Evidence map›Paper›PMID 41595844›Full record

ArticleInternational journal of environmental research and public health2025

Multidimensional Loneliness Among University Students: A Latent Profile Approach.

Aditya Banerjee, Neena Kohli, Sarabjeet Kaur Chawla, Vrrinda Kohli

Abstract read
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Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Aditya BanerjeeDepartment of Liberal Arts Humanities & Social Sciences, Manipal Academy of Higher Education, Manipal 576104, India.ORCID 0000-0002-0942-3806
Neena KohliDepartment of Psychology, University of Allahabad, Prayagraj 211002, India.ORCID 0000-0001-8753-5101
Sarabjeet Kaur ChawlaDepartment of Liberal Arts Humanities & Social Sciences, Manipal Academy of Higher Education, Manipal 576104, India.ORCID 0000-0002-4258-6674
Vrrinda KohliIndependent Researcher, Prayagraj 211002, India.

Funding

Indian Council of Social Science Research (ICSSR) RFD/2021-22/GEN/PSY/260
6 · The paper itself

Abstract

backgroundAn increasing number of university students report feeling lonely, a negative experience arising from a mismatch between perceived and actual social relationships. Loneliness has been linked to poorer mental health. However, the relationship between qualitative (sources of loneliness) and quantitative (high or low) differences in loneliness and mental health is under researched. The aims of this research were to (a) identify profiles of loneliness among university students across three indicators of loneliness, namely, social, family, and romantic indicators, using latent profile analysis (LPA); (b) examine the differences among identified profiles based on dimensions of mental health indicators (depression, anxiety, and stress), social support, and life satisfaction; and (c) assess profile membership based on demographic variables (gender, social isolation, relationship status, and education characteristics) and the Big Five personality traits (extraversion, agreeableness, openness, conscientiousness, and neuroticism).

methodA cross-sectional survey was conducted on 912 university students from five cities in Uttar Pradesh, India. Participants completed questionnaires covering demographic details and validated measures assessing loneliness, depression, stress, anxiety, social support, life satisfaction, and the Big Five personality traits. Data were analyzed using the latent profile module in Jamovi and fit indices, namely, BIC, AIC, and BLRT, and entropy was used to select the best profile.

resultsThe latent profile analysis identified four profiles for university student loneliness, including Social and emotional lonely (31.4%), Moderate romantic lonely (23.8%), Moderate social lonely (8.2%), and Severe romantic lonely (36.6%). Moreover, the Social and emotional lonely profile scored the highest on depression, anxiety, and stress. The Moderate romantic lonely profile scored the highest on life satisfaction and social support. Being in a relationship decreased the likelihood of being categorized as Severe romantic lonely. In terms of personality, neuroticism was the strongest predictor of profile membership. This study is a step towards identifying at-risk lonely individuals with varying sources of loneliness. Identifying different profiles of lonely individuals will have direct implications for designing interventions that cater to a particular group rather than a one-size-fits-all approach.

Indexed as

LonelinessStudentsAnxietyCross-Sectional StudiesDepressionFemaleHumansInterpersonal RelationsLatent Class AnalysisMalePersonal SatisfactionSocial SupportStress, PsychologicalSurveys and QuestionnairesUniversitiesYoung Adultdepressionlatent profile analysislonelinesspersonality

Identifiers

PMID41595844
PMCPMC12840607

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.