Investigating the Mechanisms by Expectation Discrepancies in Alternative Employment Contexts Affect College Students’ Mental Health: The Multilevel Roles of Self-Efficacy and Social Support

Investigating the Mechanisms by Expectation Discrepancies in Alternative Employment Contexts Affect College Students’ Mental Health: The Multilevel Roles of Self-Efficacy and Social Support | 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 Investigating the Mechanisms by Expectation Discrepancies in Alternative Employment Contexts Affect College Students’ Mental Health: The Multilevel Roles of Self-Efficacy and Social Support Huihua Luo, Zhonghua Yao, Kexin Ren, Qi Liu, wen Hu, Xinci Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6504313/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background. Grounded in Social Cognitive Career Theory researchgate, this study introduces “expectation discrepancy” into alternative employment contexts and develops a mediated–moderated model to explore the mechanisms by which the gap between college students’ employment expectations and reality affects mental health. Methods. A total of 289 valid responses were collected via an online questionnaire, and structural equation modeling (SEM) along with hierarchical regression analyses were employed to test the pathways involving expectation discrepancy, self‑efficacy, and social support. Results. The results show that expectation discrepancy negatively predicts mental health while positively predicting self‑efficacy; self‑efficacy partially mediates the relationship between expectation discrepancy and mental health; and social support significantly and positively moderates the effect of expectation discrepancy on self‑efficacy, further moderating the effect. Conclusion/Implications. This study’s innovation lies in constructing and validating a mediated–moderated model based on SCCT, providing empirical evidence to inform university career guidance, psychological intervention strategies, and related government policy‑making. Alternative employment Expectation discrepancy Self- efficacy Mental health Figures Figure 1 1 Introduction As social and economic structures transform and uncertainties intertwine in the labor market, the path to employment for college graduates has become increasingly arduous. According to the latest data, the number of university graduates in China rose to 11.58 million in 2023 [ 1 ]. Faced with such a vast pool of job seekers, the capacity of traditional fulltime positions is nearing its limit and cannot meet the growing employment demand. Consequently, an increasing number of graduates are exploring diversified employment pathways, giving rise to alternative employment models. Alternative employment refers to incomegenerating work outside of conventional fulltime roles—such as freelancing, gigeconomy tasks, platformbased jobs, and temporary contracts. Although these emerging modes of work can alleviate shortterm job pressure, they often lack standardized procedures, exhibit low stability, and suffer from insufficient socialsecurity protections [2]. The absence of occupational security, challenges in achieving work–life balance, and uncertainty about future career development present complex, farreaching impacts on graduates’ psychological wellbeing. However, university careerguidance systems remain primarily designed around traditional employment pathways, with support measures for alternative employment forms being relatively insufficient and lagging behind [3]. In the context of global economic volatility and the significant transformations and restructuring of the job market in the aftermath of the COVID-19 pandemic, an indepth exploration and understanding of college students’ mental health within alternative employment contexts is particularly crucial [4]. “Expectation discrepancy” refers to the state in which an individual’s subjective expectations about work or career differ from objective reality [ 5 ]. In the workplace, when one’s occupational role, job duties, or promotion prospects fail to align with initial expectations, a strong sense of loss and frustration arises [ 6 ]. Such negative experiences often lead to job burnout, decreased job satisfaction, and mental health problems such as anxiety and depression. As early as the 2000s, largescale surveys found that gaps between work expectations and actual conditions—or job uncertainty—are closely linked to deteriorating mental health [ 7 , 8 ]. For example, Lazarus and Folkman’s stresscoping theory indicates that individuals facing occupational instability are prone to negative emotions [9]; additionally, the expansion of higher education and intensified employment competition have increased college students’ psychological stress and adaptation difficulties[10,11]. A review of existing literature shows extensive examination of variables like job instability and flexible employment [12] on mental health, yet few studies have treated “expectation discrepancy”—the deviation between one’s subjective career or joboutcome expectations and reality—as an independent variable for systematic measurement and indepth analysis. Moreover, current research explaining the relationship between expectation discrepancy and mental health focuses mainly on employment stability, job security, and resultant anxiety or depression within traditional employment models [13]. However, these studies—largely based on stable organizational settings—cannot fully account for the mechanisms of expectation gaps in highly mobile, uncertain alternative employment contexts. Furthermore, research remains insufficient on how the gap between employment expectations and reality in alternative employment scenarios affects college students’ mental health. This gap not only limits understanding of the underlying mechanisms of mental health issues in alternative employment but also impedes the development of targeted intervention strategies by universities and governments. Self-efficacy refers to an individual's belief in their capability to successfully perform a specific task or handle environmental challenges [ 14 ]. In the occupational context, "occupational self-efficacy" serves as a significant manifestation of self-efficacy, reflecting an individual's proactivity and adaptability when facing job changes and pressures [ 15 ]. Individuals with higher self-efficacy are more likely to adjust themselves or their environment to achieve "dynamic adaptation" when encountering role conflicts or resource shortages at work, thereby mitigating the negative emotional and psychological impacts of expectation discrepancies [ 16 ]. High self-efficacy enables individuals to cope more positively with workplace challenges and maintain a higher level of mental health [ 17 ]. Moreover, Bandura and other scholars have highlighted the crucial role of self-efficacy in alleviating occupational stress [ 18 , 19 ]. Therefore, we propose that self-efficacy may mediate the relationship between expectation discrepancies and mental health; however, the specific dynamic processes and boundary conditions of this mechanism remain unclear. Further empirical research is needed to verify how expectation discrepancies influence individual self-efficacy and, consequently, lead to psychological issues such as anxiety and depression.​ Social support typically encompasses assistance and resources provided by family members, colleagues, supervisors, or broader community networks [ 20 ]. This support can manifest as emotional care and understanding, tangible material aid, or informational resources [ 21 ]. A high level of social support not only directly enhances individuals' psychological safety and well-being but also indirectly mitigates the adverse effects of expectation discrepancies on mental health by bolstering self-efficacy [ 21 , 22 ].​When individuals encounter discrepancies in career expectations, timely external support and guidance can facilitate the development of positive coping strategies, thereby reducing stress levels and maintaining psychological equilibrium. Specifically, when employees perceive high job demands, adequate support from colleagues or supervisors can buffer the decline in self-efficacy, leading to better mental health outcomes. In the context of alternative employment, university students facing expectation discrepancies may experience diminished self-efficacy; however, active support from family, peers, and educational institutions can effectively moderate these negative impacts, thereby alleviating potential harm to their mental health. This study parallels the metaverse gigwork selfefficacy model of Khan et al. [23] in employing a mediated–moderated design, yet it differs markedly in both its subjects and context. Whereas Khan et al. concentrate on occupational isolation within virtual environments, our investigation addresses alternative employment among recent university graduates in realworld settings, thereby offering greater practical value for policy makers and highereducation institutions. Furthermore, the Navigating the Gig Economy team [24] confirmed a positive effect of selfefficacy on platform workers’ psychological wellbeing but did not explore the mechanism of expectation–reality discrepancy nor consider the moderating influence of social support. By contrast, our study articulates a pathway of “expectation discrepancy → selfefficacy → mental health,” revealing the mediating role of selfefficacy under mismatched expectations and introducing social support as a boundary condition, thus extending selfefficacy theory to highuncertainty employment contexts. Finally, research in BMC Psychology [25] demonstrates that algorithmic control mechanisms can affect psychological and behavioral outcomes via emotional mediation, but its focus is on work engagement. We instead concentrate on mental health outcomes and replace “flow experience” or “occupational isolation” with social support as the moderating variable, aligning the model more closely with the actual support networks of university students. In doing so, we enrich Social Cognitive Career Theory (SCCT) by elaborating how environmental resources regulate its processes. On this basis, the present study aims to develop and validate a measurement instrument specifically designed to assess “expectation discrepancy,” thereby precisely delineating the gap between individuals’ subjective expectations and their actual work or career outcomes. Furthermore, we will systematically examine the mediating role of selfefficacy in the relationship between expectation discrepancy and mental health using structural equation modeling (SEM) and related statistical methods, thus uncovering the internal transmission mechanisms. The study will clarify how individuals can buffer the adverse psychological effects of expectation discrepancy by regulating their selfefficacy. In addition, social support—operationalized at the family, colleague, and organizational levels—will be introduced into our model as a moderating variable to explore how such support modulates the indirect effects of expectation discrepancy on mental health. The findings are expected to provide strategic guidance for psychological adjustment among university graduates, offer empirical foundations for future employment market management and policy formulation, and furnish practitioners with targeted intervention recommendations(See Fig. 1 ). 2 Theoretical foundations and research hypotheses 2.1 Theoretical foundations Social Cognitive Career Theory is a career development framework grounded in Bandura’s social cognitive theory, first articulated by Lent, Brown, and colleagues in 1994 and elaborated in subsequent research. It underscores the pivotal roles of selfefficacy, outcome expectations, and career goals in shaping career choice, careerrelated behaviors, and occupational adjustment [ 26 , 2 7].The theory posits that individuals’ confidence in executing occupational tasks (selfefficacy) and their anticipated consequences of task performance (outcome expectations) jointly influence their career behaviors, guiding action through the formulation of concrete goals [28].Furthermore,Social Cognitive Career Theory highlights the impact of contextual factors—such as social support from family, educational institutions, peers, and organizational settings—on career development. These environmental resources both foster the formation of selfefficacy and moderate individuals’ coping strategies when confronting workrelated stress and uncertainty [29].Moreover, Social Cognitive Career Theory advocates a dynamic triadic reciprocal interaction among personal attributes, behavioral choices, and environmental contexts. In this view, individual traits, behavioral enactments, and external conditions continuously interact and provide reciprocal feedback, jointly shaping career trajectories and psychological adaptation [26].This theoretical framework offers a systematic basis for understanding the complex mediating and moderating mechanisms among these variables and has been widely applied in vocational psychology and organizational behavior research. The primary focus of this study is to investigate the impact of "expectation-reality discrepancy" on the mental health of university students, examining the mediating role of self-efficacy and the moderating effect of social support within this process. Grounded in the Social Cognitive Career Theory, the model posits that discrepancies between anticipated and actual employment scenarios can influence individuals' self-efficacy, thereby altering their coping strategies and psychological states. Individuals with higher levels of self-efficacy are more likely to adopt proactive coping mechanisms to mitigate the adverse effects of such mismatches [ 30 ]. Furthermore, Social Cognitive Career Theory emphasizes the significance of environmental factors, such as support from family, colleagues, supervisors, and the broader community, in enhancing self-efficacy and improving mental health outcomes. Social support not only directly bolsters psychological security and well-being but also indirectly buffers the negative impact of expectation-reality discrepancies on mental health by strengthening self-efficacy [ 31 ]. Accordingly, this research employs Social Cognitive Career Theory as its theoretical foundation, measuring the effects of employment expectation-reality gaps, self-efficacy, and social support levels on the mental health of university students in alternative employment contexts. A structural equation model is constructed to validate the mediating effect of self-efficacy and the moderating role of social support, thereby providing empirical evidence and targeted intervention strategies for higher education institutions and relevant policymakers. 2.2 Research hypotheses 2.2.1 Expectation-reality discrepancy and self-efficacy Expectation discrepancy refers to the state in which there is a gap between an individual's actual experience and their prior expectations. When actual outcomes fall short of expectations, this discrepancy can lead to cognitive dissonance and emotional fluctuations, thereby influencing behavioral decisions and motivational drive. The characteristics of expectation discrepancy include high subjectivity, strong contextual dependence, and dynamic variability. It can both facilitate behavioral adjustments and result in negative emotions and dissatisfaction [ 32 , 33 ].​ Self-efficacy pertains to an individual's belief in their ability to handle challenges, adjust behaviors, and achieve goals within a professional context [ 34 ]. This construct reflects not only confidence and resilience in the face of job changes, skill updates, and environmental shifts but also proactive learning, continuous adaptation, and self-motivation.​ We posit that expectation discrepancy has a positive effect on self-efficacy. First, when individuals recognize a reasonable gap between their expectations and reality, this seemingly contradictory state can act as a catalyst for growth. Psychological research indicates that a moderate expectation gap serves as a "capability upgrade signal" from the brain, prompting individuals to proactively adjust strategies and enhance skills [ 35 ].​ Second, according to social cognitive theory, for instance, university students seeking employment may discover that the requirements of their desired positions slightly exceed their current competencies. In response, they often voluntarily engage in industry training, seek internship opportunities, or even replan their career paths. When students encounter discrepancies between their career expectations and actual experiences, they tend to view this inconsistency as an opportunity for self-improvement and skill acquisition. Through self-reflection, strategic adjustments, and goal restructuring, they address deficiencies, thereby increase their confidence in future success [ 14 ].​ Furthermore, moderate expectation discrepancies encourage individuals to learn from others' experiences during social interactions, obtain positive feedback, and reconstruct self-perceptions and capability expectations. This process contributes to improved social adaptability [ 36 ].​Based on the above discussion, we propose the following hypothesis:​ H1: Expectation discrepancy positively influences self-efficacy. 2.2.2 Expectation discrepancies and mental health Mental health refers to an individual's state of balance, harmony, and adaptability in cognitive, emotional, and behavioral aspects [ 37 ]. It is characterized not only by emotional stability, self-acceptance, healthy interpersonal relationships, and strong stress-coping abilities but also by having clear life goals and a sense of meaning [ 38 ].​ This study posits that expectation incongruence negatively impacts mental health. Emotionally, when there is a significant discrepancy between a university student's expectations and reality, it may lead to feelings of frustration, anxiety, and disappointment. Without sufficient external support, these emotions can accumulate over time, potentially leading to more severe psychological distress [ 39 ]. Cognitively, expectation incongruence can trigger self-doubt and self-denial. In alternative employment environments, frequent encounters with uncertainty and setbacks may cause individuals to form negative evaluations of their abilities and career prospects [ 30 ]. Behaviorally, some individuals may choose to avoid or abandon their original career goals, thereby diminishing their work motivation and potential for professional development, ultimately leading to a decline in overall mental health [ 40 ]. According to the SCCT, when individuals' expectations for future career development are inconsistent with their actual experiences, this can lead to reduced self-efficacy and outcome expectations, resulting in frustration and emotional disturbances. Such expectation discrepancies may cause cognitive dissonance, adversely affecting career decision-making and self-regulation. Over time, these effects can accumulate, potentially leading to psychological issues such as anxiety and depression, thereby negatively impacting overall mental health [ 41 ]. When individuals face a gap between expectations and reality without adequate positive feedback and effective support, their psychological stress may intensify, ultimately harming their mental well-being [ 34 ]. Surveys conducted among college students have revealed a significant positive correlation between disparities in expectations versus reality and the deterioration of mental health [ 42 ]. Therefore, for college students undergoing the transition to employment, if their expectations significantly exceed reality, they are more likely to experience severe impacts on emotional, cognitive, and behavioral levels, increasing the risk of psychological health issues such as anxiety, depression, and job burnout. Based on the above discussion, we propose the following hypothesis:​ H2: Expectation discrepancies negatively affect mental health. 2.2.3 Selfefficacy and mental health We posit that selfefficacy has a positive effect on mental health. Specifically, individuals who hold strong confidence in their own abilities tend to display a form of “psychological resilience” when confronted with challenges—much like a spring that can both bear heavy loads and then return to its original shape under pressure. This characteristic enables highselfefficacy individuals, when facing employment setbacks, to attribute failure to changeable factors (e.g., shifts in the industry environment or lack of experience) rather than to a wholesale negation of their own worth. Such an attribution pattern operates like a precise riskassessment system, helping individuals distinguish between temporary difficulties and permanent defects, thereby preventing the magnification of isolated setbacks into global failures. Luszczynska et al. [43], in a longitudinal study,reported that students with high selfefficacy were more inclined, when confronted with jobmarket competition, to plan their career trajectories and actively seek internship opportunities as a means of alleviating anxiety. Moreover, social cognitive theory suggests that individuals with high selfefficacy favor proactive problemsolving strategies over avoidance or passive coping, a behavioral style that significantly reduces psychological risks such as anxiety and depression [34]. Judge and Bono’s (2001) metaanalysis further confirmed a significant positive correlation between selfefficacy and mental health indicators (e.g., subjective wellbeing and emotional stability), demonstrating that selfefficacy’s predictive effect on mental health is independent of other personality traits [44]. Therefore, we propose the following hypothesis: H3: Selfefficacy positively influences mental health. 2.2.4 The mediating role of selfefficacy We propose that selfefficacy mediates the relationship between expectation–reality discrepancies and mental health. Specifically, in the context of university students’ engagement in alternative employment, individuals may face a gap between their anticipated and actual career prospects, remuneration, and development opportunities. This gap can elicit anxiety, depression, and other negative emotional responses, thereby undermining psychological wellbeing. Selfefficacy—defined as one’s confidence in successfully adapting to a new employment environment—has been empirically shown to exert a positive influence. According to selfefficacy theory, high selfefficacy bolsters resilience when confronting challenges and effectively alleviates the negative emotions arising from expectation–reality mismatches. Conversely, excessively high or unrealistic expectations in alternative employment contexts may erode selfefficacy, diminish problemsolving and stresscoping capacities, and consequently impair mental health. Prior research indicates that enhancing selfefficacy can mitigate the adverse effects of expectation–reality discrepancies[45,46]. Second, according to Social Cognitive Theory, individuals’ perceptions of their environment (such as discrepancies between expectations and reality) influence their behaviors and psychological states via selfefficacy, defined as one’s belief in one’s own capabilities. When confronted with a gap between employment expectations and actual circumstances, college students’ selfefficacy becomes a critical determinant of mental health: those with high selfefficacy tend to employ active coping strategies, whereas those with low selfefficacy are more susceptible to anxiety or depression [41]. Salami [23], in a study of Nigerian undergraduates, found that career expectation discrepancies not only directly precipitated psychological stress but also indirectly exacerbated negative emotions by undermining selfefficacy (direct effect accounting for 42%, mediating effect accounting for 35%) [47]. In the employment context, misalignment between expectations and reality not only generates immediate psychological dissonance—such as pessimism regarding future career prospects—but also indirectly impairs mental health by eroding selfefficacy, for instance, the belief that one is incapable of performing one’s ideal job. Accordingly, basis of the foregoing discussion, we propose the following hypothesis: H4: Selfefficacy mediates the relationship between expectation–reality discrepancies and mental health. 2.2.5 The moderating role of social support Social support refers to the emotional, informational, instrumental, and appraisal assistance and care that individuals receive from their surrounding social networks (e.g., family, friends, colleagues, schools, and communities) when confronted with stressors, challenges, or difficulties [ 31 ]. This construct has been extensively examined in the field of psychology and is considered to play a vital role in stress alleviation, the maintenance of psychological wellbeing, and the enhancement of selfefficacy. The primary dimensions of social support typically include emotional support (e.g., understanding, empathy, and consolation), informational support (e.g., advice and guidance), instrumental support (e.g., tangible aid or provision of resources), and appraisal support (i.e., positive feedback on one’s behaviors). These forms of support can exert a “buffering” effect in stressful situations, thereby mitigating the erosive impact of negative emotions on mental health [ 48 , 4 9]. We propose that social support positively moderates the effect of expectation–reality discrepancy on selfefficacy. Specifically, social support—which comprises emotional, informational, and resource assistance from family, friends, educational institutions, and social agencies—can help individuals reframe their perceptions of the employment environment and thus mitigate negative appraisals of the gap between expectations and reality [50]. When undergraduates confront alternative employment options, higher levels of social support allow them to obtain more career information, skills training, and emotional reassurance, thereby effectively weakening the adverse impact of expectation–reality discrepancy on selfefficacy [51]. Moreover, social support not only directly promotes enhancements in selfefficacy but also indirectly fosters psychological wellbeing by improving individuals’ outlook on their career prospects. Therefore, in the context of alternative employment, high levels of social support enable undergraduates to more readily embrace realworld challenges and sustain elevated selfefficacy. Second, social cognitive theory posits that individuals’ assessments of their capabilities and their subsequent behavioral choices arise from the dynamic interaction of environmental factors, personal experiences, and cognitive processes [ 31 ]. In alternative employment settings, expectation discrepancies—serving as an environmental stressor—can provoke negative emotions and selfdoubt, thereby eroding one’s sense of selfefficacy [50]. However, social support, as an external positive motivator, can moderate this cognitive appraisal process. Alleviating the anxiety and uncertainty induced by environmental pressures helps individuals maintain confidence in their adaptive capacities when confronted with employment uncertainty. High levels of emotional and informational support enable students to adopt a more balanced view of both the risks and opportunities in the job market, reconstruct positive selfefficacy appraisals, and thus buffer the adverse effects of expectation discrepancies. Moreover, from a social cognitive perspective, social support enhances mechanisms of vicarious learning and social comparison: observing others successfully navigate employment challenges strengthens one’s own positive outcome expectations.Therefore, we propose the following hypothesis: H5: Social support positively moderates the effect of expectation discrepancies on selfefficacy. 3 Research design 3.1 Procedure and sample Target population. The target population for this study comprises graduates who have opted for alternative forms of employment. Data collection. Data were collected in three sequential stages.First ,Anhui Province was selected as the primary sampling unit on the basis of geographic balance, economic-development gradient (provincial capitals, industrial cities, and major agricultural centers), and population size. This choice both facilitated logistical convenience for our onsite team and, by sampling a representative province, provided an effective reflection of labor and employment conditions in central China.Second we conducted stratified sampling across cities, applying unequalprobability sampling with replacement to identify the sampled districts and counties.Third to accommodate fieldsurvey challenges and humanresource constraints—and to secure an adequate sample within a limited timeframe—we employed simple random sampling at fixed survey stations established in areas with high concentrations of alternativeemployment participants (e.g., central business districts, industrialpark peripheries, and township markets), conducting random intercept interviews. Data Processing. The datacleaning protocol included removing invalid questionnaires completed in less than the minimum threshold time determined by the pilot study.Excluding records not meeting the target criteria (e.g., respondents aged < 18 years or with occupation ≠ “employed”) are excluded via conditional filters.Eliminating aberrant responses exhibiting fixed patterns (e.g., consecutive identical choices or wavelike sequences) is indicative of careless completion.Deleting questionnaires submitted by nontarget respondents owing to link dissemination beyond the intended population. 3.2 Measurement of variables All the items in the scales used in this study, except for control variables, were measured using a 5-point Likert scale.​ (1) Expectation incongruence Was measured via the 9item Perceived overqualification scale (SPOQ) developed by Maynard et al. (2006) [52]. In the present study, the Cronbach's alpha coefficient for this scale was 0.834.​ (2) Self-Efficacy Was measured via the 10item General selfefficacy scale (GSES) developed by Schwarzer et al. (1995) [53]. In the present study, the scale demonstrated a Cronbach’s alpha of 0.866. (3) Social Support Was measured via the 12item Multidimensional scale of perceived social support (MSPSS) developed by Zimet et al. (1988) [54]. In the present study, the scale demonstrated a Cronbach’s alpha of 0.879. (4) Mental health Was measured via the 17item Utrecht Work Engagement Scale (UWES) developed by Schaufeli et al. (2006) [55]. In the present study, the scale demonstrated a Cronbach’s alpha of 0.937. In this study, gender, highest educational attainment, years of work experience [ 56 ], and industry type [ 57 ] were included as control variables. Years of work experience reflect an individual's career stage; those with more extensive experience often possess greater professional confidence and adaptability. Industry type represents different alternative employment models (e.g., remote education, content creation, platform-based gig economy), which vary in task characteristics, social networks, and support mechanisms, potentially influencing levels of social support and mental health. Controlling for these variables helps eliminate sample heterogeneity, thereby allowing for a more accurate examination of the relationships among expectation incongruence, self-efficacy, and mental health.​ 4 Data analysis 4.1 Confirmatory factor analysis To further assess the discriminant validity among the measured variables, this study conducted a confirmatory factor analysis (CFA) viaAMOS 24.0. The analysis focused on four latent constructs: expectation inconsistency (EI), self-efficacy (SE), social support (SS), and mental health (MH). Four competing models were specified for comparison: (1) a four-factor model, where each latent construct was modeled separately; (2) a three-factor model, combining SE and SS into a single factor; (3) a two-factor model, merging EI, SE, and SS into one factor; and (4) a one-factor model, integrating all items into a single latent construct. The fit indices for each model are presented in Table 1 . Among the models, the four-factor model demonstrated the best fit, with χ²/df = 1.608, CFI = 0.904, TLI = 0.894, RMSEA = 0.046, all meeting the commonly accepted thresholds for good model fit (i.e., CFI ≥ 0.90, TLI ≥ 0.90, RMSEA ≤ 0.06, SRMR ≤ 0.08) [ 58 ]. This model significantly outperforms the alternative models, indicating that the four constructs are empirically distinct and possess satisfactory discriminant validity. Table 1 Results of confirmatory factor analysis Model χ 2 df χ 2 /df CFI TLI RMSEA SRMR Four-factor model: EI, SE, SS, MH 1632.205 1015 1.608 0.904 0.894 0.046 0.0532 Three-factor model: EI, SE + SS,MH 2615.591 1077 2.429 0.761 0.75 0.07 0.0679 Two-factor model: EI + SE + SS, MH 3208.818 1079 2.974 0.67 0.655 0.083 0.0943 One-factor model: EI + SE + SS + MH 5036.951 1080 4.664 0.386 0.359 0.113 0.172 Note: EI = Expectation inconsistency, SE = Self-efficacy, SS = Social support, MH = Mental health. 4.2 Descriptive statistics and correlation results As shown in Table Table 2 , expectation discrepancy is significantly negatively correlated with mental health (r = -0.182, p < 0.01) and significantly positively correlated with self-efficacy (r = 0.233, p < 0.001). Additionally, self-efficacy was significantly positively correlated with mental health (r = 0.617, p < 0.01). These results provide empirical support for Hypotheses 1 to 3. The findings are consistent with the theoretical expectations of this study and offer preliminary support for the proposed hypotheses. Table 2 Means, standard deviations, and correlations of the variables Variable M SD 1 2 3 4 5 6 7 8 1. Gender 1.58 0.5 1 2. Highest Educational Level 2.22 0.51 − .118* 1 3. Years of Work Experience 2.04 0.67 − .181** -0.005 1 4. Industry Type 3 1.92 -0.018 0 -0.046 1 5. Expectation Discrepancy 3.54 0.64 − .139* 0.059 0.054 − .119* 1 6. Self-Efficacy 3.5 0.64 -0.099 0.091 0.061 0.026 .233** 1 7. Social Support 3.63 0.66 -0.048 0.021 0.086 -0.085 .233** .617** 1 8. Mental Health 2.64 0.77 -0.074 0.107 − .133* 0.066 − .182** .128* .135* 1 Note: N = 289,p < 0.05, p < 0.01, p < 0.001.The same notation applies hereinafter. 4.3 Hypothesis testing As shown in Model 2 and Model 4 of Table Table 3 , expectation discrepancy is positively associated with self-efficacy (β = 0.226, p < 0.001) and negatively associated with mental health (β = -0.192, p < 0.01), thus supporting Hypotheses 1 and 2. Model 6 further indicates that expectation discrepancy is positively related to psychological distress (β = 0.12, p < 0.05), supporting Hypothesis 3. According to Model 5, when self-efficacy is included in the regression model, expectation discrepancy remains negatively associated with mental health (β = -0.231, p < 0.001). These results suggest that psychological safety partially mediates the relationship between leadership style (i.e., humble leadership and abusive supervision) and knowledge hiding behavior. Moreover, we conducted a bootstrap test to further validate this mediating effect. The indirect effect was 0.047, with a 95% confidence interval of [0.008, 0.081], which does not include zero (see Table Table 4 ). Therefore, Hypothesis 4 is supported. Table 3 Hierarchical regression results testing the mediating effect of self-efficacy Variable Self-Efficacy Mental Health Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Gender -0.08 -0.051 -0.088 -0.114 -0.105 -0.079 Education Level 0.082 0.072 0.096 0.104 0.092 0.086 Work Tenure 0.048 0.042 -0.146* -0.141* -0.148** -0.152* Industry Type 0.027 0.054 0.057 0.034 0.025 0.054 Expectation Discrepancy 0.226*** -0.192** -0.231*** Self-Efficacy 0.171** 0.12* R² 0.019 0.068 0.04 0.076 0.103 0.054 Adjusted R² 0.005 0.052 0.026 0.059 0.084 0.037 F 1.377 4.144*** 2.957* 4.626*** 5.384*** 3.233** Table 4 Decomposition of total, direct, and indirect effects (bootstrap = 5000) Effect Type Effect SE 95% CI Lower (BootLLCI) 95% CI Upper (BootULCI) Total Effect -0.234 0.071 -0.373 -0.094 Direct Effect -0.281 0.072 -0.422 -0.14 Indirect Effect 0.047 0.022 0.008 0.081 This study further examined the moderating role of social support by conducting hierarchical regression analyses via SPSS 25.0. Prior to testing, both expectation discrepancy and social support were meancentered. The relevant regression results are shown in Table 5 . As indicated by Model 9 in Table 5 , the interaction between expectation discrepancy and social support positively predicts selfefficacy (β = 0.163, p < 0.01), thereby supporting Hypothesis 5 Table 5 Hierarchical regression results: moderating effect analysis Predictors SelfEfficacy Model 7 Model 8 Model 9 Gender -0.051 -0.048 -0.033 Highest education/degree 0.072 0.067 0.059 Years of work experience 0.042 0 0.01 Industry type 0.054 0.087 0.088 Expectation discrepancy 0.226*** 0.093 0.093* Social support 0.599*** 0.576*** Expectation discrepancy × Social support 0.163** R² 0.068 0.405 0.416 Adjusted R² 0.052 0.392 0.402 F 4.144** 31.96*** 28.635*** This study employed a bootstrap procedure with 5,000 resamples and a 95% confidence interval to examine the moderated mediation effect of organizational justice on resistance to change; the results are presented in Table Table 6 . As shown in Table 6 , social support significantly moderates the indirect effect of expectation incongruence on mental health via selfefficacy: the indirect effect differs between high and low levels of social support, and its 95% confidence interval does not include zero [0.0009, 0.0799], indicating that social support strengthens the mediating role of selfefficacy in the relationship between expectation incongruence and mental health. Table 6 Results of the moderated mediation effect analysis (bootstrap = 5,000) Moderator Level Effect SE 95% CI Lower (BootLLCI) 95% CI Upper (BootULCI) Mean − 1 SD 0.0398 0.0208 0.0051 0.0863 Mean 0.0194 0.0138 0.0062 0.048 Mean + 1 SD 0.0009 0.0181 0.0291 0.044 Moderated indirect effect 0.0307 0.0207 0.0009 0.0799 Discussion Grounded in Social Cognitive Theory and situated within the context of alternative employment among university graduates, this study examined how expectation incongruence influences mental health and the mechanisms through which this effect unfolds. Consistent with our hypotheses, greater discrepancy between career expectations and reality was associated with poorer mental health outcomes. Selfefficacy emerged as a key mediator: when students perceived a mismatch between their expectations and actual work experiences, their belief in their ability to manage career challenges diminished, which in turn exacerbated psychological distress. Moreover, social support functioned as a positive moderator of the expectation–selfefficacy link. Specifically, under high levels of support from family, peers, and institutions, the adverse impact of expectation incongruence on selfefficacy was attenuated, thereby buffering against downstream declines in mental health. The moderated mediation model thus underscores the dual importance of individual cognitive resources and contextual social resources in shaping adaptive responses to employment transitions. By integrating expectation incongruence, selfefficacy, and social support into a unified framework, our findings extend prior work in vocational psychology and highlight dynamic processes of cognitive appraisal and social buffering in the face of nontraditional career pathways. Limitations and directions for future research Despite its contributions, this study has several limitations that suggest avenues for further inquiry. Crosssectional design. Because data were collected at a single time point, causal inferences regarding the temporal ordering of expectation incongruence, selfefficacy, and mental health remain tentative. Future research should employ longitudinal or experimental designs to trace how these relationships evolve over time and to establish stronger evidence of causality. Selfreport measures. Although we used wellvalidated scales, reliance on selfreports may introduce common method variance, social desirability bias, and recall inaccuracies. Subsequent studies could incorporate multisource assessments (e.g., behavioral observations, peer or supervisor ratings) to enhance measurement objectivity and reduce potential bias. Unmeasured confounds. Mental health in alternative employment settings is influenced by myriad factors—such as socioeconomic background, financial stress, and family dynamics—that were not exhaustively controlled here. Future work should include a broader set of covariates or apply propensityscore matching to better isolate the unique effects of expectation incongruence, selfefficacy, and social support. Conclusions This study advances our understanding of university graduates’ psychological adaptation to alternative employment by demonstrating (a) a direct negative effect of expectation incongruence on mental health, (b) a mediating role of selfefficacy in this relationship, and (c) a buffering role of social support both on the expectation–selfefficacy link and on the overall indirect effect. Theoretically, our dynamic adjustment model enriches Social Cognitive Career Theory by foregrounding expectation gaps as a pivotal driver of careerrelated wellbeing. Practically, the findings underscore the need for highereducation institutions, career services, and policymakers to help students set realistic expectations, bolster their selfefficacy, and cultivate robust support networks. Such interventions hold promise for mitigating the psychological risks associated with nontraditional employment trajectories and promoting healthier career transitions. Declarations Ethics declarations Ethics approval and consent to participate All participants in the study provided informed consent and agreed to the publication of this paper. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This study was funded by Open Research Project of Anhui Engineering Research Center for Intelligent Computing and Information Innovation, Fuyang Normal University(Grant number ICII202507). Author Contribution Conceptualization:HH L; Methodology, formal analysis and investigation: HH L, ZH Y ;Writing—original draft:HH L, Q L, XC L, WH, KX R; Writing—review and editing: HH L.All authors read and approved the final manuscript. Acknowledgements The authors would like to thank all the participants. 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Relationship of core self‑evaluations traits—self‑esteem, generalized self‑efficacy, locus of control, and emotional stability—with job satisfaction and job performance: A meta‑analysis. Journal of Applied Psychology, 86(1), 80–92. Guarnaccia, C., Scrima, F., & Civilleri, A., et al. (2018). The role of occupational self‑efficacy in mediating the effect of job insecurity on work engagement, satisfaction, and general health. Current Psychology, 37, 488–497. Tomas, J. (2021). Occupational self‑efficacy as a mediator in the reciprocal relationship between job demands and mental health complaints: A three‑wave investigation. International Journal of Environmental Research and Public Health, 18(21), Article 11532. Salami, S. O. (2010). Emotional intelligence, self‑efficacy, psychological well‑being and students’ attitudes: Implications for quality education. European Journal of Educational Studies, 2(3), 247–257. Cohen, S. (2004). Social relationships and health. American Psychologist, 59(8), 676–684. Thoits, P. A. (2011). Mechanisms linking social ties and support to physical and mental health. Journal of Health and Social Behavior, 52(2), 145–161. Wang, Z. (2024). A review and prospect of research on factors influencing self‑efficacy. Advances in Psychology, 14(1), 273–278. Geng, C. (2020). Self‑construction, perceived social support, and anxiety among university students. Advances in Psychology, 10(11), 1–9. Maynard, D. C., Joseph, T. A., & Maynard, A. M. (2006). Underemployment, job attitudes, and turnover intentions. Journal of Organizational Behavior, 27(4), 509–536. Schwarzer, R., & Jerusalem, M. (1995). Generalized self‑efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures in Health Psychology: A User’s Portfolio (pp. 35–37). Causal and Control Beliefs. Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The Multidimensional Scale of Perceived Social Support. Journal of Personality Assessment, 52(1), 30–41. Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross‑national study. Educational and Psychological Measurement, 66(4), 701–716. Wihler, A., Meurs, J. A., & Kramer, J., et al. (2021). Does job tenure increase human capital? How general mental ability and low job stress jointly augment the job tenure–job performance relationship. Nova Science Publishers. Laditka, J. N., Laditka, S. B., & Arif, A. A., et al. (2023). Psychological distress is more common in some occupations and increases with job tenure: A 37‑year panel study in the United States. BMC Psychology, 11(1), Article 95. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6504313","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":460205251,"identity":"e81a3c38-b785-475c-9c01-ec489e52c969","order_by":0,"name":"Huihua Luo","email":"","orcid":"","institution":"Fu Yang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Huihua","middleName":"","lastName":"Luo","suffix":""},{"id":460205253,"identity":"c6dfe099-9bf4-4f12-8b80-8ff9babc1925","order_by":1,"name":"Zhonghua Yao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYJACZgYDGzt+ZubDD0jQUpCWLNnOlmZAgpYPhxg3nOdRkCBKucHxw4c/FxgcYDY+zMNgwFBjE01Yy5m0BOMZBnf4zA7zHnjAcCwtt4GglgM5Bsk8Bs+YzQ7zJRgwNhwmQsv5NwaHeQwOM25u5jGQIE7LjRzDZpCWDczEapG88SwZqDgtWeIwMJATiPEL3/nkw595/gCjsv/w4QcfamwIa1E4gMxLIKQcBOQJGjoKRsEoGAWjAAC2Vz/MI+qp5AAAAABJRU5ErkJggg==","orcid":"","institution":"Fu Yang Normal University","correspondingAuthor":true,"prefix":"","firstName":"Zhonghua","middleName":"","lastName":"Yao","suffix":""},{"id":460205255,"identity":"e7e52f9a-8274-4eec-9cc8-2f757159dd29","order_by":2,"name":"Kexin Ren","email":"","orcid":"","institution":"Fuyang University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Kexin","middleName":"","lastName":"Ren","suffix":""},{"id":460205259,"identity":"ac1875dc-8300-4123-adbd-8f8d4b001cb4","order_by":3,"name":"Qi Liu","email":"","orcid":"","institution":"Fuyang University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Liu","suffix":""},{"id":460205261,"identity":"1137f5b6-b8ef-4d22-8024-b254dabcff09","order_by":4,"name":"wen Hu","email":"","orcid":"","institution":"Fuyang University of Technology","correspondingAuthor":false,"prefix":"","firstName":"wen","middleName":"","lastName":"Hu","suffix":""},{"id":460205262,"identity":"de380722-fcb2-4ecd-be23-7ccd1f421229","order_by":5,"name":"Xinci Liu","email":"","orcid":"","institution":"Fuyang University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Xinci","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-04-22 12:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6504313/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6504313/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83324966,"identity":"ac1b4532-50a0-4419-95a3-f629cbe558c5","added_by":"auto","created_at":"2025-05-23 06:04:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17697,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6504313/v1/c9404ffe4ab0dd7fe4c6192f.png"},{"id":83325350,"identity":"c60f7faf-49be-4d58-bc15-f0be5bc57758","added_by":"auto","created_at":"2025-05-23 06:12:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1091784,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6504313/v1/4d1f804b-6eb7-467c-9c06-24d008a56b44.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigating the Mechanisms by Expectation Discrepancies in Alternative Employment Contexts Affect College Students’ Mental Health: The Multilevel Roles of Self-Efficacy and Social Support","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAs social and economic structures transform and uncertainties intertwine in the labor market, the path to employment for college graduates has become increasingly arduous. According to the latest data, the number of university graduates in China rose to 11.58\u0026nbsp;million in 2023 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Faced with such a vast pool of job seekers, the capacity of traditional fulltime positions is nearing its limit and cannot meet the growing employment demand. Consequently, an increasing number of graduates are exploring diversified employment pathways, giving rise to alternative employment models. Alternative employment refers to incomegenerating work outside of conventional fulltime roles\u0026mdash;such as freelancing, gigeconomy tasks, platformbased jobs, and temporary contracts. Although these emerging modes of work can alleviate shortterm job pressure, they often lack standardized procedures, exhibit low stability, and suffer from insufficient socialsecurity protections [2]. The absence of occupational security, challenges in achieving work\u0026ndash;life balance, and uncertainty about future career development present complex, farreaching impacts on graduates\u0026rsquo; psychological wellbeing. However, university careerguidance systems remain primarily designed around traditional employment pathways, with support measures for alternative employment forms being relatively insufficient and lagging behind [3]. In the context of global economic volatility and the significant transformations and restructuring of the job market in the aftermath of the COVID-19 pandemic, an indepth exploration and understanding of college students\u0026rsquo; mental health within alternative employment contexts is particularly crucial [4].\u003c/p\u003e \u003cp\u003e\u0026ldquo;Expectation discrepancy\u0026rdquo; refers to the state in which an individual\u0026rsquo;s subjective expectations about work or career differ from objective reality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the workplace, when one\u0026rsquo;s occupational role, job duties, or promotion prospects fail to align with initial expectations, a strong sense of loss and frustration arises [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Such negative experiences often lead to job burnout, decreased job satisfaction, and mental health problems such as anxiety and depression. As early as the 2000s, largescale surveys found that gaps between work expectations and actual conditions\u0026mdash;or job uncertainty\u0026mdash;are closely linked to deteriorating mental health [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For example, Lazarus and Folkman\u0026rsquo;s stresscoping theory indicates that individuals facing occupational instability are prone to negative emotions [9]; additionally, the expansion of higher education and intensified employment competition have increased college students\u0026rsquo; psychological stress and adaptation difficulties[10,11]. A review of existing literature shows extensive examination of variables like job instability and flexible employment [12] on mental health, yet few studies have treated \u0026ldquo;expectation discrepancy\u0026rdquo;\u0026mdash;the deviation between one\u0026rsquo;s subjective career or joboutcome expectations and reality\u0026mdash;as an independent variable for systematic measurement and indepth analysis. Moreover, current research explaining the relationship between expectation discrepancy and mental health focuses mainly on employment stability, job security, and resultant anxiety or depression within traditional employment models [13]. However, these studies\u0026mdash;largely based on stable organizational settings\u0026mdash;cannot fully account for the mechanisms of expectation gaps in highly mobile, uncertain alternative employment contexts. Furthermore, research remains insufficient on how the gap between employment expectations and reality in alternative employment scenarios affects college students\u0026rsquo; mental health. This gap not only limits understanding of the underlying mechanisms of mental health issues in alternative employment but also impedes the development of targeted intervention strategies by universities and governments.\u003c/p\u003e \u003cp\u003eSelf-efficacy refers to an individual's belief in their capability to successfully perform a specific task or handle environmental challenges [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the occupational context, \"occupational self-efficacy\" serves as a significant manifestation of self-efficacy, reflecting an individual's proactivity and adaptability when facing job changes and pressures [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Individuals with higher self-efficacy are more likely to adjust themselves or their environment to achieve \"dynamic adaptation\" when encountering role conflicts or resource shortages at work, thereby mitigating the negative emotional and psychological impacts of expectation discrepancies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. High self-efficacy enables individuals to cope more positively with workplace challenges and maintain a higher level of mental health [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Moreover, Bandura and other scholars have highlighted the crucial role of self-efficacy in alleviating occupational stress [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Therefore, we propose that self-efficacy may mediate the relationship between expectation discrepancies and mental health; however, the specific dynamic processes and boundary conditions of this mechanism remain unclear. Further empirical research is needed to verify how expectation discrepancies influence individual self-efficacy and, consequently, lead to psychological issues such as anxiety and depression.​\u003c/p\u003e \u003cp\u003eSocial support typically encompasses assistance and resources provided by family members, colleagues, supervisors, or broader community networks [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This support can manifest as emotional care and understanding, tangible material aid, or informational resources [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A high level of social support not only directly enhances individuals' psychological safety and well-being but also indirectly mitigates the adverse effects of expectation discrepancies on mental health by bolstering self-efficacy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].​When individuals encounter discrepancies in career expectations, timely external support and guidance can facilitate the development of positive coping strategies, thereby reducing stress levels and maintaining psychological equilibrium. Specifically, when employees perceive high job demands, adequate support from colleagues or supervisors can buffer the decline in self-efficacy, leading to better mental health outcomes. In the context of alternative employment, university students facing expectation discrepancies may experience diminished self-efficacy; however, active support from family, peers, and educational institutions can effectively moderate these negative impacts, thereby alleviating potential harm to their mental health.\u003c/p\u003e \u003cp\u003eThis study parallels the metaverse gigwork selfefficacy model of Khan et al. [23] in employing a mediated\u0026ndash;moderated design, yet it differs markedly in both its subjects and context. Whereas Khan et al. concentrate on occupational isolation within virtual environments, our investigation addresses alternative employment among recent university graduates in realworld settings, thereby offering greater practical value for policy makers and highereducation institutions. Furthermore, the Navigating the Gig Economy team [24] confirmed a positive effect of selfefficacy on platform workers\u0026rsquo; psychological wellbeing but did not explore the mechanism of expectation\u0026ndash;reality discrepancy nor consider the moderating influence of social support. By contrast, our study articulates a pathway of \u0026ldquo;expectation discrepancy \u0026rarr; selfefficacy \u0026rarr; mental health,\u0026rdquo; revealing the mediating role of selfefficacy under mismatched expectations and introducing social support as a boundary condition, thus extending selfefficacy theory to highuncertainty employment contexts. Finally, research in BMC Psychology [25] demonstrates that algorithmic control mechanisms can affect psychological and behavioral outcomes via emotional mediation, but its focus is on work engagement. We instead concentrate on mental health outcomes and replace \u0026ldquo;flow experience\u0026rdquo; or \u0026ldquo;occupational isolation\u0026rdquo; with social support as the moderating variable, aligning the model more closely with the actual support networks of university students. In doing so, we enrich Social Cognitive Career Theory (SCCT) by elaborating how environmental resources regulate its processes.\u003c/p\u003e \u003cp\u003eOn this basis, the present study aims to develop and validate a measurement instrument specifically designed to assess \u0026ldquo;expectation discrepancy,\u0026rdquo; thereby precisely delineating the gap between individuals\u0026rsquo; subjective expectations and their actual work or career outcomes. Furthermore, we will systematically examine the mediating role of selfefficacy in the relationship between expectation discrepancy and mental health using structural equation modeling (SEM) and related statistical methods, thus uncovering the internal transmission mechanisms. The study will clarify how individuals can buffer the adverse psychological effects of expectation discrepancy by regulating their selfefficacy. In addition, social support\u0026mdash;operationalized at the family, colleague, and organizational levels\u0026mdash;will be introduced into our model as a moderating variable to explore how such support modulates the indirect effects of expectation discrepancy on mental health. The findings are expected to provide strategic guidance for psychological adjustment among university graduates, offer empirical foundations for future employment market management and policy formulation, and furnish practitioners with targeted intervention recommendations(See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e"},{"header":"2 Theoretical foundations and research hypotheses","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Theoretical foundations\u003c/h2\u003e \u003cp\u003eSocial Cognitive Career Theory is a career development framework grounded in Bandura\u0026rsquo;s social cognitive theory, first articulated by Lent, Brown, and colleagues in 1994 and elaborated in subsequent research. It underscores the pivotal roles of selfefficacy, outcome expectations, and career goals in shaping career choice, careerrelated behaviors, and occupational adjustment [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e7].The theory posits that individuals\u0026rsquo; confidence in executing occupational tasks (selfefficacy) and their anticipated consequences of task performance (outcome expectations) jointly influence their career behaviors, guiding action through the formulation of concrete goals [28].Furthermore,Social Cognitive Career Theory highlights the impact of contextual factors\u0026mdash;such as social support from family, educational institutions, peers, and organizational settings\u0026mdash;on career development. These environmental resources both foster the formation of selfefficacy and moderate individuals\u0026rsquo; coping strategies when confronting workrelated stress and uncertainty [29].Moreover, Social Cognitive Career Theory advocates a dynamic triadic reciprocal interaction among personal attributes, behavioral choices, and environmental contexts. In this view, individual traits, behavioral enactments, and external conditions continuously interact and provide reciprocal feedback, jointly shaping career trajectories and psychological adaptation [26].This theoretical framework offers a systematic basis for understanding the complex mediating and moderating mechanisms among these variables and has been widely applied in vocational psychology and organizational behavior research.\u003c/p\u003e \u003cp\u003eThe primary focus of this study is to investigate the impact of \"expectation-reality discrepancy\" on the mental health of university students, examining the mediating role of self-efficacy and the moderating effect of social support within this process. Grounded in the Social Cognitive Career Theory, the model posits that discrepancies between anticipated and actual employment scenarios can influence individuals' self-efficacy, thereby altering their coping strategies and psychological states. Individuals with higher levels of self-efficacy are more likely to adopt proactive coping mechanisms to mitigate the adverse effects of such mismatches [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, Social Cognitive Career Theory emphasizes the significance of environmental factors, such as support from family, colleagues, supervisors, and the broader community, in enhancing self-efficacy and improving mental health outcomes. Social support not only directly bolsters psychological security and well-being but also indirectly buffers the negative impact of expectation-reality discrepancies on mental health by strengthening self-efficacy [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Accordingly, this research employs Social Cognitive Career Theory as its theoretical foundation, measuring the effects of employment expectation-reality gaps, self-efficacy, and social support levels on the mental health of university students in alternative employment contexts. A structural equation model is constructed to validate the mediating effect of self-efficacy and the moderating role of social support, thereby providing empirical evidence and targeted intervention strategies for higher education institutions and relevant policymakers.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Research hypotheses\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Expectation-reality discrepancy and self-efficacy\u003c/h2\u003e \u003cp\u003eExpectation discrepancy refers to the state in which there is a gap between an individual's actual experience and their prior expectations. When actual outcomes fall short of expectations, this discrepancy can lead to cognitive dissonance and emotional fluctuations, thereby influencing behavioral decisions and motivational drive. The characteristics of expectation discrepancy include high subjectivity, strong contextual dependence, and dynamic variability. It can both facilitate behavioral adjustments and result in negative emotions and dissatisfaction [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].​\u003c/p\u003e \u003cp\u003eSelf-efficacy pertains to an individual's belief in their ability to handle challenges, adjust behaviors, and achieve goals within a professional context [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This construct reflects not only confidence and resilience in the face of job changes, skill updates, and environmental shifts but also proactive learning, continuous adaptation, and self-motivation.​\u003c/p\u003e \u003cp\u003eWe posit that expectation discrepancy has a positive effect on self-efficacy. First, when individuals recognize a reasonable gap between their expectations and reality, this seemingly contradictory state can act as a catalyst for growth. Psychological research indicates that a moderate expectation gap serves as a \"capability upgrade signal\" from the brain, prompting individuals to proactively adjust strategies and enhance skills [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].​\u003c/p\u003e \u003cp\u003eSecond, according to social cognitive theory, for instance, university students seeking employment may discover that the requirements of their desired positions slightly exceed their current competencies. In response, they often voluntarily engage in industry training, seek internship opportunities, or even replan their career paths. When students encounter discrepancies between their career expectations and actual experiences, they tend to view this inconsistency as an opportunity for self-improvement and skill acquisition. Through self-reflection, strategic adjustments, and goal restructuring, they address deficiencies, thereby increase their confidence in future success [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].​\u003c/p\u003e \u003cp\u003eFurthermore, moderate expectation discrepancies encourage individuals to learn from others' experiences during social interactions, obtain positive feedback, and reconstruct self-perceptions and capability expectations. This process contributes to improved social adaptability [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].​Based on the above discussion, we propose the following hypothesis:​\u003c/p\u003e \u003cp\u003eH1: Expectation discrepancy positively influences self-efficacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Expectation discrepancies and mental health\u003c/h2\u003e \u003cp\u003eMental health refers to an individual's state of balance, harmony, and adaptability in cognitive, emotional, and behavioral aspects [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. It is characterized not only by emotional stability, self-acceptance, healthy interpersonal relationships, and strong stress-coping abilities but also by having clear life goals and a sense of meaning [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].​\u003c/p\u003e \u003cp\u003eThis study posits that expectation incongruence negatively impacts mental health. Emotionally, when there is a significant discrepancy between a university student's expectations and reality, it may lead to feelings of frustration, anxiety, and disappointment. Without sufficient external support, these emotions can accumulate over time, potentially leading to more severe psychological distress [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Cognitively, expectation incongruence can trigger self-doubt and self-denial. In alternative employment environments, frequent encounters with uncertainty and setbacks may cause individuals to form negative evaluations of their abilities and career prospects [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Behaviorally, some individuals may choose to avoid or abandon their original career goals, thereby diminishing their work motivation and potential for professional development, ultimately leading to a decline in overall mental health [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to the SCCT, when individuals' expectations for future career development are inconsistent with their actual experiences, this can lead to reduced self-efficacy and outcome expectations, resulting in frustration and emotional disturbances. Such expectation discrepancies may cause cognitive dissonance, adversely affecting career decision-making and self-regulation. Over time, these effects can accumulate, potentially leading to psychological issues such as anxiety and depression, thereby negatively impacting overall mental health [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. When individuals face a gap between expectations and reality without adequate positive feedback and effective support, their psychological stress may intensify, ultimately harming their mental well-being [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Surveys conducted among college students have revealed a significant positive correlation between disparities in expectations versus reality and the deterioration of mental health [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, for college students undergoing the transition to employment, if their expectations significantly exceed reality, they are more likely to experience severe impacts on emotional, cognitive, and behavioral levels, increasing the risk of psychological health issues such as anxiety, depression, and job burnout. Based on the above discussion, we propose the following hypothesis:​\u003c/p\u003e \u003cp\u003eH2: Expectation discrepancies negatively affect mental health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Selfefficacy and mental health\u003c/h2\u003e \u003cp\u003eWe posit that selfefficacy has a positive effect on mental health. Specifically, individuals who hold strong confidence in their own abilities tend to display a form of \u0026ldquo;psychological resilience\u0026rdquo; when confronted with challenges\u0026mdash;much like a spring that can both bear heavy loads and then return to its original shape under pressure. This characteristic enables highselfefficacy individuals, when facing employment setbacks, to attribute failure to changeable factors (e.g., shifts in the industry environment or lack of experience) rather than to a wholesale negation of their own worth. Such an attribution pattern operates like a precise riskassessment system, helping individuals distinguish between temporary difficulties and permanent defects, thereby preventing the magnification of isolated setbacks into global failures. Luszczynska et al. [43], in a longitudinal study,reported that students with high selfefficacy were more inclined, when confronted with jobmarket competition, to plan their career trajectories and actively seek internship opportunities as a means of alleviating anxiety. Moreover, social cognitive theory suggests that individuals with high selfefficacy favor proactive problemsolving strategies over avoidance or passive coping, a behavioral style that significantly reduces psychological risks such as anxiety and depression [34]. Judge and Bono\u0026rsquo;s (2001) metaanalysis further confirmed a significant positive correlation between selfefficacy and mental health indicators (e.g., subjective wellbeing and emotional stability), demonstrating that selfefficacy\u0026rsquo;s predictive effect on mental health is independent of other personality traits [44]. Therefore, we propose the following hypothesis:\u003c/p\u003e \u003cp\u003eH3: Selfefficacy positively influences mental health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 The mediating role of selfefficacy\u003c/h2\u003e \u003cp\u003eWe propose that selfefficacy mediates the relationship between expectation\u0026ndash;reality discrepancies and mental health. Specifically, in the context of university students\u0026rsquo; engagement in alternative employment, individuals may face a gap between their anticipated and actual career prospects, remuneration, and development opportunities. This gap can elicit anxiety, depression, and other negative emotional responses, thereby undermining psychological wellbeing. Selfefficacy\u0026mdash;defined as one\u0026rsquo;s confidence in successfully adapting to a new employment environment\u0026mdash;has been empirically shown to exert a positive influence. According to selfefficacy theory, high selfefficacy bolsters resilience when confronting challenges and effectively alleviates the negative emotions arising from expectation\u0026ndash;reality mismatches. Conversely, excessively high or unrealistic expectations in alternative employment contexts may erode selfefficacy, diminish problemsolving and stresscoping capacities, and consequently impair mental health. Prior research indicates that enhancing selfefficacy can mitigate the adverse effects of expectation\u0026ndash;reality discrepancies[45,46].\u003c/p\u003e \u003cp\u003eSecond, according to Social Cognitive Theory, individuals\u0026rsquo; perceptions of their environment (such as discrepancies between expectations and reality) influence their behaviors and psychological states via selfefficacy, defined as one\u0026rsquo;s belief in one\u0026rsquo;s own capabilities. When confronted with a gap between employment expectations and actual circumstances, college students\u0026rsquo; selfefficacy becomes a critical determinant of mental health: those with high selfefficacy tend to employ active coping strategies, whereas those with low selfefficacy are more susceptible to anxiety or depression [41]. Salami [23], in a study of Nigerian undergraduates, found that career expectation discrepancies not only directly precipitated psychological stress but also indirectly exacerbated negative emotions by undermining selfefficacy (direct effect accounting for 42%, mediating effect accounting for 35%) [47]. In the employment context, misalignment between expectations and reality not only generates immediate psychological dissonance\u0026mdash;such as pessimism regarding future career prospects\u0026mdash;but also indirectly impairs mental health by eroding selfefficacy, for instance, the belief that one is incapable of performing one\u0026rsquo;s ideal job. Accordingly, basis of the foregoing discussion, we propose the following hypothesis:\u003c/p\u003e \u003cp\u003eH4: Selfefficacy mediates the relationship between expectation\u0026ndash;reality discrepancies and mental health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 The moderating role of social support\u003c/h2\u003e \u003cp\u003eSocial support refers to the emotional, informational, instrumental, and appraisal assistance and care that individuals receive from their surrounding social networks (e.g., family, friends, colleagues, schools, and communities) when confronted with stressors, challenges, or difficulties [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This construct has been extensively examined in the field of psychology and is considered to play a vital role in stress alleviation, the maintenance of psychological wellbeing, and the enhancement of selfefficacy. The primary dimensions of social support typically include emotional support (e.g., understanding, empathy, and consolation), informational support (e.g., advice and guidance), instrumental support (e.g., tangible aid or provision of resources), and appraisal support (i.e., positive feedback on one\u0026rsquo;s behaviors). These forms of support can exert a \u0026ldquo;buffering\u0026rdquo; effect in stressful situations, thereby mitigating the erosive impact of negative emotions on mental health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e9].\u003c/p\u003e \u003cp\u003eWe propose that social support positively moderates the effect of expectation\u0026ndash;reality discrepancy on selfefficacy. Specifically, social support\u0026mdash;which comprises emotional, informational, and resource assistance from family, friends, educational institutions, and social agencies\u0026mdash;can help individuals reframe their perceptions of the employment environment and thus mitigate negative appraisals of the gap between expectations and reality [50]. When undergraduates confront alternative employment options, higher levels of social support allow them to obtain more career information, skills training, and emotional reassurance, thereby effectively weakening the adverse impact of expectation\u0026ndash;reality discrepancy on selfefficacy [51]. Moreover, social support not only directly promotes enhancements in selfefficacy but also indirectly fosters psychological wellbeing by improving individuals\u0026rsquo; outlook on their career prospects. Therefore, in the context of alternative employment, high levels of social support enable undergraduates to more readily embrace realworld challenges and sustain elevated selfefficacy.\u003c/p\u003e \u003cp\u003eSecond, social cognitive theory posits that individuals\u0026rsquo; assessments of their capabilities and their subsequent behavioral choices arise from the dynamic interaction of environmental factors, personal experiences, and cognitive processes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In alternative employment settings, expectation discrepancies\u0026mdash;serving as an environmental stressor\u0026mdash;can provoke negative emotions and selfdoubt, thereby eroding one\u0026rsquo;s sense of selfefficacy [50]. However, social support, as an external positive motivator, can moderate this cognitive appraisal process. Alleviating the anxiety and uncertainty induced by environmental pressures helps individuals maintain confidence in their adaptive capacities when confronted with employment uncertainty. High levels of emotional and informational support enable students to adopt a more balanced view of both the risks and opportunities in the job market, reconstruct positive selfefficacy appraisals, and thus buffer the adverse effects of expectation discrepancies. Moreover, from a social cognitive perspective, social support enhances mechanisms of vicarious learning and social comparison: observing others successfully navigate employment challenges strengthens one\u0026rsquo;s own positive outcome expectations.Therefore, we propose the following hypothesis:\u003c/p\u003e \u003cp\u003eH5: Social support positively moderates the effect of expectation discrepancies on selfefficacy.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3 Research design","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Procedure and sample\u003c/h2\u003e \u003cp\u003e \u003cb\u003eTarget population.\u003c/b\u003eThe target population for this study comprises graduates who have opted for alternative forms of employment.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData collection.\u003c/b\u003eData were collected in three sequential stages.First ,Anhui Province was selected as the primary sampling unit on the basis of geographic balance, economic-development gradient (provincial capitals, industrial cities, and major agricultural centers), and population size. This choice both facilitated logistical convenience for our onsite team and, by sampling a representative province, provided an effective reflection of labor and employment conditions in central China.Second we conducted stratified sampling across cities, applying unequalprobability sampling with replacement to identify the sampled districts and counties.Third to accommodate fieldsurvey challenges and humanresource constraints\u0026mdash;and to secure an adequate sample within a limited timeframe\u0026mdash;we employed simple random sampling at fixed survey stations established in areas with high concentrations of alternativeemployment participants (e.g., central business districts, industrialpark peripheries, and township markets), conducting random intercept interviews.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Processing.\u003c/b\u003eThe datacleaning protocol included removing invalid questionnaires completed in less than the minimum threshold time determined by the pilot study.Excluding records not meeting the target criteria (e.g., respondents aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years or with occupation \u0026ne; \u0026ldquo;employed\u0026rdquo;) are excluded via conditional filters.Eliminating aberrant responses exhibiting fixed patterns (e.g., consecutive identical choices or wavelike sequences) is indicative of careless completion.Deleting questionnaires submitted by nontarget respondents owing to link dissemination beyond the intended population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Measurement of variables\u003c/h2\u003e \u003cp\u003eAll the items in the scales used in this study, except for control variables, were measured using a 5-point Likert scale.​\u003c/p\u003e \u003cp\u003e(1) Expectation incongruence\u003c/p\u003e \u003cp\u003eWas measured via the 9item Perceived overqualification scale (SPOQ) developed by Maynard et al. (2006) [52]. In the present study, the Cronbach's alpha coefficient for this scale was 0.834.​\u003c/p\u003e \u003cp\u003e(2) Self-Efficacy\u003c/p\u003e \u003cp\u003eWas measured via the 10item General selfefficacy scale (GSES) developed by Schwarzer et al. (1995) [53]. In the present study, the scale demonstrated a Cronbach\u0026rsquo;s alpha of 0.866.\u003c/p\u003e \u003cp\u003e(3) Social Support\u003c/p\u003e \u003cp\u003eWas measured via the 12item Multidimensional scale of perceived social support (MSPSS) developed by Zimet et al. (1988) [54]. In the present study, the scale demonstrated a Cronbach\u0026rsquo;s alpha of 0.879.\u003c/p\u003e \u003cp\u003e(4) Mental health\u003c/p\u003e \u003cp\u003eWas measured via the 17item Utrecht Work Engagement Scale (UWES) developed by Schaufeli et al. (2006) [55]. In the present study, the scale demonstrated a Cronbach\u0026rsquo;s alpha of 0.937.\u003c/p\u003e \u003cp\u003eIn this study, gender, highest educational attainment, years of work experience [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], and industry type [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] were included as control variables. Years of work experience reflect an individual's career stage; those with more extensive experience often possess greater professional confidence and adaptability. Industry type represents different alternative employment models (e.g., remote education, content creation, platform-based gig economy), which vary in task characteristics, social networks, and support mechanisms, potentially influencing levels of social support and mental health. Controlling for these variables helps eliminate sample heterogeneity, thereby allowing for a more accurate examination of the relationships among expectation incongruence, self-efficacy, and mental health.​\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Data analysis","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Confirmatory factor analysis\u003c/h2\u003e \u003cp\u003eTo further assess the discriminant validity among the measured variables, this study conducted a confirmatory factor analysis (CFA) viaAMOS 24.0. The analysis focused on four latent constructs: expectation inconsistency (EI), self-efficacy (SE), social support (SS), and mental health (MH). Four competing models were specified for comparison: (1) a four-factor model, where each latent construct was modeled separately; (2) a three-factor model, combining SE and SS into a single factor; (3) a two-factor model, merging EI, SE, and SS into one factor; and (4) a one-factor model, integrating all items into a single latent construct. The fit indices for each model are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAmong the models, the four-factor model demonstrated the best fit, with χ²/df = 1.608, CFI = 0.904, TLI = 0.894, RMSEA = 0.046, all meeting the commonly accepted thresholds for good model fit (i.e., CFI ≥ 0.90, TLI ≥ 0.90, RMSEA ≤ 0.06, SRMR ≤ 0.08) [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. This model significantly outperforms the alternative models, indicating that the four constructs are empirically distinct and possess satisfactory discriminant validity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of confirmatory factor analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-factor model: EI, SE, SS, MH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1632.205\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1015\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.608\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0532\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree-factor model: EI, SE + SS,MH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2615.591\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1077\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.429\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0679\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo-factor model: EI + SE + SS, MH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3208.818\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1079\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.974\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0943\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne-factor model: EI + SE + SS + MH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5036.951\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1080\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.664\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote: EI = Expectation inconsistency, SE = Self-efficacy, SS = Social support, MH = Mental health.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Descriptive statistics and correlation results\u003c/h2\u003e \u003cp\u003eAs shown in Table Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, expectation discrepancy is significantly negatively correlated with mental health (r = -0.182, p \u0026lt; 0.01) and significantly positively correlated with self-efficacy (r = 0.233, p \u0026lt; 0.001). Additionally, self-efficacy was significantly positively correlated with mental health (r = 0.617, p \u0026lt; 0.01). These results provide empirical support for Hypotheses 1 to 3. The findings are consistent with the theoretical expectations of this study and offer preliminary support for the proposed hypotheses.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans, standard deviations, and correlations of the variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Gender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Highest Educational Level\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e− .118*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Years of Work Experience\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e− .181**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Industry Type\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Expectation Discrepancy\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e− .139*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e− .119*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Self-Efficacy\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.099\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.233**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Social Support\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.63\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.085\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.233**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.617**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Mental Health\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.074\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e− .133*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e− .182**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.128*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.135*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eNote: N = 289,p \u0026lt; 0.05, p \u0026lt; 0.01, p \u0026lt; 0.001.The same notation applies hereinafter.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Hypothesis testing\u003c/h2\u003e \u003cp\u003eAs shown in Model 2 and Model 4 of Table Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, expectation discrepancy is positively associated with self-efficacy (β = 0.226, p \u0026lt; 0.001) and negatively associated with mental health (β = -0.192, p \u0026lt; 0.01), thus supporting Hypotheses 1 and 2. Model 6 further indicates that expectation discrepancy is positively related to psychological distress (β = 0.12, p \u0026lt; 0.05), supporting Hypothesis 3. According to Model 5, when self-efficacy is included in the regression model, expectation discrepancy remains negatively associated with mental health (β = -0.231, p \u0026lt; 0.001). These results suggest that psychological safety partially mediates the relationship between leadership style (i.e., humble leadership and abusive supervision) and knowledge hiding behavior. Moreover, we conducted a bootstrap test to further validate this mediating effect. The indirect effect was 0.047, with a 95% confidence interval of [0.008, 0.081], which does not include zero (see Table Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Therefore, Hypothesis 4 is supported.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical regression results testing the mediating effect of self-efficacy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSelf-Efficacy\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eMental Health\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 5\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 6\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.088\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.114\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.105\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.079\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork Tenure\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.146*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.141*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.148**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.152*\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry Type\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectation Discrepancy\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.226***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.192**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.231***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Efficacy\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.171**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.12*\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR²\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted R²\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.377\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.144***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.957*\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.626***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.384***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.233**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDecomposition of total, direct, and indirect effects (bootstrap = 5000)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect Type\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI Lower (BootLLCI)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI Upper (BootULCI)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Effect\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.234\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.373\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.094\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect Effect\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.281\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.422\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect Effect\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\u003cp\u003eThis study further examined the moderating role of social support by conducting hierarchical regression analyses via SPSS 25.0. Prior to testing, both expectation discrepancy and social support were meancentered. The relevant regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. As indicated by Model 9 in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the interaction between expectation discrepancy and social support positively predicts selfefficacy (β = 0.163, p \u0026lt; 0.01), thereby supporting Hypothesis 5\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical regression results: moderating effect analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePredictors\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSelfEfficacy\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 7\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 8\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 9\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.033\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest education/degree\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of work experience\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry type\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectation discrepancy\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.226***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.093*\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.599***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.576***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectation discrepancy × Social support\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.163**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR²\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted R²\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.144**\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.96***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.635***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003eThis study employed a bootstrap procedure with 5,000 resamples and a 95% confidence interval to examine the moderated mediation effect of organizational justice on resistance to change; the results are presented in Table Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, social support significantly moderates the indirect effect of expectation incongruence on mental health via selfefficacy: the indirect effect differs between high and low levels of social support, and its 95% confidence interval does not include zero [0.0009, 0.0799], indicating that social support strengthens the mediating role of selfefficacy in the relationship between expectation incongruence and mental health.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the moderated mediation effect analysis (bootstrap = 5,000)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerator Level\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI Lower (BootLLCI)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI Upper (BootULCI)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean − 1 SD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0398\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0208\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0051\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0863\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0194\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0138\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0062\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean + 1 SD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0181\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0291\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerated indirect effect\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0307\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0207\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0799\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGrounded in Social Cognitive Theory and situated within the context of alternative employment among university graduates, this study examined how expectation incongruence influences mental health and the mechanisms through which this effect unfolds. Consistent with our hypotheses, greater discrepancy between career expectations and reality was associated with poorer mental health outcomes. Selfefficacy emerged as a key mediator: when students perceived a mismatch between their expectations and actual work experiences, their belief in their ability to manage career challenges diminished, which in turn exacerbated psychological distress. Moreover, social support functioned as a positive moderator of the expectation–selfefficacy link. Specifically, under high levels of support from family, peers, and institutions, the adverse impact of expectation incongruence on selfefficacy was attenuated, thereby buffering against downstream declines in mental health. The moderated mediation model thus underscores the dual importance of individual cognitive resources and contextual social resources in shaping adaptive responses to employment transitions. By integrating expectation incongruence, selfefficacy, and social support into a unified framework, our findings extend prior work in vocational psychology and highlight dynamic processes of cognitive appraisal and social buffering in the face of nontraditional career pathways.\u003c/p\u003e\u003cp\u003e \u003cb\u003eLimitations and directions for future research\u003c/b\u003e \u003c/p\u003e\u003cp\u003eDespite its contributions, this study has several limitations that suggest avenues for further inquiry.\u003c/p\u003e\u003cp\u003eCrosssectional design. Because data were collected at a single time point, causal inferences regarding the temporal ordering of expectation incongruence, selfefficacy, and mental health remain tentative. Future research should employ longitudinal or experimental designs to trace how these relationships evolve over time and to establish stronger evidence of causality.\u003c/p\u003e\u003cp\u003eSelfreport measures. Although we used wellvalidated scales, reliance on selfreports may introduce common method variance, social desirability bias, and recall inaccuracies. Subsequent studies could incorporate multisource assessments (e.g., behavioral observations, peer or supervisor ratings) to enhance measurement objectivity and reduce potential bias.\u003c/p\u003e\u003cp\u003eUnmeasured confounds. Mental health in alternative employment settings is influenced by myriad factors—such as socioeconomic background, financial stress, and family dynamics—that were not exhaustively controlled here. Future work should include a broader set of covariates or apply propensityscore matching to better isolate the unique effects of expectation incongruence, selfefficacy, and social support.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study advances our understanding of university graduates’ psychological adaptation to alternative employment by demonstrating (a) a direct negative effect of expectation incongruence on mental health, (b) a mediating role of selfefficacy in this relationship, and (c) a buffering role of social support both on the expectation–selfefficacy link and on the overall indirect effect. Theoretically, our dynamic adjustment model enriches Social Cognitive Career Theory by foregrounding expectation gaps as a pivotal driver of careerrelated wellbeing. Practically, the findings underscore the need for highereducation institutions, career services, and policymakers to help students set realistic expectations, bolster their selfefficacy, and cultivate robust support networks. Such interventions hold promise for mitigating the psychological risks associated with nontraditional employment trajectories and promoting healthier career transitions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e \u003cb\u003eEthics declarations\u003c/b\u003e \u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eAll participants in the study provided informed consent and agreed to the publication of this paper.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was funded by Open Research Project of Anhui Engineering Research Center for Intelligent Computing and Information Innovation, Fuyang Normal University(Grant number ICII202507).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization:HH L; Methodology, formal analysis and investigation: HH L, ZH Y ;Writing\u0026mdash;original draft:HH L, Q L, XC L, WH, KX R; Writing\u0026mdash;review and editing: HH L.All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to thank all the participants.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe datasets generated and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYang, G., \u0026amp; Bai, Y. (2022, November 18). Expected number of 2023 university graduates to reach 11.58 million [Newspaper article]. People\u0026rsquo;s Daily.\u003c/li\u003e\n\u003cli\u003eWang, Y., \u0026amp; Liu, F. (2024). Research on alternative career choices among young university students in an involuted employment market. China University Students Employment, (1), 1\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eCai, X., Chen, Q., Wen, S., et al. (2022). Reform and practice of intelligent accounting talent training under the \u0026ldquo;New Liberal Arts\u0026rdquo; background: A case study of Nanjing Audit University. Friends of Accounting, (003), 135\u0026ndash;140.\u003c/li\u003e\n\u003cli\u003ePei, W., Xiao, Z., \u0026amp; Jiang, J. (2022). Psychological problems and adjustment strategies for university student employment in the post‑pandemic era. Journal of Jiamusi Vocational Institute, 38(9), 49\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eMorvan, C., \u0026amp; O\u0026rsquo;Connor, A. (2017). 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Johnston (Eds.), Measures in Health Psychology: A User\u0026rsquo;s Portfolio (pp. 35\u0026ndash;37). Causal and Control Beliefs.\u003c/li\u003e\n\u003cli\u003eZimet, G. D., Dahlem, N. W., Zimet, S. G., \u0026amp; Farley, G. K. (1988). The Multidimensional Scale of Perceived Social Support. Journal of Personality Assessment, 52(1), 30\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eSchaufeli, W. B., Bakker, A. B., \u0026amp; Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross‑national study. Educational and Psychological Measurement, 66(4), 701\u0026ndash;716.\u003c/li\u003e\n\u003cli\u003eWihler, A., Meurs, J. A., \u0026amp; Kramer, J., et al. (2021). Does job tenure increase human capital? How general mental ability and low job stress jointly augment the job tenure\u0026ndash;job performance relationship. Nova Science Publishers.\u003c/li\u003e\n\u003cli\u003eLaditka, J. N., Laditka, S. B., \u0026amp; Arif, A. A., et al. (2023). 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Structural Equation Modeling, 6(1), 1\u0026ndash;55.\u003c/li\u003e\n\u003c/ol\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":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Alternative employment, Expectation discrepancy, Self- efficacy, Mental health","lastPublishedDoi":"10.21203/rs.3.rs-6504313/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6504313/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground.\u003c/strong\u003e Grounded in Social Cognitive Career Theory researchgate, this study introduces “expectation discrepancy” into alternative employment contexts and develops a mediated–moderated model to explore the mechanisms by which the gap between college students’ employment expectations and reality affects mental health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods.\u003c/strong\u003e A total of 289 valid responses were collected via an online questionnaire, and structural equation modeling (SEM) along with hierarchical regression analyses were employed to test the pathways involving expectation discrepancy, self‑efficacy, and social support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults. \u003c/strong\u003eThe results show that expectation discrepancy negatively predicts mental health while positively predicting self‑efficacy; self‑efficacy partially mediates the relationship between expectation discrepancy and mental health; and social support significantly and positively moderates the effect of expectation discrepancy on self‑efficacy, further moderating the effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion/Implications.\u003c/strong\u003e This study’s innovation lies in constructing and validating a mediated–moderated model based on SCCT, providing empirical evidence to inform university career guidance, psychological intervention strategies, and related government policy‑making.\u003c/p\u003e","manuscriptTitle":"Investigating the Mechanisms by Expectation Discrepancies in Alternative Employment Contexts Affect College Students’ Mental Health: The Multilevel Roles of Self-Efficacy and Social Support","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-23 06:03:55","doi":"10.21203/rs.3.rs-6504313/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-05-21T13:19:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-13T08:46:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-24T07:06:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-24T05:12:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-04-24T05:10:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdc4af33-07d1-4a27-989f-e25af81c3a1a","owner":[],"postedDate":"May 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-23T06:03:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-23 06:03:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6504313","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6504313","identity":"rs-6504313","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}