The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement

Xiangping Zhang; Wensheng Qian

doi:10.1371/journal.pone.0311597

. 2024 Dec 31;19(12):e0311597. doi: 10.1371/journal.pone.0311597

The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement

Xiangping Zhang ^1,², Wensheng Qian ^3,^*

Editor: Ehsan Namaziandost⁴

PMCID: PMC11687781 PMID: 39739649

Abstract

Purpose

While the impact of social support on academic performance is acknowledged, the specific mechanisms by which social support affects academic performance, particularly through self-efficacy and learning engagement, remain poorly understood. This study aims to examine the correlation between social support and academic achievement among Chinese middle school students, framed within the Social Cognitive Theory. It also seeks to explore the mediating roles of self-efficacy and learning engagement in this relationship.

Method

Data was collected from 265 individuals (mean age = 13.47 years, SD = 0.5) in four middle schools in Shandong Province, China in June 2023, using the simple random sample technique. Participants completed the questionnaires independently, and the data was analyzed using the structural equation model (SEM) in AMOS 24.0 and SPSS 24.0.

Results

Social support and academic performance have a direct and significant relationship with the SCT among middle school students. In addition, social support indirectly and positively affects academic performance through self-efficacy and learning engagement. The results also highlight self-efficacy as a key factor linking social support with academic performance.

Practical implications

This study offers valuable insights into the role of social support in Chinese middle school students’ academic achievement, particularly by examining the impact of self-efficacy and learning engagement. These valuable findings may guide policymakers in creating a supportive educational environment both inside and outside the classroom, enhancing adolescents’ self-confidence and engagement in learning.

Originality

This study contributes to the theoretical understanding of social support by investigating the mechanisms through which it impacts academic achievement. It clarifies the complex interactions among social support, self-efficacy, learning engagement, and academic achievement, with particular emphasis on the mediating roles of self-efficacy and learning engagement within the Chinese context.

Introduction

Within China’s compulsory education system, middle school serves as a crucial intermediary, bridging different levels of education. At this stage, academic performance is a significant indicator of students’ information acquisition and their potential for future studies. It is used to evaluate student progress, learning, and talent selection [1, 2]. In China, academic success is commonly assessed through exam scores in subjects such as Chinese, Math, and English [3, 4]. Nevertheless, this assessment approach presents challenges for middle school students in developing study routines, overcoming academic difficulties, and managing time and anxiety [5]. Learning is predominantly a cognitive endeavor that involves the acquisition of knowledge through various social activities [6]. Chinese students, however, have limited opportunities for social engagement, primarily confined to interactions within the classroom, on campus, and within their families. Social support refers to the resources obtained through social interactions, which reflect the degree of connection between an individual and their community. It serves as a defensive shield against negative emotions and stress [7, 8], providing a sense of being valued and supported by others when needed [9]. The concept has three dimensions: subjective support, objective support, and support usage [10]. Adolescents rely on certain social support to effectively manage stress, anxiety, and other psychological challenges that hinder their academic progress [11–13]. Prior studies have examined how social support affects adolescents’ learning behaviors, attitudes, motivation, and ultimately, academic performance [14, 15]. Academic performance generally refers to the grades, academic achievements, abilities, and learning outcomes demonstrated by students, assessed through various criteria [16, 17]. It has significant implications for different aspects of a student’s educational journey and prospects [18, 19]. In this study, academic performance specifically refers to students’ test scores in Chinese, English and Math.

Although previous researchers have examined the impact of social support on academic performance, less attention has been paid to the roles of self-efficacy and learning engagement. These two psychological constructs are closely related to academic performance [20]. Self-efficacy acts a crucial role in motivating individuals to achieve their goals, encouraging them to take risks, and reaching their academic outcomes [21, 22]. According to Liem et al. [23], students with higher levels of self-efficacy are more likely to participate actively in social activities and fully engage in deep learning. Moreover, students who possess a strong belief in their own academic capabilities are more inclined to feel motivated, persevere in the face of difficulties, and establish ambitious academic goals [24]. Learning engagement refers to the active participation of students in the educational process, which positively impacts on academic performance. Engaged students are typically more motivated, committed, and willing to invest the effort needed to participate in discussions, solve problems, and achieve academic success [25, 26]. These findings highlight the importance of considering self-efficacy and learning engagement when studying academic achievement. However, little attention has been paid to the influence of social support on the academic performance of Chinese middle school students. Furthermore, this study identifies a gap in understanding the precise mechanisms by which social support affects academic performance through self-efficacy and learning engagement, as outlined in relevant theoretical frameworks.

The Social Cognitive Theory (SCT), proposed by Bandura in 1986, serves as the theoretical framework for developing a chain mediation model in this study. According to this theory, human behavior is influenced by three variables: personal factors (e.g., self-efficacy), behavioral factors (e.g., learning engagement and achievement), and environmental factors (e.g., social support). Namely, individual behavior is shaped and moderated by the interaction of these personal, behavioral, and environmental elements [27]. Previous research has applied SCT to explore how personal cognitive and environmental factors influence academic performance among adolescents [28, 29]. However, less attention has been given to the interplay between social support, self-efficacy, learning engagement, and academic performance within the SCT framework. This study, therefore, aims to provide a comprehensive understanding of the combined influence of these four factors within the context of SCT.

This study adopts a broader approach by examining the interrelationships and mediating effects of social support, self-efficacy, learning engagement, and academic performance. Unlike previous research, which often focused on the impact of individual factors on academic performance, this study explores the combined effects of these variables. Its significance lies in bridging existing research gaps and enhancing our understanding of the factors that contribute to students’ academic success.

Literature review

Social support and academic performance

Relevant research has demonstrated that social support is a significant predictor of academic performance. Studies have found that social support can substantially boost individuals’ self-confidence [30], and motivation [31]. Also, researchers have shown that parental involvement and encouragement can increase students’ focus and motivation, leading to improved academic outcomes [32, 33]. In addition, a supportive family environment provides stability and emotional support, which helps students achieve higher academic grades [34]. Social support from peers is another crucial factor in influencing academic performance [35, 36]. For instance, Wentzel [37] noted that interactions with peers who exhibit positive learning attitudes and behaviors can stimulate students’ motivation and enhance their academic performance. Importantly, it has been revealed that social support from educators has a significant positive impact on academic performance [38]. Research suggests that individualized tutoring and additional assistance from teachers can address students’ specific learning needs and provide effective guidance, thereby promoting academic progress [39]. In sum, these findings underscore the critical role of social support in academic performance, highlighting that adolescents who receive support from parents, peers, and teachers are more likely to succeed in their academic pursuits. Based on this, we propose the following hypothesis:

H1: Social support is positively correlated with academic performance.

Self-efficacy as a mediator

Social support has been shown to play a crucial role in shaping self-efficacy beliefs. Research indicates that support from family, peers, and teachers can positively influence students’ self-efficacy [39–42]. For example, students who receive encouragement, guidance, and positive feedback from family members are more likely to develop a strong sense of self-efficacy in their academic abilities [43, 44]. Similarly, interactions with supportive peers and teachers who provide assistance and express confidence in students’ capabilities can further strengthen their self-efficacy beliefs [45, 46]. Moreover, self-efficacy is a significant factor in students’ academic achievement [47]. Students with higher self-efficacy are more likely to set ambitious goals, study diligently, and persist through unforeseen challenges. They are also more inclined to use effective learning strategies, seek help when needed, and overcome obstacles [48]. Conversely, students with low self-efficacy may doubt their abilities, experience increased anxiety, and achieve lower academic results [49]. Therefore, understanding the relationship between self-efficacy and academic achievement is critical for examining students’ academic success. Bai et al. [50] have suggested that self-efficacy mediates the relationship between social support and English learning performance among secondary students in Hong Kong. They argue that social support influences students’ self-efficacy beliefs, which, in turn, affect their academic performance. Based on the literature reviewed, the following hypothesis is proposed:

H2: Self-efficacy mediates the relationship between social support and academic performance.

Learning engagement as a mediator

Learning engagement is significantly influenced by social support. Mishra has put forth the notion that students’ learning engagement can be potentially enhanced by social support in the learning process [51]. For example, both academic and emotional support from peers can greatly contribute to students’ learning engagement [52]. Wong et al. [53] have asserted that teacher support can effectively stimulate students’ interest, enjoyment, dedication, investment of time, effort, emotions, and learning strategies. Additionally, Shao and Kang [41] have suggested that parental support can influence adolescents’ level of involvement in their learning endeavors.

Meanwhile, learning engagement is considered to be an important factor that affects students’ academic performance. High levels of learning engagement allow students to dedicate more time to learning activities, leading to better academic outcomes [54–56]. Classroom engagement, in particular, has been shown to have a significant impact on academic achievement [39]. Therefore, this study proposes that learning engagement may serve as a mediator between social support and academic achievement.

Self-efficacy is also believed to play a key role in increasing student involvement in learning activities [57, 58]. Students with high levels of self-efficacy are more likely to establish ambitious objectives and actively participate in learning activities [59, 60]. According to the SCT, the surrounding environment can impact personal cognition (e.g. self-efficacy) and behavior (e.g. learning engagement, academic performance). When social support is strengthened, adolescents may improve their self-efficacy, leading to better engagement in learning and, ultimately, better academic outcomes. Thus, we hypothesize that social support may influence academic performance through the sequential mediation of self-efficacy and learning engagement. The following hypotheses are derived:

H3: Self-efficacy mediates the relationship between social support and adolescents’ academic performance.
H4: Self-efficacy and learning engagement play a chain mediating role in the association between social support and adolescents’ academic achievement.

Under the guidance of the above hypotheses and Social Cognitive Theory (SCT), a theoretical model was developed to investigate the relationship between social support and adolescents’ academic performance, as well as the mediating roles of self-efficacy and learning engagement (Fig 1).

Materials and methods

Sampling and data collection

Before commencing the research, ethical considerations were prioritized. The Institutional Review Board (IRB) at Qufu Normal University carefully reviewed and approved the research procedures, ensuring that the rights and welfare of all participants were upheld. Informed consent was obtained from both students and their parents prior to participation in the survey. Additionally, consent was secured from the headmasters of the sampled schools.

The study employed a simple random sampling method to recruit Chinese middle school students who voluntarily participated in the questionnaire collection. Data was collected from June 1 to June 30, 2023. First, a structured questionnaire was administered to students during regular school hours in a classroom setting. The researchers provided clear instructions and addressed any questions or concerns from the participants. Students were encouraged to respond honestly, with the assurance of confidentiality regarding their responses. Second, the study included the collection of students’ academic performance data. Academic performance was measured using scores from the final exams in Chinese, Math, and English subjects. To ensure comparability and facilitate analysis across different subjects, the overall scores, ranging from 0 to 120, were standardized. These standardized scores were used as observed variables to measure academic achievement in the study.

A proper sample size, at least ten times the total number of observed variables, was required based on the recommendations for Structural Equation Modeling (SEM) [61]. We distributed 300 survey forms to participants aged 13–15 from four middle schools in Shandong Province, China. A total of 265 completed survey forms were received (92.6% response rate), with 14 surveys (4.7%) rejected due to incomplete records and missing answers. The selection of these four middle schools was based on their willingness to participate. Additionally, these schools are representative of diverse socioeconomic backgrounds, including a mix of urban and rural locations, varied student populations, and diverse academic performance levels. This ensured a balanced representation of both genders and different grade levels within the specified age range.

Sample characteristics

The sample consisted of 265 participants from four middle schools in eastern China. The average age of the participants was 13.71 years (SD = 0.5, range = 13–14 years). As shown in Table 2, there were 128 female students (48.3%) and 137 male students (51.7%). The sample included 93 first-year students (35.1%), 91 second-year students (34.3%), and 81 third-year students (30.6%). Regarding residence, 137 families (51.7%) lived in urban areas, while 128 families (48.3%) lived in rural areas. Concerning parental education, 159 fathers (60%) and 192 mothers (72.5%) had completed junior high school or less. Seventy-seven fathers (29.1%) and 51 mothers (19.2%) had received education at the high school or technical school level. Additionally, 17 fathers (6.4%) and 12 mothers (4.5%) had received education at the college level, while 12 fathers (4.5%) and 10 mothers (3.8%) had received education at the undergraduate level or above. In terms of monthly income, 52 families (19.6%) had an income below 3,000 yuan, 124 families (46.8%) had an income between 3,000 and 5,000 yuan, 68 families (25.7%) had an income between 5,000 and 10,000 yuan, and 21 families (7.9%) had an income above 10,000 yuan. Overall, the sample in this study is representative of the target population, as it closely matches the demographic features and distribution observed in the region.

Table 2. Reliability and validity.

Latent variable	Item	UC	SE	Z-value	P-value	SC	Cronbach’s a	CR	AVE
Social support (SS)	SS 1	1.000				0.767
	SS 2	0.890	0.079	11.272	^***	0.689
	SS 3	0.941	0.079	11.885	^***	0.722	0.876	0.880	0.596
	SS4	1.087	0.083	13.093	^***	0.787
	SS 5	1.115	0.076	14.709	^***	0.880
Self-efficacy (SE)	SE 1	1.000				0.755
	SE 2	1.072	0.082	13.038	^***	0.791
	SE 3	1.160	0.083	13.945	^***	0.842	0.892	0.895	0.633
	SE4	1.152	0.080	14.378	^***	0.867
	SE5	1.047	0.090	11.594	^***	0.712
Learning engagement (LE)	LE1	1.000				0.734
	LE2	0.905	0.077	11.809	^***	0.756
	LE3	1.013	0.086	11.843	^***	0.758	0.878	0.880	0.595
	LE4	1.068	0.081	13.259	^***	0.854
	LE5	0.960	0.082	11.701	^***	0.749

Open in a new tab

UC = Unstandardized Coefficients; SE = standard error; SC = standardized coefficients

***p < 0.001.

Questionnaire design

The questionnaire employed in the study was based on well-established tools that have been demonstrated to be reliable and valid. It consisted of two primary sections. The first section gathered demographic data such as gender, grade level, place of residence, and parental education level. This information was crucial for describing the sample and providing context for the analysis. The second section contained 15 items, carefully selected from validated and pre-existing scales measuring social support, self-efficacy, and learning engagement. Each item was chosen based on its relevance to the study’s objectives and its proven utility in previous research. Five items for assessing social support were derived from Ye and Dai’s Social Support Scale [10], chosen for their relevance to assessing perceived levels of social support among participants. Three items measuring self-efficacy were obtained from Schwarzer’s study [62], selected for their ability to capture participants’ beliefs in their academic abilities. Five items evaluating learning engagement were selected from Fang et al.’s Learning Engagement Scale [63], with adjustments made according to the Utrecht Work Engagement Scale-Student [64]. These items were chosen to assess participants’ levels of involvement, interest, and emotional connection to the learning process. All 15 items were scored on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). This scale allowed participants to rate their agreement with each statement. Specific details on the measurement items can be found in Table 1.

Table 1. Potential variables and measurement items.

Potential variable	Code	Measurement items	References
Social support (SS)	SS1	Most of my classmates care about me.	Ye and Dai (2008)
	SS 2	I can often count on the care and support of my classmates, friends, parents, and others.
	SS 3	I am surrounded by people who are close and can give me support and help.
	SS 4	Teachers, classmates, friends, family, etc. are there for me when I have problems.
	SS5	I often get emotional help and support from my classmates and friends.
Self-efficacy (SE)	SE1	If I do my best, I can always solve problems.	Fang et al. (2008)
	SE2	It is simple for me to pursue my dreams and achieve my objectives.
	SE3	I can face difficulties calmly because I am confident in my ability to deal with them.
	SE4	When there is a problem, I usually come up with solutions.
	SE5	Whatever happens to me, I can handle it.
Learning engagement (LE)	LE1	As soon as I wake up in the morning, I’m happy to study.	Schaufeli (2002)
	LE2	I find learning purposeful and rewarding.
	LE3	I am passionate about my learning.
	LE4	I am proud of my learning.
	LE5	I find learning challenging.

Open in a new tab

Statistical analysis

Data were analyzed using Amos 24.0 and SPSS 24.0. First, the Harman single-factor test was conducted to assess the potential for common method bias. Descriptive analysis was then employed to appropriately reflect the characteristics of the sample. Subsequently, structural equation modeling (SEM) was used to evaluate both the measurement and structural models. The measurement model was validated through confirmatory factor analysis, while the structural model was examined using goodness-of-fit indices and path coefficients. Finally, the significance of mediating effects was assessed using the bootstrapping method.

Results

Common method variance

A Harman single-factor test was conducted to assess the potential impact of common method variance. This analysis involved performing an exploratory factor analysis on all items from the three scales using an unrotated principal component analysis approach. The results indicated that three components had eigenvalues greater than one, with the first factor accounting for 23.704% of the total variance. This percentage falls short of the critical threshold of 50% [65]. As a result, we may infer that there is no significant common method bias in this study.

Measurement model

The measurement model provides a framework for analyzing the links between the observed indicators and the underlying components [61]. In this analysis, it is essential to evaluate both reliability and validity. Reliability is commonly assessed using Cronbach’s alpha coefficient, with values ranging from 0.80 to 0.89 considered satisfactory. Convergent validity is measured using indicators such as average variance extracted (AVE), standardized component loadings, and composite reliability (CR), with a threshold of 0.50 or higher deemed appropriate [66]. Discriminant validity is established by examining the correlations among various constructs and comparing these correlations to the square root of the AVE for each construct. If the correlations between constructs are less than the square root of the AVE for each construct, this indicates that the assessment items measure distinct constructs and demonstrate discriminant validity [67].

The reliability and convergent validity analysis results are presented in Table 2. Cronbach’s alpha coefficients ranged from 0.876 to 0.892, indicating that the measurement model is highly reliable. Additionally, standardized factor loadings varied from 0.689 to 0.880, reflecting strong convergent validity. The composite reliability (CR) and average variance extracted (AVE) values ranged from 0.880 to 0.895 and from 0.595 to 0.633, respectively, indicating good convergent validity. Table 3 shows that the AVE values for each variable exceeded the squared correlation coefficients in the corresponding rows and columns. This finding confirms that the measurement items in this study exhibit robust reliability and convergent validity. To validate discriminant validity, this study employed the Heterotrait-Monotrait (HTMT) criterion. According to Kline [68], and Henseler et al. [69], an acceptable HTMT value should remain below 0.85. Table 4 indicates that discriminant validity was achieved. Table 5 shows that the path coefficient value R² shows that only 14.1% of the total variance was explained by social support, learning engagement and academic performance. Furthermore, R² shows that 25.9% and 47.4% of the total variance in learning engagement and academic performance were explained by social support.

Table 3. Discriminate validity examination.

Potential variable	Social support	Self-efficacy	Learning engagement
Social support	0.772
Self-efficacy	0.374***	0.795
Learning engagement	0.481***	0.333***	0.771

Open in a new tab

Note: The diagonal shows the square root of the AVE of four latent constructs, whereas the diagonal below shows the correlation coefficient.

Table 4. Heterotrait-Monotrait ration (HTMT).

Potential variable	Social support	Self-efficacy
Social support
Self-efficacy	0.403
Learning engagement	0.508	0.326

Open in a new tab

Table 5. Coefficient of determination R2 variance inflation factor.

Constructs	R²	VIF
Self-efficacy	0.141	1.353
Learning engagement	0.259	1.249
Academic performance	0.474	1.537

Open in a new tab

Structural model

The study utilized the maximum likelihood estimation method in AMOS 24.0 software to examine the model. The fit indices for the data and model are as follows: χ2 = 194.930, df = 129, χ2/df = 1.511, GFI = 0.927, AGFI = 0.903, IFI = 0.977, TLI = 0.972, CFI = 0.976, RFI = 0.922, NFI = 0.934, SRMR = 0.0434, and RMSEA = 0.044. All the values met the recommended thresholds [61], indicating a good fit for the structural model. Furthermore, sensitivity analysis revealed an effect size of 0.39, meeting Cohen’s threshold for a strong statistical test with a sample size of 265 [70].

Fig 2 shows the structural model’s standardized parameter estimates, which include explanatory variance and path coefficients. The study found that the social support construct explains 14% of the variance in self-efficacy, with a standardized regression value of 0.441 (P < 0.001). The social support and self-efficacy constructs together explain 26% of the variance in the learning engagement construct, with standardized regression coefficients of 0.424 (P < 0.001) and 0.155 (P < 0.01, respectively). The social support, self-efficacy, and learning engagement variables had a significant impact on academic achievement, accounting for 47% of the variation (standardized regression coefficients of 0.298 (P < 0.001), 0.292 (P < 0.001), and 0.218 (P < 0.001). These empirical findings provide substantial support for the proposed structural model.

Analyzing the mediation of social support on academic performance

This study used the Bootstrap technique to look into the function of self-efficacy and learning engagement as mediators in the connection between social support and academic performance. Following Hayes’ recommendation [71], a bootstrap sample size of 2000 was set, with a confidence level of 95%. A mediating effect is considered statistically significant when the Bias-Corrected and Percentile methods’ confidence intervals, at a 95% confidence level, do not include zero [72]. Data analysis was performed using Amos 24.0 software. In this analysis, academic performance was treated as the dependent variable, while social support was considered the independent variable. Additionally, self-efficacy and learning engagement were regarded as mediating variables. Table 6 displays the findings of the mediation study, which identified self-efficacy and learning engagement as mediators of the association between social support and academic performance.

Table 6. Total, direct, and indirect effects of the theoretical model.

Path relationship		Point estimate	Product of coefficient		Bootstrapping
			Product of coefficient		Bias-corrected 95% CI		Percentile 95% CI
			SE	Z-value	Lower	upper	lower	upper
Test of indirect, direct and total effects
DistalIE	SS→SE→LE→AP	0.015	0.008	1.875	0.005	0.038	0.003	0.032
LMIE	SS→SE→AP	0.129	0.034	3.794	0.072	0.205	0.068	0.199
LEIE	SS→LE→AP	0.092	0.031	2.968	0.042	0.171	0.036	0.158
TIE	Total indirect effect	0.236	0.051	4.627	0.154	0.358	0.142	0.345
DE	SS→AP	0.298	0.075	3.973	0.152	0.440	0.153	0.441
TE	total effect	0.534	0.070	7.629	0.394	0.673	0.393	0.672
Percentage of indirect effects
P1	DistalIE/TIE	0.063	0.028	2.250	0.021	0.134	0.014	0.124
P2	SEIE/TIE	0.546	0.105	5.200	0.359	0.763	0.360	0.766
P3	LEIE/TIE	0.391	0.098	3.990	0.188	0.577	0.188	0.577
P4	TIE/TE	0.442	0.099	4.465	0.288	0.685	0.272	0.656
P5	DE/TE	0.558	0.099	5.636	0.315	0.712	0.344	0.728

Open in a new tab

Note: SS = Social Support, SE = Self-efficacy, LE = Learning Engagement, AP = academic Performance, IE = Indirect effect, TIE = Total Indirect Effect, DE = Direct Effect, TE = Total Effect, DIE = Distal Indirect Effect

At a 95% confidence level, the Bias-Corrected and Percentile methods’ confidence intervals do not include zero, indicating that social support has a significant total effect (bias-corrected CI [0.394, 0.673], percentile CI [0.393, 0.672], P < 0.01) and a significant direct effect (bias-corrected CI [0.152, 0.440], percentile CI [0.153, 0.441], P < 0.01) on academic performance. Furthermore, the analysis revealed significant indirect effects in three pathways. The indirect effect of social support→self-efficacy→learning engagement→academic performance was 0.015 (95% bias-corrected CI [0.005, 0.038], percentile CI [0.003, 0.032], P<0.01). The indirect effect of social support→self-efficacy→academic performance was 0.129 (95% bias-corrected CI [0.072, 0.205], percentile CI [0.068, 0.199], P<0.01). Lastly, the pathway of social support→learning engagement→academic performance had an indirect effect of 0.092 (95% bias-corrected CI [0.042, 0.171], percentile CI [0.036, 0.158], P<0.01). The results indicate that the three mediating effects were all statistically significant, providing support for H2, H3, and H4. Moreover, the direct effect accounted for 55.8% of the total effect, while the three indirect effects collectively accounted for 44.2% of the total effect. Notably, among the three indirect effects, the pathway “social support → self-efficacy → academic performance” exhibited the strongest effect.

Discussion

According to SCT, the present study looked into the link between social support, self-efficacy, learning engagement, and academic performance among adolescents. To understand the mechanism through which social support affects academic performance, the study sought to investigate the potential mediating effects of self-efficacy and learning engagement in the relationship between social support and academic performance in the exam-oriented education setting. The study’s findings are presented below.

Direct effects analysis

Our results indicate that social support has a positive and direct impact on adolescents’ academic performance. This finding is consistent with previous studies conducted by Song et al. and Jacobson and Burdsal [31, 73]. Besides, Gallardo et al. [74] hypothesized a positive correlation between social support and academic performance among middle school students. Escalante et al. [75] further reinforced this hypothesis by demonstrating that academic performance is influenced by school climate, with social support being the dominant factor. This study confirms these findings by emphasizing the positive role of social support in adolescents’ academic performance. One possible explanation for this effect is that Chinese adolescents, facing intense competition and learning pressures, may better manage the evaluation of threatening situations and boost their self-confidence when they receive timely social support. This support can encourage them to persist in overcoming learning challenges [76]. Another explanation is that adolescents who perceive social support may experience increased feelings of security and hope in their learning environment, which in turn motivates them to engage more actively in the learning process, thereby contributing to improved academic performance [77]. This study further validates social support as a predictive factor for academic performance.

Indirect effects analysis

The study found that self-efficacy partially mediates the relationship between social support and academic performance among Chinese adolescents. In accordance with Social Cognitive Theory (SCT), this finding underscores the crucial role of self-efficacy as a mediator in the pathway from social support to academic performance, consistent with prior research [78]. Under the intense pressure of examinations, Chinese middle school students who receive greater social support from peers, teachers, and parents are likely to develop the self-efficacy needed to succeed in tests and to estimate the effort required to reach their academic goals [79]. Moreover, improved relationships with parents, teachers, and classmates can reduce student stress, enhance problem-solving skills, and promote positive, self-directed behavioral patterns [80]. Adolescents who experience these benefits in their learning behaviors show higher levels of self-efficacy, which subsequently boosts their academic success. By highlighting its significant mediating role, the findings of this study further validate the importance of self-efficacy in achieving academic excellence [38]. This evidence reinforces the substantial mediating effect that self-efficacy has on the relationship between social support and academic achievement among adolescents.

The results of the study demonstrated that learning engagement also partially mediated the association between social support and academic performance among adolescents. This suggests that high levels of learning engagement may clarify why middle school students cultivate positive social factors, such as interaction with peers, teachers, and parents, to enhance their academic performance. Students who receive positive social support are more likely to engage actively in their studies, as evidenced by their eagerness to complete tasks, participation in class, and proactive pursuit of new learning opportunities, ultimately leading to improved academic outcomes [81]. Moreover, establishing connections with positive social factors fosters a supportive environment, increases adolescents’ engagement in learning, and enhances academic performance [82, 83]. These findings align with previous studies [52, 84, 85], which posit that learning engagement is a key factor linking social support and adolescents’ academic achievement.

Chain mediator effect

One of the most unexpected findings of the study was the revelation that learning engagement and self-efficacy functioned as a chain mediator in the relationship between social support and academic performance. This result aligns with Bandura’s Social Cognitive Theory (SCT), illustrating how supportive relationships and nurturing interactions with peers, parents, and educators create a positive environment conducive to the development of adolescents’ self-efficacy [78]. This self-efficacy, in turn, influences their level of engagement in learning, which leads to better academic performance. Furthermore, the study revealed that adolescents’ self-efficacy had a lesser impact on their level of learning engagement (β = 0.17, P < 0.001) compared to the influence of social support (β = 0.41, P < 0.001). This suggests that the primary source of learning engagement among adolescents is social support. Interaction with peers, teachers, parents, and others provides a supportive learning environment that enhances students’ self-efficacy in participating in educational activities [43].

Conclusion

The study aimed to examine the relationship between social support and academic performance within the context of China’s test-based culture. The current findings indicate that adolescents’ academic performance is positively and directly influenced by social support. Also, learning engagement and self-efficacy function as chain mediators in the association between social support and academic performance. The relationship and effects of these various variables are further elucidated through the lens of Social Cognitive Theory (SCT). As demonstrated by previous research, this article is distinctive and offers new insights into the roles of social support, self-efficacy, learning engagement, and academic performance within the particular academic climate of China.

Theoretical implication

This study contributes to the existing theoretical knowledge by underscoring the influence of social support on the academic performance of middle school students within the framework of Social Cognitive Theory. It supports the notion that social support plays a significant role in academic achievement by elucidating the complex interactions among social support, self-efficacy, learning engagement, and academic performance. Furthermore, this research builds on previous empirical studies that have established a link between social support and academic performance. By confirming these findings within the context of the Chinese compulsory education system and emphasizing the mediating roles of self-efficacy and learning engagement, this study enhances the theoretical understanding of the relationship between social support and academic achievement among middle school students in China.

Practical implication

Regarding the practical implications, it is essential for educational practitioners to understand how to enhance students’ academic achievement by considering social factors such as the roles of teachers, parents, and peers. To strengthen social support, teachers should create an inclusive and cohesive classroom environment that fosters respect, understanding, and collaboration among students. This can be accomplished through initiatives like peer mentorship programs and collaborative learning activities. Parents also play a vital role in establishing a conducive learning environment at home. They can do this by promoting a focused atmosphere, designating a dedicated study area, and minimizing external distractions. To enhance self-efficacy, it is important for both teachers and parents to encourage students to participate in problem-solving activities that relate to real-life situations. Additionally, they should motivate adolescents to embrace challenges and seek solutions, thereby helping them develop confidence in their abilities [86]. Furthermore, it is essential for educators and guardians to provide timely and constructive feedback that allows students to monitor their learning progress and adjust their approaches accordingly. This kind of feedback can significantly enhance students’ self-efficacy and belief in their own abilities. In terms of learning engagement, it is important for teachers, parents, and other social variables to collaborate in order to develop a comprehensive understanding of adolescents’ needs. By employing effective strategies and techniques, they can foster greater involvement in learning through meaningful and practical activities. This coordinated effort will not only engage students more deeply but also support their overall academic development.

Limitations and further research

There are several limitations to acknowledge in this study. First, the use of a cross-sectional design restricts the ability to establish causal relationships between the examined factors. Therefore, longitudinal research is required to bridge a definitive link between social support and academic performance over time. Second, the study was conducted within China’s test-oriented learning environment, which may limit the applicability of the findings to other educational contexts. To strengthen the study’s external validity, subsequent research should be undertaken in multiple countries and diverse educational settings. Other relevant factors, such as academic flow, academic resilience, and learning motivation, were not considered in this study. Future investigations should incorporate these elements into a more comprehensive theoretical framework to provide an insightful view of the dynamics involved.

Supporting information

S1 Data

(XLSX)

pone.0311597.s001.xlsx^{(43.6KB, xlsx)}

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

References

1.Zhao X, Selman R, Haste H. Academic stress in Chinese schools and a proposed preventive intervention program. Cogent Education. 2015; 2(1):1000477. 10.1080/2331186x.2014.1000477 [Google Scholar]
2.Zeb A, Ullah R, Karim R. Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations. The International Journal of Information and Learning Technology. 2024; 41(1):99–111. 10.1108/ijilt-04-2023-0046 [Google Scholar]
3.Chen J, Huebner ES, Tian L. Longitudinal relations between hope and academic achievement in elementary school students: Behavioral engagement as a mediator. Learning and Individual Differences. 2020; 78:101824. 10.1016/j.lindif.2020.101824 [Google Scholar]
4.Xu Z, Qi C. The Relationship between Teacher-student Relationship and Academic Achievement: The Mediating Role of Self-efficacy. EURASIA J Math Sci Tech Ed. 2019;15(10):em1758. 10.29333/ejmste/105610 [Google Scholar]
5.Zhang X, Gu T. Analysis of factors influencing secondary school students’ academic stress—Taking Changzhou junior high school education as an example. Science and Education Magazine.2017; 24:184–186. 10.16400/j.cnki.kjdkx.2017.08.088 [Google Scholar]
6.Rehman FU, Ismail H, Al Ghazali B M, Asad MM, Shahbaz MS, Zeb A. Knowledge management process, knowledge based innovation: Does academic researcher’s productivity mediate during the pandemic of covid-19?. Plos one. 2021;16(12):e0261573. 10.1371/journal.pone.0261573 doi: 10.1371/journal.pone.0261573 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Malecki CK, Demaray MK. Social support as a buffer in the relationship between socioeconomic status and academic performance. School Psychology Quarterly. 2006; 21(4):375. 10.1037/h0084129 [Google Scholar]
8.Wright MF, Wachs S. The buffering effect of parent social support in the longitudinal associations between cyber poly victimization and academic outcomes. Social Psychology of Education. 2021; 24:1145–1161. 10.1007/s11218-021-09647-6 [Google Scholar]
9.Cutrona CE, Russell DW. The provisions of social relationships and adaptation to stress. In Perlma D., Russell W J.(Eds.), Advances in personal relationships. Greenwich, CT: JAI Press Inc; 1987. [Google Scholar]
10.Ye Y, Dai X. Development of a social support rating scale for college students. Chinese Journal of Clinical Psychology. 2008; 16(5): 456–458. [Google Scholar]
11.Richman JM, Rosenfeld LB, Bowen GL. Social support for adolescents at risk of school failure. Social work. 1998; 43(4):309–323. 10.1093/sw/43.4.309 doi: 10.1093/sw/43.4.309 [DOI] [PubMed] [Google Scholar]
12.Roksa J, Kinsley P. The role of family support in facilitating academic success of low-income students. Research in Higher Education. 2019; 60:415–436. 10.1007/s11162-018-9517-z [Google Scholar]
13.Cao C, Zhu C, Meng Q. Chinese international students’ co** strategies, social support resources in response to academic stressors: Does heritage culture or host context matter?. Current Psychology. 2021; 40:242–252. 10.1007/s12144-018-9929-0 [Google Scholar]
14.Ahmed W, Minnaert A, van der Werf G, Kuyper H. Perceived social support and early adolescent achievement: The mediational roles of motivational beliefs and emotions. Journal of Youth Adolescence. 2010; 39:36–46. 10.1007/s10964-008-9367-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Sahil SAS, Hashim RA. The roles of social support in promoting adolescents’ classroom cognitive engagement through academic self-efficacy. Malaysian Journal of Learning and Instruction. 2022; 8: 49–69. 10.32890/mjli.8.2011.7626 [Google Scholar]
16.Wang M, Deng X, Du X. Harsh parenting and academic achievement in Chinese adolescents: Potential mediating roles of effortful control and classroom engagement. Journal of school psychology. 2018; 67:16–30. 10.1016/j.jsp.2017.09.002 doi: 10.1016/j.jsp.2017.09.002 [DOI] [PubMed] [Google Scholar]
17.Corcoran RP, Cheung A, Kim E, Xie C. Effective Universal school-based social and emotional learning programs for improving academic achievement: A systematic review and meta-analysis of 50 years of research. Educational Research Review. 2017; 25:56–72. 10.1016/j.edurev.2017.12.001 [Google Scholar]
18.Goegan LD, Daniels LM. Academic success for students in postsecondary education: The role of student characteristics and integration. Journal of College Student Retention: Research, Theory & Practice. 2021; 23(3):659–685. 10.1177/1521025119866689 [Google Scholar]
19.Kumar S, Agarwal M, Agarwal N. Defining and measuring academic performance of Hei students-a critical review. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 2021; 12(6):3091–3105. 10.17762/turcomat.v12i6.6952 [Google Scholar]
20.Dogan U. Student Engagement, Academic Self-efficacy, and Academic Motivation as Predictors of academic achievement. The Anthropologist. 2015; 20(3):553–561. 10.1080/09720073.2015.11891759 [Google Scholar]
21.Turner JC, Midgley C, Meyer DK, Gheen M, Anderman EM, Kang Y, et al. The classroom environment and students’ reports of avoidance strategies in mathematics: A multimethod study. Journal of Educational Psychology. 2022; 94: 88–106. 10.1037/0022-0663.94.1.88 [Google Scholar]
22.Rehman FU, Zeb A. Investigating the nexus between authentic leadership, employees’ green creativity, and psychological environment: evidence from emerging economy. Environmental Science and Pollution Research. 2023; 30(49):107746–107758. 10.1007/s11356-023-29928-1 doi: 10.1007/s11356-023-29928-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Liem AD, Lau S, Nie Y. The role of self-efficacy, task value, and achievement goals in predicting learning strategies, task disengagement, peer relationship, and achievement outcome. Contemporary Educational Psychology. 2008; 33: 486–512. 10.1016/j.cedpsych.2007.08.001 [Google Scholar]
24.Schunk DH, Mullen CA. Self-efficacy as an engaged learner. In Handbook of research on student engagement:219–235. Boston, MA: Springer US; 2012. 10.1007/978-1-4614-2018-7_10 [Google Scholar]
25.Wang MT, Eccles JS. School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction. 2013; 28:12–23. 10.1016/j.learninstruc.2013.04.002 [Google Scholar]
26.Fredricks JA, Blumenfeld PC, Paris AH. School engagement: Potential of the concept, state of the evidence. Review of educational research. 2004; 74(1):59–109. 10.3102/00346543074001059 [Google Scholar]
27.Bandura A. Social cognitive theory, in Handbook of Theories of Social Psychology. 2012; Vol. 1, eds Van Lange P. M., Kruglanski A. W. and E. Higgins; 2012:349–373. [Google Scholar]
28.O’Hare K, White N, Harding R, Galland B, Sellbom M, Shine B, et al. Sluggish cognitive tempo and daytime sleepiness mediate relationships between sleep and academic performance. Journal of Developmental & Behavioral Pediatrics. 2021; 42(8):637–647. doi: 10.1097/DBP.0000000000000948 [DOI] [PubMed] [Google Scholar]
29.Shuttleton C. Examining Mediation and Moderation Effects of Academic Motivation on the Relationship Between Disciplinary Events and Academic Performance in Secondary School.2019. [Google Scholar]
30.Zeb A, Gan GGG, Javaid M, Khan MN, Khan AU, Gul S. The interplay between supervisor support and job performance: Implications of social exchange and social learning theories. Journal of Applied Research in Higher Education. 2023; 15(2):429–448. 10.1108/jarhe-04-2021-0143 [Google Scholar]
31.Song J, Bong M, Lee K, Kim S I. Longitudinal investigation into the role of perceived social support in adolescents’ academic motivation and achievement. Journal of Educational Psychology. 2015; 107(3):821. 10.1037/edu0000016 [Google Scholar]
32.Rodríguez S, Piñeiro I, Gómez-Taibo ML, Regueiro B, Estévez I, Valle A. An explanatory model of maths achievement: Perceived parental involvement and academic motivation. Psicothema. 2017; 29(2):184–190. doi: 10.7334/psicothema2017.32 [DOI] [PubMed] [Google Scholar]
33.Boonk L, Gijselaers HJ, Ritzen H, Brand-Gruwel S. A review of the relationship between parental involvement indicators and academic achievement. Educational Research Review. 2028; 24:10–30. 10.1016/j.edurev.2018.02.001 [Google Scholar]
34.Wentzel KR., Russell S, Baker S. Emotional support and expectations from parents, teachers, and peers predict adolescent competence at school. Journal of Educational Psychology. 2016; 108(2):242. 10.1037/edu0000049 [Google Scholar]
35.Yu L, Zhang N, Zhang Y. Multilevel Analysis of the effects of participation, peer support, SRL and course disciplines on academic performance in SPOCs. Interactive Learning Environments. 2023; 31(7):4507–4520. 10.1080/10494820.2021.1974053 [Google Scholar]
36.Shao YH., Kang SM, Lu Q, Zhang C, Li R How peer relationships affect academic achievement among junior high school students: The chain mediating roles of learning motivation and learning engagement. BMC psychology. 2024; 12(1):278. 10.1186/s40359-024-01780-z doi: 10.1186/s40359-024-01780-z [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Wentzel KR. Peer relationships, motivation, and academic achievement at school. In Elliot A. J., Dweck C. S., & Yeag D. S.er (Eds.), Handbook of competence and motivation: Theory and application. The Guilford Press; 2017. [Google Scholar]
38.Affuso G, Zannone A, Esposito C, et al. The effects of teacher support, parental monitoring, motivation and self-efficacy on academic performance over time. European Journal of Psychology of Education. 2023; 38(1):1–23. 10.1007/s10212-021-00594-6 [Google Scholar]
39.Wang K, Zhu C. MOOC-based flipped learning in higher education: students’ participation, experience and learning performance. International Journal of Educational Technology in Higher Education. 2019; 16(1):1–18. 10.1186/s41239-019-0163-0 [Google Scholar]
40.Liu H, Liu Q, Du X, Liu J, Hoi CKW, Schumacker RE. Teacher-student relationship as a protective factor for socioeconomic status, students’ self-efficacy and achievement: a multilevel moderated mediation analysis. Current Psychology. 2021; 42(4): 3268–3283. 10.1007/s12144-021-01598-7 [Google Scholar]
41.Shao Y, Kang S. The Link Between Parent-Child Relationship and Learning Engagement Among Adolescents: The Chain Mediating Roles of Learning Motivation and Academic Self-Efficacy. Frontiers in Education. 2022. a; 7: 854549. 10.3389/feduc.2022.854549 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Zeb A, Gan GGG, Wei OJ, Karim R. Examining the nexus between situational factors and job performance through the mediating role of work engagement and self‐efficacy. Journal of Public Affairs. 2024; 24(2):e2915. 10.1002/pa.2915 [Google Scholar]
43.Shao Y, Kang S. The association between peer relationship and learning engagement among adolescents: The chain mediating roles of self-efficacy and academic resilience. Frontiers in Psychology. 2022. b; 13: 938756. 10.3389/fpsyg.2022.938756 doi: 10.3389/fpsyg.2022.938756 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Gao H, Ou Y, Zhang Z, Ni M, Zhou X, Liao L. The relationship between family support and e-learning engagement in college students: the mediating role of e-learning normative consciousness and behaviors and self-efficacy. Frontiers in Psychology. 2021; 12:573779. 10.3389/fpsyg.2021.573779 doi: 10.3389/fpsyg.2021.573779 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Chu RJ, Chu AZ. Multi-level analysis of peer support, internet self-efficacy and e-learning outcomes-The contextual effects of collectivism and group potency. Computers and Education. 2010; 55:145–154. 10.1016/j.compedu.2009.12.011 [Google Scholar]
46.Ayllón S, Alsina Á, Colomer J. Teachers’ involvement and students’ self-efficacy: Keys to achievement in higher education. PloS one. 2019; 14(5):e0216865. 10.1371/journal.pone.0216865 doi: 10.1371/journal.pone.0216865 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Wu H, Li S, Zheng J, Guo J. Medical students’ motivation and academic performance: the mediating roles of self-efficacy and learning engagement. Medical education online. 2020; 25(1):1742964. 10.1080/10872981.2020.1742964 doi: 10.1080/10872981.2020.1742964 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Kuo TM, Tsai C, Wang J. Linking web-based learning self-efficacy and learning engagement in MOOCs: The role of online academic hardiness. The Internet and Higher Education. 2021; 51: 10089. 10.1016/j.iheduc.2021.100819 [Google Scholar]
49.Zysberg L, Schwabsky N. School climate, academic self-efficacy and student achievement. Educational Psychology. 2021; 41(4):467–482. 10.1080/01443410.2020.1813690 [Google Scholar]
50.Bai B, Chao GCN, Wang C. The relationship between social support, self-efficacy, and English language learning achievement in Hong Kong. Tesol Quarterly. 2019; 53(1):208–221. 10.1002/tesq.439 [Google Scholar]
51.Mishra S. Social networks, social capital, social support and academic success in higher education: A systematic review with a special focus on ‘underrepresented’ students. Educational Research Review. 2020; 29:100307. 10.1016/j.edurev.2019.100307 [Google Scholar]
52.Bradley GL, Ferguson S, Zimmer-Gembeck MJ. Parental support, peer support and school connectedness as foundations for student engagement and academic achievement in Australian youth. Handbook of Positive Youth Development: Advancing Research, Policy, and Practice in Global Contexts. 2021; 219–236. 10.1007/978-3-030-70262-5_15 [Google Scholar]
53.Wong T K, Tao X, Konishi C. Teacher support in learning: Instrumental and appraisal support in relation to math achievement. Issues in Educational Research. 2018; 28(1):202–219. 10.3316/ielapa.437960747459453 [Google Scholar]
54.Kim HJ, Hong AJ, Song HD. The roles of academic engagement and digital readiness in students’ achievements in university e-learning environments. International Journal of Educational Technology in Higher Education. 2019; 16(1):1–18. 10.1186/s41239-019-0152-3 [Google Scholar]
55.Sun RQ, Sun GF, Ye JH. The effects of online game addiction on reduced academic achievement motivation among Chinese college students: the mediating role of learning engagement. Frontiers in Psychology. 2023; 14:1185353. 10.3389/fpsyg.2023.1185353 doi: 10.3389/fpsyg.2023.1185353 [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Ye JH, Wu YF, Nong W, Wu YT, Ye JN, Sun Y. The association of short-video problematic use, learning engagement, and perceived learning ineffectiveness among Chinese vocational students. In Healthcare.2023; 11(2):161. 10.3390/healthcare11020161 doi: 10.3390/healthcare11020161 [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Zhao Y, Zheng Z, Pan C, Zhou L. Self-Esteem and Academic Engagement Among Adolescents: A Moderated Mediation Model. 2021; 12: 690828. 10.3389/fpsyg.2021.690828 doi: 10.3389/fpsyg.2021.690828 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Sökmen Y. The role of self-efficacy in the relationship between the learning environment and student engagement. Educational Studies. 2021; 47(1):19–37. 10.1080/03055698.2019.1665986 [Google Scholar]
59.Hong JC, Zhang HL, Ye JH, Ye JN. The effects of academic self-efficacy on vocational students behavioral engagement at school and at firm internships: A model of engagement-value of achievement motivation. Education Sciences. 2021; 11(8):387. 10.3390/educsci11080387 [Google Scholar]
60.Sun Y, Hong JC, Ye JH, Ye JN. Satisfaction with Online Study Abroad Predicted by Motivation and Self-Efficacy: A Perspective Based on the Situated Expectancy–Value Theory during the COVID-19 Epidemic. Sustainability. 2023;15(5):4070. 10.3390/su15054070 [Google Scholar]
61.Zhang W, Xu M, Su H. Dance with Structural Equations. Xiamen: Xiamen University Press. 2020. [Google Scholar]
62.Schwarzer R., Optimism vulnerability, and self-beliefs as health-related cognitions: A systematic overview. Psychology and Health: An International Journal. 2020; 9:161–180. 10.1080/08870449408407475 [Google Scholar]
63.Fang L, Shi K, Zhang K. Reliability and validity of the Chinese version of the learning input scale. Chin. J. Clin. Psychol. 2008; 6: 618–620. [Google Scholar]
64.Schaufeli WB, Martinez IM, Pinto AM, Salanova M, Bakker AB. Burnout and Engagement in University Students: A Cross-National Study. Journal of Cross-Cultural Psychology. 2002; 33:464–481. 10.1177/0022022102033005003 [Google Scholar]
65.Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis, 7th Edn. New Jersey: Pearson Education; 2010. [Google Scholar]
66.Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 1998. [Google Scholar]
67.Fornell C, Larcker DF. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 1981; 66(6):39–50. 10.1177/002224378101800104 [Google Scholar]
68.Kline RB. Principles and Practice of Structural Equation Modeling, Guilford Press, New York, NY. 2011. [Google Scholar]
69.Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validityin variance-based structural equation modeling. Journal of the Academy of Marketing Science. 2015; 43(1):115–135. [Google Scholar]
70.Cohen J. A power primer. Psychol. Bull. 1992; 112:155–159. 10.1037/0033-2909.112.1.155 doi: 10.1037//0033-2909.112.1.155 [DOI] [PubMed] [Google Scholar]
71.Hayes AF. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs. 2009; 76 (4):408–420. 10.1080/03637750903310360 [Google Scholar]
72.MacKinnon D. Introduction to Statistical Mediation Analysis. Mahwah: Erlbaum; 2008. [Google Scholar]
73.Jacobson LT, Burdsal CA. Academic performance in middle school: Friendship influences. Global Journal of Community Psychology Practice. 2012; 2(3):1–12. 10.7728/0203201206 [Google Scholar]
74.Gallardo LO, Barrasa A, Fabricio G. Positive peer relationships and academic achievement across early and mid-adolescence. Social Behavior and Personality: an international journal. 2016; 44(10):1637–1648. 10.2224/sbp.2016.44.10.1637 [Google Scholar]
75.Escalante MN, Fernández-Zabala A, Goñi Palacios E, Izar-de-la-Fuente DI. School Climate and Perceived Academic Achievement: Direct or Resilience-Mediated Relationship? Sustainability. 2020; 13(1):68. 10.3390/su13010068 [Google Scholar]
76.Ma D. Research on the relationship between parent-child relationship, peer relationship and academic performance of junior high school students [Unpublished manuscript]. Qufu Normal University, China; 2020. [Google Scholar]
77.Dupont S, Galand B, Nils F. The impact of different sources of social support on academic performance: Intervening factors and mediated pathways in the case of master’s thesis. European Review of Applied Psychology. 2015; 65(5):227–237. 10.1016/j.erap.2015.08.003 [Google Scholar]
78.Bandura A, Adams NE. Analysis of self-efficacy theory of behavioral change. Cognitive therapy and research. 1977; 1(4):287–310. 10.1007/bf01663995 [Google Scholar]
79.Wang X, Yang H. Does the academic burden really get lighter the more it is reduced—A cross-sectional historical meta-analysis of secondary school students’ learning pressure. Shanghai Education Research. 2022; 10:24–30. https://doi.10.16194/j.cnki.31-1059/g4.2022.10.013 [Google Scholar]
80.Usán Supervía P, Quílez Robres A. Emotional regulation and academic performance in the academic context: The mediating role of self-efficacy in secondary education students. International Journal of Environmental Research and Public Health. 2021; 18(11): 5715. 10.3390/ijerph18115715 doi: 10.3390/ijerph18115715 [DOI] [PMC free article] [PubMed] [Google Scholar]
81.Qureshi MA, Khaskheli A, Qureshi JA, Raza SA, Yousufi SQ. Factors affecting students’ learning performance through collaborative learning and engagement. Interactive Learning Environments. 2023; 31(4):2371–2391. 10.1080/10494820.2021.1884886 [Google Scholar]
82.Wang MT, Holcombe R. Adolescents’ perceptions of school environment, engagement, and academic achievement in middle school. American Educational Research Journal. 2010; 47(3):633–662. 10.3102/0002831209361209 [Google Scholar]
83.Chen JJL. Relation of academic support from parents, teachers, and peers to Hong Kong adolescents’ academic achievement: The mediating role of academic engagement. Genetic, social, and general psychology monographs. 2005; 131(2):77–127. 10.3200/mono.131.2.77-127 doi: 10.3200/MONO.131.2.77-127 [DOI] [PubMed] [Google Scholar]
84.Jelas ZM, Azman N, Zulnaidi H, Ahmad NA. Learning support and academic achievement among Malaysian adolescents: The mediating role of student engagement. Learning Environments Research. 2016; 19:221–240. 10.1007/s10984-015-9202-5 [Google Scholar]
85.Safaee M, Rezaei A, Talepasand S. Predict academic performance based on family support, friends support and others support: The mediating role of academic self-efficacy, academic resilience and academic engagement. Educational Psychology. 2019; 15(52):239–268. 10.22054/jep.2019.41526.2658 [Google Scholar]
86.Chen Y. The effect of thematic video-based instruction on learning and motivation in e-learning. International Journal of the Physical Sciences. 2012; 7(6): 957–965. 10.5897/IJPS11.1788 [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0311597.r001

Decision Letter 0

Ehsan Namaziandost

4 Jun 2024

PONE-D-24-10692The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagementPLOS ONE

Dear Dr. Qian,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Dear author/s,

Thank you for your submission. I have now received the reviews from the reviewers. After careful consideration, we feel that it has merit but needs revision. Please carefully address the comments, provide a line-by-line response letter, and highlight all the changes you make with different comments. If you disagree with the reviewers' comments, please write a rebuttal justifying why you disagree. Thank you

Academic Editor,Ehsan Namaziandost

==============================

Please submit your revised manuscript by Jul 19 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Ehsan Namaziandost

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include a separate caption for each figure in your manuscript.

3. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Abstract:

Background:

Clarify the initial premise by breaking down the sentence for better readability.

Replace "have been acknowledged" with "are well-documented" for clarity.

Purpose:

Simplify the sentence structure.

Use "aims to" instead of "is to" for a more formal tone.

Ensure consistent tense usage (present tense) for a research aim.

Method:

Use "participants" rather than "students" to maintain formal research terminology.

Include an equal sign and parentheses for the mean age (mean age = 13.47 years, SD = 0.5) for clarity and precision.

Conclusion:

Use "To enhance adolescents' academic success" for a concise summary.

Ensure the recommendation flows logically from the results presented.

Introduction:

In China, test-based education is one of the most important methods of selecting talent, which puts many students under a lot of academic pressure [1]. Comment: Rephrase to: "In China, test-based education is a primary method for selecting talent, placing significant academic pressure on students [1]." This makes the sentence more concise and clear.

During this special academic climate, middle school students are facing challenges such as how to form learning habits and behaviors, deal with obstacles in study, and reduce learning pressure. Comment: Combine and streamline: "In this academic climate, middle school students face challenges in forming learning habits, overcoming study obstacles, and reducing learning pressure." This reduces redundancy.

It is evaluated and measured using a variety of criteria to determine students’ academic performance and progress, including grade assessment, academic skills and abilities, and academic outcomes [4, 5, 6]. Comment: Remove redundancy and tighten: "It is measured through various criteria, including grade assessments, academic skills, and outcomes [4, 5, 6].

To fill this gap, our study aims to comprehensively check the interplay between social support, self-efficacy, learning engagement, and academic performance. Comment: Clarify: "To fill this gap, our study aims to comprehensively examine the interplay between social support, self-efficacy, learning engagement, and academic performance."

The study’s goal is to give a comprehensive knowledge of the cumulative influence of social support, self-efficacy, and learning engagement on academic success. Comment: Simplify: "The study aims to provide a comprehensive understanding of the combined influence of social support, self-efficacy, and learning engagement on academic success."

The Social Cognitive Theory (SCT) gives a theoretical structure for developing a chain mediation model in this study. Comment: Simplify: "Social Cognitive Theory (SCT) provides the theoretical framework for developing a chain mediation model in this study.

Literature section:

The literature section seem good but some latest ref are necessary. The given paper are closely related to the nature of the paper can cited.

Zeb, A., Gan, G. G. G., Wei, O. J., & Karim, R. (2024). Examining the nexus between situational factors and job performance through the mediating role of work engagement and self‐efficacy. Journal of Public Affairs, 24(2), e2915.

Zeb, A., Goh, G. G. G., Javaid, M., Khan, M. N., Khan, A. U., & Gul, S. (2023). The interplay between supervisor support and job performance: Implications of social exchange and social learning theories. Journal of Applied Research in Higher Education, 15(2), 429-448.

Zeb, A., Ullah, R., & Karim, R. (2024). Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations. The International Journal of Information and Learning Technology, 41(1), 99-111.

Method:

Provide a citation for the recommended sample size standards in structural equation modeling (SEM) to support the claim of stability and reliability of the model estimate.

The sentence "The selection of these schools was based on their willingness to participate and their representation of diverse socioeconomic backgrounds." should specify how diversity in socioeconomic backgrounds was assessed and measured.

Mention the time frame during which the data collection took place.

Add a section detailing the statistical methods and software used for data analysis.

Describe how missing data was handled and any assumptions made during the analysis.

Results:

The results section seem good.

Discussion:

Mention conclusion in the one para.

Reviewer #2: 1. In the introduction, there is a lack of coherence between each paragraph.

2. In the introduction, please state the gaps in the study.

3. Please add a chapter, "literature review". 4. lines 66-98 need to be greatly condensed.

4. The lines 66~98 need to be greatly condensed and summarised in no more than one paragraph.

5. Please add sampling techniques.

6. APA formatting should not be included in the text.

7. participant characteristics should be stated in the methodology.

8 Suggest additional subheadings for research discussions.

9 Please add a section on "Conclusion".

10 The following literature is relevant to the study and is provided for reference:

The effect of online game addiction on reduced academic achievement motivation among Chinese college students: The mediating role of learning engagement

The association of short video problematic use, learning engagement, and perceived learning ineffectiveness among Chinese vocational students

Satisfaction with online study abroad predicted by motivation and self-efficacy: A perspective based on the situated expectancy–value theory during the COVID-19 epidemic

The effects of academic self-efficacy on vocational students behavioral engagement at school and at firm internships: A model of engagement-value of achievement motivation

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Dec 31;19(12):e0311597. doi: 10.1371/journal.pone.0311597.r002

Author response to Decision Letter 0

17 Jul 2024

Response to Reviewers

Title: The Chain Mediating Roles of Self-efficacy and Learning Engagement

Authors: Xiangping Zhang, Wensheng Qian

Manuscript ID: PONE-D-24-10692

Dear reviewers,

Thank you very much for your comments and professional advice. We agree with the reviewers' suggestions and will incorporate the recommended changes into the manuscript. We believe that these revisions will significantly strengthen our manuscript and provide a more robust foundation for our claims. We hope that our work can be improved again. Furthermore, we would like to show the details as follows:

Reviewer 1#

Abstract Section

Comments: In the abstract section, authors need to improve the wording, break down sentences, simplify sentence structure, switch tenses, etc. to enhance accuracy, logic, and readability.

Response: Thanks for your suggestions, you have provided us with very valuable advice to improve the quality of the abstract section. We have used your comments to improve its accuracy, logic, and readability.

1. Background was revised as “Although the effects of social support, self-efficacy, and learning engagement on academic performance are well-documented, there is still limited understanding of the specific mechanisms through which social support influences academic performance through self-efficacy and learning engagement.”

2. Purpose was revised as “This study aims to investigate the relationship between social support and adolescents' academic performance based on the Social Cognitive Theory.”

3. The method was revised as “The data was collected from 265 participants (mean age=13.47 years, SD = 0.5) in four middle schools, in the Shandong Province of China in June 2023.”

4. Conclusion was revised as “To enhance adolescents’ academic success, appropriate interventions should be implemented for teachers, parents, or other social factors, to construct a positive learning environment in and out of school to improve adolescents’ self-efficacy and learning engagement.”

Introduction Section

Comments: In the Introduction section, authors need to rephrase, combine, streamline, remove redundancy, and tighten, clarify, and simplify the sentences.

1. Rephrase “In China, test-based education is one of the most important methods of selecting talent, which puts many students under a lot of academic pressure [1].“

2. Combine and streamline: "During this special academic climate, middle school students are facing challenges such as how to form learning habits and behaviors, deal with obstacles in study, and reduce learning pressure.”

3. Remove redundancy and tighten: "It is evaluated and measured using a variety of criteria to determine students’ academic performance and progress, including grade assessment, academic skills and abilities, and academic outcomes [4, 5, 6].”

4. Clarify: "To fill this gap, our study aims to comprehensively check the interplay between social support, self-efficacy, learning engagement, and academic performance.”

5. Simplify: "The study’s goal is to give a comprehensive knowledge of the cumulative influence of social support, self-efficacy, and learning engagement on academic success.”

6. Simplify: "The Social Cognitive Theory (SCT) gives a theoretical structure for developing a chain mediation model in this study.”

Response: Thanks for your corrections, it was revised as:

1. In China, middle schools are committed to providing quality education as an essential component of compulsory education, and as such they pay special attention to the development of intellectual education. For this reason, their assessment methods focus primarily on examinations for assessing student progress, learning, and selecting talent [1, 2], which does emphasize the importance of examination results in the education process.

2. However, it cannot be ignored that this evaluation method also brings challenges to middle school students in forming learning habits, overcoming study obstacles, and reducing learning pressure [3].

3. It is measured through various criteria, including grade assessments, academic skills, and outcomes [13, 14].

4. To fill this gap, our research will look at the relationship between social support, self-efficacy, learning engagement, and academic performance, as well as the role of self-efficacy and learning engagement as mediators.

5. The study aims to provide a comprehensive understanding of the combined influence of social support, self-efficacy, and learning engagement on academic success with SCT.

6. The Social Cognitive Theory (SCT) proposed by Bandura in 1986, provides the theoretical framework for developing a chain mediation model in this study.

Literature Section

Comments: In the literature section, authors need to add some latest ref.

Response: As suggested by the reviewer, we have added more references to support the ideas proposed.

Method Section

Comments 1: In the Method section, authors need a citation for the recommended sample size standards in structural equation modeling (SEM) to support the claim of stability and reliability of the model estimate.

Response 1: We thank the reviewer for this helpful recommendation. We added the sample size selection criteria on Page 10 Lines 179-180:” It is explained that the proper sample size should be at least ten times the total number of variables observed due to the Structure Equation Modeling (SEM) recommendation [57].”

Comments 2: The sentence "The selection of these schools was based on their willingness to participate and their representation of diverse socioeconomic backgrounds." should specify how diversity in socioeconomic backgrounds was assessed and measured.

Response 2: Thank you for your question. The four middle schools chosen in our research were located in the urban and rural areas of Shandong Province, China. First of all, the geographical distribution of the four junior secondary schools itself reflects the diversity of China's socioeconomic structure. Secondly, factors such as the composition of students and the quality of education of four middle schools also reflect the diversity of China's socioeconomic structure. Furthermore, the diversity in socioeconomic backgrounds of the participating middle schools was measured by the place of residence of students, parental education level, and parental monthly income. In the text, we added the explanation on Page 10 Lines 185-188:” Meanwhile, these middle schools are representative of diverse socioeconomic backgrounds including a mix of urban and rural locations, varied student populations, and diverse academic performance levels, which ensure a balanced representation of both genders and different grade levels within the specified age range.”

Comments 3: Authors should mention the time frame during which the data collection took place.

Response 3: Thanks for your information. These participants were recruited from June 1 to June 30, 2023. we added it on Page 8 Lines 169-170.”

Comments 4: Add a section detailing the statistical methods and software used for data analysis.

Response 4: Thank you for your question. we added the explanation on Pages 12-13 Lines 227-233:” Data were analyzed using Amos 24.0 and SPSS 24.0. First, the Harman single-factor test was used to assess the possibility of common method bias. The sample’s characteristics were then appropriately reflected using descriptive analysis. Following that, a structural equation modeling (SEM) analysis was run to assess both the measurement and structural models. The measurement model was validated using confirmatory factor analysis, while the structural model was investigated using goodness-of-fit indices and path coefficients. Finally, the significance of mediating effects was determined using the bootstrapping method.”

Comments 5: Describe how missing data was handled and any assumptions made during the analysis.

Response 5: Thanks for your information. we added the explanation on Page 10 Lines 179-183:” We distributed 300 survey forms, but only 265 (92.6%) completed survey forms were received for further analysis. 14 (4.7%) were rejected because of incomplete records and missing answers.”

Conclusion Section

Comments: Mention the conclusion in one paragraph.

Response: We are so grateful for this suggestion. As suggested by the reviewer, we have revised the conclusion in one paragraph as follows.

Conclusion

The study set out to find the relationship between social support and academic performance in the context of China's test-based culture. The current data suggest that adolescents' academic performance is positively and directly impacted by social support, meanwhile, learning engagement and self-efficacy play the role of chain mediators in the association between social support and academic performance. Also, the relationship and effect of various variables are further described with the help of SCT. As evidenced by previous research studies, this article is unique and provides new insights regarding the role of social support, self-efficacy, learning engagement, and academic performance in the special academic climate of China. This research contributes to the existing academic performance literature by confirming a mediating process in the relationship among academic performance, social support, self-efficacy, and learning engagement. In the test-oriented learning climate of China, middle school students who get more help from parents, teachers, or peers can easily achieve self-efficacy and engage in learning, which in return achieve better academic performance in learning. In addition, the result of the research enhances the understanding of the relationship between social support and academic performance based on the SCT, which emphasizes the significance of social elements in determining students' self-efficacy and involvement in the learning process. Regarding the practical implications, it is conducive for educational practitioners to easier comprehend the measures of improving students' academic performance from the angle of social factors such as educators, parents, peers, etc. Regarding social support, teachers should foster an inclusive and internal classroom environment to promote respect, empathy, and cooperation in learning, such as carrying out peer mentoring programs, and cooperative learning activities. Parents should create a supportive learning environment at home, for example, building a focused atmosphere, providing dedicated study space, and minimizing external distractions. In regards to self-efficacy, teachers or parents should encourage students to participate in problem-solving activities that connect everyday learning to real-life experiences, as well as motivate adolescents to take on challenges and solve problems [80]. In addition, teachers or parents should provide timely and constructive feedback that allows students to monitor their learning progress and adjust their strategies accordingly, thereby raising students' self-efficacy. Concerning learning engagement, teachers, parents, and other social factors should work together to gain a better understanding of adolescents' needs and use tactics and skills to increase their engagement in learning through meaningful practical activities.

Reviewer 2#

Introduction Section

Comments 1: Improve the coherence between each paragraph of the Introduction.

Responsev1: We are very sorry for this kind of mistake and we have carefully reviewed the Introduction Section and the entire manuscript to improve the coherence between each paragraph.

Comments 2: State the gaps in the study.

Response 2: We are sorry to bother you with our negligence and we have added the statement of gaps in the study on Pages 4-5 Lines 63-69:” However, there is still a lack of understanding about the specific mechanisms by which social support, self-efficacy, learning engagement, and academic performance interact with one another, particularly the mediation effect of self-efficacy and learning engagement on social support and academic performance in adolescents. To fill this gap, our research will look at the relationship between social support, self-efficacy, learning engagement, and academic performance, as well as the role of self-efficacy and learning engagement as mediators.”

Comments 3: Make the literature review section a separate paragraph.

Response 3: We appreciate the reviewer for this recommendation and we have made the literature review section a separate paragraph on Pages 5-9, Line 88-160.

LITERATURE REVIEW

Social support and academic performance

Relevant research has shown that social support is a significant predictor of academic performance. It has been found that social support can significantly improve people's self-confidence [26], and motivation [27]. Researchers also have proved that parental involvement and encouragement can enhance students' focus and motivation, leading to improved academic outcomes [28, 29]. Additionally, a supportive family environment provides stability and emotional support, helping students obtain higher academic grades [30]. Social support from peers also plays a crucial role in influencing academic performance [31, 32]. For example, Wentzel noted that interactions with peers who demonstrate positive learning attitudes and behaviors can stimulate students' motivation and enhance their academic performance [33]. Importantly, it has been revealed that social support from educators has a significant positive impact on academic performance [34]. Research has indicated that individualized tutoring and additional assistance provided by teachers can address students' specific learning needs and provide effective learning guidance, thereby promoting academic progress [35]. Overall, these findings emphasize the critical role of social support in academic performance, highlighting that adolescents who get support from their parents, peers, and teachers are more inclined to achieve success in their academic pursuits. On this basis, we propose the following hypothesis.

Comments 4: The lines 66~98 need to be greatly condensed and summarised in no more than one paragraph.

Response 4: Thanks for your suggestions, we have used your comments to improve its accuracy, logic, and readability on Page 5 Lines 70-87:

“The Social Cognitive Theory (SCT), proposed by Bandura in 1986, provides the theoretical framework for developing a chain mediation model in this study. According to this theory, human behavior is influenced by three variables: personal factors (e.g., self-efficacy), behavioral factors (e.g., learning engagement and achievement), and environmental factors (e.g., social support ). Namely, individual behavior is driven and moderated by personal, behavioral, and environmental elements [23]. Past investigations have used SCT to probe into how personal cognitive or environmental factors affect academic performance among adolescents [24, 25], with less attention paid to the interplay between social support, self-efficacy, learning engagement, and academic performance within the framework of SCT. Based on the above, the study aims to provide a comprehensive understanding of the combined influence of these four factors with SCT.

This study takes a broader approach, examining the interrelationships and mediating effects of social support, self-efficacy, learning engagement, and academic performance. As a result, this study differs from previous research, which focused on the impact of single factors on academic performance. The significance of this study stems from its contribution to bridging the existing research gap and providing a better understanding of the factors that influence students' academic success. By investigating the interactive effects and mediating roles of these factors, the study proposes to offer valuable insights into the complex dynamics that influence academic performance among adolescents.”

Method Section

Comments 1: Please add sampling techniques.

Response 1: We appreciate the reviewer for this kind of recommendation and we have added the sampling techniques on Page 9-10 Line 168-178:” The present study employed the simple random sampling method to recruit Chinese middle school students to voluntarily take part in the questionnaire collection. The data was collected from 1 June to 30

Attachment

Submitted filename: Respondse to reviewers.doc

pone.0311597.s002.doc^{(123.5KB, doc)}

PLoS One. doi: 10.1371/journal.pone.0311597.r003

Decision Letter 1

Ehsan Namaziandost

25 Jul 2024

PONE-D-24-10692R1The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagementPLOS ONE

Dear Dr. Qian,

Please submit your revised manuscript by Sep 08 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Ehsan Namaziandost

Academic Editor

PLOS ONE

Additional Editor Comments:

Dear author/s,

Academic Editor,

Ehsan Namaziandost

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No

**********

6. Review Comments to the Author

Reviewer #1: Abstract: follow the given format in the abstract like purpose, method, results, findings, practical implications, and originality/value.

Introduction: lines 20-21 the sentence is clear but could be made more concise. Lines 24-26 The phrase "it cannot be ignored that" can be simplified. Lines 27-29 Consider rephrasing for better flow. Lines 29-30 the sentence is lengthy and could be broken into two for clarity. Lines 34-36 rephrase for clarity and remove redundancy. Lines 45-47 Clarify the importance of self-efficacy and learning engagement. Lines 54-59 Combine and streamline for clarity. lines 63-66 Streamline and emphasize the research gap.

Literature: The following paper can be cited its closely link with nature of the given paper.

Rehman, F. U., Ismail, H., Al Ghazali, B. M., Asad, M. M., Shahbaz, M. S., & Zeb, A. (2021). Knowledge management process, knowledge based innovation: Does academic researcher’s productivity mediate during the pandemic of covid-19?. Plos one, 16(12), e0261573. Zeb, A., Ullah, R., & Karim, R. (2024). Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations. The International Journal of Information and Learning Technology, 41(1), 99-111. Rehman, F. U., & Zeb, A. (2023). Investigating the nexus between authentic leadership, employees’ green creativity, and psychological environment: evidence from emerging economy. Environmental Science and Pollution Research, 30(49), 107746-107758.

Method: seem good.

Results: If HTMT approach is possible in AMOS can be mentioned to ensure the discriminant validity issue.

Discussion: Two headings one is Practical implication and another theoretical implications can be mentioned.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

PLoS One. 2024 Dec 31;19(12):e0311597. doi: 10.1371/journal.pone.0311597.r004

Author response to Decision Letter 1

4 Sep 2024

Title: The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement

Authors: Xiangping Zhang, Wensheng Qian

Manuscript ID: PONE-D-24-10692

Dear reviewer,

Thank you for your letter and for reviewer’ comments concerning our manuscript entitled “The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement”. All of those remarks are relevant and beneficial for the purpose of rewriting and enhancing our paper. We have thoroughly examined every comments and have made diligent corrections. We are confident that these adjustments will greatly enhance our manuscript and establish a strong basis for our assertions. We aspire for continued enhancement of our work.The responses to the reviewer's comments are as follows:

Reviewer 1#

Abstract Section

Comments: Authors must adhere to the prescribed structure for the abstract, which includes sections on the purpose, method, results, findings, practical implications, and originality/value.

Response: We appreciate your ideas, since they have given us great guidance on enhancing the quality of the abstract part. We have made revisions to this section as follows:

Purpose- While the impact of social support on academic performance is acknowledged, the specific mechanisms by which social support affects academic performance, particularly through self-efficacy and learning engagement, remain poorly understood. This study aims to examine the correlation between social support and academic achievement among Chinese middle school students, framed within the Social Cognitive Theory. It also seeks to explore the mediating roles of self-efficacy and learning engagement in this relationship.

Method- Data was collected from 265 individuals (mean age = 13.47 years, SD = 0.5) in four middle schools in Shandong Province, China in June 2023, using the simple random sample technique. Participants completed the questionnaires independently, and the data was analyzed using the structural equation model (SEM) in AMOS 24.0 and SPSS 24.0.

Results- Social support and academic performance have a direct and significant relationship with the SCT among middle school students. In addition, social support indirectly and positively affects academic performance through self-efficacy and learning engagement. The results also highlight self-efficacy as a key factor linking social support with academic performance.

Practical implications- This study offers valuable insights into the role of social support in Chinese middle school students’ academic achievement, particularly by examining the impact of self-efficacy and learning engagement. These valuable findings may guide policymakers in creating a supportive educational environment both inside and outside the classroom, enhancing adolescents’ self-confidence and engagement in learning.

Originality- This study contributes to the theoretical understanding of social support by investigating the mechanisms through which it impacts academic achievement. It clarifies the complex interactions among social support, self-efficacy, learning engagement, and academic achievement, with particular emphasis on the mediating roles of self-efficacy and learning engagement within the Chinese context.

Introduction Section

Comments: Revise the Introduction section to improve linguistic conciseness, streamline the information, and ensure clarity.Introduction: lines 20-21 the sentence is clear but could be made more concise. Lines 24-26 The phrase "it cannot be ignored that" can be simplified. Lines 27-29 Consider rephrasing for better flow. Lines 29-30 the sentence is lengthy and could be broken into two for clarity. Lines 34-36 rephrase for clarity and remove redundancy. Lines 45-47 Clarify the importance of self-efficacy and learning engagement. Lines 54-59 Combine and streamline for clarity. lines 63-66 Streamline and emphasize the research gap.

Response: Thanks for your corrections, it was revised as:

Lines 20-21 are revised as: Within China's compulsory education system, middle school serves as a crucial intermediary, bridging different levels of education. At this stage, academic performance is a significant indicator of students' information acquisition and their potential for future studies. It is used to evaluate student progress, learning, and talent selection [1, 2].

Lines 24-26 are revised as: In China, academic success is commonly assessed through exam scores in subjects such as Chinese, Math, and English [3, 4]. Nevertheless, this assessment approach presents challenges for middle school students in developing study routines, overcoming academic difficulties, and managing time and anxiety [5].

Lines 27-29 are revised as: Learning is predominantly a cognitive endeavor that involves the acquisition of knowledge through various social activities [6]. Chinese students, however, have limited opportunities for social engagement, primarily confined to interactions within the classroom, on campus, and within their families.

Lines 29-30 are revised as: Social support refers to the resources obtained through social interactions, which reflect the degree of connection between an individual and their community.

Lines 34-36 are revised as: It serves as a defensive shield against negative emotions and stress [7, 8], providing a sense of being valued and supported by others when needed [9].

Lines 45-47 are revised as: These two psychological constructs are closely related to academic performance [20]. Self-efficacy acts a crucial role in motivating individuals to achieve their goals, encouraging them to take risks, and reaching their academic outcomes [21,22].

Lines 54-59 are revised as:Learning engagement refers to the active participation of students in the educational process, which positively impacts on academic performance. Engaged students are typically more motivated, committed, and willing to invest the effort needed to participate in discussions, solve problems, and achieve academic success [25, 26].

Lines 63-66 are revised as: However, little attention has been paid to the influence of social support on the academic performance of Chinese middle school students. Furthermore, this study identifies a gap in understanding the precise mechanisms by which social support affects academic performance through self-efficacy and learning engagement, as outlined in relevant theoretical frameworks.

Literature Section

Comments: In the literature section, authors need to add some latest ref.

Response: As suggested by the reviewer, we have added more references to support the ideas proposed.

2.Zeb A, Ullah R, Karim R. Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations. The International Journal of Information and Learning Technology. 2024; 41(1):99-111. https://doi.org/10.1108/ijilt-04-2023-0046

6.Rehman FU, Ismail H, Al Ghazali B M, Asad MM, Shahbaz MS, Zeb A. Knowledge management process, knowledge based innovation: Does academic researcher’s productivity mediate during the pandemic of covid-19?. Plos one. 2021;16(12):e0261573. https://doi.org/10.1371/journal.pone.0261573

22.Rehman FU, Zeb A. Investigating the nexus between authentic leadership, employees’ green creativity, and psychological environment: evidence from emerging economy. Environmental Science and Pollution Research. 2023; 30(49):107746-107758. https://doi.org/10.1007/s11356-023-29928-1

30.Zeb A, Gan GGG, Javaid M, Khan MN, Khan AU, Gul S. The interplay between supervisor support and job performance: Implications of social exchange and social learning theories. Journal of Applied Research in Higher Education. 2023; 15(2):429-448. https://doi.org/10.1108/jarhe-04-2021-0143

42.Zeb A, Gan GGG, Wei OJ, Karim R. Examining the nexus between situational factors and job performance through the mediating role of work engagement and self‐efficacy. Journal of Public Affairs. 2024; 24(2):e2915. https://doi.org/10.1002/pa.2915

Results Section

Comments:If the HTMT technique is applicable in AMOS, it might be mentioned to address the issue of discriminant validity.

Response:In response to the reviewer's suggestion, we have implemented the HTMT technique to resolve the problem of discriminant validity.

To validate discriminant validity, this study employed the Heterotrait-Monotrait (HTMT) criterion. According to Kline [68], and Henseler et al. [69], an acceptable HTMT value should remain below 0.85. Table 4 indicates that discriminant validity was achieved.

Table 4. Heterotrait-Monotrait Ration (HTMT)

Potential variable Social support Self-efficacy Learning engagement

Social support

Self-efficacy 0.403

Learning engagement 0.508 0.326

Discussion Section

Comments: Two headings, "Practical Implications" and "Theoretical Implications," can be included in Discussion section.

Response: We are so grateful for this suggestion. As suggested by the reviewer, we have revised the discussion as follows.

Theoretical implication

Practical implication

Regarding the practical implications, it is essential for educational practitioners to understand how to enhance students' academic achievement by considering social factors such as the roles of teachers, parents, and peers. To strengthen social support, teachers should create an inclusive and cohesive classroom environment that fosters respect, understanding, and collaboration among students. This can be accomplished through initiatives like peer mentorship programs and collaborative learning activities. Parents also play a vital role in establishing a conducive learning environment at home. They can do this by promoting a focused atmosphere, designating a dedicated study area, and minimizing external distractions. To enhance self-efficacy, it is important for both teachers and parents to encourage students to participate in problem-solving activities that relate to real-life situations. Additionally, they should motivate adolescents to embrace challenges and seek solutions, thereby helping them develop confidence in their abilities [86]. Furthermore, it is essential for educators and guardians to provide timely and constructive feedback that allows students to monitor their learning progress and adjust their approaches accordingly. This kind of feedback can significantly enhance students' self-efficacy and belief in their own abilities. In terms of learning engagement, it is important for teachers, parents, and other social variables to collaborate in order to develop a comprehensive understanding of adolescents' needs. By employing effective strategies and techniques, they can foster greater involvement in learning through meaningful and practical activities. This coordinated effort will not only engage students more deeply but also support their overall academic development.

We deeply value the time and effort dedicated by the reviewers in assessing our article. We eagerly anticipate any further feedback or recommendations.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311597.s003.docx^{(24KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0311597.r005

Decision Letter 2

Ehsan Namaziandost

23 Sep 2024

The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement

PONE-D-24-10692R2

Dear Dr. Qian,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ehsan Namaziandost

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: The coefficient of determination value R square. I not found find if not available. Please include it.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

PLoS One. doi: 10.1371/journal.pone.0311597.r006

Acceptance letter

Ehsan Namaziandost

11 Dec 2024

PONE-D-24-10692R2

PLOS ONE

Dear Dr. Qian,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ehsan Namaziandost

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Data

(XLSX)

pone.0311597.s001.xlsx^{(43.6KB, xlsx)}

Attachment

Submitted filename: Respondse to reviewers.doc

pone.0311597.s002.doc^{(123.5KB, doc)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311597.s003.docx^{(24KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

[pone.0311597.ref001] 1.Zhao X, Selman R, Haste H. Academic stress in Chinese schools and a proposed preventive intervention program. Cogent Education. 2015; 2(1):1000477. 10.1080/2331186x.2014.1000477 [Google Scholar]

[pone.0311597.ref002] 2.Zeb A, Ullah R, Karim R. Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations. The International Journal of Information and Learning Technology. 2024; 41(1):99–111. 10.1108/ijilt-04-2023-0046 [Google Scholar]

[pone.0311597.ref003] 3.Chen J, Huebner ES, Tian L. Longitudinal relations between hope and academic achievement in elementary school students: Behavioral engagement as a mediator. Learning and Individual Differences. 2020; 78:101824. 10.1016/j.lindif.2020.101824 [Google Scholar]

[pone.0311597.ref004] 4.Xu Z, Qi C. The Relationship between Teacher-student Relationship and Academic Achievement: The Mediating Role of Self-efficacy. EURASIA J Math Sci Tech Ed. 2019;15(10):em1758. 10.29333/ejmste/105610 [Google Scholar]

[pone.0311597.ref005] 5.Zhang X, Gu T. Analysis of factors influencing secondary school students’ academic stress—Taking Changzhou junior high school education as an example. Science and Education Magazine.2017; 24:184–186. 10.16400/j.cnki.kjdkx.2017.08.088 [Google Scholar]

[pone.0311597.ref006] 6.Rehman FU, Ismail H, Al Ghazali B M, Asad MM, Shahbaz MS, Zeb A. Knowledge management process, knowledge based innovation: Does academic researcher’s productivity mediate during the pandemic of covid-19?. Plos one. 2021;16(12):e0261573. 10.1371/journal.pone.0261573 doi: 10.1371/journal.pone.0261573 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref007] 7.Malecki CK, Demaray MK. Social support as a buffer in the relationship between socioeconomic status and academic performance. School Psychology Quarterly. 2006; 21(4):375. 10.1037/h0084129 [Google Scholar]

[pone.0311597.ref008] 8.Wright MF, Wachs S. The buffering effect of parent social support in the longitudinal associations between cyber poly victimization and academic outcomes. Social Psychology of Education. 2021; 24:1145–1161. 10.1007/s11218-021-09647-6 [Google Scholar]

[pone.0311597.ref009] 9.Cutrona CE, Russell DW. The provisions of social relationships and adaptation to stress. In Perlma D., Russell W J.(Eds.), Advances in personal relationships. Greenwich, CT: JAI Press Inc; 1987. [Google Scholar]

[pone.0311597.ref010] 10.Ye Y, Dai X. Development of a social support rating scale for college students. Chinese Journal of Clinical Psychology. 2008; 16(5): 456–458. [Google Scholar]

[pone.0311597.ref011] 11.Richman JM, Rosenfeld LB, Bowen GL. Social support for adolescents at risk of school failure. Social work. 1998; 43(4):309–323. 10.1093/sw/43.4.309 doi: 10.1093/sw/43.4.309 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref012] 12.Roksa J, Kinsley P. The role of family support in facilitating academic success of low-income students. Research in Higher Education. 2019; 60:415–436. 10.1007/s11162-018-9517-z [Google Scholar]

[pone.0311597.ref013] 13.Cao C, Zhu C, Meng Q. Chinese international students’ co** strategies, social support resources in response to academic stressors: Does heritage culture or host context matter?. Current Psychology. 2021; 40:242–252. 10.1007/s12144-018-9929-0 [Google Scholar]

[pone.0311597.ref014] 14.Ahmed W, Minnaert A, van der Werf G, Kuyper H. Perceived social support and early adolescent achievement: The mediational roles of motivational beliefs and emotions. Journal of Youth Adolescence. 2010; 39:36–46. 10.1007/s10964-008-9367-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref015] 15.Sahil SAS, Hashim RA. The roles of social support in promoting adolescents’ classroom cognitive engagement through academic self-efficacy. Malaysian Journal of Learning and Instruction. 2022; 8: 49–69. 10.32890/mjli.8.2011.7626 [Google Scholar]

[pone.0311597.ref016] 16.Wang M, Deng X, Du X. Harsh parenting and academic achievement in Chinese adolescents: Potential mediating roles of effortful control and classroom engagement. Journal of school psychology. 2018; 67:16–30. 10.1016/j.jsp.2017.09.002 doi: 10.1016/j.jsp.2017.09.002 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref017] 17.Corcoran RP, Cheung A, Kim E, Xie C. Effective Universal school-based social and emotional learning programs for improving academic achievement: A systematic review and meta-analysis of 50 years of research. Educational Research Review. 2017; 25:56–72. 10.1016/j.edurev.2017.12.001 [Google Scholar]

[pone.0311597.ref018] 18.Goegan LD, Daniels LM. Academic success for students in postsecondary education: The role of student characteristics and integration. Journal of College Student Retention: Research, Theory & Practice. 2021; 23(3):659–685. 10.1177/1521025119866689 [Google Scholar]

[pone.0311597.ref019] 19.Kumar S, Agarwal M, Agarwal N. Defining and measuring academic performance of Hei students-a critical review. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 2021; 12(6):3091–3105. 10.17762/turcomat.v12i6.6952 [Google Scholar]

[pone.0311597.ref020] 20.Dogan U. Student Engagement, Academic Self-efficacy, and Academic Motivation as Predictors of academic achievement. The Anthropologist. 2015; 20(3):553–561. 10.1080/09720073.2015.11891759 [Google Scholar]

[pone.0311597.ref021] 21.Turner JC, Midgley C, Meyer DK, Gheen M, Anderman EM, Kang Y, et al. The classroom environment and students’ reports of avoidance strategies in mathematics: A multimethod study. Journal of Educational Psychology. 2022; 94: 88–106. 10.1037/0022-0663.94.1.88 [Google Scholar]

[pone.0311597.ref022] 22.Rehman FU, Zeb A. Investigating the nexus between authentic leadership, employees’ green creativity, and psychological environment: evidence from emerging economy. Environmental Science and Pollution Research. 2023; 30(49):107746–107758. 10.1007/s11356-023-29928-1 doi: 10.1007/s11356-023-29928-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref023] 23.Liem AD, Lau S, Nie Y. The role of self-efficacy, task value, and achievement goals in predicting learning strategies, task disengagement, peer relationship, and achievement outcome. Contemporary Educational Psychology. 2008; 33: 486–512. 10.1016/j.cedpsych.2007.08.001 [Google Scholar]

[pone.0311597.ref024] 24.Schunk DH, Mullen CA. Self-efficacy as an engaged learner. In Handbook of research on student engagement:219–235. Boston, MA: Springer US; 2012. 10.1007/978-1-4614-2018-7_10 [Google Scholar]

[pone.0311597.ref025] 25.Wang MT, Eccles JS. School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction. 2013; 28:12–23. 10.1016/j.learninstruc.2013.04.002 [Google Scholar]

[pone.0311597.ref026] 26.Fredricks JA, Blumenfeld PC, Paris AH. School engagement: Potential of the concept, state of the evidence. Review of educational research. 2004; 74(1):59–109. 10.3102/00346543074001059 [Google Scholar]

[pone.0311597.ref027] 27.Bandura A. Social cognitive theory, in Handbook of Theories of Social Psychology. 2012; Vol. 1, eds Van Lange P. M., Kruglanski A. W. and E. Higgins; 2012:349–373. [Google Scholar]

[pone.0311597.ref028] 28.O’Hare K, White N, Harding R, Galland B, Sellbom M, Shine B, et al. Sluggish cognitive tempo and daytime sleepiness mediate relationships between sleep and academic performance. Journal of Developmental & Behavioral Pediatrics. 2021; 42(8):637–647. doi: 10.1097/DBP.0000000000000948 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref029] 29.Shuttleton C. Examining Mediation and Moderation Effects of Academic Motivation on the Relationship Between Disciplinary Events and Academic Performance in Secondary School.2019. [Google Scholar]

[pone.0311597.ref030] 30.Zeb A, Gan GGG, Javaid M, Khan MN, Khan AU, Gul S. The interplay between supervisor support and job performance: Implications of social exchange and social learning theories. Journal of Applied Research in Higher Education. 2023; 15(2):429–448. 10.1108/jarhe-04-2021-0143 [Google Scholar]

[pone.0311597.ref031] 31.Song J, Bong M, Lee K, Kim S I. Longitudinal investigation into the role of perceived social support in adolescents’ academic motivation and achievement. Journal of Educational Psychology. 2015; 107(3):821. 10.1037/edu0000016 [Google Scholar]

[pone.0311597.ref032] 32.Rodríguez S, Piñeiro I, Gómez-Taibo ML, Regueiro B, Estévez I, Valle A. An explanatory model of maths achievement: Perceived parental involvement and academic motivation. Psicothema. 2017; 29(2):184–190. doi: 10.7334/psicothema2017.32 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref033] 33.Boonk L, Gijselaers HJ, Ritzen H, Brand-Gruwel S. A review of the relationship between parental involvement indicators and academic achievement. Educational Research Review. 2028; 24:10–30. 10.1016/j.edurev.2018.02.001 [Google Scholar]

[pone.0311597.ref034] 34.Wentzel KR., Russell S, Baker S. Emotional support and expectations from parents, teachers, and peers predict adolescent competence at school. Journal of Educational Psychology. 2016; 108(2):242. 10.1037/edu0000049 [Google Scholar]

[pone.0311597.ref035] 35.Yu L, Zhang N, Zhang Y. Multilevel Analysis of the effects of participation, peer support, SRL and course disciplines on academic performance in SPOCs. Interactive Learning Environments. 2023; 31(7):4507–4520. 10.1080/10494820.2021.1974053 [Google Scholar]

[pone.0311597.ref036] 36.Shao YH., Kang SM, Lu Q, Zhang C, Li R How peer relationships affect academic achievement among junior high school students: The chain mediating roles of learning motivation and learning engagement. BMC psychology. 2024; 12(1):278. 10.1186/s40359-024-01780-z doi: 10.1186/s40359-024-01780-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref037] 37.Wentzel KR. Peer relationships, motivation, and academic achievement at school. In Elliot A. J., Dweck C. S., & Yeag D. S.er (Eds.), Handbook of competence and motivation: Theory and application. The Guilford Press; 2017. [Google Scholar]

[pone.0311597.ref038] 38.Affuso G, Zannone A, Esposito C, et al. The effects of teacher support, parental monitoring, motivation and self-efficacy on academic performance over time. European Journal of Psychology of Education. 2023; 38(1):1–23. 10.1007/s10212-021-00594-6 [Google Scholar]

[pone.0311597.ref039] 39.Wang K, Zhu C. MOOC-based flipped learning in higher education: students’ participation, experience and learning performance. International Journal of Educational Technology in Higher Education. 2019; 16(1):1–18. 10.1186/s41239-019-0163-0 [Google Scholar]

[pone.0311597.ref040] 40.Liu H, Liu Q, Du X, Liu J, Hoi CKW, Schumacker RE. Teacher-student relationship as a protective factor for socioeconomic status, students’ self-efficacy and achievement: a multilevel moderated mediation analysis. Current Psychology. 2021; 42(4): 3268–3283. 10.1007/s12144-021-01598-7 [Google Scholar]

[pone.0311597.ref041] 41.Shao Y, Kang S. The Link Between Parent-Child Relationship and Learning Engagement Among Adolescents: The Chain Mediating Roles of Learning Motivation and Academic Self-Efficacy. Frontiers in Education. 2022. a; 7: 854549. 10.3389/feduc.2022.854549 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref042] 42.Zeb A, Gan GGG, Wei OJ, Karim R. Examining the nexus between situational factors and job performance through the mediating role of work engagement and self‐efficacy. Journal of Public Affairs. 2024; 24(2):e2915. 10.1002/pa.2915 [Google Scholar]

[pone.0311597.ref043] 43.Shao Y, Kang S. The association between peer relationship and learning engagement among adolescents: The chain mediating roles of self-efficacy and academic resilience. Frontiers in Psychology. 2022. b; 13: 938756. 10.3389/fpsyg.2022.938756 doi: 10.3389/fpsyg.2022.938756 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref044] 44.Gao H, Ou Y, Zhang Z, Ni M, Zhou X, Liao L. The relationship between family support and e-learning engagement in college students: the mediating role of e-learning normative consciousness and behaviors and self-efficacy. Frontiers in Psychology. 2021; 12:573779. 10.3389/fpsyg.2021.573779 doi: 10.3389/fpsyg.2021.573779 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref045] 45.Chu RJ, Chu AZ. Multi-level analysis of peer support, internet self-efficacy and e-learning outcomes-The contextual effects of collectivism and group potency. Computers and Education. 2010; 55:145–154. 10.1016/j.compedu.2009.12.011 [Google Scholar]

[pone.0311597.ref046] 46.Ayllón S, Alsina Á, Colomer J. Teachers’ involvement and students’ self-efficacy: Keys to achievement in higher education. PloS one. 2019; 14(5):e0216865. 10.1371/journal.pone.0216865 doi: 10.1371/journal.pone.0216865 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref047] 47.Wu H, Li S, Zheng J, Guo J. Medical students’ motivation and academic performance: the mediating roles of self-efficacy and learning engagement. Medical education online. 2020; 25(1):1742964. 10.1080/10872981.2020.1742964 doi: 10.1080/10872981.2020.1742964 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref048] 48.Kuo TM, Tsai C, Wang J. Linking web-based learning self-efficacy and learning engagement in MOOCs: The role of online academic hardiness. The Internet and Higher Education. 2021; 51: 10089. 10.1016/j.iheduc.2021.100819 [Google Scholar]

[pone.0311597.ref049] 49.Zysberg L, Schwabsky N. School climate, academic self-efficacy and student achievement. Educational Psychology. 2021; 41(4):467–482. 10.1080/01443410.2020.1813690 [Google Scholar]

[pone.0311597.ref050] 50.Bai B, Chao GCN, Wang C. The relationship between social support, self-efficacy, and English language learning achievement in Hong Kong. Tesol Quarterly. 2019; 53(1):208–221. 10.1002/tesq.439 [Google Scholar]

[pone.0311597.ref051] 51.Mishra S. Social networks, social capital, social support and academic success in higher education: A systematic review with a special focus on ‘underrepresented’ students. Educational Research Review. 2020; 29:100307. 10.1016/j.edurev.2019.100307 [Google Scholar]

[pone.0311597.ref052] 52.Bradley GL, Ferguson S, Zimmer-Gembeck MJ. Parental support, peer support and school connectedness as foundations for student engagement and academic achievement in Australian youth. Handbook of Positive Youth Development: Advancing Research, Policy, and Practice in Global Contexts. 2021; 219–236. 10.1007/978-3-030-70262-5_15 [Google Scholar]

[pone.0311597.ref053] 53.Wong T K, Tao X, Konishi C. Teacher support in learning: Instrumental and appraisal support in relation to math achievement. Issues in Educational Research. 2018; 28(1):202–219. 10.3316/ielapa.437960747459453 [Google Scholar]

[pone.0311597.ref054] 54.Kim HJ, Hong AJ, Song HD. The roles of academic engagement and digital readiness in students’ achievements in university e-learning environments. International Journal of Educational Technology in Higher Education. 2019; 16(1):1–18. 10.1186/s41239-019-0152-3 [Google Scholar]

[pone.0311597.ref055] 55.Sun RQ, Sun GF, Ye JH. The effects of online game addiction on reduced academic achievement motivation among Chinese college students: the mediating role of learning engagement. Frontiers in Psychology. 2023; 14:1185353. 10.3389/fpsyg.2023.1185353 doi: 10.3389/fpsyg.2023.1185353 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref056] 56.Ye JH, Wu YF, Nong W, Wu YT, Ye JN, Sun Y. The association of short-video problematic use, learning engagement, and perceived learning ineffectiveness among Chinese vocational students. In Healthcare.2023; 11(2):161. 10.3390/healthcare11020161 doi: 10.3390/healthcare11020161 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref057] 57.Zhao Y, Zheng Z, Pan C, Zhou L. Self-Esteem and Academic Engagement Among Adolescents: A Moderated Mediation Model. 2021; 12: 690828. 10.3389/fpsyg.2021.690828 doi: 10.3389/fpsyg.2021.690828 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref058] 58.Sökmen Y. The role of self-efficacy in the relationship between the learning environment and student engagement. Educational Studies. 2021; 47(1):19–37. 10.1080/03055698.2019.1665986 [Google Scholar]

[pone.0311597.ref059] 59.Hong JC, Zhang HL, Ye JH, Ye JN. The effects of academic self-efficacy on vocational students behavioral engagement at school and at firm internships: A model of engagement-value of achievement motivation. Education Sciences. 2021; 11(8):387. 10.3390/educsci11080387 [Google Scholar]

[pone.0311597.ref060] 60.Sun Y, Hong JC, Ye JH, Ye JN. Satisfaction with Online Study Abroad Predicted by Motivation and Self-Efficacy: A Perspective Based on the Situated Expectancy–Value Theory during the COVID-19 Epidemic. Sustainability. 2023;15(5):4070. 10.3390/su15054070 [Google Scholar]

[pone.0311597.ref061] 61.Zhang W, Xu M, Su H. Dance with Structural Equations. Xiamen: Xiamen University Press. 2020. [Google Scholar]

[pone.0311597.ref062] 62.Schwarzer R., Optimism vulnerability, and self-beliefs as health-related cognitions: A systematic overview. Psychology and Health: An International Journal. 2020; 9:161–180. 10.1080/08870449408407475 [Google Scholar]

[pone.0311597.ref063] 63.Fang L, Shi K, Zhang K. Reliability and validity of the Chinese version of the learning input scale. Chin. J. Clin. Psychol. 2008; 6: 618–620. [Google Scholar]

[pone.0311597.ref064] 64.Schaufeli WB, Martinez IM, Pinto AM, Salanova M, Bakker AB. Burnout and Engagement in University Students: A Cross-National Study. Journal of Cross-Cultural Psychology. 2002; 33:464–481. 10.1177/0022022102033005003 [Google Scholar]

[pone.0311597.ref065] 65.Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis, 7th Edn. New Jersey: Pearson Education; 2010. [Google Scholar]

[pone.0311597.ref066] 66.Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 1998. [Google Scholar]

[pone.0311597.ref067] 67.Fornell C, Larcker DF. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 1981; 66(6):39–50. 10.1177/002224378101800104 [Google Scholar]

[pone.0311597.ref068] 68.Kline RB. Principles and Practice of Structural Equation Modeling, Guilford Press, New York, NY. 2011. [Google Scholar]

[pone.0311597.ref069] 69.Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validityin variance-based structural equation modeling. Journal of the Academy of Marketing Science. 2015; 43(1):115–135. [Google Scholar]

[pone.0311597.ref070] 70.Cohen J. A power primer. Psychol. Bull. 1992; 112:155–159. 10.1037/0033-2909.112.1.155 doi: 10.1037//0033-2909.112.1.155 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref071] 71.Hayes AF. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs. 2009; 76 (4):408–420. 10.1080/03637750903310360 [Google Scholar]

[pone.0311597.ref072] 72.MacKinnon D. Introduction to Statistical Mediation Analysis. Mahwah: Erlbaum; 2008. [Google Scholar]

[pone.0311597.ref073] 73.Jacobson LT, Burdsal CA. Academic performance in middle school: Friendship influences. Global Journal of Community Psychology Practice. 2012; 2(3):1–12. 10.7728/0203201206 [Google Scholar]

[pone.0311597.ref074] 74.Gallardo LO, Barrasa A, Fabricio G. Positive peer relationships and academic achievement across early and mid-adolescence. Social Behavior and Personality: an international journal. 2016; 44(10):1637–1648. 10.2224/sbp.2016.44.10.1637 [Google Scholar]

[pone.0311597.ref075] 75.Escalante MN, Fernández-Zabala A, Goñi Palacios E, Izar-de-la-Fuente DI. School Climate and Perceived Academic Achievement: Direct or Resilience-Mediated Relationship? Sustainability. 2020; 13(1):68. 10.3390/su13010068 [Google Scholar]

[pone.0311597.ref076] 76.Ma D. Research on the relationship between parent-child relationship, peer relationship and academic performance of junior high school students [Unpublished manuscript]. Qufu Normal University, China; 2020. [Google Scholar]

[pone.0311597.ref077] 77.Dupont S, Galand B, Nils F. The impact of different sources of social support on academic performance: Intervening factors and mediated pathways in the case of master’s thesis. European Review of Applied Psychology. 2015; 65(5):227–237. 10.1016/j.erap.2015.08.003 [Google Scholar]

[pone.0311597.ref078] 78.Bandura A, Adams NE. Analysis of self-efficacy theory of behavioral change. Cognitive therapy and research. 1977; 1(4):287–310. 10.1007/bf01663995 [Google Scholar]

[pone.0311597.ref079] 79.Wang X, Yang H. Does the academic burden really get lighter the more it is reduced—A cross-sectional historical meta-analysis of secondary school students’ learning pressure. Shanghai Education Research. 2022; 10:24–30. https://doi.10.16194/j.cnki.31-1059/g4.2022.10.013 [Google Scholar]

[pone.0311597.ref080] 80.Usán Supervía P, Quílez Robres A. Emotional regulation and academic performance in the academic context: The mediating role of self-efficacy in secondary education students. International Journal of Environmental Research and Public Health. 2021; 18(11): 5715. 10.3390/ijerph18115715 doi: 10.3390/ijerph18115715 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311597.ref081] 81.Qureshi MA, Khaskheli A, Qureshi JA, Raza SA, Yousufi SQ. Factors affecting students’ learning performance through collaborative learning and engagement. Interactive Learning Environments. 2023; 31(4):2371–2391. 10.1080/10494820.2021.1884886 [Google Scholar]

[pone.0311597.ref082] 82.Wang MT, Holcombe R. Adolescents’ perceptions of school environment, engagement, and academic achievement in middle school. American Educational Research Journal. 2010; 47(3):633–662. 10.3102/0002831209361209 [Google Scholar]

[pone.0311597.ref083] 83.Chen JJL. Relation of academic support from parents, teachers, and peers to Hong Kong adolescents’ academic achievement: The mediating role of academic engagement. Genetic, social, and general psychology monographs. 2005; 131(2):77–127. 10.3200/mono.131.2.77-127 doi: 10.3200/MONO.131.2.77-127 [DOI] [PubMed] [Google Scholar]

[pone.0311597.ref084] 84.Jelas ZM, Azman N, Zulnaidi H, Ahmad NA. Learning support and academic achievement among Malaysian adolescents: The mediating role of student engagement. Learning Environments Research. 2016; 19:221–240. 10.1007/s10984-015-9202-5 [Google Scholar]

[pone.0311597.ref085] 85.Safaee M, Rezaei A, Talepasand S. Predict academic performance based on family support, friends support and others support: The mediating role of academic self-efficacy, academic resilience and academic engagement. Educational Psychology. 2019; 15(52):239–268. 10.22054/jep.2019.41526.2658 [Google Scholar]

[pone.0311597.ref086] 86.Chen Y. The effect of thematic video-based instruction on learning and motivation in e-learning. International Journal of the Physical Sciences. 2012; 7(6): 957–965. 10.5897/IJPS11.1788 [Google Scholar]

PERMALINK

The effect of social support on academic performance among adolescents: The chain mediating roles of self-efficacy and learning engagement

Xiangping Zhang

Wensheng Qian

Roles

Abstract

Purpose

Method

Results

Practical implications

Originality

Introduction

Literature review

Social support and academic performance

Self-efficacy as a mediator

Learning engagement as a mediator

Fig 1. The theoretical model.

Materials and methods

Sampling and data collection

Sample characteristics

Table 2. Reliability and validity.

Questionnaire design

Table 1. Potential variables and measurement items.

Statistical analysis

Results

Common method variance

Measurement model

Table 3. Discriminate validity examination.

Table 4. Heterotrait-Monotrait ration (HTMT).

Table 5. Coefficient of determination R2 variance inflation factor.

Structural model

Fig 2. The structure modeling diagram.

Analyzing the mediation of social support on academic performance

Table 6. Total, direct, and indirect effects of the theoretical model.

Discussion

Direct effects analysis

Indirect effects analysis

Chain mediator effect

Conclusion

Theoretical implication

Practical implication

Limitations and further research

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Ehsan Namaziandost

Roles

Author response to Decision Letter 0

Decision Letter 1

Ehsan Namaziandost

Roles

Author response to Decision Letter 1

Decision Letter 2

Ehsan Namaziandost

Roles

Acceptance letter

Ehsan Namaziandost

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases