Gender Differences in the Relationship Between Domain-Specific and ...

Applied Research Quality Life DOI 10.1007/s11482-016-9461-z

Gender Differences in the Relationship Between Domain-Specific and General Life Satisfaction: A Study in Iran and Serbia Veljko Jovanović 1 & Mohsen Joshanloo 2 & Dragan Đunda 3 & Ali Bakhshi 4

Received: 25 August 2015 / Accepted: 21 March 2016 # Springer Science+Business Media Dordrecht and The International Society for Quality-of-Life Studies (ISQOLS) 2016

Abstract Although the associations between satisfaction with life domains (DS) and global life satisfaction (GLS) are well-documented, the roles of culture and gender in this relationship remain largely unknown. The main aim of the present study was to examine the relationships between DS and GLS among women and men in Iran and Serbia, after establishing measurement invariance across groups. In addition, we investigated gender and country differences in DS and GLS. The sample was comprised of 623 undergraduate students from Iran and Serbia. Participants completed measures of GLS and satisfaction with the following seven domains: standard of living, Highlights • Domain-satisfaction and global satisfaction (GLS) were examined in Iran and Serbia • Gender differences in life satisfaction were examined across Iran and Serbia • Standard of living and achieving in life contributed to GLS in both countries • Gender-specific predictors of GLS were found in Iran • Significant differences were found in life satisfaction across country and gender

* Veljko Jovanović [email protected] Mohsen Joshanloo [email protected] Dragan Đunda [email protected] Ali Bakhshi [email protected]

1

Department of Psychology, University of Novi Sad, Dr Zorana Đinđića 2, 21 000 Novi Sad, Serbia

2

Department of Psychology, Keimyung University, Daegu, South Korea

3

Department of Psychology, University of Novi Sad, Novi Sad, Serbia

4

Department of Psychology, Qazvin Islamic Azad University, Qazvin, Iran

V. Jovanović et al.

health, achieving in life, relationships, safety, community-connectedness, and future security. Satisfaction with achieving in life and standard of living had similar unique contributions to GLS among Iranian women and men, whereas satisfaction with achieving in life was a stronger predictor of GLS than satisfaction with standard of living among Serbian women and men. These two domains were the only significant predictors of GLS in Serbian women and men, whereas gender-specific predictors of GLS were found in Iran. The results demonstrated that students in Serbia reported higher GLS and DS than Iranian students. Furthermore, we found that women reported higher GLS and DS than men did, with the exception of satisfaction with standard of living for which no significant gender differences were found. The present study provides new insights into the role of gender in the relationship between DS and GLS across cultures. Keywords Life satisfaction . Domain satisfaction . Gender . Culture . Measurement invariance

Introduction After pioneering studies on subjective well-being (SWB) were carried out in the 1960s, life satisfaction has become one of the most studied topics in the social sciences. Diener’s (1984) tripartite model of SWB introduced life satisfaction as a cognitive component of SWB, with positive affect and negative affect representing affective components of SWB. Life satisfaction includes two types of evaluations (Pavot and Diener 2009): global (satisfaction with life as a whole) and domain-specific (satisfaction with specific life domains). Researchers usually assess global life satisfaction (GLS) using unidimensional measures such as Satisfaction with Life Scale (SWLS; Diener et al. 1985) which is considered to be the gold standard in the field of wellbeing. Satisfaction with specific domains of life (e.g., finance, family, friends, health) is less frequently investigated, although comprehensive definitions of life satisfaction include domain-specific life satisfaction (DS). Self-reports of DS are likely to yield more complete information about a person’s well-being (Diener et al. 2013). Contrary to the assessment of GLS, there is no widely accepted scale for the assessment of DS and in previous studies the choice of specific domains of life has been somewhat arbitrary. Theoretically, it is possible to develop an infinite number of DS questions because there is a large number of relevant life domains which might differ across cultures. Different authors have proposed different key domains (e.g., Rojas 2006; Sirgy et al. 2010), but they overlap to a large extent and usually capture satisfaction with income, relations, job and health (Kapteyn et al. 2010). Based on a literature review, Cummins (1996) suggested that seven domains were essential: material wellbeing, health, productivity, intimacy, safety, community, and emotional well-being. These seven domains were captured by the Comprehensive Quality of Life Scale (ComQol; Cummins 1997), which was revised and replaced with the Personal Wellbeing Index a decade ago (Personal Wellbeing Index, PWI; International Wellbeing Group 2006). The PWI comprises seven broad domains: standard of living, health, achieving in life, relationships, safety, community-connectedness, and future security. The authors of the PWI argue that these domains represent the minimal set of broad

Gender, Culture, and Life Satisfaction

areas of life that form a first-level deconstruction of personal well-being, and which are amenable to both self-report and objective measurement (Cummins et al. 2003). In addition, the semi-abstract nature of domains has been expected to ensure a crosscultural utility of the PWI (International Wellbeing Group 2013). One of the key topics in the field of well-being has been the relationship between DS and GLS. A great deal of research has been carried out that has examined the relationship between DS and GLS and has supported the bottom-up models, with the assumption that GLS is based on satisfaction in relevant domains of life (Schimmack 2008). Bottom-up models posit that life satisfaction judgements reflect objective conditions of life (such as health, finances, security) and changing life circumstances (e.g., positive and negative life events). According to these models, GLS judgements are constructed by evaluating the conditions of life, thus implying that domain-specific satisfactions should be robust predictors of GLS. Previous studies have clearly shown that DS contribute to GLS (Loewe et al. 2014; Renn et al. 2009; van Praag et al. 2003), but also suggest that the contributions of different domains of life to GLS might vary across contexts. The present study sought to examine the relationship between DS and GLS across two countries: Iran and Serbia, while also taking gender into account. We argue that the relationship between DS and GLS might depend on culture and gender, two factors that have been rarely examined in previous studies on domain satisfaction. An additional goal of the present study was to investigate the mean differences in DS and GLS across culture and gender. Differences in the Relationship Between Domain-Satisfaction and Global Life Satisfaction Across Cultures and Gender Cultural differences have been a central issue in the field of well-being over the past few decades (e.g., Diener 2009), but to date studies have rarely examined the role of culture and gender in the relationship between DS and GLS. Previous studies have indicated that individuals use different sources to form life satisfaction judgments, and that these sources are relatively stable and chronically accessible (Schimmack et al. 2002). Therefore, it is expected that the relationships between DS and GLS would differ in various cultures, because life domains that individuals consider most relevant vary across cultures. For example, people in collectivistic societies tend to place greater emphasis on interpersonal relations and community, whereas people in individualistic societies consider individual achievements and self-esteem more relevant (Uchida and Ogihara 2012). Such differences indicate that the predictors of well-being are different in cultures oriented towards personal achievement and those oriented towards interpersonal relations. Surprisingly, only a few studies have examined whether the relationship between DS and GLS varies across cultures, and the few existing studies have produced inconsistent findings. For example, Diener and Diener (1995) demonstrated that financial satisfaction was a stronger correlate of GLS in countries with lower levels of economic developments, whereas the association between satisfaction with friends and GLS was weaker in collectivistic countries. Morrison et al. (2011) found inconsistent results, showing that the relationship between GLS and satisfaction with standard of living was strongest in richer nations. These conflicting findings are not easy to reconcile, but they suggest that societal conditions, needs, and cultural values may moderate the relationship between DS and GLS (Oishi et al. 1999). For


example, a recent experimental study showed that the contributions of personal relationships, health, and religion/spirituality to GLS depend on the relative importance of these domains in a certain cultural context (Theuns et al. 2012). Another important yet neglected issue in well-being research is whether there are gender differences in the relationship between DS and GLS across cultures. It is reasonable to expect that the association between DS and GLS might differ for men and women from different cultures, given their different roles in society and different socialization practices. Previous research has indicated that men and women derive life satisfaction from different sources. For example, social resources (such as family support, friends, and romantic relationships) are more strongly associated with life satisfaction among women than men (Diener and Fujita 1995), whereas income has been shown to be more closely related to life satisfaction among men than that of women (Pinquart and Sorensen 2000). However, it remains unknown whether gender differences in DS-GLS relationship would hold across cultures. Therefore, the present study examined not only cross-country differences in the relationship between DS and GLS, but also investigated whether the contribution of specific domains of life differs for men and women from Iran and Serbia, which differ substantially in cultural values and the societal approval of equal rights among women and men. The Global Gender Gap Index (World Economic Forum 2014), which is designed to measure gender-based gaps in access to resources and opportunities in economic participation and opportunity, educational attainment, health and survival, and political empowerment, indicates considerable differences in gender equality between Iran and Serbia, with Serbia ranking 54th and Iran ranking 137th out of 142 countries. Gender equality has been suggested as an important factor in explaining gender differences in life satisfaction across nations (e.g., Tesch-Römer et al. 2008; York and Bell 2014), but no previous study has examined DS-GLS relationship in countries with different levels of gender equality. Therefore, the present study evaluated in an exploratory manner whether marked differences in gender equality between Iran and Serbia may result in different patterns of relationships between DS and GLS for men and women in these two countries. Differences in Mean Life Satisfaction Across Cultures and Gender As previously noted, an additional goal of the present study was to examine mean differences both in DS and GLS across two countries and across gender. The majority of cross-cultural well-being studies have focused on mean differences in GLS (Veenhoven 2012). There is a lack of research on cross-cultural differences in satisfaction with specific domains of life, and it is largely unknown whether the results obtained from GLS measures would hold for domain-specific life satisfaction. Additionally, only a few studies have examined gender differences both in GLS and DS across different cultures. Gender differences in GLS are well documented, with most studies suggesting that there are no substantial gender differences in most countries across the world (Zweig 2015) or that women are slightly more satisfied with their lives than men (Graham and Chattopadhyay 2013; Vieira Lima 2011). However, much less is known about whether men and women report different levels of DS, and research on gender differences in DS have produced inconsistent findings across different countries. For example, in a study on a nationally representative


German sample, women reported greater satisfaction with family life, whereas men demonstrated greater satisfaction with leisure activities (Daig et al. 2009). In a nationally representative Croatian sample, men reported greater satisfaction with material status, health, feelings of physical safety, and future security, whereas women reported greater life satisfaction with their personal relationships and security, but these differences did not hold after controlling for income (Kaliterna and Burusic 2014). A somewhat different pattern of gender differences was found in Mexico, where men reported greater satisfaction with all domains of life, except economic domain with which women demonstrated greater satisfaction (Rojas 2007). These results are not easy to compare because the researchers used different measures of DS, but these findings suggest that gender differences in DS might indeed vary across different cultures. The Present Study The main goal of the present study was to examine the contribution of satisfaction with life domains (as measured with the PWI) to GLS (as measured with the SWLS) across two countries: Iran and Serbia, and separately for men and women. In addition, we examined cross-country and gender differences in life satisfaction (both global and domain-specific). Iran and Serbia share certain similarities, but also have marked differences, which were used to develop specific hypotheses in the present study. First, both countries are considered collectivistic societies (Hofstede et al. 2010), placing primary value on collaboration, shared interest and group harmony. Because people in collectivistic societies are expected to use social interactions as a primary source when making life satisfaction judgements (Morrison et al. 2011), we expected that in both countries satisfactions with personal relationships and community would be stronger predictors of GLS than satisfaction with domains closely related with individualistic values, such as achieving in life (Hypothesis 1). Second, both Iran and Serbia are developing countries facing challenging economic and societal conditions (Legatum Institute 2014) and with high youth unemployment rates (World Bank 2015), widespread corruption (Transparency International 2014) and moderate gross domestic product (GDP) per capita. Previous studies have shown that financial satisfaction is the strongest predictor of life satisfaction both in rich and poor countries (Ng and Diener 2014), and most studies suggest that income is more strongly related to life satisfaction in poorer countries (Bonini 2008; Diener and Diener 1995). Based on these findings, we expected that satisfaction with standard of living would explain the greatest amount of variance in GLS in both countries (Hypothesis 2). Additionally, given that interpersonal relationships have been shown to be more closely related to life satisfaction among women than men (Diener and Fujita 1995), whereas income has been shown to be more important for life satisfaction of men than women (Pinquart and Sorensen 2000), we expected that satisfactions with personal relationships and community would be stronger predictors of GLS among women both in Iran and Serbia while satisfaction with standard of living would be a stronger predictor of GLS among men in both countries as well (Hypothesis 3). Despite the similarities in collectivistic values and the level of economic development, there are also notable differences between the two countries in gender equality, as


previously noted. It is important to emphasize that no previous studies have examined the relationships between DS and GLS across gender in countries with different levels of gender equality, making it difficult to form specific hypotheses. However, based on low economic participation and a low level of access to resources for women in Iran (World Economic Forum 2014), we expected that satisfactions with standard of living and achieving in life would be weaker predictors of GLS among Iranian women than men, whereas this gender gap would be considerably smaller in Serbia which has greater gender equality (Hypothesis 4). Regarding gender differences in mean levels of GLS and DS, we expected that women would report higher life satisfaction than men both in Iran and Serbia, and the magnitude of the female–male life satisfaction gap would be similar in both countries (Hypothesis 5). Previous studies have shown that women report slightly higher life satisfaction than men in most countries across the world (Graham and Chattopadhyay 2013), including Iran (Joshanloo and Afshari 2011), and that gender differences in life satisfaction are not associated with economic development, religion, geographical region (Zweig 2015) and most indices of gender equality (Meisenberg and Woodley 2015). Finally, regarding cross-cultural differences in mean levels of GLS and DS, we expected that people in Serbia would report greater GLS than people in Iran (Hypothesis 6), in accordance with the findings showing that individuals in Serbia report slightly higher overall life satisfaction than individuals in Iran (Diener and Tay 2015; Helliwell et al. 2015). Concerning country differences in DS, however, no specific hypotheses were formulated, due to a lack of prior research on DS (as measured with the PWI) in Iran and Serbia.

Methods Sample and Procedure A total of 623 undergraduate students from Iran and Serbia participated in the present study. The Iranian sample consisted of 317 undergraduate students (55.5 % females), with a mean age of 23.07 years (SD = 4.46). The Serbian sample included 306 undergraduate students (54.6 % females) with a mean age of 21.75 years (SD = 1.84). Participation in the study was voluntary and participants did not receive any compensation. Questionnaires were administered in a group setting, in a paper-and pencil format. Instruments The Satisfaction with Life Scale (SWLS; Diener et al. 1985) is a 5-item scale (e.g., If I could live my life over, I would change almost nothing) designed to assess global life satisfaction. Items are rated on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). Both Serbian (e.g., Vasić et al. 2011) and Persian (e.g., Joshanloo 2013; Joshanloo and Afshari 2011) versions have shown adequate psychometric properties in previous studies. In the present study, Cronbach s alphas were .83 in the Serbian sample, and .77 in the Iranian sample.


The Personal Wellbeing Index-Adults (PWI-A; International Wellbeing Group 2006) was used to measure domain-specific life satisfaction. The official Persian and Serbian versions of the PWI-A were used in the present study. The PWI-A consists of seven items assessing satisfaction with the following seven domains: standard of living, health, achieving in life, relationships, safety, community-connectedness, and future security. Items are rated on an 11-point scale, from 0 (no satisfaction at all) to 10 (completely satisfied). The scale scores were transformed to a standard 0 to 100 range in order to enable comparisons with the previous studies. In the present study, the PWI-A demonstrated adequate internal consistencies both in Iran (α = .83) and Serbia (α = .83). Statistical Analyses We first examined the measurement invariance of the SWLS and PWI-A across Iran and Serbia, and across gender groups. Measurement invariance must be established before meaningful comparisons across groups can be made. Measurement invariance across groups was evaluated using a multi-group confirmatory factor analysis (MGCFA). Prior to the MGCFA, fit indices of the one-factor models of the SWLS and PWI-A were tested in each country and gender separately. The MGCFA method for invariance testing employs successive analyses with increasingly restricted models (Byrne and van de Vijver 2010; Davidov et al. 2012). Three levels of measurement invariance are usually distinguished in cross-cultural research: configural, metric and scalar. The baseline model is a configural (unconstrained) model, which implies the same number of factors in each group and the same pattern of fixed and free parameters. The metric (weak) model is nested in the configural model, and implies equal factor loadings across groups. The scalar (strong) model assumes both factor loadings and intercepts to be equal across groups. If full measurement invariance as described does not hold, partial measurement invariance is usually tested, in which some parameters are allowed to vary across groups. If (partial) metric invariance is supported, examining structural relationships between constructs can be conducted, whereas if (partial) scalar invariance is supported, means can be compared across groups. The fit of nested models is then evaluated by comparing ΔCFI and ΔRMSEA. Cut offs of .01 for ΔCFI and .015 for ΔRMSEA are used for testing significant differences between models (Chen 2007). Confirmatory factor analysis (CFA) and MGCFA were conducted using EQS 6.1. The parameter estimates were obtained using the robust maximum likelihood method with the Satorra-Bentler chi-square (SBχ2). The model fit was evaluated based on the CFI (Comparative Fit Index), RMSEA (Root Mean Square Error of Approximation) and SRMR (Standardized Root Mean Square Residual), whereas the SB χ2 was used for descriptive purposes only, because it is highly sensitive to sample size (Kline 2005). RMSEA values lower than .06 and .08, and CFI values greater than .95 and .90 were used as benchmarks for a good and acceptable model fit, respectively (Browne and Cudeck 1993; Hu and Bentler 1999). SRMR values less than .08 are generally considered as indicating a good fit. After measurement invariance testing, the contributions of DS to GLS were investigated via multiple regression analysis and relative weights analysis. In the presence of correlated predictors, beta weights might provide a biased estimate and are of limited value for interpreting the contribution of each predictor (Nimon and Oswald 2013).


Therefore, we used the MIMR-Raw.sps program (Lorenzo-Seva et al. 2010) to examine the relative contribution of each domain to GLS, and calculated relative weights reported as percentages, indicating the proportionate contribution each predictor made to R2. Country and gender differences in GLS were examined using a 2 (country) x 2 (gender) analysis of variance (ANOVA), while differences in DS were investigated using a 2-way multivariate analysis of variance (MANOVA).

Results Measurement Invariance of the SWLS Across Country and Gender Prior to testing for measurement invariance, we evaluated the original one-factor model of the SWLS for Iranian and Serbian students, and for women and men separately (Table 1). This model had a good fit based on the CFI and SRMR values in all subsamples, but RMSEA values were above threshold for an acceptable fit in all groups, except among Serbian students. An inspection of modification indices revealed a significant correlation between residuals of items 4 and 5, which was in accordance with previous studies (Clench-Aas et al. 2011; Joshanloo 2013). After allowing for these residuals to be correlated, the fit indices of the modified one-factor model improved. Therefore, the modified one-factor model allowing for correlation between errors between items 4 and 5 was used as a baseline model in measurement invariance testing. Table 1 Fit indices for structural models of the SWLS SBχ2(df)

RMSEA (90 % CI)

SRMR

CFI

Country Original one-factor model Serbia

13.19 (5)

.074 (.026–.123)

.032

.980

Iran

26.10 (5)

.116 (.074–.161)

.054

.953

Modified one-factor model Serbia

8.24 (4)

.059 (.000–.117)

.023

.989

Iran

13.65 (4)

.087 (.039–.140)

.028

.978

Gender Original one-factor model Women

20.39 (5)

.095 (.054–.139)

.038

.963

Men

22.43 (5)

.112 (.067–.161)

.057

.956

Modified one-factor model Women

15.19 (4)

.091 (.045–.141)

.030

.973

Men

5.59 (4)

.038 (.000–.104)

.018

.996

SB χ2 Satorra-Bentler scaled chi square, df degrees of freedom, RMSEA Root Mean Square Error of Approximation, CI Confidence Intervals, SRMR Standardized Root Mean Square Residual, CFI Comparative Fit Index


As shown in Table 2, the configural invariance model demonstrated a good fit across both country and gender. The full metric invariance did not hold either across country or across gender. The results revealed that loadings of items 2 and 3 were nonequivalent across groups. However, partial metric invariance freely estimating loadings of these two items was supported across both country and gender, as was evidenced by a nonsignificant drop in CFI and RMSEA indices when compared with configural models. The full scalar invariance was supported across gender, whereas a partial scalar invariance (wherein the intercept of item 1 was freely estimated) was supported across country. Taken together, these results allowed us to examine gender and country mean differences in GLS, as well as to compare structural relationships between GLS and DS. Measurement Invariance of the PWI-A Across Country and Gender Prior to testing for measurement invariance, we examined the original one-factor model of the PWI-A for Iranian and Serbian students, and for women and men separately. This model showed an acceptable fit among women and Serbian students, but a poor fit among men and Iranian students. An inspection of modification indices indicated that there was strong evidence of correlated residuals between items 4 and 6, and items 6 and 7 in men and Iranian students. To improve model fit, we decided to allow correlated residuals between these two pairs of items. The results revealed that the modified one-factor model of the PWI-A demonstrated a good fit to the data according to SRMR and CFI values both in Iran and among men, whereas RMSEA values indicated an acceptable fit in both groups (Table 3). Therefore, for testing measurement invariance, the original one-factor model of the PWI-A was used as a baseline model for women and the Serbian sample, whereas the modified one-factor model of the PWIA was used as a baseline model for men and the Iranian sample. As shown in Table 4, full scalar invariance of the PWI-A across gender was supported, as was a partial scalar invariance across country. These results enabled us Table 2 Fit indices and difference statistics for measurement invariance models of the SWLS ΔRMSEA

ΔCFI

SBχ2(df)

RMSEA (90 % CI)

Configural

21.90 (8)

.075 (.038–.113)

–

.984

–

Metric

75.99 (12)

.131 (.103–.159)

.056

.925

−.059

Partial Metric

30.23 (10)

.081 (.049–.115)

.006

.976

−.008

Scalar

103.52 (14)

.101 (.070–.133)

.020

.971

−.005

Partial Scalar

38.28 (13)

.084 (.052–.118)

.003

.979

.003

Configural

21.38 (8)

.074 (.037–.112)

–

.984

–

Metric

37.76 (12)

.083 (.054–.114)

.009

.968

−.016

Partial Metric

25.71 (10)

.071 (.038–.106)

−.003

.981

−.003

Scalar

33.34 (14)

.075 (.042–.109)

.004

.980

−.001

Model

CFI

Country

Gender

Partial Metric (loadings of items 2 and 3 freely estimated); Partial Scalar (intercept of item 1 freely estimated)

V. Jovanović et al. Table 3 Fit indices for structural models of the PWI − A SBχ2(df)

RMSEA (90 % CI)

SRMR

CFI

Country Original one-factor model Serbia

32.62 (14)

.066 (.037–.096)

.051

.945

Iran

72.67 (14)

.115 (.089–.141)

.067

.886

.080 (.051–.111)

.042

.953

Modified one-factor model Iran

36.43 (12)

Gender Original one-factor model Women

32.21 (14)

.062 (.034–.090)

.044

.964

Men

91.95 (14)

.142 (.114–.169)

.084

.864

.079 (.048–.112)

.052

.963

Modified one-factor model Men

33.07 (12)

SB χ2 Satorra-Bentler scaled chi square, df degrees of freedom, RMSEA Root Mean Square Error of Approximation, CI Confidence Intervals, SRMR Standardized Root Mean Square Residual, CFI Comparative Fit Index

to examine the contribution of DS to GLS and to test mean differences in DS and GLS across country and gender. The Relationships Between Domain Satisfaction and Global Life Satisfaction Across Country and Gender The results of multiple regression analyses and relative weights analyses which examine the relative contributions of seven life domains in predicting GLS in Iran and Table 4 Fit indices and difference statistics for measurement invariance models of the PWI-A ΔRMSEA

ΔCFI

SBχ2(df)

RMSEA (90 % CI)

Configural

67.25 (26)

.072 (.051–.092)

–

.950

–

Metric

89.85 (32)

.076 (.058–.095)

.004

.931

−.019

Partial Metric

76.27 (30)

.071 (.051–.090)

−.001

.944

−.006

Scalar

159.78 (36)

.094 (.076–.113)

.023

.938

−.006

Partial Scalar

112.50 (35)

.079 (.060–.098)

.008

.949

.005

Configural

64.47 (26)

.069 (.048–.090)

–

.964

–

Metric

87.98 (32)

.074 (.056–.094)

.005

.948

−.016

Partial Metric

69.12 (30)

.065 (.045–.085)

−.004

.964

.000

Scalar

89.08 (36)

.070 (.050–.089)

.005

.963

−.001

CFI

Country

Gender

Country: Partial Metric (loadings of items 3 and 7 freely estimated); Partial Scalar (loadings of items 3 and 7 and intercept of item 3 freely estimated). Gender: Partial Metric (loadings of item 6 and 7 freely estimated)

Gender, Culture, and Life Satisfaction Table 5 Regression of the seven domains of the PWI-A on the SWLS in Iran Total

Women

Men

β

RW (95 % CI)

β

RW (95 % CI)

β

RW (95 % CI)

Standard of living

.31**

28.2 (19.2–36.1)

.27**

23.8 (12.5–32.8)

.31**

27.8 (17.2–38)

Health

−.06

3.2 (1.6–7.6)

−.12

1.3 (.6–5.4)

.01

11.2 (5.5–18.5)

Achieving in life

.24**

24.3 (16–32.4)

.16

18.8 (9.1–30.5)

.30**

27 (18–33.5)

Personal relationships

.15**

14.8 (8.1–23.8)

.08

11.9 (4.7–24.5)

.18*

15.7 (6.8–26.7)

Safety

.05

11.3 (6.2–18)

.01

9.3 (4.3–17.6)

.04

12.3 (6–22.3)

Community

11*

10.8 (5.6–17)

18*

17.2 (8–28.4)

.09

4.7 (1.1–12.7)

Future security

.07

7.3 (3.5–14.3)

.19*

17.6 (8.7–27.5)

−.02

1.2 (.4–6.8)

R2

.45

.43

.50

* p < .05 ** p < .01

Serbia, broken down by gender, are shown in Table 5 (for Iran) and Table 6 (for Serbia). The strongest predictor of GLS in Iran was satisfaction with standard of living (β = .31, p < .01), followed by satisfaction with achieving in life (β = .24, p < .01), accounting for 28.2 and 24.3 % of R2, respectively. Contributions of personal relationships (β = .15, p < .01) and community (β = .11, p < .05) were also statistically significant in the Iranian sample, but the latter contributed only 10.8 % to R2. On the other hand, satisfaction with achieving in life (β = .33, p < .01) was the strongest predictor of GLS among Serbian students, accounting for 30.4 % of R2, followed by satisfaction with standard of living (β = .22, p < .01) and satisfaction with community (β = .16, p < .05), which contributed 18.1 and 13.3 % to R2, respectively.

Table 6 Regression of the seven domains of the PWI-A on the SWLS in Serbia Total

Standard of living

Women

Men

β

RW (95 % CI)

β

RW (95 % CI)

β

RW (95 % CI)

.22**

18.1 (9.6–27.4)

.17*

13.6 (2.7–28.5)

.25**

21.2 (10.1–35.4)

Health

.04

6.8 (2.5–14.3)

.13

12.1 (2.9–25.5)

.00

5.4 (1.5–12.8)

Achieving in life

.33**

30.4 (20–40.6)

.32**

32.3 (12.6–48.2)

.35**

29.1 (17.7–39.4)


.05

9.1 (3.7–17.1)

.03

6.9 (2.1–20.9)

.05

10 (4.5–18.9)

Safety

.12

12.5 (6.9–20.6)

.09

11.6 (3.8–23.4)

.13

12.7 (5.8–21.7)

Community

16*

13.3 (6.1–22.7)

.16

14.3 (4.4–29)

.13

11.2 (3.5–23.5)

Future security

.02

9.9 (5.3–16.4)

−.02

9.2 (3.8–20.3)

.07

10.5 (4.5–21.2)

R2

.45

* p < .05 ** p < .01

.37

.53


In the Serbian sample, satisfactions with standard of living and achieving in life contributed significantly to GLS in both women (β = .17, p < .05, β = .32, p < .01, respectively) and men (β = .25, p < .01, β = .35, p < .01, respectively), whereas the remaining domains were not significant predictors. However, the relative contribution of satisfaction with standard of living to GLS was rather small among females in Serbia, accounting for 13.6 % of R2. Satisfaction with standard of living was also a significant predictor of GLS among women (β = .27, p < .01, accounting for 23.8 % of R2) and men (β = .31, p < .01, accounting for 27.8 % of R2) in Iran. Satisfactions with achieving in life (β = .30, p < .01; relative contribution = 27 %) and personal relationships (β = .18, p < .05; relative contribution = 15.7 %) were significant predictors of GLS only among Iranian men, whereas satisfactions with community (β = .18, p < .05) and future security (β = .19, p < .05) were significant predictors of GLS only among Iranian women, accounting for 17.2 and 17.6 % of R2, respectively. It is important to note that whereas achieving in life was not a statistically significant predictor of GLS among Iranian women, its relative contribution (18.8 %) to GLS was comparable to contributions of satisfactions with community and future security in Iranian women. Interestingly, contributions of DS to GLS were exactly the same in Iranian and Serbian samples (R2 = .45 for both samples), but in both countries DS explained more variance among men (R2 = .50 in Iran, R2 = .53 in Serbia) than among women (R2 = .43 in Iran, R2 = .37 in Serbia). Differences in Global Life Satisfaction Across Country and Gender A 2 (country: Iran, Serbia) x 2 (gender: females, males) ANOVA was used to examine the differences in GLS (as measured with the SWLS) across country and age. The results indicated small effects of country (F(1, 617) = 40.65, partial η2 = .06) and gender (F(1, 617) = 9.95, partial η2 = .02), whereas the interaction between country and gender was not significant (F(1, 617) = .01, partial η2 = .00). Serbian students (M = 4.76, SD = 1.12) reported higher GLS (Cohen’s d = .51) than Iranian students (M = 4.16, SD = 1.25), and women reported higher GLS than men both in Iran (Cohen’s d = .24) and Serbia (Cohen’s d = .28). Differences in Domain Life Satisfaction Across Country and Gender A 2 (country: Iran, Serbia) x 2 (gender: females, males) MANOVA was used to examine the effects of country and gender and their interaction on satisfaction across seven life domains. The results showed significant effects for country (Wilks λ = .72, F(7, 611) = 34.46, partial η2 = .28), gender (Wilks λ = .94, F(7, 611) = 5.44, partial η2 = .06), and interaction between country and gender (Wilks λ = .96, F(6, 611) = 3.27, partial η2 = .04). The results of univariate tests showed that all domains contributed significantly to the differences between Iranian and Serbian students. Serbian students reported higher satisfaction with all seven life domains than Iranian students (see Table 7). The largest difference was observed in satisfaction with achieving in life (partial η2 = .24). Significant gender differences were observed for all domains (in favor of women), except for standard of living where no significant differences emerged. It is important to

4.29 (1.35)

66.59 (22.77)

67.50 (25.15)

71.31 (23.59)

71.65 (22.12)

58.98 (21.41)

76.59 (20.11)

55.34 (22.04)

LS Life satisfaction, SWLS Satisfaction with Life Scale

4.16 (1.25)

Global LS (SWLS)

68.04 (25.06)

Safety

61.20 (26.70)

66.56 (24.10)


62.02 (25.65)

55.93 (22.17)

Achieving in life

Future security

72.15 (21.62)

Health

Community

55.27 (22.15)

Standard of living

3.99 (1.11)

56.31 (27.89)

53.33 (26.58)

63.97 (26.29)

60.21 (25.03)

52.13 (22.58)

66.60 (22.23)

55.18 (22.38)

4.76 (1.12)

67.34 (23.78)

74.84 (23.87)

76.94 (21.27)

79.67 (18.79)

78.26 (17.89)

81.61 (17.83)

68.91 (19.98)

Total

Men

Total

Women

Serbia

Iran

Table 7 Mean scores (and standard deviations) across Iran and Serbia, broken down by gender

4.90 (1.02)

68.73 (22.43)

77.83 (22.19)

78.19 (20.37)

82.23 (18.89)

79.70 (17.87)

80.60 (18.93)

69.88 (19.51)

Women

4.59 (1.22)

65.65 (25.29)

71.23 (25.36)

75.43 (22.28)

76.59 (18.26)

76.52 (17.83)

82.83 (16.39)

67.75 (20.54)

Men

.06

.01

.08

.04

.09

.24

.06

.09

Country

.02

.02

.04

.01

.04

.02

.01

.00

Gender

.00

.01

01

.00

.01

.00

.02

.00

Country X Gender

Effect sizes (partial η2) for comparisons



note that gender differences were more pronounced in Iran than in Serbia. However, effects sizes for gender were small (partial η2 range from .01 to .04). The interaction between country and gender was significant only for satisfaction with health (partial η2 = .02). Iranian women reported greater satisfaction with health than Iranian men, whereas no significant differences between women and men were observed in Serbia.

Discussion The main aim of the present study was to examine the relative contributions of DS to GLS among women and men in Iran and Serbia. In addition, we investigated crosscountry and gender differences in both global and domain-specific satisfaction with life. The results showed that satisfactions with standard of living and achieving in life were the most significant predictors of overall life satisfaction both in Iran and Serbia (on a total sample level). These results are consistent with findings of previous studies that show that these two domains of the PWI-A tend to be the most robust predictors of overall life satisfaction across different cultures (e.g., International Wellbeing Group 2013; Renn et al. 2009; Smyth et al. 2010). Yet our findings do not support the prediction that people in collectivistic cultures (such as Iran and Serbia) would place greater value on interpersonal domains than achieving in life when judging overall life satisfaction. Two interpersonal domains of the PWI-A (personal relationships and community) demonstrated limited predictive value for GLS in both countries, suggesting that social relations are not a primary source of GLS among people in collectivistic cultures faced with challenging socio-economic conditions. Standard of living and achieving in life domains had similar contributions to GLS in Iran, whereas satisfaction with achieving in life was a stronger predictor of GLS than satisfaction with standard of living in Serbia (as shown in Tables 5 and 6). The greater relative importance of achieving in life than standard of living for GLS in Serbia is not consistent with previous findings that suggest that financial satisfaction should be a better predictor of life satisfaction than achieving in less economically developed countries such as Serbia (e.g., Diener and Diener 1995). This may be due to the fact that our samples consisted solely of undergraduate students, which may place less importance on standard of living in their university life as compared to individuals in later stages of life. Interestingly, the only significant predictors of GLS among Serbian women and men were satisfactions with standard of living and achieving in life, whereas gender-specific predictors of GLS emerged in Iran. Satisfactions with community and future security contributed significantly to GLS only among Iranian women, and satisfactions with personal relationships and achieving in life were significantly associated with GLS only among Iranian men (as shown in Table 5), although the relative contributions of personal relationships to GLS in Iran were similar across gender (11.9 % among women, and 15.7 % among men). The results regarding the importance of personal relationships for GLS among men and women in Iran do not support the assumption that social resources are more important for life satisfaction of women in this country. However, it is important to note that the personal relationships domain in PWI-A does


not specify whether it refers to family, friends or people in general, and thus it can be interpreted in various ways by respondents. The community domain contributed significantly to GLS only among Iranian women, but not Iranian men, suggesting that women in Iran may place greater value on the broader societal context. In addition to this domain, the future security domain was also a significant predictor of life satisfaction in Iranian women. Unequal opportunity and reduced access to goal-related resources for women in Iran (as indicated by a very high Gender Gap in Iran; World Economic Forum 2014) could lead to a greater uncertainty about the future as well as more concerns about one’s relationship with the larger society. In particular, exceptionally low levels of economic participation for women in Iran (World Economic Forum 2014) may lead to a dark outlook on one’s future security and social standing among young Iranian women who will be entering the job market in near future. This may partly explain the greater importance of these two domains for overall life satisfaction among Iranian women. We expected that due to substantial gender inequality in Iran, satisfaction with standard of living and achieving in life would be weaker predictors of GLS among Iranian women than men. However, the results of the present study only partially supported this hypothesis by indicating that satisfaction with standard of living contributed almost equally to GLS among Iranian women and men, whereas satisfaction with achieving in life was more important to GLS of Iranian men than women. These findings suggest that a low level of access to resources for Iranian women can reduce the importance of achieving in life as a source for making judgements about life satisfaction, but do not diminish the importance of standard of living among Iranian women. It appears that standard of living plays a prominent role in life satisfaction even when there is a limited access to economic resources. Our findings support both the universalist approach (insisting on universal predictors of life satisfactions across cultures) and the culture-specific approach (asserting that predictors of life satisfaction vary across cultures) to predictors of life satisfaction. Consistent with the universalist approach, satisfactions with standard of living and achieving in life were associated with GLS in both countries, but they were not equally important in Iran and Serbia, thus affirming the role of cultural and societal factors. The importance of community and future security for GLS among Iranian women, and personal relationships for GLS among Iranian men, but not among Serbian men and women, corroborates the culture-specific approach. These findings suggest that a thorough understanding of the role of specific life domains in life satisfaction across different countries must include cultural variables, such as values and social roles. The results of the contribution of DS to GLS are in accordance with the results of Diener and Tay (2015), who found that life satisfaction captured more dimensions of quality of life than just economic indicators. Although financial satisfaction is a robust predictor of life satisfaction across the world, post-materialist needs such as autonomy and respect are also associated with life satisfaction (Ng and Diener 2014). Our results support the importance of financial satisfaction among youth in Iran and Serbia, but also indicate that satisfaction with non-material domains such as achieving in life is essential to well-being. The implication of these findings is that researchers should measure both material and psychological determinants of well-being to yield a complete picture of life satisfaction and SWB.


Contributions of DS to GLS were exactly the same in Iranian and Serbian samples, thus explaining 45 % of the variance in GLS in both countries. The amount of explained variance is comparable to previous studies using the PWI-A (e.g., Lau et al. 2005; Renn et al. 2009). However, our results indicated that DS explained greater amount of variance in GLS among men (50 % in Iran, 53 % in Serbia) than women (43 % in Iran, 37 % in Serbia). These results suggest that satisfaction with specific domains of life as measured by the PWI-A are generally more important to men’s life satisfaction than women’s. This is in accordance with previous studies showing that a broader range of life domains is associated with women’s life satisfaction than men’s (Schafer et al. 2013). In addition, the PWI-A captures only a limited scope of life domains and does not include domains such as family which have been shown to be more important for females (e.g., Scott et al. 2010). We found that women reported greater global and domain specific life satisfaction, with the exception of satisfaction with standard of living where no significant differences between women and men were found. However, these gender differences were not large. These findings are in accordance with previous studies which demonstrated that women generally report higher levels of life satisfaction, but the impact of gender is rather small (e.g., Lucas and Gohm 2000). It is important to note that previous research on gender differences in life satisfaction has produced conflicting results. For example, Vieira Lima (2011) found that women have higher life satisfaction than men in developing countries and lower life satisfaction in rich countries, whereas Graham and Chattopadhyay (2013) report that women are more satisfied than men, except in low-income countries. Studies trying to explain this women-men well-being gap have also produced inconsistent findings. Zweig (2015) argued that gender differences in life satisfaction were not associated with economic development and women’s rights, whereas Tesch-Römer et al. (2008) found that gender inequality affects gender gap in life satisfaction. Our results show that gender differences in life satisfaction (in favor of women) are larger in Iran, which has greater gender inequality than Serbia. Thus, our results suggest that women can still be more satisfied with their lives than their male counterparts even in the face of gender inequality. It should also not be forgotten that Iran has made considerable progress towards gender equality in the field of tertiary education over the past decade (World Economic Forum 2014), which may contribute to female students’ greater life satisfaction. Finally, the cross-country comparison of overall life satisfaction, showing greater GLS in Serbia than Iran, is in line with the findings of global surveys on well-being that show somewhat higher SWB in Serbia than Iran (e.g., Helliwell et al. 2015). In addition, compared with Iranian students, Serbian students consistently reported higher life satisfaction across different life domains. Although data from a Gallup-Healthways poll indicate that people in Iran report somewhat higher levels of well-being across different components (financial, community, and physical) than people in Serbia (Gallup 2014), these results are not comparable due to the different methodology – a single-item measure of DS within PWI-A, and multi-item measures used by Gallup which capture different aspects of well-being. In the present study, the largest differences were observed for satisfaction with achieving in life, such that Iran scored remarkably lower than Serbia. This may indicate that Iranian university students set higher standards for evaluating their levels of achievement than Serbian students do.


But this may also reflect the fact that Iranian society is dealing with high rates of inflation and unemployment (Looney 2012), which may come to affect young people’s satisfaction with their levels of achievements at present and in the near future. However, given the dearth of studies on domain satisfaction in the countries under scrutiny here, these should be considered speculations. Future studies along these lines could help to better understand these cultural differences. Considering the poor social and economic conditions in Serbia, one would expect lower levels of life satisfaction among Serbian youth. However, in the current study the average satisfaction of Serbian students with most domains is similar to life satisfaction of students in developed European countries such as Austria (Renn et al. 2009) and the Netherlands (Van Beuningen and de Jonge 2011). Yet, levels of satisfactions with standard of living and future security reported by Serbian students in the present study are lower in comparison to those previously found among students in developed countries. These two domains, along with satisfactions with achieving in life and community, were also the lowest among Iranian students. A similar pattern of results was obtained in a recent study conducted in a representative sample in Croatia (Kaliterna and Burusic 2014), with young adults aged between 18 and 25 years showing the lowest satisfaction with material status and future security. The results regarding satisfaction with standard of living is to be expected because both Iran and Serbia rank low on indicators of economic and social development. Relatively low levels of satisfaction with future security indicate that students both in Iran and Serbia have modest expectations regarding their future, which is understandable given the high youth unemployment rates in both countries (about 30 % in Iran, and about 50 % in Serbia; World Bank 2015). These results should cause concern because positive expectations about the future are fundamental for human adaptation and well-being (Carver et al. 2010). Our findings are in keeping with studies that show people in Iran and Serbia have scores below the international average on optimism (Gallagher et al. 2013). Our study highlights the importance of culture and gender in research into the relationships between DS and GLS, but there are several important limitations that should be kept in mind. First, the study samples included only undergraduate students, so findings cannot be generalized to other age groups. Second, we used cross-sectional design, which did not allow us to test the causal direction between GLS and DS. Third, we did not control for a number of socio-demographic and economic factors (e.g., income, socio-economic status), which might be different among students in Iran and Serbia. Finally, although the PWI-A has been found to demonstrate acceptable reliability and validity despite its short length (International Wellbeing Group 2013), given that it measures each domain of life by a single item, future research may benefit from using multiple-item scales of domain satisfaction for a more comprehensive assessment of domain satisfaction (Diener et al. 2013). Despite these limitations, the present study provided new insights into the relationship between DS and GLS in two relatively understudied cultures. The study also shed light on the role gender plays in this relationship. We found similarities and differences across both the countries and gender groups. As discussed, whereas many of our findings are in line with previous empirical evidence, some were unprecedented, which indicate areas where more research is required. We also reported promising findings on the statistical properties of the scales used in the present study. Evidence on


measurement invariance of the scales rules out the possibility that the cross-cultural and cross-gender differences we reported are due to differential test functioning. Hence it is hoped that this study contributes to the growing literature that aims to internationalize the study of mental well-being. Given the lack of relevant studies on DS and its relationship with GLS, further research is certainly needed to fully elucidate the factors influencing how people evaluate their life domains in diverse cultural contexts. Acknowledgments This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant No. 179006). Compliance with Ethical Standards Conflict of Interest

The authors declare that they have no conflict of interest.

References Bonini, A. (2008). Cross-national variation in individual life satisfaction: Effects of national wealth, human development, and environmental conditions. Social Indicators Research, 87, 223–236. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing Structural Equation Models (pp. 136–162). Beverly Hills: Sage. Byrne, B. M., & van de Vijver, F. (2010). Testing for measurement and structural equivalence in large-scale cross-cultural studies: Addressing the issue of nonequivalence. International Journal of Testing, 10, 107– 132. Carver, C. S., Scheier, M. F., & Segerstrom, S. C. (2010). Optimism. Clinical Psychology Review, 30, 879– 889. Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14, 464–504. Clench-Aas, J., Nes, R. B., Dalgard, O. S., & Aaro, L. E. (2011). Dimensionality and measurement invariance in the Satisfaction with Life Scale in Norway. Quality of Life Research, 20, 1307–1317. Cummins, R. A. (1996). The domains of life satisfaction: An attempt to order chaos. Social Indicators Research, 38, 303–328. Cummins, R. A. (1997). Comprehensive Quality of Life Scale – Adult. Manual (5th ed.). Melbourne: School of Psychology, Deakin University. Cummins, R. A., Eckersley, R., Pallant, J., Van Vugt, J., & Misajon, R. (2003). Developing a national index of subjective wellbeing: The Australian Unity Wellbeing Index. Social Indicators Research, 64, 159–190. Daig, I., Herschbach, P., Lehmann, A., Knoll, N., & Decker, O. (2009). Gender and age differences in domainspecific life satisfaction and the impact of depressive and anxiety symptoms: A general population survey from Germany. Quality of Life Research, 18, 669–678. Davidov, E., Dülmer, H., Schlüter, E., Schmidt, P., & Meuleman, B. (2012). Using a multilevel structural equation modeling approach to explain cross-cultural measurement noninvariance. Journal of CrossCultural Psychology, 43, 558–575. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575. Diener, E. (2009). Culture and well-being: The collected works of Ed Diener (Social Indicators Research Series, Vol. 38). The Netherlands: Springer. Diener, E., & Diener, M. (1995). Cross-cultural correlates of life satisfaction and self-esteem. Journal of Personality and Social Psychology, 68, 653–663. Diener, E., & Fujita, F. (1995). Resources, personal strivings, and subjective well-being: A nomothetic and idiographic approach. Journal of Personality and Social Psychology, 68, 926–935. Diener, E., & Tay, L. (2015). Subjective well‐being and human welfare around the world as reflected in the Gallup World Poll. International Journal of Psychology, 50, 135–149. Diener, E., Emmons, R., Larsen, R., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49, 71–75.

Gender, Culture, and Life Satisfaction Diener, E., Inglehart, R., & Tay, L. (2013). Theory and validity of life satisfaction scales. Social Indicators Research, 112, 497–527. Gallagher, M. W., Lopez, S. J., & Pressman, S. D. (2013). Optimism is universal: Exploring the presence and benefits of optimism in a representative sample of the world. Journal of Personality, 81, 429–440. Gallup, Inc. (2014). State of global well-being: Results of the Gallup-Healthways Global Well-being Index. Retrieved Jun 10, 2015, from:http://info.healthways.com/hs-fs/hub/162029/file-1634508606-pdf/ WBI2013/Gallup-Healthways_State_of_Global_Well-Being_vFINAL.pdf. Graham, C., & Chattopadhyay, S. (2013). Gender and well-being around the world. International Journal of Happiness and Development, 1, 212–232. Helliwell, J., Layard, R., & Sachs, J. (2015). World Happiness Report. New York: Earth Institute, Columbia University. Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and Organizations: Software of the Mind (3rd ed.). New York: McGraw-Hill. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. International Wellbeing Group. (2006). Personal Wellbeing Index–Adult (PWI–A). Melbourne: Australian Centre on Quality of Life, Deakin University. International Wellbeing Group. (2013). Personal Wellbeing Index (5th ed.). Melbourne: Australian Centre on Quality of Life, Deakin University. Joshanloo, M. (2013). The influence of fear of happiness beliefs on responses to the Satisfaction with Life Scale. Personality and Individual Differences, 54, 647–651. Joshanloo, M., & Afshari, S. (2011). Big five personality traits and self-esteem as predictors of life satisfaction in Iranian Muslim university students. Journal of Happiness Studies, 12, 105–113. Kaliterna, Lj., & Burusic, J. (2014). Age and gender differences in well-being in Croatia. Social Indicators Research Series, 53, 249–262. Kapteyn, A., Smith, J. P., & Van Soest, A. (2010). Life satisfaction. In E. Diener, J. E. Helliwell, & D. Kahneman (Eds.), International differences in well-being (pp. 70–104). Oxford: Oxford University Press. Kline, R. B. (2005). Principles and practices of structural equation modeling (2nd ed.). New York: Guilford Press. Lau, A. L. D., Cummins, R. A., & McPherson, W. (2005). An investigation into the cross-cultural equivalence of the Personal Wellbeing Index. Social Indicators Research, 72, 403–430. Legatum Institute. (2014). The 2014 Legatum Prosperity Index. Retrieved May 5, 2015, from http://media. prosperity.com/2014/pdf/publications/PI2014Brochure_WEB.pdf. Loewe, N., Bagherzadeh, M., Araya-Castillo, L., Thieme, C., & Batista-Foguet, J. M. (2014). Life domain satisfactions as predictors of overall life satisfaction among workers: Evidence from Chile. Social Indicators Research, 118, 71–86. Looney, R. (2012). The Iranian economy: The glass half empty. London: The Legatum Institute. Lorenzo-Seva, U., Ferrando, P. J., & Chico, E. (2010). Two SPSS programs for interpreting multiple regression results. Behavior Research Methods, 42, 29–35. Lucas, R. E., & Gohm, C. L. (2000). Age and sex differences in subjective well-being across cultures. In E. Diener & E. M. Suh (Eds.), Culture and subjective well-being (pp. 291–318). Massachusetts: Bradford. Meisenberg, G., & Woodley, M. A. (2015). Gender differences in subjective well-being and their relationships with gender equality. Journal of Happiness Studies, 16, 1539–1555. Morrison, M., Tay, L., & Diener, E. (2011). Subjective well-being and national satisfaction: Findings from a worldwide survey. Psychological Science, 22, 166–171. Ng, W., & Diener, E. (2014). What matters to the rich and the poor? Subjective well-being, financial satisfaction, and post-materialistic needs across the world. Journal of Personality and Social Psychology, 107, 326–338. Nimon, K. F., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16, 650–674. Oishi, S., Diener, E. F., Lucas, R. E., & Suh, E. M. (1999). Cross-cultural variations in predictors of life satisfaction: Perspectives from needs and values. Personality and Social Psychology Bulletin, 25, 980– 990. Pavot, W., & Diener, E. (2009). Review of the Satisfaction With Life Scale. Assessing well-being. Social Indicators Research Series, 39, 101–117. Pinquart, M., & Sorensen, S. (2000). Influences of socioeconomic status, social network, and competence on subjective well-being in later life: A meta-analysis. Psychology and Aging, 15, 187–224. Renn, D., Pfaffenberger, N., Platter, M., Mitmansgruber, H., Cummins, R. A., & Hofer, S. (2009). International well-being index: The Austrian version. Social Indicators Research, 90, 243–256.

V. Jovanović et al. Rojas, M. (2006). Life satisfaction and satisfaction in domains of life: Is it a simple relationship? Journal of Happiness Studies, 7, 467–497. Rojas, M. (2007). The complexity of wellbeing: A life-satisfaction conception and a domains-of-life approach. In I. Gough & J. A. McGregor (Eds.), Wellbeing in developing countries: From theory to research (pp. 259–280). Cambridge: Cambridge University Press. Schafer, M. H., Mustillo, S. A., & Ferraro, K. F. (2013). Age and the tenses of life satisfaction. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 68, 571–579. Schimmack, U. (2008). The structure of subjective wellbeing. In M. Eid & R. J. Larsen (Eds.), The science of subjective well-being (pp. 97–123). New York: Guilford. Schimmack, U., Diener, E., & Oishi, S. (2002). Life-satisfaction is a momentary judgment and a stable personality characteristic: The use of chronically accessible and stable sources. Journal of Personality, 70, 345–384. Scott, J., Plagnol, A. C., & Nolan, J. (2010). Perceptions of quality of life: Gender differences across the life course. In J. Scott, R. Crompton, & C. Lyonette (Eds.), Gender inequalities in the 21st century: New barriers and continuing constraints (pp. 193–214). Edward Elgar: Cheltenham. Sirgy, M. J., Widgery, R. N., Lee, D., & Yu, G. B. (2010). Developing a measure of community well-being based on perceptions of impact in various life domains. Social Indicators Research, 96, 295–311. Smyth, R., Nielsen, I., & Zhai, Q. (2010). Personal wellbeing in urban China. Social Indicators Research, 95, 231–251. Tesch-Römer, C., Motel-Klingebiel, A., & Tomasik, M. J. (2008). Gender differences in subjective wellbeing: Comparing societies with respect to gender equality. Social Indicators Research, 85, 329–349. Theuns, P., Baran, B., Van Vaerenberg, R., Hellenbosch, G., & Tiliouine, H. (2012). A cross-cultural experimental approach to the contribution of health, religion and personal relations to subjective satisfaction with life as a whole. Psicológica, 33, 591–608. Transparency International. (2014). Corruption Perceptions Index. Retrieved Jun 5, 2015, from: http://www. transparency.org/cpi2014/results. Uchida, Y., & Ogihara, Y. (2012). Personal or interpersonal construal of happiness: A cultural psychological perspective. International Journal of Wellbeing, 2, 354–369. Van Beuningen, J., & de Jonge, T. (2011). The Personal Wellbeing Index: Construct validity for the Netherlands. Discussion paper (201124). Statistics Netherlands: The Hague. van Praag, B. M. S., Frijters, P., & Ferrer-i-Carbonell, A. (2003). The anatomy of subjective well-being. Journal of Economic Behavior and Organization, 51, 29–49. Vasić, A., Šarčević, D., & Trogrlić, A. (2011). Zadovoljstvo životom u Srbiji [Satisfaction with life in Serbia]. Primenjena Psihologija, 2, 151–177. Veenhoven, R. (2012). Cross-national differences in happiness: Cultural measurement bias or effect of culture? International Journal of Wellbeing, 2, 333–353. Vieira Lima, S. (2011). A cross-country investigation of the determinants of the happiness gender gap. Mimeo.University of Milan-Bicocca, Department of Economics, Milan, Italy. World Bank. (2015). World databank. [Custom cross-tabulation of data]. Retrieved July 3, 2015, from: http:// data.worldbank.org/indicator/SL.UEM.1524.ZS. World Economic Forum (2014). The Global Gender Gap Report 2014. Retrieved July 7, 2015, from: http:// www3.weforum.org/docs/GGGR14/GGGR_CompleteReport_2014.pdf. York, R., & Bell, S. E. (2014). Life satisfaction across nations: The effects of women’s political status and public priorities. Social Science Research, 48, 48–61. Zweig, J. S. (2015). Are women happier than men? Evidence from the Gallup World Poll. Journal of Happiness Studies, 16, 515–541.