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Psychiatry Research 317 (2022) 114900 Contents lists available at ScienceDirect Psychiatry Research journal homepage: www.elsevier.com/locate/psychres Loneliness and psychosocial predictors of psychosis-proneness during COVID-19: Preliminary findings from Croatia Alena Gizdic a, *, Tatiana Baxter b, Neus Barrantes-Vidal a, c, d, Sohee Park b a Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona, Spain b Department of Psychology, Vanderbilt University, Nashville, TN, USA c Sant Pere Claver – Fundació Sanitària, Barcelona, Spain d Centre for Biomedical Research Network on Mental Health (CIBERSAM), Instituto, de Salud Carlos III, Barcelona, Spain A R T I C L E I N F O A B S T R A C T Keywords: The present study investigated psychosocial predictors of psychosis-risk, depression, anxiety, and stress in COVID-19 Croatia during the COVID-19 pandemic. Given Croatia’s recent transgenerational war trauma and the relative Loneliness lack of available prodromal data, this study presents a unique opportunity to examine the impact of loneliness Psychosis and other psychosocial factors on psychosis-risk and mental health in this population. 404 Croatian participants Trauma Mental health completed an anonymous online survey of physical and mental health questions. 48 participants met the criteria Croatia for elevated psychosis-risk on prodromal questionnaire (PQ-16). Loneliness had a significant impact on psy­ chosis-risk. Exposure to trauma was associated with psychosis-risk and loneliness, while domestic abuse/violence was associated only with the distress surrounding psychotic-like symptoms. COVID concern was also associated with psychosis-risk. Lastly, the associations between psychosis-risk and depression, anxiety, and stress were robust. These findings highlight the important role of loneliness in psychosis-proneness in Croatia. Depression, anxiety, and stress were also closely related to elevated psychosis-risk. Loneliness is a highly salient issue for individuals with psychosis and it is important to target loneliness within a multi-faceted psychosocial inter­ vention for those at risk for schizophrenia. 1. Introduction Deterioration of mental health among the general public may be as severe as effects found among the survivors of SARS-CoV-2. About 34% The survival and flourishing of social species such as humans de­ of patients infected with SARS-CoV-2 were diagnosed with psychiatric pends largely on close-knit social networks and cooperation. Existing disorders in the 6 months following their illness (Taquet et al., 2021), evidence indicates that social connectedness supports good health out­ most commonly, mood and/or anxiety disorders (Butler et al., 2020). comes (Holt-Lunstad, 2018; Ehsan et al., 2019) including mental health Although there is relatively low incidence of psychotic disorder after (Degnan et al., 2018; Nitschke et al., 2021). However, in the last two COVID-19 infection (1.4%), there have been reports of sudden onset of years there have been significant social changes brought about by the psychosis in individuals with no psychiatric history (Kozato et al., 2021). global COVID-19 pandemic and consequential public health measures. Among the general population, the prevalence of mental health condi­ Increased unemployment, financial insecurity, and poverty are likely to tions during the COVID-19 may be just as alarming. Dean et al. (2021) have long-lasting impacts on mental health outcomes (Holmes et al., reported overall increase in psychosocial distress across four countries. 2020) but disrupted social connectedness due to the pandemic may have Importantly, Lee et al. (2021) found depression in 36.8%, anxiety in an even broader impact on mental health across all age groups, socio­ 29.5%, stress in 24.5% and prodromal psychosis signs in 12.8% of the economic strata, and cultures (e.g., Dean et al., 2021). The pandemic general Korean population despite the very low COVID infection rate in necessitated social distancing measures to control the spread of the the country. virus. These public health strategies may have had detrimental effects on Despite the shift towards studying the consequences of the pandemic mental health including increased feelings of loneliness, isolation, and on mental health, there is still a lack of data from the general population. anxiety (Carvalho et al., 2020). Social distancing and enforced social isolation may exacerbate * Corresponding author. E-mail address: alena.gizdic@uab.cat (A. Gizdic). https://doi.org/10.1016/j.psychres.2022.114900 Received 2 August 2022; Received in revised form 5 October 2022; Accepted 8 October 2022 Available online 9 October 2022 0165-1781/© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Table 1 Table 3 Demographic information. Descriptive data for the main psychosocial predictors. . N (Total) M (SD) Range Mean SD Range Age 404 39.6 (13.7) 17–73 DASS (N ¼ 331) Depression 6.72 7.21 0–39 N % p* Anxiety 4.44 5.52 0–32 Gender Stress 8.46 6.98 0–35 Male 84 20.8 PQ Female 317 78.5 <0.001 Items endorsed 2.90 3.17 0–16 Prefer not to answer 3 0.7 Distress endorsed 3.12 5.48 0–36 Education SNI Elementary school 3 0.7 High-Contact Roles 4.32 2.98 0–11 High school 75 18.6 People in Social Network 3.80 2.65 0–10 Technical school 27 6.7 Embedded Networks 2.23 1.92 0–8 Bachelor’s degree 56 13.9 Loneliness 39.74 8.83 22–66 <0.001 Master’s degree 189 46.8 Doctoral degree 47 11.6 Note: DASS=Depression, Anxiety and Stress; PQ= prodromal questionnaire; Other 5 1.2 SNI=Social Network Index; Loneliness= the UCLA Loneliness scale. Prefer not to answer 2 0.5 Employment status identifies loneliness itself as a reliable risk factor for psychosis onset (da Full time (including full time students) 309 76.5 Part time ((including part time students) 16 4.0 Rocha et al., 2018; Mäki et al., 2014), especially during the COVID-19 Unemployed 40 9.9 <0.001 pandemic (Tso and Park, 2020). Research increasingly highlights the Retired 11 2.7 impact of loneliness on psychosis symptom expression, especially in Other 28 6.9 non-clinical population (da Rocha et al., 2018). Healthcare Worker Loneliness is defined as a discrepancy between an individual’s Yes 91 22.5 No 269 66.6 <0.001 preferred and actual social relations (Peplau and Perlman, 1982; n/a 44 10.9 Cacioppo et al., 2015). Increased loneliness is associated with lower Current Living situation education level, lower income, unemployment, single-status and history Living alone 59 14.6 of psychiatric diagnosis (Cacioppo et al., 2015). There are significant Living with friends/roommates 8 2.0 Living with partner 49 12.1 mental health consequences of loneliness. For example, higher levels of Living with family 282 69.8 <0.001 loneliness is associated with sensitivity to stress and threats (Nowland Homeless 1 0.2 et al., 2018) and the severity of post-traumatic stress disorder (PTSD) Other 4 1.0 (Solomon et al., 2015). Compared to the pre-pandemic period, there has Prefer not to answer 1 0.2 been a three-fold increase in severe loneliness brought about by General Health Poor 5 1.2 COVID-19 (O’Sullivan et al., 2021). This exacerbation of loneliness Fair 25 6.2 might be partially attributed to various public health interventions that Good 71 17.6 <0.001 were implemented to impede the spread of coronavirus including Very good 161 39.9 lockdowns, curtailing of social gatherings, and restricted travel. Excellent 83 20.5 Consequently, social isolation has been associated with depression, n/a 59 14.6 COVID-19 concern anxiety, and increased rates of suicide attempts among the general Not concerned 60 14.8 population (Elovainio et al., 2017). With respect to the COVID-19 Somewhat concerned 228 56.3 <0.001 pandemic, the risk for psychiatric disorders appears to be significantly Moderately concerned 51 12.6 increased by loneliness (Tso and Park, 2020; Park et al., 2020). More­ Extremely concerned 6 1.5 Traumatic experience over, the impact of existing PTSD symptomatology on perceived stress Yes 185 45.8 was mediated by loneliness (Jeftić et al., 2021): individuals might No 152 37.6 experience post-traumatic stress reactions (e.g., trauma-related fear and n/a 67 16.6 heightened physiological arousal) when triggered by traumatic re­ minders like lockdown and severe restrictions (Tsur et al., 2018). Although trauma triggers lose their intensity over time (Howell et al., Table 2 2015), it is important to examine how they may be associated with risk General health items (n = 345). for psychiatric disorders following recent war experiences in Croatia. Mean SD Range The impact of war-related trauma in Croatia has had detrimental effects Physical health was not good n 3.09 4.83 0–30 on mental health and quality of life in this population (Babić-Banaszak Mental health was not good n 5.97 8.05 0–30 et al., 2002; Vukojević et al., 2020). Similarly, the survivors of the war in Feeling happy (positive)p 17.02 9.10 0–30 Bosnia and Herzegovina were found to suffer from severe trauma even Feeling hopeful p 14.00 10.58 0–30 after 25 years. This study concluded that war experiences and reminders Feeling love p 18.62 19.06 0–30 n have devastating mental health consequences (Jeftić et al., 2021). Usual activities were affected due to health problems 5.59 8.30 0–30 Usual activities were affected due to pain n 3.67 7.03 0–30 In the first study on mental health in Croatia conducted during the Feeling worried. anxious. or tensen 7.52 8.92 0–30 first national lockdown (May 2020), between 17.8% and 19.1% of participants reported severe depression, anxiety, and stress (Jokić Begić p=positive direction, n=negative direction. Note1: Number of days (over the past 30 days) in which health problems et al., 2020). A second study in Croatia (Ajduković et al., 2020) con­ occurred; SD=standard deviation. ducted during July 2020, when the restrictions had been partially relaxed, reported that between 7.7% and 7.8% of participants were at risk for either depression or anxiety disorder, with high levels of stress in psychosocial stress related to the pandemic, potentially contributing to 7.2% of participants; these findings may show high levels of adaptability psychosis onset (Javed and Shad, 2021). Moreover, while social stress and resilience during the pandemic. Interestingly, in comparison to and social withdrawal are often regarded as prodromal symptoms of mental health data emerging from other European countries and some psychosis (van Winkel et al., 2008; Mäki et al., 2014), growing evidence parts of Asia, Croatia seems to have relatively lower incidences of stress, 2 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Fig. 1. Levels of depression, anxiety, and stress among 331 respondents. anxiety, and depression disorders (Newby et al., 2020; Park et al., 2020; Croatia. The participants completed an online, anonymous survey in Rossi et al., 2020). Studies have also shown that the prevalence of PTSD Croatian, created via SurveyMonkey. The survey link was distributed via among individuals in Croatia who had experienced at least one trau­ online channels and platforms including university emailing lists, social matic event during the COVID-19 pandemic was 14% (Ajduković et al., media platforms, and in person. Before starting the survey, participants 2020), which is similar to prevalence in Ireland, where acknowledged their participation was voluntary, and consented to COVID-19-related PTSD rate is 17.7% (Karatzias et al., 2020). Despite participate and have their anonymous data used for analysis. The survey the background of existing war-related trauma, mental health risk in the was open to everyone and described by introducing type of questions Croatian population during the pandemic appears to be broadly similar that will be asked, including the possibility to stop at any time. The to that of other countries. However, it is possible that within the Croa­ average time of survey completion was about 24 min. Data collection tian population, shared pain or adversity affected by war promotes occurred between July and September 2020, during the first peak wave solidarity, resulting in social cohesion (see Bastian et al., 2014). Upon of COVID-19 pandemic. This study received exempt status from the large scale disasters such as a massive earthquake or a terrorist attack, Vanderbilt University Institutional Review Board (Vanderbilt IRB people who work together to survive and help each other emotionally exempt #200,337). are more socially resilient and have better mental health outcomes (see Garcia and Rime, 2019). Thus, it may be that individual differences in 2.2. Measures vulnerability to psychological disorders might be uniquely affected by trauma and social disconnection. The survey consisted of 183 questions that asked about participant The present study investigated the role of psychosocial predictors of demographics, questions regarding COVID-19 concern, past trauma both physical and mental health (and, in particular, of loneliness) among exposure, and general and mental health, including validated measures the Croatian population during COVID-19, with specific focus on psy­ to assess loneliness (the UCLA (University of California, Los Angeles) chosis risk, depression, anxiety and stress. We hypothesized that lone­ Loneliness Scale; Russell, 1996); depression, anxiety, and stress liness would have a negative impact on mental health overall and will (Depression, Anxiety and Stress Scale (DASS-21); Lovibond and Lovi­ act as significant risk factor in predicting psychotic symptoms. Further, bond, 1995) and psychosis risk (Prodromal Questionnaire-16 (PQ-16); we expect that individuals with a history of trauma will be more Ising et al., 2012). Also, questions about social network were asked vulnerable to the effects of the current pandemic, loneliness, and psy­ (Social Network Index (SNI); Cohen et al., 1997). chosis risk. Because of Croatia’s recent history of transgenerational war To assess the effects of the COVID-19 pandemic on individuals’ daily trauma and the relative lack of prodromal data, this study presented a lives, we asked participants to self-report changes in their financial sit­ unique opportunity to examine the impact of loneliness and other psy­ uation, current/past quarantine periods, number of days spent at home, chosocial factors on psychosis-proneness. and level of concern about the pandemic. Likert scale ratings were given with appropriate responses to each item (i.e., for level of COVID 2. Methods concern, options ranged from not at all concerned to extremely concerned). To assess past and cumulative trauma, participants were asked to report 2.1. Participants and procedure experiences of traumatic events from an established list (e.g., natural disasters, war, sudden loss of family, abuse, and neglect, forced The sample consisted of 404 adults (aged 18 and above) residing in displacement etc.) with the option to write-in events that were not 3 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Table 4 Psychosocial predictors of general and mental health status. Model statistics Variable statistics df ΔR 2 ΔF p β T p General health Step 1 5 0.124 7.873 <0.001 Step 2 3 0.030 3.232 0.023 Age − 0.132 2.219 0.027* Gender − 0.001 0.015 0.988 Domestic abuse/ − 0.192 3.376 0.001* violence COVID-19 concern − 0.117 2.034 0.043* Traumatic experience − 0.089 1.510 0.132 SNI Social Network − 0.071 0.932 0.352 SNI Embedded Network 0.026 0.361 0.718 Loneliness − 0.179 3.047 0.003* Days physical health not good Step 1 5 0.076 4.591 <0.001 Step 2 3 0.074 8.039 <0.001 Age − 0.094 1.579 0.116 Gender 0.045 0.795 0.427 Domestic abuse/ 0.080 1.398 0.163 violence COVID-19 concern 0.108 1.885 0.061 Traumatic experience 0.107 1.805 0.072 SNI Social Network 0.162 2.134 0.034* SNI Embedded Network − 0.109 1.495 0.136 Loneliness 0.266 4.521 <0.001* Days mental health not good Step 1 5 0.148 9.659 <0.001 Step 2 3 0.129 16.352 <0.001 Age − 0.100 1.815 0.071 Gender 0.042 0.800 0.424 Domestic abuse/ 0.116 2.201 0.029* violence COVID-19 concern 0.137 2.590 0.010* Traumatic experience 0.166 3.038 0.003* SNI Social Network − 0.035 0.501 0.617 SNI Embedded Network − 0.115 1.707 0.089 Loneliness 0.318 5.846 <0.001* Days usual activities affected by health Step 1 5 0.077 4.623 <0.001 Step 2 3 0.062 6.675 <0.001 Age − 0.112 1.875 0.062 Gender 0.048 0.830 0.407 Domestic abuse/ 0.168 2.919 0.004* violence COVID-19 concern 0.136 2.357 0.019* Traumatic experience − 0.045 0.757 0.450 SNI Social Network 0.021 0.275 0.783 SNI Embedded Network 0.028 0.377 0.706 Loneliness 0.265 4.467 <0.001 Days usual activities affected by pain Step 1 5 0.058 3.453 0.005 Step 2 3 0.029 2.94 0.034 Age − 0.139 2.248 0.025* Gender 0.052 0.880 0.380 Domestic abuse/ 0.064 1.090 0.277 violence COVID-19 concern 0.129 2.162 0.031* Traumatic experience 0.070 1.150 0.251 SNI Social Network 0.053 0.674 0.501 SNI Embedded Network 0.037 0.488 0.626 Loneliness 0.176 2.879 0.004* Days feeling worried. anxious or tense Step 1 5 0.137 8.892 <0.001 Step 2 3 0.095 11.364 <0.001 Age − 0.195 3.445 0.001* Gender 0.044 0.820 0.413 Domestic abuse/ 0.087 1.603 0.110 violence COVID-19 concern 0.153 2.796 0.006* Traumatic experience 0.132 2.348 0.020* SNI Social Network 0.028 0.393 0.695 SNI Embedded Network − 0.074 1.073 0.284 Loneliness 0.306 5.457 <0.001* DASS stress (continued on next page) 4 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Table 4 (continued ) Model statistics Variable statistics df ΔR2 ΔF p β T p Step 1 5 0.152 9.824 <0.001 Step 2 3 0.179 24.203 <0.001 Age − 0.165 3.102 0.002* Gender 0.032 0.621 0.535 Domestic abuse/ 0.046 0.912 0.363 violence COVID-19 concern 0.032 0.623 0.534 Traumatic experience 0.229 4.335 <0.001* SNI Social Network 0.052 0.767 0.444 SNI Embedded Network 0.004 0.062 0.951 Loneliness 0.448 8.457 <0.001* DASS anxiety Step 1 5 0.129 8.133 <0.001 Step 2 3 0.127 15.491 <0.001 Age − 0.216 3.851 <0.001* Gender − 0.016 0.297 0.767 Domestic abuse/ 0.096 1.791 0.074 violence COVID-19 concern 0.049 0.897 0.371 Traumatic experience 0.158 2.835 0.005* SNI Social Network − 0.023 0.324 0.747 SNI Embedded Network 0.084 1.231 0.219 Loneliness 0.375 6.719 <0.001* DASS depression Step 1 5 0.158 10.342 <0.001 Step 2 3 0.219 31.834 <0.001 Age − 0.171 3.328 0.001* Gender 0.044 0.899 0.370 Domestic abuse/ 0.121 2.451 0.015* violence COVID-19 concern 0.050 1.018 0.309 Traumatic experience 0.161 3.157 0.002* SNI Social Network − 0.014 0.211 0.833 SNI Embedded Network − 0.023 0.372 0.711 Loneliness 0.477 9.341 <0.001 PQ total Step 1 5 0.135 8.371 <0.001 Step 2 3 0.168 21.264 <0.001 Age − 0.219 3.980 <0.001* Gender − 0.202 3.833 <0.001* Domestic abuse/ 0.094 1.779 0.076 violence COVID-19 concern 0.074 1.395 0.164 Traumatic experience 0.002 0.042 0.966 SNI Social Network − 0.068 0.974 0.331 SNI Embedded Network 0.050 0.736 0.462 Loneliness 0.418 7.647 <0.001* PQ distress Step 1 5 0.155 9.809 <0.001 Step 2 3 0.173 22.671 <0.001 Age − 0.217 4.017 <0.001* Gender − 0.118 2.279 0.023* Domestic abuse/ 0.208 4.009 <0.001 violence COVID-19 concern 0.059 1.140 0.255 Traumatic experience 0.033 0.611 0.542 SNI Social Network − 0.035 0.511 0.610 SNI Embedded Network 0.073 1.096 0.274 Loneliness 0.434 8.091 <0.001 Note1. Predictive variables kept in the second step: age, gender, domestic abuse/violence, level of concern about COVID-19, and traumatic experience. Note2. DASS=Depression, Anxiety and Stress; PQ= prodromal questionnaire. SNI=Social Network Index; Loneliness= the UCLA Loneliness scale. included in the list. Also, questions about instances of domestic Subjective feelings of loneliness and social isolation were assessed with violence/abuse in the past month were asked. the UCLA Loneliness Scale. Quality, size, and diversity of social net­ DASS-21 yielded three subscale scores quantifying depression, stress, works (e.g., number of social roles, embedded social networks, and and anxiety, which were then stratified into 5 severity levels ranging regular contacts) were assessed with SNI. from none to extremely severe. The PQ-16 assessed the number of psychotic-like experiences endorsed by each participant (i.e., their total 2.3. Statistical analysis score) and accompanying distress (i.e., their distress score). A total score of 6 or more qualifies high risk status for psychosis (Ising et al., 2012). Descriptive statistics were performed to measure demographic 5 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Fig. 2. Impact of loneliness on prodromal (PQ-16) scores during COVID-19. information, general and mental health statuses, COVID-19 concern, and mental health showed a significant negative association of age on gen­ incidence of trauma and domestic violence. T-tests were conducted to eral health, DASS subscales, and both PQ total and distress scores assess general health between age groups, genders, trauma groups, and (Table 4). Domestic abuse/violence was negatively associated to general concern levels regarding COVID-19. Hierarchical linear regressions were health in which there was an increase of days when mental health was also performed to assess the roles of psychosocial predictors, loneliness, poor and when activities were affected by poor health as well as and social network size in determining physical and mental health increased DASS depression. COVID-19 concern led to a decrease in variables. In the first step, independent variables for age, gender, do­ general health items; to an increase in the number of days when mental mestic violence, trauma experience, and concern for COVID- 19 were health was poor, when usual activities were affected by health and by used to form the basic model. In the second step, loneliness, social pain, and to an increased feelings of worry, anxiety, or tension. Past network diversity, and social network size were included in the full incidence of traumatic experience increased the number of days mental model. For each dependent variable (e.g., self-reported health, days health was poor, the days spent worried, anxious, or tense as well as physically ill, days when physical and mental health limited engagement stress, anxiety, and depression. In the second step, there was a signifi­ in usual activities, days when pain limited functioning, days mentally ill, cant negative association between loneliness and indices of general days feeling anxious, DASS, and PQ-scores), change in R2 between the health in this sample. The increased loneliness was positively associated basic model and full model was used to examine whether the addition of with the number of days physical health and mental health was poor; loneliness and/or the social network variables explained more of the days when usual activities were affected by health and by pain, and days variance in these variables, after controlling for age, gender, domestic when the participant felt worried, anxious, or tense. Also, increased violence, trauma, and COVID concern. Bonferroni correction of p < loneliness was associated with greater stress, anxiety, and depression. 0.0045 was applied to minimize Type I Errors. Lastly, participants reported the number of days in the past month when they experienced poor physical health. These “sick days” were nega­ 3. Results tively associated with the SNI (social network index) such that those with diminished social network were more likely to report increased The total of 404 (78.5% females) participants participated in the number of sick days. study. See Table 1 for the detailed descriptive data of the demographic The analysis of PQ items indicated that 16.7% participants met the information. From those, 85.4% completed the general health items criteria as high-risk for psychosis. Loneliness was positively associated (Table 2) of which 71–73% went on to complete the mental health item. to prodromal total and distress scores (Fig. 2). Gender influenced both DASS was completed by 81% of participants (Table 3, Fig. 1), PQ was PQ total and distress scores in which women endorsed fewer items and completed by 71% of which 17% were a high risk for psychosis reported less distress compared to man. However, there were no sig­ (Table 3), SNI was completed by 76% and 73.5% completed UCLA nificant sex differences in experience of loneliness. Domestic abuse/ Loneliness (Table 3). violence was positively associated only to PQ distress as well as was the Participants indicated an overall good physical and mental health concern with COVID. Furthermore, exposure to trauma was positively over the past 30 days (Table 2). associated to loneliness, but not to prodromal symptoms of psychosis. In the first step, the analysis of psychosocial measures of general and Importantly, both PQ total and distress scores were associated with 6 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Fig. 3. Impact of prodromal symptoms on depression, anxiety, and stress during COVID-19. DASS subscales in which higher PQ led to higher experience of stress, psychosis (da Rocha et al., 2018). The COVID-19 pandemic has dis­ anxiety, and depression (Fig. 3). rupted social connectedness and networking, which can provide pro­ tection against the distress, but also against the feelings of loneliness. 4. Discussion Given the relationship between loneliness and psychosis (Badcock et al., 2020) it is not surprising that psychosis-risk and loneliness are highly The preliminary findings highlight the important role of psychoso­ interrelated during the pandemic. cial factors, specifically loneliness, in determining mental wellbeing in With respect to trauma, domestic abuse/violence was also associated Croatia during the COVID-19 pandemic. Although most participants with elevated risk for psychosis. The impact of previous trauma strongly indicated overall good general health, our findings show that a sub­ affected the mental health and increased stress, anxiety, depression, and stantial number of psychosocial predictors including high levels of the number of days feeling worried, anxious, and tense during the COVID concern led to a decrease in both general health and wellbeing. pandemic. Surprisingly, previous exposure to trauma was relatively There was an overall increase in the number of days when mental health weakly associated with psychosis-risk, despite the history of wars and was not good, when usual activities were affected by poor health or pain, recent natural disasters in Croatia. One of the potential reasons for the and when participants felt worried, anxious, or tense. Our findings are in weak association could be the lower prevalence of psychosis in the line with overall research on the impact of COVID-19 pandemic on general population compared with the much greater rates of depression, mental health, suggesting that social isolation and distancing might anxiety, and stress. This is supported by the previous research findings increase signs of anxiety, depression, stress, and loneliness (Carvalho showing that within Croatian population, prevalence of depression, et al., 2020). anxiety and stress is very high (Loncar et al., 2006; Mollica et al., 2001). In our study, loneliness was found to be a considerable problem in Furthermore, one must consider the population-wide adaptation to the general population during the pandemic. It was associated with poor increasing levels of adversity over time across multiple generations in general health as well as poor mental health, feelings of worry, anxiety, Croatia, which has survived one-hundred years of war trauma resulting or tension. Loneliness had a statistically significant impact on psychosis- from the World War I, World War II, Independence War between 1991 proneness; with psychosis-proneness being strongly associated with and 1995 (Lampe et al., 2022). Thus, COVID-19 pandemic situation, depression, anxiety, and stress. This finding is in line with growing ev­ even though dire, maybe not have been experienced as stressful or idence for loneliness as a transdiagnostic risk factor across many traumatic as previous nation-wide catastrophes. Another possible different mental disorders, but especially as a major risk factor for explanation could be ascribed to mirroring behaviors (Dilthey and 7 A. Gizdic et al. Psychiatry Research 317 (2022) 114900 Rickman, 1976), which suggests that individuals tend to feel and behave Acknowledgments similarly to the overall crowd; strengthening the notion that all are bound together in this pandemic situation, resulting in resilience and We would like to thank Igna Brajevic-Gizdic, MD, PhD, psychiatrist protection from adverse effects (Vukojevic et al., 2020; Bastian et al., from Public Health Institute of Split and Dalmatia County, Mental 2014; Gracia et al., 2019). Lastly, post-trauma recovery treatments are Health Service Department for outpatient treatment of Addiction in commonly available in Croatia; for example, past war victims and sur­ Split, Croatia for help with data collection. vivors have undergone excessive PTSD treatments and/or are still under medical supervision and therapy. Therefore, this existing mental health References infrastructure might have provided much needed additional support. 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