What Makes Young Russians Happy and Satisfied With Their Lives?

Abstract

Participants (N = 10,672 with the mean age of 20.7 years) of the Russian Character and Personality Survey (RCPS), involving 40 universities or colleges from across the Russian Federation, rated their happiness and satisfaction with life; the ratings were combined into an index of subjective well-being (SWB). Using the National Character Survey (NCS), participants also rated their own personality characteristics as well as those of an ideal person and a typical Russian living in their own region. Only two personality (test) subscales—N3: Depression and E6: Positive Emotions—were correlated with SWB on the between-individual level of analysis. Although spiritual values associated with a negative attitude toward money are typically regarded as an essential part of the Russian national character, our results demonstrated that only satisfaction with one’s own financial situation was a reliable predictor of SWB. In those regions where people had, on average, a higher life expectancy, better education, and a higher level of wealth, individuals also tended to be happier and more satisfied with their lives.

Keywords

subjective well-being happiness life satisfaction National Character Survey

Leo Tolstoy’s memorable Anna Karenina starts with an often-cited observation that “Happy families are all alike; every unhappy family is unhappy in its own way.” However, this observation may only partly be true. Increasing evidence suggests that in different parts of the world, people may be happy in their own way (Kööts-Ausmees, Realo, & Allik, 2013; Kuppens, Realo, & Diener, 2008). Although money cannot buy happiness (Ahuvia, 2008; Diener & Biswas-Diener, 2002, 2009; Fischer & Boer, 2011; Graham, 2011), it is hard to be satisfied with your life when you need to struggle with the scarcity of material resources (Diener & Seligman, 2004; Srivastava, Locke, & Bartol, 2001). Because the availability of financial and material resources differs substantially both across and within cultures, it is also expected that people find different ways of being happy. In other words, “most people are pretty happy,” as Biswas-Diener, Vittersø, and Diener (2005) argued, not only in industrialized societies but also in cultures where people lead materially simple lives—there just seem to be many alternative ways of being happy and satisfied with one’s life.

Besides living conditions and health, personality characteristics may be associated with subjective well-being (SWB), mainly because they are difficult to separate. By examining how one usually feels, thinks, and behaves—typically referred to as one’s personality characteristics (McCrae & Costa, 2003)—it is possible to predict with reasonable accuracy how happy and satisfied one is with his or her life or SWB (Lucas & Diener, 2008). It was concluded more than 15 years ago that “a substantial portion of stable SWB is due to personality” (Diener & Lucas, 1999, p. 214), and a later meta-analyses of hundreds of personality traits demonstrated that, among other findings, those associated with the Neuroticism, Extraversion, and Agreeableness dimensions are indeed linked to SWB (DeNeve & Cooper, 1998; Steel, Schmidt, & Shultz, 2008). This suggests that some people simply tend to be on average happier than others, regardless of their everyday circumstances. However, individual differences may not be the only reason as to why countries may differ in the average level of happiness. Because the mean difference in personality traits across countries is about 8.5 times smaller than the difference between any two individuals, randomly selected from these samples (Allik et al., 2017), it may not be enough to explain the observed cultural differences in terms of SWB.

Although the general link between SWB and personality has been firmly established, the precise nature of this association remains problematic. It is more or less obvious that Neuroticism is linked negatively, and Extraversion and Conscientiousness positively to SWB (DeNeve & Cooper, 1998; Dobewall, Realo, Allik, Esko, & Metspalu, 2013; Hayes & Joseph, 2003; Lucas & Diener, 2008; Steel et al., 2008; Vittersø, 2001; Weiss, Bates, & Luciano, 2008), but the contribution of other personality dimensions, as well as their specific facets, to SWB is less clear.

One reason for this is the complicated nature of personality judgments themselves. When an individual describes his or her personality, or somebody’s personality he or she knows sufficiently well, the resulting personality scores are a mixture of different components. In addition to differential information—in what way a person (the target of his or her ratings) is different from other people—scores also contain information about stereotypic accuracy (similarity of all people) and social desirability (Cronbach, 1955; Cronbach & Gleser, 1953; Gage & Cronbach, 1955). When we observe correlation between SWB and personality traits, we are not generally aware of which components of personality judgments are responsible for the observed correlation. It is logical to expect that differential information explains the lion’s share of this correlation; but, it is not impossible for stereotypic accuracy to be responsible for the observed link (at least in part), also.

Although basic techniques on how to separate the distinctiveness of personality profiles (differential accuracy) from normativeness (stereotypic accuracy) are nowadays widely used (Allik, Borkenau, Hrebícková, Kuppens, & Realo, 2015; Bernieri, Zuckerman, Koestner, & Rosenthal, 1994; Borkenau & Zaltauskas, 2009; Furr, 2008), these methods are not very useful if we are to examine the relationship between personality traits and some external variables. If we transform personality scores using a linear transformation (e.g., by standardizing them by fixing their means to zero—the operation required for computing distinctiveness scores), the correlations with external variables remain unchanged. This means that for identifying different components of personality judgment, we need to use other techniques.

One of these alternative methods is to administer the same personality questionnaire using different instructions. For example, in addition to asking people to faithfully describe their own personalities, it is also possible to instruct participants to describe the personality of a “generalized” person. In this study, we asked our participants to describe the personality traits of an ideal person (Edwards, 1957): “Please try to describe an ideal person with the most desirable personality characteristics.” The same group of participants were also asked to rate a typical Russian living in their region (cf. Allik, Mõttus, & Realo, 2010). Using different instructions, it was possible to distinguish the contributions of different components of judgments. Another instruction is to describe a typical representative of a nation (Terracciano et al., 2005) or a ethnical group (Allik, Alyamkina, & Meshcheryakov, 2015).

We cannot rule out, however, that SWB is essentially a normative concept. Imagine that the descriptions of an ideal person, not self-descriptions, are better predictors of SWB. For example, the more a person thinks that positive mood, friendliness, and dutifulness are socially desirable traits, the more satisfied he or she is with his or her life. An analogous relationship may exist between national stereotypes and SWB. Let us suppose that our participants think that a typical Russian is jovial, outgoing, and open-minded. Those who more strongly endorse this particular national stereotype are also happier and more satisfied with their lives. On the contrary, those who think that a typical Russian is miserable, timid, and bigoted are also unhappy and dissatisfied with their lives. Of course, these different scenarios of the relationship between different components of personality judgment and SWB do not exclude each other. They may contribute simultaneously to the relationship but with different strengths. One of the main aims of this article is to establish to what extent different components of personality ratings contribute to SWB.

Approximately 10 years ago, Russia ranked 168 out of 178 countries on the Satisfaction with Life Index (White, 2007). In the World Database of Happiness, participants are asked to answer the question, “Taking all together, how satisfied or dissatisfied are you currently with your life as a whole?” Using the scale from 1 = dissatisfied to 10 = satisfied, Russia ranked, with the mean score 4.3, 83 out of 91 nations in early 2000s (Veenhoven, 2009). Since then, the life satisfaction of Russians has increased. For example, Russia’s score in the Better Life Index has climbed up to 6.0 points out of 10 in 2015 (Organisation for Economic Co-operation and Development [OECD], 2015), which is still lower than the OECD average of 6.5. Although SWB in Russia is now approximately on the same level with Greece, Portugal, and some post-Communist countries, including Latvia and Estonia, it is still in the lower parts in different rankings (Abbott & Sapsford, 2006; Cavallo et al., 2015; Decancq, 2017; Easterlin, 2009; Habibov & Afandi, 2015; Ryan et al., 1999). Indeed, as can be predicted from socio-economic indicators (Mizobuchi, 2017), it seems that Russians have lower life satisfaction. It ought to be noted, however, that recent evidence suggests an upward trend in the levels of SWB in Russia as the SWB level of Russians, according to the 2017 World Happiness Report, ranks 49 out of 155 countries (Helliwell, Layard, & Sachs, 2017).

With the exception of 2017 World Happiness Report, the consistently low positions have raised some doubts that Russian data may not reflect Russians’ self-appraisals adequately, due to distortions in translation and a differential response bias (Veenhoven, 2001). Recently, it was proposed that Russians (compared with Americans and other Western nations) reported greater inhibition of the expression of happiness. In other words, there may be a cultural norm which deters Russians from displaying the happiness they actually feel (Lynch, La Guardia, & Ryan, 2009; Sheldon et al., 2017). Although likely, it remains to be demonstrated if the size of the inhibition is large enough to explain the relatively low position of Russians in the overall ranking of happiness. Also, proof is needed that Russian cultural display rules are more restrictive than those of other cultures (cf. Safdar et al., 2009). It was observed, for example, that Russians tend to express emotions with higher authenticity than Germans (Mendzheritskaya, Hansen, & Horz, 2015), which may cast doubt on the theory of cultural inhibition.

It has been proposed that social and economic hardships, a high crime rate, and high levels of alcohol consumption are among the main factors that contribute to relatively low levels of life satisfaction in Russia, although the direction and presence of the cause and effect may be disputed (Frijters, Geishecker, Haisken-DeNew, & Shields, 2006; Massin & Kopp, 2014; Stickley, Koyanagi, Roberts, Goryakin, & McKee, 2015). It is well known that in countries with high levels of human development, life satisfaction becomes disentangled from money (Diener & Biswas-Diener, 2002; Diener, Diener, & Diener, 1995; Diener & Seligman, 2004; Kuppens et al., 2008). The same rule is valid at the level of individual because emotional well-being seems to stop rising beyond a certain annual income (Kahneman & Deaton, 2010). Thus, Russia belongs to a group of nations where the link between life satisfaction and material factors may be still present.

In addition, we cannot neglect a possibility that cultural factors determine, at least in part, the level of life satisfaction. A common view, as noticed by Joshanloo and Weijers (2014), in contemporary Western culture is that personal happiness is one of the most important values in life. For example, in American culture, unlike many others, it is believed that failing to appear happy is cause for concern. The authors of that article introduced the concept of aversion of happiness (Joshanloo and Weijers, 2014), which may be relatively widespread in some cultures and not in others. It is possible that a low level of life satisfaction among Russians is the result of this aversion to happiness. Indeed, Anna Wierzbicka identified one of several keywords that most accurately reflects the Russian mentality as toska (“melancholy”; Wierzbicka, 1992). Although a previous study failed to identify unhappiness as a unique trait of the Russian soul (Allik et al., 2011), it may be possible that Russian culture, unlike American culture, does not produce the same degree of pressure toward the attainment of happiness, which may also lower Russian SWB scores. Yet, another possibility is that discrepancies between ideal and actual self-concept would be negatively associated with well-being. Because actual Russian self-concept may be more distant to their ideal, a low level of life satisfaction among Russians can be attributed this discrepancy (Lynch et al., 2009).

It is often alleged that the Russian national character is unique, being very different from European and Asian cultures (Allik et al., 2011). Among the allegedly unique features, Russians have generally negative attitudes toward money and material welfare (Trifonova, 2005). Russia is apparently one of the few places where the biblical wisdom that “it is easier for a camel to go through the eye of a needle than for someone who is rich to enter the kingdom of God” is believed to be true. In contrasting themselves with the materialistic cultures of the West, Russians began to define themselves in terms of their spiritual qualities, through their distinctive “Russian soul” (Allik et al., 2011). The spiritual values of Russians are perceived as an alternative to the mentality of Western culture, which is considered exceedingly materialistic, lacking a desirable spirituality (Wierzbicka, 2002). Provided that Russian mentality is based on exceptional spiritual foundation, it is expected that the notion of money and happiness is incongruous, which finds support among a sizable portion of the Russian population. For example, researchers have found some evidence that negative attitudes toward money are associated with a higher level of trust, tolerance, and civic identity (Tatarko & Schmidt, 2012). From another perspective, ignoring unfavorable material conditions is a rational strategy for protecting one’s life satisfaction from a direct dependence on material conditions.

The purpose of this study is to identify factors that are associated with young Russians’ happiness and life satisfaction. In the Russian Character and Personality Survey (RCPS; Allik et al., 2009; Allik et al., 2011), more than 10,000 participants from 40 universities or colleges from 34 federal constituents (republics and other administrative areas) contributed to the survey in 2006 to 2007. Participants were students with a mean age of around 21 years. Although more than 60 different nationalities were mentioned in the response forms, respondents were sufficiently proficient in Russian to answer items written in Russian. Because economic and political conditions have changed substantially over the last decade, the picture obtained by the RCPS potentially characterizes a bygone time. However, these more than 10,000 participants are now in their mid-30s, which means they most likely form the most active part of Russian society in terms of their productivity. Therefore, knowing the decade-old associations of their SWB may also help to explain how they feel, think, and perform nowadays, in modern-day Russia.

Method

Participants and Procedure

Members of the RCPS, which involved 40 universities or colleges from across the Russian Federation, collected valid data from 10,672 participants. The 40 samples were collected in 34 federal regions (oblast, krai, okrug, or republic), of which six (Novosibirsk, Primorsk, Sverdlovsk, Tatarstan, Udmurtia, and Volgograd) were represented by two samples. Data were collected during the period 2006 to 2007. More precise information about RCPS can be found in our previous publications (Allik et al., 2010; Allik et al., 2009; Allik et al., 2011).

Each of the 40 samples was divided into two separate groups. The first group in each sample (3,705 participants across all samples; mean age: 20.7 ± 2.9 years; 75% women) was instructed to fill in the National Character Survey, or the NCS (Terracciano et al., 2005), three times. The number of participants varied slightly across the three conditions. The questionnaire was administered in three stages, to ensure that respondents did not know they would be rating a typical Russian, an ideal person, and themselves before they started. First, they were asked to rate a typical Russian living in their region (stereotype ratings; N = 3,677). After completing the first task, collaborators asked participants orally to proceed to the next page, which contained the same NCS items but with no instructions. Participants were then instructed orally to complete the inventory by rating their own personality traits (self-ratings; N = 3,672). Finally, participating students were instructed to describe the personality traits of an ideal person using the same scale a third time (ideal ratings; N = 3,610). The instructions were as follows:

Finally, we would like to know which answers to the inventory items would be most desirable when one is trying to gain the approval of other people. In other words, please try to describe an ideal person with the most desirable personality characteristics.

In each of the 40 samples, the second group of participants (N = 7,065; 78% women; mean age: 20.9 ± 3.6 years) was asked, in addition to self-ratings using the NCS, to identify an ethnically Russian adult or college-aged man or woman they knew well and to rate this target using the Russian observer-rating version of the Neuroticism-Extraversion-Openness Personality Inventory–Revised (NEO PI-R; not considered in this article). Together with the first group of participants, the number of valid NCS self-rating protocols was 10,672. All questionnaires contained items measuring happiness, life satisfaction, religiosity, and other topics.

Measures

SWB

The questionnaire contained two items which measured SWB. The items were taken from the questionnaire of the World Values Survey and were worded as follows: “All things considered, how satisfied are you with your life as a whole these days?” The response scale consisted of a 10-point scale, with extreme points labeled 1 = completely dissatisfied and 10 = completely satisfied. The second happiness item can be translated so: “Taking all things together, would you say you are ‘very happy,’ ‘rather happy,’ ‘not very happy,’ and ‘not at all unhappy’?” The correlation between these two items was sufficiently high: r = .48, N = 10,487, p < .00001. One reason why this correlation was slightly lower than usual was due to the shorter response scale for the happiness item. However, the correlation was high enough to combine answers on these two items into a single SWB index. To accomplish this, both scores were initially standardized (M = 0, with SD = 1) and then summed.

NCS

The NCS consists of 30 bipolar scales with two or three adjectives or phrases at each pole of the scale (Terracciano et al., 2005). For example, the first item asks how likely it is that the assessed target is anxious, nervous, and worried versus how at ease, calm, or relaxed he or she is. There are five response options between the poles. Each of the bipolar scales measures one of the 30 facets assessed by the NEO PI-R (McCrae & Costa, 2010), with six items for each of the five major dimensions of personality traits. Although the NCS was initially designed for measurement of national stereotypes, it is also suitable for measuring self-ratings and social desirability (Allik et al., 2010; Realo et al., 2009).

Satisfaction with financial situation (SFS)

Participants were asked about satisfaction with their financial situation. The response scale had 10 points ranging from 1 = very unsatisfied to 10 = extremely satisfied.

Subjective social status (SSS or MacArthur Ladder)

Participants were asked to position themselves on an imaginary 10-step social or MacArthur ladder (Adler, Epel, Castellazzo, & Ickovics, 2000). The item read,

People belong to different strata of society. It could be imagined as a ladder along which one can move up, as well as down, in society. The top of the ladder represents the highest position in society in terms of wealth and influence. At the bottom of the ladder are those who are literally expelled from the society. Where would you place yourself on this ladder?

Participants were asked to place themselves on the step that they, though, best represented their social standing.

Religiosity

Religiosity was measured with a 10-point response scale, with the extremes marked: 0 = not religious at all and 10 = deeply religious. The item translates to the following: “With no regard to belonging to any confession or religious group, how religious do you consider yourself?”

Materialism–idealism

Participants were asked to decide to which opposite points of view they feel more sympathy. For example, one pair of opposing views stated that “Material things are no less important than spiritual” and “Spiritual is primary and material is secondary.” These descriptions marked the opposite ends on a 10-point response scale.

Regional Level Indicators

Human Development Index (HDI)

The 34 federal regions were characterized by a set of demographic (density of population) and socioeconomic indicators. The HDI, characterizing each federal region, was obtained from the Independent Institute for Social Policy (IISP) homepage (Allik et al., 2009). The HDI is a combined measure of life quality, which is computed on the basis of three indicators with equal weight: life expectancy at birth, overall literacy combined with secondary and tertiary education enrollment ratio, and gross domestic product (GDP) per capita at purchasing power parity in U.S. dollars.

Index of Democracy (IoD)

This index characterizes the development of democracy in the regions (Yearbook 2007, 2007).

Life-Quality Index (LQI)

LQI is a composite index of life quality in different regions of the Russian Federation (Yearbook 2007, 2007).

Results

The mean scores of SWB for each sample are shown in the first column of Table 1. Because differences between samples were not large, SWB varied in a relatively limited range from –.25 (Yoshar-Ola) to .26 (Moscow). The mean scores of several indicators and personality characteristics are also shown: N3: Depression; E6: Positive Emotions; Subjective Socio-economic Status (MacArtur Ladder); Satisfaction with one’s finances; Religiosity Index; Materialism/Idealism Index; HDI; LQI; Democracy Index (rank in the Russian Federation); Distance from Moscow (km).

Table 1.

The Mean Scores of Measures and Indicators for 40 Studied Samples.

Sample	Region	SWB Index	N3	E6	SES	Fin	Relig	M/I	HDI	LQI	Dem	Dist
Abakan	Khakassia	−0.06	49.1	50.8	5.74	4.92	4.98	5.23	0.739	0.064	23	3,376
Adyghe	Adyghe	−0.08	47.6	52.8	5.72	5.09	5.94	5.74	0.725	0.076	23	1,252
Arkhangelsk	Arkhangelsk	0.04	48.4	53.1	5.65	5.16	5.89	5.77	0.768	0.134	37	993
Arzamas	Nizhny Novgorod	−0.14	48.8	50.7	5.45	4.90	6.46	5.58	0.757	0.256	41	402
Astrakhan	Astrakhan	0.04	47.7	52.4	5.65	4.91	6.08	5.60	0.758	0.172	27	1,272
Chelyabinsk	Chelyabinsk	0.10	48.6	51.2	5.68	5.39	5.15	5.29	0.773	0.201	36	1,496
Dubna	Moscow	−0.04	50.4	51.4	5.31	4.90	5.74	5.92	0.754	0.319	35	22
Elabuga	Tatarstan	0.14	48.2	51.3	5.81	5.48	6.12	5.69	0.812	0.206	23	720
Izhevsk1	Udmurtia	0.00	49.7	51.7	5.70	4.93	5.77	5.47	0.766	0.173	30	969
Izhevsk2	Udmurtia	0.02	47.9	52.5	5.73	5.09	5.53	5.28	0.766	0.173	30	969
Kazan	Tatarstan	0.06	49.1	52.7	5.85	5.32	6.01	5.41	0.812	0.206	23	720
Krasnodar	Krasnodar	−0.03	47.4	52.2	5.75	4.93	6.02	5.82	0.763	0.158	27	1,196
Kurgan	Kurgan	−0.15	48.7	51.7	5.53	4.86	4.91	5.01	0.730	0.118	24	1,730
Magadan	Magadan	−0.04	48.4	52.6	5.65	4.93	5.15	5.28	0.765	0.099	29	5,906
Moscow	Moscow	0.26	48.1	53.3	5.73	5.79	5.86	6.48	0.754	0.319	35	0
Nizhnevartovsk	Khanty-Mansi	0.01	48.8	51.5	6.06	5.42	6.04	5.28	n.a.	0.161	33	1,900
Novosibirsk1	Novosibirsk	−0.06	48.9	52.1	5.68	4.99	5.39	5.35	0.773	0.297	39	2,812
Novosibirsk2	Novosibirsk	0.03	46.7	53.7	5.64	4.81	5.75	5.64	0.773	0.297	39	2,812
Omsk	Omsk	−0.04	47.9	51.8	5.66	4.60	5.44	5.40	0.794	0.212	29	2,238
Orel	Orel	0.07	47.4	51.9	5.97	5.04	6.08	6.34	0.768	0.168	24	325
Perm	Perm	−0.12	49.7	51.1	5.63	5.00	5.38	5.32	0.760	0.177	41	1,156
Petrozavodsk	Karelia	−0.06	49.1	51.5	5.69	4.79	5.64	5.54	0.742	0.165	41	700
Ryazan	Ryazan	0.02	48.6	53.3	5.86	5.24	6.50	5.46	0.758	0.173	28	185
Sakhalinsk	Sakhalin	0.05	49.6	50.2	6.14	5.14	5.49	5.79	0.755	0.065	33	6,645
Samara	Samara	0.04	47.5	53.6	5.63	4.81	6.52	5.41	0.787	0.258	42	857
Taganrog	Rostov	0.18	48.3	52.3	6.09	5.56	5.46	5.50	0.754	0.162	26	958
Tambov	Tambov	0.13	46.6	53.4	5.89	5.27	6.63	5.64	0.752	0.123	28	418
Ufa	Bashkorstan	0.24	45.8	54.5	5.96	5.31	6.00	5.92	0.786	0.160	18	1,169
Ulan-Ude	Buryatia	0.05	48.3	52.2	5.87	5.25	6.29	5.42	0.728	0.137	30	4,421
Ussuriysk	Primorsk	−0.14	48.7	53.2	5.58	4.92	5.13	5.12	0.736	0.174	28	6,417
Vladimir	Vladimir	−0.10	50.6	49.7	5.57	5.14	5.88	5.95	0.732	0.127	34	179
Vladivostok	Primorsk	−0.04	48.8	52.6	5.61	4.82	5.10	5.40	0.736	0.174	28	6,417
Volgograd1	Volgograd	0.00	47.4	52.9	5.52	5.17	5.75	5.51	0.765	0.171	32	906
Volgograd2	Volgograd	0.01	49.1	49.9	5.93	5.56	5.61	5.55	0.765	0.171	32	906
Vologda	Vologda	0.01	48.9	52.2	5.68	4.92	6.04	5.91	0.783	0.169	29	409
Voronezh	Voronezh	0.14	49.4	51.6	5.69	5.49	5.97	5.97	0.755	0.185	29	466
Yaroslavl	Yaroslavl	−0.06	49.8	51.7	5.45	4.96	5.61	5.69	0.771	0.187	31	249
Yekaterinburg1	Sverdlovsk	−0.12	49.4	51.1	5.37	4.68	5.84	5.42	0.767	0.203	45	1,417
Yekaterinburg2	Sverdlovsk	0.08	47.3	52.8	5.63	4.95	5.65	5.67	0.767	0.203	45	1,417
Yoshkar-Ola	Mari El	−0.25	48.3	52.3	5.55	4.56	6.13	5.53	0.731	0.142	27	642

Source. For more details of samples and regions, see Allik et al. (2009).

Note. SWB = Subjective Well-Being Index (normalized scores); N3 = N3: Depression; E6 = E6: Positive Emotions; SES = Subjective Socio-economic Status (MacArtur Ladder); Fin = Satisfaction with one’s finances; Relig = Religiosity Index; M/I = Materialism/Idealism Index; HDI = Human Development Index; LQI = Life-Quality Index; Dem = Democracy Index (rank in the Russian Federation); Dist = Distance from Moscow (km); n.a. = not available.

Multiple regression is a measure of how well a given variable, say SWB, can be predicted using a linear function of a set of other variables, such as personality scores or HDI. One could say, of course, that multilevel modeling would be a more appropriate method for the analysis but because variances in subsamples were comparable, there was no reason to expect that the correlations based on individual level data and the correlations based on aggregated data from individuals are different (Ostroff, 1993). Based on these considerations, we started the analyses by predicting SWB from personality ratings. We first conducted the analysis by using the self-ratings as predictors. Then, multiple regression was conducted with using the ratings of an ideal person. Finally, the ratings of typical Russian were used as predictors.

First, we computed multiple regression on the basis of self-ratings from which we predicted the SWB scores. The beta coefficients of the regression are shown in Figure 1. It shows that only two traits out of 30 have statistically significantly strong associations with SWB. Low level of N3: Depression and high level of E6: Positive Emotions predicted a high level of SWB with a beta coefficient higher than |.12|. We also predicted the SWB rating using the ratings of an ideal person and, consequently, the ratings of a typical Russian. None of these ratings predicted SWB strongly enough (above |.10|). Perhaps the strongest predictor was the social desirability ratings of O1: Fantasy. Those participants who thought that openness to fantasy is a desirable trait reported a higher level of SWB. In general, however, social desirability and typicality were not strongly related to happiness and life-satisfaction ratings.

Figure 1.

Beta coefficients of the multiple regression by which SWB was predicted from 30 personality scales answered under different instructions (self-, ideal, and stereotype ratings).

Next, we predicted SWB from the 10 indicators listed in Table 1. Besides regression coefficients, Table 2 also shows correlations between SWB and indicators on the individual (N = 10,472) and sample (N = 40) levels. For example, on both levels of the analysis there was a sizable correlation: .30 and .57, respectively, between SWB and Subjective Socio-economic Status, measured with the MacArtur Ladder. However, in the multiple regressions, the association with subjective socioeconomic status (SES) was noticeably reduced. On the level of samples, the impact of SES fell below significance.

Table 2.

Correlations and Coefficients of Multiple Regression Predicting SWB From Measures and Indicators at Individual and Sample Level.

	SWB
	Individual level (N = 10,472)				Sample level (N = 40)
	Correlations		Regression		Correlations		Regression
	r	p	β	p	r	p	β	p
N3: Depression	−.29	>.001	−.17	>.001	−.42	.007	−.17	.242
E6: Positive Emotions	.27	>.001	.12	>.001	.36	.022	.21	.141
Religiosity	.11	>.001	.03	.001	.24	.128	−.02	.874
Materialism–Idealism	.07	>.001	.06	>.001	.47	.002	.09	.461
Subjective Socio-economic Status (MacArthur)	.30	>.001	.12	>.001	.57	>.001	.13	.367
Satisfaction with financial situation	.43	>.001	.01	>.001	.74	>.001	.70	>.001
Human Developmental Index					.42	.008	.45	.041
Life-Quality Index					.41	.009	−.27	.275
Democracy Index					−.20	.228	.18	.175
Distance from Moscow					−.18	.273	−.03	.830
Multiple R			.52				.89
Adjusted R²			26.96%				71.26%

Note. SWB = subjective well-being.

On the individual level of analysis, approximately 27% of SWB variance can be predicted from N3: Depression and E6: Positive Emotion scores, in addition to religiosity, materialism–idealism, subjective SES, and satisfaction with one’s financial situation. When SWB was predicted from the sample mean scores, only two indicators made a significant contribution. In those samples and regions where the HDI was higher and people were more satisfied with their financial situation, the level of SWB was also higher. Multiple regression with these two significant predictors explained about 71% of the SWB variance at the aggregated level.

Discussion and Conclusion

Personality researchers are well aware that every personality score is a mixture of different components of judgment. Besides distinctiveness—how a given target distinguishes from an average individual—personality judgments also reflect, to a different degree, various forms of normativeness and social desirability. Personality judgments may be accurate or inaccurate because the one who makes them assumes that his or her target is to some extent similar to every other person he or she could know or is a typical representative of his or her own nation. Judges can also attribute traits based on the expectations they have with respect to normal, socially acceptable behavior. For example, we may assume that someone is punctual not because we have previous experience with this person but merely because we believe that people usually try to comply with such socially acceptable norms. As such, this implies that the observed correlations between personality traits and SWB may not be caused by the distinctive accuracy of our judgments, but may be at least partly due to the factors of assumed similarity and social desirability.

In this study, we tried to separate the different components of judgment by using different instructions. For example, questionnaire items for the self- or other-ratings can be judged on the basis of their social desirability (Edwards, 1957). Although instructions may be different, the answers given to these various instructions are typically correlated. For example, the judged desirability of a trait is highly correlated with the probability that the trait will be endorsed either in self- or other-descriptions (Edwards, 1953). However, the results of this study demonstrated that SWB is substantially linked to self-descriptions and not to the description of a typical member one’s own nation or an ideal person who is socially acceptable. What people think about a typical Russian or an ideal person was generally unrelated to whether they are themselves satisfied with their own lives. Thus, real feelings, and not what someone is normatively expected to feel, determine life satisfaction and happiness.

One could say that there is nothing new in the reported results because everyone knows that a high level of Extraversion and a low level of Neuroticism facilitate SWB; it is generally believed that the link between SWB and personality is organized in terms of the Big Five dimensions (Olesen, Thomsen, & O’Toole, 2015; Steel & Ones, 2002). Like some previous studies (e.g., Dobewall et al., 2013), this one demonstrated that the link of SWB to personality traits is rather selective. When SWB was predicted from personality, two subscales (of the personality test), N3: Depression and E6: Positive Emotions, explained the largest portion of the variance. Considering the fact that depression is almost synonymous with negative emotions, we can conclude that the main content of SWB is entirely emotional. People are happy and satisfied with their lives when they are able to avoid negative emotions and experience positive ones. Furthermore, the item measuring E6: Positive Emotions directly mentioned “happiness,” as did the question about happiness, which was part of the SWB index. In addition, the item measuring N3: Depression referred to being “satisfied,” which is almost synonymous with being “happy.” As a result, the associations between personality scales and SWB may reflect construct (if not direct measurement) overlaps.

It is tempting to speak about SWB and personality as separate constructs. Indeed, only if we can measure SWB independently of personality traits would we be permitted to use causal language (e.g., that avoidance of negative emotions and the experience of positive ones determines happiness and satisfaction). In reality, emotions do not cause happiness and life satisfaction. It is impossible to ignore the point that items which are difficult to separate from each other can be used to measure both constructs. From this perspective, positive and negative emotions are simply attributes that are necessary for the definition of what it means to be happy and satisfied with one’s own life. The answer is simple: well-being is mainly not worrying and staying happy!

Previous studies have shown that the mean scores of happiness have a meaningful pattern of geographic distribution (Aslam & Corrado, 2012; Oswald & Wu, 2010; Rentfrow, Mellander, & Florida, 2009). The geographic distribution of SWB in the Russian Federation seems to have the same principal pattern. Residents of various constituents of the Russian Federation have a high level of well-being where objective life quality is higher. However, when individual differences were smoothed out by means of aggregation, and we operated only with the mean values of samples, there was only one factor that explained regional differences in SWB. After controlling for all factors, only satisfaction with one’s financial situation explained interregional differences in mean SWB. This observation is supported by other observations, such as the residents of the Russian Federation being mainly concerned with their health and difficult financial situation (OECD, 2011, 2015).

It is certainly an interesting result that the mean SWB scores were not directly related to the objectively measured economic wealth of a region but to the average perceived wealth of an individual. Unfortunately, to avoid the discontinuation of participation in the study, we avoided questions concerning individual incomes. Therefore, we are not aware of, for example, how satisfaction with a participant’s financial situation relates to their actual financial situation. On the aggregate level, the economic wealth of the region was not related to the mean satisfaction with personal finances in this region. However, satisfaction with personal finances was generally higher in constituents with a higher life expectancy. In those regions of the Russian Federation where people are healthier and live longer, individuals are, on average, more satisfied with their financial situation (r = .36 N = 40, p = .02).

It is remarkable that on both levels of the analysis—individual and aggregated—endorsement of spiritual values is accompanied with higher levels of happiness and life satisfaction. It was also proposed that it is a Russian cultural norm to inhibit the expression of happiness, the result of which drives Russia very often to the bottom of various cross-cultural rankings of happiness (Sheldon et al., 2017). It was also an idea that unhappiness is a unique aspect of the Russian soul, which may prevent participants to express their life satisfaction in a true extent (Allik et al., 2011). The declared priority of spirituality over material needs vanished when we looked for a joint influence of all factors affecting SWB. On the aggregated level, SWB was almost completely explained by the mean value of financial satisfaction, not other factors including the primacy of spiritual values in one’s life. This indicates that although participants emphasized priority of spiritual over material needs, in reality their life satisfaction was more predictable from the gratification they obtained from their financial situation (Ahuvia, 2008; Schyns, 2001).

As is the case with many studies, this one, too, has some limitations that ought to be considered while interpreting the results. First, it should be acknowledged that we used single-item indicators of Big Five domains that could involve more measurement error that could attenuate the effects. Although one way to minimize the measurement error would be to use latent variable modeling (and aggregating scores of five traits), we opted for the more detailed view of personality characteristics with the trade-off of potential increase in measurement error. Second, the sample used in this study limits the generalization of the findings to an extent as university students were surveyed. Although it would have been interesting to include more representative sample (in terms of population), the current data provide uniqueness in the scope of regions surveyed. Third, we acknowledge that the sample used in this study is clustered, and the estimates of the obtained effects in the aggregate sample reflect a mixture of both group level and individual level effects. Fourth, the principal dependent variable was combined of a life satisfaction item and a 4-point happiness indicator that could results in higher measurement error. Finally, the statistical power for the multiple regression at the level of region is low, and this ought to be kept in mind while interpreting the results.

Although acknowledging the limitations mentioned above, the results of the current study are novel. First, the study is representative of 40 different regions of Russia, and it involved more than ten thousand participants—allowing for individual level and region level analysis. Second, the results showed that two personality test subscales, namely Depression (Neuroticism) and Positive Emotions (Extraversion) were correlated with SWB on the between-individual level of analysis. Third, SWB could be predicted from one’s own financial situation. Finally, in regions where people had, on average, higher life expectancy, better education, and higher level of wealth, individuals were happier and more satisfied with their lives.

Footnotes

Authors’ Note

Research data that support the findings of the current study are available upon scholarly request. The authors are grateful to Helle Pullmann, Anastasia Trifonova, and members of the Russian Character and Personality Survey (RCPS) for their assistance with collecting the data.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Preparation of this manuscript was supported by institutional research funding (IUT2-13) from the Estonian Ministry of Education and Science to Jüri Allik.

Author Biographies

Jüri Allik (University of Tartu, Estonian Academy of Sciences) primary field of research is visual psychophysics and models of perception. Allik’s recent research, however, is more concentrated on personality, emotions, intelligence, and cross-cultural comparison.

Rene Mõttus (University of Edinburgh, University of Tartu) is interested in various topics related to human personality, such as how to most efficiently represent human presonality, personality development, developing computational models of personality processes, and delineating the causes and consequences of personality variability within and between individuals. In addition, Mõttus is also interested in studying intelligence.

Anu Realo (University of Warwick, UK and University of Tartu, Estonia) is interested in personality and cross-cultural psychology and has conducted research on cultural and individual variation in personality traits, emotional experience, values, and subjective well-being. Her current research also tackles complex relationships among personality, health, and subjective well-being, as well as the genetics of personality traits.

Dmitri Rozgonjuk (University of Tartu) is a doctoral student in psychology. His main interests include the relationships between digital technology engagement and individual differences in personality and other psychological constructs.

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