Psychotic disorders are a disabling group of brain disorders characterized by hallucinations, delusions, disorganized communication, impaired planning, reduced motivation and blunted affect. Their aetiology is multifactorial, and although a substantial genetic contribution is firmly established, researchers have increasingly emphasized the modifiable social and economic attributes that shape both risk and outcome (1,2). Sociodemographic variables frequently serve as observable markers of underlying psychiatric morbidity and psychological distress, and in resource-limited settings they may be the only risk indicators routinely available to primary care workers. The relationship between socioeconomic position and psychosis has been debated for decades under two competing explanations. The social causation hypothesis holds that the adversity, insecurity and chronic stress associated with poverty increase the risk of developing psychosis, whereas the social drift hypothesis proposes that the illness itself impairs functioning and causes affected individuals to descend the socioeconomic ladder. Yu and Williams, reviewing this literature, concluded that psychotic disorders may cause downward mobility among adults and lead them to drift into lower socioeconomic strata, while also noting that individuals who fail to complete secondary schooling are substantially more likely to receive a diagnosis of psychotic disorder than college graduates (1). The two mechanisms are not mutually exclusive, and cross-sectional community data cannot distinguish between them. Marital status has attracted particular attention because it is potentially modifiable and because marriage functions simultaneously as a structural form of social support and as a mediator of social integration and belonging (3,4). People who are married consistently show lower levels of mental disorder and higher perceived social support than those who are not (4,5). Li and colleagues demonstrated that unfavourable marital status was associated with higher odds of social dysfunction among community-dwelling patients with schizophrenia (6), while Vaingankar and colleagues found that mental disorders were associated with lower perceived social support and that being married positively influenced this relationship (4). Employment shows a comparable pattern: individuals with severe mental disorder have impaired capacity to work and are frequently out of the labour force years before their first hospitalization, whether through neurocognitive impairment, residual symptoms, poor educational attainment, absenteeism or stigma (7,8). Family history remains the single strongest known risk indicator. Epidemiological surveys have shown elevated rates of schizophrenia-spectrum and other disorders among relatives of affected individuals; Faridi and colleagues found psychosis among first-degree relatives in 19.1% of first-episode patients (9), and Şahin and Elboğa reported a psychiatric family history in nearly half of patients with chronic psychosis (10). Living arrangements and housing quality complete the picture: Jacob and colleagues found that people living alone had 1.39 to 2.43 times higher odds of psychotic disorder across three successive national surveys (11), and a meta-analysis by Ayano and colleagues demonstrated markedly elevated prevalence of psychosis among homeless populations (12). Religion, by contrast, has shown inconsistent associations, influencing the content of psychopathology and coping more than its occurrence (13,14). Most of this evidence derives from clinical samples or from high-income settings. Community-level data from rural India, where kinship structures, housing and employment differ markedly, remain sparse. The present analysis therefore compares individuals identified with a psychotic disorder during a door-to-door survey of a rural community in southern Karnataka with the remainder of that community across eight social variables. The prevalence and diagnostic pattern of psychotic disorders in this cohort are reported separately

This analysis is based on a community-based cross-sectional survey conducted through the Department of Psychiatry of a medical college and research hospital serving Hoskote taluk, a rural area of Bengaluru Rural district in southern Karnataka, between July 2020 and June 2021. Institutional Ethics Committee approval was obtained before the study began and written informed consent was taken from every participant. Households in the rural catchment area were enumerated and visited door to door. All residents aged 18–65 years of either sex who consented were enrolled. Individuals with serious or debilitating endocrine, cardiovascular, haematological or neurological illness, and those with intellectual disability, were excluded so that psychotic phenomena attributable to such conditions or to global intellectual impairment would not be misclassified. A total of 958 individuals were surveyed. Sociodemographic data were recorded on a semi-structured proforma designed for the study. The eight social variables examined here were marital status (married, unmarried, divorced, widowed); employment status, classified as professional, skilled, semi-skilled, unskilled or unemployed; educational attainment (postgraduate, graduate, pre-university, secondary schooling, primary schooling, illiterate); socioeconomic class, graded as upper, upper middle, lower middle, upper lower or lower; religion; family history of psychotic disorder in any relative; living arrangement, dichotomized as living with or without family; and type of housing, classified as pakka (permanent construction of durable materials) or kachcha (temporary construction of mud, thatch or other non-durable materials), a standard indicator of household material deprivation in Indian surveys. Case ascertainment proceeded in two stages. All participants were screened using the Mini International Neuropsychiatric Interview, a brief structured diagnostic interview suited to community application (15), together with the Psychosis Screening Questionnaire of Bebbington and Nayani, developed specifically to detect psychotic phenomena in general population surveys (16). Those screening positive underwent full diagnostic evaluation by a qualified psychiatrist using the Structured Clinical Interview for DSM-IV Axis I Disorders, and diagnoses were assigned according to DSM-IV criteria (17). Seven individuals met criteria for a psychotic disorder and formed the case group; the remaining 951 individuals constituted the comparison group. Data were entered into Microsoft Excel and analysed using the Statistical Package for the Social Sciences version 21.0. Categorical variables were expressed as numbers and percentages and continuous variables as mean ± standard deviation. The distribution of each social variable was compared between the case and comparison groups using the Chi-square test, with the Fisher exact test applied where expected cell frequencies were small; a p value below 0.05 was considered statistically significant. Because the case group comprised only seven individuals, several cells contained expected frequencies below five, and the resulting test statistics are reported with this constraint explicitly acknowledged in the interpretation of findings

Seven individuals with a psychotic disorder were compared with 951 individuals without. Table 1: Marital status in cases and comparison group Marital status Comparison group n (%) Psychotic disorder group n (%) p value Married 688 (72.34) 3 (42.86) 0.00036 Unmarried 265 (27.87) 2 (28.57) Divorced 7 (0.74) 1 (14.29) Widowed 45 (4.73) 1 (14.29) Total 951 (100.00) 7 (100.00) Chi-square = 18.39. Fewer than half of those with a psychotic disorder were currently married (42.86%) compared with almost three-quarters of the comparison group (72.34%). Divorce and widowhood were disproportionately represented among cases, at 14.29% each against 0.74% and 4.73% respectively in the comparison group. Taken together, 57.15% of cases were unmarried, divorced or widowed compared with 33.34% of the comparison group, a statistically significant difference (p = 0.00036) (Table 1). Table 2: Employment status in cases and comparison group Employment status Comparison group n (%) Psychotic disorder group n (%) p value Professional 49 (5.15) 0 (0.00) 0.016 Skilled 287 (30.18) 1 (14.29) Semi-skilled 321 (33.75) 1 (14.29) Unskilled 218 (22.92) 2 (28.57) Unemployed 76 (7.99) 3 (42.86) Total 951 (100.00) 7 (100.00) Chi-square = 12.06. Unemployment was more than five times as frequent among cases as in the comparison group (42.86% versus 7.99%), and no case was a professional. Conversely, skilled and semi-skilled work accounted for only 28.58% of cases against 63.93% of the comparison group. The gradient across occupational categories was statistically significant (p = 0.016) (Table 2). Table 3: Educational attainment in cases and comparison group Educational status Comparison group n (%) Psychotic disorder group n (%) p value Postgraduate 21 (2.21) 0 (0.00) 0.003 Graduate 166 (17.46) 0 (0.00) Pre-university 286 (30.07) 0 (0.00) Secondary schooling 280 (29.44) 1 (14.29) Primary schooling 101 (10.62) 3 (42.86) Illiterate 97 (10.20) 3 (42.86) Total 951 (100.00) 7 (100.00) Chi-square = 17.77. No individual with a psychotic disorder had studied beyond secondary school. Illiteracy and primary schooling together accounted for 85.72% of cases compared with 20.82% of the comparison group, while pre-university education and above accounted for 49.74% of the comparison group and none of the cases. This difference was statistically significant (p = 0.003) (Table 3). Table 4: Socioeconomic class in cases and comparison group Socioeconomic class Comparison group n (%) Psychotic disorder group n (%) p value Upper 151 (15.88) 0 (0.00) 0.021 Upper middle 264 (27.76) 1 (14.29) Lower middle 326 (34.28) 1 (14.29) Upper lower 117 (12.30) 2 (28.57) Lower 93 (9.78) 3 (42.86) Total 951 (100.00) 7 (100.00) Chi-square = 11.44. The socioeconomic distribution of cases was displaced downwards relative to the comparison group. The lower and upper-lower classes together comprised 71.43% of cases against 22.08% of the comparison group, whereas no case belonged to the upper class, which accounted for 15.88% of the comparison group. The difference was statistically significant (p = 0.021) (Table 4). Table 5: Religion in cases and comparison group Religion Comparison group n (%) Psychotic disorder group n (%) p value Hindu 807 (84.86) 6 (85.71) 0.96 Muslim 91 (9.57) 1 (14.29) Christian 37 (3.89) 0 (0.00) Jain 12 (1.26) 0 (0.00) Others 4 (0.42) 0 (0.00) Total 951 (100.00) 7 (100.00) Chi-square = 0.55. The religious composition of the two groups was essentially identical, Hindus comprising 85.71% of cases and 84.86% of the comparison group. No statistically significant difference was observed (p = 0.96) (Table 5). Table 6: Family history, living arrangements and type of housing in cases and comparison group Variable Category Comparison group n (%) Psychotic disorder group n (%) p Family history of psychotic disorder Present 39 (4.10) 3 (42.86) 0.00001 Absent 912 (95.90) 4 (57.14) Living arrangement With family 921 (96.85) 5 (71.43) 0.0001 Without family 30 (3.15) 2 (28.57) Type of housing Pakka 931 (97.90) 5 (71.43) 0.00001 Kachcha 27 (2.84) 2 (28.57) Chi-square: family history = 24.89; living arrangement = 13.90; housing = 18.76. A family history of psychotic disorder was present in 42.86% of cases compared with 4.10% of the comparison group, a more than tenfold difference and the strongest association observed (p = 0.00001). Living apart from family was reported by 28.57% of cases against 3.15% of the comparison group (p = 0.0001), and kachcha housing by 28.57% of cases against 2.84% of the comparison group (p = 0.00001) (Table 6). Table 7: Summary of associations between social variables and psychotic disorder Variable Chi-square p value Significance Family history of psychotic disorder 24.89 0.00001 Significant Type of housing 18.76 0.00001 Significant Marital status 18.39 0.00036 Significant Educational attainment 17.77 0.003 Significant Living arrangement 13.90 0.0001 Significant Employment status 12.06 0.016 Significant Socioeconomic class 11.44 0.021 Significant Religion 0.55 0.96 Not significant Seven of the eight social variables examined showed a statistically significant association with the presence of a psychotic disorder, the strongest being family history, type of housing and marital status. Religion alone showed no association (Table 7).

Psychotic disorder in this rural community was strongly patterned by social disadvantage. The most robust association was with family history, present in 42.86% of cases against 4.10% of the comparison group. This magnitude is consistent with the wider literature: Faridi and colleagues found psychosis among first-degree relatives in 19.1% of first-episode patients and among any relative in 34.0% (9), while Şahin and Elboğa reported a psychiatric family history in 48.6% of patients with chronic psychotic disorders (10). Familial aggregation reflects both shared genetic liability and shared environmental adversity, and the finding underlines the practical value of a family history question as a case-finding tool for primary care workers in rural settings. Marital status showed a clear gradient, with only 42.86% of cases currently married against 72.34% of the comparison group and a disproportionate concentration of divorce and widowhood among cases. Li and colleagues found that unfavourable marital status was associated with significantly higher odds of social dysfunction among community-dwelling patients with schizophrenia (6), and Vaingankar and colleagues showed that mental disorders were associated with lower perceived social support, with marriage positively influencing that relationship (4). Two mechanisms are usually invoked to explain the protective effect of social ties, a stress-buffering model operating under conditions of stress and a main-effects model operating irrespective of stress level, with perceived support enhancing help-seeking and coping through positive appraisal (3,5). Marriage may function both as a structural form of support and as a mediator of social integration and purpose. The direction of the association cannot be determined here: psychosis may impair the capacity to form and sustain marriage, while marital breakdown may equally precipitate or aggravate illness. Unemployment was more than five times as common among cases, and no case held professional employment. This closely parallels Turner and colleagues, who found that unemployed individuals at first presentation with psychosis had significantly longer duration of untreated psychosis, more negative symptoms and lower quality of life than those employed, with an unemployment rate nine times the local figure (7), and Hakulinen and colleagues, who documented markedly low employment both before and especially after diagnosis of a severe mental disorder (8). Poor neurocognitive functioning, residual symptoms, impaired interpersonal functioning, low motivation, restricted educational attainment and stigma all plausibly contribute. Educational findings pointed the same way, with no case having studied beyond secondary school and 85.72% being illiterate or primary-educated; Yu and Williams observed that those without a completed secondary education were 1.79 times more likely to receive a diagnosis of psychotic disorder than graduates (1). Early cognitive alteration impairing school functioning is one plausible explanation, and elevated stress from altered social cognition another (2). The downward displacement of socioeconomic class among cases, together with the excess of kachcha housing and of living apart from family, completes a coherent picture of material and social deprivation. These findings are consistent with the social drift hypothesis articulated by Yu and Williams (1), with the elevated odds of psychotic disorder among those living alone reported by Jacob and colleagues (11), and with the markedly raised prevalence of psychosis among homeless populations demonstrated by Ayano and colleagues (12). Religion, by contrast, showed no association, in keeping with evidence that religion shapes the content of psychopathology, coping and treatment adherence rather than the occurrence of illness (13,14). These results must be interpreted with considerable caution. The case group comprised only seven individuals, so that most contingency tables contained expected cell frequencies below five, violating the assumptions of the Chi-square test and rendering the reported p values unstable; exact methods and confidence intervals around effect estimates would be preferable, and replication in a larger sample is essential before any causal weight is placed on these associations. The cross-sectional design cannot separate social causation from social drift. The survey was confined to a single taluk and to adults aged 18–65 years, and fieldwork coincided with the COVID-19 pandemic period. Notwithstanding these constraints, the consistency of the direction of association across seven independent variables, and its concordance with a substantial international literature, suggests that the underlying pattern is real and identifies concrete targets — family screening, supported employment, literacy, housing and social integration — for community mental health programmes in rural India.

Among 958 adults surveyed door to door in a rural community of southern Karnataka, the seven individuals identified with a psychotic disorder differed significantly from the rest of the community on seven of eight social variables. They were less often married and more often divorced or widowed, more often unemployed and never professionally employed, overwhelmingly illiterate or educated only to primary level, concentrated in the lower and upper-lower socioeconomic classes, far more likely to report a family history of psychotic disorder, more likely to live apart from family and more likely to occupy kachcha housing. Religion showed no association. Psychotic disorder in this setting is therefore embedded in a matrix of familial vulnerability and material and social deprivation. Community mental health services for rural India should incorporate family history screening as a case-finding tool and should address employment, literacy, housing and social integration alongside pharmacological treatment. Given that these conclusions rest on seven cases, larger multi-centre studies using exact statistical methods and longitudinal designs are required to confirm the associations and to distinguish social causation from social drift.

1. Yu Y, Williams DR. Socioeconomic status and mental health. In: Aneshensel CS, Phelan JC, editors. Handbook of the Sociology of Mental Health. New York: Kluwer Academic/Plenum Publishers; 1999. p. 151-66. 2. Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Ustün TB. Age of onset of mental disorders: a review of recent literature. Curr Opin Psychiatry. 2007;20(4):359-64. 3. Reblin M, Uchino BN. Social and emotional support and its implication for health. Curr Opin Psychiatry. 2008;21(2):201-5. 4. Vaingankar JA, Abdin E, Chong SA, Sambasivam R, Jeyagurunathan A, Seow E, et al. The association of mental disorders with perceived social support, and the role of marital status: results from a national cross-sectional survey. Arch Public Health. 2020;78:108. 5. Waite LJ, Lehrer EL. The benefits from marriage and religion in the United States: a comparative analysis. Popul Dev Rev. 2003;29(2):255-76. 6. Li XJ, Wu JH, Liu JB, Li KP, Wang F. The influence of marital status on the social dysfunction of schizophrenia patients in community. Int J Nurs Sci. 2015;2(2):149-52. 7. Turner N, Browne S, Clarke M, Gervin M, Larkin C, Waddington JL, et al. Employment status amongst those with psychosis at first presentation. Soc Psychiatry Psychiatr Epidemiol. 2009;44(10):863-9. 8. Hakulinen C, Elovainio M, Arffman M, Lumme S, Suokas K, Pirkola S, et al. Employment status and personal income before and after onset of a severe mental disorder: a case-control study. Psychiatr Serv. 2020;71(3):250-5. 9. Faridi K, Pawliuk N, King S, Joober R, Malla AK. Prevalence of psychotic and non-psychotic disorders in relatives of patients with a first episode psychosis. Schizophr Res. 2009;114(1-3):57-63. 10. Şahin Ş, Elboğa G. Family history in chronic psychotic disorders. Med Sci Discov. 2019;6(2):8-11. 11. acob L, Haro JM, Koyanagi A. Relationship between living alone and common mental disorders in the 1993, 2000 and 2007 National Psychiatric Morbidity Surveys. PLoS One. 2019;14(5):e0215182. 12. Ayano G, Tesfaw G, Shumet S. The prevalence of schizophrenia and other psychotic disorders among homeless people: a systematic review and meta-analysis. BMC Psychiatry. 2019;19(1):370. 13. Gearing RE, Alonzo D, Smolak A, McHugh K, Harmon S, Baldwin S. Association of religion with delusions and hallucinations in the context of schizophrenia: implications for engagement and adherence. Schizophr Res. 2011;126(1-3):150-63. 14. Nolan JA, McEvoy JP, Koenig HG, Hooten EG, Whetten K, Pieper CF. Religious coping and quality of life among individuals living with schizophrenia. Psychiatr Serv. 2012;63(10):1051-4. 15. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33. 16. 1Bebbington P, Nayani T. The Psychosis Screening Questionnaire. Int J Methods Psychiatr Res. 1995;5(1):11-19. 17. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Clinician Version. Washington, DC: American Psychiatric Press; 1997