Social disconnection and paranoid thoughts in the general population sample: A network analysis investigating differential associations of social isolation and loneliness

Social disconnection and paranoid thoughts in the general population sample: A network analysis investigating differential associations of social isolation and loneliness | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social disconnection and paranoid thoughts in the general population sample: A network analysis investigating differential associations of social isolation and loneliness Błażej Misiak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4992331/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Social disconnection has been implicated in the development of paranoia. Yet, both components of social disconnection, i.e., social isolation and loneliness, were mostly investigated separately. The present study aimed to explore as to whether social isolation and loneliness show differential associations with paranoid thoughts. Methods The study was based on a representative sample of 5,099 general population adults (aged 44.9 ± 15.4 years, 52.2% women). Self-reports were used to assess psychopathological symptoms, cognitive processes, perceptions of social interactions, loneliness, and social isolation. Results Linear regression and network analyses were performed. Loneliness and social isolation were significantly and independently associated with paranoid thoughts in linear regression analyses. Paranoid thoughts were more strongly associated with loneliness than social isolation. No significant association of the interaction between social isolation and loneliness with paranoid thoughts was found. A network analysis revealed that the nodes representing social isolation and loneliness were not directly connected to the nodes of paranoid thinking. In the shortest pathways, loneliness and social isolation were independently associated with paranoia. The shortest pathway between loneliness and paranoia led through only one mediating node representing external attribution biases. In turn, the shortest pathway between social isolation and paranoia led through two mediating nodes representing social anhedonia and external attribution biases. Conclusion The findings imply that social isolation and loneliness might exert additive effects on the occurrence of paranoid thoughts. External attribution biases and social anhedonia might play important roles in the association of social disconnection with paranoia. paranoia persecutory thoughts ideas of reference information processing social withdrawal Figures Figure 1 Figure 2 Figure 3 Introduction Paranoid thoughts can be defined as ungrounded beliefs that other people intentionally threaten, plot, or try to harm. These experiences are highly prevalent and in severe presentations may manifest as persecutory delusions [ 1 ]. Importantly, paranoid thoughts are considered transdiagnostic phenomena as they might also appear in the context of mental disorders that are not conceptualized within the psychosis spectrum, e.g., in personality and anxiety disorders [ 2 ]. In the general population samples, it has been shown that paranoid thinking is associated with younger age, lower intellectual functioning, stressful experiences, high levels of co-occurring psychiatric symptoms (e.g., anxiety, dissociation, and insomnia), substance use, and increased use of mental health services [ 1 , 3 – 5 ]. Social contexts are important in the development of psychotic experiences, represented by paranoid thoughts. In particular, several studies have focused on the role of social disconnection manifesting in social isolation and/or loneliness [ 6 – 8 ]. These two constructs, although often used interchangeably, refer to various aspects of social disconnection. Indeed, social isolation is an objective construct defined as the number of social bonds that is lower than the average [ 9 ]. In turn, loneliness covers the discrepancy between desired and actual social relationships and interactions [ 10 ]. Both constructs are also modestly correlated suggesting that they might show different underlying mechanisms and consequences. On the basis of a meta-analysis, it has been shown that loneliness is significantly associated with psychosis [ 11 ] and psychotic experiences [ 6 ]. Importantly, this association was found to be stronger in non-clinical than clinical samples [ 6 ]. Also, the authors of this meta-analysis found that loneliness is more strongly associated with paranoia than with psychotic experiences in general ( r = 0.448 vs. r = 0.302) [ 6 ]. It has been shown that social isolation and loneliness might be causally associated with the emergence of psychotic experiences. Indeed, some studies based on the experience sampling methodology (ESM) have demonstrated that loneliness and social isolation might predict the emergence of psychotic experiences in general or paranoia specifically [ 12 – 14 ]. These studies revealed that negative affect might mediate this association. In turn, another study demonstrated that negative affect while being alone, but not social isolation itself, predicts the occurrence of psychotic experiences [ 15 ]. However, bidirectional associations between psychotic experiences and loneliness have also been observed by ESM studies [ 13 ]. Potentially causal effects of loneliness on the emergence of paranoia have also been reported by experimental studies [ 16 , 17 ]. Various cognitive processes might explain on how social disconnection contributes to the development of paranoia. Among them, some studies have focused on the role of cognitive biases. In a convenience sample of middle-aged and older adults, it has been observed that external attribution biases (i.e., a tendency to attribute own actions and behaviours to actions and behaviours of other people) mediate that association between loneliness and psychotic experiences [ 18 ]. Similarly, there is evidence that individuals with psychosis are likely to engage in safety behaviours (i.e., actions undertaken to prevent anticipated harm) that have been shown to drive actions on persecutory delusions [ 19 ] and might be associated with experiencing loneliness [ 20 ]. Finally, it has been observed that impairments of social cognition (i.e., processes involved in the interpretation of social signals from other people) might be associated with a reduced social network size in people at clinical high risk of psychosis [ 21 ]. Some individuals might avoid social interactions due to high levels of rejection sensitivity and social interaction anxiety. Also, a longitudinal study revealed that rejection sensitivity might predict the occurrence of social interaction anxiety [ 22 ]. Moreover, it is important to note that paranoia and social interaction anxiety share a common denominator related to appraisals of social contexts as threatening. It has been shown that loneliness predicts both social interaction anxiety and paranoia [ 14 , 23 ]. There is also evidence that increased rejection sensitivity appears in individuals at clinical high risk of psychosis and might account for experiencing loneliness [ 24 ]. Finally, both psychotic experiences and social disconnection might also be the consequence of increased disinterest in social interactions (the phenomenon known as social anhedonia) [ 25 , 26 ]. Previous studies have shown a variety of processes that might explain the association between social disconnection and paranoia. However, some research gaps still exist and warrant deeper insights into this phenomenon. First, most studies have focused either on loneliness or social isolation neglecting potential interactions between both constructs. Second, specific processes linking paranoia and social disconnection have been assessed in separate models thereby limiting comprehensive insights. Therefore, the present study aimed to investigate as to whether social isolation and loneliness show an interactive effect in the association with paranoid thoughts in the general population sample. Second, the study aimed to explore as to whether different psychological processes (i.e., those related to cognitive processing and biased perceptions of social interactions) mediate the association between social disconnection and paranoia. Methods Participants Participants were enrolled through the quota sampling method in order to ensure sample representativeness in terms of sociodemographic characteristics (age, gender, the level of education, employment status, and place of residence across all federal states in Poland). The study was carried out in July – August, 2024. It was performed by a research company using its own online access panel. Members of this panel are enrolled through regular campaigns. In case of underrepresented groups (e.g., old-age individuals, ethnic minorities), additional campaigns are regularly initiated. Data were collected through the internet-based survey. All individuals aged at least 18 years were eligible for participation. Participants were informed about confidentiality of the survey. All of them provided consent to participate. The protocol of this study was approved by the Bioethics Committee at Wroclaw Medical University, Wroclaw, Poland. Measures All variables were measured using self-reports that were used in the Polish language versions (Table 1 ). Also, the items to record age, gender, the level of education, employment status, place of residence, and average monthly income were used. Moreover, the participants were surveyed about substance use in the preceding month (other than alcohol and nicotine), lifetime and preceding month history of psychiatric treatment. Table 1 Measures used in the present study. Domain Description Depressive symptoms The Patient Health Questionnaire-9 (PHQ-9) was administered (Kroenke et al., 2001). It includes 9 items that refer to the presence of depressive symptoms over the period of preceding 2 weeks. Items are rated on a 4-point scale (0 – “not at all”, 3 – “nearly every day”). The total score is 0–27 (higher scores indicate a greater level of depressive symptoms). The Cronbach’s alpha was 0.897 in the present study. Anxiety symptoms The Generalized Anxiety Disorder-7 (GAD-7) was administered (Spitzer et al., 2006). It includes 7 items that refer to the presence of generalized anxiety symptoms over the period of preceding 2 weeks. Items are rated on a 4-point scale (0 – “not at all”, 3 – “nearly every day”). The total score is 0–21 (higher scores indicate a greater level of depressive symptoms). The Cronbach’s alpha was 0.944 in the present study. Paranoia The Revised Green et al. Paranoid Thoughts Scale (R-GPTS) was administered (Freeman et al., 2021). It includes two subscales measuring ideas of reference (part A, 8 items) and ideas of persecution (part B, 10 items) over the period of preceding month. Items are rated on a 5-point scale (0 – “not at all”, 4 – “totally”). Respondents are instructed to rate experiences that did not occur under the influence of substance use. In the present study, the Cronbach’s alphas for parts A and B were 0.930 and 0.964, respectively. Social anhedonia The Revised Social Anhedonia Scale-Brief (RSAS-B) was used (Winterstein et al., 2011). The RSAS-B is an abbreviated version of the Revised Social Anhedonia Scale from the Wisconsin Schizotypy Scales (Eckblad et al., 1982). It includes 15 items with true-and-false responses. Responses to each item are rated as 1 or 0. The total RSAS-B score ranges between 0 and 15, where higher scores refer to greater levels of social anhedonia. The Cronbach’s alpha was 0.821 in the present study. Social interaction anxiety The Social Interaction Anxiety Scale (SIAS) was administered (Mattick and Clarke, 1998). It is based on 20 items describing various characteristics of social anxiety. Respondents are asked to rate the level each item is characteristic for them on a 5-point scale (0 – “not at all”, 4 – “extremely”). The Cronbach’s alpha was 0.947 in the present study. Rejection sensitivity The Adult Rejection Sensitivity Questionnaire (ARSQ) was used (Berenson et al., 2009). It describes 9 situations in which people ask things of others. Each situation is rated with the rejection concern item (responses range between 1 – “very unconcerned” and 6 – “very concerned”), and the rejection expectancy item (responses range between 1 – “very unlikely” and 6 – “very likely”. A rejection sensitivity score is calculated for each situation by multiplying the level of rejection concern by the level of rejection expectancy. The total rejection sensitivity score is the mean of rejection sensitivity scores across all situations. In the present study, the Cronbach’s alphas for rejection concern items and rejection expectancy items were 0.868 and 0.826, respectively. Cognitive biases The Davos Assessment of Cognitive Biases Scale-18 (DACOBS-18) was administered (Gaweda et al., 2018). It is an abbreviated version of the DACOBS(van der Gaag et al., 2013) that includes 18 items rated on a 7-point scale (1 – “strongly disagree” and 7 – “strongly agree”). The items are included in 4 specific subscales measuring attributional biases (4 items), safety behaviors (5 items), social cognition problems (4 items), and subjective cognitive problems (5 items). In the present study, the Cronbach’s alphas were 0.801, 0.745, 0.733, and 0.809 for the subscales measuring attributional biases, safety behaviors, social cognition problems, and subjective cognitive problems, respectively. Loneliness The 11-item version of the De Jong Gierveld Loneliness Scale (DJGLS) was used (de Jong-Gierveld and Kamphuls, 1985; Grygiel et al., 2013). Each item includes 5 possible responses (“yes!”, “yes”, “more or less”, “no”, and “no!”). It includes two subscales: the first one measures emotional loneliness (6 items) and the second one refers to social loneliness (5 items). The total score is calculated by counting positive and neutral responses (“yes!”, “yes”, and “more or less”) to items measuring emotional loneliness as well as negative and neutral responses (“no!”, “no”, and “more or less”) to items measuring social loneliness. The total DJGLS score ranges between 0 and 11, where higher scores indicate a greater level of loneliness. In the present study, the Cronbach’s alphas for emotional loneliness subscale and social loneliness subscale were 0.874 and 0.810, respectively. Social isolation A 6-item version of the Lubben Social Network Scale (LSNS-6) was administered (Lubben et al., 2006). The items measure the number of family members and friends who are seen or heard at least once a month, with whom the respondent can talk about private matters, and who can be called on for help. Items are rated on a 6-point scale. The total LSNS-6 score ranges between 0 and 20, where lower scores indicate a greater level of social isolation. The Cronbach’s alpha was 0.876 in the present study. Berenson, K.R., Gyurak, A., Ayduk, O., Downey, G., Garner, M.J., Mogg, K., Bradley, B.P., Pine, D.S., 2009. Rejection sensitivity and disruption of attention by social threat cues. J Res Pers 43, 1064–1072. de Jong-Gierveld, J., Kamphuls, F., 1985. The Development of a Rasch-Type Loneliness Scale. Appl Psychol Meas 9, 289–299. Eckblad, M., Chapman, L.J., Chapman, J.P., Mishlove, M., 1982. The revised social anhedonia scale. University of Wisconsin. Freeman, D., Loe, B.S., Kingdon, D., Startup, H., Molodynski, A., Rosebrock, L., Brown, P., Sheaves, B., Waite, F., Bird, J.C., 2021. The revised Green et al., Paranoid Thoughts Scale (R-GPTS): psychometric properties, severity ranges, and clinical cut-offs. Psychol Med 51, 244–253. Gaweda, L., Prochwicz, K., Krezolek, M., Klosowska, J., Staszkiewicz, M., Moritz, S., 2018. Self-reported cognitive distortions in the psychosis continuum: A Polish 18-item version of the Davos Assessment of Cognitive Biases Scale (DACOBS-18). Schizophr Res 192, 317–326. Grygiel, P., Humenny, G., Rebisz, S., Świtaj, P., Sikorska, J., 2013. Validating the Polish Adaptation of the 11-Item De Jong Gierveld Loneliness Scale. Eur J Psychol Assess 29, 129–139. Kroenke, K., Spitzer, R.L., Williams, J.B., 2001. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 16, 606–613. Lubben, J., Blozik, E., Gillmann, G., Iliffe, S., von Renteln Kruse, W., Beck, J.C., Stuck, A.E., 2006. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist 46, 503–513. Mattick, R.P., Clarke, J.C., 1998. Social Interaction Anxiety Scale (SIAS). APA PsycTests. Spitzer, R.L., Kroenke, K., Williams, J.B., Lowe, B., 2006. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 166, 1092–1097. van der Gaag, M., Schutz, C., Ten Napel, A., Landa, Y., Delespaul, P., Bak, M., Tschacher, W., de Hert, M., 2013. Development of the Davos assessment of cognitive biases scale (DACOBS). Schizophr Res 144, 63–71. Winterstein, B.P., Silvia, P.J., Kwapil, T.R., Kaufman, J.C., Reiter-Palmon, R., Wigert, B., 2011. Brief assessment of schizotypy: Developing short forms of the Wisconsin Schizotypy scales. Pers Individ Dif 51, 920–924. Statistical analysis There were no missing data, except for those related to monthly income as some participants refused to provide this information. In the first step, linear regression analyses were performed. The levels of ideas of persecution and reference were included as a dependent variable in separate models. Model 1 was limited to testing direct effects of loneliness and social isolation, while model 2 also included the interaction between loneliness and social isolation. Covariates (age, gender, the level of education, employment status, place of residence, monthly income, a lifetime history of psychiatric treatment, and substance use in the preceding months) were added to model 3. To control for multicollinearity, the variance inflation factor (VIF) was assessed. The VIF values higher than 4 were interpreted as those indicating significant multicollinearity [ 39 ]. This part of data analysis was carried out in the SPSS software, version 28. To provide insights into potential mechanisms underlying the association between social disconnection components, a network analysis was performed in the R software. It included the following variables: (1) age; (2) gender; (3) the level of education; (4) place of residence; (5) employment status; (6) monthly income; (7) a lifetime history of psychiatric treatment; (8) substance use in the preceding month; (9) loneliness; (10) social isolation; (11) depressive symptoms; (12) anxiety symptoms; (13) ideas of persecution; (14) ideas of reference; (15) social anhedonia; (16) rejection sensitivity; (17) social interaction anxiety; (18) attributional biases; (19) safety behaviours; (20) social cognition problems, and (21) subjective cognitive problems. Variables 1–7 were included as covariates. Due to inclusion of both categorical and continuous variables, the mixed graphical models implemented in the mgm package [ 40 ] were used to estimate the network. The L1-penalized regression (LASSO) was performed to provide regularization and shrink weak associations [ 41 ]. The Extended Bayesian Information Criterion (EBIC), using the tuning parameter λ that controls the level of sparsity, was applied to select the penalty parameter [ 42 ]. The λ was set at 0.5 as proposed previously [ 41 ]. To indicate the shortest pathways between the measures of social disconnection (i.e., social isolation and loneliness) and paranoid thoughts, the Dijkstra’s algorithm was used [ 43 ]. This algorithm allows to show the minimum number of mediating variables with the strongest correlation coefficients that are needed to appear between variables of interest. Node centralities were assessed by estimating the bridge expected influence [ 44 ]. It represents the sum of positive and negative edge weights between the node in a specific community and all nodes from other communities. Communities were identified using the “ walktrap ” algorithm implemented in the EGAnet package [ 45 ]. The network accuracy and stability were analysed in the bootnet package [ 46 ]. The case-drop bootstrapping with 1,000 iterations was used to assess stability of the bridge expected influence and edge weights [ 46 ]. The network was considered stable if the correlation stability coefficient (CS-C) was higher than 0.25 (preferably it should be higher than 0.50). Moreover, for all edge weights, the 95%CI was estimated and visualized using non-parametric bootstrapping. A higher 95%CI indicates a lower precision in estimating edge weights. All visualizations were prepared using the qgraph package [ 47 ]. Results General characteristics of the sample General characteristics of the sample and a flow diagram of participants are shown in Table 2 and Figure S1 , respectively. A total of 5,099 individuals (aged 44.9 ± 15.4 years, 52.2% women) participated in the present study. Most frequently, the participants reported a higher level of education (49.0%), full-time employment (57.8%), urban place of residence (67.6%), and a monthly income of 750–1,500 USD (48.7%). A lifetime and preceding month history of psychiatric treatment was reported by 21.7% and 10.6% participants, respectively. Substance use (other than alcohol and nicotine) in the preceding month was reported by 6.9% participants. Table 2 Descriptive characteristics of the sample ( n = 5099). Mean ± SD or n (%) Age, years 44.9 ± 15.4 Gender Men Women Other 2431 (47.7) 2662 (52.2) 6 (0.1) Education Primary Vocational Secondary Higher 94 (1.8) 411 (8.1) 2098 (41.1) 2496 (49.0) Employment status Unemployed Retired Full-time employment Part-time employment Student 435 (8.5) 1002 (19.6) 2946 (57.8) 482 (9.5) 234 (4.6) Place of residence Rural Urban, up to 50,000 inhabitants Urban, 50,000–150,000 inhabitants Urban, 150,000–500,000 inhabitants Urban, > 500,000 inhabitants 1650 (32.4) 1166 (22.9) 816 (16.0) 714 (14.0) 753 (14.7) Monthly income 3,750 USD Refused to answer 1082 (21.2) 2485 (48.7) 722 (14.2) 133 (2.6) 44 (0.9) 633 (12.4) Psychiatric treatment, lifetime 1108 (21.7) Psychiatric treatment, preceding month 539 (10.6) Substance use (other than alcohol and nicotine), preceding month 353 (6.9) LSNS-6, social isolation 15.9 ± 6.0 DJGLS, loneliness 5.2 ± 3.7 RSAS, social anhedonia 4.5 ± 3.5 ARSQ, rejection sensitivity 11.5 ± 5.3 SIAS, social interaction anxiety 30.7 ± 16.1 DACOBS-18, subjective cognitive problems 16.5 ± 5.9 DACOBS-18, social cognition problems 14.2 ± 4.4 DACOBS-18, attributional biases 13.9 ± 5.0 DACOBS-18, safety behaviors 14.4 ± 5.5 PHQ-9, depressive symptoms 7.4 ± 6.0 GAD-7, anxiety symptoms 6.1 ± 5.5 RGPTS, ideas of reference 9.1 ± 8.1 RGPTS, ideas of persecution 7.7 ± 10.0 Linear regression analyses Results of linear regression analyses are reported in Table 3 . There were significant main effects of loneliness and social isolation on the level of ideas of persecution across all models. Also, significant main effects of loneliness on ideas of reference were significant across all models. Main effect of social isolation on ideas of reference was significant only after adjustment for covariates. No significant effects of the interaction between loneliness and social isolation on the level of paranoid thoughts were found. Model 3 (i.e., with the effects of covariates) explained significantly higher percentage of variance (as measured by R 2 values) compared to models 1 and 2. All VIF values were lower than 4. Table 3 Results of linear regression analysis testing the association of loneliness and social isolation with paranoid thoughts. Model Independent variable Dependent variable Ideas of persecution * Ideas of reference ** β p β p Model 1 Loneliness 0.369 < 0.001 0.402 < 0.001 Social isolation 0.040 < 0.001 0.023 0.121 Model 2 Loneliness 0.369 < 0.001 0.402 < 0.001 Social isolation 0.040 < 0.001 0.023 0.121 Loneliness × social isolation 0.002 0.853 –0.004 0.729 Model 3 Loneliness 0.295 < 0.001 0.329 < 0.001 Social isolation 0.096 < 0.001 0.067 < 0.001 Loneliness × social isolation –0.009 0.479 –0.016 0.193 Age –0.180 < 0.001 –0.204 < 0.001 Gender –0.030 0.023 0.017 0.180 Education level –0.093 < 0.001 –0.084 < 0.001 Employment status –0.031 0.024 –0.035 0.020 Place of residence –0.023 0.079 –0.034 0.008 Substance use (previous month) 0.086 < 0.001 0.081 < 0.001 Psychiatric treatment (lifetime) 0.055 < 0.001 0.074 < 0.001 * R 2 = 0.188 for model 3 (significantly higher compared to models 1 and 2, p < 0.001) * R 2 = 0.224 for model 3 (significantly higher compared to models 1 and 2, p < 0.001) Network estimation The network estimated in the present study is shown in Fig. 1 A. A total of 67 edges, out of 210 potential edges, had a non-zero weight (31.9%, Table S1 ). No isolated nodes were detected. Shortest pathways in the network The shortest pathways between social disconnection measures (i.e., loneliness and social isolations) and paranoid thoughts are shown in Fig. 2 . In these pathways, loneliness was connected to ideas of persecution through a mediating effect of attributional biases. In turn, social isolation was connected to ideas of persecution through the effects of social anhedonia and attributional biases. Importantly, loneliness and social isolation were not directly interconnected within the shortest pathways. Bridge centrality Altogether, four communities of nodes were identified in the network (Figure S2). Two communities represented covariates. The first one included age, gender, the level of education, place of residence, employment status, and monthly income. The second one covered a lifetime history of psychiatric treatment and substance use (other than alcohol and nicotine) in the preceding month. Interestingly, social isolation and loneliness clustered together with social anhedonia, social interaction anxiety, rejection sensitivity, attributional biases, safety behaviours, social cognition problems, and subjective cognitive problems. Finally, the community of psychopathological symptoms was identified and included depressive symptoms, anxiety symptoms, ideas of persecution, and ideas of reference. Apart from covariates, nodes with the highest bridge expected influence were social interaction anxiety, social anhedonia, loneliness, attributional biases, and rejection sensitivity (in decreasing order, Fig. 1 B). Network stability and accuracy The CS-C value was 0.75 (the same value was obtained for the bridge expected influence and edge weights) indicating that results were stable while dropping various proportions of data (Figure S2). For most edge weights, the 95%CI range was relatively narrow suggesting sufficient accuracy (Figure S3). Discussion Main findings from this study indicate that loneliness and social isolation exert additive effects on the level of paranoid thoughts. However, both social disconnection components were not found to be directly connected to paranoid thoughts. The most likely pathway from loneliness to paranoid thoughts led through attributional biases. In turn, the most likely pathway from social isolation to paranoid thoughts appeared to require two mediating nodes, i.e., social anhedonia and attributional biases. Importantly, within the shortest pathways, social isolation and loneliness were not interconnected confirming the findings of linear regression analyses that both phenomena might be independently associated with the occurrence of paranoid thoughts. To our knowledge, potential interactive effects of social isolation and loneliness on the occurrence of psychotic experiences have not been reported so far. It is needed to note that social disconnection has been associated with a variety of negative health outcomes, beyond those related to mental health. To date, combined effects of loneliness and social isolation have been documented with respect to age-related cognitive decline [ 48 ]. There is evidence that individuals who experience both loneliness and social isolation show worse health risk profiles than those with one or the other alone [ 49 , 50 ]. In case of memory impairments, it has been shown that social isolation exerts larger effects than loneliness [ 48 ]. In our study, we found that loneliness is more closely related to paranoid thinking. Also, our linear regression analyses revealed that effects of loneliness on paranoid thoughts were stronger compared to those of social isolation. These observations might suggest that specific combinations of social disconnection components might exert differential effects on specific health outcomes. Experimental and ESM studies have demonstrated that loneliness might contribute to the emergence of psychotic experiences in general and paranoia specifically. Also, as noted by a prior systematic review, lonely individuals hold hostile intent attributions [ 51 ]. According to cognitive models, loneliness increases hypervigilance for social threats and the risk of attentional and confirmatory biases making lonely individuals more likely to perceive the world as threatening and to develop negative perceptions about other people [ 52 , 53 ]. In light of evolutionary considerations, these processes play a self-protective role [ 54 ]. A bias towards perception of others being responsible for negative events (i.e., external attribution bias) has been conceptualized as the core mechanism underlying the development of paranoia. In these considerations, paranoia has also been posited as a defence against reduced self-esteem [ 55 – 57 ]. On the basis of a meta-analysis, it has been shown attributional biases are highly prevalent among individuals at clinical high risk of psychosis [ 58 ]. In this meta-analysis, the effect size for attributional biases was higher (g = -0.708) than the one for other cognitive processes, including social cognition (g = -0.477), emotion processing (g = -0.446), and social perception (g = -0.383). External attributions have also been associated with psychotic experiences in non-clinical samples [ 59 ]. In the present study, the shortest pathway between social isolation and paranoid thoughts was similar to the one between loneliness and paranoid thoughts. However, it also appeared to include the effects of social anhedonia that was ranked among nodes with the highest bridge centrality in the network. These observations suggest that social isolation is most likely related to paranoid thoughts only if social anhedonia is present. By definition, social anhedonia is a trait-like disinterest in and a lack of reward from social interactions [ 60 ]. Individuals with high levels of social anhedonia prefer solitude and report reduced negative affect while being alone [ 61 , 62 ]. Moreover, there is some evidence that social anhedonia might predict the development of psychosis and psychotic symptoms [ 26 ] over time [ 63 ]. There are certain limitations of the present study that need to be considered. First, the study was cross-sectional and thus conclusions about causality cannot be made. However, at this point it is needed to note that social disconnection has been bidirectionally associated with the occurrence of psychotic symptoms. Second, although the study was based on a large and representative sample, the selection bias cannot be ruled out. Indeed, the questionnaires were only available in the Polish language and the study was based on the online survey. Therefore, individuals with potentially higher levels of social disconnection, i.e., those with migrant status and those who do not use internet were likely underrepresented in our sample. Third, it is needed to note that single-timepoint assessments of social disconnection do not provide full insights into chronicity of loneliness and social isolation. Indeed, it has been suggested that chronic and acute social disconnection might exert differential effects on health outcomes [ 7 ]. Finally, findings may not be generalizable over clinical populations as the participants did not undergo a thorough clinical assessment. The present study offers important implications for clinical practice. It indicates that a thorough assessment of social disconnection components might be of importance while planning specific interventions for paranoid experiences. At this point, it is also needed to note the bridging effect of social anhedonia in the association between social isolation and paranoid thoughts. This might imply that increasing social contacts may not be effective in people with paranoid thoughts and social isolation as they might show reduced pleasure from social interactions. In this regard, targeting attributional biases that also appeared to bridge the association of both social isolation and loneliness with paranoid thoughts might be promising. To date, optimal interventions for loneliness and social isolation in people with paranoid thoughts have not been developed. Moreover, studies addressing the efficacy of cognitive-behavioural therapy for psychosis with respect to improving the level of loneliness have provided mixed findings [ 64 , 65 ]. Nevertheless, there is some evidence that interventions focused on loneliness might be feasible in people with psychosis and need to be developed [ 66 ]. In sum, findings from the present study warrant the need to dissect the effects of loneliness and social isolation while investigating the role of social disconnection in people with psychosis-related outcomes. Both components of social disconnection might show additive effects with respect to the occurrence of paranoid thoughts. Yet, the relevance of social isolation in people with paranoid thoughts might be weaker compared to loneliness. Our findings also indicate the aberrant information processing and social anhedonia play important roles in the association between social disconnection and paranoid thoughts. Future studies need to provide deeper insights into our findings by investigating clinical population using longitudinal designs. Moreover, it is needed to study distinct combinations of social isolation and loneliness with respect to various outcomes in people with psychosis including those related to somatic health. Declarations Competing interests The author declares no competing interests Funding The present study was funded from “the Initiative of Excellence – Research University” provided by Wroclaw Medical University, Wroclaw, Poland (task number: IDUB.C230.24.001). Author Contribution BM – conceptualization, methodology, funding acquisition, data curation, validation, data analysis, visualization, manuscript writing Data Availability Data supporting the present study are available from the corresponding author upon a reasonable request. References Freeman D, McManus S, Brugha T, Meltzer H, Jenkins R, Bebbington P (2011) Concomitants of paranoia in the general population. Psychol Med 41(5):923–936. 10.1017/S0033291710001546 Fanti E, Di Sarno M, Di Pierro R (2023) In search of hidden threats: A scoping review on paranoid presentations in personality disorders. 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PLoS ONE 15(3):e0230673–e0230673. 10.1371/journal.pone.023067 Newall NEG, Menec VH (2019) Loneliness and social isolation of older adults: Why it is important to examine these social aspects together. J Soc Pers Relat 36(3):925–939. 10.1177/0265407517749045 Spithoven AWM, Bijttebier P, Goossens L (2017) It is all in their mind: A review on information processing bias in lonely individuals. Clin Psychol Rev 58:97–114. 10.1016/j.cpr.2017.10.003 Cacioppo JT, Hawkley LC (2009) Perceived social isolation and cognition. Trends Cogn Sci 13(10):447–454. 10.1016/j.tics.2009.06.005 Howes OD, Murray RM (2014) Schizophrenia: an integrated sociodevelopmental-cognitive model. Lancet 383(9929):1677–1687. 10.1016/S0140-6736(13)62036-X Cacioppo JT, Hawkley LC, Ernst M, Burleson M, Bernston GG, Nouriani B, Spiegel D (2006) Loneliness within a nomological net: An evolutionary perspective. J Res Personality 40:1054–1085. 10.1016/j.jrp.2005.11.007 Bentall RP, Kinderman P, Kaney S (1994) The self, attributional processes and abnormal beliefs: towards a model of persecutory delusions. Behav Res Ther 32(3):331–341. 10.1016/0005-7967(94)90131-7 Bentall RP, Corcoran R, Howard R, Blackwood N, Kinderman P (2001) Persecutory delusions: a review and theoretical integration. Clin Psychol Rev 21(8):1143–1192. 10.1016/s0272-7358(01)00106-4 Murphy P, Bentall RP, Freeman D, O'Rourke S, Hutton P (2018) The paranoia as defence model of persecutory delusions: a systematic review and meta-analysis. Lancet Psychiatry 5(11):913–929. 10.1016/S2215-0366(18)30339-0 Lee TY, Hong SB, Shin NY, Kwon JS (2015) Social cognitive functioning in prodromal psychosis: A meta-analysis. Schizophr Res 164(1–3):28–34. 10.1016/j.schres.2015.02.008 Livet A, Navarri X, Potvin S, Conrod P (2020) Cognitive biases in individuals with psychotic-like experiences: A systematic review and a meta-analysis. Schizophr Res 222:10–22. 10.1016/j.schres.2020.06.016 Barkus E, Badcock JC (2019) A Transdiagnostic Perspective on Social Anhedonia. Front Psychiatry 10:216. 10.3389/fpsyt.2019.00216 Brown LH, Silvia PJ, Myin-Germeys I, Kwapil TR (2007) When the need to belong goes wrong: the expression of social anhedonia and social anxiety in daily life. Psychol Sci 18(9):778–782. 10.1111/j.1467-9280.2007.01978.x Kwapil TR, Silvia PJ, Myin-Germeys I, Anderson AJ, Coates SA, Brown LH (2009) The social world of the socially anhedonic: exploring the daily ecology of asociality. J Res Pers 43:103–106. 10.1016/j.jrp.2008.10.008 Kwapil TR (1998) Social anhedonia as a predictor of the development of schizophrenia-spectrum disorders. J Abnorm Psychol 107(4):558–565. 10.1037//0021-843x.107.4.558 Winkler K, Lincoln TM, Wiesjahn M, Jung E, Schlier B (2024) How does loneliness interact with positive, negative and depressive symptoms of psychosis? New insights from a longitudinal therapy process study. Schizophr Res 271:179–185. 10.1016/j.schres.2024.07.024 Jackson HJ, McGorry PD, Killackey E, Bendall S, Allott K, Dudgeon P, Gleeson J, Johnson T, Harrigan S (2008) Acute-phase and 1-year follow-up results of a randomized controlled trial of CBT versus Befriending for first-episode psychosis: the ACE project. Psychol Med 38(5):725–735. 10.1017/S0033291707002061 Lim MH, Penn DL, Thomas N, Gleeson JFM (2020) Is loneliness a feasible treatment target in psychosis? Soc Psychiatry Psychiatr Epidemiol 55(7):901–906. 10.1007/s00127-019-01731-9 Additional Declarations No competing interests reported. Supplementary Files SupplementaryAppendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4992331","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":352449312,"identity":"eb20fd43-02ef-49fe-a7bb-737b57dcd9a3","order_by":0,"name":"Błażej Misiak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYBACA3YQycPAwMbA2MDYUAERlQBiGZxamFG0nEFo4cGvBQoYG9uI0GLOzPz4wwcZhmg+/sONH2fOOxxtcID54G0ehjs4tVg2sxkYzuBhyG2TSGyW3LjtcO6GA2zJ1jwMz3A77DCDQTIPWAtjg+RDoJZtB3jMpHkYDuPRwv7h8B+QFv6DzT8fzgFp4f9GQAuPYTMDSAtDYpvkxgawLWx4tVg28xQz9vBIgPzSZjnjWHru/sNsxpZzDHD7xZy9ffOHnz02ufP7jz++2VNjnTuzvfnhjTcVd+RwaQEDxh4JJB44pgwO4NXBwPADU4iQllEwCkbBKBhBAAAWFlX+1sFFagAAAABJRU5ErkJggg==","orcid":"","institution":"Wroclaw Medical University","correspondingAuthor":true,"prefix":"","firstName":"Błażej","middleName":"","lastName":"Misiak","suffix":""}],"badges":[],"createdAt":"2024-08-28 15:46:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4992331/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4992331/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65458593,"identity":"1315a6b2-19d5-4261-8971-212ca1e310e3","added_by":"auto","created_at":"2024-09-27 17:02:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":530508,"visible":true,"origin":"","legend":"\u003cp\u003eThe network analysed in the present study. Specific variables are visualized as nodes that are connected with edges. Filled parts of the rings around nodes show predictability. Thicker and more saturated edges indicate stronger associations. Green edges represent positive associations, red edges show negative associations while grey edges indicate relationships between categorical variables with more than 2 levels, for which no sign can be indicated.\u003c/p\u003e","description":"","filename":"Figure1651.png","url":"https://assets-eu.researchsquare.com/files/rs-4992331/v1/2316e590d1947a8011ff8c0a.png"},{"id":65459176,"identity":"0b026b9a-1f4b-4666-9eb4-54eacfa62f52","added_by":"auto","created_at":"2024-09-27 17:10:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":418635,"visible":true,"origin":"","legend":"\u003cp\u003eThe bridge expected influence of all nodes in the network.\u003c/p\u003e","description":"","filename":"Figure1652.png","url":"https://assets-eu.researchsquare.com/files/rs-4992331/v1/d8b4600867b3fe6d949e336c.png"},{"id":65458591,"identity":"c0b73b5e-c9d0-4c25-a4bc-0f0dc469b087","added_by":"auto","created_at":"2024-09-27 17:02:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eThe shortest pathways between loneliness (A), social isolation (B), and paranoid thoughts.\u003c/p\u003e","description":"","filename":"Figure1653.png","url":"https://assets-eu.researchsquare.com/files/rs-4992331/v1/d430442acbae78a0aa97540e.png"},{"id":70094402,"identity":"694d31e0-db64-4237-b853-c5f65d564142","added_by":"auto","created_at":"2024-11-28 09:32:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1463286,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4992331/v1/f7bf68da-67b7-445e-8abe-c45b9ab72293.pdf"},{"id":65459177,"identity":"5a6d0b9f-bc3c-4292-a575-d28ccb208fd2","added_by":"auto","created_at":"2024-09-27 17:10:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":400922,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryAppendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-4992331/v1/a767d2b9e4b534d650a6070a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Social disconnection and paranoid thoughts in the general population sample: A network analysis investigating differential associations of social isolation and loneliness","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParanoid thoughts can be defined as ungrounded beliefs that other people intentionally threaten, plot, or try to harm. These experiences are highly prevalent and in severe presentations may manifest as persecutory delusions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Importantly, paranoid thoughts are considered transdiagnostic phenomena as they might also appear in the context of mental disorders that are not conceptualized within the psychosis spectrum, e.g., in personality and anxiety disorders [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the general population samples, it has been shown that paranoid thinking is associated with younger age, lower intellectual functioning, stressful experiences, high levels of co-occurring psychiatric symptoms (e.g., anxiety, dissociation, and insomnia), substance use, and increased use of mental health services [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSocial contexts are important in the development of psychotic experiences, represented by paranoid thoughts. In particular, several studies have focused on the role of social disconnection manifesting in social isolation and/or loneliness [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These two constructs, although often used interchangeably, refer to various aspects of social disconnection. Indeed, social isolation is an objective construct defined as the number of social bonds that is lower than the average [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In turn, loneliness covers the discrepancy between desired and actual social relationships and interactions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Both constructs are also modestly correlated suggesting that they might show different underlying mechanisms and consequences. On the basis of a meta-analysis, it has been shown that loneliness is significantly associated with psychosis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and psychotic experiences [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Importantly, this association was found to be stronger in non-clinical than clinical samples [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Also, the authors of this meta-analysis found that loneliness is more strongly associated with paranoia than with psychotic experiences in general (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.448 vs. \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.302) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt has been shown that social isolation and loneliness might be causally associated with the emergence of psychotic experiences. Indeed, some studies based on the experience sampling methodology (ESM) have demonstrated that loneliness and social isolation might predict the emergence of psychotic experiences in general or paranoia specifically [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These studies revealed that negative affect might mediate this association. In turn, another study demonstrated that negative affect while being alone, but not social isolation itself, predicts the occurrence of psychotic experiences [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, bidirectional associations between psychotic experiences and loneliness have also been observed by ESM studies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Potentially causal effects of loneliness on the emergence of paranoia have also been reported by experimental studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVarious cognitive processes might explain on how social disconnection contributes to the development of paranoia. Among them, some studies have focused on the role of cognitive biases. In a convenience sample of middle-aged and older adults, it has been observed that external attribution biases (i.e., a tendency to attribute own actions and behaviours to actions and behaviours of other people) mediate that association between loneliness and psychotic experiences [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, there is evidence that individuals with psychosis are likely to engage in safety behaviours (i.e., actions undertaken to prevent anticipated harm) that have been shown to drive actions on persecutory delusions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and might be associated with experiencing loneliness [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Finally, it has been observed that impairments of social cognition (i.e., processes involved in the interpretation of social signals from other people) might be associated with a reduced social network size in people at clinical high risk of psychosis [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome individuals might avoid social interactions due to high levels of rejection sensitivity and social interaction anxiety. Also, a longitudinal study revealed that rejection sensitivity might predict the occurrence of social interaction anxiety [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, it is important to note that paranoia and social interaction anxiety share a common denominator related to appraisals of social contexts as threatening. It has been shown that loneliness predicts both social interaction anxiety and paranoia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. There is also evidence that increased rejection sensitivity appears in individuals at clinical high risk of psychosis and might account for experiencing loneliness [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Finally, both psychotic experiences and social disconnection might also be the consequence of increased disinterest in social interactions (the phenomenon known as social anhedonia) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have shown a variety of processes that might explain the association between social disconnection and paranoia. However, some research gaps still exist and warrant deeper insights into this phenomenon. First, most studies have focused either on loneliness or social isolation neglecting potential interactions between both constructs. Second, specific processes linking paranoia and social disconnection have been assessed in separate models thereby limiting comprehensive insights. Therefore, the present study aimed to investigate as to whether social isolation and loneliness show an interactive effect in the association with paranoid thoughts in the general population sample. Second, the study aimed to explore as to whether different psychological processes (i.e., those related to cognitive processing and biased perceptions of social interactions) mediate the association between social disconnection and paranoia.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eParticipants were enrolled through the quota sampling method in order to ensure sample representativeness in terms of sociodemographic characteristics (age, gender, the level of education, employment status, and place of residence across all federal states in Poland). The study was carried out in July \u0026ndash; August, 2024. It was performed by a research company using its own online access panel. Members of this panel are enrolled through regular campaigns. In case of underrepresented groups (e.g., old-age individuals, ethnic minorities), additional campaigns are regularly initiated. Data were collected through the internet-based survey. All individuals aged at least 18 years were eligible for participation. Participants were informed about confidentiality of the survey. All of them provided consent to participate. The protocol of this study was approved by the Bioethics Committee at Wroclaw Medical University, Wroclaw, Poland.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eAll variables were measured using self-reports that were used in the Polish language versions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Also, the items to record age, gender, the level of education, employment status, place of residence, and average monthly income were used. Moreover, the participants were surveyed about substance use in the preceding month (other than alcohol and nicotine), lifetime and preceding month history of psychiatric treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasures used in the present study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Patient Health Questionnaire-9 (PHQ-9) was administered (Kroenke et al., 2001). It includes 9 items that refer to the presence of depressive symptoms over the period of preceding 2 weeks. Items are rated on a 4-point scale (0 \u0026ndash; \u0026ldquo;not at all\u0026rdquo;, 3 \u0026ndash; \u0026ldquo;nearly every day\u0026rdquo;). The total score is 0\u0026ndash;27 (higher scores indicate a greater level of depressive symptoms). The Cronbach\u0026rsquo;s alpha was 0.897 in the present study.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Generalized Anxiety Disorder-7 (GAD-7) was administered (Spitzer et al., 2006). It includes 7 items that refer to the presence of generalized anxiety symptoms over the period of preceding 2 weeks. Items are rated on a 4-point scale (0 \u0026ndash; \u0026ldquo;not at all\u0026rdquo;, 3 \u0026ndash; \u0026ldquo;nearly every day\u0026rdquo;). The total score is 0\u0026ndash;21 (higher scores indicate a greater level of depressive symptoms). The Cronbach\u0026rsquo;s alpha was 0.944 in the present study.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParanoia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Revised Green et al. Paranoid Thoughts Scale (R-GPTS) was administered (Freeman et al., 2021). It includes two subscales measuring ideas of reference (part A, 8 items) and ideas of persecution (part B, 10 items) over the period of preceding month. Items are rated on a 5-point scale (0 \u0026ndash; \u0026ldquo;not at all\u0026rdquo;, 4 \u0026ndash; \u0026ldquo;totally\u0026rdquo;). Respondents are instructed to rate experiences that did not occur under the influence of substance use. In the present study, the Cronbach\u0026rsquo;s alphas for parts A and B were 0.930 and 0.964, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial anhedonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Revised Social Anhedonia Scale-Brief (RSAS-B) was used (Winterstein et al., 2011). The RSAS-B is an abbreviated version of the Revised Social Anhedonia Scale from the Wisconsin Schizotypy Scales (Eckblad et al., 1982). It includes 15 items with true-and-false responses. Responses to each item are rated as 1 or 0. The total RSAS-B score ranges between 0 and 15, where higher scores refer to greater levels of social anhedonia. The Cronbach\u0026rsquo;s alpha was 0.821 in the present study.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial interaction anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Social Interaction Anxiety Scale (SIAS) was administered (Mattick and Clarke, 1998). It is based on 20 items describing various characteristics of social anxiety. Respondents are asked to rate the level each item is characteristic for them on a 5-point scale (0 \u0026ndash; \u0026ldquo;not at all\u0026rdquo;, 4 \u0026ndash; \u0026ldquo;extremely\u0026rdquo;). The Cronbach\u0026rsquo;s alpha was 0.947 in the present study.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRejection sensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Adult Rejection Sensitivity Questionnaire (ARSQ) was used (Berenson et al., 2009). It describes 9 situations in which people ask things of others. Each situation is rated with the rejection concern item (responses range between 1 \u0026ndash; \u0026ldquo;very unconcerned\u0026rdquo; and 6 \u0026ndash; \u0026ldquo;very concerned\u0026rdquo;), and the rejection expectancy item (responses range between 1 \u0026ndash; \u0026ldquo;very unlikely\u0026rdquo; and 6 \u0026ndash; \u0026ldquo;very likely\u0026rdquo;. A rejection sensitivity score is calculated for each situation by multiplying the level of rejection concern by the level of rejection expectancy. The total rejection sensitivity score is the mean of rejection sensitivity scores across all situations. In the present study, the Cronbach\u0026rsquo;s alphas for rejection concern items and rejection expectancy items were 0.868 and 0.826, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive biases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Davos Assessment of Cognitive Biases Scale-18 (DACOBS-18) was administered (Gaweda et al., 2018). It is an abbreviated version of the DACOBS(van der Gaag et al., 2013) that includes 18 items rated on a 7-point scale (1 \u0026ndash; \u0026ldquo;strongly disagree\u0026rdquo; and 7 \u0026ndash; \u0026ldquo;strongly agree\u0026rdquo;). The items are included in 4 specific subscales measuring attributional biases (4 items), safety behaviors (5 items), social cognition problems (4 items), and subjective cognitive problems (5 items). In the present study, the Cronbach\u0026rsquo;s alphas were 0.801, 0.745, 0.733, and 0.809 for the subscales measuring attributional biases, safety behaviors, social cognition problems, and subjective cognitive problems, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe 11-item version of the De Jong Gierveld Loneliness Scale (DJGLS) was used (de Jong-Gierveld and Kamphuls, 1985; Grygiel et al., 2013). Each item includes 5 possible responses (\u0026ldquo;yes!\u0026rdquo;, \u0026ldquo;yes\u0026rdquo;, \u0026ldquo;more or less\u0026rdquo;, \u0026ldquo;no\u0026rdquo;, and \u0026ldquo;no!\u0026rdquo;). It includes two subscales: the first one measures emotional loneliness (6 items) and the second one refers to social loneliness (5 items). The total score is calculated by counting positive and neutral responses (\u0026ldquo;yes!\u0026rdquo;, \u0026ldquo;yes\u0026rdquo;, and \u0026ldquo;more or less\u0026rdquo;) to items measuring emotional loneliness as well as negative and neutral responses (\u0026ldquo;no!\u0026rdquo;, \u0026ldquo;no\u0026rdquo;, and \u0026ldquo;more or less\u0026rdquo;) to items measuring social loneliness. The total DJGLS score ranges between 0 and 11, where higher scores indicate a greater level of loneliness. In the present study, the Cronbach\u0026rsquo;s alphas for emotional loneliness subscale and social loneliness subscale were 0.874 and 0.810, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA 6-item version of the Lubben Social Network Scale (LSNS-6) was administered (Lubben et al., 2006). The items measure the number of family members and friends who are seen or heard at least once a month, with whom the respondent can talk about private matters, and who can be called on for help. Items are rated on a 6-point scale. The total LSNS-6 score ranges between 0 and 20, where lower scores indicate a greater level of social isolation. The Cronbach\u0026rsquo;s alpha was 0.876 in the present study.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eBerenson, K.R., Gyurak, A., Ayduk, O., Downey, G., Garner, M.J., Mogg, K., Bradley, B.P., Pine, D.S., 2009. Rejection sensitivity and disruption of attention by social threat cues. J Res Pers 43, 1064\u0026ndash;1072.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003ede Jong-Gierveld, J., Kamphuls, F., 1985. The Development of a Rasch-Type Loneliness Scale. Appl Psychol Meas 9, 289\u0026ndash;299.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eEckblad, M., Chapman, L.J., Chapman, J.P., Mishlove, M., 1982. The revised social anhedonia scale. University of Wisconsin.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eFreeman, D., Loe, B.S., Kingdon, D., Startup, H., Molodynski, A., Rosebrock, L., Brown, P., Sheaves, B., Waite, F., Bird, J.C., 2021. The revised Green et al., Paranoid Thoughts Scale (R-GPTS): psychometric properties, severity ranges, and clinical cut-offs. Psychol Med 51, 244\u0026ndash;253.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eGaweda, L., Prochwicz, K., Krezolek, M., Klosowska, J., Staszkiewicz, M., Moritz, S., 2018. Self-reported cognitive distortions in the psychosis continuum: A Polish 18-item version of the Davos Assessment of Cognitive Biases Scale (DACOBS-18). Schizophr Res 192, 317\u0026ndash;326.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eGrygiel, P., Humenny, G., Rebisz, S., Świtaj, P., Sikorska, J., 2013. Validating the Polish Adaptation of the 11-Item De Jong Gierveld Loneliness Scale. Eur J Psychol Assess 29, 129\u0026ndash;139.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eKroenke, K., Spitzer, R.L., Williams, J.B., 2001. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 16, 606\u0026ndash;613.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eLubben, J., Blozik, E., Gillmann, G., Iliffe, S., von Renteln Kruse, W., Beck, J.C., Stuck, A.E., 2006. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist 46, 503\u0026ndash;513.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eMattick, R.P., Clarke, J.C., 1998. Social Interaction Anxiety Scale (SIAS). APA PsycTests.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSpitzer, R.L., Kroenke, K., Williams, J.B., Lowe, B., 2006. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 166, 1092\u0026ndash;1097.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003evan der Gaag, M., Schutz, C., Ten Napel, A., Landa, Y., Delespaul, P., Bak, M., Tschacher, W., de Hert, M., 2013. Development of the Davos assessment of cognitive biases scale (DACOBS). Schizophr Res 144, 63\u0026ndash;71.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eWinterstein, B.P., Silvia, P.J., Kwapil, T.R., Kaufman, J.C., Reiter-Palmon, R., Wigert, B., 2011. Brief assessment of schizotypy: Developing short forms of the Wisconsin Schizotypy scales. Pers Individ Dif 51, 920\u0026ndash;924.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThere were no missing data, except for those related to monthly income as some participants refused to provide this information. In the first step, linear regression analyses were performed. The levels of ideas of persecution and reference were included as a dependent variable in separate models. Model 1 was limited to testing direct effects of loneliness and social isolation, while model 2 also included the interaction between loneliness and social isolation. Covariates (age, gender, the level of education, employment status, place of residence, monthly income, a lifetime history of psychiatric treatment, and substance use in the preceding months) were added to model 3. To control for multicollinearity, the variance inflation factor (VIF) was assessed. The VIF values higher than 4 were interpreted as those indicating significant multicollinearity [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This part of data analysis was carried out in the SPSS software, version 28.\u003c/p\u003e \u003cp\u003eTo provide insights into potential mechanisms underlying the association between social disconnection components, a network analysis was performed in the R software. It included the following variables: (1) age; (2) gender; (3) the level of education; (4) place of residence; (5) employment status; (6) monthly income; (7) a lifetime history of psychiatric treatment; (8) substance use in the preceding month; (9) loneliness; (10) social isolation; (11) depressive symptoms; (12) anxiety symptoms; (13) ideas of persecution; (14) ideas of reference; (15) social anhedonia; (16) rejection sensitivity; (17) social interaction anxiety; (18) attributional biases; (19) safety behaviours; (20) social cognition problems, and (21) subjective cognitive problems. Variables 1\u0026ndash;7 were included as covariates. Due to inclusion of both categorical and continuous variables, the mixed graphical models implemented in the \u003cem\u003emgm\u003c/em\u003e package [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] were used to estimate the network. The L1-penalized regression (LASSO) was performed to provide regularization and shrink weak associations [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The Extended Bayesian Information Criterion (EBIC), using the tuning parameter λ that controls the level of sparsity, was applied to select the penalty parameter [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The λ was set at 0.5 as proposed previously [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. To indicate the shortest pathways between the measures of social disconnection (i.e., social isolation and loneliness) and paranoid thoughts, the Dijkstra\u0026rsquo;s algorithm was used [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This algorithm allows to show the minimum number of mediating variables with the strongest correlation coefficients that are needed to appear between variables of interest.\u003c/p\u003e \u003cp\u003eNode centralities were assessed by estimating the bridge expected influence [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It represents the sum of positive and negative edge weights between the node in a specific community and all nodes from other communities. Communities were identified using the \u0026ldquo;\u003cem\u003ewalktrap\u003c/em\u003e\u0026rdquo; algorithm implemented in the \u003cem\u003eEGAnet\u003c/em\u003e package [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe network accuracy and stability were analysed in the \u003cem\u003ebootnet\u003c/em\u003e package [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The case-drop bootstrapping with 1,000 iterations was used to assess stability of the bridge expected influence and edge weights [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The network was considered stable if the correlation stability coefficient (CS-C) was higher than 0.25 (preferably it should be higher than 0.50). Moreover, for all edge weights, the 95%CI was estimated and visualized using non-parametric bootstrapping. A higher 95%CI indicates a lower precision in estimating edge weights. All visualizations were prepared using the \u003cem\u003eqgraph\u003c/em\u003e package [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eGeneral characteristics of the sample\u003c/h2\u003e \u003cp\u003eGeneral characteristics of the sample and a flow diagram of participants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, respectively. A total of 5,099 individuals (aged 44.9 \u0026plusmn; 15.4 years, 52.2% women) participated in the present study. Most frequently, the participants reported a higher level of education (49.0%), full-time employment (57.8%), urban place of residence (67.6%), and a monthly income of 750\u0026ndash;1,500 USD (48.7%). A lifetime and preceding month history of psychiatric treatment was reported by 21.7% and 10.6% participants, respectively. Substance use (other than alcohol and nicotine) in the preceding month was reported by 6.9% participants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive characteristics of the sample (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5099).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean \u0026plusmn; SD or \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.9 \u0026plusmn; 15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGender\u003c/em\u003e\u003c/p\u003e \u003cp\u003eMen\u003c/p\u003e \u003cp\u003eWomen\u003c/p\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2431 (47.7)\u003c/p\u003e \u003cp\u003e2662 (52.2)\u003c/p\u003e \u003cp\u003e6 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEducation\u003c/em\u003e\u003c/p\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003cp\u003eVocational\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (1.8)\u003c/p\u003e \u003cp\u003e411 (8.1)\u003c/p\u003e \u003cp\u003e2098 (41.1)\u003c/p\u003e \u003cp\u003e2496 (49.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEmployment status\u003c/em\u003e\u003c/p\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003cp\u003eRetired\u003c/p\u003e \u003cp\u003eFull-time employment\u003c/p\u003e \u003cp\u003ePart-time employment\u003c/p\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435 (8.5)\u003c/p\u003e \u003cp\u003e1002 (19.6)\u003c/p\u003e \u003cp\u003e2946 (57.8)\u003c/p\u003e \u003cp\u003e482 (9.5)\u003c/p\u003e \u003cp\u003e234 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlace of residence\u003c/em\u003e\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003cp\u003eUrban, up to 50,000 inhabitants\u003c/p\u003e \u003cp\u003eUrban, 50,000\u0026ndash;150,000 inhabitants\u003c/p\u003e \u003cp\u003eUrban, 150,000\u0026ndash;500,000 inhabitants\u003c/p\u003e \u003cp\u003eUrban, \u0026gt; 500,000 inhabitants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1650 (32.4)\u003c/p\u003e \u003cp\u003e1166 (22.9)\u003c/p\u003e \u003cp\u003e816 (16.0)\u003c/p\u003e \u003cp\u003e714 (14.0)\u003c/p\u003e \u003cp\u003e753 (14.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMonthly income\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;750 USD\u003c/p\u003e \u003cp\u003e750\u0026ndash;1,500 USD\u003c/p\u003e \u003cp\u003e1,500\u0026ndash;2,500 USD\u003c/p\u003e \u003cp\u003e2,500\u0026ndash;3,750 USD\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3,750 USD\u003c/p\u003e \u003cp\u003eRefused to answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1082 (21.2)\u003c/p\u003e \u003cp\u003e2485 (48.7)\u003c/p\u003e \u003cp\u003e722 (14.2)\u003c/p\u003e \u003cp\u003e133 (2.6)\u003c/p\u003e \u003cp\u003e44 (0.9)\u003c/p\u003e \u003cp\u003e633 (12.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric treatment, lifetime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1108 (21.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric treatment, preceding month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e539 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubstance use (other than alcohol and nicotine), preceding month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e353 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLSNS-6, social isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.9 \u0026plusmn; 6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDJGLS, loneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.2 \u0026plusmn; 3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRSAS, social anhedonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5 \u0026plusmn; 3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARSQ, rejection sensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.5 \u0026plusmn; 5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIAS, social interaction anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.7 \u0026plusmn; 16.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACOBS-18, subjective cognitive problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.5 \u0026plusmn; 5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACOBS-18, social cognition problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.2 \u0026plusmn; 4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACOBS-18, attributional biases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.9 \u0026plusmn; 5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDACOBS-18, safety behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.4 \u0026plusmn; 5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHQ-9, depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4 \u0026plusmn; 6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAD-7, anxiety symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1 \u0026plusmn; 5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRGPTS, ideas of reference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.1 \u0026plusmn; 8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRGPTS, ideas of persecution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7 \u0026plusmn; 10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLinear regression analyses\u003c/h2\u003e \u003cp\u003eResults of linear regression analyses are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. There were significant main effects of loneliness and social isolation on the level of ideas of persecution across all models. Also, significant main effects of loneliness on ideas of reference were significant across all models. Main effect of social isolation on ideas of reference was significant only after adjustment for covariates. No significant effects of the interaction between loneliness and social isolation on the level of paranoid thoughts were found. Model 3 (i.e., with the effects of covariates) explained significantly higher percentage of variance (as measured by R\u003csup\u003e2\u003c/sup\u003e values) compared to models 1 and 2. All VIF values were lower than 4.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of linear regression analysis testing the association of loneliness and social isolation with paranoid thoughts.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eIdeas of persecution\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIdeas of\u003c/p\u003e \u003cp\u003ereference\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoneliness \u0026times; social isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoneliness \u0026times; social isolation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubstance use (previous month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePsychiatric treatment (lifetime)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.188 for model 3 (significantly higher compared to models 1 and 2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.224 for model 3 (significantly higher compared to models 1 and 2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eNetwork estimation\u003c/h2\u003e \u003cp\u003eThe network estimated in the present study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. A total of 67 edges, out of 210 potential edges, had a non-zero weight (31.9%, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). No isolated nodes were detected.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eShortest pathways in the network\u003c/h2\u003e \u003cp\u003eThe shortest pathways between social disconnection measures (i.e., loneliness and social isolations) and paranoid thoughts are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In these pathways, loneliness was connected to ideas of persecution through a mediating effect of attributional biases. In turn, social isolation was connected to ideas of persecution through the effects of social anhedonia and attributional biases. Importantly, loneliness and social isolation were not directly interconnected within the shortest pathways.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBridge centrality\u003c/h2\u003e \u003cp\u003eAltogether, four communities of nodes were identified in the network (Figure S2). Two communities represented covariates. The first one included age, gender, the level of education, place of residence, employment status, and monthly income. The second one covered a lifetime history of psychiatric treatment and substance use (other than alcohol and nicotine) in the preceding month. Interestingly, social isolation and loneliness clustered together with social anhedonia, social interaction anxiety, rejection sensitivity, attributional biases, safety behaviours, social cognition problems, and subjective cognitive problems. Finally, the community of psychopathological symptoms was identified and included depressive symptoms, anxiety symptoms, ideas of persecution, and ideas of reference. Apart from covariates, nodes with the highest bridge expected influence were social interaction anxiety, social anhedonia, loneliness, attributional biases, and rejection sensitivity (in decreasing order, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eNetwork stability and accuracy\u003c/h2\u003e \u003cp\u003eThe CS-C value was 0.75 (the same value was obtained for the bridge expected influence and edge weights) indicating that results were stable while dropping various proportions of data (Figure S2). For most edge weights, the 95%CI range was relatively narrow suggesting sufficient accuracy (Figure S3).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMain findings from this study indicate that loneliness and social isolation exert additive effects on the level of paranoid thoughts. However, both social disconnection components were not found to be directly connected to paranoid thoughts. The most likely pathway from loneliness to paranoid thoughts led through attributional biases. In turn, the most likely pathway from social isolation to paranoid thoughts appeared to require two mediating nodes, i.e., social anhedonia and attributional biases. Importantly, within the shortest pathways, social isolation and loneliness were not interconnected confirming the findings of linear regression analyses that both phenomena might be independently associated with the occurrence of paranoid thoughts.\u003c/p\u003e \u003cp\u003eTo our knowledge, potential interactive effects of social isolation and loneliness on the occurrence of psychotic experiences have not been reported so far. It is needed to note that social disconnection has been associated with a variety of negative health outcomes, beyond those related to mental health. To date, combined effects of loneliness and social isolation have been documented with respect to age-related cognitive decline [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. There is evidence that individuals who experience both loneliness and social isolation show worse health risk profiles than those with one or the other alone [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In case of memory impairments, it has been shown that social isolation exerts larger effects than loneliness [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In our study, we found that loneliness is more closely related to paranoid thinking. Also, our linear regression analyses revealed that effects of loneliness on paranoid thoughts were stronger compared to those of social isolation. These observations might suggest that specific combinations of social disconnection components might exert differential effects on specific health outcomes.\u003c/p\u003e \u003cp\u003eExperimental and ESM studies have demonstrated that loneliness might contribute to the emergence of psychotic experiences in general and paranoia specifically. Also, as noted by a prior systematic review, lonely individuals hold hostile intent attributions [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. According to cognitive models, loneliness increases hypervigilance for social threats and the risk of attentional and confirmatory biases making lonely individuals more likely to perceive the world as threatening and to develop negative perceptions about other people [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In light of evolutionary considerations, these processes play a self-protective role [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. A bias towards perception of others being responsible for negative events (i.e., external attribution bias) has been conceptualized as the core mechanism underlying the development of paranoia. In these considerations, paranoia has also been posited as a defence against reduced self-esteem [\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. On the basis of a meta-analysis, it has been shown attributional biases are highly prevalent among individuals at clinical high risk of psychosis [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. In this meta-analysis, the effect size for attributional biases was higher (g = -0.708) than the one for other cognitive processes, including social cognition (g = -0.477), emotion processing (g = -0.446), and social perception (g = -0.383). External attributions have also been associated with psychotic experiences in non-clinical samples [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, the shortest pathway between social isolation and paranoid thoughts was similar to the one between loneliness and paranoid thoughts. However, it also appeared to include the effects of social anhedonia that was ranked among nodes with the highest bridge centrality in the network. These observations suggest that social isolation is most likely related to paranoid thoughts only if social anhedonia is present. By definition, social anhedonia is a trait-like disinterest in and a lack of reward from social interactions [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Individuals with high levels of social anhedonia prefer solitude and report reduced negative affect while being alone [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Moreover, there is some evidence that social anhedonia might predict the development of psychosis and psychotic symptoms [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] over time [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are certain limitations of the present study that need to be considered. First, the study was cross-sectional and thus conclusions about causality cannot be made. However, at this point it is needed to note that social disconnection has been bidirectionally associated with the occurrence of psychotic symptoms. Second, although the study was based on a large and representative sample, the selection bias cannot be ruled out. Indeed, the questionnaires were only available in the Polish language and the study was based on the online survey. Therefore, individuals with potentially higher levels of social disconnection, i.e., those with migrant status and those who do not use internet were likely underrepresented in our sample. Third, it is needed to note that single-timepoint assessments of social disconnection do not provide full insights into chronicity of loneliness and social isolation. Indeed, it has been suggested that chronic and acute social disconnection might exert differential effects on health outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Finally, findings may not be generalizable over clinical populations as the participants did not undergo a thorough clinical assessment.\u003c/p\u003e \u003cp\u003eThe present study offers important implications for clinical practice. It indicates that a thorough assessment of social disconnection components might be of importance while planning specific interventions for paranoid experiences. At this point, it is also needed to note the bridging effect of social anhedonia in the association between social isolation and paranoid thoughts. This might imply that increasing social contacts may not be effective in people with paranoid thoughts and social isolation as they might show reduced pleasure from social interactions. In this regard, targeting attributional biases that also appeared to bridge the association of both social isolation and loneliness with paranoid thoughts might be promising. To date, optimal interventions for loneliness and social isolation in people with paranoid thoughts have not been developed. Moreover, studies addressing the efficacy of cognitive-behavioural therapy for psychosis with respect to improving the level of loneliness have provided mixed findings [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Nevertheless, there is some evidence that interventions focused on loneliness might be feasible in people with psychosis and need to be developed [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn sum, findings from the present study warrant the need to dissect the effects of loneliness and social isolation while investigating the role of social disconnection in people with psychosis-related outcomes. Both components of social disconnection might show additive effects with respect to the occurrence of paranoid thoughts. Yet, the relevance of social isolation in people with paranoid thoughts might be weaker compared to loneliness. Our findings also indicate the aberrant information processing and social anhedonia play important roles in the association between social disconnection and paranoid thoughts. Future studies need to provide deeper insights into our findings by investigating clinical population using longitudinal designs. Moreover, it is needed to study distinct combinations of social isolation and loneliness with respect to various outcomes in people with psychosis including those related to somatic health.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe author declares no competing interests\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003e The present study was funded from \u0026ldquo;the Initiative of Excellence \u0026ndash; Research University\u0026rdquo; provided by Wroclaw Medical University, Wroclaw, Poland (task number: IDUB.C230.24.001).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBM \u0026ndash; conceptualization, methodology, funding acquisition, data curation, validation, data analysis, visualization, manuscript writing\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData supporting the present study are available from the corresponding author upon a reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFreeman D, McManus S, Brugha T, Meltzer H, Jenkins R, Bebbington P (2011) Concomitants of paranoia in the general population. 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Soc Psychiatry Psychiatr Epidemiol 55(7):901\u0026ndash;906. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00127-019-01731-9\u003c/span\u003e\u003cspan address=\"10.1007/s00127-019-01731-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"paranoia, persecutory thoughts, ideas of reference, information processing, social withdrawal","lastPublishedDoi":"10.21203/rs.3.rs-4992331/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4992331/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eSocial disconnection has been implicated in the development of paranoia. Yet, both components of social disconnection, i.e., social isolation and loneliness, were mostly investigated separately. The present study aimed to explore as to whether social isolation and loneliness show differential associations with paranoid thoughts.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study was based on a representative sample of 5,099 general population adults (aged 44.9 \u0026plusmn; 15.4 years, 52.2% women). Self-reports were used to assess psychopathological symptoms, cognitive processes, perceptions of social interactions, loneliness, and social isolation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eLinear regression and network analyses were performed. Loneliness and social isolation were significantly and independently associated with paranoid thoughts in linear regression analyses. Paranoid thoughts were more strongly associated with loneliness than social isolation. No significant association of the interaction between social isolation and loneliness with paranoid thoughts was found. A network analysis revealed that the nodes representing social isolation and loneliness were not directly connected to the nodes of paranoid thinking. In the shortest pathways, loneliness and social isolation were independently associated with paranoia. The shortest pathway between loneliness and paranoia led through only one mediating node representing external attribution biases. In turn, the shortest pathway between social isolation and paranoia led through two mediating nodes representing social anhedonia and external attribution biases.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe findings imply that social isolation and loneliness might exert additive effects on the occurrence of paranoid thoughts. External attribution biases and social anhedonia might play important roles in the association of social disconnection with paranoia.\u003c/p\u003e","manuscriptTitle":"Social disconnection and paranoid thoughts in the general population sample: A network analysis investigating differential associations of social isolation and loneliness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-27 17:02:11","doi":"10.21203/rs.3.rs-4992331/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6b0930c-359b-4c23-9543-958d8e777df2","owner":[],"postedDate":"September 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-28T09:24:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-27 17:02:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4992331","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4992331","identity":"rs-4992331","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}