Life satisfaction index (LSI) test, adaptation N.V.

Are we happy today? Were we happy before? How satisfied are representatives of different communities with their lives? How does our living conditions affect this?

These questions are important for each of us. But how difficult it is to answer them! Today, life satisfaction and happiness are of central interest in social science research, including “mainstream” economics.

Sociologists often recommend complementing measures of subjective well-being with measures of economic well-being, such as GDP per capita.

But how to measure happiness? Are there reliable comparative measures of happiness across time and space that can explain what makes us happy?

In this article we* will discuss theoretical and empirical data that will help answer these questions (*hereinafter on behalf of the authors).

Here's a quick overview of the article

1. Satisfaction and happiness surveys measure subjective well-being fairly accurately.

2. Levels of satisfaction and happiness vary widely both within and across countries.

3. People who are more affluent are more likely to say they are happy than people who are less affluent. Richer countries tend to have higher average levels of population happiness.

4. Important life events affect our level of happiness only in the short term, which indicates the tendency of people to adapt to change.

I. EMPIRICAL APPROACH

I.1 Cross-country comparisons

Level of happiness in the world, comparison by country

The 2017 World Happiness Report was compiled using data from the Gallup Worldwide Poll, a collection of nationally representative surveys conducted in more than 160 countries in more than 140 languages. The main Gallup Poll question reads:

"Cantril's Staircase"

« Imagine a staircase with steps numbered 0 (at the bottom) to 10 (at the top). The top step represents the best life possible for you, the bottom step represents the worst possible life. What rung of the ladder do you feel you are on now?”(Also known as Cantril's Ladder).

The map below shows the average responses of respondents to this question in different countries. Like the steps of a ladder, the values ​​in the card range from 0 to 10.

There are large differences between countries.
Nordic countries lead the rankings in 2016, with Finland, Norway, Denmark, the Netherlands and Iceland the highest scores (all with averages above 7). In the same year, the Central African Republic, South Sudan, Tanzania, Rwanda and Haiti had the lowest national scores (all with average scores below 3.5).

It turns out that self-reported satisfaction with life correlates with other indicators of well-being:

wealthier and more prosperous countries tend to have higher average happiness levels.

Long-term changes in life satisfaction - World Value Survey results

The World Value Survey collects data from a number of representative national population surveys in nearly 100 countries, with the earliest estimates dating back to 1981.

As we see, in most countries the trend is positive:
in 49 out of 69 countries, data from two or more surveys showed a significant increase in the results of the earlier period.

In Zimbabwe, the share of "very happy" or "fairly happy" increased from 56.4% in 2004 to 82.1% in 2014.

Long-term changes in happiness - Eurobarometer results

(*translator's note - a series of opinion polls commissioned by the European Commission since 1973 in EU member states)

In a number of countries, studies have been conducted annually for more than 40 years. The table below shows the proportion of people who are "very satisfied" or "fairly satisfied" with their standard of living.

Two points should be especially emphasized. First, life satisfaction scores often fluctuate along trends. In France, for example, the overall trend from 1974 to 2016 is positive, although not without ups and downs. Second, despite temporary fluctuations, decadal trends are generally positive for most European countries.

In most cases, the proportion of "very satisfied" or "fairly satisfied" increased over the entire study period. However, there are some obvious exceptions, one of which is Greece. Add Greece to the graph and you will see that in 2007 about 67% of Greeks said they were satisfied with their lives; but 5 years later, after the financial crisis, the corresponding figure dropped to 32.4%. Despite recent improvements, Greeks today are, on average, far less satisfied with their lives than they were before the financial crisis. No other European country in this sample went through a comparable “negative shock”.

Above average. Distribution of life satisfaction ratings

Most country studies on “happiness” and satisfaction focus on average indicators. However, distributional differences are also important.

The table below shows the distribution of the responses received between steps of the ladder. In each case, the height of the bars is proportional to the survey response rate. The distribution of colors corresponds to the distribution by country. For each region, for comparison, we additionally indicated the “distribution of satisfaction” in the world.

These graphs show the distribution of satisfaction levels in sub-Saharan Africa — the region with the lowest average scores — these graphs are located to the left of the satisfaction graphs for Europe. This means that the distribution of scores in European countries stochastically dominates over the distribution of scores in sub-Saharan Africa.

This means that the proportion of “happy” people in sub-Saharan Africa is significantly lower than that of Western Europe, regardless of which Ladder score we use as the threshold for defining “happy.” Similar findings can be obtained by comparing data from other regions with high average scores (eg North America, Australia and New Zealand) with regions with lower average scores (eg South Asia).

It should be noted that the distribution of satisfaction in Latin America itself is high across the board — it consistently ranks to the right of other regions with roughly comparable income levels, such as Central and Eastern Europe. Latin American countries tend to have higher subjective satisfaction than other countries with comparable levels of economic development. Next, in the section on the social environment, we will show that culture and history play an important role in shaping the level of satisfaction with life.

(In)correct perception of the happiness of others

We tend to underestimate the average level of happiness of those around us. Here are the results of a survey conducted by the International Institute of Marketing and Sociological Research Ipsos (Ipsos Perils of Perception), where respondents are asked to guess what others would answer to a question about happiness in the World Value Survey.

The horizontal axis shows the actual share of those who are “very happy” or “fairly happy” according to the World Value Survey. The vertical line shows the average " a guess" the same number (i.e., the one that respondents made regarding the share of those who answered that they were “very happy” or “quite happy” in their country).

If the respondents guessed correctly, then all observations would fall on the red line at 45 degrees. But, as we see, all countries’ indicators are significantly below 45 degrees. In other words, people in every country underestimated their happiness ratings. The most extreme deviations were found in Asia — South Koreans tend to think that 24% of people report that they are happy, but in reality — 90%.

The highest percentage of correct guesses in this sample (Canada and Norway) is 60%. This is lower than the lowest actual happiness score of any other country in the sample (which matches Hungary's score at 69%).

Why do people get so wrong? It may be that we tend to misreport our own happiness, so good guesses on average may be a good predictor of true satisfaction (and a poor predictor of our own satisfaction). However, for these measures to be valid, people would have to misreport their own happiness while assuming that other respondents are correct.

In addition, it is believed that “happiness ratings” given by friends are more accurate (see below), and that respondents tend to be good at assessing emotions simply by observing facial expressions (see below).

Therefore, it is likely that people tend to have positive attitudes toward themselves but negative attitudes toward strangers.

In addition, it was noted that people can be optimistic about their future and at the same time deeply pessimistic about the future of their nation or the world. We discuss this phenomenon in more detail in our article on optimism and pessimism (see the section on individual optimism and social pessimism).

I.2 Within-country indicators

Unequal satisfaction in East and West Germany

The map below shows life satisfaction scores in Germany (based on the Cantril Ladder), summing up the averages of the federal states. The first thing that strikes you is the clear division between Germany's East and West in the course of its political division that existed before reunification in 1990.

Several academic papers have examined this “happiness gap” in Germany in more detail, using data from, for example, the German Socio-Economic Group (Petrunik and Pfeiffer, 2016). These studies offer two main ideas:

First, the “gap” has been narrowing in recent years, which is true both for average differences and for “conditional differences”, which can be estimated after taking into account socio-economic and demographic parameters. See how the “gap” has narrowed since the reunion in these Petrunyk and Pfeifer maps (Petrunyk and Pfeifer, 2016).

Second, differences in household income and unemployment status are important factors influencing satisfaction. Why then, even after accounting for these and other parameters, the gap between East and West remains significant. This is due to a broader empirical phenomenon:

culture and history are important for life satisfaction.

In particular, former communist countries tend to have lower subjective satisfaction scores than other countries with comparable levels of economic development (see section on social environment).

Unequal satisfaction in the US and other developed countries

The General Society Survey - GSS has been conducted annually in the United States since 1972. About 1,500 respondents were surveyed.

Using this source, Stevenson and Wolfers (2008) show that,

while the national average has remained broadly constant, disparities in life satisfaction in the United States have declined substantially in recent decades.

The authors also note that this statement is true both when considering inequality in satisfaction and in terms of response variance, and when considering inequality in terms of gaps between demographic groups.

2/3 of the "black and white" gap in life satisfaction in the US has decreased, and the gap between "levels of happiness" in relation to women has been completely eliminated (previously, women were somewhat happier than men. Now, the level of women's happiness is declining, and today there is no statistical difference when controlling other characteristics).

Today, white Americans remain happier on average, even after accounting for differences in education and income.

Stevenson and Wolfers' results are consistent with other studies examining changes in "happiness inequality" (or inequality in life satisfaction) over time. In particular, the researchers noted that

there is a relationship between economic growth and the reduction of “happiness inequality” — even as income inequality increases at the same time.

The chart below, from Clark, Fleche, and Senik (2015), visualizes the evolution of “happiness inequality” in a survey conducted in developed countries that experienced continuous GDP growth.

In this chart, “happiness inequality” is measured by the degree of dispersion, namely the standard deviation of responses to the World Value Survey. As we can see, there is a broad negative trend. In their article, the authors show that this trend is positive for countries with declining GDP.

Why do indicators of “happiness inequality” decrease as income inequality increases?

Clark, Flesch and Senik argue that one reason is that rising national income allows for greater provision of public goods, which in turn limits the distribution of subjective welfare. This situation may also be consistent with rising income inequality, as public goods such as improved health have different effects on income and well-being.

But it is also possible that economic growth in developed countries will be distributed in a more diverse society in terms of cultural expressions, allowing people to “converge” on higher “levels of happiness” even if they “diverge” in income, tastes and consumption (see . data in an article in the New York Times).

I. CORRELATIONS, DETERMINATES AND CONSEQUENCES

II.1 Income

The relationship between higher national income and increased average life satisfaction

If we compare life satisfaction reports around the world at any time this moment time, we can immediately see that respondents in richer countries tend to report higher life satisfaction than those in poorer countries (see chart below).

Each point in the diagram corresponds to a different country. The vertical arrangement of the dots shows the approximate national average for life satisfaction on the Cantril Ladder; while the horizontal layout shows GDP per capita on a purchasing power equality basis (i.e. GDP per capita after adjusting for inflation and price differences across countries).

This correlation holds even when we control for other factors: Richer countries tend to have higher life satisfaction than poorer countries.

The relationship between higher incomes and higher life satisfaction

It was stated above that the richer the country, the higher the level of happiness of its population, and vice versa. Here we will show that the same is true for the situation within countries:

Rich people tend to be happier than poor people within a country.

In the tables below, we prove the relationship between income and happiness through income quintiles. Each panel in the table represents an associated scatterplot of data for a specific country. This means that for each country we observe a line connecting five points: each point corresponds to the average income in income quintiles (horizontal axis) from the average life satisfaction in that income quintile (vertical axis).

What does this table tell us? We see that in all cases the lines are ascending: respondents with higher incomes tend to have higher average levels of life satisfaction. However, in some countries the lines are more curved and linear (for example, in Costa Rica, the richer are happier than the poorer across the entire income distribution); while in other countries the lines are less curved and non-linear (for example, the richest group people in the Dominican Republic are as happy as the second-richest group).

The table on the left shows the same data, but instead of plotting each country separately, it shows all countries in one grid.

The resulting graph may seem a bit confusing, reminiscent of a spaghetti graph, but it confirms the complex pattern: despite kinks here and there, the lines tend to point upward.

Do income and happiness levels correlate? - YES, they correlate, both within a country and between countries.

Just by taking a quick glance at the following table, you will see the key data derived from the previous three tables.

To show the relationship between income and happiness in different countries, the relationship between life satisfaction (on the vertical axis) and GDP per capita (on the horizontal axis) is plotted here. Each country is represented by an arrow on the grid, and the location of the arrow tells us the corresponding combination of average income and happiness.

To show the relationship between income and happiness inside countries, each arrow has a slope corresponding to the correlation between household income and life satisfaction within that country. In other words: the slope of the arrow indicates how strong the relationship is between income and life satisfaction within that country (see table on the left).

If the arrow points northeast, it means that richer people tend to report higher life satisfaction than poorer people in the same country. If the arrow is horizontal (that is, pointing east), this means that rich people are, on average, as happy as poor people in the same country.

As we can see, there is a very clear pattern: rich countries tend to be happier than poor countries (observations center around an upward trend), and richer people in countries tend to be happier than poorer people in the same countries (arrows consistently directed to the northeast).

It is important to note that the horizontal axis is measured on a logarithmic scale. Cross-country income-happiness relationships do not have a one-way relationship with income (this relationship is “log-linear”). We use a logarithmic scale to highlight two key facts: (i) at no point in the global income distribution is the relationship horizontal; and (ii) a doubling of average income is associated with approximately the same increase in life satisfaction, regardless of world distribution position.

These results have been examined in more detail in a number of recent academic studies. It is important to note that in the work cited by Stevenson and Wolfers (2008), these correlations also hold after controlling for country characteristics, such as population demographics, and are robust to different data sources and measures of personal well-being.

Economic growth and happiness levels

Let's try to prove that as countries become richer, the population tends to report higher average life satisfaction.

This table uses data from the World Value Survey to determine the evolution of average national income and "average national happiness" over time. This shows the ratio of the share of those who are “very happy” or “very satisfied” according to the World Value Survey (vertical axis) to GDP per capita (horizontal axis). Each country is drawn as a line connecting the first and last available observations across all waves of the study.

We see that countries experiencing economic growth also tend to increase their “happiness levels” according to the World Value Survey. This correlation holds after controlling for other factors that also vary over time (see this graph from Stevenson and Wolfers (2008) for the correlation of GDP per capita with changes in life satisfaction after controlling for changes in demographic structure and other variables).

It is important to note here that economic growth and growth in “happiness levels” are generally interrelated. Some countries experience economic growth during certain periods without an increase in “happiness levels.”

Considering the evidence, the US experience over recent decades is quite revealing.

Easterlin's paradox

Economic growth does not always correlate with increased satisfaction. This claim was first made by Richard Easterlin in the 1970s. Since then, much discussion has been devoted to this issue, now known as the Easterlin Paradox.

The paradox was based on the fact that

Richer countries tend to have higher “happiness levels,” but in some countries that were re-surveyed in the 1970s, “happiness levels” did not increase with income.

This combination of empirical evidence was paradoxical because the cross-country data (countries with higher incomes tended to have higher “happiness levels”) were, in some cases, inconsistent with the actual data over time. Interestingly, Easterlin and other researchers relied on data from the United States and Japan to confirm this seemingly puzzling observation. However, if we take a closer look at the data underlying the trends in these two countries, they no longer seem so paradoxical.

Graph from Easterlin and Angelescu 2011

Let's start with Japan. There, the most available data on satisfaction assessments were obtained from the so-called Life in nation surveys for 1958. These studies show that average life satisfaction has remained constant during a period of impressive economic growth. However, not all so simple.

Stevenson and Wolfers (Stevenson and Wolfers, 2008) show that questions of life satisfaction in the Life of the Nation Surveys have changed over time, making it difficult, if not impossible, to track changes in "happiness levels" over the entire period.

The table on the left breaks down life satisfaction data from surveys into “sub-periods” that never answer the question. As we can see, the data does not confirm the paradox: the relationship between GDP and growth in happiness in Japan is direct during comparable study periods.

The reason for the supposed paradox is actually a misidentification of how "happiness levels" have changed over time.

In the situation with the USA, the explanation is different. In particular, if we look more closely at economic growth in the United States over recent decades, one fact looms large: growth has not benefited most people. Income inequality in the United States is exceptionally high and has been increasing over the past four decades, with the income of the average household growing much more slowly than the income of the top 10% of the population. As a result, trends in overall satisfaction should not be seen as paradoxical: the income and standard of living of the typical US citizen have not increased over the past several decades (you can read more about this in the article on inequality and income distribution).

II.2 HEALTH

Life expectancy and satisfaction

Health is an important predictor of life satisfaction, both within and between countries. Each point in the diagram below represents one country. The vertical position of the dots shows the national life expectancy from birth, and the horizontal position shows the national average value of life satisfaction according to the Cantril Ladder (a scale from 0 to 10, where 10 is the highest possible life satisfaction).

As we can see from the graph, there is a strong positive correlation: countries where people live longer are also countries where people are more likely to say they are satisfied with their lives. Similar relationships hold for other health outcomes (for example, life satisfaction tends to be higher in countries with lower child mortality).

The relationships shown in the graph clearly reflect more than just the relationship between health and “happiness”, as countries with high life expectancy also tend to have many other characteristics. However, the positive correlation between life expectancy and life satisfaction remains after controlling for country-specific parameters such as income and social protection.

Mental health and happiness levels

By examining the correlation of physical illness with other factors such as income and education, the table above measures the degree (where each bar indicates the degree of relationship) with which mental illness (depression and anxiety disorders) are correlated with satisfaction scores.

These are "conditional correlations" - they correspond to the relationship between two variables after taking into account the factors listed in the footnote to the table. Negative values ​​indicate that people who have been diagnosed with depression or anxiety disorders are more likely to have lower life satisfaction.

The size of the coefficients, especially in the US and Australia, tells us that the relationships we are seeing are very strong.

For reference, in the UK, US, and Australia, the magnitude of the correlation between mental illness and life satisfaction is higher than the magnitude of the correlation between income and life satisfaction.

Obviously, this correlation is the result of two-way relationships:

those suffering from depression and anxiety disorders are less likely to feel happy;

those who consider themselves unhappy are more likely to have depression or anxiety disorders. However, it's still important to remember that anxiety, depression, and feeling unhappy often go hand in hand.

II.3 LIFE EVENTS

How do life events affect your happiness?

Do people tend to adjust to life situations, returning to a basic "level of happiness"?

Clarke (2008) uses data from the German Socio-Economic Panel to identify groups of people who experience multiple events in life and work and to see how these events affect the evolution of their life satisfaction.

The red lines in the table on each individual plot indicate the estimated effect for various events at a given point in time (hairlines indicate the confidence range of each estimate).

In all cases, the results were separated by gender, and timestamped so that "0" denotes the time the respective event occurred (with negative and positive values ​​indicating years before and after the event). All estimates take individual characteristics into account, so the data shows the impact of an event after controlling for other factors
(for example, income, etc.).

First, it should be noted that most events indicate the evolution of a latent situation: people become unhappy in the period before divorce, while they become happy already in the period before marriage.

Second, single events in life tend to affect happiness in the short term, and people often adapt to these changes. Of course, there are clear differences in how people adapt. In the case of divorce, life satisfaction first falls, then rises and remains high. There is a negative shock to unemployment in both the short and long term, especially among men. And for marriage, life satisfaction builds up and disappears after marriage.

Overall, the evidence suggests that adaptation is an important dimension of satisfaction. Many common but important life events have moderate long-term effects on satisfaction scores. However, adaptation to events such as long-term unemployment is neither absolute nor immediate.

Is disability related to satisfaction?

A number of studies have noted that long-term paraplegia per se does not correlate with satisfaction (see, for example, the often cited article by Brickman, Coates, and Janoff-Bulman, 1978).

(*translator's note: paraplegia - paralysis of both lower or both upper limbs)

This statement caught our attention because it speaks to the very meaning of satisfaction and has important implications for the general issue. For example, when considering in court regarding compensation for disability.

Comparing differences in satisfaction among people with different degrees of disability is not an ideal source of evidence for the impact of a tragic situation on happiness. People with paraplegia potentially differ from those without paraplegia in ways that are difficult to measure. The best source of evidence is from long-life studies (longitudinal studies), in which people are followed over time.

Oswald and Powdthavee (2008) use data from a UK longitudinal study to explore whether accidents and subsequent disability lead to long-term disruption and life dissatisfaction.

Life satisfaction in persons with severe disabilities, BHPS 1996–2002. — Oswald and Poudthave (2006)

The graph compiled by Oswald and Paudthave shows the average satisfaction of a group of people who became severely disabled (at time T) and remained disabled for the next two years (T + 1 and T + 2). Where "severe disability" means that the disability prevents them from performing daily activities.

As we see — and as the authors point out, more accurately using econometric methods — those who become disabled experience a sharp decline in satisfaction and recover only partially. This confirms the assumption that

Although adaptation plays a role for general life events, the concept of life satisfaction is indeed sensitive to tragic events.

II.4 SOCIAL ENVIRONMENT

Correlation between culture and life satisfaction

The relationship between happiness levels between countries suggests that culture and history are important to life satisfaction. For example, as the chart below shows, Latin American countries have higher levels of satisfaction relative to other countries with comparable levels of economic development due to their cultural and historical background.

This chart shows satisfaction measured on Cantril's ten-tier ladder vertically against GDP per capita horizontally.

Here Latin America is not a special case. For example, former communist countries tend to have lower life satisfaction scores relative to other countries with comparable characteristics and levels of economic development.

Academic research in positive psychology discusses other models. Diener and Suh (2002) write: “In recent years, the impact of cultural differences on satisfaction has been studied, recognizing that there are profound differences in what makes people happy. For example, self-esteem is less strongly related to life satisfaction, and extraversion is less strongly associated with beneficial affect in collectivistic cultures than in individualistic cultures."

To our knowledge, there are no rigorous studies examining the causal mechanisms linking culture and life satisfaction. However, it seems natural to expect that cultural factors shape how people collectively understand happiness and meaning in life.

The relationship between feelings of freedom and satisfaction

The society we live in can dramatically change the availability of what we can do with our lives.

The table below shows the relationship between feelings of freedom and satisfaction according to the Gallup Poll. The variable measuring satisfaction corresponds to the average values ​​of the Cantril Ladder; while the variable measuring the feeling of freedom corresponds to the proportion of people who agree with the statement: “ In this country I am happy with my freedom to choose what I do with my life».

As we can see, there are clear positive relationships: countries where you can freely choose and control your life tend to be countries where people are happier. As Inglehart et al. (2008) show, this positive relationship persists even after we control for other factors such as income and religiosity.

Interestingly, this table also shows that although there is a sense of freedom in some countries, average satisfaction is low (for example, in Rwanda); There are no countries where perceived freedom is low and average life satisfaction is high (i.e. there are no countries in the top left corner of the chart).

To our knowledge, there are no rigorous studies of the causal mechanisms linking feelings of freedom and happiness. However, it seems natural to expect that self-determination and lack of coercion are important components of what people consider to be a happy and meaningful life.

The link between the media and discouragement

Johnston and Davey (1997) conducted an experiment in which they edited short television news stories to show positive, neutral, or negative material and then showed them to three different groups of people. The authors found that people who watched the “negative” material , were more likely to report a sad mood.

This link between emotional content in the news and changes in mood is all the more important if we believe that media censorship favors negative or positive coverage of newsworthy facts (see, e.g., Combs and Slovic 1979).

Of course, mood is not the same as satisfaction from life. However, as we discuss below, surveys that measure happiness often capture the emotional aspects of satisfaction. And in any case, people's perception of the significance of life depends to a large extent on their expectations of what is possible and likely to happen in their lives.

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III. DATA QUALITY AND MEASUREMENT

Can happiness be measured?

The most natural way to try to measure satisfaction is to ask people what they think and feel.

Some social scientists tend to measure experiential or emotional aspects of satisfaction (e.g., “I feel very happy”), while others tend to study evaluative or cognitive aspects of satisfaction (e.g., “I think I am leading a very positive life”). People's own opinions of happiness and satisfaction are known to be correlated with things they typically associate with satisfaction, such as cheerfulness and smiling.

Experimental psychologists have also shown that self-reports of satisfaction, based on surveys, appear to be associated with the activity of those parts of the brain that are responsible for feelings of pleasure and satisfaction.

Various surveys have confirmed that people who say they are happy also tend to sleep better and verbally express positive emotions more often.

The table in Kahneman and Krueger (2006) provides a list of variables that researchers have found to be associated with happiness and life satisfaction.

Correlations between high satisfaction and “happiness”

Smile frequency

Smile with the eyes (“genuine smile”)

Happiness as measured by friends

Frequent verbal expression of positive emotions

Sociability and extroversion

Sleep quality

Happiness of close relatives

Self-assessment of health

Are “life satisfaction” and “feeling happy” the same thing?

It is important to remember that satisfaction and happiness are not synonymous.

The chart above shows that these two dimensions are closely related to each other (countries that score high on one dimension also tend to score high on the other dimensions), but they are not identical (there is significant variance, with many countries using one and the same result for one variable showed a different result for another variable).

The differences in responses to the questions are consistent with the idea that subjective satisfaction has two sides: experiential or emotional, evaluative or cognitive.

Of course, the boundaries between emotional and cognitive dimensions of well-being are blurred in our minds; Therefore, in practice, both types of questions measure both parameters to varying degrees.

Are average measures of “happiness” really meaningful?

The most common way to analyze happiness data is to average the values ​​across groups of people.

Is it reasonable to take average ratings of life satisfaction? Or, to put it in technical terms: are the Cantril Ladder results truly a cardinal measure of well-being?

The evidence tells us that results based on the Cantril Ladder questions do provide clear measurements — respondents were able to translate verbal labels such as “very good” and “very bad” into approximately the same numerical values.

But as with any aggregate measure of social progress, averages must be interpreted carefully, even if they make arithmetical sense.

For example, if we look at "happiness" in terms of age in a given country, we can see that older people do not appear happier than younger people. However, this may be because the age-at-moment average confounds two factors: the age effect (people in the same group become happier as they get older, across all groups) and the group effect (at all ages, older generations less happy than younger generations). If the group effect is very strong, then the situation in the moment shows that people become less happy as they age, when in fact the opposite is true, in fact this is true for all ages.

This example is actually taken from real life: data from the United States (Sutin et al. (2013)) showed that satisfaction levels tend to increase with age across generations, but overall levels of satisfaction depend on the period in which people were born .

How important is language for cross-country comparisons of “happiness”?

Linguistic differences are often seen as one of the main obstacles to comparative studies of happiness across countries. However, there is evidence to suggest that comparability issues, at least with regard to language, are less complex than many people think.

For example, research has shown that in surveys where respondents are shown photographs or videos of other people, respondents can broadly determine whether the person shown to them was happy or sad; and this was also true when respondents were asked to randomly rate the condition of people from other cultural communities. (See Sandvik et al., 1993; Diener and Lucas, 1999).

Research has also shown that "original emotions" across cultures (i.e., emotions that are unique and have no equivalent in English) are not experienced more frequently or differently than those that can generally be translated into English (see Scollon et al., 2005).

So there seems to be some basic understanding of what it means to be “happy.”

The problem of subjective human well-being has deep roots in the history of philosophy, sociology and other sciences. In psychology, this problem has increasingly attracted the attention of researchers in recent decades, which is largely due to the urgent need for psychological practice to determine and understand what serves as the basis for the psychological balance of an individual.

R. M. Shamionov defines subjective well-being as a person’s emotional and evaluative attitude towards his life, his own personality, relationships with other people, as well as processes that are important for him from the point of view of acquired normative, value and semantic ideas about prosperous external and internal environment, expressed in satisfaction with it and the experience of happiness.

Researchers interpret the structure of an individual’s subjective well-being in different ways. E. Diener and R. Bradburn model of psychological well-being, which includes two components: cognitive (intellectual assessment of satisfaction with various areas of one’s life) and emotional (presence of a good or bad mood) [according to: 3, p. 25].

Later, other models of subjective well-being were proposed. Thus, K. Rieff developed a six-component model of psychological well-being. In this model, psychological well-being acts as an integral indicator that combines self-acceptance, positive relationships with others, autonomy, environmental management, purpose in life and personal growth. In L.V. Kulikov’s model, subjective well-being is presented as consisting of several interconnected types of well-being - social, spiritual, physical (bodily), material and psychological, each of which has its own structure. N.A. Baturin and co-authors, considering the cognitive-affective theory of social learning by U. Michel, came to the conclusion that it is advisable to use a three-component structure of well-being, including affective, cognitive-affective and cognitive components.

Recently, more and more researchers are leaning towards a three-component structure of an individual’s psychological well-being, including cognitive, emotional and conative (behavioral) aspects. The cognitive component includes an individual's assessment of his own life and is characterized by the main indicator - life satisfaction. The emotional component of psychological well-being is represented by a positive or negative emotional pole (depending on the experience of events), facilitating or hindering the realization of the goals, needs and intentions of the individual. The conative component is expressed in the relationship of the individual to the surrounding reality through the prism of intrapersonal and interpersonal relationships [according to: 7, p. 6].

When considering subjective well-being as a systemic phenomenon, researchers pay special attention to the mechanisms of its formation. E. Diener, for example, believed that the well-being of an individual can only be determined on the basis of internal experience, and external criteria must be considered through the prism of subjectivity, which is directly dependent on the level of well-being. E. Diener clarified N. Bradburn’s theory, according to which a person experiences certain emotions of varying strength throughout life, interacting with each other and developing a certain locus of satisfaction, which influences the perception and assessment of various life circumstances [according to: 8, p. 414].

The mechanism for the formation of well-being described by R. M. Shamionov deserves attention. The author believes that various components of well-being (such as satisfaction with oneself, life, marriage, profession, working conditions, etc.) are not only interconnected, but a number of them are mutually integrated, that is, satisfaction with work contains satisfaction with relationships, etc. Psychological defense mechanisms can perform a regulatory function in relation to various areas of life, compensating for dissatisfaction in any area not only by revaluing it, but also by possibly redirecting activity to areas where the individual experiences satisfaction. The chain-hierarchy of various psychological and socio-psychological components in interrelation and mutual determination with various spheres of satisfaction creates conditions for the emergence of subjective well-being, influencing the personal priorities of the subject.

By satisfaction, R. M. Shamionov understands a complex, dynamic socio-psychological formation based on the integration of cognitive and emotional-volitional processes, characterized by a subjective emotional-evaluative attitude (toward oneself, social relationships, life, work) and having a motivating force that promotes action , search, management of internal and external objects. Guidelines for qualifying the personal level of well-being, according to R. M. Shamionov, lie in the sphere of socialization. An individual’s assessment of the level of his well-being is based on social comparison, during which the subject correlates the results of his activities and external attitudes towards him by comparing himself and his well-being with others, by correlating the well-being of others with his own well-being, or by comparing the level of personal well-being at different time periods with active needs and expresses an emotional-evaluative attitude, which qualifies as a certain level of well-being.

The uniqueness of subjective well-being lies in the fact that the mechanisms of its formation are located not only in the social environment, but, at the same time, in the inner world of the individual. Subjective well-being acts as a mechanism for regulating the subject’s selective activity in various spheres of social life and is determined by various factors.

Target of this study: studying the relationship between life satisfaction and gender identity and socio-demographic characteristics of the individual.

Techniques: 1) E. Diener’s Life Satisfaction Scale (SWLS); 2) questionnaire S. Bem. E. Diener's Life Satisfaction Scale has extensive practice. This scale was proposed by E. Diener, R. A. Emmons, R. J. Larsen and S. Griffin in 1985, adapted and validated in Russian by D. A. Leontyev and E. N. Osin in 2003. The validity of this brief screening technique is confirmed by exploratory factor analysis. The life satisfaction scale measures the cognitive assessment of the conformity of life circumstances with the individual's expectations. This indicator shows somewhat weaker relationships with other measures of subjective well-being, however, as one would expect, it will be more closely related to objective indicators of the success of an individual’s life. The scale has fairly high psychometric characteristics and is interconnected with a wide range of indicators of subjective and psychological well-being. Abroad, the methodology is systematically used in cross-national monitoring.

The Sex Role Inventory (BSRI) was proposed by Sandra Bem in 1974 to diagnose psychological sex and determine the degree of androgyny, masculinity and femininity of an individual. The questionnaire can be used in different ways: the subject can fill it out himself to determine psychological gender; also, by changing the instructions, one can study the individual’s susceptibility to stereotypes of masculinity-femininity, and in the form of an expert rating, when the subject is an expert for assessing people well known to him (husband, wife, parents, etc.).

Sample. The respondents were 118 people aged from 26 to 40 years, of which 69 were women and 49 men. Level of education: 81.8% of respondents with higher education, 9.1% with incomplete secondary education, 6.8% with specialized secondary education, 2.3% with an academic degree. 72.9% of respondents rated their level of material well-being (self-esteem) as “average”, 16.9% - “low”, 9.3% - “high”, 0.9% - “very low”.

Research results. A study of life satisfaction using E. Diener’s methodology showed that 12 people (10.2%) were “extremely satisfied” with their lives. The largest number of respondents - 42 people (37.3%) showed the level of “very satisfied” (the result is above average). “More or less satisfied” with their life (average result) - 32 people (27.1%). 25 respondents (21.2%) were “slightly dissatisfied” with their lives. Five people (4.2%) were “dissatisfied” with their lives. The “very dissatisfied” level was not identified in our sample.

Let us present the results of a comparative analysis of life satisfaction among men and women (Fig.). There were no statistically significant differences in life satisfaction between men and women.

Rice. Life satisfaction in men and women

As a result of the study of the characteristics of the respondents’ gender identity using S. Bem’s methodology, it was revealed that 83% of the entire sample of respondents (men and women) belong to the androgynous type of psychological gender. The masculine type was detected in 14% of men and one woman. 17% of women belong to the feminine type. The types of “pronounced masculinity” and “pronounced femininity” were not identified among respondents.

Correlation analysis using the Pearson coefficient did not reveal any connections between life satisfaction and gender identity (androgyny and masculinity) of respondents. Although we note that according to S. Bem, androgyny contributes to the subjective well-being of the individual. At the same time, our study revealed (at the trend level) that women’s femininity increases their life satisfaction (Pearson’s coefficient). This result may indicate that in the modern sociocultural situation, gender identity is not as significant as other factors, in particular socio-demographic factors, influence an individual’s life satisfaction.

Using cross-tabulations compiled in SPSS, we correlated the results on the life satisfaction scale with gender, age, education, marital status, presence of children, and level of material well-being of respondents.

We will describe the “portrait” of a person satisfied with their life based on the results of a sample of 44 respondents (37.3%), 20 men and 24 women, who showed high satisfaction with life (the “very satisfied” level). Satisfied with their life: man (38.8%) or woman (36.2%), aged 29-31 years (45.4%), mostly with higher education (84.1%), registered married (63. 6%) and having 1 child (63.6%), with an average (according to their own assessment) level of material well-being (77.3%). The portrait of a person “dissatisfied” with his life looks different (there are 5 people in our sample): this is a 26- or 39-year-old man with a higher education, unmarried, without children, who assesses his material well-being as low.

One-factor analysis of variance revealed significant differences between subjective satisfaction and self-assessment of the level of material well-being of respondents. The higher respondents (men and women) assess their material well-being, the higher their life satisfaction. This is probably due to the fact that in the modern sociocultural situation, at the age of 26-40, men and women are at the peak of social and economic activity, arranging a comfortable life, and are responsible for the material support of their family.

Thus, the study revealed that life satisfaction, which does not differ statistically significantly between men and women, is not associated with their androgyny and masculinity. At the same time, at the trend level, it was revealed that a woman’s femininity increases her life satisfaction. Data were obtained that in this sample of the factors taken into account (gender, age, marital status, the presence of children, self-assessment of material well-being), self-assessment of material well-being has the greatest impact on life satisfaction for men and women.

The concept of life satisfaction is complex and multi-layered. Is it possible to define it in a more specific way? Can it be quantified and assessed? If so, what results are obtained for the Russian population? What worries Russians most?

One of the traditional areas of sociological research is the study of the role and significance of various aspects of people's life. For many years now, large-scale work of this kind has been carried out by both Russian and Western sociologists. Another equally important research area is the problem of measuring population satisfaction with their lives. Such work is carried out on a regular basis, in particular, by sociologists from countries participating in the Common Economic Space. However, despite the internal unity of these areas of research, their methodological unification has not yet been carried out. Meanwhile, the need to conduct operational monitoring of the social well-being of the population requires solving this problem. In this article we propose one of the possible approaches to solving it based on the construction of an integral index of life satisfaction.

1. Typology of life satisfaction factors. Satisfaction with life is a complex, complex concept that accumulates many factors and aspects, each of which is largely an independent phenomenon. In this regard, in order to quantitatively measure the degree of satisfaction with life, in our opinion, it is advisable to adhere to the following computational algorithm:

• to form the most complete set of factors affecting life satisfaction;
• assess the level of satisfaction of the population with each of these factors (that is, calculate the factor satisfaction indices);
• assess the level of importance of each factor (i.e., calculate factor significance indices, on the basis of which it is possible to determine factor significance coefficients);
• calculate the generalized index of life satisfaction, which consists of the sum of factor satisfaction indices adjusted for the factor significance coefficient.

Let us consider in more detail the first stage of this algorithm.

Building an index of satisfaction with life involves the fulfillment of four indispensable conditions.

First, life satisfaction factors must be defined in such a way as to cover all aspects of human life, without missing a single essential aspect of the individual's social being. Otherwise, the completeness of the specified index will be lost and it will turn into a kind of private social indicator.

Secondly, in the final construction of the life satisfaction index, the number of factors should not be too large (no more than 15), since in this case the analyticity of the scheme will be lost, the index itself will become opaque, and the interpretation of quantitative results will turn into a laborious procedure. Here we go contrary to some research traditions, which are focused on building the most complete and detailed lists of basic values, including up to 38 positions.

Thirdly, each particular factor, no matter what, must represent an aggregated phenomenon in which the primary “collapse”, compression of social information has already been carried out. Although highly detailed indicators are highly dynamic and sensitive, their merging into a universal indicator degenerates into an illogical and eclectic procedure.

Fourthly, all factors of life satisfaction must represent certain basic values, in relation to which measurements can be made regarding their importance for the respondents and the level of satisfaction with them. Moreover, these values ​​by default assume their antipodes or so-called “anti-values”.

In this regard, a specific set of factors can be presented as follows:

1. Personal and family security (absence of rampant crime, criminalization of life and arbitrariness of the authorities, minimization of man-made disasters with a risk to life and health);
2. Material well-being (availability of normal housing, clothing, food, the ability to provide education and medical care for yourself and your family);
3. Family well-being (harmonious relationships with family members, mutual love and respect);
4. Achieving the set goals (the presence of social and political freedom, the presence of real opportunities to realize the potential of social mobility);
5. Creative self-realization (the possibility of self-expression at work and outside of work, including in public life);
6. Availability of good, fruitful leisure (availability of free time and ways to use it effectively, including relaxation during vacations and travel, access to cultural values, etc.);
7. Good climate and good weather (absence of natural disasters, prolonged rains, sudden changes in temperature and pressure, the weather corresponds to the current time of year, a sufficient number of sunny days, etc.).
8. Decent social status (respected profession, solid position, qualification degrees, titles, ranks, awards, etc.).
9. The presence of effective informal social contacts (friendship, communication, mutual understanding, sex, etc.);
10. Social stability, confidence in the future (absence of social and political upheavals, absence of ill-conceived and unprepared economic reforms, moderate inflation, unemployment, etc.);
11. Comfortable living environment (good ecology, developed social infrastructure, etc.);
12. Good health (absence of chronic diseases, serious and fatal injuries).

Of course, in addition to the above factors, there are always some other aspects of social life that have not been taken into account, but their influence, as a rule, can be neglected without losing meaningful conclusions. In further applied research, the 11th factor is divided into two independent aspects of life: a positive environmental situation; developed social infrastructure.

The proposed typology of life satisfaction factors is based, in our opinion, on the indisputable position that the stability of the socio-economic system is determined by the homeostasis of society, achieved in the process of satisfying the basic human instincts - self-preservation, self-reproduction (procreation) and self-realization (self-expression) . It is easy to see that the set of factors proposed above covers all three basic instincts with a sufficient degree of completeness.

Of course, there are other classifications of basic human values. For example, in the psychological tradition of the Sufis, there are five fundamental goods to which a person gravitates: life, power, happiness, knowledge and peace. It is easy to see that these values ​​correlate in a very definite way with the three basic instincts. In any case, the proposed 12 groups of life satisfaction factors equally cover both the three basic instincts and the five basic Sufi values. Thus, 12 factors of life satisfaction with sufficient completeness reflect all the diversity of social life.

2. Methodology for assessing the generalized life satisfaction index. Let us consider the remaining three stages of the algorithm for assessing the generalized life satisfaction index proposed in the previous section. To do this, first of all, it is necessary to assess the level of satisfaction of the population with each of the 13 factors. This task involves calculating factor satisfaction indices Dj. The initial information is the question: how satisfied are you with the j-th factor of life activity? The following standard format for possible responses is used:

1. Quite satisfied;
2. Satisfied rather than dissatisfied;
3. More dissatisfied than satisfied;
4. Not satisfied at all;
5. I find it difficult to answer.

Then it is advisable to calculate the index of satisfaction with the jth factor of life using the following formula, which is the most adequate tool for diagnosing the social situation:

where j is the life satisfaction factor index; i is the index of the respondents’ answer to the question regarding satisfaction with the j-th factor; n is the total number of provided options for answering the question (in our case 5); x ji - the proportion of respondents (in percent) who indicated the i-th answer option for the j-th factor of life satisfaction; a i- weight coefficient of the i-th answer option (for all factors of life, a unified scale of weight coefficients is used; 0≤ a i≤1); k is a normalizing coefficient, the value of which is determined during computational experiments.

In relation to our problem, the system of weighting coefficients for all factors is the same and has the following structure: a 1=1,0; a 2=0,6; a 3=0,4; a 4=0. Sometimes in applied research, in addition to the group of people who found it difficult to answer, a group of people who did not give any answer at all is taken into account. When calculating partial (factorial) life satisfaction indices, both of these groups can be combined and considered as a collective “risk factor” that can spill over into any of the four main groups of respondents.

Obtaining a vector of values ​​for factor indices of life satisfaction involves their further aggregation into a final indicator using a traditional weighting procedure. In this case, the weighting coefficients should reflect the relative importance of the factors. To implement this procedure, it is necessary to carry out two operations: calculate the factor significance indices W j , on the basis of which the significance weight coefficients b j are then determined for all factors. The initial information for determining the degree of importance of each factor of life satisfaction is the following question design: how important is the j-th factor of life activity for you? The format of possible answers is identical to that used when assessing the level of satisfaction with various factors of life:

1. Quite important;
2. More important than not important;
3. More unimportant than important;
4. Not important at all;
5. I find it difficult to answer.

Then the importance index of each factor is calculated using a formula similar to (1):

where, as in formula (1), j is the life satisfaction factor index; i is the index of the respondents’ answer to the question regarding the importance of the j-th factor; n is the total number of provided options for answering the question (in our case 5); y ji - the proportion of respondents (in percent) who indicated the i-th answer option for the j-th vital activity factor; a i- weight coefficient of the i-th answer option (for all factors a single scale of weight coefficients is used; 0≤ a i≤1); k is a normalizing coefficient, the value of which is determined during computational experiments. For indicator (2), as well as for indicator (1), the system of weighting coefficients for all factors is the same and has the following structure: a 1=1,0; a 2=0,6; a 3=0,4; a 4=0.

Identification of indices (2) allows us to establish a hierarchy of life activity factors, however, for the subsequent “merger” of all factors into an aggregate index of life satisfaction, it is necessary to move from values ​​(2) to weighting coefficients of the importance of each factor, which are calculated using a simple formula:

where m is the total number of life satisfaction factors (in our case 13).

Procedure (3) allows us to normalize all factors in such a way that the classical balance condition is satisfied:

Having estimates of the values ​​of factor satisfaction indices D j and factor importance coefficients b j, the generalized life satisfaction index D is easily calculated using the formula:

The social indicator (5) is the desired assessment, which can be used to quickly diagnose the level of social well-being of the population. At the same time, the aggregate form of the structure (5) brings important positive aspects to the practice of monitoring and analyzing the social climate.

Firstly, any changes in the generalized life satisfaction index can be meaningfully interpreted by “revealing” its composition. The point is that the analyst can clearly identify which specific factor of life activity was responsible for the observed increase or decrease in the general index of life satisfaction. This fact makes it possible to almost automatically identify “bottlenecks” in the social well-being of the population, which in turn can have important practical significance in the development of state social policy.

Secondly, it becomes possible to conduct in-depth factor analysis, “splitting” the shifts occurring in the mood of the population into three components: due to changes in the social situation; due to changes in people’s value systems; due to joint shifts in the mood and value system of the population. From a formal point of view, such an analytical scheme corresponds to the dynamization of relation (5) through the following expansion:

The first component of the right side of equation (6) reflects shifts in the general index of life satisfaction due to changes in the social situation (ΔD j), the second component - due to changes in people’s value systems (Δb j), the third component - due to joint shifts in mood and in the value system of the population (ΔD j and Δb j).

Thus, relationships (5) and (6) make it possible to link together issues related to clarifying the role and significance of various aspects of people’s lives and issues related to measuring life satisfaction.

Looking ahead a little, we point out that the introduced indices (1), (2) and (5) are designed in such a way that their sensitivity is slightly reduced compared to traditional indicators. This means that even minor shifts in their magnitude should be perceived as significant social changes. At first glance, it may seem that the reduced sensitivity of the proposed analytical structures is their methodological disadvantage. However, a closer look at the problem suggests that this is not the case. The fact is that indicators that are too “malleable” often capture random social changes, a kind of “white noise”, which only disorients the analyst. Indices (1), (2) and (5) do not have this drawback, since they are not so susceptible to social white noise and are not subject to excessively strong random fluctuations in the mood of the population.

One more aspect of the proposed methodology deserves special mention. The fact is that the generalized index of life satisfaction includes many factors between which stable connections can arise. For example, an increase in satisfaction with one's financial situation is usually accompanied by an increase in creative self-realization. There can be quite a lot of such pairwise combinations within the framework of the 13-factor model of the generalized index. Consequently, the generalized index changes not only as a result of surges in any of the particular factors, but as a result of their synchronous and interdependent changes. Note that the effect of “hardwired interdependence” of private factors is essentially reminiscent of the effect of multicollinearity in regression analysis. However, it should be emphasized here that this is not a disadvantage of our computational scheme and does not contradict the logic and purity of social analysis. Indeed, the model of a generalized index of life satisfaction, being a complex factorial construct, is nevertheless not an econometric dependence, and therefore it is not subject to the limitations that are inherent in statistical models.

3. Empirical assessment of life satisfaction. The methodology for assessing the generalized index of life satisfaction developed in the previous sections was tested using data from a survey conducted by VTsIOM in July 2005. The results of calculations for individual factors are shown in Table 1. The value of the normalizing coefficient in the calculations was k=0.001 (a similar parameter was used in). In addition to the indicators indicated in the previous sections, Table 1 shows the values ​​of the contribution V j of each factor to the formation of the final value of the generalized life satisfaction index: V j =b j D j /D. The final value of the generalized life satisfaction index was 53.1%.

How to classify the received numbers?

First, we systematize the general conclusions.

Table 1. Components of the generalized life satisfaction index.

Vital factor	Satisfaction index (D j), %	Significance index (W j), %	Weighting factor (b j)	Contribution (share) of a factor to life satisfaction (V j), %
1. Personal and family safety	54,4	93,9	0,0876	8,97
2. Financial situation of the family	39,8	94,6	0,0883	6,61
3. Family relationships	75,3	94,4	0,0880	12,48
4. Opportunity to achieve your goals	50,6	78,7	0,0734	6,99
5. Availability of leisure and the possibility of its effective implementation	52,8	70,8	0,0660	6,58
6. Creative self-realization at work and outside of work	50,0	66,8	0,0623	5,87
7. Comfortable climate and good weather	61,6	73,6	0,0686	7,96
8. Social status	56,3	73,4	0,0685	7,26
9. Friendship, communication	72,1	82,4	0,0768	10,44
10. Economic and political situation in the country	36,2	83,5	0,0778	5,31
11. Ecology	44,2	84,5	0,0788	6,55
12. Social infrastructure	42,8	79,7	0,0743	5,99
13. State of health of the person and his family members	53,2	95,9	0,0894	8,97

1. The resulting estimate of the generalized life satisfaction index of 53.1% generally lies in the area of ​​realistic values ​​and is confirmed by previous sociological studies. For example, research by VTsIOM using a simplified survey scheme, when the level of life satisfaction was determined immediately (without splitting into individual factors and their subsequent summation), for Russia in 2004-2005. give figures from 45.6 to 47.8%. Thus, these estimates are of the same order, which indicates the continuity of both approaches. At the same time, our estimate turns out to be somewhat overestimated compared to the previous ones, which may be due to two reasons. Either the typology of factors used in the generalized index of life satisfaction is not complete and some factors that are “bottlenecks” of life activity are excluded from it, or when answering the aggregated question about life satisfaction, respondents, on the contrary, do not take into account some positive aspects of life, which are reflected in our typology of factors . Considering that most people have a psychological tendency to excessively dramatize everyday life, the second reason should be considered more likely. If this is so, then a small upward adjustment in the life satisfaction index is itself an important result.

2. The calculations show that factor indices of life satisfaction are more flexible than factor indices of importance. For example, the absolute polarization for factor indices of life satisfaction (the difference between the maximum and minimum values) is 39.1 p.p., and for factor indices of importance - 29.1 p.p. (Table 1). Relative polarization (the ratio of absolute polarization to the minimum value) is even higher: for factor indices of life satisfaction it is 108%, and for factor indices of importance it is 44%. Thus, differences in the social environment are more significant than differences in the degree of importance of certain aspects of people's lives. This result is quite logical and indicates that the analytical design of the generalized life satisfaction index (5) correctly reflects existing social imperatives.

3. The data in Table 1 show that the values ​​of factor significance indices are shifted to the right border of the scale, that is, to 100%. This leads to the fact that the weighting coefficients of different factors bj do not differ as significantly as might be expected. At first glance, this result seems strange. However, from a methodological point of view, this is quite normal, since all the factors themselves are largely aggregated and, therefore, at a qualitative level, approximately equally important (without any of them, life, one might say, loses its meaning). In addition, in many studies devoted to the comparison of various aspects of economic activity and social life, the same values ​​of factor weights are used. In this sense, the methodology we use allows us to make a more accurate calibration of weighting coefficients and reconstruct the hierarchy of various aspects of people’s life.

4. The value of the generalized life satisfaction index of 53.1% lies in the so-called “zone of uncertainty.” The index mark of 50% serves as a natural boundary for the dichotomy of the population’s social well-being: if the index is more than 50%, then the population is more satisfied with their life than dissatisfied; if the index is less than 50%, then the population is more likely to be dissatisfied with life than satisfied. In this sense, the index value of 53.1% indicates that the Russian population still gravitates toward the “zone of satisfaction” rather than the “zone of dissatisfaction.” However, taking into account possible statistical errors, such a positive trend with a margin of 3 percentage points. looks so weak that the state of health of Russians would be more correctly assessed as borderline - “50x50”. It will be possible to talk about a clear predominance of a positive trend only when the generalized life satisfaction index exceeds the 60 percent mark. It should be noted that the aggregate index value of 53% corresponds well to the current state of the Russian economy, characterized by complete uncertainty of the future and an approximate parity of achievements and defeats of 15 years of reforms.

Thus, if we sum up the results of the quantitative identification of the generalized life satisfaction index, we can state the following: Russia is in a borderline state when the question of which trend in the social well-being of the population will prevail - positive or negative - is being decided. In modern language, the country is at a bifurcation point, when the very direction of further development of the domestic society is determined. Conditions of this kind, when society turns into a so-called bifurcation cauldron, are extremely dangerous, since any, even minor, negative impacts can upset the unstable balance and cause a protracted crisis.

4. Hierarchy of life satisfaction factors. Factor indices of satisfaction with various aspects of life are constructed in such a way that they have at least three “tips”: 40, 50 and 60%. If the index value is less (more than) 50%, then this means a generally unsatisfactory (satisfactory) situation in the social well-being of the population. If the satisfaction index value falls below 40%, then this indicates an extremely poor social climate; if the satisfaction index is more than 60%, then this indicates a clear predominance of positive assessments of current life among the population. Based on such simple quantitative criteria, it is possible to draw a picture of the state of affairs that had developed in the life of the Russian population by July 2005. “Painful” factors form a group with satisfaction index values ​​less than 40%; “favorable” factors have a specified index value of more than 60%; other factors can be considered more or less neutral.

Two factors are considered “painful”: the economic and political situation in the country (36.2%); financial situation of the family (39.8%). Both of these factors depend to a certain extent on the actions of the authorities and the current economic situation and have little dependence on individuals. The impossibility of actively influencing the current situation with a simultaneous awareness of its deadlock leads to the formation of pessimistic sentiments regarding these two factors.

On the opposite side of the social hierarchy are such “favorable” factors of life satisfaction as: family relationships (75.3%); friendship, communication (72.1%); climate, weather (61.6%). A completely different pattern is visible here, namely: family relationships and positive social contacts almost entirely depend on the person himself, which makes it possible to build them in such a way as to increase the level of satisfaction with these aspects of life. Climate and weather, on the contrary, are natural phenomena that do not depend on either the individual or the authorities. Accordingly, people adapt to them first of all, often from the very moment of their birth, which allows them to more or less effectively resist this factor and form a completely acceptable level of satisfaction with it.

In general, the existing dichotomy in factor satisfaction indices is in favor of a favorable development of events: out of 13 factors, only 4 have values ​​below 50%. Meanwhile, one cannot ignore the fact that a low level of satisfaction with most aspects of life provokes Russians into a closed existence in narrow social groups (family and friends). The long-term development of this trend leads to a decrease in the political, business and creative activity of people, which in turn further preserves the negative social environment. If in the near future there is no turning point in the level of satisfaction with the environment (44.2%) and social infrastructure (42.8%), then the natural conditions for the manifestation of such a basic human instinct as self-expression will disappear.

The conclusion drawn about the destructive impact of the current social environment on the creative qualities of Russians is confirmed by the hierarchical configuration of factor significance indices. Thus, among the 13 factors studied, the last place in importance was the factor of creative self-realization (66.8%) (Table 1). This means that the Russian population pushes the thirst for creativity into the background and concentrates attention on the problems of primitive life support. We can say that the instincts of self-preservation and procreation have largely suppressed the manifestations of the instinct of self-expression. From an economic point of view, such an imbalance in the value system of Russians is fraught with the gradual destruction of national human capital, a decline in the quality of the workforce and a decrease in the country’s competitiveness on the world stage.

5. Differentiation of life satisfaction by social groups. The general picture drawn in the previous sections regarding Russians’ satisfaction with their lives needs to be detailed from the point of view of the social strata that make up Russian society. First of all, let's focus on more universal patterns. In this case, we will use a simplified analysis technique: for all social groups we will compare only one characteristic - the proportion of respondents who are completely satisfied with the corresponding factor of life activity. We will cultivate a similar approach when analyzing the relative importance of the life factors being studied.

1. The data obtained convincingly show that life satisfaction among men is, on average, higher than among women. For all life satisfaction factors studied, the proportion of respondents who are completely satisfied with the state of affairs is higher for men than for women. The only exception is the factor of communication with friends, where the indicated shares are almost equal with an insignificant advantage in favor of women of 0.1 percentage points. The resulting conclusion seems quite logical, since the male part of the population is traditionally less whimsical and less scrupulous in relation to even the key standards of life support, not to mention the “small” joys of life. What seems truly unexpected is, perhaps, only the absence of any exceptions to this rule.

2. The distribution of life support factors by level of importance among men and women demonstrates a rather interesting difference: for women, factors directly aimed at life support are more important than for men, and for men, factors are more important in one way or another related to creative self-realization. Thus, compared to men, women pay more attention to personal safety, financial situation, family relationships, weather and climatic living conditions, ecology, social infrastructure and health. Men pay higher attention to the ability to achieve their goals, the availability of effective leisure, creative self-realization, social status, communication with friends, and the economic and political situation in the country. In other words, the value system of women is noticeably shifted towards the instincts of self-preservation and procreation, while among men it is towards the instinct of creative self-realization. This pattern generally confirms functional differences in the population by gender. However, it should immediately be noted that all the noted distortions are very insignificant, so that we can talk about a fundamentally different value system for men and women.

3. One of the stabilizing forces of society is a group of rich people. As a rule, as a person’s well-being increases, the level of importance of all factors of life increases. For example, for the group of “poor people” who can barely make ends meet, the share of people who note the importance of the factor of creative self-realization is 26.9%, while for the group of “rich people” who are able to purchase apartments, dachas and other expensive life benefits, it reaches 72.7%. Thus, the following pattern takes place: the greater a person’s income (wealth), the more significant all life values ​​are for him. Accordingly, it is the class of wealthy people who are interested in preserving and strengthening basic values. And, on the contrary, as a person becomes impoverished, his social lumpenization, the role and meaning of most values ​​for him increasingly turn into fiction. In addition, the more “convex” value system of high-income social groups is also supported by a higher level of life satisfaction. Thus, the share of people who report complete satisfaction with their financial situation among the “poor” is 2.4%, and among the “rich” - 45.5%. In relation to family relationships, these figures are 39.2 and 63.4%, respectively, to the possibilities of achieving goals - 4.7 and 45.5%, to the availability of effective leisure - 7.6 and 54.6%, to creative self-realization - 7.7 and 24.8%, to health - 9.9 and 54.6%, to the weather - 21.9 and 36.4%, to the environment - 7.6 and 13.6%, etc. In other words, the general conclusion about the need to increase the living standards of the population in order to reduce social tension in the country is fully confirmed by the data obtained.

4. Another stabilizing force in society is youth. Sociological surveys show that as a person ages, the importance of all factors of life decreases for him. For example, for the group of people aged 18-24 years, the share of respondents who note the importance of achieving their goals is 66.1%, while for people over 60 years old - 31.5%. In other words, with age, a person’s value system becomes less “convex”, and the level of indifference to basic life values ​​increases. This fact corresponds to the theory of instincts, according to which basic instincts are suppressed with age. Simply put, by the time of retirement, a person has lived long enough to no longer worry too much about his life (i.e., the instinct of self-preservation has “worked out” to a sufficient extent), and not to be burdened with caring for children who have already grown up by this time (i.e., the instinct of reproduction has “worked out”) and not be tormented by the lack of creative success, which either already exists (i.e., he has “worked out” the instinct of self-realization), or they will not exist anyway. Such liberation from basic instincts undermines a person’s social activity, which is confirmed by survey data.

5. Large cities, such as Moscow and St. Petersburg, have a devastating impact on all aspects of a person’s life satisfaction. Conversely, large urban settlements with a population of more than 0.5 million people have a beneficial effect. Unfortunately, the structure of the questionnaire is such that it is impossible to determine the line between a prosperous large city and a socially unfavorable metropolis. However, this pattern is not subject to discussion. For example: the share of people who report complete satisfaction with the level of personal safety for residents of Russian megacities (Moscow and St. Petersburg) is 6.8%, while for residents of large cities (more than half a million people) it is 30.3%. For other factors of life satisfaction, the spread between the indicated indicators is also large: financial situation - 6.1 versus 14.3%; family relationships - 42.9 versus 58.2%; possibility of achieving goals - 9.2 versus 19.2%; availability of effective leisure time - 12.9 versus 23.0%; creative self-realization - 7.9 versus 21.9%; climate and weather - 18.4 against 29.4%; economic and political situation - 2.5% against 10.1%, etc. As a rule, among all types of settlements, these estimates for megacities are minimal, and for large cities - maximum. The identified effect is clear: good living conditions are created mainly in large cities with a population of more than 0.5 million people; excessive overaccumulation of people in giant megacities destroys the positive achievements of a large city.

6. When studying differences in life satisfaction between different social groups, very interesting “age shocks” are revealed, which are sharp mood swings between nearby age groups. Thus, the share of people who report complete satisfaction with communication with friends for the group of 18-24 years old is 52.1%; in the next age group of 25-44 years, this figure drops by about 10 percentage points, after which for people aged 45-59 years it decreases by another 10 percentage points. Apparently, this effect is associated with a decrease in the level of “contact” of people as they age and an increase in requirements for this kind of contact. An equally interesting effect is observed in the dynamics of the share of respondents who report complete satisfaction with the environment: for the group of 18-24 years old it is 17.4%, then in the next age group of 25-44 years it decreases by almost 10 percentage points, after which it slowly increases. Such effects are observed quite often and are apparently associated with the change from youthful euphoria to a sober assessment of the situation during the transition to independent life.

7. Differences in life satisfaction between different social groups suggest the presence of a “professional advantage” effect, when representatives of some professions receive an extremely large advantage over representatives of others. For example, only 13.9% of the unemployed showed complete satisfaction with the factor of personal safety, compared to 36.0% of the “siloviki” (i.e., employees of law enforcement agencies). When studying the factor of effective leisure, the same figure for housewives was 10.6%, and for “siloviki” - 32.0%. Only 22.8% of entrepreneurs showed complete satisfaction with their social status versus 32.0% of security officials. In this case, there is a traditionally privileged position in Russia for representatives of security forces. An analysis of family relationships shows that complete satisfaction with this factor is typical only for 38.0% of unskilled workers, compared to 63.4% for enterprise managers and chief specialists. Apparently, professional management skills acquired at work are quite successfully transplanted into the family, which helps to streamline family relationships, which is what accounts for these differences.

To summarize, it should be emphasized that interfactor differences in both the degree of importance of various life factors and the level of satisfaction with them are, as a rule, much smaller than intrafactor imbalances between different social groups.

The approach to a comprehensive assessment of life satisfaction developed in this article has so far only passed the very initial stage of testing. The indicative and analytical capabilities inherent in the generalized life satisfaction index can become more fully manifested only with the accumulation of spatiotemporal arrays of reporting data. However, it is already possible to formulate a program for using the new social indicator.

It is advisable to monitor the generalized life satisfaction index in a monthly observation mode. In this case, ideally, each month it is necessary to recalculate both factor indices of life satisfaction and factor indices of significance. If this is not possible, then you can use a truncated scheme, when factor indices of significance are reassessed only once a quarter, and factor indices of life satisfaction - every month. Within a quarter, the significance factor indices are assumed to be unchanged. Based on monthly (or quarterly) assessments of the generalized life satisfaction index, it is necessary to derive its average annual value. Formation of the “history” of this indicator will subsequently make it possible to integrate it into more general macroeconomic studies.

Literature

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3. Balatsky E.V. Social heterogeneity of the Common Economic Space // “Monitoring of Public Opinion”, No. 2, 2005.
4. Basic values ​​of Russians: Social attitudes. Life strategies. Symbols. Myths. M.: House of Intellectual Books. 2003.
5. Ivleva G.Yu. Transformation of the economic system: review of concepts and outlines of the general theory // “Society and Economics”, No. 10, 2003.
6. Hazrat Inayat Khan. Alchemy of happiness. M.: Sphere. 2003.
7. Balatsky E.V. Methods for diagnosing the social well-being of the population // “Monitoring of Public Opinion”, No. 3, 2005.

RESEARCH OF LIFE SATISFACTION ON THE EXAMPLE OF THE POPULATION OF THE VOLOGDA REGION

Smoleva Elena Olegovna
Institute of Socio-Economic Development of Territories RAS
Researcher

annotation
The article presents the results of a sociological study of life satisfaction using the example of the population of the Vologda region. Most of the population of the Vologda region are satisfied with their lives (61%), dissatisfaction was noted by 17% of respondents. The factors of life activity with which respondents are most and least satisfied are identified. The analysis of differentiation of satisfaction by social groups was carried out. Gender and age differences in life satisfaction, differences in satisfaction with various spheres of life of urban and rural residents, and representatives of various professions have been identified.

THE STUDY OF LIFE SATISFACTIONTHE EXAMPLE OF THE VOLOGDA REGION

Smoleva Elena Olegovna
Institute of Socio-Economic Development of Territories of Russian Academy of Science
researcher

Abstract
The article presents the results of the survey of life satisfaction on the example of the Vo-logda region. Most of the population of the Vologda region are satisfied with their lives (61%), dissatisfaction noted by 17% of respondents. The article presents the factors of life that are the most and least satisfied respondents. The author has revealed differentiation in the level of the life satisfaction of different social groups. The author has revealed gender and age differences in satisfaction with life, differences of urban and rural residents, representatives of various professions.

Satisfaction or dissatisfaction with life determines a person’s behavior in various spheres of life. Life satisfaction “...reflects a person’s assessment of his life, where there is no gap between the existing situation and what seems to him to be an ideal situation, or one that he deserves.”

Life satisfaction is an important indicator of “the internal stability of society, the level of public support for the activities of the authorities and government institutions in general.”

Significant factors for life satisfaction in general are the following factors: the presence of close social connections, job satisfaction, health, availability of free time for leisure activities, personal qualities (self-esteem, extraversion, meaningfulness of life), positive emotions (good mood). Less significant is material support.

The objectives of the study were to determine the level and factors of life satisfaction of the population of the Vologda region.

The methodological basis of the study is a sociological survey of the population of the Vologda region. Sample size – 1500 respondents over the age of 18; The sampling error does not exceed 5%.

According to the study, the majority of the population of the Vologda region are satisfied with their lives (61%), while 12% of respondents are completely satisfied with their lives, and another 49% are somewhat satisfied. 17% noted dissatisfaction, of which only 3% expressed complete dissatisfaction with their lives.

Respondents are least satisfied with the situation in the country (44% of respondents are satisfied) and their financial situation (52%). “Favorable factors” (the satisfaction index of which exceeds 50%) include family, interpersonal relationships, and position in society.

The greatest importance for the population is financial situation (importance index 76%), family well-being (74%), the situation in the country (69%), social status (68%) and work (67%). Among all factors, the population attaches the least importance to “lifestyle” (importance index 56%).

Satisfaction with life in general is at the same level for men and women. Men and women are equally satisfied with the sphere of family and interpersonal relationships, various aspects of their professional activities: the content of their work as a whole, the ability to choose a place of work, relationships with work colleagues, the conditions of their professional activities (studies).

Men are more satisfied with their lifestyle in general, their position in society, and their financial situation, but less satisfied with their education (Fig. 1). Among women there is a very low level of satisfaction with the situation in the state.

Women also demonstrate lower satisfaction in the areas of life support and leisure: they are less satisfied with the services sector, household and medical care, everyday recreation, leisure, and the opportunity to go on vacation (Fig. 2).

Young people under 30 years of age are little satisfied with their position in society, their financial situation, the possibilities of choosing a place of work, spending vacations and leisure time, their education, and the current situation in society (Fig. 3).

At the same time, it is necessary to note the decrease in the importance of various life spheres with age. As we age, the proportion that attach importance to interpersonal communication (relationships with friends are important for 92% of young people surveyed and 85% of people over 55 (60) years old) and the sphere of professional activity decreases.

The differences in satisfaction with various spheres of life of urban and rural residents of the Vologda region are significant (64% of respondents in the city versus 53% in the countryside). This can be explained by the different socio-economic status of the city and the village. Rural residents are more dissatisfied with their living conditions and professional activities (Fig. 4).

An analysis of the differentiation of life satisfaction among representatives of various professional groups revealed differences due to their status and material and financial support. A higher percentage of people who are satisfied with life in general is among managers of state enterprises and government employees (88% of respondents), military personnel (76%), entrepreneurs (75%) and office workers (75%). Among the working population, the fewest people who are satisfied with life are among workers in agriculture (55%), trade and service workers (58%), and representatives of blue-collar professions (59%).

Among persons not classified as workers (students, pensioners, disabled people and the unemployed), the number of people expressing satisfaction with life is even lower: 55% among pensioners, 41% among the unemployed, 8% among the disabled. The low numbers are due to dissatisfaction with the situation in professional activities and material security. For representatives of these categories, choosing a place of work is problematic - from 8% (among disabled people) to 36% (among students) are satisfied with the possibility of choice.

The conducted research confirms the relevance of the problem being studied, since the study of the factors that determine life satisfaction makes it possible to identify “risk groups”, which include people who need help aimed at increasing their subjective well-being.

Usually, productivity is understood as a certain set of life achievements, successes, and accomplishments of an individual. In scientific and psychological research, it can appear as a variable that is measured on the basis of objective and subjective indicators. From the point of view of measurement reliability, objective indicators are preferable, but psychology and other social and human sciences that study personality as a subject of one’s own life “have not yet developed sufficiently strict criteria on the basis of which an integrative measurement of the productivity of human life as a whole would become real and its individual stages". Meanwhile, for psychological analysis, subjective indicators of productivity, which are formed as a result of a person’s self-assessment of individual life activity according to internal criteria of success and failure, are of no less value. In essence, they are forms of a person’s subjective experience of his own life as successful or unsuccessful, productive or unproductive, realized or unrealized. These experiences unfold in the individual’s self-awareness, and therefore the empirical study of the level of life productivity can be based on methods of formalized and free self-report.

Various subjective indicators have been proposed for analyzing the productivity of individual life activity. In Russian psychology, the causometric psychobiographical approach is popular, within the framework of which productivity is assessed by the degree of saturation of the subjective picture of the life path with significant events of the past, present and future. In foreign psychology, the concept of life satisfaction, developed by E. Diener and his colleagues in line with research into the subjective well-being of an individual, has received wide recognition. In this concept, life satisfaction is considered as a cognitive component of subjective well-being, not mixed with affective components - a maximum of emotionally positive states and a minimum of emotionally negative states. Satisfaction is defined as a global assessment of real life through the prism of subjective standards of a “good life”, which are constructed independently or acquired ready-made from the social environment. The overall level of satisfaction at any given time indicates the degree of discrepancy between the reality of life and personal standards of a “good life.”

The study of the relationship between the meaning of life and the components of subjective well-being of the individual forms one of the main lines in modern existential and positive psychology. A number of foreign and domestic studies have documented a direct correlation between the level of meaningfulness and life satisfaction, which is interpreted as evidence of the need for meaning for the subjective well-being of an individual. The meaning of life is considered in two ways: some researchers see it as an independent phenomenon, acting as an external condition, an exogenous determinant of subjective well-being, while other authors include it in the internal structure of an individual’s psychological well-being as one of the components. In general, this correlation is interpreted as a factual confirmation of V. Frankl’s idea about the primacy of the desire for meaning and the derivation from it of the positive phenomena of human existence - happiness, satisfaction, self-actualization. It should be noted that a similar idea was expressed by Russian existentially thinking philosophers and psychologists, for example, S.L. Rubinstein: “The transformation of a derivative result into a direct immediate goal of action and life, the transformation of life into a pursuit of pleasure, which turns a person away from solving his life problems, is not life, but its perversion, leading to its inevitable devastation.

On the contrary, the less we chase happiness, the more we are busy with the work of our lives, the more positive satisfaction and happiness we find.” The meaning of life is thus considered as an important condition contributing to the achievement of an acceptable level of personal satisfaction with life.

This is a correct, but far from exhaustive explanation of all possible relationships between the meaning of life and life satisfaction. What often escapes the attention of researchers is that the meaning of life is “built-in” inside the psychological mechanism that ensures the formation and maintenance of a sense of satisfaction with life. In the individual consciousness, it is framed in the form of a subjective model of the desired future, or life ideal, and serves as an internal standard with which the individual is compared when assessing his current life. In other words, it performs an evaluative function in relation to the life achievements of the individual. The subjective experience of satisfaction or dissatisfaction is derived from the evaluative function of the meaning of life and, as it were, “sums up” the overall productivity of individual life activity. It signals how the individual is doing with the practical realization of the meaning of life; how much she progresses and succeeds in individual life activities; to what extent has she approached the ideal state, which is “designed” by the meaning of life. It logically follows from this that life satisfaction is a subjective experience of an individual regarding the productivity of individual life activity, assessed through the prism of the meaning of life.

Taking into account the evaluative function helps to understand why meaningfulness and satisfaction are closely related, and at the same time relatively independent phenomena. After all, a meaningful life is not always satisfying, and a satisfying life does not necessarily imply the presence of meaning. The fact is that the presence of meaning in life is important and necessary, but in itself not a sufficient basis for subjective satisfaction with life. A meaningful life becomes satisfying and happy only if a person productively realizes its meaning. If a person is not able to productively realize the existing meaning, it turns from a factor of satisfaction into a source of unhappiness and suffering. The suboptimal meaning of life actually represents the case when meaningfulness of life serves as a prerequisite not for a feeling of deep satisfaction and a stable feeling of happiness, but for uncomfortable, traumatic experiences. In this situation, the presence of meaning in life turns out to be not a benefit, but a psychological burden for the individual. The suboptimal meaning of life burdens life with such contradictions that fetter and inhibit the self-realization of the individual and, therefore, deprive him of the opportunity to enjoy success in life, to feel satisfied with life and with himself.

Thus, subjective experiences of satisfaction or dissatisfaction with life reflect the dynamics of a person’s practical realization of the meaning of his own life. The degree of satisfaction is determined by how successfully a person progresses in realizing the meaning of his own life and the life goals, plans, and programs derived from it. Various types of suboptimal meaning in life negatively affect the pace and productivity of this advancement, as a result of which the level of life satisfaction falls and the threat of a meaning crisis arises.