Abstract

The relationship between the mental health and academic achievement of college students is not only related to their individual growth and development but also has a profound impact on the quality of higher education and the cultivation of social talent. Understanding the interaction and influencing mechanisms between mental health and academic achievement can help individuals adjust learning and psychological states and achieve a virtuous cycle between mental health and academic achievement. A survey was conducted on 3871 freshmen using the Symptom Check-List-90 (SCL-90), Academic Self-efficacy Scale (ASES), China College Student Adjustment Scale (CCSAS), and basic quality assessment scores. The results showed that (1) Mental health is significantly correlated with learning adaptation, academic self-efficacy, and academic achievement, and mental health can significantly negatively predict academic achievement; (2) Learning adaptation partially mediates the relationship between mental health and academic self-efficacy; Academic self-efficacy plays a complete mediating role between mental health and academic achievement; (3) Learning adaptation and academic self-efficacy play a chain mediated role between mental health and academic achievement. Therefore, schools can enhance the cultivation of students鈥� psychological qualities, cultivate their adaptability to changes in learning environments and learning methods, and systematically enhance the cultivation of students鈥� academic self-efficacy to improve their academic achievements.

Introduction

In today鈥檚 rapidly changing social environment, the relationship between the mental health and academic achievements of college students is receiving increasing attention [1, 2]. This relationship is not only related to the growth and development of individual students but also has a profound impact on the quality of education in colleges and universities and the cultivation of talent in society [3]. Academic performance refers to the learning outcomes students achieve after each stage of their study. Due to its complexity and dynamism, there is no consensus in the academic community on its definition. Despite varying standards, academic performance is generally classified into five categories: knowledge-based, skill-based, grade-based, career-oriented, and intention- and persistence-oriented [4]. Most scholars consider academic performance to be a critical indicator of a student鈥檚 learning outcomes. Usually, teachers check students鈥� learning achievements through phased testing or continuous evaluation [5]. Academic achievement in this study refers to the basic quality assessment results of learners during their time in school, which refers to the comprehensive evaluation of students鈥� academic performance in the prescribed teaching courses of the school and the general quality evaluation in terms of morality, intelligence, physical fitness, and aesthetics formed in the second classroom. College students are faced with various pressures from their studies [6], employment [7], and interpersonal relationships [8], which may have adverse effects on their mental health. Academic workload stress may lead to psychological issues such as anxiety and depression among students, which in turn can affect their learning efficiency and academic performance [9]. Moreover, mental health issues may also hinder students from fully realizing their potential and limit their academic achievements [10]. Therefore, exploring the relationship between mental health and academic achievement among college students is of crucial importance. By understanding the interaction and impact mechanism between the mental health and academic achievement, universities and educators can better focus on the holistic development of students and implement targeted educational and support measures. At the same time, it also helps students better understand themselves, adjust their learning and psychological states, achieve a virtuous cycle of academic achievement and mental health [11], and more importantly, interrupt the transmission of poverty from generation to generation [12].

When reviewing and summarizing existing research, we paid special attention to studies on Chinese university student populations. These studies have explored the performance and changes of university students in terms of academic performance, self-efficacy, and self-esteem from multiple angles and levels. Specifically, the academic performance, self-efficacy, and self-esteem of college students are not static, but exhibit dynamic changes with personal growth and external environmental changes [13,14,15]. With the rapid development and transformation of society, college students are facing multiple unprecedented pressures, which not only stem from academic performance but also encompass employment [7], interpersonal relationships [8], social cognitive career development [16], and the realization of self-worth [17]. The occurrence and development of psychological problems will have a great impact on students鈥� academic performance. As a core component of university life, academic performance not only reflects the level of knowledge mastery of students but also reflects their comprehensive qualities and abilities [4]. However, when psychological problems quietly arise, they silently erode the academic foundation of students, leading to decreased learning efficiency, a lack of concentration, slow thinking, and other problems, which in turn affect academic performance [1]. Murphy, et al. [18] conducted a study with 37,397 primary school students as participants, and the results indicated that mental health is an important predictor of future academic achievements. Research conducted by Suldo, et al. [19] showed that subjective well-being predicted the grade point average (GPA) of 300 middle school students one year later. In a study with 510 health science majors as subjects, Hamaideh and Hamdan-Mansour [20] reported that achievement motivation, aptitude, and depression levels were the best predictors of academic performance. Therefore, this study proposes Hypothesis 1: mental health has a predictive effect on students鈥� academic achievement.

Learning adaptation, as an important factor for measuring students鈥� adaptability to learning and development, mainly refers to the psychological and behavioral process through which the subject can actively adjust itself according to the learning environment and learning needs to achieve a balance with the learning environment [21]. Investigating the learning adaptability of college students is crucial, particularly for freshmen, as it significantly impacts their academic progress and overall well-being. Studies on adaptation and academic performance reveal a strong correlation between students鈥� social, learning, and psychological adaptability and their academic outcomes. Social adaptation, learning adaptation, and psychological adaptation can significantly affect students鈥� academic performance [22, 23]. The degree of academic adaptation is closely related to factors such as personality activity level and emotionality [24]. Meanwhile, studies have also found academic performance was positively correlated to academic self-efficacy [25], interpersonal relationships and learning adaptability also have a significant impact on the academic achievement of college students [26], and improving the learning adaptation level of new students can help improve academic performance [27]. Therefore, hypothesis 2 is proposed: learning adaptation plays a mediating role between mental health and academic achievement.

Self-efficacy refers to people鈥檚 belief in their ability to organize and implement the action processes required to achieve specific goals [28]. Academic self-efficacy pertains to its utilization and execution in the realm of academics. Different intensities of academic self-efficacy can lead individuals to exhibit positive learning behaviors of different intensities when completing academic tasks, thereby affecting the completion of academic tasks [29]. Research on foreign language learning has also shown that self-efficacy can effectively predict foreign language learning outcomes [30]. With respect to academic self-efficacy, some studies have shown a significant partial mediating effect between positive academic emotions and mastery goal orientation in college students [31], and self-efficacy plays a mediating role between self-identity and achievement motivation [32], which in turn affects academic achievement. Therefore, hypothesis 3 is proposed: academic self-efficacy plays a mediating role between mental health and academic achievement.

Previous studies have shown a positive correlation between academic adaptation and academic self-efficacy, and academic adaptation has a significant positive impact on academic self-efficacy [33]. Specifically, when students can effectively adapt to the learning environment and tasks, they are more likely to achieve academic success. And these successful experiences will enhance students鈥� confidence, making them believe that they could cope with future learning challenges, thereby improving their academic self-efficacy. It is generally believed that both intellectual and nonintelligence factors can affect an individual鈥檚 academic achievement level [34], and both factors can jointly influence and predict a student鈥檚 academic achievement. However, generally speaking, the difference in intelligence levels among most people is not significant, and in this case, nonintelligence factors such as emotional intelligence can have a greater impact on an individual鈥檚 academic achievement [35]. Related studies have shown that self-efficacy, intrinsic motivation, learning strategies, and academic achievement are significantly positively correlated, while extrinsic motivation and performance goals are significantly negatively correlated [36]. Some scholars have also used average indicators to measure students鈥� academic achievement, but research has shown that the emotional intelligence and self-esteem of college students do not have an impact on their academic achievement [37], while self-efficacy has a significant positive impact on academic achievement [38]. Both learning motivation and learning strategies have a certain impact on students鈥� academic achievement [39]. Related studies have shown a certain correlation between self-efficacy and mental health levels [40, 41]. Further research has revealed significant positive correlations between proactive personality, academic performance, academic adaptation, and academic self-efficacy, and academic self-efficacy plays a fully mediating role in the impact of proactive personality on academic performance [25]. Therefore, Hypothesis 4 is proposed: Learning adaptation and academic self-efficacy play a chain mediating role between mental health and academic achievement.

By reviewing and analyzing the literature, this study proposes four hypotheses for verification (as shown in Fig.听1): (1) Mental health has a predictive effect on student academic achievement; (2) Learning adaptation plays a mediating role between mental health and academic achievement; (3) Academic self-efficacy plays a mediating role between mental health and academic achievement; and (4) Learning adaptation and academic self-efficacy play a chain mediating role between mental health and academic achievement.

Fig. 1

Conceptual framework diagram

Method

Participants

Firstly, this study strictly adheres to the Helsinki Declaration, and all methods are implemented in accordance with relevant guidelines and regulations. Secondly, this study has been approved by the committee of the Hebei Petroleum University of Technology. Finally, all participants voluntarily provided informed and written consent, indicating their willingness to participate and support the study.

Freshman students from a higher vocational college in Hebei Province were selected as the research subjects. All participants were informed of the purpose of the study after recruitment, and if they did not agree to use the data, they could choose to withdraw from the study at any time. For the exclusion of invalid questionnaires, the following steps were taken: (1) Clarify the definition of invalid questionnaires, which are those that cannot be analyzed normally due to incomplete filling, obvious illogical answers, or other obvious errors. (2) A preliminary screening was conducted on all collected questionnaires, excluding those with obvious missing or incorrect information (such as age 68). (3) Further logical and consistency checks were conducted on the remaining questionnaires, excluding those whose answers were clearly illogical or had obvious contradictions. (4) All questionnaires were subjected to data cleaning and outlier handling to ensure the quality and reliability of the final questionnaire data used for analysis. Finally, we obtained 3871 valid questionnaires, including 2830 males (73.1%) and 1041 females (26.9%); There are 3044 people (78.6%) from rural areas and 823 people (21.3%) from urban areas; The age range is between 17 and 20 years old, with an average age of 18.17鈥壜扁��0.85 years old (see Table听1).

Table 1 Demographic information of variables (N鈥�=鈥�3871)

Measures

The symptom checklist-90 (SCL-90)

The Symptom Checklist-90 (SCL-90), initially revised and customized by Derogatis and Cleary [42], has undergone a preliminary analysis by Jin, et al. [43] and colleagues on the results of 1,388 adults in China. Based on this analysis, they established norms for the Chinese population. The SCL-90 has since gained widespread research and application in China. The scale uses 10 factors, including somatization, anxiety, obsessive-compulsive, depression, interpersonal sensitivity, psychotism, paranoia, hostility, phobic anxiety, and others, to reflect the psychological symptoms of students in 10 aspects. The severity is divided into 5 levels from 鈥�1鈥� (asymptomatic) to 鈥�5鈥� (extremely severe), and the total score of the sum of 90 individual scores in the scale can indicate the severity of students鈥� psychological symptoms. This study used the total SCL-90 score as a mental health indicator; the higher the score was, the more psychological problems the test subjects had, and the corresponding level of mental health was lower. The alpha coefficient of the SCL-90 among Chinese university students is 0.98, the construct validity of SCL-90 performs well (CFI鈥�=鈥�0.999, RMSEA鈥�=鈥�0.029) [44].

Academic self-efficacy scale (ASES)

The scale developed by Liang [45] was used to measure self-efficacy in learning ability and self-efficacy in learning behavior. Each dimension has 11 items, totaling 22 items. The scale adopts a 5-point scoring system, where 鈥�1鈥� represents 鈥渃ompletely inconsistent鈥� and 鈥�5鈥� means 鈥渇ully compliant鈥�. The total score for each dimension is obtained by adding up all items within each dimension. The higher the score is, the greater the corresponding efficiency. The two-dimensional alpha coefficients were 0.82 and 0.752, respectively, indicating good reliability Liang [45], and these two factors can explain 85.6% of the total variation, indicating that the questionnaire has good reliability and validity.

China college student adjustment scale (CCSAS)

The China College Student Adjustment Scale was developed by Fang, et al. [46] and mainly includes 7 dimensions鈥攍earning adaptation, campus life adaptation, interpersonal relationship adaptation, emotional adaptation, self-adaptation, career adaptation, and satisfaction鈥攆or a total of 60 items. The scale adopts a 5-point scoring system ranging from 1 (disagree) to 5 (agree), and the higher the score is, the better the adaptation to the current situation. The alpha coefficient ranges from 0.65 to 0.93, and the retest reliability ranges from 0.96 to 1.00 [46], the structural validity of the scale was analyzed using exploratory factor analysis, and it was found that the factor loadings of all items were above 0.45, and the cumulative explanatory power of each dimension exceeded 42%. This study only extracted learning adaptation dimensions for testing.

Academic achievement

The basic quality assessment scores from the comprehensive quality assessment of students in the past semester were selected as indicators of their academic achievement (see Fig.听2 for details). As a comprehensive, standardized, and scientific evaluation system for the quality development of students in this higher vocational college, comprehensive quality evaluation mainly adopts a combination of recording and evaluation, quantitative and qualitative methods to comprehensively evaluate the quality of students in school, downplaying their identity and innate talents, emphasizing the importance of learning, and encouraging students to highlight their individuality and develop comprehensively in morality, intelligence, physical fitness, and aesthetics while meeting the basic requirements of the university. Comprehensive quality evaluation mainly includes basic and developmental qualities, among which basic qualities refer to the general qualities formed by students in terms of ideology, culture, and learning in the teaching and second classroom stipulated by the school, while developmental qualities refer to the qualities formed by students in the school education process that can reflect innovation ability, application skills, practical skills, and other innovative practical aspects. Because developmental quality evaluation is only used to locally adjust the evaluation level of scholarships, it is not currently included in the research scope.

Fig. 2

Process diagram of the comprehensive assessment of academic achievement

Procedure

After one month of enrollment in the first semester, all first-year psychological commissioners will be trained as the main examiners to familiarize themselves with the methods of using mobile phones to access the 鈥淢ental Health Cloud Platform鈥�, as well as the questionnaire guidance and testing process. During the formal testing, the main participant first read out the instructions and only started answering after confirming that all participants understood. The participants were tested using the SCL-90, ASES, and CCSAS. At the end of the first semester, the basic quality evaluation scores of all test subjects were exported from the comprehensive evaluation system.

Data analysis

The data used in this study is all sourced from the School Mental Health Assessment Center, which is responsible for regularly collecting and managing the mental health assessment results of all students in the school. In the data preprocessing stage, we carefully examined the dataset and confirmed that all records were complete and without any missing values. This study used Excel 2016 to input the data, SPSS 19.0 to calculate the means and standard deviations of the variables, Pearson correlation to calculate the correlation coefficients between variables, and regression analysis of the relationships between variables. The bootstrap method was used to estimate the confidence interval of the mediation path coefficient. A structural equation model was constructed and validated using Amos 21.0.

Results

Common method bias

Except for academic achievement, which was measured objectively, all other variables in this study were collected using self-report scales, which may lead to common method bias. Therefore, through Harman鈥檚 single factor test, there were a total of 13 factors with eigenvalues greater than 1. The first factor explained 32.591% of the variance, which did not reach the critical value of 40%, indicating that the common method bias phenomenon was not severe.

Correlation and regression analysis of research variables

To study the relationships among student mental health, learning adaptation, academic self-efficacy, and academic achievement, a correlation analysis was conducted on the four variables. The descriptive results and correlation coefficients between each variable are shown in Table听2. Mental health (SCL-90 total score) was significantly negatively correlated with learning adaptation, academic self-efficacy, and academic achievement; learning adaptation was significantly positively correlated with academic self-efficacy and academic achievement; and academic self-efficacy was significantly positively correlated with academic achievement.

Table 2 Analysis of the correlation between mental health, learning adaptation, academic self-efficacy, and academic achievement (N鈥�=鈥�3871)

After conducting regression analysis with mental health as the independent variable and academic achievement as the dependent variable, it was found that mental health issues can significantly negatively predict academic achievement (尾=-0.012, t=-2.298, p鈥�&濒迟;鈥�0.05).

The chain mediation model test

The data were standardized using SPSS, a bootstrap mediation variable test was conducted, a sample size of 5000 was selected, and a 95% confidence interval was set. The data (Table听3) indicate that the overall effect of mental health prediction on academic achievement is significant (the confidence interval does not include 0), with a magnitude of -0.039. The confidence interval for 鈥渕ental health 鈫抣earning adaptation鈫� academic achievement鈥� is 0, indicating that the mediating path of learning adaptation is not significant. The confidence interval of 鈥渕ental health 鈫抋cademic self-efficacy 鈫抋cademic achievement鈥� does not include 0, and the mediating path is significant with a magnitude of -0.002, indicating that academic self-efficacy plays a mediating role between mental health and academic achievement. The confidence interval of 鈥渕ental health 鈫� learning adaptation 鈫� academic self-efficacy 鈫� academic achievement鈥� does not include 0, and the mediating path is significant, with a magnitude of -0.016, accounting for 40.57% of the total effect. That is, learning adaptation and academic self-efficacy play a chain mediating role between mental health and academic achievement, and mental health can affect the academic achievement of college students by influencing learning adaptation and academic self-efficacy.

Table 3 Mediation effect test

A structural equation model was constructed using Amos 21.0 for further validation. The initial model, which is a saturated model, is shown in Fig.听3(a). After removing insignificant paths, the modified model is shown in Fig.听3(b). The modified fitting index is shown in Table听4, and the overall fitting index is good. Mental health negatively predicted learning adaptation (尾=-0.29, p鈥�<鈥�0.001) and academic self-efficacy (尾=-0.03, p鈥�<鈥�0.01). Learning adaptation positively predicted academic self-efficacy (尾鈥�=鈥�0.80, p鈥�<鈥�0.001) and partially mediated the relationship between mental health and academic self-efficacy, with a mediating effect value of -0.232. Academic self-efficacy can positively predict academic achievement (尾鈥�=鈥�0.10, p鈥�<鈥�0.01). The model further confirms the existence of chain-mediated effects. The greater the mental health level of students is, the better their learning adaptation, and the stronger their academic self-efficacy is, the greater their corresponding academic success.

Fig. 3

Structural Equation Model. (a) Structural Equation Model 1. (b) (Revised) Structural Equation Model 2

Table 4 Fit indices of the structural equation models

Discussion

This study investigated the relationships between mental health and learning adaptation, academic self-efficacy, and academic achievement among 3871 freshmen from a vocational college in Hebei Province. The research results show that mental health issues are significantly correlated with learning adaptation, academic self-efficacy, and academic achievement and that mental health can significantly negatively predict academic achievement. This research result supports hypothesis 1 that mental health has a predictive effect on student academic achievement, which is consistent with previous research [18, 20]. This means that when students鈥� mental health is poor, their academic achievement is often affected and shows a downward trend. This finding is consistent with previous research that there is a close relationship between mental health and academic achievement [47]. However, when learning adaptation and academic self-efficacy were added as chain mediating variables in the model, the paths of mental health 鈫� academic achievement, and mental health 鈫� learning adaptation 鈫� academic achievement were not significant, but the path of academic adaptation between mental health and academic self-efficacy was significant. This may be due to the mediating variables of learning adaptation and academic self-efficacy, which absorb most of the impact of mental health on academic achievement. In the model, the addition of these two variables makes the direct impact of mental health on academic achievement relatively weak, and therefore no longer statistically significant.

Academic self-efficacy plays a mediating role between mental health and academic achievement. This research result supports hypothesis 3: Academic self-efficacy plays a mediating role between mental health and academic achievement. The impact of mental health on academic achievement is mediated by academic self-efficacy, where the level of mental health affects academic achievement by influencing self-efficacy [48]. Academic self-efficacy is an important indicator of students鈥� self-learning ability [49] and is a key factor in learning motivation. It directly affects how individuals cope with challenges from different learning contexts. Therefore, students with high self-efficacy are more likely to experience success, making them more likely to engage and less prone to fatigue during the learning process [50]. That is, students with higher levels of mental health have greater academic self-efficacy and greater academic confidence and are more willing to believe that they can complete their studies well through their own efforts. This high level of confidence can encourage students to actively create a suitable academic environment and become more willing to participate in school activities related to morality, intelligence, physical fitness, and aesthetics. During periods of academic difficulty, people tend to believe in their ability to change and adjust their learning strategies to better suit them, helping them achieve better academic achievement. Previous studies have revealed the changing trends of college students in variables such as academic performance, self-efficacy, and self-esteem [13,14,15]. These trends are not static but exhibit diversity over time and across individual differences. The existence of such heterogeneity implies that educators and researchers need to consider the specific needs and developmental pathways of different student groups to more effectively support their personal growth and academic success.

Learning adaptation plays a partial mediating role between mental health and academic self-efficacy. Mental health can directly negatively predict academic self-efficacy and can also influence academic self-efficacy by negatively influencing learning adaptation. The more mental health problems a student has, the more difficult it is to adapt to learning; the more difficult it is to adapt to learning, the lower the academic self-efficacy. Students with higher levels of mental health also have greater adaptability to new learning environments, and good learning adaptation can effectively enhance their academic self-efficacy. In addition, when considering the effects of learning adaptation and academic self-efficacy on the relationship between mental health and academic achievement, it was found that the mediating effect of learning adaptation between mental health issues and academic achievement was no longer significant (hypothesis 2), while learning adaptation and academic self-efficacy played a chain mediating role between mental health and academic achievement. This research result supports hypothesis 4: Learning adaptation and academic self-efficacy play a chain mediating role between mental health and academic achievement. Individuals with fewer mental health problems exhibit better learning adaptation, and high-level learning adaptation is a protective factor against the development of greater academic self-efficacy, which can reduce the negative impact of mental health problems on academic self-efficacy. Higher academic self-efficacy will further have a positive impact on individual academic achievement. Past research has found that learning adaptation and academic self-efficacy influence each other [51]. In this study, we also observed that learning adaptation can positively predict a sense of self-efficacy. Learning adaptation is a multidimensional and complex process [52, 53], involving how students adjust their learning strategies, manage learning resources, and cope with learning challenges. When students can adapt well to the learning environment, they tend to gain more successful experiences and positive learning feedback, which helps to enhance their academic self-efficacy. As Yongmei and Chen [51] pointed out, learning adaptation can create more opportunities for students to demonstrate their abilities, thereby strengthening their academic self-efficacy. Although there is a mutual influence between academic self-efficacy and learning adaptation, in this study, we specifically focus on the promoting effect of learning adaptation on academic self-efficacy. Learning adaptation is not only an antecedent variable of academic self-efficacy but also a result variable, and their interaction forms a complex dynamic system. When students feel that they can effectively adapt to learning, their academic self-efficacy will correspondingly increase, thereby promoting better learning adaptation.

Conclusion and inspiration

This study explores the relationship between the mental health of college freshmen and their academic achievement, and finds a significant negative correlation between their mental health problem and academic achievement. In addition, mental health not only directly has a negative impact on academic achievement, but also indirectly promotes the improvement of academic achievement through the complete mediation of academic self-efficacy and the chain mediation effect formed by learning adaptation and academic self-efficacy. This emphasizes the importance of improving the mental health level of college students in promoting their comprehensive development and academic achievement. Based on these conclusions, we can propose measures to enhance students鈥� mental health, learning adaptation, academic self-efficacy, and academic achievement.

(1) Strengthen the cultivation of students鈥� psychological qualities from the perspective of all university workers. Psychological health is an important predictor of academic performance for college freshmen, and the higher the level of psychological health, the better the academic performance [54]. Therefore, schools should strengthen the cultivation of students鈥� psychological qualities. Specifically, universities should establish a developmental mindset for cultivating the psychological qualities of students from the perspective of all university workers. All student workers and teachers are workers who implement mental health education, allowing the concept of mental health and the cultivation of psychological qualities to permeate into four aspects of the school鈥檚 education model, management model, service model, and student worker team construction model, permeating every aspect of students鈥� school life. To achieve such a training model, all educators must master and practice the basic concepts of mental health education. Therefore, universities need to strengthen the training of all teachers in terms of mental health literacy, knowledge and skills in mental health education, and methods for cultivating student mental health, creating a positive and healthy campus psychological atmosphere, making every teacher a tentacle for mental health, and influencing every student. By strengthening the enrollment education for new students, conducting timely and regular mental health surveys, organizing rich mental health education activities, conducting personalized psychological counseling, and intervening in psychological crises, we can stabilize and improve the overall mental health level of students, help them establish awareness that they are the first person responsible for their mental health, cultivate good living and learning habits, and truly achieve the goal of using life to influence life, promoting the improvement of the mental health level of all students.

(2) Cultivate students鈥� adaptability to changes in the learning environment and learning methods. Learning adaptation plays a partial mediating role between mental health and academic self-efficacy. When students鈥� mental health is good, they are more likely to have a positive learning attitude and good study habits, making it easier for them to adapt to changes in the learning environment [55]. The improvement of this learning adaptability will further enhance students鈥� academic self-efficacy, making them more confident in their ability to complete academic tasks. Adaptability can directly and positively predict learning engagement [56]. Good adaptability can help students effectively adjust their cognition and behavior and actively and quickly change their self-awareness and learning behavior to ensure enthusiasm, sustainability, stability, and concentration in the university learning process and to improve their level of learning engagement. Therefore, it is recommended that educators strengthen the cultivation of students鈥� adaptability to changes in learning environments and learning methods. By offering general courses on mental health education, adaptive group psychological counseling, and quality expansion training courses and conducting class activities and lectures by renowned teachers, they can help students correctly understand the university and evaluate themselves, position themselves in new roles, and develop themselves; master communication skills, life skills, and self-care abilities; create harmonious interpersonal relationships; actively seek social support when necessary; establish clear learning plans, establish university goals and academic confidence, and stimulate internal learning drive; and master commonly used self-psychological adjustment methods and timely and effectively eliminate learning and interpersonal pressure. Effectively promoting students to quickly adapt to the environment of university learning and life, achieving a psychological state that is balanced with the learning environment, enhancing students鈥� perception of being able to and effectively achieve learning goals, and their perception of being in contact with teachers, reducing the low academic self-efficacy and unpleasant emotions caused by mental health problems, improving learning engagement, and enhancing the level of academic achievement.

(3) The cultivation of students鈥� academic self-efficacy should be systematically strengthened. According to the results of this study, academic self-efficacy plays a chain mediated role between mental health and academic achievement. This indicates that when college students have good mental health, they are more likely to have higher academic self-efficacy, that is, confidence in their ability to complete learning tasks and achieve good grades [57]. This high level of academic self-efficacy will further promote students鈥� learning adaptation, enabling them to better adjust their learning strategies, manage learning pressure, and actively participate in learning activities. Ultimately, this positive learning adaptation and efficient learning behavior will translate into better academic achievement. Therefore, In the process of education and teaching, the concept of positive psychology should be integrated to systematically cultivate students鈥� academic self-efficacy. Specifically, when new students first enroll, they need to strengthen their training in learning and environmental adaptation. By helping students complete the role transition from middle school students to college students, establishing professional interests, understanding the professionalism, autonomy, exploration, practicality, and diverse evaluation criteria of university learning, they can help students explore the meaning of their college life, set academic goals, and learn how to learn and live in university, assisting students in forming and accumulating successful experiences, enhancing academic self-efficacy, and enhancing their level of effort and persistence in learning. After the adaptation process is completed, students will further understand that in addition to professional knowledge, self-management skills, transferability, and other aspects of university learning. This will help students understand their own learning methods and explore the most suitable learning methods and strategies so that they can respond with a positive attitude and appropriate cognitive strategies when facing challenging tasks. Through these systematic trainings, students can be better engaged in university studies, improve their innovation, application, and practical skills, and create better academic achievements.

(4) In addition to conventional measures, artificial intelligence can also be utilized to promote students鈥� mental health. Firstly, for monitoring students鈥� psychological issues, schools can build artificial intelligence-based emotion monitoring and warning systems to monitor students鈥� emotional state changes in real time and issue timely warnings when abnormalities are detected. This type of system can integrate physiological data collected by wearable devices (such as heart rate variability, sleep quality, etc.) and online behavioral data, analyze these data using machine learning algorithms, and predict students鈥� mental health risks. Once high-risk students are identified, the system can automatically trigger intervention mechanisms, such as sending care messages, recommending psychological counseling services, or notifying the school鈥檚 mental health center. Furthermore, based on the research findings that mental health is an important predictor of academic performance, a comprehensive academic counseling and psychological support platform can be developed, utilizing artificial intelligence technology to optimize the allocation of learning resources while paying attention to students鈥� mental health status. The platform can dynamically adjust learning plans based on students鈥� academic performance and mental health status, ensuring that students can maintain a good psychological state while pursuing academic achievements. In addition, the platform can also promote positive interaction between teachers and students, and create a supportive learning environment.

Some examples, such as designing and developing mobile applications for postpartum depression in pregnant women and flight attendants, provide them with corresponding psychological support. In addition, there have been studies on short video applications optimized with artificial intelligence, which effectively reduce suicidal ideation among college students by guiding compassionate meditation practices. This not only reflects the precise role of artificial intelligence in personalized content push and mental health counseling, but also demonstrates its significant contribution in identifying and intervening in potential suicide risks earlier, ensuring students鈥� life safety and mental health. In other aspects, studies have also revealed the enormous potential of multimedia technology in improving the understanding of medical and health information, which further emphasizes the unlimited possibilities of the integration of artificial intelligence and multimedia technology in optimizing information presentation, enhancing user cognitive experience, and promoting mental health. The Woebot project developed by Stanford University provides innovative mental health support solutions for college students suffering from depression and anxiety disorders [58]. The Woebot utilizes chatbot technology to interact with users through text-based conversations and offers 鈥渆motion tracking鈥� services. This service not only helps users identify their emotional states but also provides personalized suggestions for emotional improvement through the combination of intelligent algorithms and cognitive behavioral therapy principles [59]. The successful implementation of the Woebot project demonstrates the unique advantages of artificial intelligence in mental health support.

Limitations

Despite the large sample size of this study, due to time constraints, it can only provide data from a specific semester or year, and cannot reveal the developmental trajectories of variables such as mental health, academic achievement, learning adaptation, and academic self-efficacy over time. Therefore, future research directions can explore how to integrate time-series data, panel data, experimental designs, causal inference methods, and other approaches to gain a more comprehensive understanding of the relationships and dynamic processes between mental health and academic performance, while ensuring the objectivity and reliability of the research.