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What predicts mental health profiles in first-generation college freshmen?: the role of proactive personality and university environment

BMC Psychology volume 13, Article number: 166 (2025) Cite this article

Abstract

Background

The mental health of first-generation college students has received much attention from researchers. The dual-factor model of mental health emphasizes the integration of psychopathology and well-being to achieve a comprehensive assessment of mental health. Previous research has focused on the psychopathology and well-being of first-generation college students in isolation while ignoring the overall mental health development.

Aim

This study aims to identify the mental health profiles of first-generation college freshmen (indexed by symptoms of psychopathology and well-being) using a person-centered approach, and examine direct and interactive associations of proactive personality and university environment with mental health profiles.

Method

This study included 557 first-generation college freshmen recruited from universities in China. Participants completed measures assessing proactive personality, university environment, mental health continuum, and depression, anxiety, and stress. Latent profile analysis, multinomial logistic regression, and simple slope analyses were used to investigate these relationships.

Results

The results revealed four mental health profiles, namely flourishing mental health, moderate mental health, content-dominated but symptoms, and symptoms-dominated but content. A multinomial logistic regression analysis revealed that first-generation college freshmen with higher proactive personality and university environment were more inclined to fall into the flourishing mental health profile compared to other sub-optimal mental health profiles. The interaction term between proactive personality and university environment was significant. Specifically, compared to proactive first-generation college freshmen in high levels of university environment, those in low levels of university environment were more inclined to be categorized into the flourishing mental health profile rather than the symptoms-dominated but content profile.

Conclusion

These results underscore the diverse nature of mental health changes in first-generation college freshmen, underscoring the need for tailored prevention strategies.

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Introduction

With the expansion of higher education in China, first-generation college students account for approximately 70% of the college student population [1]. First-generation college students are students whose parents have not obtained a bachelor’s degree [2]. Compared to their non-first-generation peers, these students face unique challenges in college. Due to the lack of family economic, social and cultural capital, they often encounter accumulated disadvantages, including poor academic preparation, financial hardships, and acculturation difficulties [3, 4]. First-generation college students find it hard to obtain support from family and friends and lack the necessary skills and indirect experiences to access resources and opportunities throughout their college years [3, 5]. These adverse factors increase their vulnerability to mental health issues, including depression, anxiety, stress, and suicidal ideation [6, 7]. Moreover, the transition from high school to university poses difficulties. Students navigate changes in identity, academics, and interpersonal interactions during their first year [8, 9]. Focusing on the first-generation college freshman is of great significance for predicting students’ college adjustment and preventing mental health risks [10].

The dual-factor model of mental health proposes that mental health should be considered as a holistic state, encompassing both the absence of mental illness and the presence of positive well-being [11]. Symptoms of psychopathology and well-being are distinct but essential components of mental health; their integration enables a more comprehensive assessment. However, previous research on the mental health of first-generation college students has largely approached the issue from the psychopathology perspective, focusing solely on mental illness. This approach can only provide a one-sided reflection of mental health status [12]. Additionally, not all first-generation college students experience mental health risks, even in unfavorable situations. The mental health patterns among first-generation college students vary significantly, indicating considerable heterogeneity within this group. Previous variable-centered studies have been unable to explore the different developmental patterns of mental health among first-generation college students. Addressing these limitations, this research employs a person-centered approach based on the dual-factor model of mental health, integrating both negative indicators (i.e. depression, anxiety, and stress) and positive indicators (i.e. well-being) to explore the natural developmental patterns of mental health among first-generation college students.

Why do first-generation college students exhibit varying patterns of mental health? Based on the conservation of resources theory, individuals’ well-being and health are shaped by both personal resources (e.g., proactive personality) and environmental factors (e.g., university environment). Particularly in stressful situations, abundant personal resources promote individuals to cope with uncertainty and challenges, thereby enhancing their well-being and health. Furthermore, the theory posits that resources flow through “caravan passageways”, which refer to environmental factors that can either enhance or hinder the personal resources [13]. A supportive, stable, and secure environment is more conducive to facilitate personal resource utilization. Specifically, proactive personality is defined as an individual’s stable tendency to engage in proactive behavior to affect environmental change, and it is classified as a personal resource [14]. This personality allows individuals to better manage transitions and navigate uncertainties and challenges in their environment. Additionally, a supportive and inclusive university environment significantly enhances the effectiveness of proactive personality in promoting mental health. Hence, this research explores the direct and interactive relationships between proactive personality, university environment and mental health profiles among first-generation college students.

The dual-factor model of mental health

Traditional mental health assessment has primarily been grounded in the psychopathology perspective, defining mental health as the absence of illness. Nevertheless, the emergence of positive psychology has shifted researchers’ focus toward positive mental health indicators, such as well-being. The dual-factor mental health model conceptualizes mental health as a holistic state, encompassing both the absence of mental illness and the presence of positive well-being, which enables individuals to develop their full potential [11, 15, 16]. Symptoms of psychopathology and well-being are significant and distinct components of mental health. A comprehensive evaluation of mental health requires the integration of both components [17]. Based on this framework, at least four sub-groups of mental health can be identified: (a) Flourishing (low symptoms and high well-being); (b) Troubled (high symptoms and low well-being); (c) Vulnerable (low symptoms and low well-being); and (d) Symptomatic but content (high symptoms and high well-being).

Researches have supported the benefits of the dual-factor mental health approach over traditional psychopathology-based approaches to mental health classification. The four mental health subgroups differed in academic, physical health, interpersonal relationships, and social functioning. Compared to the other three mental health groups, students in the flourishing group achieve the higher levels of academic performance, life quality, and life satisfaction [18, 19]. A research focusing on adolescent indicates that flourishing students excel in academic outcomes, academic self-concept and goals, social support, and social relationships relative to vulnerable students [17, 20, 21]. This underscores that the mere absence of symptoms is insufficient for achieving optimal functioning [22]. Additionally, while both the troubled group and the symptomatic but content group exhibit symptoms of psychopathology, students in the symptomatic but content group demonstrate superior social functioning and physical health than those in the troubled group [17]. Previous studies suggest that the dual-factor mental health model provides a more nuanced description of mental health functioning.

Applying latent profile analysis to investigate mental health among first-generation college student

Previous research using a variable-centered approach to examine the mental health of first-generation college students has produced mixed results. Studies grounded in the deficit framework argue that first-generation college students encounter accumulated disadvantages that can deteriorate their mental health [7]. Compared to their non-first-generation peers, first-generation college students tend to struggle in college, experiencing higher levels of anxiety, depression, and stress, along with lower levels of well-being and life satisfaction [7, 23, 24]. Stephens et al. found that they experience “cultural mismatch” in college, which can lead to increased stress and emotional issues [25]. Conversely, other researches based on the asset framework suggest that first-generation college students possess potential resources, such as resilience and school support [4, 26]. These resources contribute to helping them cope with adverse situations and maintain positive mental health status [27]. Studies found that the levels of depression, anxiety, stress, and life satisfaction among first-generation college students are comparable to non-first-generation college students [4, 27, 28]. A longitudinal study revealed a significant trend of improvement in depressive symptoms among first-generation college students during their college years [4]. These inconsistent results indicate considerable heterogeneity within this group. Previous variable-centered studies have examined different mental health indicators in isolation, and ignored the natural development patterns of mental health.

Latent profile analysis is a person-centered approach that classifies individuals based on responses to a set of continuous indicators [29]. Compared with the variable-centered approach, the person-centered approach has two advantages. First, the variable-centered approach assumes sample homogeneity and treats it as a single undifferentiated entity. In contrast, the person-centered approach emphasizes group heterogeneity and considers the sample to be composed of subgroups with different characteristics [30]. This approach more accurately reflects the complexity of real world [31]. Second, the person-centered approach facilitates the exploration of complex interactions among variables, rather than merely analyzing a single variable. This approach reveals hidden structures and patterns in datasets, identifies subgroup characteristics, and enables the examination of relationships between subgroups, predictors, and outcomes [32, 33]. Therefore, this study employs latent profile analysis to uncover distinct mental health profiles among first-generation college students.

Previous dual-factor studies using latent profile analysis have focused on child, adolescent, and adult populations. For example, a study conducted among employees in China identified four mental health subgroups: flourishing, symptomatic but content, vulnerable, and troubled [34]. Studies focusing on child and adolescent populations identified three (i.e., flourishing, vulnerable, and troubled) and five (i.e., flourishing, good mental health, moderate mental health, symptomatic but content, and troubled) mental health profiles, respectively [18, 22]. These studies indicate that mental health profiles differ slightly from the four hypothesized groups of dual-factor model. Notably, the flourishing mental health group tends to be the most stable. To date, there has been no study investigating the mental health of first-generation college students based on the dual-factor model. Based on prior research findings, we anticipate the emergence of a flourishing mental health subgroup among first-generation college students, coexisting with other sub-optimal mental health groups.

Proactive personality and mental health profiles

Not all first-generation college students situated in disadvantaged situations encounter mental health issues. The conservation of resource theory proposes that abundant personal resources facilitate individuals to cope with unfavorable situations, thereby enhancing their well-being and health [35]. Individuals who initially have a set of resources have more opportunities to acquire new resources through investing resources, thus creating the resource gain spirals. Furthermore, accumulating resources contributes to the maintenance of mental health. This study focuses on the impact of proactive personality, considered a personal resource, on mental health. This is because mental health is emphasized as a state of positive psychological well-being, which includes both the absence of mental illness and the presence of thriving [11]. Individuals with proactive personalities are more likely to engage in proactive, change, and future-oriented behaviors [36]. Such constructive behavior forms a crucial foundation for personal prosperity [37]. Proactive personality, characterized as a stable, positive, and healthy trait [38], has a profound impact on mental health.

Many studies indicate a positive association between proactive personality and mental health. Researches involving college student populations have found that proactive personality is positively correlated with subjective well-being [39] and negatively correlated with stress, anxiety, and depression [40]. Veterans, identified as an at-risk group, have more mental health issues. And proactive personality, as a personal resource, helps them better cope with stressful situations and promotes their overall well-being [41]. These studies suggest that proactive personality may play a crucial role in the mental health of first-generation college students. Based on the results of variable-centered studies, we assume that proactive first-generation college students are more inclined to fall into the flourishing mental health group compared to the other sub-optimal mental health groups.

University environment and mental health profiles

Perceptions of the university environment refer to how welcomed and comfortable students feel in their educational setting [42]. The university environment, as an important part of social support system, influences the healthy development of college students. Family members of first-generation college students lack experience in higher education. It is difficult for families to provide support for students’ adjustment and development in college [42]. However, school is the primary setting for an individual’s early life activities in addition to the family. The support perceived by first-generation college students in the university environment is highly conducive to their healthy development. The stage-environment fit theory proposes that students’ healthy development necessitates an environment that aligns with their psychological needs [43]. A supportive university environment addresses students’ psychological needs for autonomy, competence, and relatedness, thereby enhancing their mental health [44].

Previous research has found a link between the university environment and mental health. A study by Gloria et al. found that Latino college students who perceived more barriers at university reported lower subjective well-being [45]. Over time, a positive school climate drives students to develop flourishing mental health trajectories rather than sub-optimal mental health trajectories [46]. Based on previous research, we assume that first-generation college students who perceive higher levels of comfort and popularity in the university environment are more inclined to fall into the flourishing mental health group compared to the other sub-optimal mental health groups.

The interactive associations of proactive personality and university environment with mental health profiles

According to the conservation of resource theory, individuals’ well-being and health are shaped by the interaction between the environment (such as university environment) and personal resources (such as proactive personality). This theory introduces the concept of caravan passageways. Caravan passageways refer to environmental conditions that can either enhance or hinder individual resources. A supportive, stable, and safe environment will facilitate individuals to utilize resources more effectively. In this study, the utility of proactive personality as a personal resource is influenced by environmental factors. A supportive and inclusive university environment is conducive to student initiative and enhances the effective utilization of proactive personality. Prior research on employees has found that in supportive and fair work environments, the positive influences of proactive personality on organizational behaviors and outcomes (i.e., creativity and team performance) are amplified [47, 48]. Wan et al. found that safe organizational climate motivates proactive employees to exhibit less disruptive behavior [49]. Building on these findings, we propose that proactive first-generation college students with higher levels of university environment tend to fall into the flourishing mental health group than those with lower levels of university environment.

The current study

The aim of this study was to identify subgroup patterns of first-generation college freshmen’ mental health by combining positive (i.e., well-being) and negative (i.e., depression, anxiety, and stress) indicators of mental health. In addition, we explore the direct and interactive associations of proactive personality and university environment with these emerging mental health profiles. This study provides a comprehensive understanding of mental health patterns among first-generation college freshmen, extending beyond previous variable-centered researches. Additionally, we provide insights into how individual and environmental factors influence the mental health patterns of first-generation college freshmen from the perspective of individual-environment interaction, filling a gap in the existing literature. We propose three primary hypotheses for this study.

Hypothesis 1

(H1): First-generation college freshmen may exhibit several distinct mental health patterns, including flourishing mental health and other sub-optimal mental health groups.

Hypothesis 2

(H2): First-generation college freshmen with higher levels of proactive personality and university environment are more inclined to fall into the flourishing mental health group compared to the other sub-optimal mental health groups.

Hypothesis 3

(H3): There are interactive associations of proactive personality and university environment with latent mental health subgroups. Proactive first-generation college freshmen with high levels of university environment tend to fall into the flourishing mental health group than those with low levels of university environment.

Materials and methods

Participants and procedure

A randomized cluster sampling method was used to recruit 575 first-generation college freshmen from two undergraduate universities in the eastern and central regions of China. 18 participants answered the polygraph questions incorrectly, so we proceeded with formal analyses using the remaining sample of 557 first-generation college freshmen (341 females, 216 males; Mage = 18.44 years, SD = 0.77). Of these, 343 participants were from the university in the central region, while 214 were from the university in the eastern region. The inclusion criterion for first-generation college students was that neither parent had obtained a bachelor’s degree. In addition, Chinese higher education has evolved from an elitist stage to a popularized stage. Consequently, previous studies have classified undergraduate universities into high-level and general universities [50, 51]. Generally, universities included in the “double world-class project” announced by the Ministry of Education of China are classified as high-level universities, while the others are considered general universities [52, 53]. All participants in this study attended general universities.

In this study, the questionnaires were distributed in paper format. Participants filled out questionnaires during class. Prior to participation, each participant was required to sign an informed consent. The researchers explained the purpose of the study to the participants and emphasized that participation would be anonymous and voluntary. All procedures adhered to the Declaration of Helsinki. This study was conducted from December 18 to 22, 2023, coinciding with the end of the freshmen’s first semester. Data from all participants were collected within five days.

Measures

Proactive personality scale

Bateman and Crant developed the proactive personality scale [14]. The Chinese version of this scale was adapted by Shang and Gan [54]. The scale is unidimensional and consists of 11 items (e.g., When faced with problems, I confront them head-on). Participants scored their responses employing a 7-point Likert scale (1 = “Strongly Disagree”, 7 = “Strongly Agree”). Higher scores reflect stronger proactive personality tendency. In this research, the Cronbach’s α values of the total scale was 0.88.

The university environment scale

The university environment scale was developed by Gloria and Kurpius [42]. This scale consists of 14 items (e.g., I do not feel valued as a student on campus), of which 5 are reverse-scored. Participants responded to a 7-point Likert scale (1 = “Strongly Disagree”, 7 = “Strongly Agree”). The higher scores indicate that students perceive a higher level of comfort and welcome in the university environment. The scale was translated into Chinese employing a standard back-translation method. Existing study has demonstrated that the scale has good internal consistency [55]. In this research, the Cronbach’s α values of the total scale was 0.89.

The mental health Continuum—Short form

This scale was developed by Keyes and the Chinese version was translated by Yin and He [56, 57]. It consists of 14 items and contains three dimensions of emotional (e.g., I feel happy), psychological (e.g., I feel good at managing the responsibilities in daily life), and social well-being (e.g., I feel that our society is becoming a better place). Scoring was conducted using a 6-point Likert scale (0 = “Never”, 5 = “Every Day”). Higher scores reflect higher levels of well-being. In this research, the Cronbach’s α values of the overall scale and its subscales were 0.96 (overall scale), 0.91 (emotional well-being), 0.93 (psychological well-being), and 0.90 (social well-being).

The depression anxiety stress Scale—21-item version

This scale is a shortened version developed by Lovibond and Lovibond and the Chinese version was translated and modified by Moussa, Lovibond and Laub [58, 59]. This scale was used to assess the psychological symptoms. This scale consists of 21 items and contains three subscales of depression (e.g., I felt that life was meaningless), anxiety (e.g., I was worried about situations in which I might panic and make a fool of myself), and stress (e.g., I found it hard to wind down). A 4-point Likert scale (0 = “Not True”, 3 = “Very True”) was used to rate the frequency and severity of experiencing symptoms over the previous week. Higher scores indicate higher levels of depression, anxiety or stress. In this present study, the Cronbach’s α values of the total scale and its subscales were 0.97 (full scale), 0.92 (depression), 0.86 (anxiety), and 0.91 (stress).

Data analyses

SPSS 21.0, Mplus 7.0, and R 4.2.2 software were used to analyze the data in this study. Descriptive analysis and Pearson correlation analysis for all variables were performed using SPSS 21.0. For the person-centered analysis, we applied Latent Profile Analysis to investigate mental health profiles in Mplus 7.0. We gradually increased the number of latent profiles and calculated the parameters of each model. Then model comparisons were performed to determine the optimal model based on various model fit indices, which included Akaike information criterion, Bayesian information criterion, sample-adjusted BIC and entropy, etc [60]. In this study, 4 classes were identified as the best latent profile models. To confirm clear distinctions in mental health profiles across negative and positive indicators, we conducted multivariate analysis of variance and the followup post hoc test. In the last step, we employed multinomial logistic regression to explore the effects of proactive personality and college environment on mental health profiles. To examine the interaction of proactive personality and university environment, we carried out simple slope analyses and plotted graphs using the “nnet package” in R 4.2.2 [61].

Results

Preliminary analyses

Table 1 presents the means, standard deviations, and Pearson’s correlations among the variables in this study. The results indicate that first-generation college freshmen in the sample have moderately high levels of emotional, psychological, and social well-being and low levels of depression, anxiety, and stress. Proactive personality and university environment were significantly negatively correlated with depression, anxiety, and stress, while positively correlated with emotional, psychological, and social well-being. A negative association was also identified between the symptoms of psychopathology indicators and the well-being indicators.

Table 1 Descriptive analysis and correlation
Full size table

Latent profile analysis

Six indicators were used in the LPA. Each indicator was calculated by averaging the corresponding measures for depression (7 items), anxiety (7 items), stress (7 items), emotional well-being (3 items), psychological well-being (6 items), and social well-being (5 items). We increased the number of classes in the latent profile models from one to five. Table 2 shows the fit indices for each latent profile model. No more class models were explored because the LMR yielded insignificant results following the 5-class model. The entropy values of all models above 0.70 show acceptable classification accuracy. The p values of LMR tests indicated that the 5-class model was rejected. In the 2-, 3-, and 4-class models, the AIC, BIC, and aBIC values decreased as the number of profiles increased, suggesting a better fit for the models. Therefore, the 4-class model was considered as the optimal model. Figure 1 indicated the standardized means of depression, anxiety, stress, emotional well-being, psychological well-being, and social well-being about the emerging profiles.

Table 2 Fit statistics for latent profile models based on mental health
Full size table
Fig. 1
figure 1

Patterns of mental health in the four-profile model. Note: DEP = depression; ANX = anxiety; STR = stress; EMO = emotional well-being; PSY = psychological well-being; SOC = social well-being

Full size image

The findings of the MANOVA analysis indicate the degree of differences among the four mental health classes concerning each mental health indicator. The findings showed that all indicators exhibited significant differences across the four classes (Table 3). Each of the four mental health profiles we identified was described. The first class (n = 254, 45.6%) reported the lowest scores in depression, anxiety, and stress, alongside higher scores in emotional, psychological, and social well-being, which we termed “flourishing mental health”. The second class (n = 57, 10.3%) reported moderate scores in depression, anxiety, and stress, but the highest scores in emotional, psychological, and social well-being, which we termed “content-dominated but symptoms”. In the third class (n = 148, 26.6%), first-generation college freshmen reported the lower scores in depression, anxiety, and stress. The scores of emotional, psychological and social well-being were around the scales’ midpoints. We labeled this class “moderate mental health”. In the fourth class (n = 97, 17.4%), first-generation college freshmen reported the highest scores in depression, anxiety, and stress. The scores of emotional, psychological and social well-being were above the scales’ midpoints. We labeled this class “symptoms-dominated but content”.

Table 3 Mean differences in study indicators across mental health profiles
Full size table

Multinomial logistic regression analysis

Lastly, we sought to test whether proactive personality and university environment play an important role in identifying emerging profiles. In multinomial logistic regression analysis, the flourishing mental health profile was used as the reference group. As shown in Table 4, first-generation college freshmen reporting high levels of proactive personality and university environment were more inclined to be categorized to the flourishing mental health profile than the moderate mental health and symptoms-dominated but content profiles. Moreover, the interaction term between proactive personality and university environment was significant in the profiles contrast between the symptoms-dominated but content profile and flourishing mental health profile.

Table 4 Multiple multinomial regression analysis predicting mental health profiles
Full size table

The findings of simple slope analysis show that the negative effect of proactive personality on the probability between the “symptoms-dominated but content” profile and the “flourishing mental health” profile was borderline significant at low levels of university environment (M -1SD; b = -0.39, SE = 0.22, t = -1.75, p =.08). However, the effect of proactive personality on the probability between the “symptoms-dominated but content” profile and the “flourishing mental health” profile was insignificant at high levels of university environment (M + 1SD; b = 0.65, SE = 0.41, t = 1.58, p =.11). In Fig. 2, we illustrate how the predicted probability for mental health of first-generation college freshmen varies across proactive personality scores (1–7) for three levels of university environment (Mean, Mean-1SD, and Mean + 1SD). Proactive personality increases the predicted probability of being the memberships of the flourishing mental health profile more rapidly in the low levels of university environment than in the high levels of university environment. These results indicate that first-generation college freshmen possessing lower levels of university environment reap larger benefits from proactive personality than first-generation college freshmen possessing higher levels of university environment.

Fig. 2
figure 2

Interaction effect of proactive personality and university environment on the probability of “flourishing mental health” and “symptoms-dominated but content” profiles

Full size image

Discussion

Mental health profiles were explored based on a variety of indicators among first-generation college freshmen. The results revealed four mental health profiles. Additionally, we examined the associations of personal resource and university environment with these emerging profiles. Our findings are discussed in detail below.

This research identified four distinct mental health profiles among first-generation college freshmen, categorized as flourishing mental health, moderate mental health, symptoms-dominated but content, and content-dominated but symptoms profiles. These results indicate that there is significant group heterogeneity in the mental health of first-generation college freshmen, confirming our hypothesis (H1). The flourishing and moderate mental health profiles in our study are similar with the results of previous studies. Two person-centered studies examined the mental health of Korean primary school students and California high school students, respectively, both of which identified two classes: flourishing mental health and moderate mental health [62, 63]. In addition, the profiles of symptoms-dominated but content and the content-dominated but symptoms were identified. This suggests that symptoms and well-being can coexist as two distinct aspects of mental health. Although first-generation college freshmen face mental health risks, they also possess positive potential. Positive interventions for the mental health of first-year students can effectively prevent further deterioration of mental health.

Inconsistent with previous dual-factor research, the vulnerable and troubled groups did not emerge in this study. One possible explanation is that the first-generation college freshmen in this study exhibited higher levels of well-being, which may have hindered the identification of these groups. First-year students have recently transitioned from the high-pressure, centralized management mode of high school to the relatively free and relaxed management mode of college [64]. Freshmen do not really face the pressure of academic and skill exams and job search in their first semester [65]. In such a relatively relaxed environment, students are more likely to experience a sense of well-being. A study showed that first-year students possessed higher levels of subjective well-being compared to sophomores and seniors [66]. In addition, the assumptions about the equalizing consequences of social selection in the education propose that disadvantaged students who access higher education possess strong learning abilities and excellent qualities after multiple stages of selections [67, 68]. These contribute to the development of positive mental health. A study by Wang et al. on first-generation college students in China found that their levels of subjective well-being were generally moderately high [69].

The direct associations of proactive personality and university environment with these emerging profiles were examined. The results indicate that first-generation college freshmen with higher levels of proactive personality and university environment were more inclined to be categorized into the flourishing mental health profile compared to the moderate mental health and symptoms-dominated but content profiles. Our hypothesis (H2) is confirmed. Our findings align with previous research. Proactive personality encourages students to take initiative and self-regulate, helping them cope with the new environment’s stresses and challenges [14]. This personality ultimately reduces mental health crises [70]. Moreover, Fink found that increased support and a sense of belonging within the university environment was able to meet students’ basic psychological needs, which in turn significantly improved their mental health [71].

The interactive associations of proactive personality and university environment with these emerging profiles were examined. The interactive effect of proactive personality and university environment on the probability between the symptoms-dominated but content group and the flourishing mental health group was significant. Specifically, first-generation college freshmen with lower levels of university environment benefit more from proactive personality than those with higher levels of university environment. This finding is contrary to our hypothesis (H3). However, this result may be supported by an alternative view from conservation of resource theory. This view highlights that human cognition tends to significantly overemphasize resource loss while underestimating resource gain [72]. The expectation of future resource losses prompts individuals to quickly and effectively utilize their personal resources to counteract such losses. When first-generation college freshmen perceive lower levels of comfort and popularity in university environment, this means they may anticipate to face greater adversity or resources losses in the future. This motivates them to maximize their personal resources for positive utility.

Contributions and limitations

This research made several important contributions. Firstly, this research provides a comprehensive understanding of first-generation college freshmen’ mental health patterns, which extends beyond previous variable-centered researches. Along with the flourishing mental health and moderate mental health profiles, we identified the symptoms-dominated but content and content-dominated but symptoms profiles, which has previously been overlooked [22]. Secondly, we provide insights into how individual and environmental factors directly and interactively influence the mental health patterns of first-generation college freshmen from the perspective of individual-environment interaction, filling a gap in the existing literature. This study explores the positive effects of proactive personality on mental health in the context of specific environmental conditions, which contributes to a more contextualized perspective on the effectiveness of proactive personality.

From a practical standpoint, this study helps to clarify the heterogeneity within first-generation college freshmen regarding their mental health characteristics and needs, and to recognize the role of protective factors for different mental health patterns. Accordingly, we propose several crisis prevention and intervention strategies. First, colleges should assess students’ mental health on a more comprehensive approach. The screening scales selected in the annual psychological census should include scales that reflect positive aspects of mental health, such as the mental health continuum scale. Second, colleges should establish personal psychological files and propose targeted interventions based on the different needs of different students. For example, teachers should pay more attention to first-generation college students exhibiting symptoms-dominated but content pattern. These students experience significant mental health risks. Teachers should adopt psychological interventions such as mindfulness and cognitive behaviour therapy to develop their ability to defuse anxiety, stress and depression [73, 74]. Students in the moderate mental health group exhibited no severe psychological symptoms but reported the lowest levels of well-being. Therefore, teachers should conduct positive psychology programs to develop students’ positive strengths rather than eliminate negative symptoms [75]. Finally, proactive personality and university environment can predict mental health profiles. Colleges and faculty should foster a diverse and inclusive campus culture and promote first-generation college students to be proactive in setting goals and coping with current challenges [76]. Such efforts can enhance their mental health.

This research has several limitations. Firstly, the sample comprised only first-year students from universities in mainland China. As a result, the four identified mental health profiles require further replication in other populations (e.g., individuals from different grades or cultural backgrounds). Secondly, all factors examined in this research relied on self-reports. This study could have been enhanced by including data from other sources, such as teachers, peers, and parents, to complement the self-reported information. Thirdly, this study employed a cross-sectional design, which precludes inferences about how mental health changes over time and about the causal relationships between mental health and the antecedent variables. Future research can adopt a longitudinal design to assess. Finally, this study focused exclusively on proactive personality and university environment. Future researchers should also consider exploring additional personal factors (e.g., big five personality traits) and environmental factors (e.g., family functionality) to predict mental health profiles among first-generation college student [77, 78].

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Zhang HF, Zhao L, Guo F. A portrait of first-generation college students in China: an analysis based on the China college student survey. Tsinghua J Educ. 2016;37:72–8. https://doi.org/10.14138/j.1001-4519.2016.06.007207

    Article  Google Scholar 

  2. Atherton MC. Academic preparedness of first-generation college students: different perspectives. J Coll Stud Dev. 2014;55(8):824–9. https://doi.org/10.1353/csd.2014.0081

    Article  Google Scholar 

  3. House LA, Neal C, Kolb J. Supporting the mental health needs of first generation college students. J. College Stud. Psychother. 2020;34(2):157–167. https://doi.org/10.1080/87568225. 2019.1578940.

  4. Wilbur TG. Stressed but not depressed: a longitudinal analysis of first-generation college students, stress, and depressive symptoms. Soc Forces. 2021;100(1):56–85. https://doi.org/10.1093/sf/soaa091

    Article  Google Scholar 

  5. Gloria AM, Castellanos J. Desafios y Bendiciones: a multiperspective examination of the educational experiences and coping responses of first-generation college Latina students. J Hispanic High Educ. 2012;11(1):82–99. https://doi.org/10.1177/1538192711430382

    Article  Google Scholar 

  6. Jeong HJ, Kim S, Lee J. Mental health, life satisfaction, supportive parent communication, and help-seeking sources in the wake of COVID-19: first-generation college students (FGCS) vs. non-first-generation college students (non-FGCS). J Coll Stud Psychother. 2023;37(2):71–86. https://doi.org/10.1080/87568225.2021.1906189

    Article  Google Scholar 

  7. Cody K, Scott JM, Simmer-Beck M. Examining the mental health of university students: a quantitative and qualitative approach to identifying prevalence, associations, stressors, and interventions. J Am Coll Health. 2024;72(3):776–86. https://doi.org/10.1080/07448481

    Article  PubMed  Google Scholar 

  8. Brazil N, Andersson M. Mental well-being and changes in peer ability from high school to college. Youth Soc. 2018. https://doi.org/10.1177/0044118X18764526

    Article  Google Scholar 

  9. Brissette I, Scheier MF, Carver CS. The role of optimism in social network development, coping, and psychological adjustment during a life transition. J Pers Soc Psychol. 2022;82:102.

    Article  Google Scholar 

  10. Auerbach RP, Mortier P, Bruffaerts R, Alonso J, Benjet C, Cuijpers P,… Kessler RC.WHO world mental health surveys international college student project: prevalence and distribution of mental disorders.J. Abnorm. Psychol. 2018;127(7):623–638. https://doi.org/10.1037/abn0000362.

  11. Greenspoon PJ, Saklofske DH. Toward an integration of subjective well-being and psychopathology. Soc Indic Res. 2001;54(1):81–108.

    Article  Google Scholar 

  12. Keyes CLM. The mental health continuum: from languishing to flourishing in life. J Health Soc Behav. 2002;43:207–22. https://doi.org/10.2307/3090197

    Article  PubMed  Google Scholar 

  13. Hobfoll SE. Social and psychological resources and adaptation. Rev Gen Psychol. 2002;6:307–24. https://doi.org/10.1037/1089-2680.6.4.307

    Article  Google Scholar 

  14. Bateman TS, Crant JM. The proactive component of organizational behavior: a measure and correlates. J Organ Behav. 1993;14(2):103–18. https://doi.org/10.1002/job.4030140202

    Article  Google Scholar 

  15. Westerhof GJ, Keyes CL. Mental illness and mental health: the two continua model across the lifespan. J Adult Dev. 2010;17:110–9. https://doi.org/10.1007/s10804-009-9082-y

    Article  PubMed  Google Scholar 

  16. World Health Organization. Promoting mental health: concepts, emerging evidence, practice. 2004. https://www.who.int/publications/i/item/9241562943. Accessed 18 June 2024.

  17. Suldo SM, Shaffer EJ. Looking beyond psychopathology: the dual-factor model of mental health in youth. School Psych Rev. 2008;37(1):52–68. https://doi.org/10.1080/02796015.2008.1208790

    Article  Google Scholar 

  18. Gregory T, Monroy NS, Grace B, Finlay-Jones A, Brushe M, Sincovich A, et al. Mental health profiles and academic achievement in Australian school students. J Sch Psychol. 2024;103. https://doi.org/10.1016/j.jsp.2024.101291

  19. Kim EK, Dowdy E, Furlong MJ, You S. Mental health profiles and quality of life among Korean adolescents. Sch Psychol Int. 2017;38(1):98–116. https://doi.org/10.1177/0143034316682296

    Article  Google Scholar 

  20. Suldo SM, Thalji A, Ferron J. Longitudinal academic outcomes predicted by early adolescents’ subjective well-being, psychopathology, and mental health status yielded from a dual factor model. J Posit Psychol. 2011;6(1):17–30. https://doi.org/10.1080/17439760.2010.536774

    Article  Google Scholar 

  21. Suldo SM, Thalji-Raitano A, Kiefer SM, Ferron JM. Conceptualizing high school students’ mental health through a dual-factor model. School Psychol Rev. 2016;45(4):434–57. https://doi.org/10.17105/SPR45-4.434-457

    Article  Google Scholar 

  22. Zhou J, Jiang S, Zhu X, Huebner ES, Tian L. Profiles and transitions of dual-factor mental health among Chinese early adolescents: the predictive roles of perceived psychological need satisfaction and stress in school. J Youth Adolesc. 2020;49(10):2090–108. https://doi.org/10.1007/s10964-020-01253-7

    Article  PubMed  Google Scholar 

  23. Jenkins SR, Belanger A, Connally ML, Duron KM. First-generation undergraduate students’ social support, depression, and life satisfaction. J Coll Couns. 2013;16(2):129–42. https://doi.org/10.1002/j.2161-1882.2013.00032.x

    Article  Google Scholar 

  24. Liang W, Liu S, Zhao C. Impact of student-supervisor relationship on postgraduate students’ subjective well-being: a study based on longitudinal data in China. High Educ. 2021;1–33. https://doi.org/10.1007/s10734-020-00644-w

  25. Stephens NM, Townsend SS, Markus HR, Phillips LT. A cultural mismatch: independent cultural norms produce greater increases in cortisol and more negative emotions among first-generation college students. J Exp Soc Psychol. 2012;48(6):1389–93. https://doi.org/10.1016/j.jesp.2012.07.008

    Article  Google Scholar 

  26. Cheng M, Kang YJ. Things are increased by being diminished: another discourse on the cultural capitals of underclass. Tsinghua J Educ. 2016;37(4):83–91.

    Google Scholar 

  27. Rockwell DM, Kimel SY. A systematic review of first-generation college students’ mental health. J Am Coll Health. 2023;1–13. https://doi.org/10.1080/07448481.2023.2225633

  28. Garriott PO, Hudyma A, Keene C, Santiago D. Social cognitive predictors of first-and non-first-generation college students’ academic and life satisfaction. J Couns Psychol. 2015;62(2):253. https://doi.org/10.1037/cou0000066

    Article  PubMed  Google Scholar 

  29. Wang Y, Kim E, Yi Z. Robustness of latent profile analysis to measurement noninvariance between profiles. Educ Psychol Meas. 2022;82(1):5–28. https://doi.org/10.1177/0013164421997896

    Article  PubMed  Google Scholar 

  30. Howard MC, Hoffman ME. Variable-centered, person-centered, and person-specific approaches: where theory Meets the method. Organ Res Methods. 2018;21(4):846–76. https://doi.org/10.1177/1094428117744021

    Article  Google Scholar 

  31. Morin AJS, Bujacz A, Gagné M. Person-centered methodologies in the organizational sciences: introduction to the feature topic. Organ Res Methods. 2018;21(4):803–13. https://doi.org/10.1177/1094428118773856

    Article  Google Scholar 

  32. Aydin MA, Yıldız M, Kiyici M, Yildiz M, Kirksekiz A, Kızıloğlu Ş. The effect of digital obesity and phubbing level on life satisfaction: latent profile analysis. BMC Psychol. 2024;12(1):754. https://doi.org/10.1186/s40359-024-02256-w

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wen ZL, Xie JY, Wang HH. Principles, procedures and programs of latent class models. J East China Normal Univ. 2023;1:1–15. https://doi.org/10.16382/j.cnki.1000-5560.2023.01.001

    Article  Google Scholar 

  34. Xu Y, Xiong S, Zhang B, Chen Y. Dual-factor model of mental health in Chinese employees: a latent profile analysis. J Happiness Stud. 2023;24(8):2627–45. https://doi.org/10.1007/s10902-023-00695-7

    Article  Google Scholar 

  35. Hobfoll SE, Halbesleben J, Neveu JP, Westman M. Conservation of resources in the organizational context: the reality of resources and their consequences. Annu Rev Organ Psych. 2018;5(1):103–28. https://doi.org/10.1146/annurev-orgpsych-032117-104640

    Article  Google Scholar 

  36. Tornau K, Frese M. Construct clean-up in proactivity research: a meta‐analysis on the Nomological net of work‐related proactivity concepts and their incremental validities. Appl Psychol. 2013;62(1):44–96. https://doi.org/10.1111/j.1464-0597.2012.00514.x

    Article  Google Scholar 

  37. Elena S. Phenomenon of proactive coping behavior in occupational health psychology. Organizatsionnaya Psikologiya. 2020;10(4):156–83.

    Google Scholar 

  38. Duffy RD, Blustein DL, Diemer MA, Autin KL. The psychology of working theory. J Couns Psychol. 2016;63(2):127. https://doi.org/10.1037/cou0000140

    Article  PubMed  Google Scholar 

  39. Zhou W, Li M, Xin L, Zhu J. The interactive effect of proactive personality and career exploration on graduating students’ well-being in school-to-work transition. Int J Ment Health Pr. 2018;20(2):41–54. https://doi.org/10.32604/IJMHP.2018.010737

    Article  Google Scholar 

  40. Huang S, Yan X, Zhang J, Zhang X, Miao D, Wu S. Does meaning in life mediate the relationship between proactive personality and well-being? Soc Behav Pers. 2020;48(12):1–9. https://doi.org/10.2224/sbp.9453

    Article  Google Scholar 

  41. Grzesik ER, Ghosh A. Hope, proactive personality, coping styles, and satisfaction with life among veterans during COVID-19. Mil Psychol. 2023;35(5):440–50. https://doi.org/10.1080/08995605.2023.2204060

    Article  PubMed  PubMed Central  Google Scholar 

  42. Gloria AM, Kurpius SER. The validation of the cultural congruity scale and the university environment scale with Chicano/a students. Hisp J Behav Sci. 1996;18(4):533–49. https://doi.org/10.1177/07399863960184007

    Article  Google Scholar 

  43. Eccles JS, Roeser RW. Schools as developmental contexts during adolescence. J Res Adolescence. 2011;21(1):225–41. https://doi.org/10.1111/j.1532-7795.2010.00725.x

    Article  Google Scholar 

  44. Wang MT, Degol JL. School climate: a review of the construct, measurement, and impact on student outcomes. Educ Psychol Rev. 2016;28(2):315–52. https://doi.org/10.1007/s10648-015-9319-1

    Article  Google Scholar 

  45. Gloria AM, Castellanos J, Scull NC, Villegas FJ. Psychological coping and well-being of male Latino undergraduates: sobreviviendo La Universidad. Hisp J Behav Sci. 2009;31(3):317–39. https://doi.org/10.1177/0739986309336845

    Article  Google Scholar 

  46. Gao Q, Niu L, Wang W, Zhao S, Xiao J, Lin D. Developmental trajectories of mental health in Chinese early adolescents: school climate and future orientation as predictors. Res Child Adolesc Psychopathol. 2024;1–15. https://doi.org/10.1007/s10802-024-01195-9

  47. Horng JS, Tsai CY, Yang TC, Liu CH. Exploring the relationship between proactive personality, work environment and employee creativity among tourism and hospitality employees. Int J Hosp Manag. 2016;54:25–34. https://doi.org/10.1016/j.ijhm.2016.01.004

    Article  Google Scholar 

  48. Yu X, He B, Liu M, Wang A, Yuan Y. The effect of distributive justice climate on virtual team performance: a moderated mediation model. Front Psychol. 2022;13. https://doi.org/10.3389/fpsyg.2022.950581

  49. Wan J, Qin M, Zhou W, Wu Y. Effect of proactive personality on employees’ pro-social rule breaking: the role of promotion focus and psychological safety climate. Curr Psychol. 2024;43(14):12768–81. https://doi.org/10.1007/s12144-023-05362-x

    Article  Google Scholar 

  50. Zhou LP, Sun XZ, Yue CJ. Why educational investment pays off—high-level universities’ educational earnings and class distinctions in the context of higher education expansion. Educational Res. 2024;46(10):95–110.

  51. Jia RX, Li HB. Just above the exam cutoff score: elite college admission and wages in China. J Public Econ. 2021;196(6).

  52. Bao ZM. Research on the formation process and marginalization track of students with learning difficulties in high-level universities in China. China Youth Study. 2022;04112–9. https://doi.org/10.19633/j.cnki.11-2579/d.2022.0059

  53. Yang TR, Wang WJ. The patterns and characteristics of cross-border higher education of China’s high-level universities: a case study of 10 universities. Renmin Univ China Educ J. 2024;6:23–38.

    Google Scholar 

  54. Shang JY, Gan YQ. The influence of initiative personality on career decision-making self-efficacy of college graduates. Acta Scientiarum Naturalium Universitatis Pekinensis. 2009;45(3):548–54.

    Google Scholar 

  55. Wei M, Ku T-Y, Liao KY-H. Minority stress and college persistence attitudes among African American, Asian American, and Latino students: perception of university environment as a mediator. Cult Divers Ethn Min. 2011;17(2):195–203. https://doi.org/10.1037/a0023359

    Article  Google Scholar 

  56. Keyes CLM. Mental health in adolescence: is America’s youth flourishing? Am. J Orthopsychiat. 2006;76:395–402. https://doi.org/10.1037/0002-9432.76.3.395

    Article  Google Scholar 

  57. Yin KL, He JM. Reliability and validity of the mental health continuum-short form in adults. Chin Ment Health J. 2012;26(05):388–92. https://doi.org/10.3969/j.issn.100-6729.2012.05.015

    Article  Google Scholar 

  58. Lovibond SH, Lovibond PF. Manual for the depression anxiety stress scales. Sydney: Psychology Foundation; 1995.

    Google Scholar 

  59. Moussa MT, Lovibond PF, Laube R. Psychometric properties of a Chinese version of the 21-item depression anxiety stress scales (DASS21). Sydney: Transcultural Mental Health Centre; 2001.

    Google Scholar 

  60. Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model. 2007;14(4):535–69. https://doi.org/10.1080/10705510701575396

    Article  Google Scholar 

  61. Beck MW. Neural net tools: visualization and analysis tools for neural networks. J Stat Softw. 2018;85(11):1. https://doi.org/10.18637/jss.v085.i11

    Article  PubMed  PubMed Central  Google Scholar 

  62. Kim EK, Dowdy E, Furlong MM, You S. Complete mental health screening: psychological strengths and life satisfaction in Korean students. Child Indic Res. 2018;12:901–15. https://doi.org/10.1007/s12187-018-9561-4

    Article  Google Scholar 

  63. Moore SA, Dowdy E, Nylund-Gibson K, Furlong MJ. A latent transition analysis of the longitudinal stability of dual-factor mental health in adolescence. J Sch Psychol. 2019;73:56–73. https://doi.org/10.1016/J.JSP.2019.03.003

    Article  PubMed  PubMed Central  Google Scholar 

  64. Cao J, Wang K, Shi Y, Pan Y, Lyu M, Ji Y. The associations between social support change and physical activity trajectory from late adolescence to young adulthood. BMC Public Health. 2023;23(1):1496. https://doi.org/10.1186/s12889-023-16422-z

    Article  PubMed  PubMed Central  Google Scholar 

  65. Yin B. An investigation on the emotional management ability of preschool education students. J Weifang Eng Vocat Coll. 2020;33(04):58–63.

  66. Cheng T, Lin Q, Fu H. Love forgiveness and subjective well-being in Chinese college students: the mediating role of interpersonal relationships. Front Psychol. 2021;12. https://doi.org/10.3389/fpsyg.2021.634910

  67. Mare RD. Social background and school continuation decisions. J Am Stat Assoc. 1980;75(370):295–305.

    Article  Google Scholar 

  68. Stolzenberg RM. Educational continuation by college graduates. Am J Sociol. 1994;99(4):1042–77. https://doi.org/10.1086/230371

    Article  Google Scholar 

  69. Wang Q, Zhi K, Yu B, Cheng J. Social trust and subjective well-being of first-generation college students in China: the multiple mediation effects of self-compassion and social empathy. Front Psychol. 2023;14. https://doi.org/10.3389/fpsyg.2023.1091193

  70. Pfund GN, Bono TJ, Hill PL. A higher goal during higher education: the power of purpose in life during university. Transl Issues Psychol Sci. 2020;6(2):97. https://doi.org/10.1037/tps0000231

    Article  Google Scholar 

  71. Fink JE. Flourishing: exploring predictors of mental health within the college environment. J Am Coll Health. 2014;6(62):380–8. https://doi.org/10.1080/07448481.2014.917647

    Article  Google Scholar 

  72. Hobfoll SE. Conservation of resources: a new attempt at conceptualizing stress. Am Psychol. 1989;44(3):513–24. https://doi.org/10.1037/0003-066x.44.3.513

    Article  PubMed  Google Scholar 

  73. Alshahrani KM, Johnson J, Prudenzi A, O’Connor DB. The effectiveness of psychological interventions for reducing PTSD and psychological distress in first responders: a systematic review and meta-analysis. PLoS ONE. 2022;17(8). https://doi.org/10.1371/journal.pone.0272732

  74. Kim SY, Suh H, Oh W, Daheim J. (2021). Daily change patterns in mindfulness and psychological health: a pilot intervention. J. Clin. Psychol. 2021;77(3):496–515. https://doi.org/10.1002/jclp.23043

  75. Laakso M, Fagerlund Å, Lagerström M. Increasing student well-being through a positive psychology intervention: changes in salivary cortisol, depression, psychological well‐being, and hope. Appl Psychol Health Well Being. 2025;17(1). https://doi.org/10.1111/aphw.12616

  76. Greguras GJ, Diefendorff JM. Why does proactive personality predict employee life satisfaction and work behaviors? A field investigation of the mediating role of the self-concordance model. Pers Psychol. 2010;63(3):539–60. https://doi.org/10.1111/j.1744-6570.2010.01180.x

    Article  Google Scholar 

  77. Gil M, Kim SS, Min EJ. Machine learning models for predicting risk of depression in Korean college students: identifying family and individual factors. Front Public Health. 2022;10. https://doi.org/10.3389/fpubh.2022.1023010

  78. Kang W, Malvaso A. Personality traits and mental health: considering the role of age. Psychol Int. 2024;6(4):816–26. https://doi.org/10.3390/psycholint6040052

    Article  Google Scholar 

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Acknowledgements

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Funding

This work was supported by the Philosophy and Social Science Planning Project of Henan Province (Grant No. 2024BJY00246).

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Authors and Affiliations

  1. School of Education, Shanghai Normal University, Shanghai, China

    Ru Chen & Xin Gao

  2. School of Psychology, Henan University, Kaifeng, China

    Zekun Zhang

  3. College of Artificial Intelligence, Henan Institute of Economy and Trade, Zhengzhou, China

    Mingxue Hong

  4. College of Education Science, Henan Institute of Science and Technology, Xinxiang, China

    Lulu Zhang

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Contributions

R. C. contributed to the conceptualization, methodology, data collection, statistical analyses, writing-original draft, writing-review & editing, visualization, and funding acquisition. X. G. contributed to the conceptualization, methodology, writing-review & editing, and supervision. Z. Z. contributed to the data collection and writing-original draft. M. H. contributed to the data collection and data curation. L. Z. contributed to the writing-review, editing & revision. All authors contributed to the article and approved the submitted version.

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Correspondence to Xin Gao.

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This study was approved by the Research Ethics Committee of Shanghai Normal University (No. 2023035). All procedures performed in the study involving human participants were in accordance with ethical standards. Informed consent was obtained from all individual participants included in the study.

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Chen, R., Gao, X., Zhang, Z. et al. What predicts mental health profiles in first-generation college freshmen?: the role of proactive personality and university environment. BMC Psychol 13, 166 (2025). https://doi.org/10.1186/s40359-025-02498-2

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ISSN: 2050-7283

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