Life satisfaction and mental health in Chinese adults.
It is generally accepted that financial status is the most effective predictor of LS (Chou & Chi, 1999; Zhang & Yu, 1998). However, Oishi, Diener, Lucas, and Suh (1999), in a study of 39 nations, found that financial satisfaction was more strongly associated with LS in poorer nations than in wealthier nations, in which home LS was more strongly related to LS. This suggests that actual income may not be the direct factor that affects LS. Johnson and Krueger (2006) confirmed this view and found that perceived financial status (PFS) mediated the association between actual wealth and LS. They further pointed out that sense of control appeared to act as a mechanism to convert life circumstances into LS. Therefore, although actual income may indirectly affect LS through psychological factors, such as social comparison (Diener, Emmons, Larsen, & Griffin, 1985), it seems that PFS as a psychological variable directly affects LS. For example, self-esteem and relationship harmony (Kwan, Bond, & Singelis, 1997), and emotional intelligence (Gannon & Ranzijn, 2005) can predict LS well. In particular, Pilcher (1998) found that feelings of depression, vigor, confusion, and negative affect were significant predictors of LS. Other researchers have found that the absence of anxiety and depression were crucial for the maintenance of LS in aging adults (Beutel, Glaesmer, Wiltink, Marian, & Brahler, 2010; Collins, Glei, & Goldman, 2009). Recently, Koots-Ausmees, Realo and Allik (2013) also found that LS was best predicted by positive and negative affect.
Low or decreased LS is often associated with psychological and social problems, such as depression, anxiety, and poor social interaction (Furr & Funder, 1998). Lyyra, Tormakangas, Read, Rantanen, and Berg (2006), in a longitudinal study, found that individuals in the lowest quartile of factors of satisfaction with present life had almost double the risk of mortality compared with those in the highest quartile. However, LS can moderate the effects of stressful life events on the development of externalizing behavior problems, such as delinquent and aggressive behavior (Suldo & Huebner, 2004).
Previous researchers have explored both the demographic and psychological factors that affect LS, and the impact of LS on mental and behavioral problems. However, there have been few studies in which the effects of PFS and mental health (MH) on judging LS have been simultaneously tested. As poor PFS may trigger mental problems, further clouding the judgment of LS, it is important to investigate the inner process of LS judgment.
After more than 30 years of reform and opening up, China has achieved rapid economic development, urbanization, and increased population mobility. Individual incomes have become diverse and income gaps are widening. These factors may directly conflict with individuals' PFS, decreasing their sense of fairness as well as LS and MH, and possibly causing mental and behavioral problems.
Our main objective in this study was to examine the relationship between LS and MH in Chinese adults. We focused on how PFS and MH affect LS, to offer implications so that the government and organizations will pay more attention to individuals' true feelings. This would undoubtedly benefit the social harmony of China. We questioned whether or not the LS and MH of Chinese adults increase synchronously with rapid economic development, and if PFS is a vital psychological factor in the judgment of LS.
Participants were composed of 397 Chinese adults (183 women, 214 men) from urban and rural communities in Chongqing, Hubei, Henan, and Shandong provinces. They were aged from 18 to 65 years (M [+ or -] SD = 35.31 [+ or -] 9.53), and comprised 55 workers, 90 peasants, 35 business people, 198 teachers, and 19 civil servants. The participants completed informed consent forms prior to volunteering to participate in the study.
The study sample was selected on a voluntary basis with the permission of the community residents' committees. Participants completed a brief demographic questionnaire that included gender, age, and occupation. Then they gave a subjective judgment of their PFS. PFS was based on the question "Think about the financial situation of your friends, neighbors, and colleagues in the past years. When comparing yourself to them overall, how would you describe your family's financial situation?" Response choices were "good", "average", and "bad". Then they completed the two self-report questionnaires (SWLS and GHQ-20). To control for possible bias in the answers from one questionnaire to another, the questionnaires were answered in random order.
Satisfaction With Life Scale (SWLS; Diener et al., 1985). We used the Chinese version which was translated and adapted by Xiong and Xu (2009), and contains five items. Participants indicated their level of agreement on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). In the present study, Cronbach's [alpha] = .79, and correlations among five items were between .23 and .64.
General Health Questionnaire. We used the 20-item Chinese version of the General Health Questionnaire (GHQ-20; Li & Kam, 2002), which was developed from the GHQ-30 (Huppert, Walters, Day, & Elliott, 1989) to measure mental health. The questionnaire consists of three subscales, that is, sense of adequacy, depression, and anxiety. Participants scored 1 when they agreed with the statements and 0 when they disagreed with the statements. In the present study, Cronbach's [alpha] = .82, and Cronbach's [alpha] of the subscales ranged from .63 to .75.
Data were analyzed using SPSS version 15.0. Descriptive statistics were applied to identify the characteristics of LS and MH. One-way analysis of variance (ANOVA) was performed to determine whether or not PFS produced effects on LS and MH. The correlations among LS and the subscales of MH were analyzed using the Pearson product-moment correlation coefficient, and predictors of LS were analyzed using stepwise multiple linear regression analysis.
Overall Status of LS and MH
The score for sense of adequacy (M [+ or -] SD = 0.75 [+ or -] 0.21) was higher than the theoretical mean of 0.5, t = 22.93, p < .001. Scores for LS (M [+ or -] SD = 2.85 [+ or -] 0.84), depression (M [+ or -] SD = 0.15 [+ or -] 0.23), and anxiety (M [+ or -] SD = 0.32 [+ or -] 0.33) were significantly lower than the theoretical means of 3, (t = -3.40, p < .001), 0.5, (t = -29.33, p < .001), and 0.5, (t = -10.69, p < .001).
Effect of PFS on LS and MH
Individuals' different PFS accounted for different levels of LS, F (2, 394) = 12.20, p < .01, sense of adequacy, F (2, 394) = 4.00, p < .05, and anxiety, F (2, 394) = 8.89, p < .01. Further analysis showed that people who perceived themselves to have good financial status reported higher LS and sense of adequacy, and lower anxiety than did those who did not (see Table 1).
Correlations Among LS and Subscales of MH
Pearson's correlations showed that LS was positively correlated with sense of adequacy (r = .42, p < .01), and negatively correlated with depression (r = -.30, p < .01) and anxiety (r = -.31, p < .01).
Predictors of LS
Multiple linear regression analysis was performed to determine which factors could predict LS (see Table 2). Sense of adequacy, depression, and anxiety were found to be significant predictors of LS, F(3, 393) = 32.39, p < .001. Sense of adequacy ([beta] = .32) positively predicted LS, and depression ([beta] = -.13) and anxiety ([beta] = -.13) negatively predicted LS. The three factors explained 21% of the variance.
It is generally accepted that LS is negatively skewed above the scale midpoint (Cummins, 1995), but the mean score of LS in the present study was significantly lower than the theoretical mean. When compared with normative data of the SWLS (Chen & Davey, 2008; Pavot & Diener, 1993), the LS of our participants was lower than in most other samples. When Easterlin, Morgan, Switek, and Wang (2012) compared Chinese individuals' LS from 1990 to 2010, they found that it followed a U-shaped pattern (declining from 1990 to around 2000-2005, and then turning upward). The lower level of LS in the present study may be due to the composition of the sample which included 260 rural residents and 137 urban residents. National Bureau of Statistics of China's (2012) data show that in 2011, rural residents' per capita net income was 6,977 yuan (US$1,140), and urban residents' per capita net income was 23,979 yuan (US$3,918). As Oishi et al. (1999) have suggested, financial satisfaction plays an important role in judgments of LS in poor districts. For those with poor financial status, their primary goal is to satisfy their basic living needs. When this occurs, psychological needs emerge. Therefore, it is socioeconomic status (SES) that plays a vital role in predicting LS.
In the present study, participants' MH level was higher than the theoretical midpoint. This is consistent with Chan's (1993) conclusion that Chinese individuals report few mental health problems. MH was also affected by PFS in the present study. This finding is consistent with that of Baum, Garofalo, and Yali (1999) that SES is a predictor of a range of health and illness outcomes. As an important factor affecting MH, SES could provide a social safety net (Easterlin et al., 2012). These findings may be beneficial to mental health services. At home and at school, parents and teachers should guide children to develop a realistic view of money. In the field of psychological counseling, social comparison strategy training could be an important topic.
Our finding that LS is significantly correlated with the MH subscales confirms Kuppens, Realo, and Diener's (2008) conclusion that positive and negative emotions affect judgments of LS. In particular, positive emotions are more strongly related to LS than is the absence of negative emotions. Therefore, the MH subscales are good predictors of LS. These findings are consistent with those of several recent studies (Beutel et al., 2010; Koots-Ausmees et al., 2013).
There are several limitations in the present study. Owing to some limiting conditions, we could not select a large sample of participants by stratified random sampling in all the provinces of China. In addition, as the cross-sectional nature of the data allowed only an examination of the association between LS and MH, it would be helpful to obtain longitudinal data to examine the causal relationship. The objective financial status should also be combined with PFS in future research.
Nevertheless, we have contributed to the literature by increasing the understanding of several issues. We found that rapid economic development did not cause a synchronous increase in LS and level of MH for Chinese people, and that PFS and MH affect LS in two important ways. That is, PFS may be a direct psychological factor affecting LS, in that it affects the level of MH, and MH factors affect the judgment of LS. These findings imply that MH may play a role in the relationship between PFS and LS, but whether or not it mediates or moderates this relationship needs further investigation. Finally, sense of adequacy was the strongest psychological predictor of LS.
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Shaanxi Normal University
Southwest University, Chongqing
MEI SHI AND MING JI
Shaanxi Normal University
Xuhui Bao, Department of Psychology, Shaanxi Normal University; Weigang Pan, School of Psychology, Southwest University; Mei Shi and Ming Ji, Department of Psychology, Shaanxi Normal University.
This study was supported by the Fundamental Research Funds for the Central Universities of China (GK20100405).
Correspondence concerning this article should be addressed to: Ming Ji, Department of Psychology, Shaanxi Normal University, Yanta District, Xi'an 710062, People's Republic of China. Email: email@example.com
Table 1. LS and MH Scores According to PFS (M [+ or -] SD) PFS N LS Sense of adequacy 1 = good 123 3.58 [+ or -] 0.84 0.83 [+ or -] 0.19 2 = ordinary 128 2.85 [+ or -] 0.81 0.75 [+ or -] 0.20 3 = bad 146 2.53 [+ or -] 0.91 0.68 [+ or -] 0.25 F 12.20 *** 4.00 * Post hoc 1>2 ***>3 *** 1>3 *, 2>3 * PFS Depression Anxiety 1 = good 0.09 [+ or -] 0.22 0.12 [+ or -] 0.21 2 = ordinary 0.15 [+ or -] 0.22 0.32 [+ or -] 0.32 3 = bad 0.20 [+ or -] 0.29 0.46 [+ or -] 0.37 F 1.73 8.89 *** Post hoc 1<2 ***<3 *** Note. * p < .05, *** p < .001. Table 2. Summary of Stepwise Multiple Regression Analysis Predicting LS Model MH subscales B P t Sig. R 1 Sense of adequacy 1.68 .42 8.71 .001 .42 2 Sense of adequacy 1.45 .36 7.18 .001 .45 Depression -.64 -.17 -3.43 .001 3 Sense of adequacy 1.28 .32 6.08 .001 .46 Depression -.49 -.13 -2.52 .012 Anxiety -.34 -.13 -2.45 .015 Adj. [DELTA] Model MH subscales [R.sup.2] [R.sup.2] 1 Sense of adequacy .17 .17 2 Sense of adequacy .20 .03 Depression 3 Sense of adequacy .21 .01 Depression Anxiety
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|Author:||Bao, Xuhui; Pan, Weigang; Shi, Mei; Ji, Ming|
|Publication:||Social Behavior and Personality: An International Journal|
|Date:||Nov 1, 2013|
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