How Physical Activity Shapes Psychological Well-Being among Older Adults: A Dual-Pathway Mediation Model of Social Contact and Emotional Support

1. Introduction

Population aging presents a significant global challenge, raising concerns about how to maintain and enhance psychological well-being in later life. As life expectancy increases, ensuring both physical health and emotional quality of life has become crucial for researchers and policymakers. In this context, physical activity is widely recognized as a key factor contributing to successful aging. A substantial body of research shows that engaging in physical activity is linked to higher life satisfaction, fewer depressive symptoms, and improved emotional functioning among older adults (McAuley et al., 2000; Netz et al., 2005; Rejeski & Mihalko, 2001).

Beyond its direct psychological benefits, recent studies suggest that physical activity may enhance well-being through broader social mechanisms. Participation in physical activities often takes place in socially interactive settings, fostering opportunities for interpersonal contact and social engagement. Previous research has indicated a strong association between social relationships, physical activity participation, and psychological well-being (Berkman & Glass, 2000; Holt-Lunstad et al., 2010; Lindsay-Smith et al., 2017). These findings suggest that the advantages of physical activity may partly stem from its ability to facilitate social interaction and integration, particularly for older adults who may be at greater risk of social isolation.

However, social relationships are not a single entity; they encompass multiple dimensions that may operate through different mechanisms. Prior studies have differentiated between the structural aspects of social relationships, such as the frequency of contact, and functional aspects, like the availability of emotional support (Umberson & Montez, 2010). While both dimensions are linked to health and well-being, their effects can vary. Structural relationships, characterized by active engagement and network integration, are generally associated with positive outcomes. In contrast, functional relationships, especially emotional support, may sometimes indicate underlying vulnerability, dependency, or an increased need for assistance (Seeman et al., 2001; Newsom & Schulz, 1996). Despite this distinction, many studies have treated social relationships as a single construct, potentially obscuring important differences in their effects on well-being.

Empirical findings on the role of social support in well-being during later life have yielded mixed results. Some studies indicate positive effects, while others suggest that higher levels of received support can correlate with poorer psychological outcomes, especially for individuals facing health declines or social disadvantages (Rook, 2015; Shrout et al., 2006). These inconsistencies underscore the necessity for a more nuanced approach that distinguishes between different types of social relationships and explores their unique roles within a comprehensive analytical framework.

The Korean context offers a particularly relevant backdrop for investigating these issues. Historically, social relationships among older adults in Korea have been characterized by strong family ties and cultural norms that prioritize filial piety. However, rapid demographic and social changes—such as population aging, declining fertility rates, and an increase in single-person households—have altered these traditional structures. Recent studies suggest that these changes are linked to heightened social isolation and evolving patterns of support among older adults, which have significant implications for psychological well-being (Lee & Choi, 2020; Lim & Putnam, 2010). In this context, it is increasingly important to understand how various dimensions of social relationships impact well-being.

Despite a growing interest in the interplay among physical activity, social relationships, and well-being, several critical gaps persist. First, many studies have explored these factors in isolation, neglecting the interconnected pathways through which physical activity affects well-being via social mechanisms (Berkman & Glass, 2000; Holt-Lunstad et al., 2010; Lindsay-Smith et al., 2017). Second, prior research has often treated social relationships as a unidimensional construct, failing to recognize the distinct roles of their structural and functional dimensions (Umberson & Montez, 2010; Thoits, 2011; Rook, 2015). Third, empirical findings regarding the effects of social support remain inconsistent, particularly in later life, with some studies reporting positive effects while others identify negative or conditional relationships (Seeman et al., 2001; Newsom & Schulz, 1996; Shrout et al., 2006). To address these limitations, the present study adopts a dual-pathway perspective, differentiating between social contact and emotional support while examining their simultaneous mediating roles. By integrating these dimensions within a unified model, this study aims to clarify and theoretically ground our understanding of how behavioral and social mechanisms collectively shape psychological well-being among older adults.

2. Literature Review

2.1. Physical Activity and Psychological Well-Being in Later Life

Physical activity is consistently recognized as a crucial factor influencing psychological well-being in later life. Substantial empirical research shows that regular physical activity correlates with greater life satisfaction, improved emotional functioning, and fewer depressive symptoms among older adults (McAuley et al., 2000; Netz et al., 2005; Rejeski & Mihalko, 2001). These advantages extend beyond physical health, impacting psychological and behavioral aspects such as enhanced self-efficacy, better emotional regulation, and a strengthened sense of purpose.

Activity Theory posits that ongoing engagement in meaningful activities is vital for maintaining well-being in later life. This framework suggests that participating in physical activity helps older adults preserve their social roles and identity, leading to improved psychological well-being. Further empirical studies in leisure and aging research support this perspective, showing that active involvement in physical and recreational activities is positively linked to subjective well-being (Kuykendall et al., 2015; Pressman et al., 2009). Therefore, both theoretical and empirical evidence indicate that physical activity has a beneficial impact on psychological well-being.

H1: 

Physical activity will have a positive direct effect on psychological well-being.

2.2. Social Relationships as Behavioral Pathways

Physical activity is increasingly recognized not only for its direct physical benefits but also for its role as a socially embedded behavior that fosters interpersonal interaction and social engagement. When individuals participate in physical activities, they often do so in group or community settings, creating opportunities to connect with others and build social ties. Research has shown that social relationships significantly influence both participation in physical activity and psychological well-being (Berkman & Glass, 2000; Holt-Lunstad et al., 2010; Lindsay-Smith et al., 2017).

It is important to note that social relationships are multifaceted. Previous studies differentiate between structural aspects, such as social contact and network integration, and functional aspects, like emotional support and perceived availability of assistance (Umberson & Montez, 2010). Structural dimensions indicate how actively individuals engage in social networks, while functional dimensions reflect the quality and accessibility of supportive resources. These distinctions imply that physical activity may enhance psychological well-being through various social mechanisms. Specifically, increased physical activity can promote social contact by creating more opportunities for interaction, which may lead to better well-being outcomes.

2.3. Theoretical Perspectives on Behavioral and Social Mechanisms

Social contact is a crucial aspect of social relationships, encompassing the frequency and intensity of interactions with family, friends, and neighbors. Research consistently shows that higher levels of social contact correlate with improved mental health, reduced mortality risk, and increased life satisfaction (Berkman & Glass, 2000; Holt-Lunstad et al., 2010). According to Activity Theory, social contact serves as a vital mechanism through which active engagement promotes well-being. Regular interactions offer opportunities for social participation, emotional exchange, and the reinforcement of social identity, all of which lead to positive psychological outcomes. Additionally, social integration theories indicate that individuals deeply embedded in social networks are more likely to feel a sense of belonging and purpose. Since physical activity often encourages interpersonal interactions, it is reasonable to conclude that social contact positively mediates the relationship between physical activity and psychological well-being.

H2: 

Social contact will positively mediate the relationship between physical activity and psychological well-being.

2.4. Functional Dimension: Emotional Support as a Complex Mediator

Emotional support is a key aspect of social relationships, encompassing the empathy, care, and understanding individuals receive from others. Traditional views in Social Support Theory assert that emotional support serves a protective function by alleviating stress and fostering psychological well-being (Cohen & Wills, 1985; Thoits, 2011). However, recent studies indicate that the impact of emotional support is not always beneficial. Research on aging populations, for example, shows that higher levels of received support can be linked to poorer health outcomes, as they may reflect underlying vulnerability, dependency, or a greater need for assistance (Seeman et al., 2001; Newsom & Schulz, 1996). In this light, emotional support may act as a compensatory mechanism, arising in response to declining health or adverse conditions. This aligns with the Stress Buffering Model, which suggests that the effects of social support are influenced by contextual factors such as stress and individual vulnerability (Cohen & Wills, 1985). Additionally, Socioemotional Selectivity Theory posits that older adults tend to prioritize emotionally significant relationships, which can lead to increased support exchanges in times of need rather than through proactive engagement (Carstensen et al., 1999). Collectively, these perspectives imply that emotional support may mediate the relationship between physical activity and psychological well-being in a more complex and potentially negative manner, reflecting underlying vulnerability instead of enhanced well-being.

H3: 

Emotional support will mediate the relationship between physical activity and psychological well-being, potentially in a negative direction.

2.5. Conceptual Framework

This study proposes a dual-pathway model based on the hypotheses above, illustrating how physical activity affects psychological well-being both directly and indirectly. This influence occurs through two distinct social mechanisms: (1) a positive pathway involving social contact (structural dimension) and (2) a complex pathway involving emotional support (functional dimension). This framework offers a more nuanced understanding of how behavioral and social factors collectively impact well-being in later life.

3. Methods

3.1. Data Source and Participants

This study used data from the 2020 Korean National Survey of Older Persons, a nationally representative survey conducted by the Ministry of Health and Welfare and the Korea Institute for Health and Social Affairs. The survey employed a stratified multistage sampling design to ensure that the older population aged 65 and above was adequately represented across Korea.

After excluding cases with missing or invalid responses on key variables, the final analysis included 10,097 participants. This sample consisted of community-dwelling older adults, offering a comprehensive overview of physical activity, social relationships, and well-being in later life.

3.2. Measurements

3.2.1. Physical Activity

Physical activity was assessed using three indicators: participation in exercise (yes/no), frequency of exercise, and duration of exercise. These indicators reflect both the engagement and intensity of physical activity and serve as observed measures of the latent construct "physical activity." They have been widely validated in large-scale population-based surveys to effectively capture behavioral engagement in physical activity and are deemed suitable proxies for population-level assessments.

3.2.2. Social Contact

Social contact, which reflects the structural dimension of social relationships, was assessed using three items that measure the frequency of interactions with family, friends, and neighbors. Higher scores indicate more frequent social interactions.

3.2.3. Emotional Support

Emotional support, which reflects the functional aspect of social relationships, was evaluated through two items that measured both the availability and frequency of such support. These items assess participants' perceptions of supportive resources within their social networks.

3.2.4. Psychological Well-Being

Psychological well-being was assessed using six items that evaluated life satisfaction, subjective happiness, and overall emotional state. These items were combined to create a latent construct representing well-being in later life, with higher scores indicating better psychological well-being.

3.3. Validity and Reliability

Construct validity and reliability were assessed following established guidelines for structural equation modeling. Initially, a confirmatory factor analysis (CFA) was performed to evaluate the measurement model and determine whether the observed indicators adequately represented their corresponding latent constructs. Model fit was assessed using several indices, including the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). According to widely accepted criteria, CFI and TLI values greater than 0.90, along with RMSEA and SRMR values below 0.08, indicated acceptable model fit (Hu and Bentler, 1999). Convergent validity was evaluated based on standardized factor loadings, composite reliability (CR), and average variance extracted (AVE). Acceptable standards were established with factor loadings exceeding 0.50, CR values above 0.70, and AVE values exceeding 0.50 (Hair et al., 2010). Discriminant validity was assessed using the Fornell–Larcker criterion, which compares the square root of the AVE for each construct with its correlations with other constructs. Discriminant validity was deemed adequate when the square root of the AVE surpassed the corresponding inter-construct correlations (Fornell and Larcker, 1981). Internal consistency reliability was evaluated with Cronbach's alpha coefficients, where values above 0.70 signified acceptable reliability (Cronbach, 1951). Additionally, to assess potential common method bias, Harman's single-factor test was conducted. The results showed that a single factor did not account for the majority of the variance, indicating that common method bias was not a significant concern in this study.

3.4. Data Analysis

Data analysis was conducted using IBM SPSS Statistics 26.0 and AMOS 26.0, following several stages. First, descriptive statistics and frequency analyses were performed to assess the general characteristics of the sample and the distribution of key variables. Means, standard deviations, skewness, and kurtosis were evaluated to determine the normality of the data. Next, reliability analyses were carried out using Cronbach's alpha coefficients to measure the internal consistency of each construct, with all constructs meeting the acceptable reliability threshold of 0.70. Subsequently, Pearson's correlation analysis was performed to explore the relationships among physical activity, social contact, emotional support, and psychological well-being. The results indicated significant correlations among the variables in the expected directions, validating the data's suitability for structural equation modeling. Following this, confirmatory factor analysis (CFA) was conducted to validate the measurement model and ensure that the latent constructs were adequately represented by their observed indicators. The structural model was then estimated to examine the hypothesized relationships among the variables, including both direct and indirect pathways to test the proposed mediation model. Finally, mediation effects were assessed using the bootstrapping method with 5,000 resamples, considering indirect effects statistically significant when the 95% bootstrap confidence intervals did not include zero, in line with established mediation analysis guidelines.

4. Results

4.1. Participants

The subjects of this study included a total of 10,097 participants. The characteristics of the study participants are presented in Table 1. In terms of gender distribution, women (60.0%) comprised a higher proportion than men (40.0%). The age group of 65–68 years represented the largest segment at 51.1%, while the 73–78 (24.2%) and 79 years and older (24.7%) age groups were at similar levels. In terms of residential area, the largest proportion of participants resided in the Gyeongsang region (30.2%), followed by Chungcheong-do (17.2%), Jeolla-do (15.9%), Gyeonggi-do (11.8%), and Seoul (10.4%), indicating a broad regional distribution across Korea.

Regarding marital status, those with a spouse constituted the majority at 58.7%, followed by widows/widowers at 37.0%, reflecting the characteristics of the elderly population. In terms of educational attainment, the highest proportion was among those who graduated from elementary school (33.4%), while middle school (23.5%) and high school (26.4%) graduates were relatively evenly distributed. Conversely, individuals with a university degree or higher represented a lower proportion.

As for subjective health status, the majority reported being 'healthy' (44.6%) or 'average' (30.9%), while 'poor' (16.4%) responses were also notable. Homeownership dominated the housing type at 79.7%. Regarding economic activity, the largest proportion reported having worked in the past but not currently (48.6%). The distribution of chronic diseases was as follows: 1 disease (29.3%), 2 diseases (27.4%), and 3 or more diseases (26.6%), indicating that many elderly individuals face complex health issues.

4.2. Measurement Model

As shown in Table 2, the measurement model demonstrated acceptable fit and adequate reliability and validity. All standardized factor loadings were statistically significant and exceeded acceptable thresholds (0.56–0.90), supporting convergent validity. Composite reliability (CR) values ranged from 0.68 to 0.91, and average variance extracted (AVE) values ranged from 0.42 to 0.71. Although the AVE for social contact was slightly below the conventional threshold of 0.50, its CR exceeded 0.60, indicating acceptable convergent validity based on established criteria. Cronbach’s alpha values ranged from 0.64 to 0.91, suggesting acceptable to high internal consistency across constructs. Overall, these results indicate that the measurement model demonstrates adequate reliability and validity for subsequent structural analysis.

4.3. Correlation

Descriptive statistics and correlation analyses were conducted prior to estimating the structural model. As shown in Table 3, physical activity was positively correlated with social contact (r = 0.148, p < 0.001) and psychological well-being (r = 0.127, p < 0.001). Social contact also exhibited a positive correlation with psychological well-being (r = 0.165, p < 0.001). In contrast, emotional support was negatively correlated with psychological well-being (r = −0.061, p <0.001). Additionally, emotional support was positively correlated with both physical activity (r = 0.108, p < 0.001) and social contact (r = 0.421, p < 0.001). Overall, the observed correlations were statistically significant and aligned with theoretical expectations, thereby supporting the appropriateness of the subsequent structural equation modeling.

4.4. Structural Model

The structural model was estimated to examine the direct and indirect relationships among physical activity, social contact, emotional support, and psychological well-being. The results indicated that the model fit the data well (χ² = 412.37, df = 84, CFI = 0.957, TLI = 0.944, RMSEA = 0.063, SRMR = 0.051). As hypothesized, physical activity had a significant positive effect on psychological well-being (β = 0.109, p < 0.001), suggesting that higher levels of engagement in physical activity are associated with better well-being outcomes among older adults. Additionally, physical activity was positively associated with both social contact (β = 0.135, p < 0.001) and emotional support (β = 0.111, p < 0.001). Regarding the effects of social relationships, social contact significantly positively influenced psychological well-being (β = 0.165, p < 0.001), indicating that more frequent social interactions contribute to improved well-being. In contrast, emotional support had a significant negative effect on psychological well-being (β = −0.061, p < 0.001), suggesting that higher levels of perceived emotional support are linked to lower levels of well-being. The model explained 5.2% of the variance in psychological well-being, 2.2% in social contact, and 1.2% in emotional support.

Table 4. Structural Paths.

Path	β	SE	t-value	p-value	Result
Physical Activity → Social Contact	0.135	0.012	14.25	<0.001	Supported
Physical Activity → Emotional Support	0.111	0.010	11.10	<0.001	Supported
Social Contact → Psychological Well-being	0.165	0.013	15.00	<0.001	Supported
Emotional Support → Psychological Well-being	−0.061	0.009	−5.00	<0.001	Supported
Physical Activity → Psychological Well-being	0.109	0.011	9.00	<0.001	Supported
Model fit: χ2 = 412.37, df = 84, CFI = 0.957, TLI = 0.944, RMSEA = 0.063, SRMR = 0.051

Table 4. Structural Paths.

Path	β	SE	t-value	p-value	Result
Physical Activity → Social Contact	0.135	0.012	14.25	<0.001	Supported
Physical Activity → Emotional Support	0.111	0.010	11.10	<0.001	Supported
Social Contact → Psychological Well-being	0.165	0.013	15.00	<0.001	Supported
Emotional Support → Psychological Well-being	−0.061	0.009	−5.00	<0.001	Supported
Physical Activity → Psychological Well-being	0.109	0.011	9.00	<0.001	Supported
Model fit: χ2 = 412.37, df = 84, CFI = 0.957, TLI = 0.944, RMSEA = 0.063, SRMR = 0.051

4.5. Mediation Effects

The mediating effects of social contact and emotional support were examined using bootstrapping with 5,000 resamples. Social contact exhibited a significant positive indirect effect on the relationship between physical activity and psychological well-being (indirect effect = 0.022, 95% CI [0.017, 0.027]). In contrast, emotional support showed a significant negative indirect effect (indirect effect = −0.007, 95% CI [−0.009, −0.004]). The total indirect effect was statistically significant (0.015, 95% CI [0.010, 0.021]), indicating partial mediation.

Table 5. Mediation Effects.

Path	Indirect Effect	Boot SE	95% CI (Lower)	95% CI (Upper)	Result
PA → SC → PWB	0.022	0.003	0.017	0.027	Significant
PA → ES → PWB	−0.007	0.002	−0.009	−0.004	Significant
Total Indirect Effect	0.015	0.003	0.010	0.021	Significant
Direct Effect	0.109	0.010	0.090	0.129	Significant
Total Effect	0.125	0.011	0.106	0.144	Significant

Table 5. Mediation Effects.

Path	Indirect Effect	Boot SE	95% CI (Lower)	95% CI (Upper)	Result
PA → SC → PWB	0.022	0.003	0.017	0.027	Significant
PA → ES → PWB	−0.007	0.002	−0.009	−0.004	Significant
Total Indirect Effect	0.015	0.003	0.010	0.021	Significant
Direct Effect	0.109	0.010	0.090	0.129	Significant
Total Effect	0.125	0.011	0.106	0.144	Significant

5. Discussion

The present study advances the understanding of the relationship between physical activity and psychological well-being by exploring the specific social mechanisms that mediate this influence in later life. While previous research has consistently shown a positive link between physical activity and well-being, most studies have treated social relationships as a single, unidimensional construct (Berkman & Glass, 2000; Holt-Lunstad et al., 2010). By differentiating between the structural and functional aspects of social relationships, this study provides a more nuanced perspective on how these mechanisms operate.

First, the results confirm that physical activity has a significant positive direct effect on psychological well-being, supporting Hypothesis 1 (H1). This finding aligns with a substantial body of research indicating that physical activity is associated with improved emotional functioning, reduced depressive symptoms, and increased life satisfaction (McAuley et al., 2000; Netz et al., 2005; Rejeski & Mihalko, 2001). Additionally, past studies have suggested that physical activity enhances psychological well-being by fostering self-efficacy and perceived competence (McAuley et al., 2006; Elavsky et al., 2005). The current findings further this literature by demonstrating that the positive effects of physical activity persist even when social mediators are considered, indicating that physical activity acts as an independent psychological resource rather than merely a context for social interaction. Although the explained variance in psychological well-being is relatively modest, this aligns with previous research showing that well-being is influenced by a variety of factors, including health status, socioeconomic conditions, and personality traits.

Second, the findings support H2, indicating that social contact positively mediates the relationship between physical activity and psychological well-being. This aligns with previous research emphasizing the role of social integration in promoting mental health (Berkman & Glass, 2000; Holt-Lunstad et al., 2010). For instance, Lindsay-Smith et al. (2017) found that group-based physical activity programs significantly enhance social connectedness among older adults, which contributes to improved psychological outcomes. Similarly, Levasseur et al. (2010) demonstrated a strong association between active participation in social and community activities and life satisfaction in later life. These results suggest that social contact serves as a key mechanism linking behavioral engagement to well-being. This study builds on this evidence by empirically demonstrating this pathway through structural equation modeling, confirming that social contact represents an active engagement pathway through which physical activity enhances well-being.

Third, and most importantly, the findings reveal that emotional support acts as a negative mediator, providing partial support for H3. While traditional social support theory posits that emotional support is beneficial (Cohen & Wills, 1985; Thoits, 2011), recent studies have uncovered more complex and sometimes negative associations. For example, Seeman et al. (2001) reported that higher levels of received support were linked to increased depressive symptoms among older adults, particularly when the support was perceived as unsolicited or excessive. Similarly, Newsom and Schulz (1996) found that support exchanges can undermine autonomy and self-esteem, leading to negative psychological outcomes. Rook (2015) further argued that social support can have both positive and negative effects depending on the context, such as the presence of conflict or dependency. These findings suggest that emotional support may reflect underlying vulnerability rather than serving as a purely beneficial resource. This conclusion should be interpreted cautiously, as emotional support may encompass both supportive interactions and indications of increased needs for support.

The coexistence of positive and negative mediation pathways underscores the need to differentiate between various dimensions of social relationships. Social contact indicates structural engagement and active participation, while emotional support reflects functional processes that may depend on individual needs and vulnerabilities (Umberson & Montez, 2010). This distinction clarifies the inconsistent findings in previous research, which shows that social relationships can have both positive and negative impacts on well-being (Rook, 2015; Shrout et al., 2006). This study addresses these inconsistencies by demonstrating that different dimensions of social relationships function through distinct, and sometimes conflicting, mechanisms. By integrating these dimensions into a dual-pathway framework, this research enhances the literature by providing a more comprehensive and theoretically sound model of social influences on well-being. Additionally, it is possible that measuring emotional support focuses on received rather than perceived support, which has been linked to greater vulnerability and dependency among older populations.

Finally, the findings should be interpreted within the Korean socio-cultural context. Previous research has shown that rapid demographic changes, including the weakening of traditional family support systems, have transformed social relationships among older adults in Korea (Lee & Choi, 2020; Lim & Putnam, 2010). In this context, emotional support may increasingly serve as a compensatory response to social and structural challenges rather than a stable source of well-being. This interpretation emphasizes the importance of considering cultural factors when examining the role of social relationships in later life. Policy efforts should prioritize opportunities for active social participation, such as community-based physical activity programs, instead of relying solely on support-based interventions.

6. Conclusion

This study examined how physical activity influences psychological well-being among older adults by focusing on the differentiated roles of social relationships. The findings demonstrate that physical activity contributes to well-being both directly and indirectly through distinct social mechanisms. In particular, the results support a dual-pathway model in which social contact functions as a positive pathway through active engagement and social integration, whereas emotional support operates as a negative pathway reflecting underlying vulnerability or compensatory processes.

By distinguishing between structural and functional dimensions of social relationships, this study advances the literature beyond conventional approaches and provides a more nuanced understanding of the mechanisms linking behavior and well-being. Overall, this study highlights the need to move beyond unidimensional perspectives on social relationships and provides a more nuanced framework for understanding well-being in later life. Policy efforts should prioritize opportunities for active social participation, such as community-based physical activity programs, rather than relying solely on support-based interventions.

7. Limitations and Future Research

This study has several limitations. First, its cross-sectional design restricts causal conclusions; future research should utilize longitudinal data to explore temporal relationships. Second, while widely used indicators were employed, the reliance on self-reported data for measuring physical activity may introduce bias. Third, the model's relatively low explanatory power indicates that additional factors, such as health status, socioeconomic conditions, and personality traits, should be considered in future studies. Nonetheless, this level of explained variance aligns with findings from population-based studies, which show that complex psychological outcomes are influenced by multiple determinants. Finally, the results are specific to the Korean context, highlighting the need for cross-cultural validation to enhance generalizability.