likert scale ranging from strongly disagree to strongly agree. The PRFQ reliably and validly assessed parental reflective functioning (Luyten et al., 2017; Anis et al., 2020).

Emotional Experience and Regulation

The Difficulties in Emotion Regulation Scale- Short Form (DERS-SF; German version: Ehring et al., 2008) is a 18-item self-report measure to assess emotional dysregulation across six domains: non-acceptance of emotional responses, lack of emotional awareness, limited access to ER strategies, lack of emotional clarity, difficulties engaging in goal-directed behavior, and impulse control difficulties when experiencing negative emotions. Participants rate the frequency with which the 18 statements apply to themselves by choosing from a five-point Likert-type scale. The items were recoded, with higher scores for each item and a higher overall score indicating more deficits in emotional dysregulation. The original version of the DERS showed high internal consistency (α = 0.93), good test-retest reliability, and adequate constructive and predictive validity (Gratz and Roemer, 2004). The German version of the DERS also demonstrated adequate to good internal consistencies within the original sample (0.76 < α < 0.87; Ehring et al., 2008).

The Positive and Negative Affect Schedule (PANAS; Janke and Glöckner-Rist, 2014) captures various feelings and emotions consisting of 20 items. With ten items each, the dimensions of positive and negative affect are captured on a 5-point Likert scale with response options “not at all” to “extremely.” Reliability assessment good Cronbach’s α values of 0.86 for the two dimensions of positive and negative affect (Janke and Glöckner-Rist, 2014).

Symptomatic anger was assessed using the anger/hostility subscale of the Symptom-Checklist-90 (SCL-90R-S; Franke, 2014). Six items are rated on a five-point Likert scale from 0 (not at all) to 4 (extremely) with higher scores indicating higher distress. The subscale has demonstrated sufficient internal consistency (α = 0.79; Franke, 2014).

In addition, two items from the German of the Child Abuse Potential Inventory (CAPI; Deegener et al., 2009) were utilized to assess general anger/hostility (English translation of the German version: “I am often angry inside”; “Many things in my life make me angry”). Items are rated on a four-point Likert scale. The CAPI is a valid and reliable inventory to determine the degree of stress of parents or other primary caregivers to assess the risk of child endangerment and abuse (Milner, 1994). Internal consistency (α = 0.91) is high (Deegener et al., 2009).

Pandemic-Related Adversity

Pandemic Phases

A dimensional score specifying different phases of the lockdown will be calculated. The score will be calculated based on the specific lockdown phase present at the assessment timepoint of each individual participant.

COVID-19 Adversity Scale

This summative score, developed as part of the project, is composed of items that are classified as stressful in the context of the COVID-19 pandemic. These include e.g., pandemic-related adversity experienced due to social contact restrictions, changes in life style (incl. activities, nutrition, exercise) and experience of lack of access to health care due to the pandemic. The COVID-19 adversity scale for families additionally covers experiences relevant to families and partnership support (incl. homeschooling, co-parenting). The conceptually derived scales (e.g., Benke et al., 2020; Kujawa et al., 2020; Rossi et al., 2020) will be empirically validated using confirmatory factor analyses.

Outcomes

Psychological Distress

Psychological Symptom Severity

The Patient Health Questionnaire (PHQ-D; German version: Löwe et al., 2008) represents a widely used, valid screening instrument based on the DSM-IV for the diagnosis of mental disorders. In order to assess psychological distress, the depression module (PHQ-9) with nine items and the module on generalized anxiety (GAD-7; English original version: Spitzer et al., 2006; German translation and validation: Löwe et al., 2008) with seven items are used in this study. Both modules are answered on a four-point scale (0 = “not at all” to 3 = “almost every day”) and are characterized by high validity, good internal consistencies (PHQ-9: α = 0.88; GAD-7: α = 0.89) and, especially for the depression module, by a high sensitivity to change (Gräfe et al., 2004; Löwe et al., 2008).

Regulatory Problems in Infants/Toddlers

Regulatory problems, which include excessive crying, sleep-onset, and night waking problems were assessed by parental report utilizing four screening items based on the structured diagnostic interview for regulatory problems in infancy (BABY-DIPS; Popp et al., 2016) and frequency and duration criteria of the Diagnostic Classification System DC:0-3R (Zero to Three, 2005). In addition, regulatory problems and related parental burden were assessed dimensionally utilizing 13 items from the Questionnaire for Crying, Feeding, and Sleeping (QCFS), which has been shown to be a valid measure for clinically significant regulatory disorders (Gross et al., 2013). Items are rated on a four-point Likert scale from never/rarely to always/every day. Higher scores signify more regulatory problems across all areas. Both instruments validly and reliably assess regulatory problems in infancy.

Further Secondary Outcomes

Psychological Well-being

Well-being

The German short version of the World Health Organization Well-Being Index (WHO-5; Brähler et al., 2007; Topp et al., 2015) consists of five items that refer to the well-being within the past 2 weeks. The response options are positively worded and refer to participants’ mood, calmness and relaxation, as well as perceived vitality, activity, restfulness of sleep and interest in things of daily living (Simon, 2017). The evaluation of the answers is recorded via a six-point Likert scale (0 = at no time; 5 = all the time). For scoring, the response scores of the five items are added together. The raw scores vary from 0 to 25 points, with a score of 0 being interpreted as the lowest psychological well-being and lowest quality of life, and a score of 25 being interpreted as the highest psychological well-being and highest quality of life. A score of <13 points is recommended as a cut-off criterion for poor psychological well-being. The internal consistencies of the test can be assessed as good with α = 0.88 (cf. α ≥ 0.89; Brähler et al., 2007; Döring and Bortz, 2016).

Violence and Maltreatment

Intimate Partner Violence During the Pandemic

The modified Partner Violence Screen (PVS, Nyberg et al., 2008) was used to assess exposure to partner violence during the last 12 months and particularly, since the beginning of the pandemic. The original PVS (Feldhaus et al., 1997) consists of three items that capture physical abuse and perceptions of safety. It has been translated to German and adapted by Nyberg et al. (2008) by including two items that capture sexual abuse and reasons to seek medical assistance related to violence. The measure has shown a sensitivity of 0.80 and a specificity of 0.78 (Nyberg et al., 2008). In this study, the PVS was modified in order to screen for violence against a partner of either gender and the item on medical assistance has been deleted due to the context of our study which does not provide crisis intervention.

Child Maltreatment During the Pandemic

We assessed child maltreatment and violence among parents with 7 items stemming from a nationwide survey on young families in Germany (KID 0-3; Eickhorst et al., 2015). The items cover instances of child abuse and neglect (e.g., “Has your child been shaken or pushed against a wall by an adult?”) and instances of partner violence (e.g., “Has one parent threatened the other parent seriously?”). All items are assessed dichotomously (yes/no). We asked participants to answer whether instance occurred before or since the beginning of the pandemic or both. The measure has been successfully used to assess child maltreatment in German young families.

Pandemic-Related Phenomena

Conspiracy Beliefs

The Conspiracy Mentality Questionnaire (CMQ) by Bruder et al. (2013) is an instrument that captures the conspiratorial mentality as a one-dimensional construct. On an eleven-point scale with a range from: 0% “certainly not” to 100% “certain” with a total of five-items, a generic conspiracy conviction is shown. The internal consistency of the questionnaire has been calculated and showed “good” results of Cronbach‘s Alpha for the German language version (α = 0.84). In addition, the model indices showed a very good fit (CFI > 0.95, RMSEA < 0.06), as well as factor loadings of >0.50. Furthermore, the test-retest-reliability in a 2-week interval was also satisfactory.

Media Consumption

Participants are asked about their media usage (e.g., type of newspapers, social media platforms, YouTube channels or podcasts) and indicate, which media they have used to obtain information about the Covid-19 pandemic.

Authoritarianism

The short scale authoritarianism (KSA-3) by Beierlein et al. (2014) is an economic instrument for assessing authoritarianism with its three sub-dimensions (aggression, submission and conventionalism). The scale comprises a total of nine items, with three items per sub-dimension. Those are rated on a five-point rating scale with a range from: (1) completely disagree to (5) completely agree. The factorial validity shows model indices of CFI = 0.962, RMSEA = 0.067, and SRMR = 0.043, which can be classified as satisfactory. Furthermore, factor loadings of all items on the scale (>0.50) and the three sub-dimensions on the general factor authoritarianism were shown. Using the McDonald ω coefficient, the reliability of the scales was determined, showing sufficient reliabilities of the three sub-dimensions of ω = 0.86 for authoritarian aggression, ω = 0.74 for authoritarian subservience, ω = 0.78 for conventionalism.

Posttraumatic Growth Inventory

Posttraumatic Growth Inventory (PTGI-SF; Cann et al., 2010) is the short form of the Posttraumatic Growth Inventory from Tedeschi and Calhoun (1996) and comprises 10 items about the positive outcomes of traumatic experiences. The five domains include New Possibilities, Relating to Others, Appreciation of Life, Spiritual Change and Personal Strength are measured with two items for each subscale. The calculation of the reliability has shown sufficient results (α = 0.90). Also, the Fit indices indicate a good fit (CFI = 0.965; RMSEA = 0.072). We adapted the instructions in order to assess posttraumatic growth related to the pandemic.

Vaccination Status and Attitude

We have included two questions about COVID-19 vaccination status of the participant and their close relatives as well as their motivation their general attitude toward COVID-19 vaccination.

Statistical Analysis

Data within individual timepoints will be assessed for missing data and patterns of missingness. For missing at random data, we will conduct multiple imputation by chained equations (MICE) using the R package mice (Groothuis-Oudshoorn and Van Buuren, 2011). We will use predictive mean matching (Little, 1988) as imputation algorithm, since it is moderately robust when the empirical data deviate from distributional assumptions (Kleinke, 2017). Cross-sectional analysis: To answer research questions 1 to 2.4 on the association between childhood trauma, psychological capacities, pandemic-related adversity and psychological distress structural equation modeling will be applied for the cross-sectional data analyses. Longitudinal analysis: To answer the research questions 3 to 6.1 on the moderating and mediating effect of the named risk and protective factors regarding the relationship of pandemic-related adversity and psychological distress as well as potential associated pandemic-related phenomena, the data analyses of the longitudinal correlations are performed using multilevel modeling with measurement time points (level 1) nested in subjects (level 2). Here, changes in psychological distress at Level 1 is predicted by pandemic-related distress factors and linear time, as well as potential covariates (including age, gender). Psychological capacities are introduced as a mediator at Level 1. Analyses will be conducted using the Lavaan and semPlot-packages of the statistical software R.

Discussion

This paper describes the study protocol of a cross-sectional and longitudinal study on risk and protective factors of mental health during the COVID-19 pandemic. To the best of the authors’ knowledge, this is the first study of its kind that investigates the moderating and mediating role of traumatic experiences and psychological capacities during the pandemic in a large community sample with a particular focus on families using a longitudinal design.

By expanding and testing the existing transdiagnostic models of childhood trauma and psychopathology (McLaughlin et al., 2020), and mentalizing (Luyten et al., 2020), this study will make an important contribution to a better understanding of risk and protective factors of mental health in the course of a worldwide pandemic crisis and the experience of related adverse events. Furthermore, the longitudinal examination of psychological capacities like personality functioning, mentalizing skills and emotion regulation in the relationship between pandemic-related stressors and psychological stress experience may provide valuable information for the development of pre- and intervention measures for potential psychological stress experience during and post the pandemic.

The strengths of this study include the broad and comprehensive recruitment approach, the investigation of theoretically grounded risk and protective factors of mental health during the COVID-19 crisis, in particular investigating a vulnerable population of families with young children.

Limitations of this study include a strategy that is primarily limited to online recruitment, which may potentially exclude individuals, who do not access these online platforms. Moreover, this sample is self-selected and will not be representative for the larger general population of Germany or Europe.

In addition, the survey is long and may attract only highly motivated individuals. Thus, our results will contribute to identifying risk and protective factors which, however, we cannot claim to be representative for the general population. In case of a large drop-out in the follow-up assessments, the sample will further suffer from self-selection processes. However, we will assess demographic characteristics in the follow-up surveys in order to accurately describe the sample in these aspects and will take on control measures for oversampling younger and better educated participants. Another limitation is the use of only self-report assessments, which may result in response biases and are limited to contents that are consciously processable. Finally, although we aim to assess pandemic-related adversity operationalized by including pandemic phases as well as a COVID-19 adversity scale retrospectively, the lack of pre-pandemic data limits our data validity regarding immediate effects caused by the pandemic-related restrictions and measures on mental health.

In light of the massive global psychological impact of the pandemic, this study with a strong focus on intra- and interpersonal psychological risk and protective factors will be of direct relevance to the evaluation of how pandemic measures affect vulnerable populations but also to the development of mental health and preventive services during and after the pandemic.

Author Contributions

JV drafted the current manuscript. AB, LK, HW, JH, AG, and ST revised, corrected, and finally approved. All authors provided a substantial contribution to the conception and design of the work by developing the research question, study design, methodology, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved.

Funding

This study was funded by the German Association of Psychoanalysis (Deutsche Gesellschaft für Psychoanalyse; DPG).

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.

References

Abdi, R., and Pak, R. (2019). The mediating role of emotion dysregulation as a transdiagnostic factor in the relationship between pathological personality dimensions and emotional disorders symptoms severity. Person. Individ. Differ. 142, 282–287. doi: 10.1016/j.paid.2018.09.026

CrossRef Full Text | Google Scholar

Aldao, A., Nolen-Hoeksema, S., and Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: a meta-analytic review. Clin. Psychol. Rev. 30, 217–237. doi: 10.1016/j.cpr.2009.11.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Anis, L., Perez, G., Benzies, K. M., Ewashen, C., Hart, M., and Letourneau, N. (2020). Convergent validity of three measures of reflective function: parent development interview, parental reflective function questionnaire, and reflective function questionnaire. Front. Psychol. 11:3385. doi: 10.3389/fpsyg.2020.574719

PubMed Abstract | CrossRef Full Text | Google Scholar

Bäuerle, A., Teufel, M., Musche, V., Weismüller, B., Kohler, H., Hetkamp, M., et al. (2020). Increased generalized anxiety, depression and distress during the COVID-19 pandemic: a cross-sectional study in Germany. J. Public Health 42, 672–678. doi: 10.1093/pubmed/fdaa106

PubMed Abstract | CrossRef Full Text | Google Scholar

Beierlein, C., Asbrock, F., Kauff, M., and Schmidt, P. (2014). Die Kurzskala Autoritarismus (KSA-3): Ein ökonomisches Messinstrument zur Erfassung Dreier Subdimensionen Autoritärer Einstellungen. Mannheim: GESIS – Leibniz Institut für Sozialwissenschaften.

Google Scholar

Bender, D. S., Morey, L. C., and Skodol, A. E. (2011). Toward a model for assessing level of personality functioning in DSM–5, part I: a review of theory and methods. J. Person. Assessment 93, 332–346. doi: 10.1080/00223891.2011.583808

PubMed Abstract | CrossRef Full Text | Google Scholar

Benke, C., Autenrieth, L. K., Asselmann, E., and Pané-Farré, C. A. (2020). Lockdown, quarantine measures, and social distancing: associations with depression, anxiety and distress at the beginning of the COVID-19 pandemic among adults from Germany. Psychiatry Res. 293:113462. doi: 10.1016/j.psychres.2020.113462

PubMed Abstract | CrossRef Full Text | Google Scholar

Biondi, S., Casale, S., Burrai, J., Mazza, C., Cavaggioni, G., Ferracuti, S., et al. (2021). Personality and lockdown: a study on italian undergraduates during the COVID-19 pandemic. Front. Psychiatry 12:622366. doi: 10.3389/fpsyt.2021.622366

PubMed Abstract | CrossRef Full Text | Google Scholar

Brähler, E., Mühlan, H., Albani, C., and Schmidt, S. (2007). Teststatistische Prüfung und normierung der deutschen Versionen des EUROHIS-QOL lebensqualität-index und des WHO-5 wohlbefindens-index. Diagnostica 53, 83–96. doi: 10.1026/0012-1924.53.2.83

CrossRef Full Text | Google Scholar

Breyer, B., and Bluemke, M. (2016). Deutsche version der positive and negative affect schedule PANAS (GESIS panel) [German version of the positive and negative affect schedule PANAS]. Zusammenstellung Sozialwissenschaftlicher Items und Skalen (ZIS). doi: 10.6102/zis242

CrossRef Full Text | Google Scholar

Brown, S. M., Doom, J. R., Lechuga-Peña, S., Watamura, S. E., and Koppels, T. (2020). Stress and parenting during the Global COVID-19 Pandemic. Child Abuse Negl. 110:104699. doi: 10.1016/j.chiabu.2020.104699

PubMed Abstract | CrossRef Full Text | Google Scholar

Bruder, M., Haffke, P., Neave, N., Nouripanah, N., and Imhoff, R. (2013). Measuring individual differences in generic beliefs in conspiracy theories across cultures: conspiracy mentality questionnaire. Front. Psychol. 4:225. doi: 10.3389/fpsyg.2013.00225

PubMed Abstract | CrossRef Full Text | Google Scholar

Cann, A., Calhoun, L. G., Tedeschi, R. G., Taku, K., Vishnevsky, T., Triplett, K. N., et al. (2010). A short form of the posttraumatic growth inventory. Anxiety Stress Coping 23, 127–137. doi: 10.1080/10615800903094273

PubMed Abstract | CrossRef Full Text | Google Scholar

Cellini, N., Canale, N., Mioni, G., and Costa, S. (2020). Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy. J. Sleep Res. 29:e13074.

Google Scholar

Chandola, T., Kumari, M., Booker, C. L., and Benzeval, M. (2020). The mental health impact of COVID-19 and lockdown-related stressors among adults in the UK. Psychol. Med. [Online ahead of print] 1–10. doi: 10.1017/S0033291720005048

PubMed Abstract | CrossRef Full Text | Google Scholar

Cloitre, M., Khan, C., Mackintosh, M. A., Garvert, D. W., Henn-Haase, C. M., Falvey, E. C., et al. (2019). Emotion regulation mediates the relationship between ACES and physical and mental health. Psychol. Trauma: Theory Res. Pract. Pol. 11:82. doi: 10.1037/tra0000374

PubMed Abstract | CrossRef Full Text | Google Scholar

Deegener, G., Spangler, G., Körner, W., and Becker, N. (2009). Eltern-Belastungs-Screening zur Kindeswohlgefährdung. Deutsche Form des Child Abuse Potential Inventory (CAPI) von Joel S. Milner. Göttingen: Hogrefe.

Google Scholar

Dimitrijević, A., Hanak, N., Altaras Dimitrijević, A., and Jolić Marjanović, Z. (2018). The Mentalization Scale (MentS): a self-report measure for the assessment of mentalizing capacity. J. Person. Assessment 100, 268–280. doi: 10.1080/00223891.2017.1310730

PubMed Abstract | CrossRef Full Text | Google Scholar

Dimitrijević, A., Ristein, L., Licata, M., Hamburger, A., Altaras Dimitrijević, A., and Jolić Marjanović, Z. (2017). Validation of the German Version of the Mentalization Scale (D- MentS). Manuscript in Preparation.

Google Scholar

Döring, N., and Bortz, J. (2016). Forschungsmethoden und Evaluation. Wiesbaden: Springerverlag.

Google Scholar

Dyrendal, A., Kennair, L. E. O., and Bendixen, M. (2021). Predictors of belief in conspiracy theory: the role of individual differences in schizotypal traits, paranormal beliefs, social dominance orientation, right wing authoritarianism and conspiracy mentality. Person. Individ. Differ. 173:110645. doi: 10.1016/j.paid.2021.110645

CrossRef Full Text | Google Scholar

Ehring, T., Fischer, S., Schnülle, J., Bösterling, A., and Tuschen-Caffier, B. (2008). Characteristics of emotion regulation in recovered depressed versus never depressed individuals. Person. Individ. Differ. 44, 1574–1584. doi: 10.1016/j.paid.2008.01.013

CrossRef Full Text | Google Scholar

Eickhorst, A., Brand, C., Lang, K., Liel, C., Neumann, A., Schreier, A., et al. (2015). Die Prävalenzstudie, Kinder in Deutschland–KiD 0-3“zur erfassung von psychosozialen belastungen und frühen hilfen in familien mit 0-3-jährigen kindern: studiendesign und analysepotential. Soziale Passagen 7, 381–387. doi: 10.1007/s12592-015-0212-z

CrossRef Full Text | Google Scholar

Feldhaus, K. M., Koziol-McLain, J., Amsbury, H. L., Lowenstein, S. R., and Abbott, J. T. (1997). Accuracy of 3 brief screening questions for detecting partner violence in the emergency department. JAMA 277, 1357–1361. doi: 10.1001/jama.1997.03540410035027

CrossRef Full Text | Google Scholar

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., et al. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the adverse childhood experiences (ACE) study. Am. J. Prevent. Med. 14, 245–258. doi: 10.1016/S0749-3797(98)00017-8

CrossRef Full Text | Google Scholar

Fernández, R. S., Crivelli, L., Guimet, N. M., Allegri, R. F., and Pedreira, M. E. (2020). Psychological distress associated with COVID-19 quarantine: latent profile analysis, outcome prediction and mediation analysis. J. Affect. Disord. 277, 75–84. doi: 10.1016/j.jad.2020.07.133

PubMed Abstract | CrossRef Full Text | Google Scholar

Fonagy, P., Gergely, G., Jurist, E. L., and Target, M. (2002). Affect Regulation, Mentalization, and the Development of the Self. London: Karnac Books.

Google Scholar

Franke, G. H. (2014). Symptom-Checklist-90-Standard: SCL-90-S; Manual. Göttingen: Hogrefe.

Google Scholar

Gräfe, K., Zipfel, S., Herzog, W., and Löwe, B. (2004). Screening psychischer Störungen mit dem “Gesundheitsfragebogen für Patienten (PHQ-D)”. Diagnostica 50, 171–181. doi: 10.1026/0012-1924.50.4.171

CrossRef Full Text | Google Scholar

Gratz, K. L., and Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and initial validation of the difficulties in emotion regulation scale. J. Psychopathol. Behav. Assessment 26, 41–54. doi: 10.1023/B:JOBA.0000007455.08539.94

CrossRef Full Text | Google Scholar

Groothuis-Oudshoorn, K., and Van Buuren, S. (2011). Mice: multivariate imputation by chained equations in R. J. Stat, Softw. 45, 1–67.

Google Scholar

Gross, S., Reck, C., Thiel-Bonney, C., and Cierpka, M. (2013). Empirical basis of the questionnaire for crying, feeding and sleeping. Praxis Kinderpsychologie Kinderpsychiatrie 62, 327–347. doi: 10.13109/prkk.2013.62.5.327

PubMed Abstract | CrossRef Full Text | Google Scholar

Guo, J., Fu, M., Liu, D., Zhang, B., Wang, X., and van IJzendoorn, M. H. (2020). Is the psychological impact of exposure to COVID-19 stronger in adolescents with pre-pandemic maltreatment experiences? A survey of rural chinese adolescents. Child Abuse Negl. 110:104667. doi: 10.1016/j.chiabu.2020.104667

PubMed Abstract | CrossRef Full Text | Google Scholar

Hartman, T. K., Marshall, M., Stocks, T. V., McKay, R., Bennett, K. M., Butter, S., et al. (2020). Different conspiracy theories have different psychological and social determinants: comparison of three theories about the origins of the COVID-19 virus in a representative sample of the UK population. PsyArXiv [Preprints] doi: 10.31234/osf.io/mz5sw

CrossRef Full Text | Google Scholar

Horesh, D., and Brown, A. D. (2020). Traumatic stress in the age of COVID-19: a call to close critical gaps and adapt to new realities. Psychol. Trauma: Theory Res. Pract. Pol. 12:331. doi: 10.1037/tra0000592

PubMed Abstract | CrossRef Full Text | Google Scholar

Hu, T., Zhang, D., Wang, J., Mistry, R., Ran, G., and Wang, X. (2014). Relation between emotion regulation and mental health: a meta-analysis review. Psychol. Rep. 114, 341–362. doi: 10.2466/03.20.PR0.114k22w4

CrossRef Full Text | Google Scholar

Huang, Y. L., Fonagy, P., Feigenbaum, J., Montague, P. R., and Nolte, T. London Personality and Mood Disorder Research Consortium (2020). Multidirectional pathways between attachment, mentalizing, and posttraumatic stress symptomatology in the context of childhood trauma. Psychopathology 53, 48–58. doi: 10.1159/000506406

PubMed Abstract | CrossRef Full Text | Google Scholar

Janiri, D., Kotzalidis, G. D., Giuseppin, G., Molinaro, M., Modica, M., Montanari, S., et al. (2020). Psychological distress After Covid-19 recovery: reciprocal effects with temperament and emotional dysregulation. an exploratory study of patients over 60 years of age assessed in a post-acute care service. Front. Psychiatry 11:590135. doi: 10.3389/fpsyt.2020.590135

PubMed Abstract | CrossRef Full Text | Google Scholar

Janke, S., and Glöckner-Rist, A. (2014). “Deutsche Version der positive and negative affect schedule (PANAS),” in Zusammenstellung Sozialwissenschaftlicher Items und Skalen, eds S. Janke and A. Glöckner-Rist (Mannheim: GESIS), 6102.

Google Scholar

Jetelina, K. K., Knell, G., and Molsberry, R. J. (2021). Changes in intimate partner violence during the early stages of the COVID-19 pandemic in the USA. Injury Prevent 27, 93–97. doi: 10.1136/injuryprev-2020-043831

PubMed Abstract | CrossRef Full Text | Google Scholar

Kaufman, E. A., Xia, M., Fosco, G., Yaptangco, M., Skidmore, C. R., and Crowell, S. E. (2016). The Difficulties in Emotion Regulation Scale Short Form (DERS-SF): validation and replication in adolescent and adult samples. J. Psychopathol. Behav. Assessment 38, 443–455. doi: 10.1007/s10862-015-9529-3

CrossRef Full Text | Google Scholar

Kerber, A., Schultze, M., Müller, S., Rühling, R. M., Wright, A. G., Spitzer, C., et al. (2019). Development of a short and ICD-11 compatible measure for DSM-5 maladaptive personality traits using ant colony optimization algorithms. Assessment doi: 10.1177/1073191120971848

PubMed Abstract | CrossRef Full Text | Google Scholar

Kernberg, O. F., and Caligor, E. (2005). “A psychoanalytic theory of personality disorders,” in Major Theories of Personality Disorder, eds M. F. Lenzenweger and J. F. Clarkin (New York, NY: Guilford Press), 114–156.

Google Scholar

Kim, A. W., Nyengerai, T., and Mendenhall, E. (2020). Evaluating the mental health impacts of the COVID-19 pandemic: perceived risk of COVID-19 infection and childhood trauma predict adult depressive symptoms in urban South Africa. Psychol. Med. [Online ahead of print] 1–13. doi: 10.1017/S0033291720003414

PubMed Abstract | CrossRef Full Text | Google Scholar

Kleinke, K. (2017). Multiple imputation under violated distributional assumptions: a systematic evaluation of the assumed robustness of predictive mean matching. J. Educ. Behav. Stat. 42, 371–404. doi: 10.3102/1076998616687084

CrossRef Full Text | Google Scholar

Kocjan, G. Z., Kavčič, T., and Avsec, A. (2021). Resilience matters: explaining the association between personality and psychological functioning during the COVID-19 pandemic. Int. J. Clin. Health Psychol. 21:100198. doi: 10.1016/j.ijchp.2020.08.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Kroenke, K., Wu, J., Yu, Z., Bair, M. J., Kean, J., Stump, T., et al. (2016). Patient health questionnaire anxiety and depression scale: initial validation in three clinical trials. Psychosom Med. 78, 716–727. doi: 10.1097/PSY.0000000000000322

PubMed Abstract | CrossRef Full Text | Google Scholar

Kujawa, A., Green, H., Compas, B. E., Dickey, L., and Pegg, S. (2020). Exposure to COVID-19 pandemic stress: associations with depression and anxiety in emerging adults in the United States. Depression Anxiety 37, 1280–1288.

Google Scholar

Lassri, D., and Desatnik, A. (2020). Losing and regaining reflective functioning in the times of COVID-19. Clinical risks and opportunities from a mentalizing approach. Psychol. Trauma: Theory Res. Pract. Pol. 12, 38–40. doi: 10.1037/tra0000760

CrossRef Full Text | Google Scholar

Lawson, M., Piel, M. H., and Simon, M. (2020). Child maltreatment during the COVID-19 pandemic: consequences of parental job loss on psychological and physical abuse towards children. Child Abuse Negl. 110:104709. doi: 10.1016/j.chiabu.2020.104709

PubMed Abstract | CrossRef Full Text | Google Scholar

Leibovitz, T., Shamblaw, A. L., Rumas, R., and Best, M. W. (2021). COVID-19 conspiracy beliefs: relations with anxiety, quality of life, and schemas. Person. Individ. Differ. 175:110704.

Google Scholar

Li, L. Q., Huang, T., Wang, Y. Q., Wang, Z. P., Liang, Y., Huang, T. B., et al. (2020). COVID-19 Patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J. Med. Virol. 92, 577–583. doi: 10.1002/jmv.25757

PubMed Abstract | CrossRef Full Text | Google Scholar

Little, R. J. A. (1988). Missing-Data adjustments in large surveys. J. Bus. Econ. Stat. 6, 287–301. doi: 10.2307/1391878

CrossRef Full Text | Google Scholar

Löwe, B., Decker, O., Müller, S., Brähler, E., Schellberg, D., Herzog, W., et al. (2008). Validation and standardization of the generalized anxiety disorder screener (GAD-7) in the general population. Med. Care 46, 266–274.

Google Scholar

Luyten, P., Campbell, C., Allison, E., and Fonagy, P. (2020). The mentalizing approach to psychopathology: state of the art and future directions. Annu. Rev. Clin. Psychol. 16, 297–325. doi: 10.1146/annurev-clinpsy-071919-015355

PubMed Abstract | CrossRef Full Text | Google Scholar

Luyten, P., Nijssens, L., Fonagy, P., and Mayes, L. C. (2017). Parental reflective functioning: theory, research, and clinical applications. Psychoanalytic Study Child 70, 174–199. doi: 10.1080/00797308.2016.1277901

CrossRef Full Text | Google Scholar

Mandelli, L., Petrelli, C., and Serretti, A. (2015). The role of specific early trauma in adult depression: a meta-analysis of published literature. Childhood trauma and adult depression. Eur. Psychiatry 30, 665–680. doi: 10.1016/j.eurpsy.2015.04.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Mazza, C., Ricci, E., Biondi, S., Colasanti, M., Ferracuti, S., Napoli, C., et al. (2020). A nationwide survey of psychological distress among Italian people during the COVID-19 pandemic: immediate psychological responses and associated factors. Int. J. Environ. Res. Public Health 17:3165. doi: 10.3390/ijerph17093165

PubMed Abstract | CrossRef Full Text | Google Scholar

McLaughlin, K. A., Colich, N. L., Rodman, A. M., and Weissman, D. G. (2020). Mechanisms linking childhood trauma exposure and psychopathology: a transdiagnostic model of risk and resilience. BMC Med. 18:96. doi: 10.1186/s12916-020-01561-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Milner, J. S. (1994). Assessing physical child abuse risk: the child abuse potential inventory. Clin. Psychol. Rev. 14, 547–583. doi: 10.1016/0272-7358(94)90017-5

CrossRef Full Text | Google Scholar

Nyberg, E., Hartman, P., Stieglitz, R., and Riecher-Rössler, A. (2008). Screening partnergewalt: ein deutschsprachiges screeninginstrument für häusliche gewalt gegen frauen. Fortschritte Neurol.-Psychiatrie (FDN) 76, 28–36.

Google Scholar

Olajide, K., Munjiza, J., Moran, P., O’Connell, L., Newton-Howes, G., Bassett, P., et al. (2018). Development and psychometric properties of the standardized assessment of severity of personality disorder (SASPD). J. Person. Disord. 32, 44–56. doi: 10.1521/pedi_2017_31_285

CrossRef Full Text | Google Scholar

Oleksy, T., Wnuk, A., Maison, D., and Łyś, A. (2021). Content matters. Different predictors and social consequences of general and government-related conspiracy theories on COVID-19. Person. Individ. Differ. 168:110289.

Google Scholar

Petzold, M. B., Bendau, A., Plag, J., Pyrkosch, L., Mascarell Maricic, L., Betzler, F., et al. (2020). Risk, resilience, psychological distress, and anxiety at the beginning of the COVID-19 pandemic in Germany. Brain Behav. 10:e01745. doi: 10.1002/brb3.1745

PubMed Abstract | CrossRef Full Text | Google Scholar

Pierce, M., Hope, H., Ford, T., Hatch, S., Hotopf, M., John, A., et al. (2020). Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry 7, 883–892. doi: 10.1016/S2215-0366(20)30308-4

CrossRef Full Text | Google Scholar

Popp, L., Fuths, S., Seehagen, S., Bolten, M., Gross-Hemmi, M., Wolke, D., et al. (2016). Inter-rater reliability and acceptance of the structured diagnostic interview for regulatory problems in infancy. Child Adolescent Psychiatry Ment. Health 10, 1–10. doi: 10.1186/s13034-016-0107-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Prichard, E. C., and Christman, S. D. (2020). Authoritarianism, conspiracy beliefs, gender and COVID-19: links between individual differences and concern about COVID-19, mask wearing behaviors, and the tendency to blame China for the virus. Front. Psychol. 11:597671. doi: 10.3389/fpsyg.2020.597671

PubMed Abstract | CrossRef Full Text | Google Scholar

Ramsauer, B., Lotzin, A., Mühlhan, C., Romer, G., Nolte, T., Fonagy, P., et al. (2014). A randomized controlled trial comparing circle of security intervention and treatment as usual as interventions to increase attachment security in infants of mentally ill mothers: study protocol. BMC Psychiatry 14:24. doi: 10.1186/1471-244X-14-24

PubMed Abstract | CrossRef Full Text | Google Scholar

Rek, K., Thielmann, I., Henkel, M., Crawford, M., Piccirilli, L., Graff, A., et al. (2020). A psychometric evaluation of the standardized assessment of severity of personality disorder (SASPD) in nonclinical and clinical German samples. Psychol. Assessment 32:984. doi: 10.1037/pas0000926

PubMed Abstract | CrossRef Full Text | Google Scholar

Rodríguez-Rey, R., Garrido-Hernansaiz, H., and Collado, S. (2020). Psychological Impact and associated factors during the initial stage of the coronavirus (COVID-19) pandemic among the general population in Spain. Front. Psychol. 11:1540. doi: 10.3389/fpsyg.2020.01540

PubMed Abstract | CrossRef Full Text | Google Scholar

Rossi, R., Socci, V., Talevi, D., Mensi, S., Niolu, C., Pacitti, F., et al. (2020). COVID-19 pandemic and lockdown measures impact on mental health among the general population in Italy. Front. Psychiatry 11:790. doi: 10.3389/fpsyt.2020.00790

PubMed Abstract | CrossRef Full Text | Google Scholar

Salari, N., Hosseinian-Far, A., Jalali, R., Vaisi-Raygani, A., Rasoulpoor, S., Mohammadi, M., et al. (2020). Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis. Glob. Health 16, 1–11.

Google Scholar

Scher, C. D., Stein, M. B., Asmundson, G. J., McCreary, D. R., and Forde, D. R. (2001). The childhood trauma questionnaire in a community sample: psychometric properties and normative data. J. Traumatic Stress 14, 843–857. doi: 10.1023/A:1013058625719

CrossRef Full Text | Google Scholar

Shorer, M., and Leibovich, L. (2020). Young Children’s emotional stress reactions during the COVID-19 outbreak and their associations with parental emotion regulation and parental playfulness. Early Child Dev. Care 1–11. doi: 10.1080/03004430.2020.1806830

CrossRef Full Text | Google Scholar

Simon, M. (2017). Das Gesundheitssystem in Deutschland. Bern: Hogrefe.

Google Scholar

Spitzer, R. L., Kroenke, K., Williams, J. B., and Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Internal Med. 166, 1092–1097. doi: 10.1001/archinte.166.10.1092

PubMed Abstract | CrossRef Full Text | Google Scholar

Šrol, J., Mikušková, E. B., and Cavojova, V. (2020). When we are worried, what are we thinking? Anxiety, lack of control, and conspiracy beliefs amidst the COVID-19 pandemic. Appl. Cogn. Psychol. 35, 720–729.

Google Scholar

Tedeschi, R. G., and Calhoun, L. G. (1996). The posttraumatic growth inventory: measuring the positive legacy of trauma. J. Traumatic Stress 9, 455–471. doi: 10.1007/BF02103658

PubMed Abstract | CrossRef Full Text | Google Scholar

Topp, C. W., Østergaard, S. D., Søndergaard, S., and Bech, P. (2015). The WHO-5 well-being index: a systematic review of the literature. Psychother. Psychosomatics 84, 167–176. doi: 10.1159/000376585

PubMed Abstract | CrossRef Full Text | Google Scholar

Valdez, D., Ten Thij, M., Bathina, K., Rutter, L. A., and Bollen, J. (2020). Social media insights into US mental health during the COVID-19 pandemic: longitudinal analysis of twitter data. J. Med. Internet Res. 22:e21418.

Google Scholar

Vazquez, C., Valiente, C., García, F. E., Contreras, A., Peinado, V., Trucharte, A., et al. (2021). Post-traumatic growth and stress-related responses during the COVID-19 pandemic in a national representative sample: the role of positive core beliefs about the world and others. J. Happiness Stud. [Online ahead of print] 1–21. doi: 10.1007/s10902-020-00352-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Ventura Wurman, T., Lee, T., Bateman, A., Fonagy, P., and Nolte, T. (2020). Clinical management of common presentations of patients diagnosed with BPD during the COVID-19 pandemic. The contribution of the MBT framework. Counsell. Psychol. Q. 292, 1–27. doi: 10.1080/09515070.2020.1814694

CrossRef Full Text | Google Scholar

Wingenfeld, K., Spitzer, C., Mensebach, C., Grabe, H. J., Hill, A., Gast, U., et al. (2010). Die deutsche Version des Childhood Trauma Questionnaire (CTQ): erste befunde zu den psychometrischen Kennwerten. PPmP-Psychotherapie⋅Psychosomatik⋅ Medizinische Psychol. 60, 442–450. doi: 10.1055/s-0030-1247564

PubMed Abstract | CrossRef Full Text | Google Scholar

World Health Organization [WHO] (2020). Managing the COVID-19 Infodemic: Promoting Healthy Behaviours and Mitigating the Harm from Misinformation and Disinformation. Geneva: World Health Organiztion.

Google Scholar

Wu, T., Jia, X., Shi, H., Niu, J., Yin, X., Xie, J., et al. (2020). Prevalence of mental health problems during the COVID-19 pandemic: a systematic review and meta-analysis. J. Affect. Disord. 281, 91–98. doi: 10.1016/j.jad.2020.11.117

PubMed Abstract | CrossRef Full Text | Google Scholar

Xiong, J., Lipsitz, O., Nasri, F., Lui, L. M., Gill, H., Phan, L., et al. (2020). Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J. Affect. Disord. 277, 55–64. doi: 10.1016/j.jad.2020.08.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Zeegers, M. A., Colonnesi, C., Stams, G. J. J., and Meins, E. (2017). Mind matters: a meta-analysis on parental mentalization and sensitivity as predictors of infant–parent attachment. Psychol. Bull. 143:1245. doi: 10.1037/bul0000114

PubMed Abstract | CrossRef Full Text | Google Scholar

Zero to Three (2005). Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood: Revised Edition (DC: 0-3R). Washington, DC: Zero to Three.

Google Scholar

Zimmermann, J., and Leising, D. (2015). Deutsche Übersetzung der Standardized Assessment of Severity of Personality Disorder (SASPD). Unpublished Measure.

Google Scholar