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. 2023 Oct 6;11:316. doi: 10.1186/s40359-023-01349-2

Postgraduates’ time management disposition and mental health: mediating role of life satisfaction and moderating role of core self-evaluations

Shen Liu 1,✉, Minghua Song 2,✉, Han Teng 1,✉
PMCID: PMC10559621  PMID: 37803401

Abstract

Background

The current study aimed to investigate the relationship between postgraduates’ time management disposition and mental health. As such, it constructed a moderated mediation model to examine the mediating role of life satisfaction on the relationship between graduate students’ time management disposition and mental health and examine whether this role was moderated by core self-evaluations.

Methods

455 postgraduates were surveyed by the Adolescence Time Management Disposition Inventory, the Adolescent Students’ Life Satisfaction Scale, the revised version of the Chinese Core Self-Evaluation Scale, and the revised version of the Chinese General Health Questionnaire.

Results

Time management disposition, life satisfaction, core self-evaluation, and mental health were significantly correlated. Time management disposition indirectly affected mental health through the mediating effect of life satisfaction. Core self-evaluation moderated the second half of the mediating effect of time management disposition on mental health via life satisfaction.

Conclusion

The findings reveal the mechanism between time management disposition and mental health, which will help school educators to guide postgraduates in developing good time management disposition and improving life satisfaction and core self-evaluation, and thus improve their mental health.

Keywords: Time management disposition, Life satisfaction, Core self-evaluations, Mental health, Postgraduates

Introduction

With the rapid development of society, transformation of educational strategies, and continuous expansion of postgraduate enrollment, postgraduate groups are faced with multiple pressures from their studies, families, and society and are prone to mental health problems such as anxiety and depression [1]. The mental health of postgraduates, as a higher-level group in the education system, is not only related to their own academic progress and healthy growth, but it also has an important impact on the development of an entire country’s scientific research level. Therefore, it is necessary to mind and improve the mental health of postgraduate students and improve their quality of life [1]. However, most studies on the influencing factors of graduate students’ mental health have constructed an inhibitory model of “negative traits (e.g., depression, anxiety, aggression) → positive factors (e.g., achievement motivation, self-efficacy, empathy)”, and explored the influencing factors, such as the failure of social media self-control [2, 3]. However, the development model of “positive traits (e.g., confidence, self-esteem, optimism) → positive factors (e.g., achievement motivation, self-efficacy, empathy)” has rarely been constructed to improve postgraduates’ mental health level. Therefore, the current study attempts to clarify the internal mechanism of the positive factors affecting postgraduates’ mental health and thus provide a reference for formulating relevant measures to improve postgraduates’ adaptability and maintain their mental health.

The academic community highly ranks time management disposition among the many factors that affect the mental health of graduate students [4, 5]. Time management disposition refers to individuals’ psychological and behavioral characteristics regarding how they use time based on their understanding of the value and meaning of time [2, 6]. It is not only the cognitive characteristics of an individual’s attitude, planning, and utilization of time but also an individual’s values and behavioral tendencies towards time. Further, it is a personality characteristic with a multidimensional and multilevel psychological structure [7]. According to the process model of time management, time planning and monitoring can improve the judgment ability of self-time management and thus increase positive experiences [8]. For example, individuals who managing time well have a positive sense of self-reliance, self-concept, and self-confidence; are more likely to realize self-worth; and tend to have higher levels of mental health [9]. However, individuals who neglect time management have a relatively low level of self-confidence and are prone to a strong sense of inferiority, increased anxiety, and low self-evaluation [8]. It is easy to identify a close relationship between time management disposition and mental health.

Life satisfaction refers to individuals’ overall cognitive assessment of their life status for some or most of the time, according to the standards they construct [10]. As a cognitive component, life satisfaction is a key factor and an important indicator for measuring mental health [11]; it is also an essential feature and the core of mental health [12]. In their longitudinal study, Fergusson et al. found a strong correlation between life satisfaction and mental health [13]. Previous studies have found that improving individuals’ life satisfaction can help promote their academic development, while preventing them from developing psychological and behavioral problems [14, 15]. Individuals with lower life satisfaction may adopt negative coping styles and experience more negative emotions (such as depression), which would seriously affect their mental health [16, 17]. In addition, time management disposition positively predicts life satisfaction [18, 19]. Specifically, individuals who manage and use their time well are more likely to remain calm and be at ease in life and in their studies, be praised by their teachers and classmates, and experience increased positive emotions such as happiness and satisfaction, thereby improving their self-esteem, self-confidence levels, and life satisfaction [9]. In addition, individuals with a good time management disposition will use their time more rationally, complete study and work tasks efficiently, and free up more time to develop hobbies and participate in recreational activities. This not only helps to improve their life satisfaction but also helps to relieve academic pressure, thereby reducing the risk of psychological problems [20]. Therefore, the current study proposes hypothesis H1: Life satisfaction mediates the relationship between time management disposition and mental health.

Core self-evaluation is the most basic evaluation and estimation of individuals’ self-capacity and value, and it is a deep-level personality resource structure [21]. According to the benefit mechanism of self-evaluation, individuals with high self-evaluation can perceive more positive cognitive emotions, thereby maintaining their positive emotional experiences [22]. The study found that core self-evaluation not only has an important positive significance on individuals’ mental health, well-being, and life satisfaction, but it can also moderate the negative effects of adverse environmental stimuli [23, 24]. At the same time, according to the protective-protective model, different protective factors may interact when predicting developmental outcomes; that is, the predictive effect of a protective factor (such as time management tendency) on the outcome variable (mental health) may vary depending on the level of another protective factor, such as core self-evaluation [25]. It is speculated that time management disposition and core self-evaluation may jointly affect mental health. Compared with individuals with low core self-evaluation, individuals with high core self-evaluation levels have a stronger sense of control in their daily life and studies, believe in their own abilities, and recognize their own values; thus, they effectively inhibiting the negative impact of anxiety and depression [25]. In addition, individuals with high core self-evaluation are better at time management and reduce the stress caused by the lack of time [26], thus reducing the possibility of psychological problems. As such, the current study proposes hypothesis H2a: Core self-evaluation moderates the relationship between time management disposition and mental health.

As a positive psychological quality, core self-evaluation not only positively affects life satisfaction [27], but also the prediction of life satisfaction on mental health [28]. Research shows that individuals with high core self-evaluations tend to set more aggressive goals; access more resources to deal with challenges caused by life and work conflicts; demonstrate strong time management skills [29]; and are good at choice and self-harmony interests, values, and growth needs, thereby increasing job and life satisfaction [27]. At the same time, according to the promotion hypothesis of the protection factor-protection factor model [30] and the time management process model [31], core self-evaluation will amplify or enhance the positive effect of time management disposition on life satisfaction. In other words, when core self-evaluation is high, individuals with high time management disposition are more efficient and more likely to meet their own needs, thereby improving their life satisfaction level. When core self-evaluation is low, individuals with high time management disposition still have higher life satisfaction compared to those with low time management disposition; however, important psychological resources are reduced and the predictive effect of time management tendency on life satisfaction may be relatively weak. Based on this, the current study proposes hypothesis H2b: Core self-evaluation moderates the relationship between time management disposition and life satisfaction.

In addition, an increase in individual life satisfaction, if sustained, will promote more positive outcomes [32], thereby reducing the risk of psychological problems. According to conservation of resources theory, core self-evaluation may enhance the positive effect of life satisfaction on mental health [33]. Specifically, individuals with high core self-evaluation are better at coping with negative emotions [34] and less likely to have psychological problems [35]. In contrast, individuals with low core self-evaluations are more prone to psychological problems, such as anxiety and depression [36]. On this basis, the current study hypothesizes that H2c: Core self-evaluation moderates the relationship between life satisfaction and mental health.

In conclusion, the current study constructed the theoretical model shown in Fig. 1 to explore the role of life satisfaction and core self-evaluation in the effect of time management disposition on mental health. We proposed these hypotheses including life satisfaction mediates the relationship between time management disposition and mental health (H1), core self-evaluation moderates the relationship between time management disposition and mental health (H2a), core self-evaluation moderates the relationship between time management disposition and life satisfaction (H2b), and core self-evaluation moderates the relationship between life satisfaction and mental health (H2c).

Fig. 1.

Fig. 1

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Theoretical model

Methods

Study design and participants

An a priori power analysis revealed that to test a simple mediation model with an anticipated small effect size for the view between time-management disposition to life satisfaction and between life satisfaction to mental health indicated a minimum of approximately 450 participants would be needed to test for mediation using the parametric bootstrap procedure for calculating the standard error of the indirect effect [37]. In order to adequately power a test of moderated mediation, we anticipated needing a minimum sample size of 400 participants (using bootstrapped procedure to estimate SE) for potential moderated mediation given a small effect size [38]. We selected students from three universities in Anhui and Hubei, China. We chose these three universities because they presented rural, industrial, and economic territories. 480 postgraduates were recruited via questionnaires and scales. Among them, 25 postgraduates were excluded owing to missing or consecutive answers the same option. Finally, 455 valid data points were obtained with an effective recovery rate of 94.79%. Among the 455 participants, 329 were male and 126 were female between 23 and 30 years old, with an average age of 23.31 years (SD = 1.72). In addition, there were 397 postgraduates in the first grade, 25 postgraduates in the second grade, and 33 postgraduates in the third grade and above. All subjects participated in the study voluntarily. After completing the study, the subjects received certain rewards (20 RMB) or equivalent gifts (a pen or a notebook). The Ethics Committee of Anhui Agricultural University approved the current study, in accordance with the ethical principles of the Declaration of Helsinki. All subjects gave written informed consent in accordance with the ethical principles of the Declaration of Helsinki.

Measures

The adolescence time management disposition inventory

Time management disposition was measured using the Adolescence Time Management Disposition Inventory [6]. The inventory includes three dimensions with 44 items: time value (e.g., “no matter what I do, the first thing I have to consider is time”), time monitoring concept (e.g., “I usually organize my daily activities into a schedule”), and time efficacy (e.g., “I think my time allocation between study and extracurricular activities is reasonable”).The higher the average score, the higher the participant’s time management disposition, with 1 meaning “totally disagree” and 5 meaning “totally agree.” The subscales scores of the time value, time monitoring concept and time efficacy were respectively 35.20, 79.33, and 34.71. In the current study, Cronbach’s α coefficient of the inventory, time value, time monitoring concept and time efficacy were respectively 0.94, 0.81, 0.90, 0.78. In the current study, the second-order CFA model generated a very good fit with χ2/df = 2.50, RMSEA = 0.058, CFI = 0.95, NFI = 0.94, GFI = 0.90, and both the absolute and value-added adaptation indexes were within the acceptable range.

The adolescent students’ life satisfaction scale

Life satisfaction was measured using the Adolescent Students’ Life Satisfaction Scale [39]. The scale includes six dimensions with 36 items: friendship (e.g., “my friends respect me”), family (e.g., “I like to be with my parents”), study (e.g., “I have achieved desirable academic achievement”), freedom (e.g., “basically no one is forcing me to do things I don’t like to do”), school (e.g., “I feel uncomfortable at school”), and environment (e.g., “there are many unpleasant things around the environment I live in”). The higher the average score, the higher the participant’s life satisfaction, with 1 meaning “totally disagree” and 7 meaning “totally agree.” The subscales scores of the friendship, family, study, freedom, school, and environment were respectively 38.13, 39.00, 28.98, 27.49, 31.86, and 27.01. In the current study, Cronbach’s α coefficient of the scale, friendship, family, study, freedom, school, and environment were respectively 0.92, 0.79, 0.90, 0.87, 0.65, 0.85, 0.62. In the current study, the second-order CFA model generated a very good fit with χ2/df = 0.35, RMSEA = 0.020, CFI = 0.95, NFI = 0.94, GFI = 0.95, and both the absolute and value-added adaptation indexes were within the acceptable range.

The revised version of the Chinese core self-evaluation scale

Core self-evaluations were measured using the revised version of the Chinese Core Self-Evaluation Scale [40]. The scale has only one dimension with 10 items (e.g., “I believe in myself to be successful in life”). The higher the average score, the higher the participant’s core self-evaluations, with 1 meaning “totally disagree” and 5 meaning “totally agree.” In the current study, Cronbach’s α coefficient of the scale was 0.88. In the current study, the second-order CFA model generated a very good fit with χ2/df = 3.98, RMSEA = 0.061, CFI = 0.96, NFI = 0.94, GFI = 0.95, and both the absolute and value-added adaptation indexes were within the acceptable range.

The revised version of the Chinese general health questionnaire

Mental health was assessed using the revised version of the Chinese General Health Questionnaire [41]. The questionnaire includes three dimensions with 20 items: self-affirmation (e.g., “basically everything is happy”), depression (e.g., “I lose confidence in myself”) and anxiety (e.g., “I feel uneasy and nervous all day”). The higher the average score, the higher the participant’s mental state, with 1 meaning “yes” and 0 meaning “no”; depression and anxiety were scored in reverse. In the current study, Cronbach’s α coefficient of the questionnaire was 0.90. In the current study, the second-order CFA model generated a very good fit with χ2/df = 3.87, RMSEA = 0.004, CFI = 0.93, NFI = 0.95, GFI = 0.95, and both the absolute and value-added adaptation indexes were within the acceptable range.

Data collection

After obtaining the informed consent of the students themselves, this study was conducted a collective survey on a class basis. The participants filled out the questionnaires in a quiet classroom, with trained psychology students as the subjects. Before conducting the survey, the subjects explained the requirements, the instructions, and provided timely guidance when the participant encountered problems. The participants anonymously filled out the questionnaires, collected it on the spot for numbering (approximately 30 min). After the end, the subjects explained the research purpose to the participants and asked if they have guessed the research purpose.

Data analysis

Owing to common method biases, during the test process, participants were informed that the research questionnaires were limited to academic research, their personal information would be confidential, and their right to withdraw or suspend the research would be respected. Meanwhile, we conducted a common method bias test based on Harman’s single factor test, in which less than 40% indicated no significant common method bias [42]. SPSS 22.0 was used to provide demographic variables and descriptive statistics of the four studied variables and correlation matrices and thus further control the variables and perform model tests. Model 59 of the PROCESS macro program (download address: http://www.Afhayes.com/) written by Hayes was used to perform the moderated mediating model test [43].

Results

Common method biases test

All data were collected from the participants’ self-reports; therefore, the results were susceptible to common method bias [42]. Following Zhou and Long, Harman’s single-factor test was adopted as the common method bias test [44]. The results showed that 24 components had eigenvalues greater than 1.0, and the largest single component accounted for 18.13% of the variance, far less than 40%. This indicates that the current study’s results had no obvious common method bias.

Descriptive analysis

Table 1 shows the mean, standard deviation, and correlation matrix of the variables used in the current study. The results showed that time management disposition, life satisfaction, and self-evaluation were significantly positively correlated with mental health; time management disposition, life satisfaction, and self-evaluation were significantly positively correlated; and time management disposition and life satisfaction were significantly positively correlated. This suggests that the data obtained in the current study can be used for further analysis.

Table 1.

Means, standard deviations, and correlation matrices of variables (n = 455)

M SD 1 2 3 4 5 6 7
1. Gender — — —
2. Age 23.31 1.72 0.07 —
3. Grade — — -0.06 0.44** —
4. Time management disposition 3.39 0.55 0.04 -0.01 0.02 —
5. Life satisfaction 5.35 0.76 0.02 -0.08 -0.10** 0.29** —
6. Core self-evaluations 3.66 0.65 0.01 0.04 -0.02 0.28** 0.58** —
7. Mental health 0.70 0.15 0.01 -0.03 -0.07 0.22** 0.54** 0.59** —
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Note: Gender is a dummy variable, male = 0, female = 1; N = 398; *p-value < 0.05, **p-value < 0.01, and ***p-value < 0.001, the same as below

Mediated modeling testing

Using the hierarchical regression analysis method proposed by Wen et al. [45], all variables were standardized, and a regression analysis of mental health was conducted on time management disposition and on core self-evaluation. With time management disposition in the first tier and life satisfaction in the second tier (see Table 2), life satisfaction had a significant predictive effect on mental health after it was added to the model as a mediating variable (β = 0.52, p < 0.001), but time management disposition had no significant predictive effect on mental health (β = 0.07, p = 0.084). This indicates that life satisfaction plays a complete mediating role between time management disposition and mental health. The total effect of time management disposition on mental health was 0.22, the direct effect was 0.07, the mediation effect was 0.15, the confidence interval was [0.09, 0.22], and the pooled proportion of the total effect was 0.682. Therefore, 68.2% of the effect of time management disposition on mental health occurred through life satisfaction, supporting H1.

Table 2.

Regression analysis of mental health on time management disposition and core self-evaluation

Predictive variables Mental health
R R 2 F β

Level 1

Time management disposition

 0.22 0.05 23.16*** 0.22***

Level 2

Time management disposition

 0.54 0.29 94.28*** 0.07
Life satisfaction 0.52***
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Thereafter, model 59 (a moderated mediation model) was used in the SPSS 23.0 macro program PROCESS to analyze whether core self-evaluations moderate the relationship between time management disposition, life satisfaction, and mental health. If the 95% confidence interval does not contain 0, the mediation effect holds [38]. As shown in Table 3, time management disposition significantly predicted life satisfaction (β = 0.14, p < 0.001), whereas the interaction between time management disposition and core self-evaluations did not significantly predict life satisfaction (β=-0.01, p = 0.671). Therefore, the first half of the mediating effect of time management disposition on mental health was not significantly moderated by core self-evaluation. Life satisfaction significantly predicted mental health (β = 0.28, p < 0.001), and the interaction between life satisfaction and core self-evaluations significantly predicted mental health (β=-0.11, p < 0.001). Therefore, the second half of the mediating effect of time management disposition on mental health was moderated by core self-evaluation. Thus, Hypothesis H2c was validated.

Table 3.

Mediated modeling testing of time management disposition on mental health

Regression equations Overall fit index Significance of Regression coefficients
Outcome variables Predictive variables R R 2 R 2 β 95% CI t
Time management disposition 0.14 [0.06, 0.22] 3.46***
Life satisfaction Core self-evaluations 0.59 0.35 80.30*** 0.54 [0.46, 0.62] 13.54***
Time management disposition×Core self-evaluations -0.01 [-0.08, 0.05] -0.42
Time management disposition 0.03 [-0.04, 0.11] -0.85
Mental health Life satisfaction 0.65 0.42 81.87 0.28 [0.19, 0.37] -6.29***
Core self-evaluations 0.41 [0.32, 0.50] -9.21***
Life satisfaction×Core self-evaluations -0.11 [-0.16, -0.05] 3.51***
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Further, Model 14 in PROCESS was used to test whether the size of the mediating effect varied with the change in the moderator variable. The results showed that the mediating effect of time management disposition on mental health was significant at two levels: between the core self-evaluation below one standard deviation and the mean one below standard deviation (see Table 4).

Table 4.

The mediating effect of different core self-evaluations on time management disposition affecting mental health through core self-evaluations

Core self-evaluations Effect size Bootstrap SE 95% CI
Below M–1 SD 0.11 0.03 [0.06, 0.17]
Between M + 1 SD 0.08 0.02 [0.05, 0.13]
Above M + 1 SD 0.05 0.02 [0.02, 0.09]
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Using one standard deviation of the mean of high and low core self-evaluations as the standard, the high core self-evaluation group (M + 1SD) and the low core self-evaluation groups (M-1SD) were distinguished, and a simple slope analysis was performed (see Figs. 2 and 3). Figure 2 shows that, for individuals with lower core self-evaluations, time management disposition positively and significantly predicted mental health (Bsimple=0.28, t = 4.97, 95% CI=[0.17, 0.39], p < 0.001). For individuals with higher core self-evaluations, time management disposition did not significantly predict mental health (Bsimple=-0.08, t=-1.72, 95% CI=[-0.17, 0.01], p = 0.087). Figure 3 shows that for individuals with lower core self-evaluations, life satisfaction positively and significantly predicted mental health (Bsimple=0.39, t = 7.63, 95% CI=[0.29, 0.49], p < 0.001). For individuals with higher core self-evaluations, life satisfaction was less positively predictive of mental health (Bsimple=-0.08, t=-1.72, 95% CI=[-0.17, 0.01], p = 0.087).

Fig. 2.

Fig. 2

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The moderating effect of core self-evaluations on the relationship between time management disposition and mental health

Fig. 3.

Fig. 3

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The moderating effect of core self-evaluations on the relationship between life satisfaction and mental health

Discussion

The findings of current study help to clarify how and under what conditions there is a significant relationship between postgraduate time management tendencies and mental health. Further, they have certain theoretical significance for deepening and expanding the research on the relationship between postgraduate time management disposition and mental health, and provide a practical reference for the prevention and intervention of mental health problems in postgraduate groups.

The current study found a significant positive correlation between time management disposition and mental health; that is, the stronger the time management disposition, the less likely the occurrence of psychological problems, and the higher the mental health level. This is consistent with existing research findings [46]. Individuals with higher time management disposition tend to have stronger time management ability, and this ability will positively and subtly affect the individuals’ mental health. In addition to completing regular academic tasks, graduate students may also undertake various complex and challenging scientific research tasks, and time is undoubtedly a valuable resource. Having strong time management ability will help the graduate students to improve their work and study efficiency, and thus develop a stronger sense of control over their lives and have fewer psychological problems even under high pressure from studies and research. This finding supports the developmental model of “positive traits → positive factors” developed in the current study. From the perspective of positive psychology, high core self-evaluation, as a positive inner cognition, is an important resource for individual physical and mental health and development and should be valued [47].

In addition, life satisfaction played a mediating role between time management disposition and mental health, and individuals with stronger time management tendencies had higher life satisfaction and fewer psychological problems. These findings are also consistent with a previous study [48]. Individuals with strong time management disposition are good at scientific management and rational control of time, which helps them to experience more positive emotions in life, thereby improving life satisfaction. Life satisfaction, as a subjective experience, is also closely related to mental health [49, 50]. When graduate students have a high life satisfaction level, their physical and mental health is maintained at a good level. This finding shows that in the development model of “positive traits→positive factors”, an individual’s positive traits may also affect another positive factor through one positive factor to achieve good and sustainable physical and mental development. Therefore, school educators can attempt to guide and train postgraduates on time management ability and thus improve their ability to manage their studies and life, thereby improving their life satisfaction as well as physical and mental health.

The current study verified the moderating role of core self-evaluation as an important protective factor for mental health. First, core self-evaluation moderates the direct path of “time management disposition → mental health”. Time management disposition significantly and positively predicted the mental health of individuals with low core self-evaluation but the predictive effect was not significant for those with high self-evaluation. This may be because, for individuals with low core self-evaluation, improving time management ability will reduce the sense of stress due to lack of time to a certain extent [26], thereby reducing the possibility of psychological problems. Second, core self-evaluation moderated the second half of the mediating effect of “time management tendency→life satisfaction→mental health.” For individuals with high core self-evaluation levels, the negative effect of life satisfaction on mental health scores was weakened. In general, the moderating effect of core self-evaluation is shown as a relieving effect, and high core self-evaluation can effectively maintain a good level of individual mental health and reduce the possibility of psychological problems. This is consistent with existing research findings that core self-evaluation can moderate the impact of related factors on mental health [51]. To a certain extent, this is also consistent with the assumptions of the “protection factor-protection factor” model [25]. That is, core self-evaluation and life satisfaction are protective factors that can jointly maintain and promote mental health. Finally, the current study did not find a moderating effect of core self-evaluation on the first half of the mediating effect of “time management tendency → life satisfaction → mental health.” This indicates that time management tendency significantly predicts life satisfaction for individuals with both high and low core self-evaluations [20], making the difference between the two insignificant.

This may be because graduate students are in a special stage of transition from early to mid-adulthood, have a longer moratorium than undergraduates do, and have a higher education level. Their beliefs and expectations regarding how they plan and use their time largely determine their happiness [46]. This in turn affects their life satisfaction, which is less affected by the level of core self-evaluation in the process. Therefore, postgraduate tutors and school educators can take up relevant measures, such as specialized mental training and positive affirmation of postgraduates’ personal achievements, to improve the core self-evaluation level of postgraduate groups and thus protect and improve their mental health.

The current study’s theoretical contribution includes improving postgraduates’ mental health by constructing a developmental model of “positive traits→positive factors.” From a development perspective, it explores the practical method, takes service guidance orientation as the core, discusses the relationship between postgraduate time management tendency and mental health, reveals the mediating role of life satisfaction and the moderating role of core self-evaluation, and deepens the research on postgraduate time management. Understanding the impact mechanism of mental health has a certain theoretical value. Practically, the current study focused on finding that preventing and intervening in postgraduate mental health is crucial. The mediating effect of life satisfaction suggests that postgraduate tutors and school educators can improve postgraduates’ ability to manage their studies and life through training, thereby improving their life satisfaction and mental health. The moderating role of core self-evaluation indicates that positive core self-evaluation, as an important protective factor for graduate students’ mental health, should be highly valued.

However, the current study has some limitations that need to be further improved and explored. First, the data in the current study are cross-sectional; therefore, it is difficult to determine the causal relationship between the variables. Subsequent studies could consider combining longitudinal tracking methods to test the findings of the current study. Second, the current study has not examined postgraduate academic stress as a factor that may affect the mental health of postgraduates to a certain extent. Subsequent research can consider controlling for this factor and other related factors to further test the findings of the current study.

Conclusions

The current study concludes that time management disposition is an important predictor of mental health, and life satisfaction plays a mediating role between time management disposition and mental health. Core self-evaluations played a moderating role in the second half of the direct effect of time management disposition on mental health and the mediating effect of time management disposition on mental health through life satisfaction. School educators can improve their mental health by guiding graduate students in developing good time management disposition and enhancing their life satisfaction and core self-evaluation levels.

Acknowledgements

The authors would like to thank all participants for their collaboration.

Authors’ contributions

H.T. and M.S. designed the study. S.L. collected the data, analyzed the data, and wrote the original manuscript. S.L., M.S. and H.T. revised the manuscript. All authors have read and approved the final manuscript.

Funding

The current study was conducted with the financial support of the Starting Fund for Scientific Research of High-Level Talents at Anhui Agricultural University (rc432206), the Outstanding Youth Program of Philosophy and Social Sciences in Anhui Province (2022AH030089), the Project in Humanities and Social Science Research of Ministry of Education of the People’s Republic of China (20YJA880048) and the New Liberal Arts Research and Reform Practice Project of the People’s Republic of China (2021040009).

Data Availability

Data and materials are available on request from the corresponding author.

Declarations

Ethics approval and consent to participate

The ethics committee of Anhui Agricultural University approved the study protocol. Participants signed an informed consent form before beginning the research. The study’s objectives, confidentiality, and anonymity were described, and volunteers were given full authority to complete the questionnaire. All methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not Applicable.

Competing interests

The authors report no conflict of interest.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Shen Liu, Email: liushen@ahau.edu.cn.

Minghua Song, Email: 02615@zjhu.edu.cn.

Han Teng, Email: hanteng99@163.com.

References

  • 1.Zhou L, Geng JY, Wang XC, Lei L. (2021). The role of basic needs in the relationship between supervisor-induced ostracism and mental health among postgraduate students. Psychological Development and Education. 2021;37(2):222-9.
  • 2.Chen PS, Li J, Kim SY. (2021). Structural relationship among mobile phone dependence, self-efficacy, time management disposition, and academic procrastination in college students. Iranian Journal of Public Health. 2021;50(11):2263–73. [DOI] [PMC free article] [PubMed]
  • 3.Wang YB, Tian T, Wang JJ. A study on the impact of psychological empowerment on mental health of postgraduate students—mediating role of sense of meaning in life. High Educ Forum. 2022;29(1):117–20. [Google Scholar]
  • 4.Jiang MY, Gao Z, Kong LL, Gao M, Zhang LP, Yu ZY. Relationship between postgraduates’ mobile phone dependence and perceived stress: the mediating effect of time management. Campus Life & Mental Health. 2021;19(6):472–6. [Google Scholar]
  • 5.Zhu XJ. Research on time management tendency and test anxiety in graduate students. The Theory and Practice of Innovation and Entrepreneurship. 2020;3(9):149–50. [Google Scholar]
  • 6.Huang XT, Zhang ZJ. The compiling of adolescence time management disposition inventory. Acta Physiol Sinica. 2001;33(4):338–43. [Google Scholar]
  • 7.Fan CY, Sun XJ, Liu HS. Time management disposition and subjective wellbeing in undergraduate students. Psychol Dev Educ. 2012;28(1):99–104. [Google Scholar]
  • 8.Guo JC, Ye YT. How core self-evaluations influences life satisfaction in adolescents: the mediating effects of hope. Stud Psychol Behav. 2017;15(5):663–8. [Google Scholar]
  • 9.Zhou YH, Lv CF, Yang YC. Time management disposition and academic procrasnition: sense of self-efficiency as a moderator. Chin J Clin Psychol. 2014;22(3):533–6. [Google Scholar]
  • 10.Shin DC, Johnson DM. Avowed happiness as an overall assessment of the quality of the life. Soc Indic Res. 1978;5(1):475–92. doi: 10.1007/BF00352944. [DOI] [Google Scholar]
  • 11.Civitci A. Perceived stress and life satisfaction in college students: belonging and extracurricular participation as moderations. Procedia-Social and Behavioral Sciences. 2015;205:271–81. doi: 10.1016/j.sbspro.2015.09.077. [DOI] [Google Scholar]
  • 12.Yu GL. A new interpretation of mental health: the well-being perspective. J Beijing Normal Univ (Social Sciences) 2022;67(1):72–81. [Google Scholar]
  • 13.Fergusson DM, McLeod GFH, Horwood LJ, Swain NR, Chapple S, Poulton R. Life satisfaction and mental health problems (18 to 35 years) Psychol Med. 2015;45:2427–36. doi: 10.1017/S0033291715000422. [DOI] [PubMed] [Google Scholar]
  • 14.Blackie LE, Jayawickreme E, Forgeard MJC, Jayawickreme N. The protective function of personal growth initiative among a genocide-affected population in Rwanda. Psychol Trauma: Theory Res Pract Policy. 2015;7(4):333–9. doi: 10.1037/tra0000010. [DOI] [PubMed] [Google Scholar]
  • 15.Guzmán J, Green JG, Oblath R, Holt MK. Life satisfaction mediates the association between mental health risk and perceptions of school functioning among children and adolescents. Contemp School Psychol. 2020;24:389–99. doi: 10.1007/s40688-019-00257-w. [DOI] [Google Scholar]
  • 16.Sæther SMM, Knapstad M, Askeland KG, Skogen JC. Alcohol consumption, life satisfaction and mental among norwegian college and university students. Addict Behav Rep. 2019;10:100216. doi: 10.1016/j.abrep.2019.100216. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Zhang JJ, Liu T, Chen YL. Effect of life satisfaction on freshmen’s mental health: a chain mediating role of basic psychological needs and positive emotions. J Jinzhou Med Univ (Social Sci Edition) 2021;19(3):70–3. [Google Scholar]
  • 18.Chen XP, Bai NN. Relationship between time management disposition, confidence and life satisfaction in normal university students. China J Health Psychol. 2016;24(2):216–9. [Google Scholar]
  • 19.Mi DD, Zheng LJ. Research on the relationship between graduate students’ time management disposition, personal striving and life satisfaction. China J Health Psychol. 2012;20(2):261–3. [Google Scholar]
  • 20.Coccia C, Darling CA. Having the time of their life: College student stress, dating and satisfaction with life. Stress and Health. 2014;32(1):28–35. doi: 10.1002/smi.2575. [DOI] [PubMed] [Google Scholar]
  • 21.Judge TA, Locke EA, Durham CC. The dispositional causes of job satisfaction: a core evaluations approach. Res Organizational Behav. 1997;19:151–88. [Google Scholar]
  • 22.Li JB, Nie YG. Reflection and prospect on core self-evaluations. Adv Psychol Sci. 2010;18(12):1848–57. [Google Scholar]
  • 23.Extremera N, Rey L. Core self-evaluation are associated with judgements of satisfaction with life via positive but not negative effect. Pers Indiv Differ. 2018;103:112–6. doi: 10.1016/j.paid.2018.03.054. [DOI] [Google Scholar]
  • 24.Xiang YH, Zhao JX, Li QY, Zhang WR, Dong X, Zhao JJ. Effect of core-evaluation on mental health symptoms among chinese college students: the mediating roles of benign and malicious envy. Psychiatric Annals. 2019;49(6):277–84. doi: 10.3928/00485713-20190508-01. [DOI] [Google Scholar]
  • 25.Hou ZH, Song HY, Xue X, Tan L. Does R&D abusive supervision always inhibit employee’s job crafting? A moderated double path model. Sci Technol Manage Res. 2022;42(6):124–34. [Google Scholar]
  • 26.Antwi CO, Fan C, Aboagye MO, Brobbey P, Jababu Y, Affum-Osei E, Avornyo P. Job demand stressors and employee’s creativity: a within-person approach to dealing with hindrance and challenge stressors at the airport environment. Serv Ind J. 2018;39(3–4):250–78. [Google Scholar]
  • 27.Judge TA, Bono JE, Erez A, Locke EA. Core self-evaluations and job and life satisfaction: the role of self-concordance and goal attainment. J Appl Psychol. 2005;90:257–68. doi: 10.1037/0021-9010.90.2.257. [DOI] [PubMed] [Google Scholar]
  • 28.Tsaousis I, Nikolaou I, Serdaris N, Judge TA. Do the core self-evaluations moderate the relationship between subjective well-being and physical and psychological health? Pers Indiv Differ. 2007;42(8):1441–52. doi: 10.1016/j.paid.2006.10.025. [DOI] [Google Scholar]
  • 29.Tew MJ, Noe RA, Scheurer AJ, Michel JW. The relationships of work-family conflict and core self-evaluations with informal learning in a managerial context. J Occup Organizational Psychol. 2015;89(1):92–110. [Google Scholar]
  • 30.Bao ZZ, Zhang W, Li DP, Li DL, Wang YH. School climate and academic achievement among adolescents: a moderated mediation model. Psychol Dev Educ. 2013;29(1):61–70. [Google Scholar]
  • 31.Macan TH. Time management: test of a process model. J Appl Psychol. 1994;79(3):381–91. doi: 10.1037/0021-9010.79.3.381. [DOI] [Google Scholar]
  • 32.Ryff CD, Singer B. The contours of positive human health. Psychol Inq. 1998;9(1):1–28. doi: 10.1207/s15327965pli0901_1. [DOI] [Google Scholar]
  • 33.Alarcon GM, Edwards JM, Menke LE. Student burnout and engagement: a test of the conservation of resources theory. J Psychol. 2011;145(3):211–27. doi: 10.1080/00223980.2011.555432. [DOI] [PubMed] [Google Scholar]
  • 34.Zhao JJ, Song FX, Chen Q, Li M, Wang YH, Kong F. Linking shyness to loneliness in chinese adolescents: the mediating role of core self-evaluation and social support. Pers Indiv Differ. 2018;125:140–4. doi: 10.1016/j.paid.2018.01.007. [DOI] [Google Scholar]
  • 35.Tisu L, Lupșa D, Vîrgă D, Rusu A. Personality characteristics, job performance and mental health: the mediating role of work engagement. Pers Indiv Differ. 2020;153:109644. doi: 10.1016/j.paid.2019.109644. [DOI] [Google Scholar]
  • 36.James D. Self- and group-focused internalized racism, anxiety, and depression symptoms among african american adults: a core self-evaluation mediated pathway. Group Processes & Intergroup Relations. 2020;24(8):1335–54. doi: 10.1177/1368430220942849. [DOI] [Google Scholar]
  • 37.Fritz MS, MacKinnon DP. Required sample size to detect the mediated effect. Psychol Sci. 2007;18(3):233–9. doi: 10.1111/j.1467-9280.2007.01882.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Preacher KJ, Rucker DD, Hayes AF. Addressing moderated mediation hypotheses: theory, methods, and prescriptions. Multivar Behav Res. 2007;42(1):185–227. doi: 10.1080/00273170701341316. [DOI] [PubMed] [Google Scholar]
  • 39.Zhang XG, He LG, Zheng X. Adolescent students’ life satisfaction: its construct and scale development. J Psychol Sci. 2004;27(5):1257–60. [Google Scholar]
  • 40.Du JZ, Zhang X, Zhao Y. Reliability, validation and construct confirmatory of core self-evaluations scale. Psychol Res. 2012;5(3):54–60. [Google Scholar]
  • 41.Li H, Mei JR. Assessing psychological well-being of college student: psychometric properties of GHQ-20. Psychol Dev Educ. 2002;18(1):75–9. [Google Scholar]
  • 42.Podsakoff PM, Mackenzie SB, Lee JY, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879–903. doi: 10.1037/0021-9010.88.5.879. [DOI] [PubMed] [Google Scholar]
  • 43.Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. Guilford Press; 2013.
  • 44.Zhou H, Long LR. Statistical remedies for common method biases. Adv Psychol Sci. 2004;22(6):942–50. [Google Scholar]
  • 45.Wen ZL, Ye BJ. Different methods for testing moderated mediation models: competitors or backups? Acta Physiol Sinica. 2014;46(5):714–26. [Google Scholar]
  • 46.Chen BZ, Zheng X, Sun XJ. The impact of social media self-control failure on subjective well-being of postgraduates and its mechanism. Psychol Dev Educ. 2021;37(6):882–8. [Google Scholar]
  • 47.Geng JY, Han L, Gao FQ. Shyness and depressive symptoms: a multiple mediation model involving core self-evaluations and sense of security. J Affect Disord. 2021;286:19–26. doi: 10.1016/j.jad.2021.01.035. [DOI] [PubMed] [Google Scholar]
  • 48.Yu XD, Xiong XL, Liang X, Lu C, Deng LY, Gao DG. Ego identity status and time management in college students: mediating effect of emotion and attention of passage of life time. Psychol Dev Educ. 2021;37(3):381–90. [Google Scholar]
  • 49.Hui QP, Wang ZH, He AM. A longitudinal follow-up study of the relationship between mental symptoms and life satisfaction among undergraduates. Chin J Clin Psychol. 2021;29(5):1028–31. [Google Scholar]
  • 50.Lombardo P, Jones W, Wang L, Shen X, Goldner EM. The fundamental association between mental health and life satisfaction: results from successive waves of a canadian national survey. BMC Public Health. 2018;18(1):342. doi: 10.1186/s12889-018-5235-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Zhang R, Ye C. The impact mechanisms of emotional labor on psychological health among special education teachers: an empirical study based on longitudinal moderated mediation model. J Fujian Normal Univ (Philosophy Social Sci Edition) 2018;51(1):146–53. [Google Scholar]

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