The Eastern Zhongyong Thinking Style Buffers the Socioeconomic Gradient in Well-Being

The Eastern Zhongyong Thinking Style Buffers the Socioeconomic Gradient in Well-Being | 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 The Eastern Zhongyong Thinking Style Buffers the Socioeconomic Gradient in Well-Being Yukun Zhao, Yu Mao, Zhensen Liang, Kaiping Peng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7751702/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Socioeconomic status (SES) robustly stratifies well-being (WB), yet culturally grounded cognitive resources may blunt this gradient. We tested whether zhongyong, an Eastern thinking style emphasizing multi-perspective integration, contextual fit, and moderation buffers the SES-WB links in China. N = 600 adults completed an online survey assessing both subjective and objective SES indicators, alongside both Western and Eastern indicators. Zhongyong was measured both globally and by facets (Multi-thinking, Holism, Harmoniousness). Analyses used mean-centered predictors with SES×zhongyong interactions and simple-slope probes. The results indicated that SES related to greater WB, with subjective SES showing larger and more consistent associations than objective SES. Zhongyong also correlated positively with WB. Crucially, zhongyong buffered SES–WB slopes, most clearly for subjective SES and symptom outcomes. Facet analyses indicated that Holism was the most consistent and largest moderator, and Harmoniousness was least predictive. Findings position zhongyong as a psychological resource that attenuates the socioeconomic gradient in WB. The results advance a culturally plural account of psychological resources and suggest zhongyong-informed skills as low-cost targets to protect disadvantaged groups’ well-being. zhongyong well-being ikigai SES thinking style Figures Figure 1 1. Introduction 1.1 The relationship between socioeconomic status (SES) and well-being Decades of research show that people with higher SES report better well-being than those with fewer resources. For example, Kahneman & Deaton ( 2010 ) used data from more than 450,000 U.S. respondents and found that life evaluation rose steadily with log income, whereas emotional well-being rose with income up to a threshold and then plateaued. More recently, Killingsworth, Kahneman, & Mellers ( 2023 ) found that emotional well-being continues to rise with income for most people, with a flattening only among the least happy. Meta-analytic evidence also supports a positive link between economic status and subjective well-being across diverse contexts, with stronger effects where material scarcity is greater (Howell & Howell, 2008 ). Various mechanisms were proposed to explain this relationship. Most notably, perceived control (Johnson & Krueger, 2006 ; Wang et al., 2023 ), social comparison (Ren et al., 2022 ), and perceived fairness (Ren et. al, 2022 ) were found to mediate the influence of SES to well-being. Not surprisingly, subjective SES is often a stronger predictor than objective SES, because it is how people perceive their SES, rather than what their actual SES is, that affects these variables. Indeed, a large meta-analysis of 357 studies (N = 2.35 million) showed that subjective SES correlated more strongly with subjective well-being ( r = .22) than did objective SES ( r = .16), and subjective SES also partly mediated the association between objective SES and well-being association, consistent with the idea that perceived status translate resources into felt quality of life (Tan, Kraus, Carpenter, & Adler, 2020 ). 1.2 Protective factors buffering the SES-WB relationship A growing body of research has identified various factors that can buffer the impact of low SES on well-being. First, Social factors. The availability of support can help offset the stresses associated with low income or social disadvantages. For example, Zhao & Peng ( 2021 ) found that when perceived social support was high, the association between relative deprivation and depression was significantly weaker. Similarly, Non et al. ( 2020 ) found that adults who had higher social support in mid-life were more likely to engage in healthy behaviors regardless of their disadvantaged childhood SES. Second, psychological factors. For example, optimism has been identified as a protective factor in the face of adversity. Non et al. ( 2020 ) showed that in those who had a disadvantaged childhood, higher optimism in adulthood predicted healthier behaviors despite their early SES disadvantage. Similarly, resilience could entail adaptability, perseverance, and positive coping that protect well-being under socioeconomic stress. Evidence from a Chinese college student sample illustrated that resilience moderated the link between family SES and academic burnout, so that low-SES students with high resilience showed much lower levels of learning burnout compared to low-resilience students of similar SES (Wu et al., 2022 ). Third, behavioural factors. For example, physical activity can benefit mood, reduce stress, and improve health, which will be especially valuable for those under high stress or economic hardship. A recent large-scale study found that moderate-to-vigorous physical activity (≥ 150 minutes/week) buffered against the risk of depressive symptoms in low-SES individuals (Ye et al., 2025 ). This buffering effect was particularly strong among those who were unemployed, a severe SES disadvantage group. Cognitive factors were also found to be effective buffers against low SES. Most notably, the growth mindset of SES itself, i.e., the belief that one’s SES can change and improve with effort, as opposed to the fixed mindset of SES, that sees SES as a fixed, unchangeable status. In a large longitudinal study using national survey data, Zhao et al. ( 2021 ) found that those with a growth mindset did not show as large a drop in well-being when SES was low, compared to those with a fixed mindset. Another example is a person’s perceived control over life outcomes. Lachman & Weaver ( 1998 ) demonstrated that a strong sense of control can virtually eliminate class disparities in well-being. In their analysis of thousands of adults, higher perceived control was linked to better health, greater life satisfaction, and lower depression across the board. Critically, they found that low-income individuals who maintained a high sense of control had levels of health and well-being comparable to those of higher-income individuals. In contrast, low-income individuals with low control fared worse. This means beliefs on control act as a protective shield for low-SES individuals, offsetting some negative effects of socioeconomic hardship. 1.3 East Asian thinking styles and well-being This article aims to explore the moderating role of East Asian thinking styles on the SES-WB relationship. Peng, Spencer-Rodgers, & Nian ( 2006 ) identified the characteristics of East Asian cognition as tolerance of contradiction, mindset of change, and holism. They were found to facilitate well-being, particularly for those facing adversities (Spencer-Rodgers & Peng, 2018 ). First, the East Asian thinking styles help people to accept contradiction and change in life, which in turn support their adaptation. Spencer-Rodgers et al. ( 2009 ) found that those high on holistic cognition do not insist on consistency in their attitudes or self-concepts across situations, making them more flexibly adapt to dynamic environments. Similarly, openness to contradiction has been associated with psychological resilience. Yao et al. ( 2024 ) found that people with a holistic mindset are more resilient and have more adaptive coping when facing complex life problems. This flexibility offsets the negative impact of adversity to well-being that happens more often in low SES population. Second, East Asian thinking styles encourages contextual thinking and integration of information from bigger scope (Nisbett et al., 2001 ) This is protective to well-being of low SES people. For instance, if something bad happens, a holistic thinker might recognize situational factors instead of blaming their own fixed traits. Research in cross-cultural psychology shows East Asians tend to downplay dispositional blame in favor of situational explanations, compared to Westerners (Wong & Liu, 2018 ). Holistic thinking can also lead people to find meaning and gratitude in adversity. During the COVID-19 pandemic, for example, individuals high in holistic thinking were markedly better at deriving meaning from the crisis and feeling gratitude despite hardships (Lee et al., 2023 ) In contrast, those low in holistic thinking had more difficulty seeing anything beyond isolated negatives. Crucially, gratitude and meaning are well-known predictors of psychological resilience and lower depression. Third, East Asian thinking is tightly linked with the dialectical ethos of emotional moderation. Individuals with dialectical beliefs often aim for moderate emotions rather than pure positivity. They believe happiness and sadness can co-exist and that emotional states inevitably change, and refrain from chasing extreme happiness and accept negative experiences as natural (Miyamoto & Ryff, 2011 ). Indeed, the Dialectical Behavior Therapy was developed based on the Eastern dialectical principles, to teach clients to accept reality while working on change (Robins & Rosenthal, 2011 ). DBT’s success in treating borderline personality disorder and emotion dysregulation highlights how embracing opposites can foster emotional regulation, stress tolerance, and self-compassion, all key ingredients of well-being (Lynch et al., 2006 ). 1.4 Zhongyong (ZY) as a moderator of the SES-WB relationship Zhongyong (中庸), often translated as “Doctrine of the Mean”, a paragon of East Asian thinking style that emphasizes moderation, multi-perspective integration, contextual fit, and harmony-maintenance. It advocates avoidance of extremes while adjusting one’s stance to the situation. Modern psychology operationalizes it with the zhongyong Thinking Style Scale (ZYTS; Wu & Lin, 2005 ), which captures three facets: multi-thinking (considering multiple perspectives), holism (integrating information to see the whole), and harmoniousness (context-appropriate, harmony-preserving responding). Yang et al. ( 2016 ) showed that higher zhongyong is linked to lower depression and anxiety and higher life satisfaction and self-esteem. Furthermore, their experimental study revealed that zhongyong thinking training can lead to less depressive symptoms compared with the control group. Zhongyong also has a robust positive associations with resilience, partly via cognitive reappraisal and positive affect as well as context-sensitive appraisal style (Zhou & Li, 2022 ). In work settings, zhongyong attenuates the harmful effects of hindrance stress on emotional exhaustion and job satisfaction, and helps employees channel some challenge stress into eustress (Chou et al., 2014 ). Among Chinese young adults, zhongyong is positively associated with psychosocial well-being and negatively with adjustment problems, and more importantly, buffers the typically negative association between expressive suppression and psychosocial adjustment (Cui, Tang, & Huang, 2022 ). Together, these findings converge on a picture of zhongyong as a psychological resource that stabilizes affect, supports adaptive reappraisal, and sustains well-being, as well as weaken the impact of certain stressors on mental health. Despite this pattern, we found no published study directly testing zhongyong as a moderator of the relationship between SES and well-being. The Reserve Capacity Model (RCM, Gallo, de Los Monteros, & Shivpuri, 2009 ) predicts that individuals’ appraisal and regulation resources buffer the emotional toll of disadvantage. Zhongyong is precisely such a resource that promotes reappraisal and context-appropriate responding. Moreover, as shown earlier in this article, subjective SES is often a stronger predictor of well-being than objective SES. As zhongyong shapes how status is construed and emotionally managed, it should blunt the negative slope from subjective low SES to poorer well-being, much as it already buffers work stress and maladaptive regulation. Therefore, zhongyong, especially its cognitive components of multiple perspective taking and holism, fits the profile of a culturally situated reserve capacity that could buffer the negative impact of low SES to well-being. 1.5 Ikigai as an Eastern indicator of well-being There are also research showing that individuals high in East Asian thinking sometimes score lower on life satisfaction and positive affect (Wong & Liu, 2018 ). Multiple studies have noted that stronger dialectical self-beliefs correlate with lower reported SWB or self-esteem in East Asian samples (Spencer-Rodgers et al., 2004 ; Lee & Wu, 2008 ; Wong et al., 2011 ). However, this appears to be an artifact of measurement and cultural definition of happiness. Because dialectical individuals do not equate well-being with maximizing positive emotions alone, they report moderate happiness by choice. Importantly, accepting negativity is not seen as “unhappy” in dialectical culture. Researchers point out that dialectical lay beliefs about happiness lead people to value calm contentment over exuberance (Wong & Liu, 2018 ). Therefore, while East Asian thinkings might appear to lower happiness on Western metrics, it actually reflects a different, balanced form of well-being. To make a culturally accurate case, our outcomes should not be limited to Western indicators. This study includes ikigai as an Eastern construct and measurement of well-being. Ikigai is a Japanese term, literally meaning “a reason for living”. It captures a blend of daily purpose, engagement, and a sense of being needed that Western scales only partially tap. Empirically, ikigai is robustly associated with better mental health and life evaluation and has been linked to lower all-cause mortality in a large Japanese cohort, underscoring criterion importance beyond self-reports (Sone et al., 2008 ). At the same time, ikigai has proven measurable and reliable outside Japan, with validated translations in UK (Fido, Kotera, & Asano, 2020 ), France (Vandroux & Auzoult-Chagnault, 2023 ), Germany (Hajek et al., 2024 ), and a mixed sample of participants from North America and Europe (Wilkes et al., 2023 ). Moreover, cross-national survey work in the Asia-Pacific found ikigai was a transferable construct tied to social resources, suggesting it indexes culturally salient pathways to well-being that are meaningful in East Asian settings like China and South Korea (Park, 2015 ). Therefore, including ikigai as a DV lets us test whether zhongyong protects both Western and Eastern well-being constructs that matters for flourishing in Chinese contexts. 1.6 The current study The current study tests whether zhongyong, an indigenous Chinese thinking style, buffers the SES gradient in well-being in mainland China. We operationalize well-being multifacetedly, spanning both Western and Eastern indicators, and covering both the positive and the negative measures. Because subjective SES often tracks well-being more strongly than objective SES, we examine both and explicitly contrast their associations and interactions with zhongyong. Beyond a global zhongyong effect, we ask which facets, namely multi-perspective thinking, holism, or harmony-maintenance, carry the most buffering. We hypothesize that: H1: Lower SES relates to lower SWLS, meaning in life, and ikigai, and higher depression/anxiety; subjective SES will show stronger effects than objective SES. H2: Higher zhongyong predicts higher SWLS, meaning in life, ikigai and lower depression/anxiety (positive main effects across outcomes). H3: zhongyong moderates the SES-WB relationship, so that the SES–WB slope is weaker at high zhongyong, i.e., low-SES participants with high zhongyong report relatively preserved well-being. H4: Perceived SES × zhongyong interactions are larger than objective SES × zhongyong interactions. H5: Multi-perspective thinking and holism contribute the bigger parts of buffering than harmoniousness. 2. Methods 2.1 Participants We recruited N = 600 adults residing in mainland China via an online survey platform. Two attention checks were added to the survey. All participants passed them. To ensure variability of SES, we balanced their gender, age, income, education, region, and hukou (the Chinese household registration system that divide people into urban and rural residents). Table 1 reports the sample characteristics. Table 1 Summary of sample SES Categorical Indicators Category % Gender Male 50.7 Female 49.3 Other 0 Education Middle School or Lower 16.8 High School 18.7 Junior College 18.8 College 24.3 Postgraduate 21.3 Hukou Urban 74.2 Rural 25.8 City Tier-1 12.7 Tier-2 19.5 Tier-3 17.3 Tier-4 19.5 Tier-5 19.3 Tier-6 11.7 Continuous Indicators Mean SD Age 46.7 15.4 Monthly Income (RMB) 15,165 16,566 2.2 Measures Socioeconomic Status . The objective SES measures included individual monthly income and education level. Two China-specific measures were also collected. First, hukou . It’s a Chinese household registration system that records a person's basic information and permanent residence and determines where citizens can access public services and benefits. It has two major categories: rural and urban residents. The rural hukou is widely considered less privileged than the urban hukou. Second, the tier of the cities. The megacities like Beijing and Shanghai are considered the tier-1 cities of China. Other cities are also rated mainly based on economical indices, like GDP per capita, population, and job opportunities. The smaller the tier number is, the more prosperous a city is. The subjective SES was measured using the MacArthur Scale of Subjective Social Status (society ladder, Adler, 2007 ). Participants were presented a picture of a 10-rung ladder depicting society, with higher rungs indicating higher standing. They indicated the rung that best represented their standing in society. This single-item measure is widely used and shows robust associations with well-being and health. zhongyong Thinking style . Zhongyong was measured with the zhongyong Thinking Style Scale (ZYTS, Wu & Lin, 2005 ), which operationalizes the balance-seeking cognitive style across three facets: multi-thinking, holism, and harmoniousness. It has 13 items, e.g. “I am used to thinking about the same thing from multiple perspectives” (multi-thinking), “I will try to integrate my opinions into the ideas of others” (holism), “I usually express conflicting opinions in a tactful way” (harmoniousness). Items were rated on a 5-point scale from very inconsistent to very consistent , with higher scores indicating stronger zhongyong style. Prior work demonstrates adequate reliability/validity and the three-facet structure. In this study, the Cronbach’s α for these three dimensions and the whole scale were .723, .747, .736, and .878 respectively. Life satisfaction. Global life evaluation was assessed with the Satisfaction With Life Scale (SWLS, Diener et al., 1985 ). It has 5 items on cognitive judgments of one’s life, e.g., “In most ways my life is close to my ideal.” Items were rated on a 7-point scale from strongly agree to strongly disagree , with lower scores indicating greater life satisfaction. We reversed the scores during data analysis so that the scores can reflect the level of life satisfaction directly. The SWLS has good psychometrics and is widely used as a narrow-band measure of life satisfaction. In this study, the Cronbach’s α for the scale was .887. Meaning in life. The Presence subscale of the Meaning in Life Questionnaire (Steger et al., 2006 ) to assess the sense of meaningfulness a person feels in life. It has 5 items, e.g., “I understand my life’s meaning”, including one reverse-scored item, “My life has no clear purpose”. Items were rated on a 7-point scale from strongly agree to strongly disagree , with lower scores indicating greater meaning in life. We reversed the scores during data analysis so that the scores can reflect the level of meaning in life directly. In this study, the Cronbach’s α for the scale was .846. Depression and anxiety. Emotional symptoms were assessed over the past week with the Depression and Anxiety sub-dimensions of the Brief Symptom Inventory-18 (Derogatis, 2001 ). Each sub-dimension consists of 6 items, e.g., “Feeling no interest in things” (depression), “Spells of terror or panic” (anxiety). Items were rated on a 5-point scale from not at all to extremely , with higher scores indicating more severe symptoms. In this study, the Cronbach’s α for the depression and anxiety sub-dimensions were .868 and .902 respectively. Ikigai. Ikigai was measured with the Ikigai-9 scale (Imai, 2012 ). It has 9 items, e.g., “I think my existence is needed by something or someone”. They are rated on a 5-point scale from strongly agree to strongly disagree , with lower scores indicating greater ikigai. We reversed the scores during data analysis so that the scores can reflect the level of ikigai directly. In this study, the Cronbach’s α for the scale was .879. 2.3 Procedure The survey was administered online in Chinese. Data was analysed using RStudio 2025.05.0. 3. Results 3.1 Main effects Since this study adopts a cross-sectional design, we estimated a common latent factor (CLF) CFA with equal loadings on all items and the CLF constrained orthogonal to the substantive factors to evaluate potential common-method variance. Results showed that adding the CLF did not meaningfully alter the measurement model. Standardized trait loadings were identical before vs. after including the method factor. Global fit indices changed trivially, and the equal CLF loading was negligible. These results indicate that common-method variance is unlikely to account for the observed correlations or the moderation patterns analyzed in this study. Table 2 shows correlations among the study variables. Age showed small but interpretable associations with SES and well‑being. Older participants tended to reside in higher‑tier cities ( r = .121, p = .003), reported lower formal education ( r = − .545, p < .001), and slightly higher life satisfaction ( r = .081, p = .047). Correlations of age with other SES indicators, zhongyong, and other well-being variables were near zero. The gender differences were significant in income ( r = − .119, p = .003), indicating that women make less money than men in China. But the gender differences in other SES variables, zhongyong, and well-being variables were uniformly small or insignificant. Table 2 Correlations of SES, zhongyong, and well-being variables Variables 1 2 3 4 5 6 7 8 9 10 11 12 1 Age - 2 Gender − .100* - 3 Hukou − .019 − .004 - 4 Tier .121** − .057 .015 - 5 Education − .545** .042 − .205** − .155** - 6 Income − .079 − .119** − .116** − .045 .330** - 7 Ladder .046 .019 − .179** − .021 .196** .263** - 8 zhongyong − .036 .000 − .120** .006 .141** .114** .130** - 9 Life Satisfaction .081* − .062 − .095* .122** .025 .127** .324** .264** - 10 Meaning in Life .022 − .085* − .091* .141** .081* .128** .283** .381** .565** - 11 Depression − .024 .064 .128** − .068 − .126** − .139** − .229** − .185** − .465** − .516** - 12 Anxiety − .024 .062 .021 − .032 − .058 − .099* − .146** − .406** − .108** − .338** .781** - 13 Ikigai − .024 − .087* − .120** .145** .118** .175** .333** .715** .342** .631** − .618** − .451** * p < 0.05 . ** p < 0.01 . As expected, higher SES was associated with better well‑being across indicators. The subjective SES exhibited the largest and most consistent links. The ladder of perceived status correlated with higher life satisfaction ( r =. 324, p < .001), greater meaning ( r = .283, p < .001), higher ikigai ( r = .333, p < .001), and lower depression ( r = − .229, p < .001) and anxiety ( r = − .146, p < .001). Objective SES indicators showed the same general pattern with smaller magnitudes. Income related to higher life satisfaction, meaning in life, and ikigai, and fewer depressive and anxiety symptoms. Education correlated positively with meaning in life and ikigai and negatively with depression. Its association with life satisfaction and anxiety were negligible. Hukou also tracked well‑being. Further independent t -test showed that those registered in urban hukou had significantly higher levels of life satisfaction ( t = 2.332, p = .020), meaning in life ( t = 2.239, p = .026), ikigai ( t = 2.965, p = .003), and lower levels of depression ( t = -3.151, p = .002) than their fellow compatriots in rural hukou. In line with prior research, SES predicted well-being variables, and the associations of the subjective SES with WB were stronger than those of the objective SES with WB. The only SES indicator that didn’t correlate negatively with well-being was the city tier, which correlated positively with life satisfaction, meaning in life, and ikigai, with near‑zero links to negative symptoms. This was probably because the degree of prosperity of a city doesn’t necessary reflect a person’s SES directly, especially the perceived SES. Prior research also showed that the relationship between city population and wealth and well-being was not linear (Zhao et al., 2019 ). Overall, H1 was supported. Higher zhongyong was also associated with higher well-being. The correlations were significant between zhongyong and life satisfaction ( r =. 264, p < .001), meaning in life ( r = .381, p < .001), ikigai ( r = .342, p < .001), depression ( r = − .185, p < .001), and anxiety ( r = − .108, p < .001). H2 was supported. 3.2 Moderations We estimated 80 moderation models (4 SES indicators × 5 well-being outcomes × 4 zhongyong indices). City tier was not included because it was not a negative predictor of well-being. Table 3 shows the parameters of the model results. Table 3 Summary of moderation models DV SES Moderator β SE t p ΔR² R² Slope of SES @ Low ZY (p) Slope of SES @ High ZY (p) Anxiety Education Harmoniousness -0.0775 0.0307 -1.8071 0.0712 0.0214 0.0054 .0146 (.57) − .0528 (.04) Holism -0.0694 0.0354 -1.5479 0.1222 0.0188 0.0039 .0108 (.69) − .0496 (.05) MultiThinking -0.1052 0.0314 -2.3604 0.0186 0.0144 0.0092 .0262 (.33) − .0653 (.01) ZY -0.1022 0.0376 -2.2967 0.022 0.0223 0.0087 .0277 (.31) − .0613 (.02) Hukou Harmoniousness 0.0502 0.0962 1.1853 0.2364 0.0164 0.0023 − .0471 (.54) .0917 (.29) Holism 0.1073 0.0973 2.7661 0.0058 0.025 0.0125 − .1197 (.1) .1774 (.03) MultiThinking 0.0547 0.0916 1.3385 0.1812 0.006 0.003 − .045 (.55) .1064 (.21) ZY 0.0839 0.1106 2.0378 0.042 0.0187 0.0068 − .0889 (.24) .1432 (.1) Income Harmoniousness 0.0089 < 0.0001 0.2128 0.8315 0.0217 0.0001 0 (.1) 0 (.18) Holism 0.0387 < 0.0001 0.9953 0.32 0.0223 0.0016 0 (.02) 0 (.38) MultiThinking -0.0414 < 0.0001 -1.1523 0.2497 0.0136 0.0022 0 (.32) 0 (.01) ZY -0.004 < 0.0001 -0.1002 0.9202 0.0194 < 0.0001 0 (.14) 0 (.11) Ladder Harmoniousness 0.0697 0.0233 2.0162 0.0442 0.0379 0.0066 − .0788 (0) − .0216 (.35) Holism 0.1231 0.0264 3.46 0.0006 0.0506 0.0191 − .1024 (0) − .0015 (.95) MultiThinking 0.084 0.024 2.3229 0.0205 0.0313 0.0088 − .0885 (0) − .0196 (.41) ZY 0.1014 0.0275 2.9316 0.0035 0.0434 0.0138 − .0909 (0) − .0078 (.74) Depression Education Harmoniousness -0.0511 0.0296 -1.2102 0.2267 0.0526 0.0023 − .0228 (.36) − .0664 (.01) Holism -0.0622 0.0343 -1.4029 0.1612 0.0405 0.0032 − .0204 (.44) − .0735 (0) MultiThinking -0.0537 0.0305 -1.215 0.2248 0.0307 0.0024 − .0212 (.42) − .067 (.01) ZY -0.07 0.0364 -1.5949 0.1113 0.0485 0.0041 − .0123 (.64) − .072 (0) Hukou Harmoniousness 0.0575 0.0924 1.3861 0.1662 0.0546 0.003 .0809 (.28) .2368 (0) Holism 0.1414 0.0937 3.7067 0.0002 0.058 0.0217 − .0186 (.79) .3646 (0) MultiThinking 0.0046 0.0886 0.1138 0.9094 0.0307 < 0.0001 .1515 (.04) .1639 (.05) ZY 0.0823 0.1065 2.0354 0.0423 0.0522 0.0066 .0486 (.5) .2718 (0) Income Harmoniousness -0.0115 < 0.0001 -0.2789 0.7804 0.0536 0.0001 0 (.06) 0 (.02) Holism -0.0007 < 0.0001 -0.018 0.9856 0.0405 < 0.0001 0 (.02) 0 (.02) MultiThinking -0.0269 < 0.0001 -0.7565 0.4497 0.0335 0.0009 0 (.07) 0 (.01) ZY -0.0245 < 0.0001 -0.6199 0.5356 0.0489 0.0006 0 (.09) 0 (.01) Ladder Harmoniousness 0.1024 0.0221 3.0537 0.0024 0.095 0.0142 − .1177 (0) − .0354 (.11) Holism 0.1477 0.0252 4.2628 < 0.0001 0.0991 0.0275 − .1412 (0) − .0225 (.3) MultiThinking 0.109 0.023 3.0873 0.0021 0.0775 0.0148 − .1248 (0) − .0373 (.1) ZY 0.132 0.0262 3.9339 0.0001 0.1002 0.0234 − .1292 (0) − .0232 (.29) LS Education Harmoniousness 0.0377 0.0591 0.8959 0.3707 0.0584 0.0013 − .034 (.5) .0305 (.54) Holism 0.0661 0.0682 1.5026 0.1335 0.0563 0.0036 − .0549 (.3) .0581 (.24) MultiThinking 0.0799 0.0604 1.8322 0.0674 0.0554 0.0053 − .0847 (.11) .0519 (.3) ZY 0.0722 0.0719 1.6683 0.0958 0.0741 0.0043 − .0751 (.15) .0484 (.32) Hukou Harmoniousness -0.0291 0.1844 -0.7048 0.4812 0.0634 0.0008 − .1317 (.37) − .2899 (.08) Holism -0.064 0.1876 -1.6823 0.093 0.0617 0.0045 − .031 (.83) − .379 (.02) MultiThinking 0.0274 0.1753 0.6867 0.4925 0.0559 0.0007 − .2659 (.07) − .1172 (.47) ZY -0.0211 0.211 -0.5278 0.5979 0.0742 0.0004 − .125 (.38) − .2397 (.14) Income Harmoniousness -0.0349 < 0.0001 -0.8515 0.3948 0.0691 0.0011 0 (.01) 0 (.22) Holism -0.0353 < 0.0001 -0.9273 0.3542 0.0662 0.0013 0 (.01) 0 (.19) MultiThinking -0.0541 < 0.0001 -1.5458 0.1227 0.0636 0.0038 0 (0) 0 (.41) ZY -0.0404 < 0.0001 -1.0374 0.3 0.0809 0.0017 0 (.01) 0 (.31) Ladder Harmoniousness -0.0423 0.0431 -1.2984 0.1946 0.1462 0.0024 .2682 (0) .2001 (0) Holism -0.0377 0.0492 -1.1193 0.2635 0.1488 0.0018 .2754 (0) .2147 (0) MultiThinking -0.0029 0.0445 -0.0864 0.9312 0.1377 < 0.0001 .243 (0) .2382 (0) ZY -0.0315 0.0508 -0.9696 0.3326 0.1562 0.0013 .2589 (0) .2082 (0) Meaning Education Harmoniousness -0.0234 0.0438 -0.5758 0.565 0.1218 0.0005 .0443 (.23) .0136 (.71) Holism 0.0522 0.0506 1.2277 0.22 0.1177 0.0022 − .0011 (.98) .0674 (.06) MultiThinking 0.0741 0.0451 1.7455 0.0814 0.1056 0.0046 − .0342 (.38) .0629 (.09) ZY 0.0415 0.053 0.9984 0.3185 0.1473 0.0014 − .0099 (.79) .0445 (.22) Hukou Harmoniousness -0.0212 0.1368 -0.5303 0.5961 0.1235 0.0004 − .0884 (.42) − .1767 (.15) Holism -0.1089 0.1387 -2.9684 0.0031 0.128 0.0129 .0941 (.37) − .3602 (0) MultiThinking 0.0076 0.131 0.195 0.8455 0.104 0.0001 − .1397 (.2) − .1081 (.37) ZY -0.0426 0.1552 -1.1108 0.2671 0.1489 0.0018 − .0195 (.85) − .197 (.1) Income Harmoniousness -0.0542 < 0.0001 -1.3678 0.1719 0.1309 0.0027 0 (.01) 0 (.47) Holism -0.0419 < 0.0001 -1.1375 0.2558 0.125 0.0019 0 (.01) 0 (.27) MultiThinking -0.001 < 0.0001 -0.0304 0.9758 0.1083 < 0.0001 0 (.08) 0 (.09) ZY -0.0194 < 0.0001 -0.5202 0.6031 0.1527 0.0004 0 (.05) 0 (.22) Ladder Harmoniousness -0.0372 0.0324 -1.1621 0.2456 0.1782 0.0019 .1682 (0) .1223 (0) Holism -0.078 0.0369 -2.3709 0.0181 0.1866 0.0077 .2032 (0) .1068 (0) MultiThinking -0.0227 0.0337 -0.6727 0.5014 0.1597 0.0006 .1633 (0) .1353 (0) ZY -0.0522 0.0379 -1.6559 0.0983 0.204 0.0037 .1742 (0) .1097 (0) ikigai Education Harmoniousness 0.0394 0.0304 0.9657 0.3346 0.1159 0.0014 .0194 (.45) .0552 (.03) Holism 0.0681 0.0354 1.5875 0.1129 0.1012 0.0038 .0098 (.72) .0717 (.01) MultiThinking 0.1095 0.0315 2.5548 0.0109 0.0884 0.01 − .0195 (.48) .08 (0) ZY 0.0878 0.0371 2.0894 0.0371 0.1285 0.0064 − .0093 (.73) .0705 (.01) Hukou Harmoniousness -0.0307 0.0952 -0.7664 0.4438 0.1171 0.0009 − .0936 (.22) − .1823 (.03) Holism -0.1151 0.0971 -3.1044 0.002 0.1101 0.0144 .0232 (.75) − .3093 (0) MultiThinking 0.0303 0.0918 0.7727 0.44 0.0832 0.0009 − .1754 (.02) − .0877 (.3) ZY -0.0421 0.109 -1.0835 0.279 0.1252 0.0017 − .0637 (.39) − .1854 (.03) Income Harmoniousness -0.032 < 0.0001 -0.8064 0.4203 0.1292 0.001 0 (0) 0 (.04) Holism -0.0335 < 0.0001 -0.9051 0.3658 0.1132 0.0012 0 (0) 0 (.03) MultiThinking -0.0202 < 0.0001 -0.5879 0.5568 0.0942 0.0005 0 (0) 0 (.02) ZY -0.0195 < 0.0001 -0.5168 0.6055 0.1362 0.0004 0 (0) 0 (.03) Ladder Harmoniousness -0.0252 0.0223 -0.7954 0.4267 0.1936 0.0009 .135 (0) .1135 (0) Holism -0.0655 0.0255 -1.9958 0.0464 0.1907 0.0054 .1587 (0) .1027 (0) MultiThinking -0.0386 0.0233 -1.1495 0.2508 0.1647 0.0019 .1437 (0) .1107 (0) ZY -0.0482 0.0262 -1.5295 0.1267 0.2048 0.0031 .1433 (0) .102 (0) The SES and moderator variables were mean-centered before forming products. The β reported in the table were standardized. Across outcomes, zhongyong reliably attenuated status gradients, with the clearest evidence for subjective SES and the symptom outcomes, as illustrated in Fig. 1 . For depression and anxiety, the ladder × zhongyong interactions were positive and significant ( β ≈ .10 – .13), indicating weaker negative SES slopes at higher zhongyong. Simple-slope analyses showed that among participants low in zhongyong, lower ladder standing predicted more symptoms (e.g., for depression, β ≈ −.13, p < .001), whereas at high zhongyong, the SES–symptom slope was reduced in magnitude and close to zero ( β ≈ −.02 – .04, ns). Predicted values from linear models with mean‑centered Ladder and moderator. Depicted lines show the Ladder-Symptoms slope at low (− 1 SD) and high (+ 1 SD) levels of zhongyong. A parallel but valence-reversed pattern emerged for meaning in life and ikigai. Ladder × zhongyong interactions were negative, indicating shallower positive SES slopes under higher zhongyong ( β ≈ −.05, p = .02 – .04). Simple slopes confirmed that meaning/ikigai rose with ladder at low zhongyong ( β ≈ .16 – .20, p < .001) but less so at high zhongyong ( β ≈ .10 – .11, p < .001), consistent with a buffering (slope-flattening) effect. For life satisfaction, ladder × zhongyong interactions trended in the same direction but were smaller and often not significant. Overall, H3 was supported. Objective SES indicators showed fewer and less consistent moderation effects. Interactions involving income were uniformly non-significant. For education and hukou, significant effects were sporadic and mixed. Even when significant, they were generally weaker than the ladder effects and sometimes departed from a strict buffering pattern. Across all tests, ladder interactions showed greater absolute effect sizes and a higher share of buffering-consistent effects (about half of ladder tests vs. ~ 1 in 9 for objective SES). H4 was supported. Collapsing across SES indicators and outcomes, Holism produced the largest average interaction magnitudes (mean β ≈ .069) and the most buffering-consistent significant effects. Global zhongyong ranked next (mean β ≈ .052). Multi-Perspective Thinking followed (mean β ≈ .046), and Harmoniousness was smallest (mean β ≈ .039) with the fewest significant cases. H5 was supported. 4. Discussion 4.1 Main findings This study set out to test whether zhongyong, a culturally grounded Eastern thinking style, buffers the socioeconomic gradient in well-being among adults in mainland China. Using a multifaceted outcome set that included both Western and Eastern indicators, and contrasting subjective with objective SES markers, three clear patterns emerged. First, we replicated the baseline SES–WB gradient: higher SES related to greater life satisfaction, meaning in life, and ikigai, and to lower depression and anxiety. Subjective SES displayed the largest and most consistent associations with well-being, whereas objective SES effects were smaller. These results align with prior work emphasizing the centrality of perceived standing for psychological functioning. Zhongyong also showed robust positive zero-order associations with well-being across the board, supporting the view that a balance-seeking, context-integrative cognitive style corresponds to better mental health and flourishing in contemporary Chinese contexts. Second, zhongyong buffered the SES-WB slope, most clearly when SES was indexed subjectively. For the symptom outcomes (depression, anxiety), Ladder × zhongyong interactions were positive and statistically reliable. Low‑status participants reported substantially fewer symptoms when high in zhongyong, and the typically steeper status–symptom slope observed at low zhongyong was attenuated toward zero at high zhongyong. For evaluative and eudaimonic outcomes like meaning in life and ikigai, Ladder × zhongyong interactions were negative and smaller in magnitude but consistent with the same buffering logic that the positive association between subjective SES and meaning or ikigai was shallower at higher zhongyong. By contrast, objective SES × zhongyong interactions were fewer, smaller, and less consistent. Our facet analyses also clarified that the Holism and Multi-perspective Thinking facets contributed more than the harmoniousness facet, suggesting that big-picture, integrative processing rather than relational harmony per se is the more active ingredient in buffering socioeconomic disadvantage. Notably, the moderating effects generalized across Western and Eastern outcome constructs: zhongyong not only protected life satisfaction and symptoms, but also ikigai, underscoring its relevance for both culturally indigenous and widely used well-being measures. 4.2 Contributions and implications This study made some theoretical contributions. First, it extended the Reserve Capacity Model (Gallo, de Los Monteros, & Shivpuri, 2009 ) with a culturally grounded cognitive resource. Our findings position the Eastern thinking style of zhongyong as a cultural resource that dampens the socioeconomic gradient in well-being, most clearly when status is construed subjectively. This extends the RCM beyond typical Western resource sets like perceived control, coping, and support. Second, it explored a culturally plural measurement model for well-being disparities. We coupled Western well-being variables like life satisfaction, meaning in life, depressive and anxious symptoms, and ikigai, an Eastern construct, with SES and an indigenous thinking style moderator. The integrated design offered a template for culture-aware disparities research that can be replicated across settings. We demonstrated that zhongyong’s protective effects generalized to an indigenous, relationally inflected sense of life worth, connecting cultural thinking styles to cultural forms of flourishing with demonstrated real-world significance. Third, this study identifying the more active ingredients within zhongyong that link most closely to protection under disadvantage. Facet analyses showed that the big-picture integrative processing rather than harmony-maintenance per se as the pivotal protective mechanism. This contributes to an emerging literature that anchors zhongyong in cognitive-emotional processes rather than only in social harmony scripts (Wu & Lin, 2005 ). This study has important practical implications too. As shown in this study and many prior research, low SES is associated with thwarted well-being. This study indicates that zhongyong-based trainings might effectively reduce depressive and anxious symptoms in Chinese samples, and improve well-being in both Eastern and Western measures. Psychological interventions can be designed for lower-status population, focusing on holistic information integration and multi-perspective reframing. Furthermore, this study suggests that indigenous psychological elements could function as cultural reserve capacities that flatten the socioeconomic gradient in well-being, implying that models of health and well-being disparities should explicitly incorporate culture-fit resources rather than treating psychosocial resources as culturally neutral. 4.3 Limitations and future directions There are several limitations in this study. First, the cross-sectional design of this study couldn’t provide any causal inference. Future research should adopt longitudinal or experimental designs to establish causal directionality. Second, our sample comprised Chinese adults and the moderator is an indigenous Chinese thinking style. The buffering we observe may be partly contingent on cultural fit, i.e., to the extent to which a mindset is normative and socially rewarded in each ecology. Prior cross-cultural work indicates that East-Asian psychological norms and styles are more strongly tied to adaptive emotion regulation and “balanced” well-being in East-Asian contexts, whereas in Western samples they can be neutral or even negatively related to certain well-being indicators (Butler, Lee, & Gross, 2007 ; Miyamoto & Ryff, 2011 ; Soto et al., 2011 ; Miyamoto et al., 2013 ; Kirchner-Häusler et al., 2023 ). Future research is needed to test the moderation model by zhongyong and other indigenous cultural constructs in non-Chinese populations. Third, our online recruited sample ensured variability but was not probability-based and may not mirror population distributions. Estimates may not be interpreted as population prevalences. Future research should be expanded to more representative and more diverse samples for better generalizing the findings. Declarations Author contributions YZ designed the study, analysed the data, and wrote the article. YM co-designed the study, translated the ikigai scale, and participated in writing of the article. JL ran the data collection. KP supervised the design and administration of the study. Ethical approval This study was approved by the Human Research Ethics Committee of the Department of Psychology and Cognitive Science of Tsinghua University. Declaration of Helsinki and the APA Ethical Principles were followed during the study. Consent to participate Informed consent was obtained from all participants involved in this study. Consent to publish Not Applicable. Data availability Data is provided within the supplementary information files. Clinical trial number Not applicable. Funding Declaration No funding was provided for this study. Competing interests The authors declare that there are no competing interests and no financial interest in the preparation of this article. References Adler, N. (2007). The MacArthur scale of subjective social status. MacArthur research network on SES & health . Butler, E. A., Lee, T. L., & Gross, J. J. (2007). Emotion regulation and culture: Are the social consequences of emotion suppression culture-specific?. Emotion , 7 (1), 30. Chou, L. F., Chu, C. C., Yeh, H. C., & Chen, J. (2014). Work stress and employee well‐being: The critical role of Z hong‐Y ong. Asian Journal of Social Psychology , 17 (2), 115-127. Cui, L., Tang, G., & Huang, M. (2022). Expressive suppression, confucian Zhong Yong thinking, and psychosocial adjustment among Chinese young adults. Asian Journal of Social Psychology , 25 (4), 715-730. Derogatis, L. R. (2001). BSI 18, Brief Symptom Inventory 18: Administration, scoring and procedures manual . NCS Pearson, Incorporated. Diener, E. D., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of personality assessment , 49 (1), 71-75. Fido, D., Kotera, Y., & Asano, K. (2020). English translation and validation of the Ikigai-9 in a UK sample. International Journal of Mental Health and Addiction , 18 (5), 1352-1359. Gallo, L. C., de Los Monteros, K. E., & Shivpuri, S. (2009). Socioeconomic status and health: what is the role of reserve capacity?. Current directions in psychological science , 18 (5), 269-274. Hajek, A., Imai, T., Zwar, L., & König, H. H. (2024). Translation and Validation of the German Version of the Ikigai-9. Societies , 14 (3), 39. Hittner, E. F., Rim, K. L., & Haase, C. M. (2019). Socioeconomic status as a moderator of the link between reappraisal and anxiety: Laboratory-based and longitudinal evidence. Emotion , 19 (8), 1478. Howell, R. T., & Howell, C. J. (2008). The relation of economic status to subjective well-being in developing countries: a meta-analysis. Psychological bulletin , 134 (4), 536. Imai, T. (2012). The reliability and validity of a new scale for measuring the concept of Ikigai (Ikigai-9). [Nihon koshu eisei zasshi] Japanese journal of public health , 59(7), 433-439. Johnson, W., & Krueger, R. F. (2006). How money buys happiness: genetic and environmental processes linking finances and life satisfaction. Journal of personality and social psychology , 90 (4), 680. Kahneman, D., & Deaton, A. (2010). High income improves evaluation of life but not emotional well-being. Proceedings of the national academy of sciences , 107 (38), 16489-16493. Killingsworth, M. A., Kahneman, D., & Mellers, B. (2023). Income and emotional well-being: A conflict resolved. Proceedings of the National Academy of Sciences , 120 (10), e2208661120. Kirchner-Häusler, A., De Leersnyder, J., Uskul, A. K., Mirzada, F., Vignoles, V. L., Rodríguez-Bailón, R., ... & Uchida, Y. (2023). Cultural fit of emotions and subjective well-being: replicating comparative evidence and extending it to the Mediterranean region. Current Research in Ecological and Social Psychology , 5 , 100171. Lachman, M. E., & Weaver, S. L. (1998). The sense of control as a moderator of social class differences in health and well-being. Journal of personality and social psychology , 74 (3), 763. Lee, A., Cheng, C. M. Y., Lee, L. Y., Esposito, G., & Cheon, B. K. (2023). Thanking in the times of the plague: The role of holistic thinking in meaning‐making and gratitude. Social and Personality Psychology Compass , 17 (11), e12854. Lee, S. J., & Wu, C. H. (2008). Comparing the level of positive tendency in a life satisfaction evaluation between Chinese and Western people. Social Indicators Research , 89 (1), 147-153. Lynch, T. R., Chapman, A. L., Rosenthal, M. Z., Kuo, J. R., & Linehan, M. M. (2006). Mechanisms of change in dialectical behavior therapy: Theoretical and empirical observations. Journal of clinical psychology , 62 (4), 459-480. Miyamoto, Y., Boylan, J. M., Coe, C. L., Curhan, K. B., Levine, C. S., Markus, H. R., ... & Ryff, C. D. (2013). Negative emotions predict elevated interleukin-6 in the United States but not in Japan. Brain, behavior, and immunity , 34 , 79-85. Miyamoto, Y., & Ryff, C. D. (2011). Cultural differences in the dialectical and non-dialectical emotional styles and their implications for health. Cognition and Emotion , 25 (1), 22-39. Nisbett, R. E., Peng, K., Choi, I., & Norenzayan, A. (2001). Culture and systems of thought: holistic versus analytic cognition. Psychological review , 108 (2), 291. Non, A. L., Román, J. C., Clausing, E. S., Gilman, S. E., Loucks, E. B., Buka, S. L., ... & Kubzansky, L. D. (2020). Optimism and social support predict healthier adult behaviors despite socially disadvantaged childhoods. International Journal of Behavioral Medicine , 27 (2), 200-212. Park, Y. (2015). Sense of “Ikigai”(reason for living) and social support in the Asia-Pacific region. Behaviormetrika , 42 (2), 191-208. Peng, K., Spencer-Rodgers, J., & Nian, Z. (2006). Naïve dialecticism and the Tao of Chinese thought. In Indigenous and cultural psychology: Understanding people in context (pp. 247-262). Boston, MA: Springer US. Ren, Z., Yue, G., Xiao, W., & Fan, Q. (2022). The influence of subjective socioeconomic status on life satisfaction: the chain mediating role of social equity and social trust. International Journal of Environmental Research and Public Health , 19 (23), 15652. Robins, C. J., & Rosenthal, M. Z. (2011). Dialectical behavior therapy. Acceptance and mindfulness in cognitive behavior therapy: Understanding and applying the new therapies , 164-192. Sone, T., Nakaya, N., Ohmori, K., Shimazu, T., Higashiguchi, M., Kakizaki, M., ... & Tsuji, I. (2008). Sense of life worth living (ikigai) and mortality in Japan: Ohsaki Study. Psychosomatic medicine , 70 (6), 709-715. Soto, J. A., Perez, C. R., Kim, Y. H., Lee, E. A., & Minnick, M. R. (2011). Is expressive suppression always associated with poorer psychological functioning? A cross-cultural comparison between European Americans and Hong Kong Chinese. Emotion , 11 (6), 1450. Spencer-Rodgers, J., Boucher, H. C., Mori, S. C., Wang, L., & Peng, K. (2009). The dialectical self-concept: Contradiction, change, and holism in East Asian cultures. Personality and Social Psychology Bulletin , 35 (1), 29-44. Spencer-Rodgers, J., & Peng, K. (Eds.). (2018). The psychological and cultural foundations of East Asian cognition: Contradiction, change, and holism . Oxford University Press. Spencer-Rodgers, J., Peng, K., Wang, L., & Hou, Y. (2004). Dialectical self-esteem and East-West differences in psychological well-being. Personality and Social Psychology Bulletin , 30 (11), 1416-1432. Steger, M. F., Frazier, P., Oishi, S., & Kaler, M. (2006). The meaning in life questionnaire: assessing the presence of and search for meaning in life. Journal of counseling psychology , 53 (1), 80. Tan, J. J., Kraus, M. W., Carpenter, N. C., & Adler, N. E. (2020). The association between objective and subjective socioeconomic status and subjective well-being: A meta-analytic review. Psychological bulletin , 146 (11), 970. Vandroux, R., & Auzoult-Chagnault, L. (2023). Validation francophone de l’échelle Ikigai-9. Psychologie française , 68 (4), 503-513. Wang, B., Zhao, H., Shen, H., & Jiang, Y. (2023). Socioeconomic status and subjective well-being: The mediating role of class identity and social activities. Plos one , 18 (9), e0291325. Wilkes, J., Garip, G., Kotera, Y., & Fido, D. (2023). Can Ikigai predict anxiety, depression, and well-being?. International Journal of mental health and addiction , 21 (5), 2941-2953. Wong, Y. J., Ho, R. M., Li, P., Shin, M., & Tsai, P. C. (2011). Chinese Singaporeans’ lay beliefs, adherence to Asian values, and subjective well-being. Personality and Individual Differences , 50 (6), 822-827. Wong, Y. J., & Liu, T. (2018). Dialecticism and mental health: Toward a yin-yang vision of well-being. Wu, C. H., & Lin, Y. C. (2005). Development of a Zhong-Yong thinking style scale. Indigenous Psychological Research in Chinese Societies , 24 , 247-300. Wu, W., Liu, Y., Yu, L., Guo, Z., Li, S., Guo, Z., ... & Zeng, Y. (2022). Relationship between family socioeconomic status and learning burnout of college students: the mediating role of subjective well-being and the moderating role of resilience. Frontiers in Psychology , 13 , 844173. Yao, Z. F., Yang, M. H., Yang, C. T., Chang, Y. H., & Hsieh, S. (2024). The role of attitudes towards contradiction in psychological resilience: the cortical mechanism of conflicting resolution networks. Scientific reports , 14 (1), 1669. Yang, X., Zhang, P., Zhao, J., Zhao, J., Wang, J., Chen, Y. U., ... & Zhang, X. (2016). Confucian culture still matters: The benefits of zhongyong thinking (doctrine of the mean) for mental health. Journal of Cross-Cultural Psychology , 47 (8), 1097-1113. Ye, R., Shen, J., Mo, Q., Xu, P., Huang, Y., Chen, J., ... & Gao, Y. (2025). The roles of physical activity and sedentary behavior in the relationship between socioeconomic status and depressive symptoms: Observations from a national study. Journal of Affective Disorders , 372 , 1-9. Zhao, S., Du, H., Li, Q., Wu, Q., & Chi, P. (2021). Growth mindset of socioeconomic status boosts subjective well-being: A longitudinal study. Personality and Individual Differences , 168 , 110301. Zhao, S., & Peng, L. (2021). Feeling matters: perceived social support moderates the relationship between personal relative deprivation and depressive symptoms. BMC psychiatry , 21 (1), 345. Zhao, Y., Yu, F., Jing, B., Hu, X., Luo, A., & Peng, K. (2019). An analysis of well-being determinants at the city level in China using big data. Social Indicators Research , 143 (3), 973-994. Zhou, S., & Li, X. (2022). Zhongyong thinking style and resilience capacity in chinese undergraduates: the chain mediating role of cognitive reappraisal and positive affect. Frontiers in Psychology , 13 , 814039. Additional Declarations No competing interests reported. Supplementary Files AppendixTables.docx Zhongyongstudyrawdata.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":140586,"visible":true,"origin":"","legend":"\u003cp\u003eModeration effects of zhongyong on the Ladder and Emotional Symptoms\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7751702/v1/86a6386994d5f33d747ccfc9.png"},{"id":107515391,"identity":"25cd1186-d5f4-4df8-a452-3f15e691feb2","added_by":"auto","created_at":"2026-04-22 08:28:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1162212,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7751702/v1/c246c16b-7cbf-472c-b966-f58065c9f0ce.pdf"},{"id":96243307,"identity":"7b96a2f7-2beb-46b9-82bb-1506d0f9e74d","added_by":"auto","created_at":"2025-11-19 07:16:01","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":46329,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7751702/v1/6b245c6aa0421ac121ba2568.docx"},{"id":95916307,"identity":"82da76e3-0cf4-4543-be02-93e9eec6b1c3","added_by":"auto","created_at":"2025-11-14 11:51:09","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":118356,"visible":true,"origin":"","legend":"","description":"","filename":"Zhongyongstudyrawdata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7751702/v1/467836c836c0d857b138f0fd.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Eastern Zhongyong Thinking Style Buffers the Socioeconomic Gradient in Well-Being","fulltext":[{"header":"1. Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 The relationship between socioeconomic status (SES) and well-being\u003c/h2\u003e\u003cp\u003eDecades of research show that people with higher SES report better well-being than those with fewer resources. For example, Kahneman \u0026amp; Deaton (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) used data from more than 450,000 U.S. respondents and found that life evaluation rose steadily with log income, whereas emotional well-being rose with income up to a threshold and then plateaued. More recently, Killingsworth, Kahneman, \u0026amp; Mellers (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that emotional well-being continues to rise with income for most people, with a flattening only among the least happy. Meta-analytic evidence also supports a positive link between economic status and subjective well-being across diverse contexts, with stronger effects where material scarcity is greater (Howell \u0026amp; Howell, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVarious mechanisms were proposed to explain this relationship. Most notably, perceived control (Johnson \u0026amp; Krueger, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), social comparison (Ren et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and perceived fairness (Ren et. al, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were found to mediate the influence of SES to well-being. Not surprisingly, subjective SES is often a stronger predictor than objective SES, because it is how people perceive their SES, rather than what their actual SES is, that affects these variables. Indeed, a large meta-analysis of 357 studies (N\u0026thinsp;=\u0026thinsp;2.35\u0026nbsp;million) showed that subjective SES correlated more strongly with subjective well-being (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.22) than did objective SES (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.16), and subjective SES also partly mediated the association between objective SES and well-being association, consistent with the idea that perceived status translate resources into felt quality of life (Tan, Kraus, Carpenter, \u0026amp; Adler, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Protective factors buffering the SES-WB relationship\u003c/h2\u003e\u003cp\u003eA growing body of research has identified various factors that can buffer the impact of low SES on well-being. First, Social factors. The availability of support can help offset the stresses associated with low income or social disadvantages. For example, Zhao \u0026amp; Peng (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that when perceived social support was high, the association between relative deprivation and depression was significantly weaker. Similarly, Non et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that adults who had higher social support in mid-life were more likely to engage in healthy behaviors regardless of their disadvantaged childhood SES. Second, psychological factors. For example, optimism has been identified as a protective factor in the face of adversity. Non et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) showed that in those who had a disadvantaged childhood, higher optimism in adulthood predicted healthier behaviors despite their early SES disadvantage. Similarly, resilience could entail adaptability, perseverance, and positive coping that protect well-being under socioeconomic stress. Evidence from a Chinese college student sample illustrated that resilience moderated the link between family SES and academic burnout, so that low-SES students with high resilience showed much lower levels of learning burnout compared to low-resilience students of similar SES (Wu et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Third, behavioural factors. For example, physical activity can benefit mood, reduce stress, and improve health, which will be especially valuable for those under high stress or economic hardship. A recent large-scale study found that moderate-to-vigorous physical activity (\u0026ge;\u0026thinsp;150 minutes/week) buffered against the risk of depressive symptoms in low-SES individuals (Ye et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This buffering effect was particularly strong among those who were unemployed, a severe SES disadvantage group.\u003c/p\u003e\u003cp\u003eCognitive factors were also found to be effective buffers against low SES. Most notably, the growth mindset of SES itself, i.e., the belief that one\u0026rsquo;s SES can change and improve with effort, as opposed to the fixed mindset of SES, that sees SES as a fixed, unchangeable status. In a large longitudinal study using national survey data, Zhao et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that those with a growth mindset did not show as large a drop in well-being when SES was low, compared to those with a fixed mindset. Another example is a person\u0026rsquo;s perceived control over life outcomes. Lachman \u0026amp; Weaver (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) demonstrated that a strong sense of control can virtually eliminate class disparities in well-being. In their analysis of thousands of adults, higher perceived control was linked to better health, greater life satisfaction, and lower depression across the board. Critically, they found that low-income individuals who maintained a high sense of control had levels of health and well-being comparable to those of higher-income individuals. In contrast, low-income individuals with low control fared worse. This means beliefs on control act as a protective shield for low-SES individuals, offsetting some negative effects of socioeconomic hardship.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e1.3 East Asian thinking styles and well-being\u003c/h2\u003e\u003cp\u003eThis article aims to explore the moderating role of East Asian thinking styles on the SES-WB relationship. Peng, Spencer-Rodgers, \u0026amp; Nian (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) identified the characteristics of East Asian cognition as tolerance of contradiction, mindset of change, and holism. They were found to facilitate well-being, particularly for those facing adversities (Spencer-Rodgers \u0026amp; Peng, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). First, the East Asian thinking styles help people to accept contradiction and change in life, which in turn support their adaptation. Spencer-Rodgers et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) found that those high on holistic cognition do not insist on consistency in their attitudes or self-concepts across situations, making them more flexibly adapt to dynamic environments. Similarly, openness to contradiction has been associated with psychological resilience. Yao et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that people with a holistic mindset are more resilient and have more adaptive coping when facing complex life problems. This flexibility offsets the negative impact of adversity to well-being that happens more often in low SES population.\u003c/p\u003e\u003cp\u003eSecond, East Asian thinking styles encourages contextual thinking and integration of information from bigger scope (Nisbett et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) This is protective to well-being of low SES people. For instance, if something bad happens, a holistic thinker might recognize situational factors instead of blaming their own fixed traits. Research in cross-cultural psychology shows East Asians tend to downplay dispositional blame in favor of situational explanations, compared to Westerners (Wong \u0026amp; Liu, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Holistic thinking can also lead people to find meaning and gratitude in adversity. During the COVID-19 pandemic, for example, individuals high in holistic thinking were markedly better at deriving meaning from the crisis and feeling gratitude despite hardships (Lee et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) In contrast, those low in holistic thinking had more difficulty seeing anything beyond isolated negatives. Crucially, gratitude and meaning are well-known predictors of psychological resilience and lower depression.\u003c/p\u003e\u003cp\u003eThird, East Asian thinking is tightly linked with the dialectical ethos of emotional moderation. Individuals with dialectical beliefs often aim for moderate emotions rather than pure positivity. They believe happiness and sadness can co-exist and that emotional states inevitably change, and refrain from chasing extreme happiness and accept negative experiences as natural (Miyamoto \u0026amp; Ryff, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Indeed, the Dialectical Behavior Therapy was developed based on the Eastern dialectical principles, to teach clients to accept reality while working on change (Robins \u0026amp; Rosenthal, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). DBT\u0026rsquo;s success in treating borderline personality disorder and emotion dysregulation highlights how embracing opposites can foster emotional regulation, stress tolerance, and self-compassion, all key ingredients of well-being (Lynch et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e1.4 Zhongyong (ZY) as a moderator of the SES-WB relationship\u003c/h2\u003e\u003cp\u003e\u003cem\u003eZhongyong\u003c/em\u003e (中庸), often translated as \u0026ldquo;Doctrine of the Mean\u0026rdquo;, a paragon of East Asian thinking style that emphasizes moderation, multi-perspective integration, contextual fit, and harmony-maintenance. It advocates avoidance of extremes while adjusting one\u0026rsquo;s stance to the situation. Modern psychology operationalizes it with the zhongyong Thinking Style Scale (ZYTS; Wu \u0026amp; Lin, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which captures three facets: multi-thinking (considering multiple perspectives), holism (integrating information to see the whole), and harmoniousness (context-appropriate, harmony-preserving responding). Yang et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) showed that higher zhongyong is linked to lower depression and anxiety and higher life satisfaction and self-esteem. Furthermore, their experimental study revealed that zhongyong thinking training can lead to less depressive symptoms compared with the control group. Zhongyong also has a robust positive associations with resilience, partly via cognitive reappraisal and positive affect as well as context-sensitive appraisal style (Zhou \u0026amp; Li, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In work settings, zhongyong attenuates the harmful effects of hindrance stress on emotional exhaustion and job satisfaction, and helps employees channel some challenge stress into eustress (Chou et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Among Chinese young adults, zhongyong is positively associated with psychosocial well-being and negatively with adjustment problems, and more importantly, buffers the typically negative association between expressive suppression and psychosocial adjustment (Cui, Tang, \u0026amp; Huang, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Together, these findings converge on a picture of zhongyong as a psychological resource that stabilizes affect, supports adaptive reappraisal, and sustains well-being, as well as weaken the impact of certain stressors on mental health.\u003c/p\u003e\u003cp\u003eDespite this pattern, we found no published study directly testing zhongyong as a moderator of the relationship between SES and well-being. The Reserve Capacity Model (RCM, Gallo, de Los Monteros, \u0026amp; Shivpuri, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) predicts that individuals\u0026rsquo; appraisal and regulation resources buffer the emotional toll of disadvantage. Zhongyong is precisely such a resource that promotes reappraisal and context-appropriate responding. Moreover, as shown earlier in this article, subjective SES is often a stronger predictor of well-being than objective SES. As zhongyong shapes how status is construed and emotionally managed, it should blunt the negative slope from subjective low SES to poorer well-being, much as it already buffers work stress and maladaptive regulation. Therefore, zhongyong, especially its cognitive components of multiple perspective taking and holism, fits the profile of a culturally situated reserve capacity that could buffer the negative impact of low SES to well-being.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e1.5 Ikigai as an Eastern indicator of well-being\u003c/h2\u003e\u003cp\u003eThere are also research showing that individuals high in East Asian thinking sometimes score lower on life satisfaction and positive affect (Wong \u0026amp; Liu, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Multiple studies have noted that stronger dialectical self-beliefs correlate with lower reported SWB or self-esteem in East Asian samples (Spencer-Rodgers et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Lee \u0026amp; Wu, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e ; Wong et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, this appears to be an artifact of measurement and cultural definition of happiness. Because dialectical individuals do not equate well-being with maximizing positive emotions alone, they report moderate happiness by choice. Importantly, accepting negativity is not seen as \u0026ldquo;unhappy\u0026rdquo; in dialectical culture. Researchers point out that dialectical lay beliefs about happiness lead people to value calm contentment over exuberance (Wong \u0026amp; Liu, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, while East Asian thinkings might appear to lower happiness on Western metrics, it actually reflects a different, balanced form of well-being.\u003c/p\u003e\u003cp\u003eTo make a culturally accurate case, our outcomes should not be limited to Western indicators. This study includes \u003cem\u003eikigai\u003c/em\u003e as an Eastern construct and measurement of well-being. Ikigai is a Japanese term, literally meaning \u0026ldquo;a reason for living\u0026rdquo;. It captures a blend of daily purpose, engagement, and a sense of being needed that Western scales only partially tap. Empirically, ikigai is robustly associated with better mental health and life evaluation and has been linked to lower all-cause mortality in a large Japanese cohort, underscoring criterion importance beyond self-reports (Sone et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). At the same time, ikigai has proven measurable and reliable outside Japan, with validated translations in UK (Fido, Kotera, \u0026amp; Asano, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), France (Vandroux \u0026amp; Auzoult-Chagnault, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Germany (Hajek et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and a mixed sample of participants from North America and Europe (Wilkes et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, cross-national survey work in the Asia-Pacific found ikigai was a transferable construct tied to social resources, suggesting it indexes culturally salient pathways to well-being that are meaningful in East Asian settings like China and South Korea (Park, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, including ikigai as a DV lets us test whether zhongyong protects both Western and Eastern well-being constructs that matters for flourishing in Chinese contexts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e1.6 The current study\u003c/h2\u003e\u003cp\u003eThe current study tests whether zhongyong, an indigenous Chinese thinking style, buffers the SES gradient in well-being in mainland China. We operationalize well-being multifacetedly, spanning both Western and Eastern indicators, and covering both the positive and the negative measures. Because subjective SES often tracks well-being more strongly than objective SES, we examine both and explicitly contrast their associations and interactions with zhongyong. Beyond a global zhongyong effect, we ask which facets, namely multi-perspective thinking, holism, or harmony-maintenance, carry the most buffering. We hypothesize that:\u003c/p\u003e\u003cp\u003eH1: Lower SES relates to lower SWLS, meaning in life, and ikigai, and higher depression/anxiety; subjective SES will show stronger effects than objective SES.\u003c/p\u003e\u003cp\u003eH2: Higher zhongyong predicts higher SWLS, meaning in life, ikigai and lower depression/anxiety (positive main effects across outcomes).\u003c/p\u003e\u003cp\u003eH3: zhongyong moderates the SES-WB relationship, so that the SES\u0026ndash;WB slope is weaker at high zhongyong, i.e., low-SES participants with high zhongyong report relatively preserved well-being.\u003c/p\u003e\u003cp\u003eH4: Perceived SES \u0026times; zhongyong interactions are larger than objective SES \u0026times; zhongyong interactions.\u003c/p\u003e\u003cp\u003eH5: Multi-perspective thinking and holism contribute the bigger parts of buffering than harmoniousness.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants\u003c/h2\u003e\u003cp\u003eWe recruited N\u0026thinsp;=\u0026thinsp;600 adults residing in mainland China via an online survey platform. Two attention checks were added to the survey. All participants passed them. To ensure variability of SES, we balanced their gender, age, income, education, region, and hukou (the Chinese household registration system that divide people into urban and rural residents). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reports the sample characteristics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eSummary of sample SES\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategorical Indicators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\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=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle School or Lower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior College\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContinuous Indicators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly Income (RMB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15,165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16,566\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measures\u003c/h2\u003e\u003cp\u003e\u003cem\u003eSocioeconomic Status\u003c/em\u003e. The objective SES measures included individual monthly income and education level. Two China-specific measures were also collected. First, \u003cem\u003ehukou\u003c/em\u003e. It\u0026rsquo;s a Chinese household registration system that records a person's basic information and permanent residence and determines where citizens can access public services and benefits. It has two major categories: rural and urban residents. The rural hukou is widely considered less privileged than the urban hukou. Second, the tier of the cities. The megacities like Beijing and Shanghai are considered the tier-1 cities of China. Other cities are also rated mainly based on economical indices, like GDP per capita, population, and job opportunities. The smaller the tier number is, the more prosperous a city is. The subjective SES was measured using the MacArthur Scale of Subjective Social Status (society ladder, Adler, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Participants were presented a picture of a 10-rung ladder depicting society, with higher rungs indicating higher standing. They indicated the rung that best represented their standing in society. This single-item measure is widely used and shows robust associations with well-being and health.\u003c/p\u003e\u003cp\u003e\u003cem\u003ezhongyong Thinking style\u003c/em\u003e. Zhongyong was measured with the zhongyong Thinking Style Scale (ZYTS, Wu \u0026amp; Lin, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which operationalizes the balance-seeking cognitive style across three facets: multi-thinking, holism, and harmoniousness. It has 13 items, e.g. \u0026ldquo;I am used to thinking about the same thing from multiple perspectives\u0026rdquo; (multi-thinking), \u0026ldquo;I will try to integrate my opinions into the ideas of others\u0026rdquo; (holism), \u0026ldquo;I usually express conflicting opinions in a tactful way\u0026rdquo; (harmoniousness). Items were rated on a 5-point scale from \u003cem\u003every inconsistent\u003c/em\u003e to \u003cem\u003every consistent\u003c/em\u003e, with higher scores indicating stronger zhongyong style. Prior work demonstrates adequate reliability/validity and the three-facet structure. In this study, the Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e for these three dimensions and the whole scale were .723, .747, .736, and .878 respectively.\u003c/p\u003e\u003cp\u003e\u003cem\u003eLife satisfaction.\u003c/em\u003e Global life evaluation was assessed with the Satisfaction With Life Scale (SWLS, Diener et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). It has 5 items on cognitive judgments of one\u0026rsquo;s life, e.g., \u0026ldquo;In most ways my life is close to my ideal.\u0026rdquo; Items were rated on a 7-point scale from \u003cem\u003estrongly agree\u003c/em\u003e to \u003cem\u003estrongly disagree\u003c/em\u003e, with lower scores indicating greater life satisfaction. We reversed the scores during data analysis so that the scores can reflect the level of life satisfaction directly. The SWLS has good psychometrics and is widely used as a narrow-band measure of life satisfaction. In this study, the Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e for the scale was .887.\u003c/p\u003e\u003cp\u003e\u003cem\u003eMeaning in life.\u003c/em\u003e The Presence subscale of the Meaning in Life Questionnaire (Steger et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) to assess the sense of meaningfulness a person feels in life. It has 5 items, e.g., \u0026ldquo;I understand my life\u0026rsquo;s meaning\u0026rdquo;, including one reverse-scored item, \u0026ldquo;My life has no clear purpose\u0026rdquo;. Items were rated on a 7-point scale from \u003cem\u003estrongly agree\u003c/em\u003e to \u003cem\u003estrongly disagree\u003c/em\u003e, with lower scores indicating greater meaning in life. We reversed the scores during data analysis so that the scores can reflect the level of meaning in life directly. In this study, the Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e for the scale was .846.\u003c/p\u003e\u003cp\u003e\u003cem\u003eDepression and anxiety.\u003c/em\u003e Emotional symptoms were assessed over the past week with the Depression and Anxiety sub-dimensions of the Brief Symptom Inventory-18 (Derogatis, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Each sub-dimension consists of 6 items, e.g., \u0026ldquo;Feeling no interest in things\u0026rdquo; (depression), \u0026ldquo;Spells of terror or panic\u0026rdquo; (anxiety). Items were rated on a 5-point scale from \u003cem\u003enot at all\u003c/em\u003e to \u003cem\u003eextremely\u003c/em\u003e, with higher scores indicating more severe symptoms. In this study, the Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e for the depression and anxiety sub-dimensions were .868 and .902 respectively.\u003c/p\u003e\u003cp\u003e\u003cem\u003eIkigai.\u003c/em\u003e Ikigai was measured with the Ikigai-9 scale (Imai, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It has 9 items, e.g., \u0026ldquo;I think my existence is needed by something or someone\u0026rdquo;. They are rated on a 5-point scale from \u003cem\u003estrongly agree\u003c/em\u003e to \u003cem\u003estrongly disagree\u003c/em\u003e, with lower scores indicating greater ikigai. We reversed the scores during data analysis so that the scores can reflect the level of ikigai directly. In this study, the Cronbach\u0026rsquo;s \u003cem\u003eα\u003c/em\u003e for the scale was .879.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Procedure\u003c/h2\u003e\u003cp\u003eThe survey was administered online in Chinese. Data was analysed using RStudio 2025.05.0.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Main effects\u003c/h2\u003e\u003cp\u003eSince this study adopts a cross-sectional design, we estimated a common latent factor (CLF) CFA with equal loadings on all items and the CLF constrained orthogonal to the substantive factors to evaluate potential common-method variance. Results showed that adding the CLF did not meaningfully alter the measurement model. Standardized trait loadings were identical before vs. after including the method factor. Global fit indices changed trivially, and the equal CLF loading was negligible. These results indicate that common-method variance is unlikely to account for the observed correlations or the moderation patterns analyzed in this study.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows correlations among the study variables. Age showed small but interpretable associations with SES and well‑being. Older participants tended to reside in higher‑tier cities (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.121, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003), reported lower formal education (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.545, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and slightly higher life satisfaction (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.081, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.047). Correlations of age with other SES indicators, zhongyong, and other well-being variables were near zero. The gender differences were significant in income (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.119, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003), indicating that women make less money than men in China. But the gender differences in other SES variables, zhongyong, and well-being variables were uniformly small or insignificant.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eCorrelations of SES, zhongyong, and well-being variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\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=\"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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.100*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTier\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.121**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.545**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.205**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.155**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.119**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.116**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.330**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.179**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.196**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.263**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\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\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ezhongyong\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.120**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.141**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.114**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.130**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLife Satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.081*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.095*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.122**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.127**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.324**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.264**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMeaning in Life\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.085*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.091*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.141**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.081*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.128**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.283**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.381**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.565**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.128**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.126**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.139**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.229**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.185**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.465**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.516**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.099*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.146**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.406**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.108**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.338**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.781**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIkigai\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.087*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.120**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.145**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.118**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.175**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.333**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.715**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.342**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.631**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.618**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.451**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e. \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eAs expected, higher SES was associated with better well‑being across indicators. The subjective SES exhibited the largest and most consistent links. The ladder of perceived status correlated with higher life satisfaction (\u003cem\u003er\u003c/em\u003e =. 324, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), greater meaning (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.283, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), higher ikigai (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.333, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and lower depression (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.229, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and anxiety (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.146, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Objective SES indicators showed the same general pattern with smaller magnitudes. Income related to higher life satisfaction, meaning in life, and ikigai, and fewer depressive and anxiety symptoms. Education correlated positively with meaning in life and ikigai and negatively with depression. Its association with life satisfaction and anxiety were negligible.\u003c/p\u003e\u003cp\u003eHukou also tracked well‑being. Further independent \u003cem\u003et\u003c/em\u003e-test showed that those registered in urban hukou had significantly higher levels of life satisfaction (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.332, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.020), meaning in life (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.239, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.026), ikigai (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.965, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003), and lower levels of depression (\u003cem\u003et\u003c/em\u003e = -3.151, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.002) than their fellow compatriots in rural hukou. In line with prior research, SES predicted well-being variables, and the associations of the subjective SES with WB were stronger than those of the objective SES with WB.\u003c/p\u003e\u003cp\u003eThe only SES indicator that didn\u0026rsquo;t correlate negatively with well-being was the city tier, which correlated positively with life satisfaction, meaning in life, and ikigai, with near‑zero links to negative symptoms. This was probably because the degree of prosperity of a city doesn\u0026rsquo;t necessary reflect a person\u0026rsquo;s SES directly, especially the perceived SES. Prior research also showed that the relationship between city population and wealth and well-being was not linear (Zhao et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Overall, H1 was supported.\u003c/p\u003e\u003cp\u003eHigher zhongyong was also associated with higher well-being. The correlations were significant between zhongyong and life satisfaction (\u003cem\u003er\u003c/em\u003e =. 264, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), meaning in life (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.381, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), ikigai (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.342, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), depression (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.185, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and anxiety (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.108, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). H2 was supported.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Moderations\u003c/h2\u003e\u003cp\u003eWe estimated 80 moderation models (4 SES indicators \u0026times; 5 well-being outcomes \u0026times; 4 zhongyong indices). City tier was not included because it was not a negative predictor of well-being. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the parameters of the model results.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\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\u003eSummary of moderation models\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSES\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eΔR\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSlope of SES @ Low ZY (p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSlope of SES @ High ZY (p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c12\" namest=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.8071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0146 (.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0528 (.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.5479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0108 (.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0496 (.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.3604\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0262 (.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0653 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.2967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0277 (.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0613 (.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.1853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0471 (.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0917 (.29)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.7661\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1197 (.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1774 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0547\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.3385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.045 (.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1064 (.21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.0378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0889 (.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1432 (.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.9953\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.38)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.1002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.0162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0788 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0216 (.35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1024 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0015 (.95)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.3229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0088\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0885 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0196 (.41)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0909 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0078 (.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.2102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0228 (.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0664 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.4029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0204 (.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0735 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0212 (.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.067 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.5949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0123 (.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.072 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0575\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.3861\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1662\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0809 (.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2368 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.7067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0186 (.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.3646 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1515 (.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1639 (.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.0354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0486 (.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2718 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.2789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.7804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0536\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.7565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.6199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.0537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1177 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0354 (.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.2628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1412 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0225 (.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.0873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1248 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0373 (.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.9339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1292 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0232 (.29)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.8959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.034 (.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0305 (.54)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0661\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0549 (.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0581 (.24)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0604\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.8322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0847 (.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0519 (.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6683\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0958\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0751 (.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0484 (.32)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.7048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1317 (.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.2899 (.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.6823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0617\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.031 (.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.379 (.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.6867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.2659 (.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1172 (.47)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0742\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.125 (.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.2397 (.14)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.8515\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.9273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0662\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.5458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.41)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.0374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.2984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.2682 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2001 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0492\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2635\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.2754 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2147 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.0864\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.243 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2382 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.9696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.2589 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.2082 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeaning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0443 (.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0136 (.71)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2277\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0011 (.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0674 (.06)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0342 (.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0629 (.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.9984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0099 (.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0445 (.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0884 (.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1767 (.15)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.9684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0941 (.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.3602 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.131\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1397 (.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1081 (.37)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0195 (.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.197 (.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.3678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.47)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.0304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1621\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1682 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1223 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.3709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.2032 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1068 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.6727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1633 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1353 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.6559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1742 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1097 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eikigai\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.9657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0194 (.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0552 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0098 (.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0717 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.5548\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0195 (.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.08 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.0894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0093 (.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.0705 (.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.7664\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0936 (.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1823 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.1151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0971\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.1044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.0232 (.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.3093 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.7727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1754 (.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0877 (.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.0835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.0637 (.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.1854 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.8064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1292\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.9051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3658\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.5168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.6055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e0 (.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLadder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarmoniousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.7954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.135 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1135 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.9958\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0464\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1587 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1027 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiThinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.1495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.1647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1437 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.1107 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.5295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.2048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.0031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.1433 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u003cp\u003e.102 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe SES and moderator variables were mean-centered before forming products. The \u003cem\u003eβ\u003c/em\u003e reported in the table were standardized.\u003c/p\u003e\u003cp\u003eAcross outcomes, zhongyong reliably attenuated status gradients, with the clearest evidence for subjective SES and the symptom outcomes, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For depression and anxiety, the ladder \u0026times; zhongyong interactions were positive and significant (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.10 \u0026ndash; .13), indicating weaker negative SES slopes at higher zhongyong. Simple-slope analyses showed that among participants low in zhongyong, lower ladder standing predicted more symptoms (e.g., for depression, \u003cem\u003eβ\u003c/em\u003e \u0026asymp; \u0026minus;.13, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), whereas at high zhongyong, the SES\u0026ndash;symptom slope was reduced in magnitude and close to zero (\u003cem\u003eβ\u003c/em\u003e \u0026asymp; \u0026minus;.02 \u0026ndash; .04, ns).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePredicted values from linear models with mean‑centered Ladder and moderator. Depicted lines show the Ladder-Symptoms slope at low (\u0026minus;\u0026thinsp;1 SD) and high (+\u0026thinsp;1 SD) levels of zhongyong.\u003c/p\u003e\u003cp\u003eA parallel but valence-reversed pattern emerged for meaning in life and ikigai. Ladder \u0026times; zhongyong interactions were negative, indicating shallower positive SES slopes under higher zhongyong (\u003cem\u003eβ\u003c/em\u003e \u0026asymp; \u0026minus;.05, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.02 \u0026ndash; .04). Simple slopes confirmed that meaning/ikigai rose with ladder at low zhongyong (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.16 \u0026ndash; .20, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) but less so at high zhongyong (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.10 \u0026ndash; .11, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), consistent with a buffering (slope-flattening) effect. For life satisfaction, ladder \u0026times; zhongyong interactions trended in the same direction but were smaller and often not significant. Overall, H3 was supported.\u003c/p\u003e\u003cp\u003eObjective SES indicators showed fewer and less consistent moderation effects. Interactions involving income were uniformly non-significant. For education and hukou, significant effects were sporadic and mixed. Even when significant, they were generally weaker than the ladder effects and sometimes departed from a strict buffering pattern. Across all tests, ladder interactions showed greater absolute effect sizes and a higher share of buffering-consistent effects (about half of ladder tests vs. ~ 1 in 9 for objective SES). H4 was supported.\u003c/p\u003e\u003cp\u003eCollapsing across SES indicators and outcomes, Holism produced the largest average interaction magnitudes (mean \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.069) and the most buffering-consistent significant effects. Global zhongyong ranked next (mean \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.052). Multi-Perspective Thinking followed (mean \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.046), and Harmoniousness was smallest (mean \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;.039) with the fewest significant cases. H5 was supported.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Main findings\u003c/h2\u003e\u003cp\u003eThis study set out to test whether zhongyong, a culturally grounded Eastern thinking style, buffers the socioeconomic gradient in well-being among adults in mainland China. Using a multifaceted outcome set that included both Western and Eastern indicators, and contrasting subjective with objective SES markers, three clear patterns emerged. First, we replicated the baseline SES\u0026ndash;WB gradient: higher SES related to greater life satisfaction, meaning in life, and ikigai, and to lower depression and anxiety. Subjective SES displayed the largest and most consistent associations with well-being, whereas objective SES effects were smaller. These results align with prior work emphasizing the centrality of perceived standing for psychological functioning. Zhongyong also showed robust positive zero-order associations with well-being across the board, supporting the view that a balance-seeking, context-integrative cognitive style corresponds to better mental health and flourishing in contemporary Chinese contexts.\u003c/p\u003e\u003cp\u003eSecond, zhongyong buffered the SES-WB slope, most clearly when SES was indexed subjectively. For the symptom outcomes (depression, anxiety), Ladder \u0026times; zhongyong interactions were positive and statistically reliable. Low‑status participants reported substantially fewer symptoms when high in zhongyong, and the typically steeper status\u0026ndash;symptom slope observed at low zhongyong was attenuated toward zero at high zhongyong. For evaluative and eudaimonic outcomes like meaning in life and ikigai, Ladder \u0026times; zhongyong interactions were negative and smaller in magnitude but consistent with the same buffering logic that the positive association between subjective SES and meaning or ikigai was shallower at higher zhongyong. By contrast, objective SES \u0026times; zhongyong interactions were fewer, smaller, and less consistent. Our facet analyses also clarified that the Holism and Multi-perspective Thinking facets contributed more than the harmoniousness facet, suggesting that big-picture, integrative processing rather than relational harmony per se is the more active ingredient in buffering socioeconomic disadvantage. Notably, the moderating effects generalized across Western and Eastern outcome constructs: zhongyong not only protected life satisfaction and symptoms, but also ikigai, underscoring its relevance for both culturally indigenous and widely used well-being measures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Contributions and implications\u003c/h2\u003e\u003cp\u003eThis study made some theoretical contributions. First, it extended the Reserve Capacity Model (Gallo, de Los Monteros, \u0026amp; Shivpuri, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) with a culturally grounded cognitive resource. Our findings position the Eastern thinking style of zhongyong as a cultural resource that dampens the socioeconomic gradient in well-being, most clearly when status is construed subjectively. This extends the RCM beyond typical Western resource sets like perceived control, coping, and support. Second, it explored a culturally plural measurement model for well-being disparities. We coupled Western well-being variables like life satisfaction, meaning in life, depressive and anxious symptoms, and ikigai, an Eastern construct, with SES and an indigenous thinking style moderator. The integrated design offered a template for culture-aware disparities research that can be replicated across settings. We demonstrated that zhongyong\u0026rsquo;s protective effects generalized to an indigenous, relationally inflected sense of life worth, connecting cultural thinking styles to cultural forms of flourishing with demonstrated real-world significance. Third, this study identifying the more \u003cem\u003eactive ingredients\u003c/em\u003e within zhongyong that link most closely to protection under disadvantage. Facet analyses showed that the big-picture integrative processing rather than harmony-maintenance per se as the pivotal protective mechanism. This contributes to an emerging literature that anchors zhongyong in cognitive-emotional processes rather than only in social harmony scripts (Wu \u0026amp; Lin, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study has important practical implications too. As shown in this study and many prior research, low SES is associated with thwarted well-being. This study indicates that zhongyong-based trainings might effectively reduce depressive and anxious symptoms in Chinese samples, and improve well-being in both Eastern and Western measures. Psychological interventions can be designed for lower-status population, focusing on holistic information integration and multi-perspective reframing. Furthermore, this study suggests that indigenous psychological elements could function as cultural reserve capacities that flatten the socioeconomic gradient in well-being, implying that models of health and well-being disparities should explicitly incorporate culture-fit resources rather than treating psychosocial resources as culturally neutral.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Limitations and future directions\u003c/h2\u003e\u003cp\u003eThere are several limitations in this study. First, the cross-sectional design of this study couldn\u0026rsquo;t provide any causal inference. Future research should adopt longitudinal or experimental designs to establish causal directionality.\u003c/p\u003e\u003cp\u003eSecond, our sample comprised Chinese adults and the moderator is an indigenous Chinese thinking style. The buffering we observe may be partly contingent on cultural fit, i.e., to the extent to which a mindset is normative and socially rewarded in each ecology. Prior cross-cultural work indicates that East-Asian psychological norms and styles are more strongly tied to adaptive emotion regulation and \u0026ldquo;balanced\u0026rdquo; well-being in East-Asian contexts, whereas in Western samples they can be neutral or even negatively related to certain well-being indicators (Butler, Lee, \u0026amp; Gross, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Miyamoto \u0026amp; Ryff, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Soto et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Miyamoto et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kirchner-H\u0026auml;usler et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Future research is needed to test the moderation model by zhongyong and other indigenous cultural constructs in non-Chinese populations.\u003c/p\u003e\u003cp\u003eThird, our online recruited sample ensured variability but was not probability-based and may not mirror population distributions. Estimates may not be interpreted as population prevalences. Future research should be expanded to more representative and more diverse samples for better generalizing the findings.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;YZ designed the study, analysed the data, and wrote the article. YM co-designed the study, translated the ikigai scale, and participated in writing of the article. JL ran the data collection. KP supervised the design and administration of the study.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Human Research Ethics Committee of the Department of Psychology and Cognitive Science of Tsinghua University. Declaration of Helsinki and the APA Ethical Principles were followed during the study.\u003c/p\u003e\n\u003cp\u003eConsent to participate\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants involved in this study.\u003c/p\u003e\n\u003cp\u003eConsent to publish\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eData is provided within the supplementary information files.\u003c/p\u003e\n\u003cp\u003eClinical trial number\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eFunding Declaration\u003c/p\u003e\n\u003cp\u003eNo funding was provided for this study.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests and no financial interest in the preparation of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdler, N. (2007). The MacArthur scale of subjective social status. \u003cem\u003eMacArthur research network on SES \u0026amp; health\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eButler, E. A., Lee, T. L., \u0026amp; Gross, J. J. (2007). Emotion regulation and culture: Are the social consequences of emotion suppression culture-specific?. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(1), 30. \u003c/li\u003e\n\u003cli\u003eChou, L. F., Chu, C. C., Yeh, H. C., \u0026amp; Chen, J. (2014). Work stress and employee well‐being: The critical role of Z hong‐Y ong. \u003cem\u003eAsian Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2), 115-127.\u003c/li\u003e\n\u003cli\u003eCui, L., Tang, G., \u0026amp; Huang, M. (2022). Expressive suppression, confucian Zhong Yong thinking, and psychosocial adjustment among Chinese young adults. \u003cem\u003eAsian Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(4), 715-730. \u003c/li\u003e\n\u003cli\u003eDerogatis, L. R. (2001). \u003cem\u003eBSI 18, Brief Symptom Inventory 18: Administration, scoring and procedures manual\u003c/em\u003e. NCS Pearson, Incorporated.\u003c/li\u003e\n\u003cli\u003eDiener, E. D., Emmons, R. A., Larsen, R. J., \u0026amp; Griffin, S. (1985). The satisfaction with life scale. \u003cem\u003eJournal of personality assessment\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e(1), 71-75.\u003c/li\u003e\n\u003cli\u003eFido, D., Kotera, Y., \u0026amp; Asano, K. (2020). English translation and validation of the Ikigai-9 in a UK sample. \u003cem\u003eInternational Journal of Mental Health and Addiction\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(5), 1352-1359.\u003c/li\u003e\n\u003cli\u003eGallo, L. C., de Los Monteros, K. E., \u0026amp; Shivpuri, S. (2009). Socioeconomic status and health: what is the role of reserve capacity?. \u003cem\u003eCurrent directions in psychological science\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(5), 269-274. \u003c/li\u003e\n\u003cli\u003eHajek, A., Imai, T., Zwar, L., \u0026amp; K\u0026ouml;nig, H. H. (2024). Translation and Validation of the German Version of the Ikigai-9. \u003cem\u003eSocieties\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3), 39.\u003c/li\u003e\n\u003cli\u003eHittner, E. F., Rim, K. L., \u0026amp; Haase, C. M. (2019). Socioeconomic status as a moderator of the link between reappraisal and anxiety: Laboratory-based and longitudinal evidence. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(8), 1478. \u003c/li\u003e\n\u003cli\u003eHowell, R. T., \u0026amp; Howell, C. J. (2008). The relation of economic status to subjective well-being in developing countries: a meta-analysis. \u003cem\u003ePsychological bulletin\u003c/em\u003e, \u003cem\u003e134\u003c/em\u003e(4), 536.\u003c/li\u003e\n\u003cli\u003eImai, T. (2012). The reliability and validity of a new scale for measuring the concept of Ikigai (Ikigai-9). \u003cem\u003e[Nihon koshu eisei zasshi]\u003c/em\u003e \u003cem\u003eJapanese journal of public health\u003c/em\u003e, 59(7), 433-439. \u003c/li\u003e\n\u003cli\u003eJohnson, W., \u0026amp; Krueger, R. F. (2006). How money buys happiness: genetic and environmental processes linking finances and life satisfaction. \u003cem\u003eJournal of personality and social psychology\u003c/em\u003e, \u003cem\u003e90\u003c/em\u003e(4), 680.\u003c/li\u003e\n\u003cli\u003eKahneman, D., \u0026amp; Deaton, A. (2010). High income improves evaluation of life but not emotional well-being. \u003cem\u003eProceedings of the national academy of sciences\u003c/em\u003e, \u003cem\u003e107\u003c/em\u003e(38), 16489-16493.\u003c/li\u003e\n\u003cli\u003eKillingsworth, M. A., Kahneman, D., \u0026amp; Mellers, B. (2023). Income and emotional well-being: A conflict resolved. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e, \u003cem\u003e120\u003c/em\u003e(10), e2208661120.\u003c/li\u003e\n\u003cli\u003eKirchner-H\u0026auml;usler, A., De Leersnyder, J., Uskul, A. K., Mirzada, F., Vignoles, V. L., Rodr\u0026iacute;guez-Bail\u0026oacute;n, R., ... \u0026amp; Uchida, Y. (2023). Cultural fit of emotions and subjective well-being: replicating comparative evidence and extending it to the Mediterranean region. \u003cem\u003eCurrent Research in Ecological and Social Psychology\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 100171. \u003c/li\u003e\n\u003cli\u003eLachman, M. E., \u0026amp; Weaver, S. L. (1998). The sense of control as a moderator of social class differences in health and well-being. \u003cem\u003eJournal of personality and social psychology\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e(3), 763.\u003c/li\u003e\n\u003cli\u003eLee, A., Cheng, C. M. Y., Lee, L. Y., Esposito, G., \u0026amp; Cheon, B. K. (2023). Thanking in the times of the plague: The role of holistic thinking in meaning‐making and gratitude. \u003cem\u003eSocial and Personality Psychology Compass\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(11), e12854.\u003c/li\u003e\n\u003cli\u003eLee, S. J., \u0026amp; Wu, C. H. (2008). Comparing the level of positive tendency in a life satisfaction evaluation between Chinese and Western people. \u003cem\u003eSocial Indicators Research\u003c/em\u003e, \u003cem\u003e89\u003c/em\u003e(1), 147-153.\u003c/li\u003e\n\u003cli\u003eLynch, T. R., Chapman, A. L., Rosenthal, M. Z., Kuo, J. R., \u0026amp; Linehan, M. M. (2006). Mechanisms of change in dialectical behavior therapy: Theoretical and empirical observations. \u003cem\u003eJournal of clinical psychology\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(4), 459-480. \u003c/li\u003e\n\u003cli\u003eMiyamoto, Y., Boylan, J. M., Coe, C. L., Curhan, K. B., Levine, C. S., Markus, H. R., ... \u0026amp; Ryff, C. D. (2013). Negative emotions predict elevated interleukin-6 in the United States but not in Japan. \u003cem\u003eBrain, behavior, and immunity\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e, 79-85. \u003c/li\u003e\n\u003cli\u003eMiyamoto, Y., \u0026amp; Ryff, C. D. (2011). Cultural differences in the dialectical and non-dialectical emotional styles and their implications for health. \u003cem\u003eCognition and Emotion\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(1), 22-39.\u003c/li\u003e\n\u003cli\u003eNisbett, R. E., Peng, K., Choi, I., \u0026amp; Norenzayan, A. (2001). Culture and systems of thought: holistic versus analytic cognition. \u003cem\u003ePsychological review\u003c/em\u003e, \u003cem\u003e108\u003c/em\u003e(2), 291.\u003c/li\u003e\n\u003cli\u003eNon, A. L., Rom\u0026aacute;n, J. C., Clausing, E. S., Gilman, S. E., Loucks, E. B., Buka, S. L., ... \u0026amp; Kubzansky, L. D. (2020). Optimism and social support predict healthier adult behaviors despite socially disadvantaged childhoods. \u003cem\u003eInternational Journal of Behavioral Medicine\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(2), 200-212. \u003c/li\u003e\n\u003cli\u003ePark, Y. (2015). Sense of \u0026ldquo;Ikigai\u0026rdquo;(reason for living) and social support in the Asia-Pacific region. \u003cem\u003eBehaviormetrika\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(2), 191-208.\u003c/li\u003e\n\u003cli\u003ePeng, K., Spencer-Rodgers, J., \u0026amp; Nian, Z. (2006). Na\u0026iuml;ve dialecticism and the Tao of Chinese thought. In \u003cem\u003eIndigenous and cultural psychology: Understanding people in context\u003c/em\u003e (pp. 247-262). Boston, MA: Springer US.\u003c/li\u003e\n\u003cli\u003eRen, Z., Yue, G., Xiao, W., \u0026amp; Fan, Q. (2022). The influence of subjective socioeconomic status on life satisfaction: the chain mediating role of social equity and social trust. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(23), 15652. \u003c/li\u003e\n\u003cli\u003eRobins, C. J., \u0026amp; Rosenthal, M. Z. (2011). Dialectical behavior therapy. \u003cem\u003eAcceptance and mindfulness in cognitive behavior therapy: Understanding and applying the new therapies\u003c/em\u003e, 164-192. \u003c/li\u003e\n\u003cli\u003eSone, T., Nakaya, N., Ohmori, K., Shimazu, T., Higashiguchi, M., Kakizaki, M., ... \u0026amp; Tsuji, I. (2008). Sense of life worth living (ikigai) and mortality in Japan: Ohsaki Study. \u003cem\u003ePsychosomatic medicine\u003c/em\u003e, \u003cem\u003e70\u003c/em\u003e(6), 709-715.\u003c/li\u003e\n\u003cli\u003eSoto, J. A., Perez, C. R., Kim, Y. H., Lee, E. A., \u0026amp; Minnick, M. R. (2011). Is expressive suppression always associated with poorer psychological functioning? A cross-cultural comparison between European Americans and Hong Kong Chinese. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(6), 1450. \u003c/li\u003e\n\u003cli\u003eSpencer-Rodgers, J., Boucher, H. C., Mori, S. C., Wang, L., \u0026amp; Peng, K. (2009). The dialectical self-concept: Contradiction, change, and holism in East Asian cultures. \u003cem\u003ePersonality and Social Psychology Bulletin\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(1), 29-44.\u003c/li\u003e\n\u003cli\u003eSpencer-Rodgers, J., \u0026amp; Peng, K. (Eds.). (2018). \u003cem\u003eThe psychological and cultural foundations of East Asian cognition: Contradiction, change, and holism\u003c/em\u003e. Oxford University Press. \u003c/li\u003e\n\u003cli\u003eSpencer-Rodgers, J., Peng, K., Wang, L., \u0026amp; Hou, Y. (2004). Dialectical self-esteem and East-West differences in psychological well-being. \u003cem\u003ePersonality and Social Psychology Bulletin\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(11), 1416-1432.\u003c/li\u003e\n\u003cli\u003eSteger, M. F., Frazier, P., Oishi, S., \u0026amp; Kaler, M. (2006). The meaning in life questionnaire: assessing the presence of and search for meaning in life. \u003cem\u003eJournal of counseling psychology\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(1), 80.\u003c/li\u003e\n\u003cli\u003eTan, J. J., Kraus, M. W., Carpenter, N. C., \u0026amp; Adler, N. E. (2020). The association between objective and subjective socioeconomic status and subjective well-being: A meta-analytic review. \u003cem\u003ePsychological bulletin\u003c/em\u003e, \u003cem\u003e146\u003c/em\u003e(11), 970.\u003c/li\u003e\n\u003cli\u003eVandroux, R., \u0026amp; Auzoult-Chagnault, L. (2023). Validation francophone de l\u0026rsquo;\u0026eacute;chelle Ikigai-9. \u003cem\u003ePsychologie fran\u0026ccedil;aise\u003c/em\u003e, \u003cem\u003e68\u003c/em\u003e(4), 503-513.\u003c/li\u003e\n\u003cli\u003eWang, B., Zhao, H., Shen, H., \u0026amp; Jiang, Y. (2023). Socioeconomic status and subjective well-being: The mediating role of class identity and social activities. \u003cem\u003ePlos one\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(9), e0291325.\u003c/li\u003e\n\u003cli\u003eWilkes, J., Garip, G., Kotera, Y., \u0026amp; Fido, D. (2023). Can Ikigai predict anxiety, depression, and well-being?. \u003cem\u003eInternational Journal of mental health and addiction\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(5), 2941-2953.\u003c/li\u003e\n\u003cli\u003eWong, Y. J., Ho, R. M., Li, P., Shin, M., \u0026amp; Tsai, P. C. (2011). Chinese Singaporeans\u0026rsquo; lay beliefs, adherence to Asian values, and subjective well-being. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(6), 822-827.\u003c/li\u003e\n\u003cli\u003eWong, Y. J., \u0026amp; Liu, T. (2018). Dialecticism and mental health: Toward a yin-yang vision of well-being.\u003c/li\u003e\n\u003cli\u003eWu, C. H., \u0026amp; Lin, Y. C. (2005). Development of a Zhong-Yong thinking style scale. \u003cem\u003eIndigenous Psychological Research in Chinese Societies\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e, 247-300.\u003c/li\u003e\n\u003cli\u003eWu, W., Liu, Y., Yu, L., Guo, Z., Li, S., Guo, Z., ... \u0026amp; Zeng, Y. (2022). Relationship between family socioeconomic status and learning burnout of college students: the mediating role of subjective well-being and the moderating role of resilience. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 844173.\u003c/li\u003e\n\u003cli\u003eYao, Z. F., Yang, M. H., Yang, C. T., Chang, Y. H., \u0026amp; Hsieh, S. (2024). The role of attitudes towards contradiction in psychological resilience: the cortical mechanism of conflicting resolution networks. \u003cem\u003eScientific reports\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 1669.\u003c/li\u003e\n\u003cli\u003eYang, X., Zhang, P., Zhao, J., Zhao, J., Wang, J., Chen, Y. U., ... \u0026amp; Zhang, X. (2016). Confucian culture still matters: The benefits of zhongyong thinking (doctrine of the mean) for mental health. \u003cem\u003eJournal of Cross-Cultural Psychology\u003c/em\u003e, \u003cem\u003e47\u003c/em\u003e(8), 1097-1113. \u003c/li\u003e\n\u003cli\u003eYe, R., Shen, J., Mo, Q., Xu, P., Huang, Y., Chen, J., ... \u0026amp; Gao, Y. (2025). The roles of physical activity and sedentary behavior in the relationship between socioeconomic status and depressive symptoms: Observations from a national study. \u003cem\u003eJournal of Affective Disorders\u003c/em\u003e, \u003cem\u003e372\u003c/em\u003e, 1-9.\u003c/li\u003e\n\u003cli\u003eZhao, S., Du, H., Li, Q., Wu, Q., \u0026amp; Chi, P. (2021). Growth mindset of socioeconomic status boosts subjective well-being: A longitudinal study. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e168\u003c/em\u003e, 110301.\u003c/li\u003e\n\u003cli\u003eZhao, S., \u0026amp; Peng, L. (2021). Feeling matters: perceived social support moderates the relationship between personal relative deprivation and depressive symptoms. \u003cem\u003eBMC psychiatry\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(1), 345.\u003c/li\u003e\n\u003cli\u003eZhao, Y., Yu, F., Jing, B., Hu, X., Luo, A., \u0026amp; Peng, K. (2019). An analysis of well-being determinants at the city level in China using big data. \u003cem\u003eSocial Indicators Research\u003c/em\u003e, \u003cem\u003e143\u003c/em\u003e(3), 973-994.\u003c/li\u003e\n\u003cli\u003eZhou, S., \u0026amp; Li, X. (2022). Zhongyong thinking style and resilience capacity in chinese undergraduates: the chain mediating role of cognitive reappraisal and positive affect. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 814039.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"zhongyong, well-being, ikigai, SES, thinking style","lastPublishedDoi":"10.21203/rs.3.rs-7751702/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7751702/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocioeconomic status (SES) robustly stratifies well-being (WB), yet culturally grounded cognitive resources may blunt this gradient. We tested whether zhongyong, an Eastern thinking style emphasizing multi-perspective integration, contextual fit, and moderation buffers the SES-WB links in China. N\u0026thinsp;=\u0026thinsp;600 adults completed an online survey assessing both subjective and objective SES indicators, alongside both Western and Eastern indicators. Zhongyong was measured both globally and by facets (Multi-thinking, Holism, Harmoniousness). Analyses used mean-centered predictors with SES\u0026times;zhongyong interactions and simple-slope probes. The results indicated that SES related to greater WB, with subjective SES showing larger and more consistent associations than objective SES. Zhongyong also correlated positively with WB. Crucially, zhongyong buffered SES\u0026ndash;WB slopes, most clearly for subjective SES and symptom outcomes. Facet analyses indicated that Holism was the most consistent and largest moderator, and Harmoniousness was least predictive. Findings position zhongyong as a psychological resource that attenuates the socioeconomic gradient in WB. The results advance a culturally plural account of psychological resources and suggest zhongyong-informed skills as low-cost targets to protect disadvantaged groups\u0026rsquo; well-being.\u003c/p\u003e","manuscriptTitle":"The Eastern Zhongyong Thinking Style Buffers the Socioeconomic Gradient in Well-Being","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 11:51:04","doi":"10.21203/rs.3.rs-7751702/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"50d11718-b05d-4641-9b96-88fe65a40e29","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:27:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 11:51:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7751702","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7751702","identity":"rs-7751702","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}