From Psychological Capital to Well-being: Job Satisfaction as a Mediator among University Lecturers in Vietnam

From Psychological Capital to Well-being: Job Satisfaction as a Mediator among University Lecturers in Vietnam | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article From Psychological Capital to Well-being: Job Satisfaction as a Mediator among University Lecturers in Vietnam Giau Thi Ngoc Nguyen, Nghia Duc Tri Nguyen, Hue-Anh Vo-Nguyen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7520312/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Grounded in Conservation of Resources (COR) theory, this study examines how future-oriented personal resources from psychological capital (optimism and hope) relate to university lecturers' well-being and whether their job satisfaction functions as a conditional resource linking these personal resources to the outcomes Methods A cross-sectional survey was administered to 224 Vietnamese university lecturers. Participants completed validated measures of psychological capital’s components (optimism, hope, self-efficacy, resilience), job satisfaction, and overall well-being. Path analysis with 5000 resampling bootstraps was used to test direct and mediating relationships. Results Job satisfaction showed a strong positive association with well-being (β = 0.296, p < 0.001). Optimism predicted both job satisfaction (β = 0.193, p = .018) and well-being (β = 0.175, p = 0.011), yielding a significant indirect effect on well-being through job satisfaction (β = 0.057, p = 0.031). Hope had a significant direct effect on well-being (β = 0.233, p = 0.001) but was not predicted to job satisfaction. Self-efficacy and resilience were not significant predictors of either outcome. Conclusions Findings clarify two pathways in accordance with COR among university lecturers, including a context-appraisal pathway in which optimism translates into greater job satisfaction and, subsequently, higher well-being, and a goal-navigation pathway in which hope directly enhances well-being independent of job evaluations. Conservation of Resources theory psychological capital optimism hope job satisfaction well-being university lecturers path analysis Figures Figure 1 Figure 2 Introduction It is well-known that teaching is one of the most stressful and demanding occupations in the world (Pithers, 1995), especially teaching in higher education (Kang & Sidhu, 2015). Due to the substantial influence on teaching quality, the responsibility for student outcomes, and overall institutional success, university lecturers - the most important human resource in higher education, encounter distinct challenges, such as substantial workloads, the imperative to publish, administrative duties, and the necessity to perpetually enhance their knowledge (Adam & Brown, 2022; Kinman & Wray, 2020). Further, competition over university ranking has been intensifying worldwide (Enders, 2014; Hazelkorn, 2011), meaning that their role becomes conflicted and complex. These unpleasant responsibilities lead to significant changes from academic settings to industrial factories, where multitasking and high productivity are the primary concerns(Rae, 2010). In other words, academic staffs are forced to reach higher professional expectations while receiving limited resources, further exhausting their coping mechanisms (Barkhuizen & Rothmann, 2008). However, due to high demands from institutions, managing to balance multiple duties (as an educator and a staff member) at once tilts this balance and places burdens on university lecturers (Urbina-Garcia, 2020). In fact, there are significant health and well-being crises associated with working in higher education (Rahman et al., 2024). Numerous studies have explored negative psychological outcomes experienced by university lecturers. They are susceptible to occupational stress, anxiety, depression, and burnout (Agyapong et al., 2022), which directly results in their job dissatisfaction and low level of well-being (Mudrak et al., 2018). In turn, lecturers with mental health problems reported a low level of teaching quality, work-related motivation, performance, and commitment (Amer et al., 2022; Daumiller et al., 2021; Wang et al., 2020). Together, empirical evidence highlights the vulnerabilities of university lecturers to the difficulties and their consequences in the current higher education landscape. Maintaining job satisfaction and well-being among academic staff is not only a human resource goal but is also directly linked to teaching quality and institutional success and competitiveness (Kwok et al., 2015). Recent literature suggested job satisfaction and well-being as crucial factors in establishing positive experiences in an academic context (Douglas et al., 2024; Rosser, 2004). It is noteworthy that the majority of studies tend to concentrate on examining the influence of workplace-related issues on the mental health of academics (Urbina-Garcia, 2020), while there were limited approaches to enhance and promote the positive and intrinsic aspects of academic staff's well-being (LaMontagne et al., 2014). Thus, the present study sought to investigate the attainment of lecturers' well-being via individual-level coping strategies. Psychological Capital as a predictor of Job Satisfaction and Well-being In response to pressures in higher education systems, Psychological Capital (PsyCap)—a construct encompassing self-efficacy, hope, resilience, and optimism—has emerged as a crucial psychological resource for assisting lecturers in sustaining their well-being and job satisfaction amid these challenges (Liu & Du, 2024; Luthans, Youssef, et al., 2007). According to Adil and Kamal (2019), PsyCap represents a significant personal capital to be taken advantage of in educational environments. Recently, its association with job satisfaction and well-being has been primarily examined from social and psychological outlook (Luthans, Avolio, et al., 2007). In the present study, a comprehensive overview of PsyCap will be applied under the viewpoint of the Conservation of Resources theoretical framework (Hobfoll, 1989) to establish a deep understanding of this concept since its perspective is regarded as one of the best resource-oriented approaches that underscores the significance of personal incentive to preserve, protect, and hoard supportive means. In the original work by Hobfoll (1989), the author argued that these attempts aim to ensure a balanced psychological condition for individuals even when there are depletions in resources due to the demands of their role. By contrast, absences in inner resources will disturb or collapse their equilibrium state when facing taxing requirements, resulting in lower job satisfaction and well-being. In other words, depending on the level of investment in personal resources, it creates gain/loss spirals that determine the ability to overcome difficulties. Individuals with greater inner resources are more likely to feel elevated levels of motivation, satisfaction, and well-being (Xanthopoulou et al., 2007). Furthermore, due to its state-like nature, PsyCap is adaptable and hence flexible to optimization (Kun & Gadanecz, 2022; Sarwar et al., 2021). Therefore, PsyCap can be accumulated via training and practice. Several studies have attempted to provide evidence of the growth of PsyCap as a developmental state through training intervention (Demerouti et al., 2011; Luthans et al., 2006; Luthans et al., 2010). These findings indicated that by cultivating PsyCap, lecturers’ resources are increasingly abundant over time, which means they are better able to cope with work-related obstacles and experience more satisfaction and achieve more well-being (Sarwar et al., 2021). Well-being as a result of Job Satisfaction Well-being is a multidimensional concept that reflects a subjective evaluation of one’s life as a whole (Diener, 1984). It is a harmonious combination of both emotional and cognitive aspects, indicated by the presence of positive affect, the absence of negative affect, and the development of satisfaction with one’s own life (Diener, 1984). According to Diener (1994), well-being demonstrates a stable construct over time. However, it is also known to be susceptible to a wide range of environmental occurrences as well as related psychological factors (Wright, 2004). Wright (2004) identifies job satisfaction as a common component that best characterizes well-being in the workplace. Job satisfaction, as described by Spector (1997), refers to the degree of pleasure that an individual experiences with their employment and the sense of achievement derived from performing it. Since work has consistently been perceived to be an indispensable element of life (Yahyagil, 2015), personal perceptions of well-being and happiness are significantly influenced by job satisfaction due to the work centrality in individuals' lives (Sironi, 2019). Thus, the level of job satisfaction varies across different domains of work, depending on an individual’s evaluations. However, the presence of job satisfaction is still the key factor determining the appearance of life satisfaction. In fact, job satisfaction was also regarded as a precursor to life satisfaction (Erdogan et al., 2012), forming a foundation for the close relationship between job satisfaction and well-being. Empirical evidence supports these claims. A meta-analysis by Bowling et al. (2010) confirmed substantive positive associations between job satisfaction and well-being via affiliated components: life satisfaction, happiness, and positive affect. Longitudinal evidence indicates a reciprocal link between job and life satisfaction. Although the life-to-job path is often slightly stronger, the evidence still suggests that job satisfaction contributes to overall well-being over time (Bialowolski & Weziak-Bialowolska, 2021; Weziak-Bialowolska et al., 2020). These findings are consistent with the part-whole perspective, which states that well-being is a high-order construct (considered as the “whole”) that is composed of multiple life domains (considered as the “part”), among which, job satisfaction is one of the domains (Bowling et al., 2010; Cannas et al., 2019). By contrast, the way an individual evaluates their job satisfaction as a specific “part” domain, in turn, influences the “whole” well-being construct. Therefore, the disparities in well-being are the result of the variance of job satisfaction and vice versa (Benevene et al., 2018). Job satisfaction as a potential mediator The aforementioned evidence suggests that job satisfaction may serve as a key mediator in the link between PsyCap and well-being. Within the Conservation of Resources theory, PsyCap enables individuals to reappraise demands as manageable challenges with efficient effort investment that converts personal resources into achievements, autonomy, and recognition (Hobfoll et al., 2018; Luthans, 2006; Luthans, Avolio, et al., 2007). These work-related benefits received from PsyCap crystallize into job satisfaction as a specific domain outcome. Under the part-whole theory, well-being is a global evaluation formed by accumulating satisfaction via life domains, in which job satisfaction is one of the main contributors (Bowling et al., 2010; Diener, 1984). Taken together, job satisfaction is a bridge between two theoretical frameworks with connections via PsyCap and well-being. The present study Based on literature review, we suggest a potential link between PsyCap and well-being as well as the mediating role of job satisfaction among university lecturers. To our best knowledge, the understanding of this mechanism remains unclear with limited supportive evidence. Research on this subject advances knowledge of the connection between academic staff’s PsyCap and their well-being while clarifying the benefit of job satisfaction as an effective resource in the academic settings. It should be noted that although PsyCap is often modeled as a higher-order construct, its four components—self-efficacy, resilience, optimism, and hope—stem from distinct theoretical traditions and may operate through different mechanisms. Drawing on Conservation of Resources (Hobfoll, 1989; Hobfoll et al., 2018), we argue that these resources not only converge into a general PsyCap factor but also exert unique effects on outcomes. Specifically, since self-efficacy is task-focused, it should more strongly predict job satisfaction, whereas optimism, hope, and resilience—resources tied to positive future expectancies and recovery—should show comparatively stronger direct effects on well-being. Therefore, job satisfaction is expected to partially mediate the relationships between each PsyCap component and well-being (Bowling et al., 2010). Testing the disaggregated model allows for the detection of heterogeneous effects and provides implications for interventions specific to each psychological ability. Additionally, job satisfaction was employed using single-item approach in the present study. On the one hand, single-item measures are less suitable for assessing specific facets (e.g., pay, supervision), however, they are appropriate when the construct of interest is overall job satisfaction (Nagy, 2002). On the other hand, recent studies do not dismiss single-item measures in relation to job satisfaction (Dolbier et al., 2005). Taken together, the present study aims to investigate these associations with the following expectations (see Figure 1). H1: University lecturers’ PsyCap components directly relate to their well-being H2: Their job satisfaction partially mediates the relationship between PsyCap components and well-being [INSERT FIGURE 1 HERE] Methods Participants and procedures A cross-sectional design was established in the present study. The protocol was reviewed and approved by the Ethics Committee of the Graduate Academy of Social Sciences, Vietnam Academy of Social Sciences (Reference No. 3462/QĐ-HVKHXH), and conducted in accordance with APA ethical guidelines for psychology studies. Participants were Vietnamese university lecturers recruited from both private and public academic institutions in Ho Chi Minh City via a convenience sampling using Google Forms platforms. They were fully informed about the present study, including the purposes and confidentiality of the study as well as their autonomy to withdraw at any time. Those who have provided consent to the study terms and conditions can proceed to the final survey. Measurements Psychological capital We employed the Vietnamese version of the 12-item Psychological Capital Questionnaire (Nguyen & Nguyen, 2011 ) to evaluate psychological capital among university lecturers. Four elements—self-efficacy, hope, optimism, and resilience from the initially published version by Luthans, Avolio, et al. ( 2007 )—are still present in this version. Participants were asked to rate their feelings on a 6-point Likert scale. The Vietnamese scale has shown appropriate structure, with CFA loadings of items and composite reliability indicate acceptable goodness of fit. Job satisfaction Job satisfaction was assessed with a single global item: “Overall, how satisfied are you with your job?” (1 = very dissatisfied to 5 = very satisfied). We chose a single-item measure because overall job satisfaction is a global evaluation, and prior evidence indicates that single-item measures show substantial convergence with multi-item instruments and adequate reliability for structural analyses (Nagy, 2002 ; Wanous et al., 1997 ). We are aware that using a single item precludes internal consistency estimates and may reduce precision; it also cannot capture satisfaction facets. We therefore interpret effects at the global level and recommend multi-item facet scales when facet-specific inferences are required. Well-being In the present study, the Vietnamese version of the WHO-5 Well-being Index (Nguyen & Le, 2021 ) was utilized to measure university lecturers’ well-being. Participants indicated how often they felt each statement applied over the previous two weeks on a 6-point scale. Prior research with the Vietnamese version has demonstrated excellent internal consistency, with the alpha coefficient of 0.95 (Nguyen & Le, 2021 ). Data analysis In the present study, data management was performed using SPSS 25.0, while JASP 0.16.4 was employed to test our hypothesis by conducting a path analysis. To illustrate the demographic characteristics, we perform descriptive statistics, including frequencies, percentage, means, standard deviations. Additionally, Cronbach’s alpha was tested to ensure the scale’s reliability, while correlation analysis was conducted to examine the relationship between variables. Furthermore, the normality of the data was evaluated using Kolmogorov–Smirnov and Shapiro–Wilk tests before testing differences in each variable level among groups. Finally, a path analysis with a 5000-sample bootstrapping was conducted to determine the total, direct, and indirect effects of the variables in the final model. Results Descriptive demographic characteristics The study included 224 university lecturers, most of whom were female (56.2%). Lecturers' ages were distributed as follows: 28–34 years old (17.0%, n = 38), 35–39 years old (23.7%, n = 53), 40–44 years old (32.6%, n = 73), 45–49 years old (12.5%, n = 28), and ≥ 50 years old (14.3%, n = 32). For current marital status, a majority (n = 142) reported being partnered (63.4%), with 36.6% not partnered (n = 82). Among the majority, most lecturers were teaching in non-STEM fields (79.0%, n = 177), while the other 21.0% were teaching in STEM (n = 47). Regarding the number of subjects they are teaching, 63.4% (n = 142) reported ≤ 3 subjects, and 36.6% (n = 82) reported ≥ 4 subjects (see Table 1). [INSERT TABLE 1 HERE] Characteristics, reliability, and correlations of variables Table 2 shows the means, standard deviations, reliability, and correlations between self-efficacy (SE), resilience (RE), hope (HO), optimism (OP), job satisfaction (JS), and well-being (WB). The internal consistency was acceptable (α = 0.694) to excellent (α = 0.947) for multi-item scales, except for JS; since it was a single item, the alpha coefficient is not applicable. All variables were positively correlated. Moderate to strong correlation was found between PsyCap facets, including SE and HO ( r = 0.489, p < 0.001), SE and RE ( r = 0.571, p < 0.001), SE and OP ( r = 0.428, p < 0.001), HO and RE ( r = 0.626, p < 0.001), HO and OP ( r = 0.531, p < 0.001), and RE and OP ( r = 0.570, p < 0.001). Besides, PsyCap facets significantly showed a weak correlation with JS in the link with SE ( r = 0.149, p = 0.025), HO ( r = 0.204, p = 0.002), RE ( r = 0.176, p = 0.008), and OP ( r = 0.250, p < 0.001). In addition, WB showed small-to-moderate positive associations with all constructs, including SE ( r = 0.304, p < 0.001), HO ( r = 0.465, p < 0.001), RE ( r = 0.424, p < 0.001), OP ( r = 0.445, p < 0.001), and JS ( r = 0.410, p < 0.001). [INSERT TABLE 2 HERE] Normal distribution of variables Normality of the study variables was examined using Kolmogorov–Smirnov and Shapiro–Wilk tests (see Table 3). All variables showed significant departures from a normal distribution with all p-values below the 0.001 threshold, including self-efficacy ( D = 0.139, W = 0.862), hope ( D = 0.120, W = 0.951), resilience ( D = 0.159, W = 0.911), optimism ( D = 0.178, W = 0.928), job satisfaction ( D = 0.301, W = 0.819), and well-being ( D = 0.126, W = 0.957). Therefore, differences between independent groups were compared using the Kruskal-Wallis and Mann-Whitney U tests. [INSERT TABLE 3 HERE] Differences between independent groups A Kruskal-Wallis test was conducted to determine the difference in SE, HO, RE, OP, JS, and WB between age groups (see Table 4). Results show that there were no significant differences in SE [ χ 2(4) = 8.631, p = 0.071], HO [ χ 2(4) = 6.902, p = 0.141], RE [ χ 2(4) = 5.634, p = 0.228], OP [ χ 2(4) = 1.070, p = 0.899], JS [ χ 2(4) = 8.253, p = 0.083], and WB [ χ 2(4) = 7.75, p = 0.100] among five age groups. To assess the difference in those variables between gender, marital status, majority, and the number of subjects, the Mann-Whitney U test was employed. Table 4 shows that most of the characteristics were not significantly different ( p > 0.05). Changes are only found in the distribution of job satisfaction between two marital status groups ( z = -2.860, p = 0.004) and of optimism between STEM and non-STEM lecturers ( z = -2.375, p = 0.018). [INSERT TABLE 4 HERE] Hypothesis testing In the final path analysis model as shown in Table 5 and Figure 2, analysis revealed that well-being can be directly predicted by optimism (β = 0.175, SE = 0.069, z = 2.545, p = 0.011, 95% CI [0.029; 0.308]), hope (β = 0.233, SE = 0.072, z = 3.214, p = 0.001, 95% CI [0.054; 0.400]), and job satisfaction (β = 0.296, SE = 0.055, z = 5.348, p < 0.001, 95% CI [0.154; 0.429]). However, job satisfaction can only be directly predicted by optimism (β = 0.193, SE = 0.082, z = 2.360, p = 0.018, 95% CI [0.045; 0.350]). Other direct paths were not statistically significant. Regarding the indirect path, the only mediating effect of job satisfaction was found in the relationship between optimism and well-being (β = 0.057, SE = 0.027, z = 2.159, p = 0.031, 95% CI [0.015; 0.120]), while other indirect effects were statistically insignificant (see Table 5 and Figure 2). The final model explained 36.1% of variance in well-being ( R 2 = 0.361), highlighting the significant role of job satisfaction in promoting the influence of optimism on well-being among academic staff. [INSERT TABLE 5 HERE] [INSERT FIGURE 2 HERE] Discussion The present study aims to investigate the direct effects of four components of PsyCap on university lecturers’ well-being while examining the mediating role of job satisfaction in the relationship. Results showed that optimism positively predicts job satisfaction and well-being, while also exhibiting an indirect effect on well-being through satisfaction. By contrast, only direct effect of hope on well-being was confirmed while the mediation path through job satisfaction in this relationship was not found. Regarding self-efficacy and resilience, these variables did not show significant direct effects on well-being as well as indirect effects via job satisfaction. Within the framework of Conservation of Resources (COR), these results clarify not only what occurs but also why and when these psychological resources benefit university lecturers. In academia, university lecturers simultaneously shoulder the tripartite roles of teaching, research, and service; work on long academic outcome cycles (projects, articles, and grants); and face frequent external subjective evaluations (e.g., student ratings) alongside competitive pressures for resources. From the COR perspective, these characteristics make the academic occupational ecology especially “sensitive” to the accumulation and transformation of personal resources into conditional resources at both departmental and institutional levels (Hobfoll, 1989 ; Hobfoll et al., 2018 ). University lecturers will strive to conserve, accumulate and invest their resources; resources then cluster into caravans and move through organizational passageways (Hobfoll, 1989 ; Hobfoll et al., 2018 ). In this lens, optimism functions primarily as an appraisal mechanism based on context. Specifically, university lecturers’ positive future expectations reduce their perception of resource loss by considering their job demands as development opportunities while interpreting negative events as temporary specific situations (Carver et al., 2010 ), thereby elevating job satisfaction. As a result, lecturers make more favorable appraisals of their working circumstances, leading to the belief that these pathways are functioning effectively, which is closely related to their job satisfaction. Therefore, the relationship between optimism and job satisfaction represents the conversion of a personal resource (positive expectancies) into a conditional resource (a positive job evaluation); job satisfaction then transmits these gains to well-being as part of a gain spiral mentioned in the COR theory (Hobfoll et al., 2018 ). In addition, job satisfaction functions as a loss mitigation and acts as an emotional buffer for well-being during difficult times. Lecturers can reduce their loss concentration, overcome losses more effectively, and burn less energy on mitigation when they perceive resources as available and recoverable (Hobfoll et al., 2018 ). In fact, job satisfaction is strongly associated with well-being in a previous study (Bowling et al., 2010 ). Therefore, our result illustrates how job satisfaction absorbs and stabilizes the positive feelings generated by optimism, subsequently amplifying them into a broader sense of well-being. Furthermore, job satisfaction serves as a catalyst for the distribution of novel resources. The COR theory emphasizes gain spirals, which propose that the more resources one invests, the more they own and vice versa (Hobfoll et al., 2018 ). In this situation, optimism functions as the primary generator, whereas job satisfaction acts as the essential mediator that transforms a personal work-related perception into a tangible well-being result. Meanwhile, hope—which includes agency (goal-navigation energy) and pathway (planning to meet goals)—has a direct effect on well-being without reliable mediation through job satisfaction since it fosters a sense of success toward long-term professional objectives, even when immediate job evaluations are not particularly favorable (Snyder, 2002 ). Therefore, hope can maintain momentum and meaning independent of temporary satisfaction with institutional processes. These functional splits align with the COR’s gain spiral logic: optimism “opens the context,” while hope “opens the route.” The non-significance of self-efficacy and resilience can also be understood from the COR perspective. Although self-efficacy and resilience are both protective resources, their effects are most visible under salient loss or threat (e.g., heavy role conflicts). Thus, when resources loss are modest, their main effects may be muffled (Hobfoll et al., 2018 ). Another COR explanation is the passageway quality. If the organizational passageway is not efficient enough, some personal resources can’t be converted into conditional outcomes (Hobfoll et al., 2018 ). These conditions can lead to overlaps with stronger resources in the construction (optimism and hope) since they may absorb shared variance, leaving little unique predictive power in models that include all four components. However, this point of view is beyond our understanding and scope in the present study; thus, it needs to be further investigated in future studies. Implications In the present study, our findings suggest that higher education settings should first reinforce their academic staff’s resource passageways, especially their optimism to convert to their job satisfaction, and, subsequently, well-being. Specifically, policymakers and university administrators, for example, can foster transparent workload and promotion criteria, expand academic autonomy with flexible course design and assessment, and provide necessary support such as timely systematic feedback and recognition for lecturers to reduce burdens related to their job. Such practices enable organizational passageways that allow personal resources to accumulate and flow, thereby fueling gain spirals from their job satisfaction to well-being (Hobfoll, 1989 ; Hobfoll et al., 2018 ). In addition, institutions should develop future-oriented personal resources (optimism and hope) through programs customized to academic work phases. Due to the direct and indirect prediction of optimism, optimism-focused training programs can improve lecturer’s context appraisals and their job satisfaction (Carver et al., 2010 ). Furthermore, hope-enhancement supports such as mentoring or coaching should be implemented to encourage goal achievement. This practice aligns with the COR’s perspective that hope recovers psychological resources and maintains motivation despite unfavorable job evaluations (Hobfoll et al., 2018 ; Snyder, 2002 ). Limitations and future directions Several limitations should be noted in the present study. First, cross-sectional design and convenience sampling were employed in the study, which limits causal inferences and generalizability, especially for mediation models. Mediation estimates can be biased relative to the underlying dynamic relations and are sensitive to unmeasured confounds (Maxwell & Cole, 2007 ). Future studies should investigate mediation models using longitudinal design (e.g. cross-lagged) to test directionality and gain/loss spirals over time (Hamaker et al., 2015 ; Little, 2013 ). Replications across disciplines/institutions/countries with stratified sampling should also be considered due to generalizability enhancement. Second, the study relies primarily on self-report, increasing the risk of common method variance (CMV) and social desirability bias particularly for attitudinal/affective variables although CMV does not invariably inflate associations (Spector, 2006 ). Future research should be considered better procedures to reduce this risk. Third, there may be measurement limitations. Global scales of self-efficacy of resilience can show ceiling effects and restricted variance in lecturer samples, raising the risk of false negatives (Bandura, 2006 ). In addition, our study did not test measurement invariance for the whole model across groups (e.g., genders). Although differences in variables were tested among groups, there is no assurance that incorporating all variables into a final estimation model will preserve the same structure across comparison groups. To fill this gap, future research should conduct invariance testing among groups. Finally, several key COR context variables may be missing in the present study, which represent organizational resource caravan passageways, such as organizational justice, autonomy, organizational support. Excluding these variables can limit the conversion process from personal resources to job satisfaction and well-being (Hobfoll et al., 2018 ). Subsequent designs should jointly measure both contextual and interpersonal resources and estimate multilevel mediation (Preacher et al., 2010 ). Conclusion This study advances understanding of university lecturers’ well-being by showing that two future-oriented personal resources are optimism and hope. They are both consequential yet functionally distinct. According to COR theory, our results indicate that optimism mainly serves as a context-appraisal resource that turns into a conditional resource (job satisfaction), while hope serves as a goal-navigation resource that sustains progress and replenishes psychological resource independent of momentary work appraisals. The robust connection between job satisfaction and well-being highlights its crucial function as a resource in higher education environments. In conclusion, the study establishes job satisfaction as an essential connect between optimism and well-being, while recognizing hope as a key motivator for well-being among university lecturers in academic context. Declarations Acknowledgement The authors would like to sincerely thank all of the participating university lecturers for kindly sharing their insights and experiences, which were crucial to the accomplishment of this research. Author contributions Giau Thi Ngoc Nguyen conceived and coordinated the study, led the design, oversaw data collection, and drafted the initial manuscript. Conceptualization was developed jointly by Giau Thi Ngoc Nguyen, Nghia Duc Tri Nguyen, Thu-Thuy Thi La, and Vu Hoang Anh Nguyen. Study design was further supported by Thu-Thuy Thi La, Le-Hang Thi Do, and Nghia Duc Tri Nguyen. Data were collected by Giau Thi Ngoc Nguyen, Hue-Anh Vo-Nguyen, Le-Hang Thi Do, and Anh Nguyen Ngo. Data analysis and interpretation were performed by Vu Hoang Anh Nguyen, Nghia Duc Tri Nguyen, and Giau Thi Ngoc Nguyen. The manuscript was written and revised by Giau Thi Ngoc Nguyen, Nghia Duc Tri Nguyen, and Vu Hoang Anh Nguyen. All authors reviewed and approved the final manuscript. Funding No funding was received in this study Data availability Data supporting the results of this research are obtainable from the corresponding author upon reasonable request. Ethics approval and consent to participate The study was approved by the Ethics Committee of the Graduate Academy of Social Sciences, Vietnam Academy of Social Sciences (Approval No. 3462/QĐ-HVKHXH). All participants provided informed consent before taking part. Consent for publication Not applicable. Clinical trial number Not applicable. Competing interests The authors declare no competing interests. References Adam, A., & Brown, N. (2022). Chapter 10: Developing the new academic. In C. S. Sarrico, M. J. Rosa, & T. Carvalho (Eds.), Research Handbook on Academic Careers and Managing Academics . Edward Elgar Publishing. https://doi.org/10.4337/9781839102639.00018 Adil, A., & Kamal, A. (2019). Authentic leadership and psychological capital in job demands-resources model among Pakistani university teachers. International Journal of Leadership in Education , 23 (6), 734-754. https://doi.org/10.1080/13603124.2019.1580772 Agyapong, B., Obuobi-Donkor, G., Burback, L., & Wei, Y. (2022). 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Management Decision , 53 (10), 2268–2286. https://doi.org/10.1108/MD-10-2014-0609 Tables Table 1 Characteristics of demographic variables (n = 224) n % Gender Males Females 98 126 43.8% 56.2% Age groups 28–34 35–39 40–44 45–49 ≥ 50 38 53 73 28 32 17.0% 23.7% 32.6% 12.5% 14.3% Marital status 1 Currently partnered Currently not partnered 142 82 63.4% 36.6% Majority 2 STEM Non-STEM 47 177 21.0% 79.0% Number of subjects ≤ 3 subjects ≥ 4 subjects 142 82 63.4% 36.6% Note. 1 Martial status variable was categorized into two groups: currently partnered (including married) and currently not partnered (including single, divorced, separated, widowed, and others). 2 Majority variable was categorized into two groups: STEM (including natural sciences and Medicine) and Non-STEM (including social sciences, linguistics, arts, economics, and others) Table 2 Means, standard deviations, reliability, and correlations between variables M ± SD α SE HO RE OP JS SE HO RE OP JS WB 5.11 ± 0.77 4.67 ± 0.73 4.92 ± 0.70 4.73 ± 0.87 3.89 ± 0.69 3.57 ± 0.88 0.830 0.792 0.694 0.825 — 0.947 — 0.489 *** 0.571 *** 0.428 *** 0.149 * 0.304 *** — 0.626 *** 0.531 *** 0.204 ** 0.465 *** — 0.570 *** 0.176 ** 0.424 *** — 0.250 *** 0.445 *** — 0.410 *** Table 3 Tests of normality for study variables Kolmogorov-Smirnov Shapiro-Wilk D p W p Self-Efficacy Hope Resilience Optimism Job Satisfaction Well-being 0.139 0.120 0.159 0.178 0.301 0.126 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.862 0.951 0.911 0.928 0.819 0.957 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 Note. D = Kolmogorov–Smirnov statistic; W = Shapiro–Wilk statistic; p < 0.05 indicates non-normality. Table 4 Differences in variables between demographic characteristics Self-efficacy Hope Resilience Optimism Job Satisfaction Well-being M ± SD p M ± SD p M ± SD p M ± SD p M ± SD p M ± SD p Gender 1 Males Females 5.13 ± 0.09 5.10 ± 0.06 0.168 4.63 ± 0.07 4.70 ± 0.06 0.582 4.88 ± 0.08 4.95 ± 0.06 0.809 4.66 ± 0.09 4.79 ± 0.07 0.402 3.87 ± 0.07 3.90 ± 0.06 0.852 3.61 ± 0.09 3.55 ± 0.07 0.436 Age groups 2 28–34 35–39 40–44 45–49 ≥ 50 5.06 ± 0.10 4.99 ± 0.12 5.13 ± 0.09 5.00 ± 0.16 5.44 ± 0.08 0.071 4.62 ± 0.11 4.50 ± 0.11 4.71 ± 0.08 4.70 ± 0.15 4.85 ± 0.13 0.141 4.82 ± 0.11 4.87 ± 0.12 4.95 ± 0.08 4.81 ± 0.11 5.17 ± 0.10 0.228 4.63 ± 0.16 4.72 ± 0.13 4.73 ± 0.10 4.80 ± 0.13 4.83 ± 0.14 0.899 3.79 ± 0.10 3.91 ± 0.10 3.82 ± 0.08 3.82 ± 0.13 4.19 ± 0.12 0.083 3.50 ± 0.14 3.45 ± 0.12 3.49 ± 0.10 3.72 ± 0.17 3.92 ± 0.15 0.100 Marital status 1 Partnered Not partnered 5.16 ± 0.06 5.03 ± 0.09 0.128 4.67 ± 0.06 4.65 ± 0.08 0.844 4.95 ± 0.06 4.87 ± 0.08 0.552 4.75 ± 0.07 4.71 ± 0.09 0.661 4.00 ± 0.06 3.72 ± 0.08 0.004 ** 3.64 ± 0.07 3.46 ± 0.09 0.152 Majority 1 STEM Non-STEM 4.95 ± 0.13 5.15 ± 0.05 0.138 4.49 ± 0.13 4.71 ± 0.05 0.176 4.79 ± 0.13 4.96 ± 0.05 0.311 4.45 ± 0.14 4.81 ± 0.06 0.018 * 3.81 ± 0.11 3.91 ± 0.05 0.443 3.45 ± 0.16 3.61 ± 0.06 0.816 Number of subjects 1 ≤ 3 subjects ≥ 4 subjects 5.10 ± 0.07 5.13 ± 0.07 0.664 4.66 ± 0.06 4.68 ± 0.08 0.915 4.91 ± 0.06 4.94 ± 0.08 0.564 4.71 ± 0.07 4.76 ± 0.10 0.677 3.94 ± 0.06 3.80 ± 0.07 0.243 3.61 ± 0.07 3.51 ± 0.10 0.511 Note. 1 The Mann-Whitney U test, 2 Kruskal-Wallis test ** p < 0.01, * p < 0.05 Table 5 Direct and indirect effects of the hypothesis model (n = 224) Model β (SE) z p 95% LLCI 95% ULCI Direct Effects SE → WB -0.002 (0.067) -0.033 0.974 -0.167 0.141 SE → JS 0.025 (0.081) 0.307 0.759 -0.156 0.188 RE → WB 0.127 (0.078) 1.634 0.102 -0.037 0.289 RE → JS -0.007 (0.094) -0.075 0.940 -0.236 0.196 OP → WB * 0.175 (0.069) 2.545 0.011 0.029 0.308 OP → JS * 0.193 (0.082) 2.360 0.018 0.045 0.350 HO → WB ** 0.233 (0.072) 3.214 0.001 0.054 0.400 HO → JS 0.094 (0.087) 1.077 0.282 -0.114 0.305 JS → WB *** 0.296 (0.055) 5.348 < 0.001 0.154 0.429 Indirect Effects SE → JS → WB 0.007 (0.024) 0.306 0.759 -0.052 0.054 RE → JS → WB -0.002 (0.028) -0.075 0.940 -0.081 0.058 OP → JS → WB * 0.057 (0.027) 2.159 0.031 0.015 0.120 HO → JS → WB 0.028 (0.026) 1.056 0.291 -0.029 0.108 Abbreviations: SE: Self-efficacy, RE: Resilience, OP: Optimism, HO: Hope, JS: Job satisfaction, WB: Well-being. *** p < 0.001, ** p < 0.01, * p < 0.05 Additional Declarations No competing interests reported. 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07:15:34","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":165747,"visible":true,"origin":"","legend":"","description":"","filename":"b15988c8633b41c5acfe28c0294474b81structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7520312/v1/9f0903fb6b303b7a4b13db8e.xml"},{"id":92475138,"identity":"721f145c-d02d-48ea-9bfe-4f4c2f05e648","added_by":"auto","created_at":"2025-09-30 07:15:34","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179539,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7520312/v1/063962228728e89e16cd27dc.html"},{"id":92475121,"identity":"93ccdac5-8f71-4999-98ef-751594ec819d","added_by":"auto","created_at":"2025-09-30 07:15:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52158,"visible":true,"origin":"","legend":"\u003cp\u003eHypothesis model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7520312/v1/e66ebed4b205a57f40c5d99e.png"},{"id":92477031,"identity":"f7e8cb67-df7b-4117-a887-b07a791036e1","added_by":"auto","created_at":"2025-09-30 07:23:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55863,"visible":true,"origin":"","legend":"\u003cp\u003ePath analysis of the mediating role of job satisfaction among university lecturers (n=224). Note. Bold lines indicate significant paths; dot lines indicate non-significant paths.\u003c/p\u003e\n\u003cp\u003e***p\u0026lt;0.001, **p\u0026lt;0.01, *p\u0026lt;0.05\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7520312/v1/c295a45c35df088d27fb4348.png"},{"id":92480014,"identity":"8caea120-b007-4b03-977b-7fda6c597960","added_by":"auto","created_at":"2025-09-30 07:39:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1250326,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7520312/v1/42f2a635-c74c-490b-b638-7c85576efae7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From Psychological Capital to Well-being: Job Satisfaction as a Mediator among University Lecturers in Vietnam","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIt is well-known that teaching is one of the most stressful and demanding occupations in the world (Pithers, 1995), especially teaching in higher education (Kang \u0026amp; Sidhu, 2015). Due to the substantial influence on teaching quality, the responsibility for student outcomes, and overall institutional success, university lecturers - the most important human resource in higher education, encounter distinct challenges, such as substantial workloads, the imperative to publish, administrative duties, and the necessity to perpetually enhance their knowledge (Adam \u0026amp; Brown, 2022; Kinman \u0026amp; Wray, 2020). Further, competition over university ranking has been intensifying worldwide (Enders, 2014; Hazelkorn, 2011), meaning that their role becomes conflicted and complex. These unpleasant responsibilities lead to significant changes from academic settings to industrial factories, where multitasking and high productivity are the primary concerns(Rae, 2010). In other words, academic staffs are forced to reach higher professional expectations while receiving limited resources, further exhausting their coping mechanisms (Barkhuizen \u0026amp; Rothmann, 2008).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, due to high demands from institutions, managing to balance multiple duties (as an educator and a staff member) at once tilts this balance and places burdens on university lecturers (Urbina-Garcia, 2020). In fact, there are significant health and well-being crises associated with working in higher education (Rahman et al., 2024). Numerous studies have explored negative psychological outcomes experienced by university lecturers. They are susceptible to occupational stress, anxiety, depression, and burnout (Agyapong et al., 2022), which directly results in their job dissatisfaction and low level of well-being (Mudrak et al., 2018). In turn, lecturers with mental health problems reported a low level of teaching quality, work-related motivation, performance, and commitment (Amer et al., 2022; Daumiller et al., 2021; Wang et al., 2020). Together, empirical evidence highlights the vulnerabilities of university lecturers to the difficulties and their consequences in the current higher education landscape.\u003c/p\u003e\n\u003cp\u003eMaintaining job satisfaction and well-being among academic staff is not only a human resource goal but is also directly linked to teaching quality and institutional success and competitiveness (Kwok et al., 2015). Recent literature suggested job satisfaction and well-being as crucial factors in establishing positive experiences in an academic context (Douglas et al., 2024; Rosser, 2004). It is noteworthy that the majority of studies tend to concentrate on examining the influence of workplace-related issues on the mental health of academics (Urbina-Garcia, 2020), while there were limited approaches to enhance and promote the positive and intrinsic aspects of academic staff\u0026apos;s well-being (LaMontagne et al., 2014). Thus, the present study sought to investigate the attainment of lecturers\u0026apos; well-being via individual-level coping strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePsychological Capital as a predictor of Job Satisfaction and Well-being\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn response to pressures in higher education systems, Psychological Capital (PsyCap)\u0026mdash;a construct encompassing self-efficacy, hope, resilience, and optimism\u0026mdash;has emerged as a crucial psychological resource for assisting lecturers in sustaining their well-being and job satisfaction amid these challenges (Liu \u0026amp; Du, 2024; Luthans, Youssef, et al., 2007). According to Adil and Kamal (2019), PsyCap represents a significant personal capital to be taken advantage of in educational environments. Recently, its association with job satisfaction and well-being has been primarily examined from social and psychological outlook (Luthans, Avolio, et al., 2007).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study, a comprehensive overview of PsyCap will be applied under the viewpoint of the Conservation of Resources theoretical framework (Hobfoll, 1989) to establish a deep understanding of this concept since its perspective is regarded as one of the best resource-oriented approaches that underscores the significance of personal incentive to preserve, protect, and hoard supportive means. In the original work by Hobfoll (1989), the author argued that these attempts aim to ensure a balanced psychological condition for individuals even when there are depletions in resources due to the demands of their role. By contrast, absences in inner resources will disturb or collapse their equilibrium state when facing taxing requirements, resulting in lower job satisfaction and well-being. In other words, depending on the level of investment in personal resources, it creates gain/loss spirals that determine the ability to overcome difficulties. Individuals with greater inner resources are more likely to feel elevated levels of motivation, satisfaction, and well-being (Xanthopoulou et al., 2007). Furthermore, due to its state-like nature, PsyCap is adaptable and hence flexible to optimization (Kun \u0026amp; Gadanecz, 2022; Sarwar et al., 2021). Therefore, PsyCap can be accumulated via training and practice. Several studies have attempted to provide evidence of the growth of PsyCap as a developmental state through training intervention (Demerouti et al., 2011; Luthans et al., 2006; Luthans et al., 2010). These findings indicated that by cultivating PsyCap, lecturers\u0026rsquo; resources are increasingly abundant over time, which means they are better able to cope with work-related obstacles and experience more satisfaction and achieve more well-being (Sarwar et al., 2021). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWell-being as a result of Job Satisfaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWell-being is a multidimensional concept that reflects a subjective evaluation of one\u0026rsquo;s life as a whole (Diener, 1984). It is a harmonious combination of both emotional and cognitive aspects, indicated by the presence of positive affect, the absence of negative affect, and the development of satisfaction with one\u0026rsquo;s own life (Diener, 1984). According to Diener (1994), well-being demonstrates a stable construct over time. However, it is also known to be susceptible to a wide range of environmental occurrences as well as related psychological factors (Wright, 2004).\u003c/p\u003e\n\u003cp\u003eWright (2004) identifies job satisfaction as a common component that best characterizes well-being in the workplace. Job satisfaction, as described by Spector (1997), refers to the degree of pleasure that an individual experiences with their employment and the sense of achievement derived from performing it. Since work has consistently been perceived to be an indispensable element of life (Yahyagil, 2015), personal perceptions of well-being and happiness are significantly influenced by job satisfaction due to the work centrality in individuals\u0026apos; lives (Sironi, 2019). Thus, the level of job satisfaction varies across different domains of work, depending on an individual\u0026rsquo;s evaluations. However, the presence of job satisfaction is still the key factor determining the appearance of life satisfaction. In fact, job satisfaction was also regarded as a precursor to life satisfaction (Erdogan et al., 2012), forming a foundation for the close relationship between job satisfaction and well-being.\u003c/p\u003e\n\u003cp\u003eEmpirical evidence supports these claims. A meta-analysis by Bowling et al. (2010) confirmed substantive positive associations between job satisfaction and well-being via affiliated components: life satisfaction, happiness, and positive affect. Longitudinal evidence indicates a reciprocal link between job and life satisfaction. Although the life-to-job path is often slightly stronger, the evidence still suggests that job satisfaction contributes to overall well-being over time (Bialowolski \u0026amp; Weziak-Bialowolska, 2021; Weziak-Bialowolska et al., 2020). These findings are consistent with the part-whole perspective, which states that well-being is a high-order construct (considered as the \u0026ldquo;whole\u0026rdquo;) that is composed of multiple life domains (considered as the \u0026ldquo;part\u0026rdquo;), among which, job satisfaction is one of the domains (Bowling et al., 2010; Cannas et al., 2019). By contrast, the way an individual evaluates their job satisfaction as a specific \u0026ldquo;part\u0026rdquo; domain, in turn, influences the \u0026ldquo;whole\u0026rdquo; well-being construct. Therefore, the disparities in well-being are the result of the variance of job satisfaction and vice versa (Benevene et al., 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJob satisfaction as a potential mediator\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aforementioned evidence suggests that job satisfaction may serve as a key mediator in the link between PsyCap and well-being. Within the Conservation of Resources theory, PsyCap enables individuals to reappraise demands as manageable challenges with efficient effort investment that converts personal resources into achievements, autonomy, and recognition (Hobfoll et al., 2018; Luthans, 2006; Luthans, Avolio, et al., 2007). These work-related benefits received from PsyCap crystallize into job satisfaction as a specific domain outcome. Under the part-whole theory, well-being is a global evaluation formed by accumulating satisfaction via life domains, in which job satisfaction is one of the main contributors (Bowling et al., 2010; Diener, 1984). Taken together, job satisfaction is a bridge between two theoretical frameworks with connections via PsyCap and well-being.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe present study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on literature review, we suggest a potential link between PsyCap and well-being as well as the mediating role of job satisfaction among university lecturers. To our best knowledge, the understanding of this mechanism remains unclear with limited supportive evidence. Research on this subject advances knowledge of the connection between academic staff\u0026rsquo;s PsyCap and their well-being while clarifying the benefit of job satisfaction as an effective resource in the academic settings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt should be noted that although PsyCap is often modeled as a higher-order construct, its four components\u0026mdash;self-efficacy, resilience, optimism, and hope\u0026mdash;stem from distinct theoretical traditions and may operate through different mechanisms. Drawing on Conservation of Resources (Hobfoll, 1989; Hobfoll et al., 2018), we argue that these resources not only converge into a general PsyCap factor but also exert unique effects on outcomes. Specifically, since self-efficacy is task-focused, it should more strongly predict job satisfaction, whereas optimism, hope, and resilience\u0026mdash;resources tied to positive future expectancies and recovery\u0026mdash;should show comparatively stronger direct effects on well-being. Therefore, job satisfaction is expected to partially mediate the relationships between each PsyCap component and well-being (Bowling et al., 2010). Testing the disaggregated model allows for the detection of heterogeneous effects and provides implications for interventions specific to each psychological ability.\u003c/p\u003e\n\u003cp\u003eAdditionally, job satisfaction was employed using single-item approach in the present study. On the one hand, single-item measures are less suitable for assessing specific facets (e.g., pay, supervision), however, they are appropriate when the construct of interest is overall job satisfaction (Nagy, 2002). On the other hand, recent studies do not dismiss single-item measures in relation to job satisfaction (Dolbier et al., 2005).\u003c/p\u003e\n\u003cp\u003eTaken together, the present study aims to investigate these associations with the following expectations (see Figure 1).\u003c/p\u003e\n\u003cp\u003eH1: University lecturers\u0026rsquo; PsyCap components directly relate to their well-being\u003c/p\u003e\n\u003cp\u003eH2: Their job satisfaction partially mediates the relationship between PsyCap components and well-being\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT FIGURE 1 HERE]\u003c/strong\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eParticipants and procedures\u003c/h2\u003e\u003cp\u003eA cross-sectional design was established in the present study. The protocol was reviewed and approved by the Ethics Committee of the Graduate Academy of Social Sciences, Vietnam Academy of Social Sciences (Reference No. 3462/QĐ-HVKHXH), and conducted in accordance with APA ethical guidelines for psychology studies. Participants were Vietnamese university lecturers recruited from both private and public academic institutions in Ho Chi Minh City via a convenience sampling using Google Forms platforms. They were fully informed about the present study, including the purposes and confidentiality of the study as well as their autonomy to withdraw at any time. Those who have provided consent to the study terms and conditions can proceed to the final survey.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMeasurements\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003ePsychological capital\u003c/h2\u003e\u003cp\u003eWe employed the Vietnamese version of the 12-item Psychological Capital Questionnaire (Nguyen \u0026amp; Nguyen, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) to evaluate psychological capital among university lecturers. Four elements\u0026mdash;self-efficacy, hope, optimism, and resilience from the initially published version by Luthans, Avolio, et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e)\u0026mdash;are still present in this version. Participants were asked to rate their feelings on a 6-point Likert scale. The Vietnamese scale has shown appropriate structure, with CFA loadings of items and composite reliability indicate acceptable goodness of fit.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eJob satisfaction\u003c/h3\u003e\n\u003cp\u003eJob satisfaction was assessed with a single global item: \u0026ldquo;Overall, how satisfied are you with your job?\u0026rdquo; (1\u0026thinsp;=\u0026thinsp;very dissatisfied to 5\u0026thinsp;=\u0026thinsp;very satisfied). We chose a single-item measure because overall job satisfaction is a global evaluation, and prior evidence indicates that single-item measures show substantial convergence with multi-item instruments and adequate reliability for structural analyses (Nagy, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Wanous et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). We are aware that using a single item precludes internal consistency estimates and may reduce precision; it also cannot capture satisfaction facets. We therefore interpret effects at the global level and recommend multi-item facet scales when facet-specific inferences are required.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eWell-being\u003c/h2\u003e\u003cp\u003eIn the present study, the Vietnamese version of the WHO-5 Well-being Index (Nguyen \u0026amp; Le, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) was utilized to measure university lecturers\u0026rsquo; well-being. Participants indicated how often they felt each statement applied over the previous two weeks on a 6-point scale. Prior research with the Vietnamese version has demonstrated excellent internal consistency, with the alpha coefficient of 0.95 (Nguyen \u0026amp; Le, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eIn the present study, data management was performed using SPSS 25.0, while JASP 0.16.4 was employed to test our hypothesis by conducting a path analysis. To illustrate the demographic characteristics, we perform descriptive statistics, including frequencies, percentage, means, standard deviations. Additionally, Cronbach\u0026rsquo;s alpha was tested to ensure the scale\u0026rsquo;s reliability, while correlation analysis was conducted to examine the relationship between variables. Furthermore, the normality of the data was evaluated using Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests before testing differences in each variable level among groups. Finally, a path analysis with a 5000-sample bootstrapping was conducted to determine the total, direct, and indirect effects of the variables in the final model.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eDescriptive demographic characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 224 university lecturers, most of whom were female (56.2%). Lecturers\u0026apos; ages were distributed as follows: 28\u0026ndash;34 years old (17.0%, n = 38), 35\u0026ndash;39 years old (23.7%, n = 53), 40\u0026ndash;44 years old (32.6%, n = 73), 45\u0026ndash;49 years old (12.5%, n = 28), and \u0026ge; 50 years old (14.3%, n = 32). For current marital status, a majority (n = 142) reported being partnered (63.4%), with 36.6% not partnered (n = 82). Among the majority, most lecturers were teaching in non-STEM fields (79.0%, n = 177), while the other 21.0% were teaching in STEM (n = 47). Regarding the number of subjects they are teaching, 63.4% (n = 142) reported \u0026le; 3 subjects, and 36.6% (n = 82) reported \u0026ge; 4 subjects (see Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT TABLE 1 HERE]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCharacteristics, reliability, and correlations of variables\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 shows the means, standard deviations, reliability, and correlations between self-efficacy (SE), resilience (RE), hope (HO), optimism (OP), job satisfaction (JS), and well-being (WB). The internal consistency was acceptable (\u0026alpha; = 0.694) to excellent (\u0026alpha; = 0.947) for multi-item scales, except for JS; since it was a single item, the alpha coefficient is not applicable.\u003c/p\u003e\n\u003cp\u003eAll variables were positively correlated. Moderate to strong correlation was found between PsyCap facets, including SE and HO (\u003cem\u003er\u003c/em\u003e = 0.489, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), SE and RE (\u003cem\u003er\u003c/em\u003e = 0.571, p \u0026lt; 0.001), SE and OP (\u003cem\u003er\u003c/em\u003e = 0.428, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), HO and RE (\u003cem\u003er\u003c/em\u003e = 0.626, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), HO and OP (\u003cem\u003er\u003c/em\u003e = 0.531, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and RE and OP (\u003cem\u003er\u003c/em\u003e = \u0026nbsp;0.570, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Besides, PsyCap facets significantly showed a weak correlation with JS in the link with SE (\u003cem\u003er\u003c/em\u003e = 0.149, \u003cem\u003ep\u003c/em\u003e = 0.025), HO (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.204, \u003cem\u003ep\u003c/em\u003e = 0.002), RE (\u003cem\u003er\u003c/em\u003e = 0.176, \u003cem\u003ep\u003c/em\u003e = 0.008), and OP (\u003cem\u003er\u003c/em\u003e = 0.250, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). In addition, WB showed small-to-moderate positive associations with all constructs, including SE (\u003cem\u003er\u003c/em\u003e = 0.304, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), HO (\u003cem\u003er\u003c/em\u003e = 0.465, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), RE (\u003cem\u003er\u003c/em\u003e = 0.424, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), OP (\u003cem\u003er\u003c/em\u003e = 0.445, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and JS (\u003cem\u003er\u003c/em\u003e = 0.410,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT TABLE 2 HERE]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNormal distribution of variables\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNormality of the study variables was examined using Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests (see Table 3). All variables showed significant departures from a normal distribution with all p-values below the 0.001 threshold, including self-efficacy (\u003cem\u003eD\u003c/em\u003e = 0.139, \u003cem\u003eW\u003c/em\u003e = 0.862), hope (\u003cem\u003eD\u003c/em\u003e = 0.120, \u003cem\u003eW\u003c/em\u003e = 0.951), resilience (\u003cem\u003eD\u003c/em\u003e = 0.159, \u003cem\u003eW\u003c/em\u003e = 0.911), optimism (\u003cem\u003eD\u003c/em\u003e = 0.178, \u003cem\u003eW\u003c/em\u003e = 0.928), job satisfaction (\u003cem\u003eD\u003c/em\u003e = 0.301, \u003cem\u003eW\u003c/em\u003e = 0.819), and well-being (\u003cem\u003eD\u003c/em\u003e = 0.126, \u003cem\u003eW\u003c/em\u003e = 0.957). Therefore, differences between independent groups were compared using the Kruskal-Wallis and Mann-Whitney U tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT TABLE 3 HERE]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDifferences between independent groups\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA Kruskal-Wallis test was conducted to determine the difference in SE, HO, RE, OP, JS, and WB between age groups (see Table 4). Results show that there were no significant differences in SE [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 8.631, \u003cem\u003ep\u003c/em\u003e = 0.071], HO [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 6.902, \u003cem\u003ep\u003c/em\u003e = 0.141], RE [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 5.634, \u003cem\u003ep\u003c/em\u003e = 0.228], OP [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 1.070, \u003cem\u003ep\u003c/em\u003e = 0.899], JS [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 8.253, \u003cem\u003ep\u003c/em\u003e = 0.083], and WB [\u003cem\u003e\u0026chi;\u003c/em\u003e2(4) = 7.75, \u003cem\u003ep\u003c/em\u003e = 0.100] among five age groups.\u003c/p\u003e\n\u003cp\u003eTo assess the difference in those variables between gender, marital status, majority, and the number of subjects, the Mann-Whitney U test was employed. Table 4 shows that most of the characteristics were not significantly different (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). Changes are only found in the distribution of job satisfaction between two marital status groups (\u003cem\u003ez\u003c/em\u003e = -2.860, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.004) and of optimism between STEM and non-STEM lecturers (\u003cem\u003ez\u0026nbsp;\u003c/em\u003e= -2.375, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT TABLE 4 HERE]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHypothesis testing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the final path analysis model as shown in Table 5 and Figure 2, analysis revealed that well-being can be directly predicted by optimism (\u0026beta; = 0.175, SE = 0.069, z = 2.545, p = 0.011, 95% CI [0.029; 0.308]), hope (\u0026beta; = 0.233, SE = 0.072, z = 3.214, p = 0.001, 95% CI [0.054; 0.400]), and job satisfaction (\u0026beta; = 0.296, SE = 0.055, z = 5.348, p \u0026lt; 0.001, 95% CI [0.154; 0.429]). However, job satisfaction can only be directly predicted by optimism (\u0026beta; = 0.193, SE = 0.082, z = 2.360, p = 0.018, 95% CI [0.045; 0.350]). Other direct paths were not statistically significant.\u003c/p\u003e\n\u003cp\u003eRegarding the indirect path, the only mediating effect of job satisfaction was found in the relationship between optimism and well-being (\u0026beta; = 0.057, SE = 0.027, z = 2.159, p = 0.031, 95% CI [0.015; 0.120]), while other indirect effects were statistically insignificant (see Table 5 and Figure 2). The final model explained 36.1% of variance in well-being (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.361), highlighting the significant role of job satisfaction in promoting the influence of optimism on well-being among academic staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT TABLE 5 HERE]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[INSERT FIGURE 2 HERE]\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study aims to investigate the direct effects of four components of PsyCap on university lecturers\u0026rsquo; well-being while examining the mediating role of job satisfaction in the relationship. Results showed that optimism positively predicts job satisfaction and well-being, while also exhibiting an indirect effect on well-being through satisfaction. By contrast, only direct effect of hope on well-being was confirmed while the mediation path through job satisfaction in this relationship was not found. Regarding self-efficacy and resilience, these variables did not show significant direct effects on well-being as well as indirect effects via job satisfaction. Within the framework of Conservation of Resources (COR), these results clarify not only what occurs but also why and when these psychological resources benefit university lecturers.\u003c/p\u003e\u003cp\u003eIn academia, university lecturers simultaneously shoulder the tripartite roles of teaching, research, and service; work on long academic outcome cycles (projects, articles, and grants); and face frequent external subjective evaluations (e.g., student ratings) alongside competitive pressures for resources. From the COR perspective, these characteristics make the academic occupational ecology especially \u0026ldquo;sensitive\u0026rdquo; to the accumulation and transformation of personal resources into conditional resources at both departmental and institutional levels (Hobfoll, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). University lecturers will strive to conserve, accumulate and invest their resources; resources then cluster into caravans and move through organizational passageways (Hobfoll, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this lens, optimism functions primarily as an appraisal mechanism based on context. Specifically, university lecturers\u0026rsquo; positive future expectations reduce their perception of resource loss by considering their job demands as development opportunities while interpreting negative events as temporary specific situations (Carver et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), thereby elevating job satisfaction. As a result, lecturers make more favorable appraisals of their working circumstances, leading to the belief that these pathways are functioning effectively, which is closely related to their job satisfaction. Therefore, the relationship between optimism and job satisfaction represents the conversion of a personal resource (positive expectancies) into a conditional resource (a positive job evaluation); job satisfaction then transmits these gains to well-being as part of a gain spiral mentioned in the COR theory (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, job satisfaction functions as a loss mitigation and acts as an emotional buffer for well-being during difficult times. Lecturers can reduce their loss concentration, overcome losses more effectively, and burn less energy on mitigation when they perceive resources as available and recoverable (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In fact, job satisfaction is strongly associated with well-being in a previous study (Bowling et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Therefore, our result illustrates how job satisfaction absorbs and stabilizes the positive feelings generated by optimism, subsequently amplifying them into a broader sense of well-being.\u003c/p\u003e\u003cp\u003eFurthermore, job satisfaction serves as a catalyst for the distribution of novel resources. The COR theory emphasizes gain spirals, which propose that the more resources one invests, the more they own and vice versa (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this situation, optimism functions as the primary generator, whereas job satisfaction acts as the essential mediator that transforms a personal work-related perception into a tangible well-being result.\u003c/p\u003e\u003cp\u003eMeanwhile, hope\u0026mdash;which includes agency (goal-navigation energy) and pathway (planning to meet goals)\u0026mdash;has a direct effect on well-being without reliable mediation through job satisfaction since it fosters a sense of success toward long-term professional objectives, even when immediate job evaluations are not particularly favorable (Snyder, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Therefore, hope can maintain momentum and meaning independent of temporary satisfaction with institutional processes. These functional splits align with the COR\u0026rsquo;s gain spiral logic: optimism \u0026ldquo;opens the context,\u0026rdquo; while hope \u0026ldquo;opens the route.\u0026rdquo;\u003c/p\u003e\u003cp\u003eThe non-significance of self-efficacy and resilience can also be understood from the COR perspective. Although self-efficacy and resilience are both protective resources, their effects are most visible under salient loss or threat (e.g., heavy role conflicts). Thus, when resources loss are modest, their main effects may be muffled (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Another COR explanation is the passageway quality. If the organizational passageway is not efficient enough, some personal resources can\u0026rsquo;t be converted into conditional outcomes (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These conditions can lead to overlaps with stronger resources in the construction (optimism and hope) since they may absorb shared variance, leaving little unique predictive power in models that include all four components. However, this point of view is beyond our understanding and scope in the present study; thus, it needs to be further investigated in future studies.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eImplications\u003c/h2\u003e\u003cp\u003eIn the present study, our findings suggest that higher education settings should first reinforce their academic staff\u0026rsquo;s resource passageways, especially their optimism to convert to their job satisfaction, and, subsequently, well-being. Specifically, policymakers and university administrators, for example, can foster transparent workload and promotion criteria, expand academic autonomy with flexible course design and assessment, and provide necessary support such as timely systematic feedback and recognition for lecturers to reduce burdens related to their job. Such practices enable organizational passageways that allow personal resources to accumulate and flow, thereby fueling gain spirals from their job satisfaction to well-being (Hobfoll, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn addition, institutions should develop future-oriented personal resources (optimism and hope) through programs customized to academic work phases. Due to the direct and indirect prediction of optimism, optimism-focused training programs can improve lecturer\u0026rsquo;s context appraisals and their job satisfaction (Carver et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Furthermore, hope-enhancement supports such as mentoring or coaching should be implemented to encourage goal achievement. This practice aligns with the COR\u0026rsquo;s perspective that hope recovers psychological resources and maintains motivation despite unfavorable job evaluations (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Snyder, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and future directions\u003c/h2\u003e\u003cp\u003eSeveral limitations should be noted in the present study. First, cross-sectional design and convenience sampling were employed in the study, which limits causal inferences and generalizability, especially for mediation models. Mediation estimates can be biased relative to the underlying dynamic relations and are sensitive to unmeasured confounds (Maxwell \u0026amp; Cole, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Future studies should investigate mediation models using longitudinal design (e.g. cross-lagged) to test directionality and gain/loss spirals over time (Hamaker et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Little, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Replications across disciplines/institutions/countries with stratified sampling should also be considered due to generalizability enhancement.\u003c/p\u003e\u003cp\u003eSecond, the study relies primarily on self-report, increasing the risk of common method variance (CMV) and social desirability bias particularly for attitudinal/affective variables although CMV does not invariably inflate associations (Spector, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Future research should be considered better procedures to reduce this risk.\u003c/p\u003e\u003cp\u003eThird, there may be measurement limitations. Global scales of self-efficacy of resilience can show ceiling effects and restricted variance in lecturer samples, raising the risk of false negatives (Bandura, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In addition, our study did not test measurement invariance for the whole model across groups (e.g., genders). Although differences in variables were tested among groups, there is no assurance that incorporating all variables into a final estimation model will preserve the same structure across comparison groups. To fill this gap, future research should conduct invariance testing among groups.\u003c/p\u003e\u003cp\u003eFinally, several key COR context variables may be missing in the present study, which represent organizational resource caravan passageways, such as organizational justice, autonomy, organizational support. Excluding these variables can limit the conversion process from personal resources to job satisfaction and well-being (Hobfoll et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Subsequent designs should jointly measure both contextual and interpersonal resources and estimate multilevel mediation (Preacher et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study advances understanding of university lecturers\u0026rsquo; well-being by showing that two future-oriented personal resources are optimism and hope. They are both consequential yet functionally distinct. According to COR theory, our results indicate that optimism mainly serves as a context-appraisal resource that turns into a conditional resource (job satisfaction), while hope serves as a goal-navigation resource that sustains progress and replenishes psychological resource independent of momentary work appraisals. The robust connection between job satisfaction and well-being highlights its crucial function as a resource in higher education environments. In conclusion, the study establishes job satisfaction as an essential connect between optimism and well-being, while recognizing hope as a key motivator for well-being among university lecturers in academic context.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to sincerely thank all of the participating university lecturers for kindly sharing their insights and experiences, which were crucial to the accomplishment of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiau Thi Ngoc Nguyen conceived and coordinated the study, led the design, oversaw data collection, and drafted the initial manuscript. Conceptualization was developed jointly by Giau Thi Ngoc Nguyen, Nghia Duc Tri Nguyen, Thu-Thuy Thi La, and Vu Hoang Anh Nguyen. Study design was further supported by Thu-Thuy Thi La, Le-Hang Thi Do, and Nghia Duc Tri Nguyen. Data were collected by Giau Thi Ngoc Nguyen, Hue-Anh Vo-Nguyen, Le-Hang Thi Do, and Anh Nguyen Ngo. Data analysis and interpretation were performed by Vu Hoang Anh Nguyen, Nghia Duc Tri Nguyen, and Giau Thi Ngoc Nguyen. The manuscript was written and revised by Giau Thi Ngoc Nguyen, Nghia Duc Tri Nguyen, and Vu Hoang Anh Nguyen. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received in this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the results of this research are obtainable from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the Graduate Academy of Social Sciences, Vietnam Academy of Social Sciences (Approval No. 3462/QĐ-HVKHXH). All participants provided informed consent before taking part.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdam, A., \u0026amp; Brown, N. (2022). Chapter 10: Developing the new academic. In C. S. Sarrico, M. J. Rosa, \u0026amp; T. Carvalho (Eds.), \u003cem\u003eResearch Handbook on Academic Careers and Managing Academics\u003c/em\u003e. Edward Elgar Publishing. https://doi.org/10.4337/9781839102639.00018\u003c/li\u003e\n\u003cli\u003eAdil, A., \u0026amp; Kamal, A. (2019). 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THE ROLE OF \u0026ldquo;HAPPINESS\u0026rdquo; IN ORGANIZATIONAL RESEARCH: PAST, PRESENT AND FUTURE DIRECTIONS. In P. L. Perrewe \u0026amp; D. C. Ganster (Eds.), \u003cem\u003eResearch in Occupational Stress and Well Being: Exploring Interpersonal Dynamics\u003c/em\u003e (Vol. 4, pp. 221-264). Emerald Group Publishing Limited. https://doi.org/10.1016/S1479-3555(04)04006-5\u003c/li\u003e\n\u003cli\u003eXanthopoulou, D., Bakker, A. B., Demerouti, E., \u0026amp; Schaufeli, W. B. (2007). The role of personal resources in the job demands-resources model. \u003cem\u003eInternational Journal of Stress Management\u003c/em\u003e,\u003cem\u003e 14\u003c/em\u003e(2), 121-141. https://doi.org/10.1037/1072-5245.14.2.121\u003c/li\u003e\n\u003cli\u003eYahyagil, M. Y. (2015). Values, feelings, job satisfaction and well-being: the Turkish case. \u003cem\u003eManagement Decision\u003c/em\u003e,\u003cem\u003e 53\u003c/em\u003e(10), 2268\u0026ndash;2286. https://doi.org/10.1108/MD-10-2014-0609\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of demographic variables (n\u0026thinsp;=\u0026thinsp;224)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e43.8%\u003c/p\u003e\n \u003cp\u003e56.2%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge groups\u003c/p\u003e\n \u003cp\u003e28\u0026ndash;34\u003c/p\u003e\n \u003cp\u003e35\u0026ndash;39\u003c/p\u003e\n \u003cp\u003e40\u0026ndash;44\u003c/p\u003e\n \u003cp\u003e45\u0026ndash;49\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e17.0%\u003c/p\u003e\n \u003cp\u003e23.7%\u003c/p\u003e\n \u003cp\u003e32.6%\u003c/p\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003cp\u003e14.3%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eCurrently partnered\u003c/p\u003e\n \u003cp\u003eCurrently not partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e63.4%\u003c/p\u003e\n \u003cp\u003e36.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajority\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eSTEM\u003c/p\u003e\n \u003cp\u003eNon-STEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e21.0%\u003c/p\u003e\n \u003cp\u003e79.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of subjects\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;3 subjects\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4 subjects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e63.4%\u003c/p\u003e\n \u003cp\u003e36.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eMartial status variable was categorized into two groups: currently partnered (including married) and currently not partnered (including single, divorced, separated, widowed, and others). \u003csup\u003e2\u003c/sup\u003eMajority variable was categorized into two groups: STEM (including natural sciences and Medicine) and Non-STEM (including social sciences, linguistics, arts, economics, and others)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMeans, standard deviations, reliability, and correlations between variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026alpha;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003cp\u003eHO\u003c/p\u003e\n \u003cp\u003eRE\u003c/p\u003e\n \u003cp\u003eOP\u003c/p\u003e\n \u003cp\u003eJS\u003c/p\u003e\n \u003cp\u003eWB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003cp\u003e4.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\n \u003cp\u003e4.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\n \u003cp\u003e3.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.489\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.571\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.428\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.149\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.304\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.626\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.531\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.204\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.465\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.570\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.176\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.424\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.250\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.445\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e0.410\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTests of normality for study variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKolmogorov-Smirnov\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eShapiro-Wilk\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eW\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003cp\u003eHope\u003c/p\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003cp\u003eOptimism\u003c/p\u003e\n \u003cp\u003eJob Satisfaction\u003c/p\u003e\n \u003cp\u003eWell-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e \u003cem\u003eD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Kolmogorov\u0026ndash;Smirnov statistic; \u003cem\u003eW\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Shapiro\u0026ndash;Wilk statistic; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates non-normality.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferences in variables between demographic characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHope\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eOptimism\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eJob Satisfaction\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eWell-being\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003cp\u003e5.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e28\u0026ndash;34\u003c/p\u003e\n \u003cp\u003e35\u0026ndash;39\u003c/p\u003e\n \u003cp\u003e40\u0026ndash;44\u003c/p\u003e\n \u003cp\u003e45\u0026ndash;49\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003cp\u003e4.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003cp\u003e5.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e\n \u003cp\u003e4.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003cp\u003e4.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003cp\u003e5.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003cp\u003e4.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e4.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e4.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003cp\u003e3.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003cp\u003e3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003cp\u003e3.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003ePartnered\u003c/p\u003e\n \u003cp\u003eNot partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e5.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e4.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajority\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eSTEM\u003c/p\u003e\n \u003cp\u003eNon-STEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.018\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of subjects\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;3 subjects\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4 subjects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e4.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e4.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e4.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003cp\u003e3.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eThe Mann-Whitney U test, \u003csup\u003e2\u003c/sup\u003eKruskal-Wallis test\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDirect and indirect effects of the hypothesis model (n\u0026thinsp;=\u0026thinsp;224)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; (SE)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ez\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% LLCI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% ULCI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eDirect Effects\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSE \u0026rarr; WB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.002 (0.067)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSE \u0026rarr; JS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.025 (0.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRE \u0026rarr; WB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.127 (0.078)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRE \u0026rarr; JS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.007 (0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOP \u0026rarr; WB\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.175 (0.069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOP \u0026rarr; JS\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.193 (0.082)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHO \u0026rarr; WB\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.233 (0.072)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHO \u0026rarr; JS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.094 (0.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJS \u0026rarr; WB\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.296 (0.055)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndirect Effects\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSE \u0026rarr; JS \u0026rarr; WB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007 (0.024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRE \u0026rarr; JS \u0026rarr; WB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.002 (0.028)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOP \u0026rarr; JS \u0026rarr; WB\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.057 (0.027)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHO \u0026rarr; JS \u0026rarr; WB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.028 (0.026)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviations: SE: Self-efficacy, RE: Resilience, OP: Optimism, HO: Hope, JS: Job satisfaction, WB: Well-being.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-social-science-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diss","sideBox":"Learn more about [Discover Social Science and Health](https://www.springer.com/journal/44155)","snPcode":"","submissionUrl":"","title":"Discover Social Science and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Conservation of Resources theory, psychological capital, optimism, hope, job satisfaction, well-being, university lecturers, path analysis","lastPublishedDoi":"10.21203/rs.3.rs-7520312/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7520312/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eGrounded in Conservation of Resources (COR) theory, this study examines how future-oriented personal resources from psychological capital (optimism and hope) relate to university lecturers' well-being and whether their job satisfaction functions as a conditional resource linking these personal resources to the outcomes\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional survey was administered to 224 Vietnamese university lecturers. Participants completed validated measures of psychological capital\u0026rsquo;s components (optimism, hope, self-efficacy, resilience), job satisfaction, and overall well-being. Path analysis with 5000 resampling bootstraps was used to test direct and mediating relationships.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eJob satisfaction showed a strong positive association with well-being (β\u0026thinsp;=\u0026thinsp;0.296, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Optimism predicted both job satisfaction (β\u0026thinsp;=\u0026thinsp;0.193, p\u0026thinsp;=\u0026thinsp;.018) and well-being (β\u0026thinsp;=\u0026thinsp;0.175, p\u0026thinsp;=\u0026thinsp;0.011), yielding a significant indirect effect on well-being through job satisfaction (β\u0026thinsp;=\u0026thinsp;0.057, p\u0026thinsp;=\u0026thinsp;0.031). Hope had a significant direct effect on well-being (β\u0026thinsp;=\u0026thinsp;0.233, p\u0026thinsp;=\u0026thinsp;0.001) but was not predicted to job satisfaction. Self-efficacy and resilience were not significant predictors of either outcome.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eFindings clarify two pathways in accordance with COR among university lecturers, including a context-appraisal pathway in which optimism translates into greater job satisfaction and, subsequently, higher well-being, and a goal-navigation pathway in which hope directly enhances well-being independent of job evaluations.\u003c/p\u003e","manuscriptTitle":"From Psychological Capital to Well-being: Job Satisfaction as a Mediator among University Lecturers in Vietnam","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 07:15:29","doi":"10.21203/rs.3.rs-7520312/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-15T13:23:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T03:28:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T14:32:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149727710768248865768724521342444047095","date":"2025-09-22T09:47:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260494228087697868545615686376074951344","date":"2025-09-18T08:07:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T07:46:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-11T04:59:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T02:50:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-05T02:49:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Social Science and Health","date":"2025-09-02T17:55:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-social-science-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diss","sideBox":"Learn more about [Discover Social Science and Health](https://www.springer.com/journal/44155)","snPcode":"","submissionUrl":"","title":"Discover Social Science and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f01569f2-cab0-4354-a622-2d150d3b310c","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T17:23:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 07:15:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7520312","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7520312","identity":"rs-7520312","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}