With the ongoing development and transformation of the global economy, the employment situation for college graduates around the world has become increasingly complex, and competition in the labor market is intensifying (Y. Li, 2024). The employability of college students has become a major concern for higher education institutions, society, and policymakers, as empirical studies and policy-oriented research have explicitly identified employability as a central goal of higher education systems (Abelha et al., 2020). Employability involves not only the mastery of professional skills but also a range of competencies such as adaptability to the workplace, problem-solving abilities, career decision-making skills, and self-efficacy (C. Li et al., 2024). Enhancing employability has become a key topic in educational reform, particularly through curriculum redesign, the integration of work-based learning, and the emphasis on transferable skills as core learning outcomes in higher education (Tao, 2022).

 

Among the factors influencing employability, the external resource of social support is widely regarded as playing a crucial role in alleviating psychological stress, boosting confidence, and enhancing self-efficacy (Kang et al., 2023). Existing research has indicated that social support has a significant positive impact on college students’ ability to cope with career pressures and improve employability (He & Yao, 2018; C. Li et al., 2022). For instance, family support provides both financial and emotional backing, school support offers career guidance and training, and peer support helps students share experiences and provides psychological encouragement (LeBouef & Dworkin, 2021; Roksa & Kinsley, 2019). As a result, the relationship between social support and employability has become a focal point in both academic and practical discussions.

 

Although research on this topic is abundant, there is still no consensus on the specific impact of social support on employability due to differences in sample size, research methods, and measurement tools (Okolie, 2022). Some studies have found that social support is positively associated with employability (F. Li et al., 2024; Xia et al., 2020), while others have suggested that this correlation is more limited or conditioned by self-efficacy (Chow et al., 2019; D. Wang et al., 2026). Therefore, the specific mechanisms and magnitude of how social support impacts college students’ employability warrant further investigation.

 

In light of these discrepancies, this study employed a meta-analytic approach to systematically integrate existing empirical research and quantify the overall effect of social support on employability (X. Li et al., 2024). In addition, we examined the moderating role of variables such as gender ratio, measurement tools of social support, and dimensions of employability. We intended for the findings to provide a reliable theoretical basis for the development of higher education and employment policies.

The concept of social support can be traced back to the 1950s, when psychologists began to examine the influence of social relationships on individual mental health, with Cobb (1976) proposing that social support could buffer stress and reduce the risk of psychological problems. The definition of social support has since become more specific and systematic, with scholars distinguishing among emotional, informational, and instrumental support types (Cui, 2023). At present, social support is generally defined as the emotional, informational, and material assistance provided by an individual’s social network—such as family, friends, colleagues, and community—when they are facing stress or difficulties (Chen et al., 2024).

 

Various instruments have been developed to measure social support, including the Multidimensional Perceived Social Support Scale (MPSSS; Zimet et al., 1988) and the Social Support Rating Scale (SSRS; Cauce et al., 1982). The MPSSS evaluates individuals’ subjective perceptions of social support, typically covering three dimensions: emotional, informational, and instrumental support (Gong et al., 2022). The SSRS provides a more comprehensive assessment of perceived support from family, friends, and other social networks (Jiang et al., 2022). In some cases, researchers have designed self-developed instruments tailored to specific research contexts or objectives (see, e.g., Yano et al., 2021).

Although many scholars have investigated graduate employability (e.g., Pérez Zúñiga et al., 2025), there is still no unified definition of employability in the context of higher education. A review of the literature suggests that employability is commonly defined as the overall capacity of students to adapt to and meet the demands of the labor market (M. Cheng et al., 2022). Specifically, employability encompasses not only professional skills but also problem-solving ability, communication skills, organizational and managerial competencies, career decision-making ability, and workplace adaptability (Shi & Ren, 2023).

 

Employability is typically measured through structured questionnaires and interviews. Common instruments include self-developed scales designed to capture specific aspects of employability based on research needs, and standardized scales such as the Employability Scale (Bennett & Ananthram, 2022), which assesses dimensions including job-seeking skills, social competence, and work motivation.

According to Bolton-King (2022) and G. Wang and Wang (2026), social support, as an external resource from family, peers, schools, and society, plays a crucial role in enhancing college students’ employability. When facing employment pressures and workplace competition, students benefit from social support in the form of psychological assistance, informational resources, and practical help, which collectively strengthen their employability. Beyond material and informational aid, social support also provides emotional encouragement, trust, and motivation, thereby fostering self-efficacy and job-search confidence. Consequently, the close association between social support and employability can be substantiated from both theoretical and empirical perspectives.

 

From a theoretical standpoint, social support can influence employability through both main-effect and buffering models. The main-effect model (Xia et al., 2020) posits that social support directly enhances psychological well-being, enabling individuals to maintain a positive outlook when facing employment challenges, which, in turn, improves employability. The buffering model suggests that social support mitigates the adverse effects of stress, helping individuals cope with employment-related pressures and reducing anxiety (Acoba, 2024). Empirical studies have further supported this relationship, reporting significant positive correlations between social support and employability. For instance, Kir et al. (2021) found a correlation coefficient of .604, whereas Alenezi et al. (2024) also confirmed a positive relationship but reported a much smaller coefficient of .114.

Studies have suggested that male and female students differ in both their need for and utilization of social support under employment stress (L. Cheng, 2020). In particular, women tend to rely more on emotional and peer support to cope with stress (Graves et al., 2021). Such support is particularly beneficial for building confidence and workplace adaptability, enabling women to perform better than men do on soft skills such as communication and teamwork (Asensio-Martínez et al., 2023). In contrast, men are more likely to seek informational and practical forms of support, such as career guidance or employment information, which more directly contribute to the development of professional skills and problem-solving abilities (Graves et al., 2021). Hence, gender differences may moderate the relationship between social support and employability.

 

According to Zimet et al. (1990), most scholars have adopted standardized scales to assess social support, while a smaller number used self-developed instruments. Standardized scales, such as the SSRS and MPSSS, have been widely applied to measure both subjective and objective aspects of social support (Zimet et al., 1988). The SSRS emphasizes objective support, including material and informational help from family and friends, making it particularly suitable for evaluating students who rely heavily on practical resources (Yue et al., 2021). The MPSSS focuses on individuals’ perceptions of support, highlighting emotional aspects that enhance self-efficacy and confidence, especially under employment pressure (Brugnoli et al., 2022). Self-developed instruments, on the other hand, often focus on family and university support dimensions (Bruno et al., 2024). Given their different emphases, the choice of measurement tools may be a potential source of heterogeneity in the relationship between social support and employability.

 

Employability is often conceptualized as a multidimensional construct, encompassing career decision making, communication, problem solving, teamwork, and other competencies (Tushar & Sooraksa, 2023). Research has suggested that social support may exert differential effects across these dimensions (Chow et al., 2019). According to Dacre Pool and Sewell (2007), when employability is measured using fewer dimensions—such as focusing only on career decision making or professional skills—the influence of social support tends to appear stronger, given the more direct link between these core skills and external support (e.g., family guidance, mentorship, or peer recommendations). However, when employability is operationalized across a broader range of dimensions, such as leadership, teamwork, or intercultural communication, the effect of social support may become diluted (Succi & Canovi, 2020). In such cases, its role in enhancing specific skills may be less pronounced, suggesting that an overly multidimensional measurement framework can obscure the direct effect of social support on employability.

This study selected Web of Science, Springer, the Education Resources Information Center, and Elsevier as the primary sources for English literature, while Chinese literature was sourced from China National Knowledge Infrastructure, Wei Pu (VIP), Wanfang, and Baidu Scholar. To ensure a comprehensive literature coverage, we  used the following keywords in both Chinese and English in the search: social support, family support, school support, peer support, and employability.

 

The criteria for literature selection were as follows: (a) focuses on the impact of social support on employability; (b) uses an empirical research method, not experimental or quasiexperimental; (c) reports sample size and correlation coefficients or values that can be converted into correlation coefficients (e.g., regression coefficients, path coefficients); (d) is published in either Chinese or English; and (e) participants are university students. We conducted further screening using the established keywords to search the literature (see Figure 1).

Through rigorous screening, we included 26 studies in the meta-analysis, of which 15 were published in Chinese and 11 in English. From these studies, we extracted 29 independent effect sizes, with a total sample size of 14,524.

 

We coded information from the 26 selected studies, including the authors, publication year, sample size, correlation coefficient, gender ratio of male and female participants, social support measurement tools, and employability measurement dimensions. If different effect sizes were reported within a single study, each effect size was coded separately. To ensure reliability and accuracy, two researchers independently performed the coding. The results were then compared, and through multiple discussions and adjustments it was determined that 98% of the information was consistent, indicating that the coding results had high reliability.

 

We used comprehensive meta-analysis software to calculate the overall effect size. Since Pearson correlation coefficients are not normally distributed, Fisher’s z transformation is typically applied before effect size aggregation to ensure that the effect size follows a normal distribution. The formula is as follows:

The transformed z values are then used with the weighted average method to calculate the summary effect size. The weighted average method is a statistical technique used to aggregate the effect sizes from multiple studies. The effect size (i.e., Fisher’s z value) of each study is categorized according to its weight, which is typically related to the sample size or other indicators, with larger sample sizes typically receiving higher weights.

Among them, z is the composite response, w_i is the weight of the i-th research, and z_i represents the cost of the i-th research to the composite z value. Finally, the obtained z value is transformed into the r value, as expressed by the following equation:

Publication bias refers to the phenomenon in academic research and publishing where studies with significant or positive results are more likely to be published than studies with nonsignificant or negative results (Egger et al., 1997). This bias can lead to incomplete results in meta-analyses, affecting the overall understanding of a particular topic or issue. Therefore, to ensure the comprehensiveness and accuracy of the research findings, a publication bias test should be conducted in meta-analyses to avoid overestimating effect sizes or drawing biased conclusions due to unpublished nonsignificant studies (Jeyaraj & Dwivedi, 2020). We used both funnel plot and fail-safe number methods to analyze publication bias in this meta-analysis.

As shown in Figure 2, the points on the funnel plot are symmetrically distributed around the combined effect size (the central vertical line), with most points concentrated at the top of the funnel. The fail-safe number value for the studies included in the meta-analysis is 7221, which is much greater than 155 (5 × 29 + 10), where 29 represents the number of effect sizes related to the relationship between social support and college students’ employability. Thus, these results suggested limited evidence of publication bias in the present meta-analysis.

In a meta-analysis, conducting a heterogeneity test is crucial to determine which effect model to use for the main effect test. If significant heterogeneity is detected, a random-effects model may be suitable, as it accounts for variability between studies. Generally, there are two methods for heterogeneity testing: the Q test and the I² test.

The I² value in Table 1 was well above 75%, indicating substantial heterogeneity. This suggests that the majority of the variability was due to heterogeneity between studies rather than random error. In addition, the test results showed that Q exceeded the degrees of freedom, indicating significant heterogeneity. In particular, the significance of the Q value further supported the differences between the study results. On the basis of these test results, we used a random-effects model in subsequent analyses to better reflect this heterogeneity.

 

Moreover, the results of the heterogeneity test provided a basis for determining whether moderation analysis was necessary. If heterogeneity is large, it is important to explore the potential factors that influence the differences in effect sizes. Consequently, this study further investigated the contextual factors that explained the inconsistent effect sizes for the same variable across different studies (i.e., a moderation analysis).

According to the results of the heterogeneity test in Table 1, we selected a random-effects model for the main effect calculation (Higgins et al., 2003). In this study, we chose the most commonly used effect size, the correlation coefficient r. The results are shown in Table 2.

According to the standards proposed by Cohen (2013), an effect size with an absolute value less than .30 indicates a weak effect, .30–.50 indicates a moderate effect, and greater than .50 indicates a strong effect. Therefore, according to Table 2, social support had a moderate positive effect on college students’ employability.

The results of the heterogeneity test indicated further moderation effect testing was required. There are two types of moderation effect test: Since gender ratio was a continuous variable, we conducted a meta-regression analysis, while the measurement tools for social support and the dimensions of college students’ employability were categorical variables, requiring subgroup analysis.

We conducted a meta-regression analysis using comprehensive meta-analysis software for the gender ratio as a moderating variable. The results are shown in Table 3 and the meta-regression plot is presented in Figure 3.

As shown in Table 3, gender ratio strengthened the relationship between social support and college students’ employability. The higher the gender ratio, the stronger the association between social support and employability.

The data points in the scatter plot exhibited some dispersion, but overall, there was an upward trend (see Figure 3). Despite the presence of some outliers, the distribution of the overall sample supported the conclusion drawn from the regression analysis. Therefore, we concluded that gender ratio played a moderate moderating role in the relationship between social support and college students’ employability.

We conducted a subgroup analysis using comprehensive meta-analysis software for the moderating variables of number of social support measurement tools and dimensions of the employability scale. The results are shown in Table 4.

The results in Table 4 indicate that different social support measurement tools had a significant impact on the relationship between social support and college students’ employability. In addition, the between-group effect size suggests there were significant differences in the relationship between social support and college students’ employability across different measurement tools. The relationship between social support and college students’ employability was the weakest in the SSRS group, indicating a low correlation. In contrast, in the self-developed scale group, the relationship was the strongest, indicating a moderate correlation.

 

Regarding the number of dimensions in the employability measures, the between-group effect size showed significant differences in the moderating effects of different employability measurement dimensions on the relationship between social support and college students’ employability. In particular, the group with three dimensions showed a strong correlation between social support and college students’ employability. In the other dimension groups, the relationship was moderate, with the largest effect size occurring in the group with five dimensions and the smallest effect size occurring in the group with eight dimensions.

This study systematically explored the impact of social support on college students’ employability through a meta-analysis of 26 studies published in Chinese or English. The results showed that social support had a significant positive effect on college students’ employability, and this relationship was influenced by moderating variables such as gender ratio, social support measurement tools, and employability measurement dimensions.

 

Social support had a moderate positive impact on college students’ employability. This finding is consistent with previous research (Noviati et al., 2024) suggesting that social support, especially that from family, school, and social networks, significantly enhances college students’ employability. In particular, college students who received more social support tended to cope better with the challenges of the job market, possessing stronger job-seeking skills and career adaptability. The main effect analysis revealed that the positive impact of social support was significant, indicating that higher education administrators should pay attention to building social support systems for college students.

 

This study further examined the moderating effect of gender ratio on the relationship between social support and employability. The regression analysis results showed that gender ratio played a significant moderating role in this relationship, such that the higher the gender ratio, the stronger was the positive impact of social support on employability. This finding suggests that gender differences may influence how college students receive and utilize social support resources. There may be different mechanisms for men and women in terms of social support acquisition and its role in enhancing employability, especially in the context of job market competition. Therefore, it is particularly important to consider the moderating role of gender differences when formulating policies and designing support systems.

 

The choice of measurement tools and dimensions also played a crucial role in revealing the relationship between social support and college students’ employability. This study found that the effect size was largest when using a self-developed scale, indicating that customized measurement tools may more accurately reflect the specific forms of social support, thereby better illustrating its impact on employability. In addition, the number of dimensions in the employability scale influenced the effect size. In the three-dimensional model, the impact of social support on employability was most significant, suggesting that in this structure social support is sufficiently differentiated to capture functional diversity, yet not overly fragmented to dilute its predictive power. Future research could further optimize measurement tools and dimensional settings to enhance the effectiveness and explanatory power of theoretical research.

From a theoretical perspective, our findings emphasize the important role of social support in enhancing college students’ employability and the relevance of moderating factors such as gender differences, measurement tools, and dimensions. The findings not only enrich the theoretical framework of social support and employability research but also provide new ideas for future research, especially in terms of in-depth discussions on gender differences and the adaptability of measurement tools.

 

From a practical perspective, the research results offer practical guidance for higher education administrators, policymakers, and career counselors. First, universities should build comprehensive social support networks to promote students’ career planning, psychological counseling, skills training, and other forms of support. In particular, colleges, schools, families, and society should closely cooperate to provide practical opportunities and career training to help students who are about to enter the job market enhance their employability. Second, personalized support based on gender differences is particularly important. Male and female students may have different needs in terms of acquiring and utilizing social support, so flexible employment support strategies should be designed based on these gender differences.

This study has certain limitations. First, we used solely existing cross-sectional studies for meta-analysis. Future research could further verify the long-term impact and causal relationship between social support and employability through experimental designs or longitudinal studies. Second, cultural differences may be an important factor influencing the effects of social support, and future research could consider cross-cultural comparisons to explore the mechanisms of social support in different cultural contexts. In addition, although gender differences were a key focus of this study, we did not explore the underlying social, cultural, or psychological factors. Future research could employ qualitative research methods to explore the specific mechanisms of gender in the relationship between social support and employability.

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