Psychology of Loneliness
DOI:
https://doi.org/10.32628/IJSRHSS252339Keywords:
Loneliness, Depression, Perceived Social Support, Maladaptive Social Cognitions, Living Alone, University Population, Cognitive-Behavioral Therapy, Ecological Momentary AssessmentAbstract
Loneliness is a subjective distress arising from a perceived mismatch between desired and actual social relationships and has been consistently linked to adverse mental and physical health outcomes. Despite the growing recognition of its public health impact, empirical investigations among Indian populations remain scarce. This study examined the prevalence, psychosocial correlates, and predictors of loneliness in a cross-sectional sample of university staff and students in Vadodara, India. Specifically, we aimed to (1) quantify loneliness levels using the UCLA Loneliness Scale (Version 3), (2) evaluate associations between loneliness, depressive symptoms (Beck Depression Inventory-II), perceived social support (MSPSS of Perceived Social Support), and maladaptive social cognitions (ULCS-SF), and (3) identify demographic and psychosocial predictors of loneliness via hierarchical regression. Between January and March 2025, 450 participants (age range 18–65 years; M = 29.4, SD = 10.2; 58% female) completed an online survey after providing informed consent following Sigma University IRB approval. The measures included the 20-item UCLA Loneliness Scale (α = 0.92), the 21-item Beck Depression Inventory–II (α = 0.89), the 12-item Multidimensional Scale of Perceived Social Support (α = 0.93), and the 15-item UCLA Loneliness Cognitions Scale–Short Form (α = 0.88), alongside demographic items on living arrangements and social media use. Data were analysed using SPSS v.26. Descriptive statistics characterised the sample, Pearson correlations assessed bivariate relationships, and hierarchical multiple regression determined the incremental predictive value of depressive symptoms, social support, and maladaptive cognitions on loneliness, controlling for demographics. Participants reported a mean loneliness score of 43.6 (SD = 12.5; range 20–78), with 32% scoring above the scale midpoint, indicating moderate-to-high loneliness. The mean BDI-II scores indicated mild depressive symptoms (M = 14.2, SD = 9.1), MSPSS scores reflected moderate perceived support (M = 58.3, SD = 14.8), and ULCS-SF scores suggested moderate endorsement of negative social cognitions (M = 38.7, SD = 10.3). Correlational analyses revealed that loneliness was strongly positively associated with depressive symptoms (r = 0.62, p < 0.001) and maladaptive cognitions (r = 0.71, p < 0.001), and negatively associated with perceived social support (r = –0.58, p < 0.001). Individuals living alone reported significantly higher loneliness than those cohabiting (t(448) = 5.12, P < 0.001). Hierarchical regression demonstrated that demographic variables (age, gender, student/staff status, living arrangement) explained 8% of the variance in loneliness (F(4,445) = 9.67, p < 0.001), with living alone as a significant predictor (β = 0.28, p < 0.001). Adding depressive symptoms increased the explained variance by 31% (β = 0.47, p < 0.001), perceived social support added 20% (β = –0.40, p < 0.001), and maladaptive cognitions contributed an additional 10% (β = 0.35, p < 0.001), culminating in a total R² of 0.69 (F(7,442) = 147.6, p < 0.001). These findings underscore the multifactorial nature of loneliness, highlighting the cognitive, affective, and social support dimensions as key intervention targets. The prominence of maladaptive social cognitions supports cognitive-behavioural frameworks for loneliness reduction, while the protective role of perceived support advocates for structured peer-support programs, particularly among individuals living alone. Given the cross-sectional design and single-institution sample, causal inferences are limited, and generalisability is constrained. Future research should employ longitudinal designs to elucidate temporal dynamics, test the efficacy of tailored cognitive-behavioural and digital Ecological Momentary Interventions, and explore cultural moderators of loneliness in diverse Indian contexts. In conclusion, addressing loneliness in university settings requires integrative approaches that combine cognitive restructuring, social support enhancement, and technology-mediated real-time interventions. Such efforts may mitigate the substantial psychological burden of loneliness and promote well-being among young and middle-aged Indian adults.
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References
Perlman, D.; Peplau, L.A. Toward a social psychology of loneliness. Pers. Relat. 1981, 3, 31–56.
Cacioppo, J.T.; Hawkley, L.C. Perceived social isolation and cognition. Trends Cogn. Sci. 2009, 13, 447–454.
Hawkley, L.C.; Cacioppo, J.T. Loneliness matters: A theoretical and empirical review of consequences and mech-anisms. Ann. Behav. Med. 2010, 40, 218–227.
Holt-Lunstad, J.; Smith, T.B.; Layton, J.B. Social relationships and mortality risk: A meta-analytic review. PLoS Med. 2010, 7, e1000316.
Loades, M.E. et al. Rapid systematic review: The impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. J. Am. Acad. Child Adolesc. Psychiatry 2020, 59, 1218–1239.e3.
Ellis, W.; Dumas, T.M.; Forbes, L.M. Physically isolated but socially connected: Psychological adjustment and stress among adolescents during the initial COVID-19 crisis. Can. J. Behav. Sci. 2020, 52, 177–187.
Krendl, A.C.; Perry, B.L. The impact of sheltering in place during the COVID-19 pandemic on older adults’ social and mental well-being. J. Gerontol. B Psychol. Sci. Soc. Sci. 2021, 76, e53–e58.
Russell, D.; Peplau, L.A.; Cutrona, C.E. The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. J. Pers. Soc. Psychol. 1980, 39, 472–480.
Beck, A.T.; Steer, R.A.; Brown, G.K. Manual for the Beck Depression Inventory-II; Psychological Corporation: San Antonio, TX, USA, 1996.
Zimet, G.D.; Dahlem, N.W.; Zimet, S.G.; Farley, G.K. The Multidimensional Scale of Perceived Social Support. J. Pers. Assess. 1988, 52, 30–41.
Cacioppo, J.T.; et al. Loneliness within a nomological net: An evolutionary perspective. J. Res. Pers. 2006, 40, 1054–1085.
Qualter, P.; et al. Loneliness across the lifespan. Perspect. Psychol. Sci. 2015, 10, 250–264.
Klinenberg, E. Going Solo: The Extraordinary Rise and Surprising Appeal of Living Alone; Penguin Press: New York, NY, USA, 2012.
Perlman, D.; Peplau, L.A. Toward a social psychology of loneliness. Pers. Relat. 1981, 3, 31–56.
Kawachi, I.; Berkman, L.F. Social ties and mental health. J. Urban Health 2001, 78, 458–467.
Cacioppo, J.T.; Cacioppo, S. The growing problem of loneliness. Lancet 2018, 391, 426.
Cacioppo, J.T.; Hawkley, L.C. Sharing loneliness. Trends Cogn. Sci. 2009, 13, 447–454.
Victor, C.R.; Yang, K. The prevalence of loneliness among adults: A case study of the United Kingdom. J. Psychol. 2012, 146, 85–104.
Masi, C.M.; Chen, H.Y.; Hawkley, L.C.; Cacioppo, J.T. A meta-analysis of interventions to reduce loneliness. Pers. Soc. Psychol. Rev. 2011, 15, 219–266.
Russell, D.W.; et al. Real-time assessment of loneliness by smartphone Ecological Momentary Assessment (EMA): Development and validation. J. Soc. Psychol. 2017, 157, 690–701.
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