Personal values and mental health among Chinese university students: a dual-factor model perspective

Abstract

Background

Personal values may be important for university students’ mental health. However, most studies focus on single indicators such as anxiety, depression, or well-being, with limited attention to overall mental health profiles. How different value dimensions relate to mental health heterogeneity from a dual-factor perspective remains unclear.

Methods

In this cross-sectional study, latent profile analysis and multinomial logistic regression were used to identify mental health profiles and examine their associations with personal values. A total of 14,929 Chinese university students completed self-report measures of personal values, anxiety, depression, life satisfaction, and psychological resilience.

Results

Three mental health profiles were identified: complete mental health, vulnerable, and troubled. The symptomatic but content profile was not found. Multinomial logistic regression showed that self-transcendence was linked to more favorable profiles, whereas self-enhancement was linked to less favorable profiles. Openness to change showed a conditional pattern: it was generally linked to lower likelihood of vulnerable or troubled membership, but among vulnerable and troubled students, higher openness to change was linked to higher likelihood of troubled membership. Conservation showed a weaker role and mainly distinguished the complete mental health and vulnerable profiles.

Conclusions

This study provides a person-centered view of mental health heterogeneity among Chinese university students. The findings suggest that personal values are differentially associated with overall mental health profiles and support integrating symptom screening, value guidance, and positive psychological resource development in university mental health education.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s40359-026-05380-x.

Introduction

Mental health refers to a dynamic process in which individuals maintain balance in cognition, emotion, behavior, and social functioning, while realizing their potential, coping effectively with life stress, and achieving positive development [1]. Chinese society is currently undergoing rapid transformation. In this context, university students’ psychological experiences have become increasingly complex [2]. Social development has created more diverse opportunities for growth and self-realization, strengthening students’ pursuit of well-being, meaning, and personal development. At the same time, uncertainty caused by social change, academic and employment competition, value conflicts, and interpersonal adjustment pressures have made anxiety, depression, and other psychological difficulties more prominent [3]. Given this coexistence of positive and negative psychological experiences, the dual-factor model of mental health provides an integrative framework beyond a symptom-based perspective. It emphasizes that complete mental health involves not only low psychopathological symptoms but also high positive psychological functioning, thereby offering a more systematic theoretical basis for understanding and assessing university students’ mental health [4].

During psychological development, personal values may play an important role in university students’ mental health [5]. Personal values are basic evaluations of life goals and action preferences. They express what people regard as meaningful and desirable, as well as influence the ways individuals think, feel, and behave [6]. Existing studies have mainly examined the effects of different value orientations on psychological adjustment through single indicators such as subjective well-being, anxiety, and depression [7, 8]. However, less attention has been paid to how personal values relate to overall mental health. Therefore, based on the dual-factor model of mental health, this study focuses on the role of personal values in individuals’ overall mental health status, aiming to provide evidence for psychological adjustment and more adaptive mental health interventions during social transformation.

Personal values: concept and structure

Personal values are abstract goals and basic beliefs that individuals regard as important and worth pursuing, guiding their choices, evaluations, and behaviors [9]. Unlike specific attitudes, short-term goals, or context-dependent preferences, values are highly abstract and relatively stable across situations. They shape how individuals understand their needs and life goals, as well as how they evaluate behavioral consequences in different contexts [10].

Owing to its well-structured motivational system and wide applicability across cultures, Schwartz’s personal value theory has become a useful approach for studying the link between values and developmental outcomes [11]. According to the theory, despite cultural differences, all individuals respond to basic requirements of biological survival, social coordination, and group functioning, which gives rise to value orientations with cross-cultural universality. Drawing on this framework, Schwartz classified personal values into ten basic categories: self-direction, stimulation, hedonism, achievement, power, security, conformity, tradition, benevolence, and universalism [11]. The overall pattern of conflict and compatibility among values forms a circular structure. In this structure, adjacent values reflect compatible motivations, whereas opposing values reflect conflicting motivations.

The value circle can be summarized by two basic conflicts [12]. The first is the conflict between self-enhancement and self-transcendence, which reflects the tension between personal interests and others’ welfare. Self-enhancement emphasizes achievement, power, and personal success, whereas self-transcendence emphasizes benevolence, universalism, and concern for others and society. The second is the conflict between openness to change and conservation, which reflects the tension between autonomous exploration and stable order. Openness to change emphasizes autonomy, exploration, and new experiences, whereas conservation emphasizes security, tradition, conformity, and stability.

Values have a relatively stable structure, but their priority also varies across individuals and cultures [10]. Extensive cross-cultural research has shown that Schwartz’s value structure is relatively stable across countries and cultural samples, but culture also influences the priority individuals assign to different values [13, 14]. Therefore, in the context of social transformation and value diversification in China, examining the structure and priorities of university students’ personal values can help clarify their value orientations and provide a basis for analyzing the relationship between different values and mental health status.

Personal values and mental health

One important reason personal values have received attention is their close association with individual mental health. Previous studies have shown that personal values are significantly related to various mental health indicators [15, 16], including life satisfaction, subjective well-being, depression, anxiety, stress responses, adjustment problems, aggressive behavior, and substance use. Sagiv and Schwartz distinguished between relatively healthy and unhealthy values, arguing that healthy values such as self-direction, universalism, and benevolence are more conducive to well-being, whereas unhealthy values such as power, conformity, and tradition may be associated with lower well-being [5]. Sortheix and Schwartz also noted that openness to change is generally related to higher life satisfaction, whereas power and other self-enhancement values are more often associated with lower life satisfaction [7].

Overall, values emphasizing autonomy, growth, and social concern are usually associated with higher life satisfaction and better psychological adjustment, whereas values emphasizing external recognition and status competition are more often linked to lower well-being or greater psychological distress. However, findings remain inconsistent [17]. Heim et al.’s review indicated that there is no stable pattern of association between personal values and internalizing problems [18]. Hanel and Wolfradt found a positive association between achievement values and depression in a German student sample [19], whereas Maercker et al. found a negative association in a Chinese student sample. These findings suggest that the relationship between personal values and mental health is not fixed, but may depend on value type, mental health indicator, and research context.

The inconsistent associations of personal values with mental health disorders and life satisfaction may partly result from cultural differences [17]. Culture shapes both the values individuals prioritize and the ways these values relate to behavior and psychological outcomes [20]. Roccas and Sagiv emphasized the need to understand value-outcome relationships within cultural contexts [10], and Sortheix and Schwartz showed that culture moderates the association between values and life satisfaction [7]. Therefore, in the context of social transformation and value diversification in China, the relationship between personal values and university students’ mental health may have specific cultural meanings and requires further examination.

Dual-factor mental health

Traditional mental health models usually focus on psychopathological symptoms and assess mental health according to the presence of symptoms such as depression and anxiety [3]. However, this one-dimensional view has limitations. It may overestimate the mental health of individuals who do not meet clinical symptom criteria but have low positive psychological functioning. It may also overlook individuals who have some psychological symptoms but still maintain relatively good positive functioning [21]. Early research argued that the absence of illness may be a necessary but not sufficient condition for mental health [22].

With the development of positive psychology, researchers have increasingly emphasized the need to include positive indicators, such as subjective well-being, in mental health assessment to better understand individuals’ mental health status [23]. Against this background, the dual-factor model of mental health gradually emerged and has been used to address the limitations of traditional psychopathology-based models [24].

The Dual-Factor Model of Mental Health offers a more comprehensive view by defining mental health as the coexistence of low psychopathological symptoms and high subjective well-being, rather than merely the absence of mental illness or the presence of high well-being alone [25]. It treats subjective well-being and psychopathological symptoms as related but distinct dimensions, resulting in four mental health states: complete mental health, characterized by high well-being and low symptoms; vulnerable, characterized by low well-being and low symptoms; symptomatic but content, characterized by high well-being and high symptoms; and troubled, characterized by low well-being and high symptoms [24]. Previous studies have supported this four-category structure across student populations [26].

To assess mental health more accurately, indicators should reflect both psychological distress and positive functioning within the dual-factor framework [27]. Negative mental health is usually assessed with established measures of psychopathology [28]. Among university students, depression and anxiety are common internalizing problems and core indicators in mental health screening and risk assessment [29]. For positive mental health, the dual-factor model originally emphasized subjective well-being. Life satisfaction, as a cognitive evaluation of one’s overall life, is a key component of subjective well-being [30]. However, positive mental health indicators in this model are not fixed; psychological resources such as resilience can also represent positive functioning [31]. Therefore, this study used life satisfaction and psychological resilience as positive indicators. Life satisfaction reflects students’ overall evaluation of academic and daily life, whereas resilience reflects their capacity to recover and adapt under stress, adversity, and uncertainty [32].

The present study

Based on Schwartz’s theory of personal values and the dual-factor model of mental health, this study focuses on Chinese university students. It first describes their value orientations, then examines the associations of four higher-order value dimensions with positive psychological functioning and negative psychological symptoms. It further uses latent profile analysis to identify mental health profiles and tests whether personal values are associated with membership in different profiles.

Specifically, this study addresses the following four research questions:

• RQ1: What value orientations do Chinese university students show in the context of social transformation and value diversification?

• RQ2: How are personal values associated with positive psychological functioning and negative psychological symptoms among Chinese university students?

• RQ3: What mental health profiles can be identified among Chinese university students based on the dual-factor model of mental health?

• RQ4: How are personal values associated with overall mental health profile membership among Chinese university students?

The innovation of this study lies in three aspects. First, it integrates Schwartz’s theory of personal values with the dual-factor model of mental health, examining mental health through both positive functioning and negative symptoms. Second, it uses a person-centered latent profile approach to identify heterogeneity in university students’ mental health and examine its association with higher-order value dimensions. Third, by focusing on Chinese university students during social transformation and value diversification, this study provides context-specific evidence for value guidance and positive psychological resource development in university mental health education.

Method

Participants and procedure

Data were collected in July 2025 from students at 18 universities in eastern, central, and western China using multistage random sampling. The reference minimum sample size was estimated at 9,604 using p = 0.50, α = 0.05, and d = 0.01, and as many eligible students as feasible were recruited. Prior to data collection, all participants received clear information about the aims of the study, the research procedures, and potential risks, and informed consent was secured before participation. All students joined voluntarily and retained the right to stop at any point. The study protocol was approved by the ethics committee and complied with the ethical standards of the Declaration of Helsinki. A total of 14,929 university students were recruited, and all participants completed the relevant measures. To ensure data quality and exclude invalid responses, two exclusion criteria were applied: (1) incorrect responses to a lie-detection item used to assess response validity, and (2) abnormal completion time, defined as below the 2.5th percentile or above the 97.5th percentile. Following the data-screening process, 13,959 questionnaires were retained for analysis, corresponding to a valid response rate of 93.5%. The analytic sample included 5,100 men and 8,859 women, accounting for 36.5% and 63.5% of the sample, respectively. Participants were between 16 and 30 years old, with a mean age of 20.16 years. Regarding university type, 55.9% were from public universities, and 44.1% were from private universities. With respect to household registration, 60.7% were from rural areas and 39.3% were from urban areas.

Measures

Depression scale

Participants’ depressive symptoms were evaluated with the CES-D-10, the brief 10-item form of the Center for Epidemiologic Studies Depression Scale proposed by Andresen [33]. Responses to each item range from 0 to 3 on a four-point Likert scale. Higher total scores reflect more frequent depressive symptoms, whereas lower totals indicate fewer symptoms. After summation, the overall score falls between 0 and 30. A score of 0–10 suggests mild symptoms, 11–15 reflects moderate symptoms, and 16–30 represents severe symptoms. This instrument has been widely applied in large-scale screening studies and has shown satisfactory validity in diverse cultural contexts. Reliability analysis in this study also supported its use, with Cronbach’s α reaching 0.86. The present study assessed participants’ depressive symptoms by applying the CES-D-10, a short form of the Center for Epidemiologic Studies.

Anxiety scale

Participants’ anxiety levels were evaluated using the Generalized Anxiety Disorder 7-item scale (GAD-7) [34]. This measure contains seven items and captures anxiety-related symptoms over the last two weeks. Scores can vary from 0 to 21, with values of 7 or higher generally regarded as the cutoff for screening potential clinically significant anxiety. The GAD-7 has been widely supported in psychometric research and has shown good applicability in different cultural populations. Reliability analysis in this study further indicated a high level of internal consistency, with Cronbach’s α reaching 0.937.

Psychological resilience scale

Participants’ psychological resilience was evaluated with the CD-RISC-10, a 10-item instrument introduced by Connor and Davidson [35]. Each item is rated from 0 to 4 on a five-level response scale. The total score is obtained by adding all item responses, and larger values represent greater resilience. Reliability testing in this study suggested excellent internal consistency for the scale, as the Cronbach’s α reached 0.972.

Life satisfaction

Following evidence that single-item measures can demonstrate acceptable validity in large-scale surveys [36] life satisfaction was assessed using one such item. Participants rated their satisfaction on a 5-point scale from 1 (very dissatisfied) to 5 (very satisfied), where elevated scores correspond to higher levels of satisfaction.

Portrait values questionnaire

This study measured individual values with the 21-item Portrait Values Questionnaire (PVQ-21) proposed by Schwartz [37]. The overall scale showed satisfactory reliability in the current sample, with Cronbach’s α equal to 0.877. Because each basic value was measured by only a limited number of items, this study grouped them into four higher-order value dimensions following Sandy [38]: self-transcendence, self-enhancement, openness to change, and conservation. The four dimensions showed acceptable internal consistency, with Cronbach’s α values of 0.822, 0.784, 0.745, and 0.817, respectively. These results indicate that the four higher-order value dimensions had acceptable reliability in the present sample.

Demographic variables

Demographic variables included gender, age, household registration, institution type, left-behind experience, and family socioeconomic status. Gender was coded as 0 = male and 1 = female. Household registration was coded as 0 = rural and 1 = urban based on status at birth. Institution type was coded as 0 = public institution and 1 = private institution. Left-behind experience was coded as 0 = no and 1 = yes, based on whether participants had lived apart from their parents for more than one year due to parental labor migration or long-term absence. Family socioeconomic status was assessed by a subjective 1–10 rating, with higher scores indicating higher perceived family socioeconomic status.

Data analysis

Data analysis was conducted using SPSS 26.0 and Mplus 8.3. Descriptive statistics were first performed in SPSS 26.0 to calculate the means, standard deviations, and correlation coefficients of the study variables. Latent profile analysis was then carried out in Mplus 8.3, with life satisfaction, psychological resilience, anxiety, and depression treated as observed indicators to identify latent mental health profiles among Chinese university students. The optimal profile solution was determined by comparing model fit indices, likelihood ratio test results, and the theoretical interpretability of the class structure. Multinomial logistic regression was finally used to examine the effects of different value dimensions on mental health profile membership. Demographic variables, including gender, age, household registration, family socioeconomic status, and left-behind experience, were included in the model as control variables.

Results

Descriptive statistics and correlation analysis

The 21 PVQ items were centered to account for variation in participants’ response tendencies. Descriptive analysis revealed clear differences across the four higher-order value dimensions. Self-transcendence ranked first, with the highest average score (M = 0.088, SD = 0.333), which suggests that this value dimension was most strongly valued in the sample. Openness to change, in contrast, ranked last and had the lowest average score (M = -0.075, SD = 0.372), indicating a comparatively weaker priority. In addition, the mean score of self-enhancement (M = 0.015, SD = 0.442) was marginally above that of conservation (M = -0.008, SD = 0.328).

The correlation matrix is presented in Table 1. Self-transcendence and openness to change were characterized by a similar pattern of associations, marked by negative relations with depression and anxiety and positive relations with life satisfaction and resilience. Self-enhancement demonstrated the opposite tendency, showing positive relations with depression and anxiety and negative relations with life satisfaction and resilience. For conservation, the pattern was comparatively weak: it was weakly and positively related to depression, significantly and negatively related to resilience, and not significantly related to anxiety or life satisfaction.

Table 1.

Descriptive statistics and correlations

	N	M	SD	Depression	Anxiety	Life satisfaction	Psychological Resilience
Depression	13,959	0.958	0.556	1
Anxiety	13,959	0.657	0.643	0.747***	1
Life satisfaction	13,959	3.67	0.798	-0.341***	-0.262***	1
Psychological Resilience	13,959	2.617	0.736	-0.439***	-0.311***	0.272***	1
Openness to Change	13,959	-0.075	0.372	-0.032***	-0.030***	0.041***	0.088***
Conservation	13,959	-0.008	0.328	0.021*	0.008	0.008	-0.068***
Self-Enhancement	13,959	0.015	0.442	0.189***	0.167***	-0.168***	-0.147***
Self-Transcendence	13,959	0.088	0.334	-0.182***	-0.146***	0.115***	0.118***

*p < 0.05, **p < 0.01, ***p < 0.001. All significance tests were two-tailed

Demographic differences

Before conducting subgroup comparisons, measurement invariance was examined across gender, household registration, and university type. The results supported configural and metric invariance for the main multi-item scales, with ΔCFI ≤ 0.010 and ΔRMSEA ≤ 0.015, indicating basic measurement comparability across demographic subgroups.

To examine demographic differences in value priorities, independent-samples t tests were conducted on the four centered higher-order value dimensions by gender, household registration, and institution type. Some differences were statistically significant. However, given the large sample size, these results should be interpreted with effect sizes. Overall, Cohen’s d values were small. Gender differences were relatively more evident but still small, while differences by household registration and institution type were weaker. These findings suggest that demographic differences in value priorities were limited, and the imbalanced sample structure did not substantially affect the overall value pattern. The detailed results are presented in Table 2.

Table 2.

Demographic differences in personal values

Grouping variable	Group/Statistic	Openness to Change	Conservation	Self- Enhancement	Self- Transcendence
Gender	Male M (SD)	-0.027 (0.363)	0.002 (0.325)	-0.027 (0.456)	0.051 (0.337)
	Female M (SD)	-0.102 (0.375)	-0.015 (0.329)	0.039 (0.432)	0.109 (0.33)
	p	< 0.001	0.003	< 0.001	< 0.001
	Cohen’s d	0.204	0.052	-0.149	-0.176
Household registration	Rural M (SD)	-0.083 (0.367)	-0.005 (0.324)	0.021 (0.43)	0.087 (0.326)
	Urban M (SD)	-0.0589 (0.382)	-0.016 (0.336)	0.001 (0.464)	0.089 (0.348)
	p	< 0.001	0.046	0.012	0.754
	Cohen’s d	-0.064	0.036	0.046	-0.006
University type	Public M (SD)	-0.084 (0.382)	-0.006 (0.331)	0.029 (0.45)	0.084 (0.339)
	Private M (SD)	-0.063 (0.359)	-0.011 (0.324)	-0.004 (0.431)	0.093 (0.326)
	p	0.001	0.362	< 0.001	0.133
	Cohen’s d	-0.054	0.016	0.075	-0.025

Latent profile analysis

To identify latent mental health profiles among young adults, latent profile analysis was conducted within the dual-factor framework using anxiety, depression, life satisfaction, and resilience as indicators. Model estimation began with a two-profile solution, and the number of profiles was increased step by step until a model with theoretical and practical meaning was identified. Following established criteria for latent class model evaluation, the optimal solution was selected based on model fit, classification accuracy, class size, and theoretical interpretability [39, 40]. The evaluation results of the competing models are shown in Table 3.

Table 3.

Model fit indices for two- to five-profile solutions of mental health

Profile	AIC	BIC	a-BIC	Entropy	LMR	BLRT	Proportion
2	146570.662	146668.732	146627.42	0.780	< 0.001	< 0.001	0.399/0.601
3	140621.538	140757.327	140700.125	0.860	< 0.001	< 0.001	0.402/0.507/0.092
4	138081.111	138254.62	138181.528	0.926	< 0.001	< 0.001	0.372/0.496/0.111/0.022
5	136535.278	136746.507	136657.525	0.899	< 0.001	< 0.001	0.185/0.285/0.399/0.022/0.108

With an increasing number of profiles, AIC, BIC, and aBIC showed a steady decline, indicating progressively better model fit. The LMR and BLRT tests were significant for the two- through five-profile solutions, suggesting that each additional profile improved model fit meaningfully [41]. The entropy values of the three-, four-, and five-profile solutions were all above 0.80, indicating acceptable classification accuracy. Although the four- and five-profile solutions showed further improvement in fit, both included classes with fewer than 5% of the sample [42]. By contrast, the three-profile solution showed good classification accuracy (Entropy = 0.860), with class proportions of 40.2%, 50.7%, and 9.2%, respectively. These class sizes were more reasonable and more suitable for subsequent analysis and theoretical interpretation [43]. Therefore, considering model fit, classification accuracy, class size, and theoretical interpretability, the three-profile solution was selected as the optimal latent profile model.

Figure 1 presents the three latent profiles based on standardized indicators. According to the score patterns of the three classes on depression, anxiety, life satisfaction, and resilience, and in light of the dual-factor model of mental health, the three profiles were labeled complete mental health, vulnerable, and troubled. The class sizes, proportions, and standardized scores are shown in Fig. 1.

Fig. 1.

Characteristics of the latent profiles. Note: Values are standardized scores of depression, anxiety, life satisfaction, and psychological resilience. Error bars represent 95% confidence intervals

The first profile was labeled vulnerable and accounted for 40.2% of the sample. This group scored above the mean on depression and anxiety, and below the mean on life satisfaction and resilience, indicating a certain level of psychological distress together with relatively limited positive psychological resources. Compared with the other profiles, this group did not show the highest levels of anxiety and depression, but had the lowest level of resilience and relatively low life satisfaction. This suggests that, although these individuals had not reached the most severe level of psychological distress, their psychological adjustment base was relatively fragile, making them more vulnerable when facing stress and environmental change [24].

The second profile, identified as complete mental health, represented 50.7% of the total sample and was the largest subgroup. Members of this profile reported minimal depression and anxiety together with the greatest life satisfaction and resilience. This pattern indicates low psychological distress and strong positive functioning. These individuals not only experienced fewer negative emotional problems, but also reported greater life satisfaction and stronger resilience and adaptive capacity. Overall, this profile showed the best mental health status and was consistent with the complete mental health profile commonly identified in dual-factor research [24].

The third profile was labeled troubled and accounted for 9.4% of the sample, representing a relatively small group. This group showed the highest levels of depression and anxiety, with anxiety being especially pronounced, and scored below the mean on both life satisfaction and resilience. It therefore reflected the typical pattern of high negative symptoms and low positive functioning. These individuals not only experienced marked psychological distress, but also lacked sufficient positive psychological resources, resulting in the weakest overall mental health status [24].

Regression analysis

The analysis controlled for gender, age, household registration, family socioeconomic status, and left-behind experience, and then entered the four uncentered higher-order value dimensions into the model as measures of value priorities [37]. The regression results are presented in Table 4. Results indicated that these personal values were significant predictors of university students’ mental health profile membership. Relative to the complete mental health profile, stronger self-transcendence was associated with a lower chance of falling into the vulnerable or troubled profile. Relative to the vulnerable profile, self-transcendence also predicted a lower likelihood of membership in the troubled profile. A different pattern emerged for self-enhancement. Higher self-enhancement was associated with greater odds of belonging to both the vulnerable and troubled profiles, and it further increased the probability of being classified into the troubled profile instead of the vulnerable profile. Overall, self-transcendence and self-enhancement showed consistent associations in opposite directions across mental health profiles.

Table 4.

Results of the regression analysis

Predictor	Vulnerable VS.	Troubled VS.	Troubled VS.
	Complete mental health	Complete mental health	Vulnerable
Gender (Male)	1.215***	2.066***	1.7***
	(0.04)	(0.064)	(0.064)
Age	0.972**	1.099***	1.131***
	(0.012)	(0.018)	(0.018)
Household registration(Rural)	1.146***	2.49***	2.173***
	(0.041)	(0.079)	(0.08)
Family socioeconomic status	0.906***	0.931***	1.027
	(0.011)	(0.018)	(0.019)
Left-behind experience (No)	0.792***	0.843*	1.064
	(0.038)	(0.064)	(0.065)
Self-transcendence	0.513***	0.413***	0.804**
	(0.045)	(0.073)	(0.072)
Conservation	1.081*	1.129	1.045
	(0.044)	(0.074)	(0.074)
Self-enhancement	1.621***	2.428***	1.498***
	(0.036)	(0.061)	(0.06)
Openness to change	0.713***	0.842***	1.18*
	(0.038)	(0.063)	(0.063)

A more differentiated pattern emerged for openness to change. Using the complete mental health profile as the reference group, greater openness to change reduced the odds of membership in both the vulnerable and troubled profiles. Using the vulnerable profile as the reference group, the same value dimension was associated with a greater likelihood of falling into the troubled profile. This indicates that the direction of its effect changed across profile comparisons. Conservation, by comparison, played a more limited role. It was only positively associated with membership in the vulnerable profile when complete mental health was used as the reference group. No significant association was found in the comparisons of complete mental health versus troubled or vulnerable versus troubled.

Discussion

Drawing on Schwartz’s value theory and the dual-factor model of mental health, this study systematically examined the relationship between personal values and mental health among Chinese university students. Overall, the results showed that personal values were not only significantly associated with negative psychological indicators, as well as positive indicators, but also further differentiated individuals’ membership in broader mental health profiles. These findings suggest that personal values play an important role in the formation and differentiation of youth mental health.

Value priorities among Chinese university students

Regarding value priorities, Chinese university students showed a clear pattern: self-transcendence ranked highest, self-enhancement and conservation were in the middle, and openness to change ranked relatively low. This pattern is partly consistent with previous youth value studies, but also reflects value orientations shaped by China’s social transformation and value diversification.

Self-transcendence ranked highest, indicating that Chinese university students strongly value benevolence, universalism, social responsibility, and concern for others. This is consistent with previous findings. Tunç [44] found that self-transcendence was the most valued dimension among British youth, while Maercker et al. [19] found that benevolence and universalism ranked high among university students in Germany, Russia, and China. Schwartz and Bardi also showed that benevolence is among the most important values across many cultures [45]. Thus, concern for others and society remains a central part of youth value systems.

In the Chinese context, the high priority of self-transcendence may also reflect collectivist orientation, relational ethics, and social responsibility [17]. Chinese culture emphasizes interdependence, relational harmony, and responsibility, which may lead students to value others’ welfare and collective interests [46]. Therefore, even amid rapid social change and growing personal development needs, concern for others and society remains highly salient.

Second, the low priority of openness to change is notable. Early adulthood is often seen as a period of autonomy, exploration, and identity development [47], yet Chinese university students in this study did not highly prioritize openness to change. This may reflect the influence of academic competition, employment pressure, and future uncertainty, which may make students more inclined toward stable and realistic development paths [48, 49].

Self-enhancement ranked in the middle, suggesting that Chinese university students do not reject achievement, competition, or personal development [50]. In a highly competitive educational and employment context, achievement and external rewards remain attractive. However, self-enhancement did not exceed self-transcendence, indicating that personal success has not replaced social concern and responsibility in students’ value systems. This reflects a pragmatic balance between personal development and social responsibility.

Conservation ranked in the lower-middle position, suggesting that students value security, tradition, conformity, and stability to some extent, but are not strongly attached to them. This partly aligns with Schwartz and Bardi’ s finding that East Asian individuals tend to value conformity and tradition more than Western individuals [45]. However, the moderate priority of conservation suggests that Chinese university students are not fully bound by traditional order. Instead, they may seek a cautious balance between stability and self-development during social transformation.

The relationship between personal values and mental health

This study found that different value dimensions were associated with university students’ mental health indicators. Self-transcendence and openness to change were linked to higher life satisfaction, stronger psychological resilience, and lower depression and anxiety. In contrast, self-enhancement was associated with poorer mental health, especially higher depression and anxiety. These findings suggest that personal values are closely related to emotional experience, positive psychological resources, and psychological adjustment.

This pattern is broadly consistent with previous research. Self-transcendence and openness to change are often associated with higher well-being and better adjustment, whereas self-enhancement is more often linked to lower well-being and greater psychological distress [51]. The similar pattern observed in Chinese university students suggests that the relationship between personal values and mental health may have some cross-cultural consistency [18].

This result can be understood through self-determination theory. Self-transcendence and openness to change are closely related to intrinsic and growth-oriented goals, which may support basic psychological needs for autonomy, relatedness, and competence. By contrast, self-enhancement relies more on external evaluation and social comparison. Overemphasis on achievement, status, and recognition may increase competitive pressure and evaluation anxiety, thereby relating to higher depression and anxiety [52].

Notably, conservation values showed weak and unstable associations with mental health indicators, which differs from some Western findings linking conservation to lower well-being [8]. This difference may reflect cultural context. Previous research suggests that the effects of values on behavior and psychological outcomes depend on sociocultural context, because culture shapes how values are expressed and translated into psychological consequences [10].

In Western cultures that emphasize autonomy and self-expression, conservation values such as tradition, conformity, and security may be viewed as constraints on personal freedom and thus relate to lower well-being [53]. In contrast, East Asian cultures tend to emphasize conformity and tradition, and Chinese culture also values relational harmony, family responsibility, social norms, and stability [54]. In this context, conservation may not necessarily be a psychological risk. It may provide order, certainty, and social belonging in the face of academic pressure, interpersonal adjustment, and future uncertainty. Thus, conservation values among Chinese university students may both limit autonomous expression and support social adaptation, which may explain their weak and unstable associations with mental health indicators.

The relationship between personal values and mental health profiles

Based on the dual-factor model of mental health, this study identified three mental health profiles among university students: complete mental health, vulnerable, and troubled. Further regression analyses showed that personal values were significantly associated with overall mental health status.

Self-transcendence showed the most stable protective association with overall mental health. Higher self-transcendence was related to higher positive psychological functioning and lower negative symptoms, and to a lower likelihood of belonging to the vulnerable or troubled groups rather than the complete mental health group. This result is broadly consistent with previous studies. Self-transcendence emphasizes benevolence, universalism, social responsibility, and concern for others. When students value goals beyond self-interest, their self-worth may be less tied to external competition and personal success, and they may gain psychological support through social connection, meaning, and prosocial behavior [55, 56].

Self-enhancement showed an unfavorable association with overall mental health. Students with higher self-enhancement were more likely to belong to the vulnerable or troubled groups rather than the complete mental health group. This finding supports previous evidence linking self-enhancement to psychological distress [57]. Self-enhancement emphasizes achievement, status, and external evaluation, which may lead individuals to base self-worth on social comparison. When students overly depend on achievement or others’ approval, their psychological state may become more vulnerable to failure and negative feedback [58]. In university contexts, academic competition, employment pressure, and developmental uncertainty are prominent. Overemphasis on achievement and external recognition may intensify evaluation anxiety and chronic stress, thereby relating to less favorable mental health profile membership [59].

Openness to change showed a more complex pattern. Previous studies usually link it to higher well-being and lower depression, as it reflects growth orientation and autonomous motivation [51]. This study partly supports this view: higher openness to change was associated with a lower likelihood of belonging to the vulnerable or troubled groups rather than the complete mental health group. However, in the comparison between the vulnerable and troubled groups, openness to change was associated with a higher likelihood of troubled group membership. This suggests that openness to change is not uniformly protective. Its psychological meaning may vary across mental health states.

This result can be understood through the stress-vulnerability framework. The theory posits that individuals’ psychological adjustment outcomes depend on the joint effects of internal vulnerability and environmental stress [60]. Openness to change emphasizes autonomous exploration, novelty, and acceptance of change. For individuals with sufficient psychological resources, it may support adaptation and growth [61]. For those already at higher psychological risk, however, the uncertainty and choice pressure involved in openness to change may become an additional burden. Thus, when individuals have stronger negative emotions, lower resilience, or limited support, pursuing change may be experienced less as growth and more as stress and loss of control. Openness to change may therefore be protective when distinguishing healthy students from risk groups, but may amplify stress among already vulnerable students. This finding suggests that the positive role of openness to change may depend on sufficient psychological resources and environmental support.

Moreover, within the Chinese sociocultural context, which emphasizes stability, responsibility, and pragmatic achievement, the autonomy and pursuit of change associated with openness to change may not always align with university students’ external environments. For students with limited psychological resources or high stress levels, this value orientation may heighten sensitivity to autonomous choice, future uncertainty, and conflicts with external expectations, thereby increasing psychological burden.

Conservation values showed a limited association with mental health profiles. They mainly distinguished the complete mental health group from the vulnerable group, but were not significant in comparisons involving the troubled group. This suggests that conservation may be more related to early vulnerability than to severe psychological problems.

This result should be understood in the Chinese cultural context. Conservation emphasizes security, tradition, order, and conformity [11]. In Chinese culture, which values family responsibility, relational harmony, and social norms, conservation may provide stability, reduce uncertainty, and enhance social belonging [53]. Therefore, it does not necessarily represent a psychological risk. However, conservation may not be a strong protective factor. Because security, responsibility, and norm conformity are widely valued in Chinese culture, individual differences in conservation may be limited, reducing its ability to distinguish mental health profiles. It may function more as a basic cultural adaptation resource than as a core psychological resource.

Conservation mainly distinguished the complete mental health group from the vulnerable group, possibly because it is more related to positive functioning than to anxiety or depression. A stronger conservation orientation may limit autonomous exploration and self-expression, thereby weakening life satisfaction and resilience. In contrast, the troubled group may be more strongly influenced by stress exposure, emotion regulation difficulties, and limited social support. Thus, conservation values among Chinese university students may be culturally adaptive but have limited psychological differentiation.

Limitations and future directions

This study has several limitations. First, its cross-sectional design prevents causal inference. The findings show only statistical associations between personal values and mental health profiles. Reverse or bidirectional effects may also exist; for example, poorer mental health may increase reliance on achievement, competition, and external recognition, thereby strengthening self-enhancement values. Future studies should use longitudinal, cross-lagged, or intervention designs to examine temporal order and causal direction. Second, although depression, anxiety, life satisfaction, and resilience reflect both negative symptoms and positive functioning, they may not fully capture mental health. Positive functioning also includes positive affect, self-esteem, meaning in life, and social functioning. Future research should include broader indicators and test the stability of profile structures across different indicator sets. Third, the sample included only Chinese university students, which may limit generalizability. Future studies should examine these associations across different age groups, occupational groups, and cultural contexts.

Conclusion

This study examined the relationship between personal values and overall mental health among Chinese university students based on Schwartz’s value theory and the dual-factor model of mental health. The main conclusions are as follows. (1) Students placed the highest priority on self-transcendence and the lowest priority on openness to change, with self-enhancement and conservation in the middle. This reflects a specific ordering of social concern, personal development, stability, and change-oriented exploration. (2) Based on depression, anxiety, life satisfaction, and resilience, three mental health profiles were identified: complete mental health, vulnerable, and troubled. This suggests that overall mental health should be understood through both negative symptoms and positive functioning. (3) Personal values distinguished profile membership. Self-transcendence predicted more favorable profiles, whereas self-enhancement predicted less favorable profiles. Openness to change showed a conditional role: it generally predicted lower likelihood of vulnerable or troubled membership, but among vulnerable and troubled students, higher openness to change predicted troubled membership. Conservation had a weak predictive role and mainly distinguished the complete mental health and vulnerable groups.

These findings suggest that university mental health education should move beyond symptom screening and integrate value guidance with positive psychological resource development. Universities should strengthen students’ social responsibility, prosocial orientation, resilience, and meaning in life, while reducing excessive achievement pressure, social comparison, and dependence on external evaluation. For vulnerable students, interventions should address both psychological distress and positive functioning.

Supplementary Information

Supplementary Material 1. ^{(98.8KB, doc)}

Authors’ contributions

W.Z. conceived the study, conducted the methodology, curated the data, performed the formal analysis, and wrote the main manuscript text. Z.L. supervised the study, validated the results, administered the project, and reviewed and revised the manuscript. All authors reviewed the manuscript.

Funding

This work was supported by the Major Project on Education and Teaching Management of Anhui Province (2023jxgl074) and the Major Project on “Four New” Research and Reform Practice of Anhui Province (2023sx170).

Data availability

In order to protect the privacy of participants, the datasets from this study are not publicly available. Researchers with reasonable academic requests may contact the corresponding author to obtain access.

Declarations

Ethics approval and consent to participate

The study protocol was reviewed and approved by the Wuhan University Research Ethics Committee (Approval No. WHU-HSS-IRB2025059). All participants provided informed consent prior to participation, including consent to the use of their anonymized data for research reporting.

Consent for publication

Written informed consent for publication was obtained from all participants.

Competing interests

The authors declare no competing interests.