4
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2023
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https://submissions.qlantic.com/index.php/qjss/article/download/104/166
https://submissions.qlantic.com/index.php/qjss/article/view/104
Social Networks Subjective Well-being Social Connectedness Social Solidarity
| Vol. 4, No. 4 (Fall 2023) |
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Original Research Article
Open Access | | |
| Linking Social Connectedness to Subjective Well-Being: A Positioning Model of Mechanical Social Solidarity | |
Fazal Qadar 1 Imran 2 Sarfaraz Khan 3 Nazirullah 4 Zahid Nasir 5 | ||
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Abstract: The study measures the association between social connectedness and subjective well-being in rural communities. The study’s population was rural areas of District Swat, Khyber Pakhtunkhwa, Pakistan. A quantitative analysis was designed, and data was collected randomly with the help of a well-structured interview schedule from males and females at two Tehsils of Swat, i.e., Khwazakehla and Matta, with a sample size of (n=473). The collected data was analyzed through descriptive and inferential statistics. The results revealed that social connectedness has an association with subjective well-being among rural communities. In conclusion, the study highlights that community people share interests, ideas, and thinking about social networking, which ultimately helps poor, marginalized people and voluntarily informs the communities regarding communal problems. The study recommended to policymakers that knowledge from outside sources is essential and that extensive networks of individuals need more up-to-date information regarding the healthcare system and their expectations for the future. | ||
Key Words: Social Networks, Subjective Well-being, Social Connectedness, Social Solidarity | ||
Introduction
Several researchers have highlighted the problem of subjective well-being in the context of individual overall life satisfaction and happiness (Diener et al., 1985; Diener, 2000; Eid & Diener, 2004; Diener, & Ryan, 2009). Social connectedness is a common problem that connects to social networking and subjective well-being. The role of social networking is one of the most significant aspects of social capital. The majority of studies have interconnected the part of social networking in the form of provision of information, resource accessibility, discovering new knowledge, constructing relationships, and preventative actions in unfavorable situations (Pinquart & Sorensen, 2000; Shiovitz-Ezra & Litwin, 2012; Huxhold, 2013). The current sustainable development goal 3 prioritizes the role of individual health and well-being for all ages in the industrialized and non-industrialized zones of the global world (Dyakova, 2017). Personal well-being can be considered non-material dimensions such as poverty reduction, human capacity building, life satisfaction, and subjective well-being (Sen, 1999; Gough et al., 2007; UNDP, 2011). Subjective well-being is achieved, and it’s the focus of an increasing number of global policymakers in recent decades (Fonseca et al., 2020). The Secretary General of the United Nations also showed enthusiasm for the subjective well-being approach in the community. The role of social connectedness is the center of communal agencies and promotes life satisfaction, happiness, and subjective well-being (Henderson & Loreau, 2023). The study found that sustainable goals could be achieved with a community participatory approach in the contemporary world, and it is used to develop social and economic policies for the overall community (Svyrydenko et al., 2023). Earlier studies proved that the relationship between social connectedness and subjective well-being is influenced by wealth, education, age, and occupation (Xu et al., 2023; Aldhaheri et al., 2023). Such as a positive social connectedness has an association between individuals’ social capital and subjective well-being (Ni & Ishii, 2023; Sarracino, 2010; Leung et al. 2011; Klein, 2011). Extensive research on social capital has been conducted across a wide range of academic fields, including education, sociology, economics, and political science. Many different philosophers and academics have, each in their way, described social capital and linked it to the micro-and macroeconomic well-being of the individual as well as the entire society (Dolan et al. 2008).
Social relationships are one of the most essential components of social capital, which is based on individuals, altruism, and compassion. The basis of social ties is favorably connected with increased life quality, the experts state (Woolcock & Narayan 2000). Social ties are the origin of exchanges that increase social capital (Coleman, 1988; Portes & Sensenbrenner, 1993). Social ties facilitate resourcefulness, thereby enhancing social capital (Lin, 2001; Akaeda, 2023). According to Pong et al. (2005), social capital can be linked to the social support and assistance component and is categorized as a social network dimension. Several authors found dimensions of subjective well-being and identified social capital as one of the most essential components of individual subjective well-being (Kahneman & Krueger, 2006; Kobau et al., 2011; Lengyel et al., 2019). However, a drop in subjective well-being is connected with negative associations, isolation, and loneliness for the individual (Shankar et al., 2015). Individuals gain social support through their social interactions. The primary sources of a person’s subjective well-being are social support from peers, neighbors, colleagues, and friends (Brown et al., 2003; Lepore, 2008). The studies concluded that the size of an individual’s social network has a favorable effect on subjective well-being among middle-aged and older (Moorman & Boener, 2017; Litwin & Shiovitz, 2011). The abovementioned critical scientific literature review guided researchers to construct a theoretical framework with the help of social solidarity to interrelate a deeper understanding between social connectedness and subjective well-being from the community perspective (See Figure 1).
Figure 1
Subjective Well-being
Social Connectedness
Mechanical Social Solidarity Theoretical Model
Study Design
The main objective of the study was to measure the association between social connectedness and individuals’ subjective well-being. The study applied quantitative research methods and a positivist standpoint. A cross-sectional research design was used for the study. The population distribution of District Swat, Tehsils Khwazakhela, and Matta is 87% of the rural population. Tehsil Khwazakhela consists of 7 Union Councils (UCs), of which 6 are rural, while Tehsil Matta consists of 14 UCs, of which 13 are rural.
Sampling Procedure and Sample Size
The total number of rural union councils was 19 in these two tehsils, with a ratio of 1:2 (1 rural UC in Khwazakhela and 2 in Matta). Based on this, two rural UCs from Tehsil Khwazakhela (Kotanai and Shin) and four rural UCs from Tehsil Matta (Beha, Pir Kalay, Darmai, and Arkot) were chosen randomly as unity of analysis. Besides, a multistage stratified random sampling technique was applied for the first level and then divided the universe into Tehsils. Furthermore, the division of Tehsils was stratified into Union Councils, and then Union Councils were divided into rural and urban Union Councils.
As a result, the required total population was (N= 214,713) and the derived sample size was (n=473) as per the analogy of the Sher Muhammad Chaudhry sample size formula (Chaudhry, 2009). The calculated sample size (n=473) is proportionally allocated to the selected Union Councils based on Bowley’s proportional allocation formula as per the population of the Union Councils (Bowley, 1926). The proportional allocation of the sample size is represented in Table 1.
Table 1
Allocation of required sample to selected union councils (n=473)
Tehsil | Union Council | Population | Require Sample size |
Khwazakhela Tehsil | Kotanai | 35,651 | 79 |
Shin | 34,973 | 77 | |
Matta Tehsil | Beha | 33,065 | 73 |
Pir Kalay | 41,148 | 91 | |
Darmai | 28,300 | 62 | |
Arkot | 41,576 | 91 | |
Total | 214,713 | 473 | |
Data Collection
The primary data was obtained from the (male and female) respondents above 18 years of age. The tool for data collection was a structured interview schedule. The questionnaire scale was adapted from (Akaeda, 2023) with 5 items. Secondly, the social connectedness scale was adapted from the study (Lee & Robbins, 1998) with 20 items, and 12 items were discarded due to low factor loading and internal consistency scores. Several items were removed due to their ambiguities and inconsistencies. In this study, the 5-point Likert scale was used to measure both independent and dependent variables. Variable computation is an essential part of data analysis. All the study items were computed and converted into a single variable.
Data Analysis
Data was analyzed through descriptive and inferential statistics. The tool was Statistical Packages for Social Sciences (SPSS) version 21. Univariate and bivariate analyses were applied, and the Chi-square test was measured. In addition, reliability analysis was performed to assess the instrument's internal consistency. Cronbach’s alpha of social connectedness was (α = 0.763, Mean = 3.564) and subjective well-being alpha level was (α = 0.721, Mean = 4.731).
Study Findings and Discussion
The study interpreted bivariate analysis with the current literature review. Each factor was analyzed and concluded. The results were logically related to the previous studies' findings.
Bivariate Analysis
Items Wise Association of Social Connectedness between Subjective Well-being Among Rural Communities
The study revealed that individuals share their profit and ideas with other people for their subjective well-being. The hypothesis was accepted with a p-value (p = 0.001), and the association was found. Hofferth and Iceland (1998) found that families in rural areas of American households are more likely to interact exclusively with kin than families in urban areas. The supporting notion of family ties is more substantial, and families are strongly connected to their kin networks. In a survey, Mair and Thivierge-Rikard (2010) found that social networks have strong relationships (such as visiting friends, neighbors, or family members) with subjective well-being among rural rather than urban older adults. Different social interaction expectations may explain subjective well-being. These findings were also confirmed by Xu et al. (2022), and the present found that family social capital was significantly associated with subjective well-being (p = 0.051).
Furthermore, a significant association (p = 0.050) was measured between social networks and subjective well-being in rural communities’ individuals. The use of social media has diverse effects on individuals. On the one hand, social media platforms expand social relationships, boosting individuals’ self-esteem, life happiness, and self-presentation alternatives (Malik et al., 2020). On the contrary, several researchers have extensively discussed the negative implications of social media usage on individuals' well-being (Kaur et al., 2021; Tandon et al., 2021a), insomnia induced by social networking use (Kaur et al., 2021), and how social media stimulates negative emotional states, such as jealousy (Malik et al., 2020; Dhir et al., 2018). Online subjective well-being is one of the issues, and research scholars should focus on the context of rural communities (Chang & Hsu, 2016; Huang, 2016; Diener et al., 2015).
Moreover, a widespread circle of friends has a relationship with subjective well-being in rural communities and a larger circle of friends with significant value (p = 0.037). Friendships, personal contacts, and a person’s sense of self are related to subjective well-being (Kramer & Schawel, 2020). Luo and Hancock (2020) concluded that self-disclosure leads to increased access to social networks, endorsements, and financial resources. Meanwhile, Kim et al. (2014) found a negative association between well-being and sharing personal information. Huang (2016) delineated a positive relationship between well-being and sharing personal information. For instance, Tandon et al. (2020) agreed that new generations share their personal information for nomination and identity of well-being.
Social network thinking is significantly associated with subjective well-being (p = 0.021). The results of the study of Shah et al. (2021) and Malik et al. (2020) were linked with the current study. Vogel et al. (2018) found that social media has privacy concerns, and people are less willing to disclose personal information. Equally, Facebook use is related to both offline and online disclosures, although privacy concerns are a barrier for individuals. In conclusion, the study of Alashoor et al. (2017) proved that social media-aware individuals related to considerable data-related familiarity, self-efficacy, perceived control, and vulnerability are increased. Notwithstanding, the current study found that social networks often have a significant relationship with subjective well-being (P=0.005) From these facts, we can conclude that feelings belong to a social construction theory. As per social constructionists, people's peers are often utilized as evaluation criteria. If an individual feels superior to others, their subjective well-being will increase. Similarly, the study measured the relationship between a person's family and financial surroundings and its impact on experience and way of thinking (George & Landerman, 1984; Hnilica, 2011). The study found that social connectedness items have an association with subjective well-being.
Similarly, the study results revealed that frequent response to social networking has a significant effect on subjective well-being (p = 0.017). Moreover, social networks create the feeling of being together with individuals and have a significant association with subjective well-being among community members (p = 0.026). Lastly, openly communicating with individuals has an association with subjective well-being (p = 0.000). The study of Dhir et al. (2018) measured network heterogeneity elements and social media use to explain the individual’s constant information and subjective well-being among rural communities. The suggestion was put forward to the policymakers that diverse social networks can improve the social interactions and communication of middle-aged and older retirees’ optimistic subjective well-being. As per the study of Lin et al. (2001), social networks are fundamental to the exchange and transfer of diverse cultural information. Thus, Allemand et al. (2012) vast and diverse social networks offer more significant social and emotional resources to communities’ individuals. The study controlled chronological age and then countered the total association of social networks with subjective well-being. The current study does not control the role of the age cohort and analyze the results. Future researchers can find the prospectus and challenges of the age cohort association with cognitive well-being and social networks (See Table 2).
Table 2
Items Wise Association Between Social Connectedness and Subjective Well-being in Rural Communities (n = 473)
Social Connectedness | Dependent Variable | Chi-square & P value |
I believe my social network members share my interests and opinions. |
subjective well-being in rural communities | χ2= 11.377 P=0.001 |
I feel that I share many similarities with the folks in my social network. | χ2= 13.664 P=0.050 | |
I'd like to expand my circle of friends. | χ2= 13.341 P=0.037 | |
I frequently find out what individuals in my social network think. | χ2= 10.956 P=0.021 | |
I believe that people in my social network frequently think of me. | χ2= 17.511 P=0.005 | |
I frequently consider persons in my social network. | χ2= 15.646 P= 0.017 | |
I often feel "together" with people in my social network, even when we don't talk. | χ2= 13.984 P=0.026 | |
I believe I can talk openly with folks in my network. | χ2= 14.095 P= 0.000 |
Note: Chi-square = χ2
Source: Survey, 2022
Combined Social Connectedness and Subjective Well-being
In the light of reported results, social connectedness and subjective well-being are conceivable. Although, Thomas (2011) found that social support has a relationship with subjective well-being. However, some analysts have found a direct association between social support and subjective well-being (Lakey et al., 2010). The study hypothesized that social connectedness and subjective well-being have an association, and the study results proved it (p = 0.000). The degree of association between social connectedness and subjective well-being was strong and significant (See Table 3).
Table 3
Combined Association Between Social Connectedness and Subjective Well-being (n = 473)
Indexed Independent variable | Dependent variable | Chi-square and P-value |
Social connectedness | subjective well-being | X2=32.065 (0.000) |
Source: Survey, 2022
Conclusions
Social connectedness and subjective well-being have an association among rural communities' individuals. The study explored that individuals share their interests, ideas, and thinking with their circle and social network. The individuals believe that caring for poor and hungry people has a relationship with subjective well-being. This technique has demonstrated high-quality results in communal connectedness issues and financially supporting social organizations. Similarly, individuals who live in rural areas are trusted and willing to help needy and marginalized people. The neighborhood has a fair impact on social cohesion. The study found that social connectedness provided large social networks for acquiring new information, knowledge, social engagement, and subjective well-being. Therefore, community-level social connectedness helps all age groups' subjective well-being. It is recommended that policymakers should arrange social connectedness awareness among communities.
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1 PhD Scholar, Department of Rural Sociology, The University of Agriculture, Peshawar, KP, Pakistan.
2 Assistant Professor of Sociology and Head, Department of Social and Gender Studies, University of Swat, Swat, KP, Pakistan.
3 Assistant Professor of Pakistan Studies and In-Charge, Center for Caucasian, Asian, Chinese, and Pakistan Studies, University of Swat, Swat, KP, Pakistan.
4 Postgraduate Researcher, Faculty of Applied Social Sciences, Universiti Sultan Zainal Abidin, Malaysia.
5 Lecturer in Pakistan Studies, Center for Caucasian, Asian, Chinese, and Pakistan Studies, University of Swat, KP, Pakistan.
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