Abstract
This article discusses two basic theories of social measurement in development studies – the quality of life (QOL) and social quality (SQ) theories. The QOL theory has a long tradition in the study of individuals’ living standards, whereas SQ theory helps us understand the traits of social circumstances. Based on survey data collected from six Asian societies, a number of QOL and SQ factors are examined in this study to show how these two approaches are both distinctive and complementary. The study suggests consideration and comparison of these measures relating to factual indicators and subjective indicators in order to reveal the features of different societies.
Introduction and the research setting
For a long time, social scientists have made great efforts to represent social circumstances in a scientific manner by using reliable data structured with coherent underlying logic. In order to achieve this goal, social scientists have attempted to fit a range of social phenomena into a unified analytical framework to meet their research needs. Employing social indicators is a way to achieve these aims, which can be used as an effective instrument in both theoretical and empirical studies (Land et al., 2007). As we have observed, various indicator systems help to improve our understanding of present social conditions, such as the Index of Social Progress (Estes, 1984), the Index of Well-being (Kacapyr, 1996), and the Human Development Index (see UNPD, 1995), etc. These indicator systems are underpinned by theories which not only influence the design and adoption of the indicators, but also enable studies measuring indictors to go beyond the level of description, thereby allowing us to interpret the meaning of the observed phenomena.
Among the various social theories using indicators to measure social realities, the quality of life (QOL) theory and the social quality (SQ) theory are the most prominent ones. The QOL theory, loosely defined as an approach underpinning quality of life studies, has supported the growth of theories of human security, development studies, and social services. For instance, in a QOL study of the elderly, Lawton (1983) used the Multilevel Assessment Instrument composed of over 100 indicators to test physical health, time use, social relations, and perceived environment. In reality, the growth of QOL research contributes to the development of both comparative and indicator studies.
The SQ theory is a relatively new approach in comparison with the QOL theory, only having been established in 1997 (see Beck et al., 2001). This theory offers a conceptual framework to understand the quality of society through the analysis of three sets of factors: the constitutional, the conditional, and the normative factors. The analysis of conditional factors takes place through the application of SQ indicators. This indicator system, including 95 indicators in 18 domains with 49 sub-domains (see Maesen and Walker, 2001), reflects the factual conditions of the four dimensions of social quality analysis: namely socioeconomic security, social cohesion, social inclusion, and social empowerment (see Figure A1 in the Appendix). In the 2000s, scholars working on these issues demonstrated that the application of the SQ indicators is very helpful for measuring social quality (Maesen and Walker, 2001; Maesen et al., 2002). In recent years, the use of this theory has expanded rapidly from Europe to Asia (and also to Australia) (see Lin et al., 2009).
For making comparisons between these two theories, we should be aware of the different emphases of using indicators in these theories serving their particular purposes and theoretical underpinnings. One of the basic differences between these two approaches is their standpoints. The QOL theory is individual-oriented. Veenhoven (1996) stated that most indices in the QOL paradigm intend to explore how well individuals live in society, while others stress that the QOL approach refers to an individual’s total well-being, including all of the emotional, social, and physical aspects of the individual’s life (Economist Intelligence Unit, 2005). Conversely, SQ scholars (e.g., Phillips, 2011) have highlighted the features of SQ theory that identify it as society-oriented, in contrast to the QOL focus on individuals. These points raise the need for more critical debates and analyses. We need to explore the very nature and the particular features of these two theories, both for their advantages and disadvantages, so as to draw out policy implications.
In this study, the differences between these two theories will be distinguished and compared in terms of methodology by keeping in mind the following questions: What are the methodological features of these two theories? Are these two theories contradictory or complementary in terms of their application to studies concerning social circumstances or realities? If they are contradictory, it will be necessary to explain how they are so, what implications this has for analysis, and under what conditions, and how effectively these two approaches can be used to describe and interpret people’s daily circumstances. To answer these questions, the research presented in this article compares the theoretical and methodological applications of the QOL and SQ theories. The empirical research is based on data collected from a set of SQSQ (‘social quality survey questionnaire’) surveys. The main purpose is not only to display the features of the societies examined in the surveys but, more importantly, to demonstrate the methods of data analysis of these two approaches.
In order to develop this kind of analysis, some observations are needed to enable this comparison. First, we should look at the relationship between objective indictors and subjective indicators. Objective indicators, including GDP per capita, the number of beds for elderly care, the number of schools, etc., can provide some fundamental grounds for defining and measuring life quality and social quality. They can provide quantitative data, although these indicators are obviously insufficient in providing a comprehensive appreciation of quality of life or quality of society without support from the subjective indicators (Noll, 2002a). Subjective indicators refer to ideas such as happiness and life satisfaction, which are, in Costanza et al.’s (2008) view, very subjective and personal; but these indicators can reflect people’s experience of well-being.
Second, there are debates over how to use subjective indicators. We can classify the subjective indicators into two types: the purely subjective indicator and the factual evaluations of the living conditions of individuals and society. The first set of indicators describe individual perceptions and satisfactions that relate to individuals’ experiences such as the feeling of joy, pleasure, contentment, and life satisfaction (Shackman et al., 2005). The second set of indicators describes respondents’ comments based on situational factors. The aggregation of these indicators allows us to comprehend the QOL condition in an ‘objective’ sense and therefore, to increase the objectivity of our description of people’s well-being. From the standpoint that the survey data (as the accumulation of individuals’ opinions) may reflect social realities objectively (at least to some extent), we regard this type of evaluation as being more objective than satisfaction indicators. Therefore, through these data, we can approach both the objective and subjective well-being of people’s lives.
The third issue about social indicators involves the argument that there is no reason for us to believe that aggregated objective indicators actually reflect the quality of people’s lives (see Schneider, 1976). Thus, the use of survey data can offer more direct evidence for the individual’s QOL situation. These data might disclose not only the conditions of people’s material living conditions, but also their subjective feelings and life satisfaction. For instance, the International Social Survey Program, the European Community Household Panel Study, the European Social Survey, etc. (Vogel, 1997) provide us with solid empirical grounds to develop studies on social circumstances. In this regard, the survey data can work better than some objective indicators to measure the QOL and SQ conditions in society, at least in terms of self-reporting.
Accordingly, this study establishes the empirical basis of its analysis on a series of surveys undertaken by the members of the Asian Consortium for Social Quality in Japan, South Korea, mainland China, Taiwan, Hong Kong, and Thailand. The institutions involved in this survey program include Chiba University, Seoul National University, Zhejiang University, National Taiwan University, City University of Hong Kong, and Thailand’s King Prajadhipok’s Institute. Flinders University in Australia also undertook a similar survey. However, since Australia is not in Asia, the survey data analyzed in this study from the six Asian countries exclude the data from Australia. The purpose of this survey is to make cross-societal comparisons of social quality conditions, with a particular emphasis on the dimensions of social inclusion and social cohesion. The surveys using the same questionnaire (‘social quality survey questionnaire’, SQSQ) were undertaken from 2009 to 2011 with over 6460 sample cases provided for comparison.
In these surveys (the features of the surveyed groups are presented in Table A1 in the Appendix), the data sets collected from mainland China, Taiwan, and Hong Kong are at the city level (Hangzhou, Taipei, and Hong Kong, respectively), while those collected in Japan, South Korea, and Thailand are at the national level. Accordingly, the data cannot be claimed as the reflection of national SQ conditions, but rather of the respondents of these societies. This is also due to the limited number of samples in each of the societies surveyed, as well as the methods of conducting surveys varying in different places according to the local needs (for the database, see Lin et al., 2012). This feature may influence the comparability of the collected data; however, since the purpose of this study is to demonstrate the methodological features of these two approaches, we will not concentrate on the ranking of these compared societies but identify the distinctive features of the two approaches.
An analysis of survey data from the QOL and SQ approaches
The QOL approach
In order to design this study from the QOL approach, first of all, we must define the domains of indicators to be used. QOL studies usually employ a large number of social indicators to study people’s lives, and thus, the list of indicators tends to be endless. Consequently, the difficulty when selecting appropriate indicators to serve research needs is a serious issue. In previous studies, the QOL factors were referred to as physical and psychological health, financial (and economic) and social well-being, as well as social relations. For instance, Kane (2003) evaluated QOL conditions by using indicators of income, health status, mental health status, disease profiles, educational level, and housing situation to measure the overall quality of life, whereas Gregory et al. (2009) regarded wealth, employment, environment, health, education, recreation and leisure time, and social belonging as the key indicators reflecting the standard of quality of life.
In this study, the indicators from key areas were selected to reflect QOL situations of the examined societies. They corresponded to the common usage, with restricted coverage that excluded the psychological dimension of QOL indicators. Thus, this study included indicators referring to income, health, education, and environment as in many QOL studies (see Hilhorst and Klatter, 1985), but it also used health and interpersonal relations as the key areas for examination. The respondents’ answers describing their living situations were analyzed and the survey questions were divided into two categories: the factual evaluation and satisfaction indicators (see Table 1).
QOL survey questions.
In the calculation of the scores for the original answers to the questions included in Table 1, a scale of 0–1 was used, with the highest score (in 0–1 score) indicating the highest QOL. All of the response categories were standardized to a normed 0–1 scale providing us with an overall score (the details of these values and the assumed score are presented in Table A2 in the Appendix). Taking the five possible responses to a question as an example, we scored the first choice as ‘0’ and the last choice as ‘1’ (excluding the answers such as ‘no answer,’ ‘not sure’ or ‘unknown’ with no score assigned) to obtain the scores plotted in Figures 1 and 2. While doing so, we assumed equal intervals for all items and used an equal weight strategy for constructing composite measures, as it can minimize extreme disagreements among all possible weighting schemes (see Land et al., 2011).
QOL situational scores.
QOL satisfaction scores.
The results after calculating the scores of the survey data are presented in Figures 1 and 2: one using the factual evaluation data (with the situational scores) and the other using the life satisfaction data. These graphs indicate that each item varies across the different societies, and no one factor can be considered dominant in determining overall QOL scores. Nevertheless, some common traits can still be observed across these societies. For instance, in all six aspects of QOL, the situational scores related to environment and employment are generally high, whereas scores related to social relations and education are relatively low (excepting mainland China and Taiwan; see Figure 1). This illustrates aspects of people’s lives where there are some more (or less) serious problems which need to be improved (or to be satisfied).
Interestingly, the situation reflected through the satisfaction indicators is quite different from the situation in the factual evaluation indicators (Figure 2). The scores of the satisfaction indicators across the six societies are closer than that of the evaluation indicators. From the details of the six items of satisfaction examined, it can be seen that respondents are most satisfied with social relation and health care but less satisfied with education and employment (see Figure 2). Since people’s comments are influenced by their general outlook on their lives, the difference between the scores in Figures 1 and 2 demonstrates that the indicators relating to people’s satisfaction do not necessarily express the true condition of QOL. Thus, only the combination of these two sets of indicators can effectively describe what is happening.
The SQ approach
The social quality (SQ) theory presents a conceptual framework of analysis for society with an emphasis on social relations and social systems. Taking this approach, the study should be linked to analyses of the four dimensions of conditional factors: namely socioeconomic security, social cohesion, social inclusion, and social empowerment (see Beck et al., 2001). In the SQSQ surveys, we asked respondents about their income levels and spending with regard to socioeconomic security, and evaluated the conditions of social cohesion in society with the questions concerning respondents’ sense of social trust (at both the interpersonal and institutional levels). We enquired about respondents’ views on social distance between the poor and the rich and between employees and employers to evaluate social inclusion, and to measure respondents’ sense of belonging to their local communities and nation. With regard to social empowerment, we asked about their participation in groups, systems, and national elections of congress representatives.
The questions used in the SQSQ surveys are presented in Table 2.The scores for the answers from the surveys were calculated in the same way as in the QOL data analysis. Figure 3 reflects the social quality conditions in these societies on the basis of the survey scores. The axes on the graph reflect the calculated SQ scores valued between 0 and 1 to represent their strength in each dimension. The original calculation data can be found in Table A3 in the Appendix. From this table, we can see that Thailand has a relatively high overall score for social quality despite the country’s relatively low level of economic development. Meanwhile, the Korean figures show a particularly low score with regard to social inclusion, whereas Taiwan shows relatively balanced scores across all four dimensions.
SQ survey questions.
The SQ situation for the six Asian societies.
Through the comparison of our survey data, it can be concluded that Thailand and Taiwan have relatively higher SQ scores, with Japan, Hong Kong, and mainland China scoring roughly in the middle, and Korea having the lowest (see Table A3 in the Appendix). Nevertheless, we should acknowledge the limits of this score calculation method for international ranking, since the suitability of the questions may be debatable with regard to their level of objectivity and how efficient the indicators are in reflecting social relations. Nevertheless, as the purpose of this study is not to engage in the business of ranking, it can still be used to illustrate the relationship among the factors in the four domains of observation for these societies.
To describe the SQ scores of these societies, a few general observations and conclusions can be made here. The contribution of socioeconomic factors to the general SQ score is very similar in the different cases (see Figure 3), as the standard deviation for socioeconomic security is as low as 0.042, in comparison to the corresponding figure for social inclusion which is as high as 0.106 (see Table 3). This situation means the cross-societal variation is mainly due to the differences in social inclusion. Also, the SQ scores in social cohesion are generally high but social empowerment is quite low (see Table A3 in the Appendix). These conclusions imply that the factors involved in social inclusion and social empowerment, rather than socioeconomic factors, bring down the average SQ scores of the societies surveyed here.
The deviation of the data in each dimension of SQ analysis.
However, as this study concerns the methodological issues, we do not focus on what makes these societies different, but rather on how to demonstrate these differences with methods of comparison, as well as the functions and implications of such methods used. The QOL and SQ theories can reveal the features of the data from their particular perspective, and through these different methods, these approaches can become instruments for social studies. In the SQ analysis, for instance, material well-being, one of the central themes in QOL studies, is not identified as the predominant criterion for the SQ of people’s lives, but factors like social inclusion and social empowerment play significant roles.
A methodological comparison of the QOL and SQ approaches
Based on the above observations on the methodological features of the QOL and SQ approaches, we can make further comparison between these two theories. With regard to the standpoints of these two theories, the QOL approach employs indicators measuring the standards of individual livelihoods with an individual-focused orientation. This orientation is further strengthened by its development along the psychological and subjective dimensions, since indicators focusing on subjective well-being emphasize the emotional and cognitive aspect of personal realities (Diener et al., 1999). In this study, we demonstrate the nature of the individual-based QOL analysis through questions on six aspects: income, employment, health, education, environment, and social relations. By using SQSQ survey data for this analysis, we illustrate how the large diversity in these data among these six societies reflects people’s general living conditions; and for any single society, the indicators on situational valuation and satisfaction give yet different profiles of life quality.
Accordingly, the potential of using the QOL approach to describe the overall conditions of society should be questioned. Some scholars (Baars, 2005; Gasper, 2011; Phillips, 2011) criticize the QOL paradigm as failing to articulate ‘social quality.’ In their view, the QOL approach takes the perspective of isolated individuals as the ultimate reality, whereas the SQ approach is oriented toward the collective nature of human relations. As Maesen and Walker (2011) argue, social quality is not just the accumulation of the life quality of individuals, and in the view of Beck et al. (2001), the SQ approach aims to construct the dialectic between the self-realization of individuals and the formation of collective identities.
To be sure, the QOL approach may also refer to some elements of the social environment, and thus, factors such as politics and human relations can be referred to in QOL studies. For example, Gregory et al. (2009) argue that the QOL theory evaluates the general well-being of individuals and societies in reference to a wide range of contextual factors (international development, health care, politics, etc.), and Veenhoven (1996) also suggests that the QOL analysis involves a number of factors such as social security, political freedom, and gender equality. Thus, to conclude that the comparison between these two theories is just ‘individual vs. society’ would be too simple. However, we should note that those social factors are located on the margins of QOL analysis. With its focus on the social system as a whole, the SQ analysis instead has the advantage of reflecting the relational aspect of social origination (Lin, 2011). Thus, the SQ analysis leads our attention to the contextual analysis of the social system beyond the indicator studies of life quality.
Meanwhile, scholars may argue, as elaborated by McEwin (1995), that the QOL approach could function not just to measure individuals’ living standards but also as a measure of trends of social change. Nevertheless, once QOL theory uses social indicators as the indicators of social change, we can observe that these changes are mostly seen in a linear model of increasing development. Indeed, many QOL indicators were used to compare the levels of development (in particular economic development) among different countries, and such comparison has a strong correlation with GDP per capita. For this reason, McGillivray (2007) regarded the QOL approach as something that could offer little more than a study of economic indicators. Thus, such analysis would have difficulty reaching the contextual, structural, and institutional reasons of social change.
The SQ approach instead presents the magnitude of four dimensions of conditional factors in order to reveal the challenges and the potential changes within society. As illustrated by this study, the method of SQ analysis can display the strength of factors in the four dimensions, and permits researchers to acknowledge the problems of social structure and interrelationships from its particular angle. Though the SQ analysis has a degree of overlap with QOL indicators in the aspect of socioeconomic security, in other dimensions, it helps understand the social circumstances beyond the sphere of people’s living conditions. In this sense, the SQ theory has certain policy implications in detecting institutional flaws and making corresponding policies, as well as in detecting the orientation and strategy of development.
To evaluate their different ideological implications, the QOL approach is underlined by notions such as modernization, life quality and incrementalism. Indeed, in the history of development, modernization theory has supported the QOL approach with the assumption that the higher the level of economic growth, the better people’s lives will be (Veenhoven, 1996). The SQ theory also supports the development process but moves the focus on individual lives to social conditions. This theory advocates an ideology of social harmony and promotes overall well-being of all social groups through improved system integration (Lin et al., 2009). Adhering to these ideas, some policy proposals can be raised such as developing institutions that are widely accessible to people so as to ensure social inclusion and, normatively, lay a solid foundation for social cohesion and solidarity.
Despite the aforementioned differences, we should still emphasize that these two theories can be complementary. Both the QOL and SQ approaches can be instruments to support social development toward a ‘good life.’ Through social indicator studies, the QOL approach can facilitate the mapping of an all-round picture of the conditions of people’s lives for a ‘good life’; however, how to define the meaning of this ‘good life’ needs social interpretation. As Cobb (2000: 6) stated, ‘in order to measure quality of life, one must have a theory of what makes up a good life.’ The SQ theory that pursues an active and coherent society could help to perceive the nature and social conditions of ‘good life.’ In this sense, these two theories can be complementary, although they might present different images of future development to the public.
The function of SQ and QOL theories can be complementary also with respect to policy practices. The QOL studies can disclose problems of housing, income, and employment, and this can encourage governments to promote social (policy) action to cope with these demands in society. The QOL indicators can also help policymakers to evaluate how well they are doing compared with, for example, their development goals or the quality of life in other countries, or to evaluate whether quality of life has improved over time. The SQ theory, however, goes beyond the policy analysis to promote solidarity and institutional integration; but its analysis can help us to undertake the most crucial tasks of policy action by unearthing the key issues for making improvements.
Conclusion and discussion
This study illustrates the features of the QOL and SQ approaches, and reveals the distinctiveness, traits, functions, purposes, and orientations of the two methodologies. In the term of their functions, for example, the QOL approach adopts a view of linear development, while SQ theory is helpful in conducting a functional-structural analysis. To illustration these features, this study uses the same set of data but reveals different emphases by applying these two approaches. Through these comparisons, this study explores the methodological characteristics of these theories. It concludes that both of these approaches are useful methods of social analysis and instruments to achieve the goal of a ‘good life.’
This study also used three sets of indicators to reflect the survey data, i.e., indicators of fact evaluation, satisfaction, and social quality. It shows that the scores of satisfaction are not very consistent with people’s factual evaluation. As evidenced, the situational score is in general lower than the satisfaction score (see Table A2, excluding the Japanese case due to missing data on neighborhood relations). This result implies that people’s well-being cannot simply be reflected in their living conditions but is also influenced by their personal feelings. As Diener and Suh (1997: 213) maintain, ‘we can comprehend quality of life fully only if we understand the interplay between social indicators in a society, and the subjective reactions of the citizens of that society.’
With this understanding, we can underscore an emphasis on the development of subjective well-being for QOL studies (Land et al., 2007). Thus, quality of life is not only the extent of development in the material world or measured by the economic life, but is also concerned with people’s feelings and how they judge their living conditions. In this study, we find that the rich countries do not show a better score on the QOL indicators than the developing countries (such as Thailand and mainland China) in terms of situational valuation and satisfaction. For instance in Thailand, the level of economic development is relatively low, but its level of satisfaction in the QOL score is generally high.
Nevertheless, the factors determining the QOL conditions will also have certain social causes. As Erickson (1993: 77) noted, the problem with an approach based on people’s self-assessment about satisfaction is ‘that it is partly determined by the level of aspiration’. However, we may need also to take the reasons of social contexts into consideration. Thus, we need to explore the social reasons for individuals’ daily circumstances and their satisfaction. By comparing the scores of the QOL and SQ with the survey data, this study indicates that average SQ scores are generally lower than average QOL scores in the societies examined here (see Tables A2 and A3). This observation is further supported by the SQ subtotal scores in the four dimensions: the mean score of socioeconomic security (in relation to material life) in all these societies is the highest (0.653), but the lowest score (0.470) is to be found in social inclusion (see Table 3).
With regard to policy orientation, the QOL and SQ approaches can both be utilized to reveal social problems. In the past, the QOL theory made great contributions to the development process with its perception that the higher the GDP per capita and the literacy rate, the higher the quality of life. This perception now seems questionable since, as claimed by some researchers (e.g., Shackman et al., 2005), material life does not automatically equate to higher life satisfaction. In this study, we get a clear impression through data analysis that a higher incomes does not necessarily lead to a more satisfying life. Rather, to develop measures of inclusive social policies for strengthening social cohesion (as promoted by the SQ theory) is the key issue to resolve social problems and achieve further development.
In all, this study discloses the particular features of the QOL and SQ theories in analysis of social realities and also shows their relations to be both distinctive and complementary. The comparative analysis from the SQ approach may explore some questions that are beyond the capacity of QOL theory, and can lead to different policy implications. The SQ studies might help QOL researchers to explain how to improve people’s well-being through the enhancement of social conditions, and such policy proposals may receive great attention not only within academic debates but also within policy circles. Thus, despite the fact that the ideology of a balanced and harmonious society, which is a traditional concern in Europe (Noll, 2002b), has existed for a long time, the SQ theory supports the ideology of social cohesion, and in its special way, gives these issues a new answer. Against this background, we can evaluate the meaning of SQ analysis in the methodological sense, and identify its significant function in our struggle to achieve a ‘good life’ and a ‘good society.’
Footnotes
Appendix
SQ survey data from the six societies.
| Questions | Japan | South Korea | Mainland China | Taiwan | Hong Kong | Thailand |
|---|---|---|---|---|---|---|
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| A1. Family spending | 0.6513 | 0.6553 | 0.7185 | 0.7080 | 0.7103 | 0.6214 |
| A2. Income levels | 0.5147 | 0.4674 | 0.3092 | 0.4251 | 0.4492 | 0.4834 |
| A3. Employment | 0.6715 | 0.7428 | 0.5731 | 0.4052 | 0.6935 | 0.8338 |
| A4. Medical expense | 0.7452 | 0.8119 | 0.8227 | 0.8760 | 0.9075 | 0.8742 |
| Subtotal score | 0.6457 | 0.6694 | 0.6059 | 0.6036 | 0.6901 | 0.7032 |
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| B1. General trust | 0.4444 | 0.2686 | 0.5719 | 0.4406 | 0.4784 | 0.2526 |
| B2. Interpersonal trust | 0.5646 | 0.5448 | 0.5300 | 0.5789 | 0.6176 | 0.6023 |
| B3. Institutional trust | 0.5455 | 0.4555 | 0.7400 | 0.5046 | 0.5978 | 0.6703 |
| B4. Pride in country | 0.7272 | 0.6631 | 0.7800 | 0.5981 | 0.6375 | 0.9752 |
| Subtotal score | 0.5704 | 0.4830 | 0.6555 | 0.5305 | 0.5828 | 0.6251 |
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| C1. Group tension | ||||||
| a. The poor and the rich | 0.3183 | 0.1763 | 0.0845 | 0.4386 | 0.3373 | 0.5078 |
| b. Managers and workers | 0.3733 | 0.1726 | 0.1592 | 0.5235 | 0.4162 | 0.5235 |
| c. Racial and ethnic groups | 0.4313 | 0.3249 | 0.4713 | 0.6123 | 0.5385 | 0.6730 |
| d. Religious groups | 0.4779 | 0.3059 | 0.5007 | 0.6511 | 0.5808 | 0.6510 |
| C2. Discrimination | 0.7870 | 0.5944 | 0.6799 | 0.5983 | 0.5977 | 0.5817 |
| Subtotal score | 0.4776 | 0.3148 | 0.3791 | 0.5648 | 0.4941 | 0.5874 |
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| D1. Political participation | / | 0.1700 | 0.1100 | 0.1400 | 0.1900 | 0.0600 |
| D2. Fear/danger | / | 0.7300 | 0.7400 | 0.7500 | 0.7400 | 0.7600 |
| D3. Freedom | 0.4959 | 0.5663 | 0.5172 | 0.6083 | 0.5737 | 0.6294 |
| D4. Social participation | 0.1300 | 0.1500 | 0.2500 | 0.4600 | 0.1300 | 0.0400 |
| D5. Voting | 0.8490 | 0.6789 | 0.5800 | 0.7699 | 0.4517 | 0.8883 |
| Subtotal score | 0.4916 | 0.4590 | 0.4394 | 0.5456 | 0.4171 | 0.4755 |
|
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0.5463 | 0.4816 | 0.5200 | 0.5611 | 0.5460 | 0.5978 |
Funding
This study is supported by the Chinese Foundation of Social Sciences on social quality research project (11AZD087).