Social capital and happiness in university students: a higher-order analysis

ABSTRACT

Social capital is a valuable asset in community psychology for the growth of happiness. The various components of social capital, including trust and reciprocity, help youth to function positively in society. Unfortunately, previous literature ignored a higher-order analysis of social capital with happiness. This research aimed to examine the association between various components of social capital and happiness. Using a convenient sampling technique, we gathered data from 843 university enrolled students (Male = 581, Female = 262, age 21–23) from four public universities in Punjab, Pakistan. The first and second hypotheses confirmed that bonding trust, bonding, bridging, and linkage engagements and components of social capital were positively associated with the happiness of youth. The higher-order social capital model should be replicated in future studies, and local government should take essential steps to get the trust of the people which is necessary for the development of society.

KEYWORDS:

• Social capital
• trust
• engagements
• happiness
• structural equation modelling

Background

The pursuit of happiness is a significant personal objective that has received considerable interest from social scientists globally (Arampatzi et al., 2018). Happiness encompasses feelings of joy, satisfaction, and well-being, accompanied by a perception that one’s life is fulfiling, significant, and valuable (Lyubomirsky, 2007). Prior research has categorized happiness into three distinct factors: life circumstances, genetic predisposition, and personal behaviours. Life circumstances include factors like marital status and employment status. Genetic predisposition refers to an individual’s inherent tendency towards positive mood and happiness. Personal behaviours include demonstrating gratitude, supporting relationships, engaging in physical activity, and participating in spiritual pursuits (Lyubomirsky et al., 2005).

Social capital is widely studied across multiple academic disciplines (Farid et al., 2021). In view of Bourdieu (1986), social capital refers to tangible and intangible resources associated with having a stable network of relationships characterized by mutual acquaintances, recognition, and institutionalization. In simpler terms, it relates to being a member of a community. Coleman (1988) characterized social capital by its function, found in the relationships between actors. The author posited that social capital encompasses the reliability of the social environment, adherence to norms, the presence of closed networks, and the effectiveness of social organizations. In view of Putnam (1993), social capital refers to social structure, including social networks, trust, and norms, that facilitates cooperation and coordination for mutual advantages.

In previous literature, social capital has positively influenced happiness (Gómez-Balcácer et al., 2022; Samreen & Majeed, 2019). The developed nations are experiencing the issue of declining happiness despite their economic competence. The existing literature shows decreased social capital as a possible cause for declining happiness. For example, Becchetti et al. (2008) and Winkelmann (2009) identified a positive association between social capital and happiness in Germany. Whereas, Helliwell et al. (2009) and Leung et al. (2010) have concluded the positive influence of social capital on happiness in Canada. Similarly, Bartolini and Sarracino (2011) revealed lower happiness in the US community due to declining social capital.

This paper enhances the existing literature on the association of various components of social capital with happiness in the following ways; Firstly, this research fulfils the contextual research gap because much of the existing literature predominately examines the developed countries that which tend to have similar financial conditions and cultural backgrounds, such as the US (Bartolini et al., 2013), Japan (Yamamura et al., 2015), Germany (Winkelmann, 2009), and Korea (Han, 2015). In comparison, there is a little work focusing on the relationship between social capital and happiness in developing nations (Lu et al., 2020) such as Pakistan. However, the present empirical research exhibits a dearth of knowledge regarding the generalizability of its findings and the degree to which they can be applied to a developing nation like Pakistan. Second, the methodological gap because previous literature only focused on trust or generalized trust, a proxy of social capital (Lu et al., 2020; Samreen & Majeed, 2019). In this context, literature ignored the operationalization of social capital at the micro level with various dimensions and sub-dimensions. Third, this research will address the theoretical gap because the previous literature ignored the higher-order analysis of social capital concerning happiness. While considering the limitations of the earlier studies, this research paper analyzes the causal effect of social capital on happiness by pursuing a twofold objective; in the beginning, we investigate the association between dimensions of social capital, including bonding, bridging, and linking capitals with happiness in youth. Furthermore, it also provides insights into the multiple dimensions of bonding, bridging, and linking social capital, such as bonding trust, bonding engagements, bridging trust, bridging engagements, linking trust, and linking engagements with happiness in youth.

Theoretical framework and hypotheses development

This study is based on the Putnam's theory of social capital (Putnam, 2000). Social capital is an umbrella term that encompasses the assets accessible to both groups and individuals through social interactions (Mahmood et al., 2018). Dimensions of social capital cover bonding, bridging (Putnam, 2000), and linking social capitals (Iqbal et al., 2023; Woolcock & Narayan, 2000). Bonding social capital refers to the close-knit ties that exist in homogeneous groups in society, such as strong ties with family, close friends, and neighbours, whereas bridging social capital encompasses to the weak connections that connect the individuals from diverse occupational and ethnic backgrounds, including informal and formal in social participation (Putnam, 2000). Linking social capital signifies the extent to which people establish relations with institutions and other people who possess mutual power or authority. These authorities facilitate the utilization of services, including employment opportunities and economic resources (Woolcock & Narayan, 2000). Theoretically, literature predicts the association of bonding and bridging social capital with happiness (Eid & Larsen, 2008) because strong and weak knit ties provide emotional support to individuals in society in times of crisis and disasters. Another similar research conducted by Laishram and Haokip (2023) concludes that bonding and bridging social capital enhance the trust in homogeneous and heterogeneous groups and provide a valuable source of happiness (Laishram & Haokip, 2023). Similarly, bridging social capital links to strong social cohesion, civic participation, and good neighbourhood relationships that foster life satisfaction and happiness (Taniguchi & Potter, 2016; Saud, 2020). Literature also predicts the relationship between linking social capital. For instance, links with administrative institutions help individuals participate in volunteer work associated with happiness (Han, 2015). Moreover, the association of individuals with different organizations in society increases their happiness levels (Dolan & Peasgood, 2008). Based upon the above theoretical justification, we proposed the subsequent hypotheses;

H₁:

Bonding social capital has a significant association with happiness

H₂:

Bridging social capital has a significant association with happiness

H₃:

Linking social capital has a significant association with happiness

Trust and happiness

Trust is central to social capital theory (Iqbal et al., 2022; Putnam, 1993). Lack of trust leads to reduced civic engagement, while trust serves as a vital social norm for social support and reciprocity (Sommerfeldt, 2018). The social capital theory has three types of trust: bonding, bridging, and linking (Iqbal et al., 2022). A strong level of trust links to social stability, governmental efficiency, and economic growth (Putnam, 1993).

However, bonding and bridging trust refer to the trust between people who belong to homogeneous and heterogeneous groups, respectively (Coleman, 1988; Putnam, 1993). Linking trust refers to the trust between individuals and institutions, such as the government or corporations (Woolcock & Narayan, 2000). Previous literature depicts that happiness can be influenced by the level of bonding, bridging (Coleman, 1988; Newton, 2001), and linking trust (Helliwell & Putnam, 2004) in the community, as trust creates a sense of security and belonging. High levels of trust can lead to increased happiness as individuals feel more connected to others and confident in their relationships and institutions (Coleman, 1988; Putnam, 1993). Homogenous groups (bonding social capital) provide a solid emotional support to the members, boosting trust and have been associated with happiness (Leung et al., 2011). Another research claims that trust within one’s family is a fundamental factor influencing happiness (Oshio, 2017). Similarly, linking trust has been associated with happiness because it makes society stable (Bjørnskov, 2008). Trust in social institutions gives people confidence, which is associated with happiness (Rodríguez-Pose & Von Berlepsch, 2014). Moreover, a research concluded that people’s trust in legislative institutions and the judiciary is positively associated with life satisfaction and happiness (Laishram & Haokip, 2023). Based on the above literature, we developed the following hypotheses;

H_1a:

Bonding trust has a positive association with happiness.

H_2a:

Bridging trust has a positive association with happiness.

H_3a:

Linking trust had a positive association with happiness.

Engagements and happiness

Similarly, bonding, bridging, and linking engagements are all important components of social capital theory (Iqbal et al., 2022; Islam et al., 2006). A strong web of associations, regardless of their forms, generates beneficial effects that promote stability, trust, economic growth, and governmental efficiency (Putnam, 1993). Bonding, bridging, and linking engagements predict well-being, a proxy of happiness (Iqbal et al., 2022). Strong social engagements, increased exposure to new ideas and perspectives, and feelings of personal growth and empowerment have all been linked to increased overall well-being and happiness (Diener & Seligman, 2002). Family engagement is positively associated with the happiness of its members, as it offers opportunities for leisure and comfort (Melton & Zabriskie, 2016). Previous research predicted a positive relationship between bridging engagement of individuals in the neighbourhood, happiness, and life satisfaction. Additionally, research has shown that strong linking engagements contribute to happiness by promoting social cooperation and solidarity (Rodríguez-Pose & Von Berlepsch, 2014). Similarly, students’ active involvement with educational institutions mitigates negative emotions and enhances their happiness (Durón-Ramos & García-Vázquez, 2018). In the context of the above discussion, this research set forth the following hypotheses;

H_1b:

Bonding engagements had a positive association with happiness.

H_2b:

Bridging engagements had a positive association with happiness.

H_3b:

Linking engagements had a positive association with happiness.

Methodology

Sampling

Using a convenient sampling technique, we gathered data from 843 participants enrolled in four public sector universities in Punjab, Pakistan. Of the 1015 distributed questionnaires, 996 were returned. After removing the incomplete and biased questionnaires, we retained 843 questionnaires for data analysis, yielding a response rate of 85%. Previous literature has identified various cut-off points for survey response rates. For example, Sekaran and Bougie (2010) recommended that a minimum response rate of 30% is sufficient for research. Similarly, De Vaus (2013) suggested that a survey response rate 30%–70% is acceptable in social sciences. However, we collected the data in a classroom original settings.

Measurement of the variables

We used social capital as an independent variable covering the following three dimensions: bonding, bridging, and linking social capital. Each dimension of social capital covered the following two sub-dimensions: trust and engagements. We adopted the social capital scale from the work of Chazdon et al. (2013) (see Appendix A). The Cronbach's alpha values (α) of the all scales were in the acceptable ranges (see Tables 3 and 5).

Table 1. Factor loading of the happiness scale (N = 843).

Labels	Items	Loadings
	Since One Month
Hap_1	I feel happiness in every situation in my life.	.743
Hap_2	I feel perfect peace of mind.	.729
Hap_3	I feel inner satisfaction.	.770
Hap_4	I feel inner fulfilment.	.730
Hap_5	I feel I have a strong ability to overcome displeasure.	.710
Hap_6	I feel spiritual fulfilment.	.675

Table 2. Demographic characteristics of the participants (N = 843).

Demographics	Category	Frequency & Percentage
Gender
	Male	581(68.9)
	Female	262 (31.1)
Age
	18–20	317 (37.6)
	21–23	433 (51.4)
	24–26	67 (7.9)
	27 or Above	26 (3.1)
Residential Area
	Rural	406 (48.2)
	Urban	438 (52.2)
Study Program
	BS	635 (75.3)
	MA/MSC	170 (2.2)
	MPhil.	38 (4.5)

Table 3. Item loadings, mean, standard deviation, VIF, AVE, CR, and Cronbach’s alpha.

	Items	Mean	SD	Loadings	VIF	AVE	CR	α
Bonding Engagements						0.545	0.826	0.725
(Boe)	Boe_1	3.474	1.146	0.844	1.522
	Boe_2	3.682	1.108	0.714	1.361
	Boe_3	3.605	1.079	0.675	1.351
	Boe_4	3.731	1.103	0.708	1.334
Bonding Trust						0.601	0.883	0.835
(Bot)	Bot_1	3.871	1.183	0.768	1.549
	Bot_3	3.827	1.135	0.784	1.625
	Bot_4	3.932	1.123	0.808	1.935
	Bot_5	3.985	1.174	0.783	1.837
	Bot_6	4.056	1.111	0.732	1.674
Bridging Engagements						0.524	0.814	0.726
(Bre)	Bre_1	3.397	1.024	0.796	1.207
	Bre_2	3.663	0.976	0.728	1.336
	Bre_4	3.386	1.159	0.661	1.626
	Bre_5	3.592	1.199	0.704	1.652
Bridging Trust						0.515	0.809	0.705
(Brt)	Brt_1	3.024	1.168	0.776	1.186
	Brt_2	3.474	1.048	0.665	1.424
	Brt_3	3.302	1.127	0.712	1.460
	Brt_5	3.243	1.173	0.713	1.343
Linking Engagements						0.591	0.896	0.862
(Lie)	Lie_1	3.695	1.419	0.751	1.840
	Lie_2	3.612	1.412	0.774	1.788
	Lie_3	3.664	1.365	0.772	1.900
	Lie_4	3.651	1.350	0.740	1.693
	Lie_5	3.988	1.329	0.783	1.756
	Lie_6	3.769	1.370	0.791	1.959
Linking Trust						0.561	0.833	0.775
(Lit)	Lit_7	2.995	1.224	0.686	1.307
	Lit_8	3.316	1.229	0.780	1.840
	Lit_9	3.332	1.218	0.589	1.498
	Lit_10	3.402	1.180	0.904	1.663
Happiness						0.509	0.861	0.821
(Hap)	Hap_1	3.651	1.189	0.685	1.622
	Hap_2	3.664	1.135	0.688	1.549
	Hap_3	3.609	1.159	0.725	1.728
	Hap_4	3.741	1.101	0.674	1.562
	Hap_5	3.493	1.168	0.680	1.487
	Hap_6	3.629	1.066	0.816	1.397

Table 4. Discriminant validity of first-order constructs through HTMT ratios.

Items	Boe	Bot	Bre	Brt	Lie	Lit	Hap
Boe	-
Bot	0.176	-
Bre	0.188	0.075	-
Brt	0.126	0.066	0.411	-
Lie	0.133	0.062	0.084	0.060	-
Lit	0.095	0.039	0.073	0.069	0.529	-
Hap	0.481	0.186	0.169	0.137	0.126	0.69	-

Table 5. AVE, CR, VIF, and Cronbach's alpha values of second-order constructs.

Types of Social Capital	VIF	AVE	CR	α
BONSOC	1.029	0.564	0.715	0.750
BRISOC	1.018	0.651	0.788	0.733
LINSOC	1.012	0.708	0.828	0.854

Similarly, we developed a six-item happiness scale with the help of previous literature. Using SPSS version 22, we calculated the KMO score and Brattlett’s test of sphericity to validate the happiness scale. If the KMO score is greater than 0.80 and has acceptable Brattlett’s test of sphericity, the scale is considered valid for factor analysis (Moore & Kirkland, 2007). We found that the happiness scale was suitable for factor analysis because SPSS loaded all items in a single factor with a KMO score of 0.866, and Brattlett’s test of sphericity was also acceptable (Chi-square = 1463.33; p = 0.000). The scale’s Cronbach’s alpha value was 0.821 (See Table 2).

Analysis of the data

Using SmartPLS ver. 4, we conducted a structural equation modelling (SEM) analysis of the data. Before this, we fulfiled SEM’s prerequisite assumptions, such as missing value analysis, common method bias, outliers, and multicollinearity. First, we excluded all the incomplete questionnaires and missing data from the analysis. Second, we checked the multivariate outlier using the Mahalanobis distance test and found no outliers. Third, we did not find a common method bias in the single-factor analysis because single factor explained only 27.41% of the variance, which was acceptable according to the recommendation of Podsakoff and Organ (1986). Moreover, data did not find evidence of multicollinearity because VIF values in Table 3 are below 5, which meets the benchmark suggested by Hair et al. (2021).

Using SmartPLS 4, we used measurement and structural models to discuss our results (see Tables 3–6). The measurement model covers convergent and discriminant validity, while the structural model deals with hypothesis testing (Hair et al., 2021). We used the bootstrapping method with 5000 resamples to examine the structural models (see Tables 7–8). We used a repeated indicator approach to validate the research model of this study. In repeated indicator method, the explicit factors of the first-order constructs are reused for the second-order construct. This process for using PLS to model second-order structures is based on Wold’s (1982) hierarchical components method.

Table 6. Discriminant validity of second-order constructs through HTMT ratio.

Types of social capital	BONSOC	BRISOC	LINSOC	Hap
BONSOC	-
BRISOC	0.303	-
LINSOC	0.235	0.074	-
Hap	0.703	0.213	0.111	-

Table 7. Relationship between BONSOC, BRISOC, LINSOC, and happiness in youth.

Hypotheses	The path	Beta Value	T-value	P-values	Decision	R^2	Q2
H1	BONSOC → Hap	0.330	8.727	<.001	Accepted	0.139	0.062
H2	BRISOC → Hap	0.122	3.434	.001	Accepted
H3	LINSOC → Hap	0.076	2.348	.019	Accepted

Table 8. The relationship between Boe, Bot, Bre, Brt, Lie, Lit, and happiness among youth.

Hypothesis	Path	Beta Value	T-value	P-values	Decision	R^2
H1a	Boe → Hap	0.433	13.424	<.001	Accepted	0.243
H1b	Bot → Hap	0.099	3.257	.001	Accepted
H2a	Bre → Hap	0.067	2.097	.036	Accepted
H2b	Brt → Hap	0.059	1.891	.059	Rejected
H3a	Lie → Hap	0.060	1.979	.048	Accepted
H3b	Lit → Hap	0.002	0.055	.956	Rejected

Results

Descriptive statistics

Table 1 depicts the demographic profile of the respondents. From the selected sample, 68.9% of the participants were male students. More than half (51.4%) of the respondents were between 21 and 23 years old. About 52.2% of respondents belonged to urban areas, and most of the participants in this survey were studying in BS programs (75.3%).

Table 3 shows the mean values of the latent variables. The findings depict that the mean values of items of the latent variables are above 3, indicating that most respondents agreed with the statements of the questions.

Measurement model of the first-order constructs

Table 3 shows the measurement model of this research. The measurement model consists of item loadings, variance inflated factor (VIF), composite reliability (CR), average variance extracted (AVE) and HTMT ratio (Hair et al., 2021). The acceptable range of item loadings and AVE exceeds 0.50 (Hair et al., 2021). Following the benchmark of Hair et al. (2021), a total of 33 retained items had AVE values greater than 0.50 (See Table 3). The cut-off value of CR is 0.70 (Hair et al., 2021). We found that all CR values of the latent variables were in the acceptable ranges (see Table 2). Similarly, multicollinearity was checked. The acceptable range of VIF values is 5 or below (Hair et al., 2021). We found that the VIF values of each construct in this study were below benchmark 5 (see Table 3). Finally, the item loadings were also acceptable.

Table 4 shows that HTMT ratios of first-order constructs were below the cut-off value of 0.85, indicating that all the constructs differed from each other and established discriminant validity (Hair et al., 2021).

Measurement model of second-order constructs

Table 5 shows the measurement model of second-order constructs of this study. The findings show that AVE, CR, VIF, and Cronbach alpha values of all variables are in acceptable ranges.

Table 6 shows that HTMT ratios of second-order variables were below the suggested value of 0.85, indicating that all the variables differed from each other and established discriminant validity.

The above findings (see Tables 1 to 5) show that first-order and second-order measurement models meet the prerequisite assumptions of SEM, and data are appropriate to run the structural models.

Structural model

Table 7 and Figure 1 show the structural model or hypothesis testing of the second-order variables. The findings show that bonding social capital (β = 0.330, t-value = 8.727, p < 0.001), bridging social capital (β = 0.122, t-value = 3.434, p = 0.001), and linking social capital (β = 0.076, t-value = 2.348, p = 0.019), have a positive association with the happiness of youth. Based on the results, we accept H₁, H₂, and H₃.

Figure 1. Relationship between BONSOC, BRISOC, and LINSOC and happiness in youth.

Table 8 and Figure 2 show the structural model or hypothesis testing of the second-order variables. The findings show that bonding engagements (β = 0.433, t-value = 13.424, p < 0.001), bonding trust (β = 0.099, t-value = 3.257, p = 0.001), bridging engagements (β = 0.067, t-value = 2.097, p = 0.036), linking engagements (β = 0.060, t-value = 1.979, p = 0.048) have a positive association with the happiness of youth. Based on these findings, we accept H₁, H₂, H₃, and H₅.

Figure 2. The relationship between Boe, Bot, Bre, Brt, Lie, Lit, and happiness in youth.

Table 7 further shows that bridging trust (β = 0.059, t-value = 1.891, p = 0.059) and linking trust (β = 0.002, t-value = 0.055, p = 0.956) have no association with happiness. Based on the results, we reject H₄ and H₆.

Assessment of the research model

Validation of the structural model relies on two measures: cross-validated redundancy (Q²) and coefficient of determination (R²). R² values should be equal to or greater than 0.10 in order to indicate that the variance explained by the endogenous variables is both statistically and practically significant (Hair et al., 2021). The R² values of this study’s criterion variable at first- and second-order analysis were 0.243 and 0.139, respectively (see Tables 7 and 8). Similarly, cross-validated redundancy (Q²) greater than 0 indicates sufficient predictive relevance for justification the research model (Henseler et al., 2009). Table 7 depicts that the model’s Q² value is 0.062, exceeding the benchmark 0, indicating a sufficient Q² value.

Discussion and conclusion

We investigated the relationship between bonding, bridging, and linking dimensions of social capital and happiness among youth. Each dimension of social capital covers the two sub-dimensions such as trust and engagements. We used SEM to test the hypotheses.

This research found a positive association between bonding (H₁) and bridging (H₂) social capital with happiness. These findings (H_1, H₂) are consistent with previous studies (Munzel et al., 2018, Growiec & Growiec, 2014; Oshio, 2017; Sørensen, 2021), which concluded that the happiness of youth linked to the strength of bonding and bridging social capitals. Individuals with strong relationships with family and friends may have greater happiness and well-being since these relationships provide support and belonging. Similarly, youth with diverse relationships across different groups may have greater opportunities for new experiences and diverse perspectives, leading to greater happiness and well-being (Helliwell & Putnam, 2004). Moreover, we found a positive association between linking social capital and happiness (H₃). The findings of H₃ align with the results of Helliwell and Putnam (2004), who concluded that participation in clubs or organizations positively influences happiness. In conclusion, youth with connections with those in power and influence have greater access to resources and opportunities, leading to greater happiness and well-being (Ekici & Koydemir, 2014).

This research found that bonding (H1b) trust positively associates with happiness. This finding is consonant with the past literature. For example, Oshio (2017) found that bonding trust is associated with increased feelings of security and belonging, linked to higher happiness levels. One of our research findings (H2b) is inconsistent with Oshio (2017), who found a positive association between bridging trust and happiness. Bridging trust is important because it increases exposure to new ideas and perspectives, which has been associated with well-being and happiness (Diener & Seligman, 2002). Surprisingly, we did not find an association between bridging trust and happiness (H2b). One of the major reasons of rejection of H2b can be heterogeneous relationships in educational institutions where respondents of this research were pursuing their higher education. Respondents belonged to different regions of the country with differences in caste, race, religion, and ethnic groups that may undermine their trust and reduce happiness. We suggest revising the findings of H2b in the future research.

Similarly, we found that linking trust does not associate with happiness (H_3b). The finding of H_3b is inconsistent with the results of Ekici and Koydemir (2014), who found that linking trust is associated with happiness. Trust in institutions enhances citizen civic participation, judicial efficiency, and decreases the corruption in government (Porta et al., 1997), social problems crime rates (Fukuyama, 1995), ultimately, boosting happiness. Similarly, Brehm and Rahn (1997) concluded that trust in political and government institutions enhances life satisfaction. Linking trust is essential for any society’s development because it helps stabilize the government and democracy (Sommerfeldt, 2018). There could be a variety of reasons for rejecting H_3b. Firstly, participants in this study may indicate a lack of trust in governmental and social organizations due to their perceived failure to meet citizens’ basic needs, which reduces overall happiness. Second, Pakistan is amid a serious political, economic, and social crisis. People in this circumstance frequently experience instability, despair, and uncertainty, which can lower their level of happiness. However, we recommend that future studies reconsider the H3b findings.

We conclude that bonding (H_1a) and bridging (H_2a) engagements are positively associated with happiness. These findings are aligned with Munzel et al. (2018), who explored that strong and weak engagements contribute to well-being and happiness. Bonding and bridging engagements refer to the mutual exchange of goods, services, or privileges between individuals. It is a key aspect of many social relationships and is often associated with happiness and well-being (Putnam, 2000). Happy relationships, whether bonding or bridging, tend to be characterized by high levels of reciprocity and mutual support (Ekici & Koydemir, 2014). We also concluded in this research that linking engagements (H₉) positively affects happiness. In context to the previous literature, Gómez-Balcácer et al. (2022) found that the strong engagement of individuals with religion and social institutions enhanced happiness among individuals. Similarly, people who engage with clubs and power structures of society have a higher level of happiness (Helliwell & Putnam, 2004).

Implications

This study has various theoretical and practical implications. First, we blend the social capital theory with happiness using a higher-order analysis approach, a new contribution to literature. We suggest replicating these findings in future research. Second, in this research, we focused on the students enrolled in public universities, and we suggest that future research should change the sample by addressing those individuals who may not be enrolled in university and belong to different age groups. Third, we developed a new six-item happiness scale in this research. We suggest applying and validating this scale on a large sample size. Finally, we found no association between linking (H_3b) and bridging trust (H_2b) with the happiness of youth. We suggest replicating these results (H_3b, H_2b) on large sample sizes and similar settings. We also suggest that the government make policies to enhance trust in society because trust helps to stabilize the government and democracy (Sommerfeldt, 2018). Our research findings motivate the government to take further steps to improve the level of social capital in society that predicts happiness. Strong bonding, bridging, and linking relationships reduce depression, loneliness, and antisocial behaviour among youth. Practically, our research findings can be helpful for policymakers to advocate policies and interventions for youth that may strengthen the community through proper engagement, promote social cohesion and well-being. Practically, the findings can be helpful for the university administration, educational policymakers, and teachers to understand the importance of social ties that develop positive psychology among youth. For this purpose, we suggest that stakeholders establish youth counselling centres in educational institutes to guide students in maintaining social relationships in times of crisis.

Limitations

This research has the following limitations: First, this research was cross-sectional in nature. Future research should follow the longitudinal research design to understand how the important components of social capital, such as trust and engagement, change over time, and influence happiness. Second, this research was limited to quantitative methodology. However, a mixed methodology can be helpful in answering the question of why social capital influences happiness. Thirdly, this research is limited to a small sample size in one province of the country, whereas future research should be conducted on a large sample size covering all provinces. Fourth, the research was limited to the youth enrolled in public universities. In the future, the research scope can be enhanced by engaging youth enrolled in private universities and those not enrolled in public or private institutions. A similar comparison can also be made between young and old people. Fifth, this research is limited to second-order analysis. The scope of the research can be enhanced by running a third-order analysis. Future research should also add a mediating variable, such as self-efficacy, in the association between social capital and happiness.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Appendix A

The social capital scale used in this research

Table

Sr.	Bonding Social Capital (BONSOC)	Strongly Disagree (1)	Disagree (2)	Neutral (3)	Agree (4)	Strongly Agree (5)
	Bonding Engagement (Boe)
Boe_1	I can count on someone in the community if I need some extra help.
Boe_2	I and people in my community do favours for each other.
Boe_3	I would ask my neighbours for help if I were sick
Boe_4	Community members would get together to help a neighbour with a serious need
	Bonding Trust (Brt)
Bot_1	My family gives me belongings.
Bot_3	My immediate neighbours give me belongings.
Bot_4	My friends in university give me belongings.
Bot_5	My place of worships gives me belongings.
Bot_6	The people who share my ethnic background give me belongings.
	Bridging Social Capital (BRISOC)
	Bridging Engagement (Bre)
Bre_1	I contact with people much older.
Bre_2	I contact with people different religion.
Bre_4	I contact with people much poorer.
Bre_5	I contact people with disabilities.
	Bridging Trust (Brt)
Brt_1	I trust on the people in clubs
Brt_2	I trust on people with other cultures.
Brt_3	I trust on people with other religious beliefs.
Brt_5	I trust on friends who are living in other community.
	Linking Social Capital (LINSOC)
	Linking Trust (Lit)
Lit_7	I trust on local government.
Lit_8	I trust on state government.
Lit_9	I trust on educational orgs in community.
Lit_10	I trust on trust on health care orgs in community.
	Linking Engagement (Lie)	Never (1)	Rarely (2)	Often (3)	Very Often (4)	Always (5)
Lie_1	I attended public meeting
Lie_2	I attended political meeting or rally.
Lie_3	I attended club or organization meeting.
Lie_4	I hosted or visited community leader.
Lie_5	I joined together to address community issue.
Lie_6	I donated money, goods, and services.

Happiness scale used in this research

Table

Sr.	Statements	Never (1)	Rarely (2)	Often (3)	Very Often (4)	Always (5)
Hap_1	I feel happiness in every situation of my life.
Hap_2	I feel a perfect peace of mind.
Hap_3	I feel inner satisfaction.
Hap_4	I feel inner fulfilment.
Hap_5	I feel I have a strong ability to overcome displeasure.
Hap_6	I feel spiritual fulfilment.