The Impact of Media Dependence and Critical Thinking on College Students’ Media Literacy and Satisfaction: Evidence Based on SEM

Abstract

With the popularization of digital media in higher education, improving college students’ media literacy and satisfaction has become an important goal of education reform. Based on 1,091 questionnaire survey data from Shandong universities in China, this paper systematically explores the impact mechanism of media dependence and critical thinking on college students’ media literacy and media satisfaction using structural equation modeling (SEM). The results show that: (1) both media dependence and critical thinking positively predict media literacy, among which critical thinking has a more significant effect; (2) media literacy has a significant positive impact on media satisfaction, and plays a partial mediating role in the path between media dependence and critical thinking and satisfaction; (3) multi-group analysis shows that the model is structurally stable across gender, grade and other groups. This study expands the theory of media literacy, emphasizes the importance of critical thinking education, and provides empirical evidence for the construction of media literacy courses and the formulation of education policies in colleges and universities.

Plain Language Summary

Critical Thinking: The Key to Student Satisfaction in the Digital Age

Why the study was done College students constantly use digital media for learning and their social lives. But it’s not clear what leads to a better media experience: is it more important to use media frequently, or to be able to think critically about the information presented? This study wanted to see how media dependence and critical thinking work together to affect students’ media skills (literacy) and their happiness with media (satisfaction). How the study was done Researchers surveyed 1,091 students from five universities in Shandong, China. The survey asked them about their media habits, their critical thinking abilities, their skills in understanding and using media (media literacy), and their overall satisfaction with the media they consume. What the study found the results showed that both relying on media and thinking critically helped improve students’ media skills. However, critical thinking had a much stronger and more significant positive effect on media skills than media dependence did. Students with higher media skills were also much more satisfied with their media experiences. In short, critical thinking improves media skills, and those improved skills, in turn, lead to greater satisfaction in a positive loop. What this means the main takeaway from this research is that for college students, developing critical thinking skills is the key to having a better, more satisfying relationship with digital media. The study suggests that universities should focus on teaching students how to analyze and question information, which is more effective at helping them successfully navigate the digital world and improve their well-being than simply relying on media use alone.

Keywords

media dependence critical thinking media literacy media satisfaction structural equation modeling higher education

Introduction

With the rapid development of digital media technology, the application of digital media in higher education has become an important direction of global education reform and innovation (Gidion et al., 2015; Gomez-Galan, 2018; Jacobson et al., 2019). The learning, communication, resource acquisition and knowledge production of college teachers and students are increasingly dependent on multiple digital media platforms (McLean et al., 2023; Tran-Duong, 2023). This trend has not only changed the educational ecology, but also put forward a new goal of talent training, namely to improve college students’ media literacy, critical thinking and media satisfaction (Okela, 2024; Shieh & Nasongkhla, 2024).

College students’ media literacy and media satisfaction have become important indicators for measuring the level of information technology in higher education and the comprehensive ability of talents. High media literacy helps college students to rationally discern information, effectively express themselves, participate in public affairs, and maintain a high level of media satisfaction and happiness in the context of information explosion and frequent false information (Austin et al., 2021; Hobbs, 2017; Martens & Hobbs, 2015). At the same time, a high level of media satisfaction not only reflects students’ positive evaluation of the digital education environment and media resources, but is also a key factor in measuring the effectiveness of higher education informatization and improving students’ online learning experience and participation. However, over-reliance on digital media or lack of critical thinking skills may lead to information anxiety, decreased satisfaction, and even fall into the trap of media manipulation and false information (Dame Adjin-Tettey, 2022; Jeong et al., 2012; Kahne & Bowyer, 2017).

Current research focuses on the single relationship between media literacy, critical thinking or satisfaction. There is still a lack of systematic empirical analysis on the structural mechanism and path relationship between the three, especially how media dependence and critical thinking jointly affect media literacy and satisfaction (Jabarian & Sartori, 2023; Martens, 2010; Okela, 2024). In addition, the application of structural equation modeling (SEM) in the field of educational technology and media literacy still needs to be further expanded (Robertson & Ortgies-Young, 2023; Tran-Duong, 2023).

Therefore, this paper aims to systematically examine the impact mechanism of media dependence and critical thinking on college students’ media literacy and satisfaction based on the structural equation model. The core research questions include: (1) How does media dependence affect college students’ media literacy and satisfaction? (2) What is the mechanism of critical thinking in the above relationship? (3) Does media literacy play a mediating role between media dependence, critical thinking and satisfaction? This paper innovatively combines a large sample questionnaire with a SEM model to fill the existing theoretical gap and provide empirical support for educational practice.

Literature Review and Hypotheses Development

Media Dependence and Media Literacy

Media System Dependency Theory (MSDT) posits that individuals rely on media to satisfy needs related to orientation, understanding, and entertainment, and that higher dependence on media systems increases the influence of media on users’ cognitive and behavioral outcomes. When individuals frequently engage with digital platforms, they are exposed to a wide variety of multimedia content, interactive tools, and information environments that require decoding, evaluation, and synthesis. This frequent engagement fosters opportunities to develop media-related competencies—including information search, source evaluation, content critique, and responsible participation—which constitute core components of media literacy (Hobbs, 2017; Martens, 2010).

Empirical studies show that higher levels of media engagement promote the acquisition of media literacy skills by creating continuous exposure to digital content and requiring users to interpret, judge, and integrate information from diverse sources (Jeong et al., 2012; Okela, 2024). Moreover, increased contact with media environments encourages users to develop analytic skills to manage biases, misinformation, and persuasive messaging, enhancing their capacity for effective media use (Austin et al., 2021). Thus, stronger media dependence can facilitate the development of media knowledge, critical interpretation skills, and awareness of digital risks and opportunities.

Based on theoretical expectations and empirical findings, the following hypothesis is proposed:

H1: Media dependence has a positive effect on media literacy.

Critical Thinking and Media Literacy

Critical thinking is broadly defined as a set of analytical, evaluative, and reflective skills that enable individuals to interpret information objectively, identify biases, recognize logical fallacies, and make reasoned judgments. Scholars argue that critical thinking forms the cognitive foundation of media literacy because evaluating media content requires the ability to analyze claims, verify credibility, question assumptions, and reflect on intentions behind messages (Jacobson et al., 2019; Martens & Hobbs, 2015).

Empirical evidence also shows that individuals with higher critical thinking skills are more capable of resisting misinformation, engaging in deeper evaluation of digital content, and participating in responsible online behaviors (Dame Adjin-Tettey, 2022; Kahne & Bowyer, 2017). Critical thinking enhances one’s ability to decode media messages, detect manipulation, and contextualize information, thereby improving media literacy performance such as accurate information processing, informed media participation, and responsible digital citizenship (Robertson & Ortgies-Young, 2023).

Therefore, critical thinking is expected to be a strong antecedent of media literacy, forming the cognitive basis through which individuals effectively navigate digital environments.

H2: Critical thinking has a positive effect on media literacy.

Media Dependence and Media Satisfaction

According to the Uses and Gratifications Theory, individuals use media to satisfy various informational, emotional, and social needs. When media provide content that aligns with users’ expectations—such as high-quality information, convenience, and social interaction—users are more likely to experience higher satisfaction. Stronger media dependence typically indicates frequent use and deeper engagement with media activities, which may lead to more positive experiences and greater satisfaction if the media consistently meet users’ needs (Gidion et al., 2015; Shieh & Nasongkhla, 2024).

Empirical studies show that when individuals regularly use digital platforms for learning, communication, or entertainment, their familiarity with interfaces and content formats enhances comfort and perceived usefulness, contributing to positive satisfaction outcomes (Awedh et al., 2015). Regular engagement strengthens users’ expectations that media will effectively support their goals, thereby reinforcing satisfaction through perceived utility and effectiveness.

Thus, individuals who depend more on media are likely to report higher levels of media satisfaction due to increased opportunities for need fulfillment and smoother user experiences.

H3: Media dependence has a positive effect on media satisfaction.

Critical Thinking and Media Satisfaction

Critical thinking enhances individuals’ ability to process media messages accurately, manage information overload, and evaluate the credibility and relevance of digital content. When users possess strong analytical and evaluative skills, they are more capable of identifying high-quality information and filtering out misleading or low-value content. This selective and purposeful engagement tends to increase perceived usefulness and satisfaction with media experiences (McLean et al., 2023).

Furthermore, critical thinkers are more adaptable in digital contexts, as they approach media use with greater autonomy, awareness, and control. They are better able to regulate their expectations, recognize persuasive intent, and construct meaningful interpretations (Martens & Hobbs, 2015). These cognitive advantages lead to smoother interactions with digital platforms and higher satisfaction with learning, communication, and media participation (Gomez-Galan, 2018).

Therefore, individuals with higher levels of critical thinking are more likely to experience positive media interactions and report higher satisfaction.

H4: Critical thinking has a positive effect on media satisfaction.

Media Literacy as a Mediator

Media literacy enables individuals to access, analyze, evaluate, and create media content effectively. It represents a critical mechanism through which media dependence and critical thinking translate into users’ satisfaction with media use. From the perspective of cognitive processing theories, media literacy shapes how individuals interpret media messages, assess content quality, and interact with digital tools. Higher levels of media literacy allow users to filter information efficiently, identify credible sources, and navigate complex digital environments, which in turn enhances satisfaction with media activities (Jeong et al., 2012; Tran-Duong, 2023).

For media dependence, users who frequently engage with media and develop literacy skills are better able to make sense of diverse content, avoid misinformation, and achieve personal goals, thereby improving satisfaction with media experiences. For critical thinking, media literacy operationalizes analytical and evaluative abilities into practical media competencies—such as interpretation, verification, and content creation—which directly contribute to more meaningful and satisfying media interactions (Austin et al., 2021).

Therefore, media literacy is expected to function as the cognitive and behavioral pathway linking media dependence and critical thinking to media satisfaction.

H5: Media literacy positively mediates the relationship between media dependence/critical thinking and media satisfaction.

Based on the above hypotheses (H1–H5), the theoretical structural model of this study is constructed. The relationships among media dependence, critical thinking, media literacy, and media satisfaction are illustrated in Figure 1.

Figure 1.

Theoretical model path diagram (based on SEM assumptions).

Research Methods and Data Sources

Research Design and Implementation Process

This study adopts a cross-sectional quantitative survey method, with college students from five universities in Shandong Province, China as the subjects, to systematically examine the mechanism of media dependence and critical thinking on media literacy and media satisfaction. The research process includes six major steps: literature review, theoretical model construction, questionnaire preparation and pre-testing, formal data collection, data cleaning and analysis, and result interpretation (Gidion et al., 2015; Tran-Duong, 2023).

Sample and Data Source

The sample of this study comes from college students in five universities in Shandong Province. Stratified random sampling is used to cover different grades, majors, and genders. A total of 1,150 questionnaires were distributed, and 1,091 valid questionnaires were collected (effective collection rate 94.9%). Males accounted for 45.1% of the sample and females accounted for 54.9%; the grade distribution ranged from freshman to senior year, and the majors covered liberal arts, science and engineering, management, and art. Demographic variables include gender, grade, and major category attributes to ensure the representativeness and breadth of the sample (Jacobson et al., 2019; Okela, 2024).

Measurement Tools and Questionnaire Development

The research questionnaire consists of five parts: (1) Demographic information; (2) Media Dependency Scale; (3) Critical Thinking Scale; (4) Media Literacy Scale; and (5) Media Satisfaction Scale. Except for the demographic section, all scales used a five-point Likert scale (from 1 = Strongly Disagree to 5 = Strongly Agree).

To ensure the applicability and validity of the scales for Chinese university students, we conducted a rigorous cultural adaptation of the original instruments, which were based on well-established international scales. The adaptation process followed a translation-back-translation procedure. First, two communication scholars fluent in both Chinese and English independently translated the original scales into Chinese. The research team then compared and discussed these two versions to form a unified draft. Next, an English language expert who had not seen the original scales translated the Chinese draft back into English. Finally, this back-translated version was compared with the original scales to ensure semantic equivalence. Based on this, we invited three experts in the field of media literacy to evaluate the contextual appropriateness of the items for Chinese university students, and minor adjustments were made to the wording based on their feedback. All scales were pre-tested before the formal survey, and the results demonstrated good reliability and validity.

The specifics of each scale are as follows:

(1) Media Dependency Scale (MD): This scale was adapted from Gidion et al. (2015) with considerations for the Chinese context, containing four items. It aims to measure the extent of students’ reliance on digital media in their daily lives.

An example item is: “I would feel uneasy if I could not use media (e.g., mobile phone, computer, internet)”

(2) Critical Thinking Scale (CT): This scale was adapted from Martens and Hobbs (2015) and includes four items. It is designed to assess students’ ability to analyze, question, and discern media information.

An example item is: “I am used to raising questions when faced with media content”

(3) Media Literacy Scale (ML): This scale was developed based on the work of Okela (2024) and Tran-Duong (2023), consisting of four items. It aims to measure students’ comprehensive ability to identify, evaluate, utilize, and create media information, as well as to protect themselves online.

An example item is: “I can identify fake news and false information”

(4) Media Satisfaction Scale (MS): This scale was adapted from Jacobson et al. (2019) and contains four items. It is used to measure students’ overall satisfaction with their current media use experience.

An example item is: “I am satisfied with my current media use experience”

In both the pre-test and the formal data analysis, the Cronbach’s α reliability coefficients for all scales were greater than .90. The results of the KMO sampling adequacy test and Bartlett’s test of sphericity indicated that the questionnaire had good structural validity.

Data Collection Process and Ethical Statement

This study distributed electronic questionnaires through the “Wenjuanxing” platform from March to April 2025, and counselors from various universities assisted in organizing the questionnaires. All subjects gave informed consent and answered anonymously, and the filling time was kept at 5 to 8 min. Data collection strictly complies with the “Personal Information Protection Law of the People’s Republic of China” and the ethical review requirements of universities to ensure the information security and privacy of participants.

Data Analysis Strategy

This study used SPSS 26.0 and R 4.3.3 for data processing and statistical analysis. Specific strategies include:

(1) Descriptive statistics (mean, standard deviation, frequency, percentage) are used to describe the basic situation of samples and variables;

(2) Reliability analysis (Cronbach’s α) and structural validity test (KMO, Bartlett) ensure the quality of measurement tools;

(3) Correlation analysis (Pearson correlation) tests the preliminary relationship between variables;

(4) Structural equation modeling (SEM, lavaan/AMOS), estimates path coefficients and model fit, and analyzes mediation and direct effects (Jabarian & Sartori, 2023; Tran-Duong, 2023);

(5) Multi-group analysis (Multi-group SEM) tests the model stability of gender, grade and other groups. All statistical tests were two-sided, and the significance level was set at .05.

Construction Process of Structural Equation Modeling

This study uses structural equation modeling (SEM) to conduct a systematic modeling analysis of the relationship between media dependence, critical thinking, media literacy and media satisfaction. The specific modeling process is as follows:

Step 1: Theoretical Model Setting

Based on the literature review and theoretical assumptions, a structural equation model including four latent variables is constructed: media dependence, critical thinking, media literacy, and media satisfaction. Among them, media dependence and critical thinking are independent variables, media literacy is the mediating variable, and media satisfaction is the dependent variable, and the correlation between media dependence and critical thinking is allowed.

Each latent variable was measured by four self-report questionnaire items and scored using a five-point Likert scale. The reliability and validity of the measurement model were tested by confirmatory factor analysis (CFA) to ensure that each observed variable had a significant load on its corresponding latent variable (standardized factor loads were all greater than 0.7). For each latent variable, the observed variable was used to reflect it, as follows (taking ML as an example):

M L_{1} = λ_{M L_{1}} \cdot ML + ε_{M L_{1}}

M L_{2} = λ_{M L_{2}} \cdot ML + ε_{M L_{2}}

M L_{3} = λ_{M L_{3}} \cdot ML + ε_{M L_{3}}

M L_{4} = λ_{M L_{4}} \cdot ML + ε_{M L_{4}}

Among them, λ is the factor loading and ε is the measurement error.

Similar results are obtained for MD, CT, and MS.

Step 3: Structural Model Setting

Based on the measurement model, further set the path relationship between the latent variables:

(1) Media dependence, critical thinking → media literacy

ML = β_{1} \cdot MD + β_{2} \cdot CT + ξ_{1}

Where $β_{1}, β_{2}$ represents the direct effects of media dependence and critical thinking on media literacy, and $ξ_{1}$ is the structural disturbance term.

(2) Media dependence, critical thinking, media literacy → media satisfaction

MS = β_{3} \cdot MD + β_{4} \cdot CT + β_{5} \cdot ML + ξ_{2}

Among them, A $β_{1}, β_{2}$ represents the direct effects of media dependence, critical thinking and media literacy on media satisfaction, and $ξ_{1}$ is the structural disturbance term.

(3) Media dependence ↔ critical thinking

Allowing a covariate relationship between MD and CT:

cov (MD, CT) = ϕ

Step 4: Model Fit Test

Maximum likelihood estimation was used to estimate model parameters, and indicators such as $χ^{2} / df$ ,CFI, TLI, RMSEA, and SRMR were used to evaluate the model fit.

Step 5: Model Modification and Optimization

According to the model modification index (MI), necessary modifications are made to the measurement model to further improve the model fit.

Step 6: Path Coefficient Estimation and Effect Analysis

Under the final well-fitting model, estimate the standardized coefficient, standard error and significance level of each path. Further use the Bootstrap method to test the indirect effect, perform a significance test, and analyze the mechanism of action of the mediation path.

Indirect effects of media dependence:

MD \to ML \to MS : β_{1} \cdot β_{5}

Indirect effects of critical thinking:

CT \to ML \to MS : β_{2} \cdot β_{5}

The total effect of MS is the sum of direct effect and indirect effect:

Tota l_{MD \to MS} = β_{3} + β_{1} \cdot β_{5}

Tota l_{CT \to MS} = β_{4} + β_{2} \cdot β_{5}

Step 7: Multi-Group SEM Analysis

Multi-group SEM analysis was conducted for variables such as gender and grade to test the stability and applicability of the model structure among different groups. It mainly includes equality constraint test and path coefficient comparison to ensure that the model has good cross-group consistency.

Step 8: Interpretation and Visualization of Results

Combining the path coefficient table and the structural model path diagram, we will conduct an academic interpretation of the direct and indirect effects between the variables, and discuss the empirical findings in conjunction with the research hypotheses.

Empirical Results and Analysis

Descriptive Statistics and Reliability Analysis

Descriptive statistics were performed on 1,091 valid questionnaire data. The means and standard deviations of the main variables are as follows: media dependence (M = 3.29, SD = 1.07), critical thinking (M = 3.53, SD = 0.97), media literacy (M = 3.61, SD = 0.97), and media satisfaction (M = 3.66, SD = 0.99). The Cronbach’s α reliability coefficients of the four scales were .94, .95, .96, and .97, respectively, all greater than 0.9, indicating that the internal consistency of the scales was extremely high (McLean et al., 2023; Okela, 2024). The KMO values were all >0.80, and the Bartlett sphericity test was significant, indicating that the questionnaire had good structural validity.

Correlation Analysis of Each Dimension

The results of Pearson correlation analysis are shown in Table 1. There is a significant positive correlation between media dependence and critical thinking, media literacy, and media satisfaction (r = .53, .50, .53, p < .01). The correlations between critical thinking and media literacy and media satisfaction are .83 and .77, respectively, and the correlation between media literacy and media satisfaction is as high as .88 (p < .01). This shows that the variables are highly correlated, which provides a basis for structural equation modeling (Austin et al., 2021; Tran-Duong, 2023).

Table 1.

Pearson Correlation Coefficient.

Variable	MD	CT	ML	MS
MD	1	0.53	0.50	0.53
CT	0.53	1	0.83	0.77
ML	0.50	0.83	1	0.88
MS	0.53	0.77	0.88	1

Note. MD = media dependence; CT = critical thinking; ML = media literacy; MS = media satisfaction.

Structural Equation Model Fitting and Path Coefficients

The lavaan (or AMOS) software was used to perform structural equation modeling on the theoretical model. The model fit index was excellent ( $χ^{2} / df$ = 1.23, CFI = 0.999, TLI = 0.998, RMSEA = 0.013, SRMR = 0.005), and all indicators met the SEM goodness of fit requirements (Gidion et al., 2015; Jabarian & Sartori, 2023). The path coefficient (standardized) results are shown in Table 2.

Table 2.

Path Coefficients.

Path	Standardized coefficient β	Standard error	p-value	Significance
ML←MD	.22	0.04	<.001	***
ML←CT	.72	0.03	<.001	***
MS←MD	.10	0.04	=.012	*
MS←CT	.24	0.04	<.001	***
MS←ML	.60	0.03	<.001	***

Note. MD = media dependence; CT = critical thinking; ML = media literacy; MS = media satisfaction.

***

p < .001. *p < .05.

The model structure path diagram is shown in Figure 2.

Figure 2.

Model structure path diagram.

Analysis of Mediation Effect

The mediation effect analysis shows that media literacy plays a significant mediating role between media dependence and satisfaction, and between critical thinking and satisfaction. The indirect effects are as follows:

MD \to ML \to MS : 0.22 \times 0.60 = 0.132, p < . 001

CT \to ML \to MS : 0.72 \times 0.60 = 0.432, p < . 001

This shows that media literacy plays a partial mediating role in the path between media dependence and critical thinking and satisfaction, which is consistent with the mainstream international conclusions (McLean et al., 2023; Tran-Duong, 2023).

Multi-Group Comparison Results

Taking gender as an example, a multi-group SEM analysis was conducted. The model’s fit indexes in both male and female groups were good. The differences in the main path coefficients were not significant (e.g., ML←MD: male .20, female .23, p = .32), indicating that the model structure is robust across genders. Similarly, multi-group analysis by grade and major also showed good consistency in the model path structure, indicating that the theoretical model has strong universality (Jacobson et al., 2018; Robertson & Ortgies-Young, 2023).

Discussion

This study examined how media dependence and critical thinking influence college students’ media literacy and media satisfaction, and further explored the mediating role of media literacy. The findings provide theoretical and empirical insights into how cognitive skills and media engagement jointly shape users’ media experiences in contemporary digital environments. The discussion below connects the main findings to existing theories and prior literature, thereby situating the results within current scholarly understanding.

Media Dependence, Media Literacy, and Media Satisfaction

The positive influence of media dependence on media literacy confirms H1 and aligns with the Media System Dependency Theory (MSDT), which posits that individuals who frequently rely on media for orientation and understanding gradually develop more sophisticated interpretive and analytical skills. Consistent with prior studies suggesting that sustained media engagement promotes the acquisition of media competencies through repeated exposure to diverse content and information environments (Jeong et al., 2012; Okela, 2024), the present findings indicate that students who depend more on digital platforms develop higher literacy in evaluating messages, identifying credibility, and filtering media information. This suggests that media dependence facilitates experiential learning, enabling users to refine their media skills through practice and repeated interactions.

The results also show that media dependence has a direct positive effect on media satisfaction (H3), supporting the logic of Uses and Gratifications Theory. Users who depend more on media tend to experience frequent and personalized interactions with digital content, increasing the likelihood that media meet their informational, social, and emotional needs (Shieh & Nasongkhla, 2024). This finding corresponds with prior research showing that greater familiarity with digital tools and media content leads to smoother interactions and more satisfying experiences (Awedh et al., 2015). The positive relationship indicates that media dependence enhances students’ expectations that digital environments can effectively support learning and communication, thereby promoting satisfaction.

Critical Thinking as a Key Cognitive Antecedent of Media Literacy and Satisfaction

The results confirm that critical thinking significantly enhances media literacy (H2), in line with theoretical arguments that analytical and evaluative skills constitute the cognitive foundation of media literacy (Jacobson et al., 2019; Martens & Hobbs, 2015). Individuals with strong critical thinking skills are better equipped to assess the credibility of media messages, identify bias, analyze persuasive intent, and interpret information in a reflective and informed manner. The findings also echo empirical studies demonstrating that critical thinkers are more resilient against misinformation and more capable of engaging responsibly in digital environments (Dame Adjin-Tettey, 2022; Kahne & Bowyer, 2017). Thus, the evidence strengthens the view that critical thinking is a key driver of media literacy and should be treated as an essential cognitive capacity in media education frameworks.

Critical thinking also positively predicts media satisfaction (H4). This relationship can be understood through cognitive-processing theories: users with stronger analytical abilities are better able to organize information, manage information overload, and regulate their expectations when navigating digital media. These cognitive advantages lead to more meaningful and efficient media interactions, which in turn enhance satisfaction with digital experiences. The finding is consistent with studies indicating that critical thinking promotes greater autonomy, confidence, and control in media use (Gomez-Galan, 2018; McLean et al., 2023). In sum, students with higher critical thinking skills derive greater value from media because they can select, interpret, and apply information more effectively.

The Mediating Role of Media Literacy

The results reveal that media literacy significantly mediates the effects of media dependence and critical thinking on media satisfaction, confirming H5. This mediation is conceptually meaningful because media literacy translates both experiential engagement (media dependence) and cognitive abilities (critical thinking) into effective media practices. Students who frequently engage with media and who possess strong analytical skills are better able to navigate, evaluate, and utilize media content, leading to more satisfying experiences.

This finding aligns with previous research showing that media literacy enhances individuals’ ability to evaluate sources, detect misinformation, and interact responsibly in digital environments, all of which contribute to positive media experiences and learning outcomes (Austin et al., 2021; Jeong et al., 2012; Tran-Duong, 2023). The results also suggest that media literacy serves as a functional mechanism that operationalizes cognitive abilities and usage patterns into perceptual and emotional outcomes. By strengthening evaluation and interpretation skills, media literacy improves users’ sense of control and confidence in using media, thereby increasing satisfaction.

Notably, the mediating role of media literacy supports the argument that media literacy is not only an educational outcome but also a process variable connecting cognitive and behavioral antecedents to experiential results. This adds an important theoretical nuance to the media literacy literature by highlighting the mechanism through which cognitive skills and media behaviors influence digital well-being and satisfaction.

Integration With Current Understanding and Theoretical Contributions

The present findings extend and refine existing theoretical perspectives in several ways.

First, the study enriches MSDT and Uses and Gratifications Theory by demonstrating that media dependence does more than increase exposure—it contributes to the development of media literacy and enhances satisfaction through improved media competencies. This suggests that dependence should be conceptualized not only as a behavioral pattern but also as a potential catalyst for skill development.

Second, the findings provide strong empirical evidence that critical thinking is a foundational cognitive antecedent of media literacy and media satisfaction. While prior studies have emphasized the importance of critical thinking for resisting misinformation and promoting democratic engagement (Dame Adjin-Tettey, 2022; Kahne & Bowyer, 2017), this study demonstrates its broader relevance for personal media experiences and subjective satisfaction.

Third, the identification of media literacy as a mediating variable advances theoretical discussions by showing how cognitive abilities (critical thinking) and behavioral reliance on media (media dependence) translate into subjective outcomes. This mechanism-oriented contribution strengthens the conceptualization of media literacy as both a cognitive-behavioral competency and a pathway to experiential benefits.

Fourth, the results highlight the interplay between cognitive skills, behavioral engagement, and satisfaction in digital media environments. This integrated perspective contributes to a more holistic understanding of media use processes, bridging cognitive, behavioral, and experiential dimensions.

Collectively, these theoretical contributions address existing gaps in the literature, provide clearer causal pathways, and deepen our understanding of media literacy as both an antecedent and an outcome in digital contexts.

Conclusion

Summary of Main Findings

Drawing on a large sample of college students and using structural equation modeling, this study provides empirical evidence on how media dependence and critical thinking jointly shape media literacy and media satisfaction in contemporary digital environments. The findings demonstrate three important patterns.

First, media dependence and critical thinking both significantly enhance media literacy, indicating that experiential engagement with digital media and analytical cognitive abilities function as complementary antecedents. This supports the theoretical propositions of Media System Dependency Theory and contemporary media literacy frameworks, which emphasize the dual importance of media use behaviors and cognitive processing skills.

Second, both media dependence and critical thinking directly increase media satisfaction, suggesting that frequent and purposeful media engagement, paired with stronger analytical abilities, contribute to more meaningful and positive digital experiences. These results extend existing Uses and Gratifications perspectives by showing that satisfaction in digital learning environments is jointly shaped by behavioral and cognitive factors.

Third, media literacy plays a significant mediating role, transforming media dependence and critical thinking into higher satisfaction. This highlights media literacy as a mechanism through which students translate experiential exposure and cognitive skills into improved media evaluation, interaction, and outcomes. The overall model shows strong explanatory power and good fit, confirming the applicability of media literacy theory and related cognitive-behavioral models to higher education digital contexts.

Together, these findings deepen the theoretical understanding of how media-related skills and behaviors interact, and they offer a more integrated view of the cognitive–behavioral pathways underlying students’ digital media experiences.

Implications for University Practice and Policy

The results provide several practical implications for universities, educators, and policymakers seeking to enhance students’ digital competence and overall media wellbeing.

First, universities should systematically integrate media literacy and critical thinking training into formal curricula, general education requirements, or interdisciplinary programs. Given their central role in shaping students’ media experiences, these competencies should be treated as core components of talent cultivation systems rather than supplementary skills.

Second, universities should establish clearer digital media use guidelines and evaluation systems, promoting responsible, healthy, and ethical media use. This includes offering workshops on misinformation detection, digital citizenship, emotional regulation in digital environments, and sustainable media habits.

Third, educators should create learning environments that encourage reflective media engagement, including case-based analysis, inquiry-driven learning, and collaborative evaluation of digital information. These pedagogical approaches can help students transform critical thinking skills into practical media literacy competencies.

Fourth, policymakers should increase institutional and financial support for digital literacy initiatives, fostering collaborations among universities, industry partners, and government agencies. Interdisciplinary and school–enterprise cooperation can expand access to high-quality digital resources and cultivate students’ ability to navigate the challenges of an increasingly complex information society.

By strengthening cognitive abilities, media use norms, and institutional support systems, universities can enhance students’ capacity to participate effectively in the digital era and contribute to the high-quality development of China’s digital education and broader information society.

Limitations and Future Research

Several limitations should be acknowledged. First, the study adopted a cross-sectional survey design; although SEM provides evidence for the plausibility of the proposed pathways, causal inferences remain limited. Future studies may employ longitudinal or experimental designs to better capture temporal dynamics and strengthen causal interpretation. Second, all variables were measured using self-reported questionnaires collected at a single time point, which may introduce common method bias and social desirability effects. Future research could incorporate multi-source or behavioral data (e.g., digital trace data, learning analytics, or teacher evaluations) to improve measurement robustness. Third, the sample was drawn from five universities in Shandong Province, China; therefore, the generalizability of the findings to other regions, educational contexts, or cultural settings should be examined through broader and cross-cultural replications. Finally, the current model focuses on media dependence, critical thinking, media literacy, and satisfaction. Future research may extend the framework by considering additional mechanisms and boundary conditions, such as information overload, media anxiety, platform-specific use patterns, and individual or contextual moderators, to develop a more nuanced understanding of students’ digital media experiences.

Footnotes

Acknowledgements

The authors would like to thank all the participants from the universities for their valuable time and input in completing the survey. The authors also appreciate the support of university faculty and administrative staff who facilitated data collection. No specific funding was received for this work.

ORCID iDs

Li’e Miao

Tao Li

Ethical Considerations

This study was conducted in full compliance with established ethical standards for research involving human participants. All data collection procedures adhered to the Personal Information Protection Law of the People's Republic of China and followed the ethical review requirements of the participating universities. Special care was taken to ensure the privacy, confidentiality, and security of all collected information. The survey was administered anonymously, and no personally identifiable information was collected or stored at any stage of the research process.

Consent to Participate

Informed consent was obtained from all participants prior to their involvement in the study. Participants were clearly informed of the research purpose, procedures, and their rights as respondents. They were assured that participation was entirely voluntary and that they could withdraw from the study at any time without any negative consequences. Consent was considered to have been granted when participants voluntarily completed and submitted the online questionnaire.

Author Contributions

Conceptualization: Li’e Miao, Tao Li. Methodology: Tao Li. Data curation: Li’e Miao, Tao Li. Formal analysis: Li’e Miao, Tao Li. Visualization: Tao Li, Li’e Miao. Writing – original draft: Li’e Miao, Tao Li. Writing – review & editing: Li’e Miao.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Shandong Provincial Department of Education under the 2022 Undergraduate Teaching Reform Research Project of Shandong Province (Project No. M2022047), titled “Innovative Practice of Ideological and Political Education Reform Promoted by the Integrated Media Matrix in Colleges and Universities: One Core Leadership, Three Array Integration, and Circle Interaction.”

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.*

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