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Volume 12, Issue 3 (2024)
Health Educ Health Promot 2024, 12(3): 407-413 |
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Received: 2024/05/28 | Accepted: 2024/08/11 | Published: 2024/09/25
Received: 2024/05/28 | Accepted: 2024/08/11 | Published: 2024/09/25
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Correlation between Social Capital and Loneliness in Older Adults in Pekanbaru, Indonesia. Health Educ Health Promot 2024; 12 (3) :407-413
URL: http://hehp.modares.ac.ir/article-4-75346-en.html
URL: http://hehp.modares.ac.ir/article-4-75346-en.html
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Abstract (1617 Views)
Aims: This study aimed to explore the correlation between social capital and loneliness among older adults residing in Pekanbaru, Indonesia.
Instrument & Methods: This cross-sectional study utilized multistage clustered sampling combined with consecutive techniques to enroll 257 participants from the Payung Sekaki sub-district and was conducted between January and February 2022. The Socio-demographic Questionnaire, Social Engagement Questionnaire, and Loneliness Questionnaire were administered to collect data and the obtained data were analyzed by the Chi-square test and logistic regression analysis using SPSS 22.
Findings: The results indicated significant associations between loneliness and age, gender, education, marital status, and social capital among older individuals. The results of the multivariate analysis using binary logistic regression revealed that education (p=0.010; OR=0.362; 95% CI=0.167-0.784) and social network (p=0.015; OR=1.836; 95% CI=1.150-2.677) were significant predictors of loneliness.
Conclusion: Socio-demographic characteristics and social capital are associated with loneliness.
Instrument & Methods: This cross-sectional study utilized multistage clustered sampling combined with consecutive techniques to enroll 257 participants from the Payung Sekaki sub-district and was conducted between January and February 2022. The Socio-demographic Questionnaire, Social Engagement Questionnaire, and Loneliness Questionnaire were administered to collect data and the obtained data were analyzed by the Chi-square test and logistic regression analysis using SPSS 22.
Findings: The results indicated significant associations between loneliness and age, gender, education, marital status, and social capital among older individuals. The results of the multivariate analysis using binary logistic regression revealed that education (p=0.010; OR=0.362; 95% CI=0.167-0.784) and social network (p=0.015; OR=1.836; 95% CI=1.150-2.677) were significant predictors of loneliness.
Conclusion: Socio-demographic characteristics and social capital are associated with loneliness.
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