Life satisfaction index a lsia
Life satisfaction index a lsia
Рейтинг стран мира по Индексу удовлетворённости жизнью
Информация об исследовании
Общество Изучение социальных процессов.
Рейтинг качества жизни в странах мира
Индекс удовлетворённости жизнью в странах мира (Satisfaction with Life Index) — комбинированный показатель, который измеряет уровень субъективного благополучия людей в странах мира. Индекс и методология исследования разработаны в 2006 году Эдрианом Уайтом (Adrian G. White), социальным психологом из Университета Лечестера, Великобритания.
В настоящее время считается, что понятие счастья или удовлетворённости жизнью — одно из наиболее важных направлений исследований в области социологии, психологии, экономики и государственного управления. Показатели удовлетворённости жизнью стали особенностью нынешнего политического дискурса и часто рассматриваются в качестве определённой альтернативы показателям экономического роста, так как в целом имеют больше общего с жизнью реальных людей, чем абстрактные экономические теории.
Индекс удовлетворённости жизнью позиционируется как глобальная проекция субъективного благополучия людей на планете и основывается на статистическом анализе данных метаисследования различных опросов, индексов и других показателей по уровню счастья граждан соответствующих стран. В ходе исследования проанализированы данные, опубликованные специализированными учреждениями Организации Объединённых Наций, Всемирного банка, Организации Экономического сотрудничества и развития, Всемирной Торговой организации, Gallup, Economist Intelligence Unit, New Economics Foundation, других международных организаций и национальных институтов — всего более 100 различных исследований по всему миру. Полученные данные также проанализированы в отношении здоровья, экономического благосостояния и доступа к образованию. Подробное описание методологии формирования Индекса и источников данных для него приводится в работе «A Global Projection of Subjective Well-being: A Challenge To Positive Psychology?»
Результаты исследования
В этом разделе представлен актуальный (периодически обновляемый в соответствии с последними результатами исследования) список стран мира, упорядоченных по Индексу удовлетворённости жизнью их жителей. Текущее исследование охватывает 178 государств (данные опубликованы в 2006 году).
Life Satisfaction
The Life Satisfaction Index-version A (LSIA)51 is a 20-item questionnaire providing a cumulative score acknowledged as a valid index of quality of life.
Related terms:
Life Satisfaction
Focus of Life Satisfaction Research
Life satisfaction is one of the oldest research issues in the social scientific study of aging. Initially, this research focused on pathology and coping, but later the issue became perceptions of quality of life. Life satisfaction and other subjective well-being measures have been of considerable importance in gerontology. Researchers and policy makers are attempting to better understand the impact on quality of life of disability, changes in health status, caregiving, bereavement, retirement, role transitions and loss, diminishing social networks, modifications in activity involvement, and personality development over the life course.
Two issues have dominated research on subjective well-being in the field of gerontology. The first concerns how best to conceptualize and measure subjective well-being. Life satisfaction is only one of several competing subjective well-being constructs, and researchers continue to work at developing appropriate measures. The second issue involves the identification of those factors in people’s lives that influence their subjective well-being. A substantial amount of research focusing on this issue and using the life satisfaction construct has been reported. The impact on life satisfaction of various interventions, programs, and policies directed at older adults has also been of recent interest.
Measures of Life Satisfaction Across the Lifespan
Convergent/Concurrent
The LSITA scores correlate positively with the Salamon-Conte Life Satisfaction in the Elderly Scale (SCLSES; Salamon & Conte, 1984 ). For example, Barrett and Murk (2006) reported a correlation of r=.78 between the total scores of the LSITA and SCLSES. The corresponding domain scores showed correlations between r=.56 (LSITA congruence of goals – SCLSES goals) and r=.75 (LSITA zest vs. apathy – SCLSES daily activities). The correlation between the LSITA and the SWLS ( Diener et al., 1985 ) also exceeded r=.50 ( Barrett & Murk, 2006 ).
Successful Aging in Women
The Life Satisfaction Inventory
The Life Satisfaction Index-version A (LSIA) 51 is a 20-item questionnaire providing a cumulative score acknowledged as a valid index of quality of life. Dimensions of the scale include zest for life; resolution and fortitude; congruence between desired and achieved goals; high physical, psychological, and social self-concept; and a happy, optimistic mood. Participants agree or disagree with the statements and a total scale score is based on number of agreements such that higher scores indicate better life satisfaction. Specific test items include questions such as: ‘as I grow older, things seem better than I thought they would be’ and ‘as I look back on my life, I am fairly well satisfied’. It is a widely used instrument and has prior evidence of an inter-rater reliability of 0.78 and validity based on relationships with other measures of life satisfaction. 51
Well-being (Subjective), Psychology of
5 Cultural Differences in SWB
Certain variables predict life satisfaction in some cultures, but not in others (Diener and Suh 2000 ). For example, self-esteem is a strong correlate of satisfaction in highly westernized, individualistic cultures, but not in collectivistic societies where the group is more important in defining who one is. Similarly, consistency and acting in congruence with the self are stronger predictors of SWB in individualistic than in collectivistic cultures. Also, individualists on average heavily use their own emotional feelings to judge their life satisfaction, whereas collectivists are more likely to weight normative prescriptions for happiness, and the views of others. For collectivists, SWB must include the belief that significant others evaluate one’s life well. The explanation for these differences between nations is that various cultures emphasize different values and goals, and therefore tend to make certain information chronically salient so that it is used when people judge their lives.
Not only are there cultural differences in the correlates of SWB, but average SWB levels differ across nations as well. For instance, high levels of SWB are currently reported in northern European nations, whereas much lower levels are reported in eastern European countries. Several factors seem to account for the differences between nations in SWB: wealth versus poverty, political stability versus instability and social disruption, and culture. In terms of culture, some societies seem to emphasize a positive approach to life, and the desirability of happiness. In these ‘positivity cultures’ there are higher levels of satisfaction than are predicted based on wealth or objective factors alone.
Set Point Theory and Public Policy
Data and Methods
As mentioned, the SWB data are for April–May 2007, a date prior to the onset of the Great Recession. Public policies for the unemployed may be temporarily expanded in the face of rising unemployment, and such actions may distort basic policy differences among countries due to differences in the severity of a recession and the policy responses thereto. For virtually all of the countries included here, however, unemployment rates were declining prior to the date when SWB was observed; hence, the policy measures should be indicative of fundamental differences in policy. NRR and ALMP measure policies as of the year 2006; the strictness measure is for 2011, the only year for which an estimate has been made.
Three macroeconomic variables that are typically found to be significantly related to SWB are also included in the analysis. The first is GDP per capita in the year 2006, measured in 2005 dollars of purchasing power ( Heston, Summers, & Aton, 2012 ). The second is the inflation rate, the percentage change in the level of prices from 2005 to 2006. The third is the unemployment rate for April–May 2007, the month in which life satisfaction was surveyed.
Note that the unemployment rate may itself be viewed as a labor market policy variable. Differences among countries in the unemployment rate may reflect, in part, differences in fiscal and monetary policies aimed at achieving full employment. But unemployment differences may also be due to nonpolicy factors underlying aggregate demand and supply.
The net replacement rate and benefit strictness indicator are measures based on legislation in each country establishing the policies relating to each. The active labor market policies variable, however, is based on spending on such policies, and may not be an accurate indicator of actual policy differences among countries. Two countries may have the same policies, but if one has a higher unemployment rate, this will induce more ALMP expenditure and lead to the impression of a policy difference on ALMP. Hence, in assessing ALMP differences across countries, it is desirable to control for unemployment, as is done in the multivariate regressions described in the following sections.
One would expect that life satisfaction would vary directly with the net replacement rate and active labor market policies, and inversely with the strictness indicator. Higher NRR and ALMP contribute to maintaining one’s income, whereas strict eligibility requirements operate in the opposite direction. With respect to the macroeconomic variables, the expectation is that life satisfaction would vary directly with GDP per capita, and inversely with both the unemployment and inflation rates. In what follows, the bivariate OLS regression relationship between life satisfaction and each of the six variables is first examined and then the multivariate relationships.
Improving Participation and Quality of Life through Occupation
Lifestyle Modifications
Work and Hidradenitis Suppurativa
A key part of life satisfaction is derived from pursuing a worthwhile occupation. This can be a challenge for individuals with HS, as they have pain and associated loss of mobility, malodorous drainage, embarrassment, and low self-esteem. Patients often report that, due to flares and pain, they are unable to go to work and may even lose their jobs due to numerous sick days. Just over 58% of patients with HS miss work, and patients missed an average of 33.6 days from work. 59 However, another study showed that patients with HS missed less work days than controls. 60 The unemployment rate of adult HS patients eligible for a job was 25.1%, compared with 6.2% for the general population in Denmark. 61 Unemployed patients more commonly suffer from extensive axillary and mammary involvement and score higher on the Dermatology Life Quality Index (DLQI). 62 No data are available on the reason for unemployment; this may be due to pain and psychological impacts or the burden of disease, which may prevent patients from undertaking education, thus diminishing employment options.
Individuals with HS should consider career options carefully, with an understanding of common triggers and the potential need for accommodations in the workplace. Hot, humid work environments should be avoided, as heat and sweat are common HS triggers. Additionally, pressure and occlusion as experienced in many jobs from sitting may be modified with a standing desk/work setting. Appropriate consultation with a career counseling professional is recommended.
Does Happiness Change? Evidence from Longitudinal Studies
Understanding Change through Stability Coefficients
A common approach to studying whether life satisfaction can change is to study stability of individual differences in life satisfaction. This approach can inform us about the extent to which rank-ordering between individuals is preserved over time. For example, if Samantha was happier than Jonathan when they were kids, will she still be happier in adulthood? Traditionally, questions such as this one are studied by examining test–retest correlations of life satisfaction over time. Higher retest correlations would indicate that rank-order was preserved to a greater degree than lower correlations. In turn, these high retest correlations would suggest that happiness does not change much, at least over the time period being studied.
Early studies on stability of individual differences in life satisfaction were almost exclusively based on two-wave designs. Moreover, they generally examined correlations over relatively short retest intervals—weeks, months, at best up to a few years (e.g., Pavot & Diener, 1993 ). Information from these studies can tell us about the extent to which individual differences are preserved over such time periods. However, they do not allow for broad conclusions about stability over time because two-wave retest correlations obscure influences of different factors on life satisfaction, some of which lead to stability and some of which lead to change ( Conley, 1984; Fraley & Roberts, 2005 ). This leads to difficulties in interpreting two-wave retest correlations in the context of stability.
Personality and Life Outcomes
Schimmack et al. assessed personality and life satisfaction in people from two relatively individualist countries (the USA and Germany) and in people from three relatively collectivist countries (Japan, Ghana, and Mexico). Their results showed that within all five countries, people who were higher in Extraversion and Emotional Stability tended to report more satisfaction with life. (This relation was due to the fact that these persons generally experienced positive emotions much more than negative emotions, a situation that usually makes people feel satisfied with their lives.) However, the link between personality and life satisfaction was somewhat stronger in the individualist countries than in the collectivist countries.
National Panel Studies Show Substantial Minorities Recording Long-Term Change in Life Satisfaction
The Dependent/Outcome Variable: Life Satisfaction
In the German and Australian panels, life satisfaction is measured on a 0–10 scale (German mean=7.0, standard deviation=1.8; Australian mean=7.8, SD=1.5). A response of 0 means “totally dissatisfied,” and 10 means “totally satisfied.” In Britain, a 1–7 scale is used (mean=5.2, SD=1.2).
Single-item measures of life satisfaction are plainly not as reliable or valid as multi-item measures, but are widely used in international surveys and have been reviewed as acceptably reliable and valid ( Diener, Suh, Lucas, & Smith, 1999; Lucas & Donnellan, 2007 ).
life satisfaction index
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H-INDEX
Translation, Cultural Adaptation, and Psychometric Properties of the Life Satisfaction Index for the Third Age—Short Form (LSITA-SF12) for Use among Ethiopian Elders
Translation, Cultural Adaptation, and Psychometric Properties of the Life Satisfaction Index for the Third Age—Short Form (LSITA-SF12) for Use among Ethiopian Elders(1) Background: Self-reported measures play a crucial role in research, clinical practice, and health assessment. Instruments used to assess life satisfaction need validation to ensure that they measure what they are intended to detect true variations over time. An adapted instrument measuring life satisfaction for use among Ethiopian elders was lacking; therefore, this study aimed to culturally adapt and evaluate the psychometric properties of the Life Satisfaction Index for the Third Age—Short Form (LSITA-SF12) in Ethiopia. (2) Methods: Elderly people (n = 130) in Metropolitan cities of northwestern Ethiopia answered the LSITA-SF12 in the Amharic language. Selected reliability and validity tests were examined. (3) Result: The scale had an acceptable limit of content validity index, internal consistency, test-retest, inter-rater reliabilities, and concurrent and discriminant validities. (4) Conclusion: The Amharic language version of LSITA-SF12 appeared to be valid and reliable measures and can be recommended for use in research and clinical purposes among Amharic-speaking Ethiopian elders.
The structure of studentsʼ subjective well-being
Introduction. Subjective well-being is one of the indicators of success and a basis of person`s socio-psychological adjustment to uncertain situations and unstable social relations. The complexity of this phenomenon requires clarifying its structure. Aim. To determine the structure of studentsʼ subjective well-being. Methods. Cognitive Features of Subjective Well-Being (KOSB-4) (O. Kaliuk, O. Savchenko), Subjective Well-Being Scale (A. Perrudet-Badoux, G. Mendelsohn, J. Chiche, adapted by M. Sokolova), Life Satisfaction Index A, LSIA (B.L. Neugarten, adapted by N. Panina), Arousability and Optimism Scale, AOS (I.S. Schuller, A.L. Comunian, adapted by N. Vodopyanova). The methodological basis is a structural-functional approach. Factor and correlation analyses were done using «STATISTICA 10.0». Results. Empirical verification of the author’s model of subjective well-being revealed the existence of three independent components in its structure (cognitive-behavioral, emotional, and contrasting). Conclusions. Students’ cognitive and behavioral aspects of well-being are not separated, they form a single factor. There is a polarity in well-being in the form of positive and negative factors.
Psychometric Properties of the Health Literacy Scale Used in the Taiwan Longitudinal Study on Middle-Aged and Older People
Health literacy, an important factor in public and personal health, is regarded as the core of patient-centered care. Older people with high health literacy are more likely to maintain a healthier lifestyle, with good control and management of chronic diseases, than those lacking or with poor health literacy. Purpose: The present study investigated the validity and reliability of the Taiwan Longitudinal Study on Aging (TLSA) Health Literacy Scale. We also evaluated the health literacy of middle-aged and older Taiwanese adults, and its probable association with health outcomes and life satisfaction. Method: We analyzed the internal consistency reliability of the nine items of the 2015 TLSA Health Literacy Scale, and their relationship with the demographic variables. Brody Instrumental Activities of Daily Living (IADL) and the Life Satisfaction Index were used for criterion validity. Moreover, exploratory factor analysis was used to examine the construct validity and to test the known-group validity. Results: The TLSA health literacy scale has good internal consistency reliability. Criterion-related validity was supported by the fact that the health literacy score was significantly correlated with the IADL and Life Satisfaction Index. Factor analysis indicated a three-factor structure. Known-group validity was supported by the results, showing that middle-aged and older people with good self-reported health status had better health literacy. Conclusions: The TLSA health literacy scale is a reliable and valid instrument for measuring health literacy in middle-aged and older people.
Standardization of Elderly Life Satisfaction Index (LSIA)
Item-Level Psychometric Properties of the Life Satisfaction Index–Z
Abstract Date Presented Accepted for AOTA INSPIRE 2021 but unable to be presented due to online event limitations. The purpose of this study was to analyze the Life Satisfaction Index–Z (LSI–Z) and provide its item-level psychometric properties. Although the LSI–Z consists of two separate unidimensional and valid subscales, it demonstrated poor precision. Therefore, OT should be aware of this critical measurement issue when using this instrument in their clinical settings and must be interpreted the test scores with some caution. Primary Author and Speaker: Heesu Choi Additional Authors and Speakers: Nam Sanghun, Ickpyo Hong
The Life Satisfaction Index-A (LSI-A): Normative Data for a General Swedish Population Aged 60 to 93 Years
Perbedaan Tingkat Kepuasan Hidup Ibu Bekerja dan Ibu Rumah Tangga
Kepuasan hidup dapat dirasakan oleh semua orang, termasuk kaum ibu. Peran seorang ibu dapat dibedakan menjadi ibu bekerja dan ibu rumah tangga. Perbedaan peran tersebut dapat mempengaruhi tingkat kepuasan hidup. Penelitian ini bertujuan untuk mengetahui perbedaan tingkat kepuasan hidup ibu bekerja dan ibu rumah tangga pada Ibu PKK Desa Kaligung Kecamatan Blimbingsari Kabupaten Banyuwangi. Jenis penelitian ini adalah penelitian deskriptif. Sampel yang digunakan dalam penelitian ini yaitu 35 orang. Penelitian ini dilakukan pada Ibu PKK di Desa Kaligung, Banyuwangi. Instrumen yang digunakan dalam penelitian ini yaitu kuesioner Life Satisfaction Index. Berdasarkan hasil penyebaran kuesioner didapatkan hasil bahwa nilai rata-rata ibu bekerja sebesar 1.64 sedangkan nilai rata-rata ibu rumah tangga sebesar 1.67. Artinya, tingkat kepuasan hidup pada kelompok ibu rumah tangga lebih tinggi dibandingkan tingkat kepuasan hidup pada kelompok ibu bekerja. Hasil penelitian ini dapat digunakan sebagai dasar pengambilan keputusan perencanaan program terkait upaya peningkatan dukungan keluarga bagi seorang ibu agar lebih dapat meningkatkan kepuasan hidupnya.
The Satisfaction of Small Russian Cities’ Residents with the Quality of Their Lives: A Case Study of Perm Krai
The problem of population satisfaction with the quality of life is considered. The subjective perception by a person of the quality of his life is an important internal factor that affects his social well-being, satisfaction with his position, prospects, and individual spheres of society. Improving the quality of life of the population is one of the primary tasks of the authorities. Therefore, the analysis of the population’s assessment of the quality of certain aspects of their lives is important for federal and local authorities to determine priority areas of social policy, develop strategies and work plans of state institutions of various departments, etc. The article presents the results of a comparative study of differences in the subjective perception of various indicators of quality of life and satisfaction with various areas of life of people of different age groups. N.V. Panina’s “Life Satisfaction Index”, I. Karler’s technique to study the degree of satisfaction with one’s functioning in various fields, the Russified version of “MOS SF-36” for assessing the quality of life were used as research tools. The study was conducted in the cities of the Upper Kama region (the north of Perm Krai). The sample size was 600 people. Respondents are representatives of three age groups. Men and women are in equal proportions. Group distribution was carried out on the basis of the age classification proposed by the Institute of Age Physiology of the Academy of Pedagogical Sciences of the USSR: adolescence (17- to 21-year-olds); maturity (middle age (36- to 55-year-olds); elderly age (56-to 75-year-olds). Groups were equalized in quantitative composition. It has been revealed that among the residents of small regional cities, regardless of age, the general level of satisfaction with the quality of life is at an average level, among older people there is a tendency to a lower level. Life satisfaction and quality of life indicators decline with age. There are no statistically significant differences in the general life satisfaction index for people of different age groups. However, some indicators of quality of life revealed significant differences. In each age group, there is a certain resource sphere of life, the successful functioning of which is the basis of satisfaction, stability, and success. It is a marital relationship for the elderly, a professional sphere for middle-aged people, a social sphere for young people. The data obtained can help to define the priorities of social policy in regions, can be used in the development of socially-oriented technologies and programs aimed at improving of the living conditions of people.
Manifestations of the viability (resilience) of parents raising children with disabilities
The paper presents the results of an empirical study of the viability, hardiness and life satisfaction index of parents raising children with disabilities in Khabarovsk city, Russian Federation. According to the results of the study, parents who raise children with disabilities show deteriorated performance on all tests. As a result of the analysis on the viability tests and the “life satisfaction index”, statistically significant differences were revealed between the two groups of the sample; on the hardiness test, such differences were shown only on one of the scales. It was found that viability for parents of children with disabilities is not a full resource. The study confirmed the key role of the indicator “meaningfulness of life” as a “vertical” factor of viability. According to the data obtained using the “Life satisfaction index” test, the most powerful influence on the value of the life satisfaction index of parents raising children with disabilities is provided by indicators of consistency between goals set and achieved and the general mood background. In addition, these indicators also strongly correlate with each other. The results of the study showed that both groups of parents who participated in the study demonstrated sufficient ability to withstand a stressful situation. Parents raising children with disabilities have a low value of the indicator “control” as an emotional and volitional element of the scale.
Multifactorial Model Of Attitudes Towards Appearance: Empirical Investigations
This study is focusing on interrelations between attitudes towards Appearance (AP), value functional significance of AP, and life satisfaction. The study is aimed at gaining a theoretical foundation of the developed Multifactorial Model of Attitudes towards AP as well as at empirical testing of the interrelations between the single factors of the model and their combined influence on life satisfaction. It is hypothesised that a different combination of the single factors of the Multifactorial Model of Attitudes towards AP has a different impact on life satisfaction. The participants were 86 females and 86 males aged between 17 and 25 years. The inventory “Diagnostics of Real Structure of Personality Value Orientations” (Bubnova, 1999) the questionnaires “Significance of AP in Various Life Situations” (Labunskaya & Serikov, 2018), Attitudes towards AP, Satisfaction and Concern” (Labunskaya & Kapitanova, 2016), the AP Perfectionism Scale (APPS) (Srivastava, 2009) and the Life Satisfaction Index developed by Neugarten and adopted by N. V. Panina (1993) were administered. The factorial analysis revealed two types of interrelations that relate to different components of the developed Multifactorial Model of Attitudes towards AP. The results showed that considering AP as a value, attributing of higher significance to AP in various interaction contexts as well as higher AP perfectionism lead to lower life satisfaction.
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Comparative Study of the Effects of Tai Chi and Square Dance on Immune Function, Physical Health, and Life Satisfaction in Urban Empty-Nest Older Adults
Objective: To compare the effects of Tai Chi and Square dance on immune function, physical health, and life satisfaction in urban, empty-nest older adults.
Methods: This cross-sectional study included 249 older adults (60–69 years) who were categorized into Tai Chi (n = 81), Square dance (n = 90), and control groups (n = 78). We evaluated immunoglobulin G (IgG) and interleukin-2 (IL-2) levels by enzyme-linked immunosorbent assay (ELISA), natural killer (NK) cell cytotoxicity by MTT assay, physical health indices by physical fitness levels, and life satisfaction by Life Satisfaction Index A (LSIA) scores.
Results: Immune function, physical health, and life satisfaction in older adults in the Tai Chi and Square dance groups were significantly better than those in the control group (P 0.05). Further, there was a significant correlation between LSIA scores and immune function (r = 0.50, P = 0.00) and physical health (r = 0.64, P = 0.00).
Conclusion: (1) Both Tai Chi and square dance practitioners had better health outcomes, compared with sedentary individuals; (2) Tai Chi practitioners had better physical health and immune function than Square dance practitioners. (3) Tai Chi and Square dance exercises had similar effects on life satisfaction among urban empty-nest older adults.
Suggestions: For urban empty-nest older adults who want to have better physical health and immune function, long-term Tai Chi exercise may be a better choice; however, those who are concerned about life satisfaction can choose either Tai Chi or Square dance exercise.
Introduction
Due to market reform, economic restructuring, the miniaturization of the family structure, and population aging in China, approximately 50% of the older adults in China are currently empty nesters (Zhen, 2016); it is estimated that by 2030, the proportion will reach 90% (Wang G. et al., 2017). Compared with regular older adults, empty nesters constitute a special group of older adults who are prone to suffering from “empty nest syndrome,” which is characterized by a series of psychological disorders, such as feelings of loneliness, emptiness, and depression, which adversely affect their mental health (Guo and Sun, 2018). Mental health not only contributes considerably to life satisfaction but also to immune function. For example, physical and mental health potentially influence life satisfaction in older adults (Pinto et al., 2016; Lombardo et al., 2018), and psychoneuroimmunology studies have indicated that thoughts, emotional patterns, and psychological dynamics are strongly interrelated with immune response (Vasile, 2020). Another research has demonstrated a positive correlation of increased job satisfaction with natural killer (NK) cell number and plasma immunoglobulin G (IgG) concentration (Nakata et al., 2013) as well as a significant relationship between mental resilience, perceived immune function, and health (Van Schrojenstein Lantman et al., 2017).
Hence, life satisfaction is an important psychological factor reflecting the mental health and quality of life of older empty nesters (Zou and Yang, 2017), and it is an abstract and synthetic concept, which involves spiritual, physical, and social factors of individuals in daily life (Holmes and Dickerson, 1987). Since feelings of loneliness, depression, and emptiness, among others, are common in older empty nesters and are associated with adverse health consequences from both mental and immune health perspectives, an intensified focus on introducing more effective intervention strategies targeted at mitigating these feelings, is imperative. It is also important to improve their mental health, immune function, and life satisfaction.
Currently, non-pharmacological strategies, such as exercise, are becoming more popular because of their multifunctional effects and the uncertain efficacy and possible side effects of pharmacological strategies. To date, several kinds of fitness programs, such as Tai Chi and Square dance exercises, have been adopted by the older population in China. Tai Chi exercise is a traditional Chinese physical exercise characterized by meditation and low-to-moderate intensity activity, and it is practiced worldwide by older adults. In addition to improving muscle strength (Manson et al., 2013b; Wehner et al., 2021), balance (Wehner et al., 2021), body mass index (Manson et al., 2013a,b), and systolic blood pressure (SBP) (Manson et al., 2013a), research has also found Tai Chi exercise to have favorable effects on immunity (Yeh et al., 2006; Ho et al., 2013)as well as physical and mental health in older adults (Holly and Helen, 2012; Zheng et al., 2017). Square dance is considered an expansion of line dancing and was introduced in 2004, to China (Li, 2011). Public places where dance sessions are usually conducted consist of music, companions, and leader(s); further, because it is easy to learn and it produces a cheerful atmosphere, Square dance is significantly popular among middle-aged and older Chinese adults, especially among older women. Research has revealed the positive effects of Square dance on depressive symptoms and quality of life-related mental well-being (Wang et al., 2020), physical health and psychological mood (Sun and Wang, 2020), and immunity (Pei et al., 2013) in older adults. To the best of our knowledge, only a few studies have investigated the effectiveness of Square dance, and no study has comparatively evaluated the effects of Tai Chi and Square dance on mental health and immune function in the older population. Research on the differences in effect on mental health and immune function between Tai Chi and Square dance may offer positive guidance to older adults in selecting an appropriate exercise program.
The purpose of this study was to compare the effects of Tai Chi and Square dance exercises on immunity and life satisfaction in empty-nest older adults. We also aimed to evaluate the effects of these exercise on other physical health indicators, including waist-to-hip ratio, SBP, diastolic blood pressure (DBP), vital capacity, resting pulse, and balance. We hypothesized that (1) both Tai Chi and Square dance exercises can have better effect on immunity, physical health, and life satisfaction in empty-nest older adults, (2) Tai Chi exercise has more better effect than Square dance on all the aforementioned indicators in empty-nest older adults, and (3) a significant correlation exists between these indicators.
Materials and Methods
Study Population
In this cross-sectional study, 249 empty-nest older adults aged 60–69 years were recruited and categorized into Tai Chi (n = 81, female/male [F/M] = 61/20), Square dance (n = 90, F/M = 65/25), and control group (n = 78, F/M = 60/18). In the Tai Chi and Square dance groups, empty-nest older adults were recruited by cluster sampling and those in the control group with the help of communities. The inclusion criteria for empty-nest older adults in the Tai Chi and Square dance groups were as follows: (1) empty-nest older adults: those without offspring or whose offspring lived in other places; (2) aged 60–69 years; (3) unlimited by gender; (4) engagement in regular exercise for at least 2 years, no less than 120 min/week, and more than 3 times/week; (5) no obvious diseases, such as neurological, cardiovascular, psychiatric, and/or metabolic disease prior to the exercise. The control participants are sedentary due to our choice, because the subjects in Tai Chi or Square dance group only do regular Tai Chi or Square dance exercise, so subjects are sedentary in control group is one of our inclusion criteria.
A sedentary lifestyle was defined as not having participated in exercise for more than once per week for the last year (Audette et al., 2006). All the eligible literate participants provided written informed consent, and for the illiterate ones, the consent statement was read out and signed by the researcher after obtaining their permission. The study’s protocol was approved by Ethics Committee of Wenzhou University (WZU-083).
Exercise
Tai Chi and Square dance sessions are in the form of a self-organized clubs. Each club has a chief organizer who is responsible for its leadership. Music is being played during exercise. Tai Chi exercises are conducted in the morning (6:00–7:10 a.m.) and Square dance in the evening (7:00–8:10 p.m.), with the exercise venue being a park or square.
Measures
Physical Health
Waist-to-Hip Ratio
Waist-to-hip ratio (WHR) is the ratio of the circumference of the waist to that of the hips. We employed measurement methods used by previous researchers (Yang et al., 2017). Waist circumference was measured at a level midway between the lowest rib and the iliac crest using a measuring tape, and hip circumference was measured using the same tape at the widest position of the buttocks, with the tape along a plane parallel to the floor and not compressing the skin, after inhalation and exhalation. Waist and hip circumferences were measured three times for each participant and were accurate to the nearest 0.1 cm, with the average of the three measurements being used for further data analysis.
Blood Pressure and Resting Heart Rate
According to the American Heart Association’s standardized protocol (Perloff et al., 1993), we measured SBP, DBP, and resting heart rate (RHR) three times for each participant using an electronic sphygmomanometer (Omron HEM-7071A, Japan), after having them sit for at least 5 min. In cases where there was a difference of more than 5 mmHg or 5 beats/min, the two closest values were adopted (Wang P. et al., 2017). We encouraged participants to avoid alcohol, cigarette smoking, coffee, tea, and excessive exercise for at least 30 min prior to measuring their blood pressure and pulse rate (Wang et al., 2012).
Vital Capacity
Vital capacity (VC) is the maximum volume of air exhaled slowly and completely after trying to inhale, that is, VC (mL) = tidal volume + expiratory reserve volume + inspiratory reserve volume (Liu et al., 2017).
We measured VC using previously described methods (Huang et al., 2019). Briefly, VC was measured using a spirometer (Jianmin, GMCS-III type A, Xinheng Oriental Technology Development Co., Ltd, Beijing, China) according to the National Physical Health Test standard guidelines of China as per the following protocol: (1) in a standing position, take 1–2 deep breaths; (2) hold the Venturi handle (the pressure hose is above the Venturi); (3) shift the head slightly backward; (4) attempt to inhale deeply until one can no longer breathe in; and (5) subsequently exhale steadily into the mouthpiece for as long as possible until there is no air left. The maximum value was recorded after three acceptable maneuver attempts. The average of the three measurements was used for further data analysis.
One-Leg Standing With Eyes Closed
We used the method described in the National Physical Health Test standard guidelines of China. Briefly, upon the assessor’s command, participants were asked to lift the non-dominant leg off the ground and keep their dominant leg vertical; in this position, participants were asked to stand for as long as possible with the time measured to the nearest to 0.01 s using a stopwatch (JinQue, JD-3B, Shanghai Automation Instrument Co., Ltd.). Before the test measurement was conducted, participants practiced 3–5 trials in the same position as that used in the official measurement. The test was stopped when participants were no longer able to maintain the requirements of the test position.
Immune Function
Overnight fasting peripheral venous blood (2 mL) was collected by qualified nurses from all participants at approximately the same time (7:30 a.m.) in a vacuum tube (Cangzhou Yongkang Pharmaceutical Products Co., Ltd., China) for measurement of IgG, Interleukin-2 (IL-2) and NK cell cytotoxicity levels, and forbid exersing, drinking and coffee the night before last.
Immunoglobulin G and Interleukin-2
We measured IgG and IL-2 levels using previously reported methods (Meng et al., 2019). The blood samples were centrifuged at 10,000 r/min for 10 min; thereafter, we collected the serum to measure the concentrations of IgG and IL-2 using the commercial enzyme-linked immunosorbent assay (ELISA) kit according to the manufacturer’s protocol. Absorbance was measured using an ELISA reader (Bio-Rad, California, United States).
Natural Killer Cell Cytotoxicity
We used peripheral blood mononuclear cells (PBMCs) to assess NK cell cytotoxicity. PBMCs were isolated by density gradient centrifugation using Ficoll-Hypaque (Tianjin Haoyang Biological Manufacture Co., Ltd., China) according to the manufacturer’s operation manual. We performed the proliferation and cytotoxicity assays using freshly isolated PBMCs.
Natural Killer Cell Isolation and Purification
PBMCs in the middle cloud layer were extracted using density gradient centrifugation and washed twice using phosphate buffer solution (Wuhan Boster Biological Technology Co., Ltd.); To every 10 7 cells, 70 μL buffer was added for resuspension, followed by 20 μL CD56 magnetic bead antibody, and subsequently incubated at 2–8°C for 15 min; 1 mL buffer was added for uniform mixing, centrifuged at 300 r/min for 5 min, and subsequently resuspended in 500 μL buffer. The MS separation column was placed in a MiniMACS TM separation magnetic field (Miltenyi Biotec, German), and the column wall was wetted with 500 μL buffer before use; the collecting tube was set in place and the resuspended cells placed on the column, and the column was subsequently washed with 3 × 500 μL buffer. Finally, the separation column was separated from the magnetic field, placed on a new collection tube, and 1 mL buffer was promptly injected to flush down NK cells. NK cells were collected and cultured. A small number of NK cells were labeled with CD56-FITC to verify if the purity exceeded 95%.
Natural Killer Cell Culture
The NK cells’ density was adjusted to 2 × 10 5 /mL. Inoculation was performed in 96-well plates in the RPMI 1640 culture system containing 10% inactivated fetal bovine serum and IL-2 (100 U/mL) and cultured in a 5% CO2 incubator at 37°C.
Natural Killer Cytotoxicity Measurement
NK cells cultured for 48 h were effector cells (E), and K562 cells in the logarithmic growth phase were target cells (T), with E:T = 20:1. Simultaneously, three parallel multiple pores, namely, the target cell pore, effector cell pore, and medium blank control pore, were set up and cultured in a 5% CO2 incubator at 37°C for 12 h. CCK-8 (10 μL; Dojindo, Japan) was added to each well and recultured for 4 h. Absorbance (OD value) was determined using a microplate reader at 450 nm wavelength as previously described (Mehla et al., 2010), and the average value was used for further analysis. Cytotoxicity = (1– [OD value of effector pore of target cell—OD value of effector pore]/OD value of target cell) × 100%.
Life Satisfaction Index A
This scale includes 20 items, and each item has three options, namely, “agree,” “disagree,” and “uncertain.” The total score was the sum of each item, with a score range of 0–20 points; a higher score indicated a higher life satisfaction (Neugarten Bernice et al., 1961).
Data Analysis
Demographic Characteristics
There were 81, 90, and 78 participants in the Tai Chi, Square dance, and control groups, respectively, with average ages of 64.4 ± 2.2, 64.6 ± 2.3, and 64.5 ± 2.3 years, respectively. No significant differences were observed in demographic data across the three group, almost three quarters of the participants in the three groups were women. The majority of the participants in the Tai Chi and Square dance groups reported that they had not participated in other forms of regular exercise, except for occasional walking; the same was reported in the control group. No statistically significant differences in demographic variables were observed across the three groups or between Tai Chi and Square dance group (Table 1).
Table 1. Demographics of the participants in the three groups (n = 249).
Immunity of the Participants
Compared with the control group, Tai Chi and Square dance significantly improved IgG, IL-2, and NK cytotoxicity levels (p 0.05). Further, there were significantly different effects on immunity and physical health indicators as well as life satisfaction (p 0.05).
The reason underlying the different effects of the Tai Chi and Square dance exercises may be their unique characteristics. Tai Chi exercise integrates physical, psychosocial, spiritual, and behavioral components to promote mind-body interactions (Wang, 2011). It is a moderate-intensity exercise, as no more than 55% maximal oxygen intake is required (Wang et al., 2004), and it should be practiced in harmony with the Tai Chi philosophy by utilizing and manipulating Qi via Tai Chi exercise (Zheng et al., 2017). Qi is a very important concept in Chinese classical philosophy and medicine. It is not a body organ which can be anatomically identified by its location like the chakras of yoga (Cho et al., 2019). In Tai Chi exercise, it is emphasized that “Qi sinks into Dantian,” “Qi runs all over the body,” and “middle Qi passes through the top,” all of which is important to eliminate diseases and improve human function. Smooth flow of Qi makes the body comfortable, and stagnation makes the body sick. Although a deep understanding of the essence of Qi is still lacking, one can feel the existence of Qi while practicing Tai Chi exercise, as smooth flow of Qi improves fingertip numbness, distension, etc.
Square dance, which integrates Chinese style dancing and music with energetic and similar rhythms (Zhou, 2014), introduced in China around 2004 and considered an expansion of line dancing (Li, 2011), is just a medium-intensity exercise. Research shows that Tai Chi exercise has significantly better effect on cognitive function and emotion in older people than Square dance (Zhang et al., 2014), as well as better effect on enhancing lower extremity strength, balance, and flexibility than brisk walking (Audette et al., 2006). Davidson et al. (2003) directly found that an 8-week clinical training program in mindfulness meditation significantly increases the left-sided anterior activation and immune function, and that activated left-sided anterior of the brain was associated with enhanced NK-cell activity (Kang et al., 1991; Davidson et al., 1999). Irwin et al. (2003) confirmed that Tai Chi potentially increases varicella-zoster virus specific cell-mediated immunity in older adults and potentially improves T-helper cell function (Yeh et al., 2009). Tai Chi exercise, which focuses on producing inner calmness, would have both physical and psychological therapeutic value (Docker, 2006). Therefore, we have reason to believe that the comprehensive nature of Tai Chi exercise rendered it significantly superior to Square dance in improving physical health and immune function.
The mechanism underlying Tai Chi exercise’s ability to significantly increase immune function compared with Square dance may be related to a more pronounced increase in antibody titer, telomerase activity, reverse gene expression, reduced DNA damage, etc. Jacobs et al. (2011) found that meditation training could suppress immune cell aging because meditation can significantly increase immunocyte telomerase activity in normal people. Moreover, Goon et al. (2008) found that practicing Tai Chi exercise for 7 years provided a significantly effective DNA repair mechanism, reduced DNA damage, and increased lymphocyte apoptosis and proliferation in older adults; the upregulated lymphocyte apoptosis and proliferation with Tai Chi exercise may also be beneficial in preventing replicative senescence during aging. Our study also found Tai Chi exercise to be significantly effective in improving WHR (p Keywords : Tai Chi, Square dance, immune function, physical health, life satisfaction, empty nest elderly
Citation: Su Z and Zhao J (2021) Comparative Study of the Effects of Tai Chi and Square Dance on Immune Function, Physical Health, and Life Satisfaction in Urban Empty-Nest Older Adults. Front. Physiol. 12:721758. doi: 10.3389/fphys.2021.721758
Received: 09 July 2021; Accepted: 14 September 2021;
Published: 05 October 2021.
Mallikarjuna Korivi, Zhejiang Normal University, China
Siew Cheok Ng, University of Malaya, Malaysia
Yuewei Liu, Sun Yat-sen University, China
Copyright © 2021 Su and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: JieXiu Zhao, zhaojiexiu@ciss.cn
This article is part of the Research Topic
Nutritional and Physical Activity Strategies to Boost Immunity, Antioxidant Status and Health, Volume II
Happiness and Life Satisfaction
First published in 2013; substantive revision May 2017.
The French translation of this entry is here: Bonheur et satisfaction
How happy are people today? Were people happier in the past? How satisfied with their lives are people in different societies? And how do our living conditions affect all of this?
These are difficult questions to answer; but they are questions that undoubtedly matter for each of us personally. Indeed, today, life satisfaction and happiness are central research areas in the social sciences, including in ‘mainstream’ economics.
Social scientists often recommend that measures of subjective well-being should augment the usual measures of economic prosperity, such as GDP per capita. 1 But how can happiness be measured? Are there reliable comparisons of happiness across time and space that can give us clues regarding what makes people declare themselves ‘happy’?
In this entry, we discuss the data and empirical evidence that might answer these questions. Our focus here will be on survey-based measures of self-reported happiness and life satisfaction. Here is a preview of what the data reveals.
All our interactive charts on Happiness and Life Satisfaction
Happiness across the world today
The World Happiness Report is a well-known source of cross-country data and research on self-reported life satisfaction. The map here shows, country by country, the ‘happiness scores’ published this report.
The underlying source of the happiness scores in the World Happiness Report is the Gallup World Poll—a set of nationally representative surveys undertaken in more than 160 countries in over 140 languages. The main life evaluation question asked in the poll is: “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?” (Also known as the “Cantril Ladder”.)
The map plots the average answer that survey-respondents provided to this question in different countries. As with the steps of the ladder, values in the map range from 0 to 10.
There are large differences across countries. According to the most recent figures, European countries top the ranking: Finland, Denmark, Iceland, Switzerland and the Netherlands have the highest scores (all with averages above 7). In the same year, the lowest national scores correspond to Afghanistan, Lebanon, Zimbabwe, Rwanda and Botswana (all with average scores below 3.5).
You can click on any country on the map to plot time-series for specific countries.
As we can see, self-reported life satisfaction correlates with other measures of well-being—richer and healthier countries tend to have higher average happiness scores. (More on this in the section below.)
Click to open interactive version
Happiness over time
Findings from the World Value Survey
In addition to the Gallup World Poll (discussed above), the World Value Survey also provides cross-country data on self-reported life satisfaction. These are the longest available time series of cross-country happiness estimates that include non-European nations.
The World Value Survey collects data from a series of representative national surveys covering almost 100 countries, with the earliest estimates dating back to 1981. In these surveys, respondents are asked: “Taking all things together, would you say you are (i) Very happy, (ii) Rather happy, (iii) Not very happy or (iv) Not at all happy”. This visualization plots the share of people answering they are Very happy or Rather happy.
As we can see, in the majority of countries the trend is positive: In 49 of the 69 countries with data from two or more surveys, the most recent observation is higher than the earliest. In some cases, the improvement has been very large; in Zimbabwe, for example, the share of people who reported being ‘very happy’ or ‘rather happy’ went from 56.4% in 2004 to 82.1% in 2014.
Click to open interactive version
Findings from Eurobarometer
The Eurobarometer collects data on life satisfaction as part of their public opinion surveys. For several countries, these surveys have been conducted at least annually for more than 40 years. The visualization here shows the share of people who report being ‘very satisfied’ or ‘fairly satisfied’ with their standards of living, according to this source.
Two points are worth emphasizing. First, estimates of life satisfaction often fluctuate around trends. In France, for example, we can see that the overall trend in the period 1974-2016 is positive; yet there is a pattern of ups and downs. And second, despite temporary fluctuations, decade-long trends have been generally positive for most European countries.
In most cases, the share of people who say they are ‘very satisfied’ or ‘fairly satisfied’ with their life has gone up over the full survey period. 2 Yet there are some clear exceptions, of which Greece is the most notable example. Add Greece to the chart and you can see that in 2007, around 67% of the Greeks said they were satisfied with their life; but five years later, after the financial crisis struck, the corresponding figure was down to 32.4%. Despite recent improvements, Greeks today are on average much less satisfied with their lives than before the financial crisis. No other European country in this dataset has gone through a comparable negative shock.
Click to open interactive version
The distribution of life satisfaction
More than averages—the distribution of life satisfaction scores
Most of the studies comparing happiness and life satisfaction among countries focus on averages. However, distributional differences are also important.
Life satisfaction is often reported on a scale from 0 to 10, with 10 representing the highest possible level of satisfaction. This is the so-called ‘Cantril Ladder’. This visualization shows how responses are distributed across steps in this ladder. In each case, the height of bars is proportional to the fraction of answers at each score. Each differently-colored distribution refers to a world region; and for each region, we have overlaid the distribution for the entire world as a reference.
These plots show that in sub-Saharan Africa—the region with the lowest average scores–the distributions are consistently to the left of those in Europe. In economics lingo, we observe that the distribution of scores in European countries stochastically dominates the distribution in sub-Saharan Africa.
This means that the share of people who are ‘happy’ is lower in sub-Saharan Africa than in Western Europe, independently of which score in the ladder we use as a threshold to define ‘happy’. Similar comparisons can be made by contrasting other regions with high average scores (e.g. North America, Australia and New Zealand) against those with low average scores (e.g. South Asia).
Another important point to notice is that the distribution of self-reported life satisfaction in Latin America is high across the board—it is consistently to the right of other regions with roughly comparable income levels, such as Central and Eastern Europe.
This is part of a broader pattern: Latin American countries tend to have a higher subjective well-being than other countries with comparable levels of economic development. As we will see in the section on social environment, culture and history matter for self-reported life satisfaction.
If you are interested in data on country-level distributions of scores, the Pew Global Attitudes Survey provides such figures for more than 40 countries.
(Mis)perceptions about others’ happiness
We tend to underestimate the average happiness of people around us. The visualization shown demonstrates this for countries around the world, using data from Ipsos’ Perils of Perception—a cross-country survey asking people to guess what others in their country have answered to the happiness question in the World Value Survey.
The horizontal axis in this chart shows the actual share of people who said they are ‘Very Happy’ or ‘Rather Happy’ in the World Value Survey; the vertical axis shows the average guess of the same number (i.e. the average guess that respondents made of the share of people reporting to be ‘Very Happy’ or ‘Rather Happy’ in their country).
If respondents would have guessed the correct share, all observations would fall on the red 45-degree line. But as we can see, all countries are far below the 45-degree line. In other words, people in every country underestimated the self-reported happiness of others. The most extreme deviations are in Asia—South Koreans think that 24% of people report being happy, when in reality 90% do.
The highest guesses in this sample (Canada and Norway) are 60%—this is lower than the lowest actual value of self-reported happiness in any country in the sample (corresponding to Hungary at 69%).
Why do people get their guesses so wrong? It’s not as simple as brushing aside these numbers by saying they reflect differences in ‘actual’ vs. reported happiness.
One possible explanation is that people tend to misreport their own happiness, therefore the average guesses might be a correct indicator of true life satisfaction (and an incorrect indicator of reported life satisfaction). However, for this to be true, people would have to commonly misreport their own happiness while assuming that others do not misreport theirs.
And people are not bad at judging the well-being of other people who they know: There is substantial evidence showing that ratings of one’s happiness made by friends correlate with one’s happiness, and that people are generally good at evaluating emotions from simply watching facial expressions.
An alternative explanation is that this mismatch is grounded in the well-established fact that people tend to be positive about themselves, but negative about other people they don’t know.It has been observed in other contexts that people can be optimistic about their own future, while at the same time being deeply pessimistic about the future of their nation or the world. We discuss this phenomenon in more detail in our entry on optimism and pessimism, specifically in a section dedicated to individual optimism and social pessimism.
Differences in happiness within countries
East and West Germany
In global surveys of happiness and life satisfaction, Germany usually ranks high. However, these national averages mask large inequalities. In the map shown we focus on regional inequalities—specifically the gap in life satisfaction between West and East Germany.
This map plots self-reported life satisfaction in Germany (using the 0-10 Cantril Ladder question), aggregating averages scores at the level of Federal States. 3 What stands out is a clear divide between the East and the West, along the political division that existed before the reunification of Germany in 1990.
For example, the difference in levels between neighboring Schleswig-Holstein (in West Germany) and Mecklenburg-Vorpommern (in East Germany) are similar to the difference between Sweden and the US – a considerable contrast in self-reported life satisfaction.
Several academic studies have looked more closely at this ‘happiness gap’ in Germany using data from more detailed surveys, such as the German Socio-Economic Panel (e.g. Petrunyk and Pfeifer 2016). 4 These studies provide two main insights:
First, the gap is partly driven by differences in household income and employment. But this is not the only aspect; even after controlling for socioeconomic and demographic differences, the East-West gap remains significant.
Germany’s happiness gap over time
And second, the gap has been narrowing in recent years, as the chart shows. In fact, the finding that the gap is narrowing is true both for the raw average differences, as well as for the ‘conditional differences’ (i.e. the differences that are estimated after controlling for socioeconomic and demographic characteristics).
The observation that socioeconomic and demographic differences do not fully predict the observed East-West differences in self-reported happiness is related to a broader empirical phenomenon: Culture and history matter for self-reported life satisfaction—and in particular, ex-communist countries tend to have a lower subjective well-being than other countries with comparable levels of economic development.
Trends in life satisfaction for East and West Germany, 1992-2013
Happiness inequality
Happiness inequality in the US and other rich countries
The General Social Survey (GSS) in the US is a survey administered to a nationally representative sample of about 1,500 respondents each year since 1972, and is an important source of information on long-run trends of self-reported life satisfaction in the country. 5
Using this source, Stevenson and Wolfers (2008) 6 show that while the national average has remained broadly constant, inequality in happiness has fallen substantially in the US in recent decades.
The authors further note that this is true both when we think about inequality in terms of the dispersion of answers, and also when we think about inequality in terms of gaps between demographic groups. They note that two-thirds of the black-white happiness gap has been eroded (although today white Americans remain happier on average, even after controlling for differences in education and income), and the gender happiness gap has disappeared entirely (women used to be slightly happier than men, but they are becoming less happy, and today there is no statistical difference once we control for other characteristics). 7
The results from Stevenson and Wolfers are consistent with other studies looking at changes of happiness inequality (or life satisfaction inequality) over time. In particular, researchers have noted that there is a correlation between economic growth and reductions in happiness inequality—even when income inequality is increasing at the same time. The visualization here uses data from Clark, Fleche and Senik (2015) 8 shows this. It plots the evolution of happiness inequality within a selection of rich countries that experienced uninterrupted GDP growth.
In this chart, happiness inequality is measured by the dispersion — specifically the standard deviation — of answers in the World Value Survey. As we can see, there is a broad negative trend. In their paper the authors show that the trend is positive in countries with falling GDP.
Why could it be that happiness inequality falls with rising income inequality?
Clark, Fleche, and Senik argue that part of the reason is that the growth of national income allows for the greater provision of public goods, which in turn tighten the distribution of subjective well-being. This can still be consistent with growing income inequality, since public goods such as better health affect incomes and well-being differently.
Another possibility is that economic growth in rich countries has translated into a more diverse society in terms of cultural expressions (e.g. through the emergence of alternative lifestyles), which has allowed people to converge in happiness even if they diverge in incomes, tastes and consumption. Steven Quartz and Annette Asp explain this hypothesis in a New York Times article, discussing evidence from experimental psychology.
Click to open interactive version
The link between happiness and income
The link across countries
Higher national incomes go together with higher average life satisfaction
If we compare life satisfaction reports from around the world at any given point in time, we immediately see that countries with higher average national incomes tend to have higher average life satisfaction scores. In other words: People in richer countries tend to report higher life satisfaction than people in poorer countries. The scatter plot here shows this.
Each dot in the visualization represents one country. The vertical position of the dots shows national average self-reported life satisfaction in the Cantril Ladder (a scale ranging from 0-10 where 10 is the highest possible life satisfaction); while the horizontal position shows GDP per capita based on purchasing power parity (i.e. GDP per head after adjusting for inflation and cross-country price differences).
This correlation holds even if we control for other factors: Richer countries tend to have higher average self-reported life satisfaction than poorer countries that are comparable in terms of demographics and other measurable characteristics. You can read more about this in the World Happiness Report 2017, specifically the discussion in Chapter 2.
As we show below, income and happiness also tend to go together within countries and across time.
Click to open interactive version
The link within countries
Higher personal incomes go together with higher self-reported life satisfaction
Above we point out that richer countries tend to be happier than poorer countries. Here we show that the same tends to be true within countries: richer people within a country tend to be happier than poorer people in the same country. The visualisations here show us this this by looking at happiness by income quintiles.
Firstly we show each country in individual panels: within each panel is a connected scatter plot for a specific country. This means that for each country, we observe a line joining five points: each point marks the average income within an income quintile (horizontal axis) against the average self-reported life satisfaction of people at that income quintile (vertical axis).
What does this visualization tell us? We see that in all cases lines are upward sloping: people in higher income quintiles tend to have higher average life satisfaction. Yet in some countries the lines are steep and linear (e.g. in Costa Rica richer people are happier than poorer people across the whole income distribution); while in some countries the lines are less steep and non-linear (e.g. the richest group of people in the Dominican Republic is as happy as the second-richest group).
In a second visualization we present the same data, but instead of plotting each country separately, showing all countries in one grid.
The resulting connected scatter plot may be messy, resembling a ‘spaghetti’ chart, but it is helpful to confirm the overall pattern: despite kinks here and there, lines are by and large upward sloping.
Looking across and within countries
A snapshot of the correlation between income and happiness—between and within countries
Do income and happiness tend to go together? The visualization here shows that the answer to this question is yes, both within and across countries.
It may take a minute to wrap your head around this visualization, but once you do, you can see that it handily condenses the key information from the previous three charts into one.
To show the income-happiness correlation across countries, the chart plots the relationship between self-reported life satisfaction on the vertical axis and GDP per capita on the horizontal axis. Each country is an arrow on the grid, and the location of the arrow tells us the corresponding combination of average income and average happiness.
To show the income-happiness correlation within countries, each arrow has a slope corresponding to the correlation between household incomes and self-reported life satisfaction within that country. In other words: the slope of the arrow shows how strong the relationship between income and life satisfaction is within that country. (This chart gives you a visual example of how the arrows were constructed for each country). 9
If an arrow points northeast, that means richer people tend to report higher life satisfaction than poorer people in the same country. If an arrow is flat (i.e. points east), that means rich people are on average just as happy as poorer people in the same country.
As we can see, there is a very clear pattern: richer countries tend to be happier than poorer countries (observations are lined up around an upward-sloping trend), and richer people within countries tend to be happier than poorer people in the same countries (arrows are consistently pointing northeast).
It’s important to note that the horizontal axis is measured in a logarithmic scale. The cross-country relationship we would observe in a linear scale would be different, since at high national income levels, slightly higher national incomes are associated with a smaller increase in average happiness than at low levels of national incomes. In other words, the cross-country relationship between income and happiness is not linear on income (it is ‘log-linear’). We use the logarithmic scale to highlight two key facts: (i) at no point in the global income distribution is the relationship flat; and (ii) a doubling of the average income is associated with roughly the same increase in the reported life-satisfaction, irrespective of the position in the global distribution.
These findings have been explored in more detail in a number of recent academic studies. Importantly, the much-cited paper by Stevenson and Wolfers (2008) 10 shows that these correlations hold even after controlling for various country characteristics such as demographic composition of the population, and are robust to different sources of data and types of subjective well-being measures.
Economic growth and happiness
In the charts above we show that there is robust evidence of a strong correlation between income and happiness across and within countries at fixed points in time. Here we want to show that, while less strong, there is also a correlation between income and happiness across time. Or, put differently, as countries get richer, the population tends to report higher average life satisfaction.
The chart shown here uses data from the World Value Survey to plot the evolution of national average incomes and national average happiness over time. To be specific, this chart shows the share of people who say they are ‘very happy’ or ‘rather happy’ in the World Value Survey (vertical axis), against GDP per head (horizontal axis). Each country is drawn as a line joining first and last available observations across all survey waves. 11
As we can see, countries that experience economic growth also tend to experience happiness growth across waves in the World Value Survey. And this is a correlation that holds after controlling for other factors that also change over time (in this chart from Stevenson and Wolfers (2008) you can see how changes in GDP per capita compare to changes in life satisfaction after accounting for changes in demographic composition and other variables).
An important point to note here is that economic growth and happiness growth tend to go together on average. Some countries in some periods experience economic growth without increasing happiness. The experience of the US in recent decades is a case in point. These instances may seem paradoxical given the evidence—we explore this question in the following section.
The Easterlin Paradox
The observation that economic growth does not always go together with increasing life satisfaction was first made by Richard Easterlin in the 1970s. Since then, there has been much discussion over what came to be known as the ‘Easterlin Paradox’.
At the heart of the paradox was the fact that richer countries tend to have higher self-reported happiness, yet in some countries for which repeated surveys were available over the course of the 1970s, happiness was not increasing with rising national incomes. This combination of empirical findings was paradoxical because the cross-country evidence (countries with higher incomes tended to have higher self-reported happiness) did not, in some cases, fit the evidence over time (countries seemed not to get happier as national incomes increased).
Notably, Easterlin and other researchers relied on data from the US and Japan to support this seemingly perplexing observation. If we look closely at the data underpinning the trends in these two countries, however, these cases are not in fact paradoxical.
Let us begin with the case of Japan. There, the earliest available data on self-reported life satisfaction came from the so-called ‘Life in Nation surveys’, which date back to 1958. At first glance, this source suggests that mean life satisfaction remained flat over a period of spectacular economic growth (see for example this chart from Easterlin and Angelescu 2011). 12 Digging a bit deeper, however, we find that things are more complex.
Stevenson and Wolfers (2008) 13 show that the life satisfaction questions in the ‘Life in Nation surveys’ changed over time, making it difficult—if not impossible—to track changes in happiness over the full period. The visualization here splits the life satisfaction data from the surveys into sub-periods where the questions remained constant. As we can see, the data is not supportive of a paradox: the correlation between GDP and happiness growth in Japan is positive within comparable survey periods. The reason for the alleged paradox is in fact mismeasurement of how happiness changed over time.
In the US, the explanation is different, but can once again be traced to the underlying data. Specifically, if we look more closely at economic growth in the US over the recent decades, one fact looms large: growth has not benefitted the majority of people. Income inequality in the US is exceptionally high and has been on the rise in the last four decades, with incomes for the median household growing much more slowly than incomes for the top 10%. As a result, trends in aggregate life satisfaction should not be seen as paradoxical: the income and standard of living of the typical US citizen has not grown much in the last couple of decades. (You can read more about this in our entry on inequality and incomes across the distribution.)
Confirmatory Factor Analysis of the Life Satisfaction Index
Abstract
Factor models of the construct of well-being in later life have shown mixed results. Here we evaluated the factor structure of the Life Satisfaction Index A (LSIA), a widely used measure. Confirmatory factor analyses using a sample of community living aged people (N = 187) suggested that a unidimensional model was not appropriate for the scale. Moreover, only two of the 10 models previously proposed for the LSIA was found to fit reasonably well. These models (Bigot, 1974; Hoyt and Creech, 1983) consisted of only eight of the 20 LSIA items. Models which utilized all 20 LSIA items tended to fit poorly, whereas, those based on subsets of items generally showed improved fit. Allowing correlated factors also improved the fit. Throughout, fit indices were computed using the Satorra-Bentler scaled test statistic because the data were not normally distributed. These results highlight the importance of theory and construct development prior to actual scale development in social indicators research.
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Оценка жизненной удовлетворенности человека (тест ИЖУ)
Оценка жизненной удовлетворенности человека (тест ИЖУ)
Оценка жизненной удовлетворенности человека (тест ИЖУ)
Навигация (только номера заданий)
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Информация
Опросник «Индекс жизненной удовлетворенности» (Life Satisfaction Index A, LSIA) разработан группой американских ученых в 1961 году, русскоязычная адаптация сделана Н. В. Паниной в 1993 году. Методика предназначена для оценки удовлетворенностью жизнью, интегративного показателя, под которым понимается самое общее представление человека о психологическом комфорте.
Помимо интегрального показателя, опросник позволяет выделить и оценить 5 различных аспектов удовлетворенности жизнью.
Опросник состоит из 20 вопросов.
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Рубрики
Высокий индекс жизненной удовлетворенности.
Лица с высокими значениями индекса характеризуются низким уровнем эмоциональной напряженности, низким уровнем тревожности, высокой эмоциональной устойчивостью, высоким уровнем удовлетворенности ситуацией и своей ролью в ней.
Дополнительную информацию о том, какие конкретные сферы жизни приносят удовлетворение или недовольство, подскажут набранные баллы по шкалам (рубрикам). Чем выше балл по каждой шкале, тем более выражено это свойство (87.5-100% — высоко, 50-75% — средне, 0-37.5% — низко):
— интерес к жизни. Шкала отражает степень энтузиазма, увлеченного отношения к обычной повседневной жизни;
— общий фон настроения. Шкала показывает степень оптимизма, удовольствия от жизни;
— положительная оценка себя и собственных поступков. Сюда относится оценка человеком своих внешних и внутренних качеств. Высокий балл отражает высокую самооценку;
— последовательность в достижении целей. Высокие показатели по данной шкале отражают такие особенности отношения к жизни, как решительность, стойкость, направленные на достижение целей. Низкая оценка по этой шкале отражает пассивное примирение с жизненными неудачами, покорное принятие всего, что приносит жизнь;
— согласованность между поставленными и достигнутыми целями. Высокие показатели отражают убежденность человека в том, что он достиг или способен достичь тех целей, которые считает для себя важными.
Средний индекс жизненной удовлетворенности.
Лица со средними значениями индекса характеризуются достаточно низким уровнем эмоциональной напряженности, низким уровнем тревожности, достаточно высокой эмоциональной устойчивостью, высоким уровнем удовлетворенности ситуацией и своей ролью в ней.
Дополнительную информацию о том, какие конкретные сферы жизни приносят удовлетворение или недовольство, подскажут набранные баллы по шкалам (рубрикам). Чем выше балл по каждой шкале, тем более выражено это свойство (87.5-100% — высоко, 50-75% — средне, 0-37.5% — низко):
— интерес к жизни. Шкала отражает степень энтузиазма, увлеченного отношения к обычной повседневной жизни;
— общий фон настроения. Шкала показывает степень оптимизма, удовольствия от жизни;
— положительная оценка себя и собственных поступков. Сюда относится оценка человеком своих внешних и внутренних качеств. Высокий балл отражает высокую самооценку;
— последовательность в достижении целей. Высокие показатели по данной шкале отражают такие особенности отношения к жизни, как решительность, стойкость, направленные на достижение целей. Низкая оценка по этой шкале отражает пассивное примирение с жизненными неудачами, покорное принятие всего, что приносит жизнь;
— согласованность между поставленными и достигнутыми целями. Высокие показатели отражают убежденность человека в том, что он достиг или способен достичь тех целей, которые считает для себя важными.
Низкий индекс жизненной удовлетворенности.
Лица с низкими значениями индекса характеризуются высоким уровнем эмоциональной напряженности, высоким уровнем тревожности, низкой эмоциональной устойчивостью, низким уровнем удовлетворенности ситуацией и своей ролью в ней.
Дополнительную информацию о том, какие конкретные сферы жизни приносят удовлетворение или недовольство, подскажут набранные баллы по шкалам (рубрикам). Чем выше балл по каждой шкале, тем более выражено это свойство (87.5-100% — высоко, 50-75% — средне, 0-37.5% — низко):
— интерес к жизни. Шкала отражает степень энтузиазма, увлеченного отношения к обычной повседневной жизни;
— общий фон настроения. Шкала показывает степень оптимизма, удовольствия от жизни;
— положительная оценка себя и собственных поступков. Сюда относится оценка человеком своих внешних и внутренних качеств. Высокий балл отражает высокую самооценку;
— последовательность в достижении целей. Высокие показатели по данной шкале отражают такие особенности отношения к жизни, как решительность, стойкость, направленные на достижение целей. Низкая оценка по этой шкале отражает пассивное примирение с жизненными неудачами, покорное принятие всего, что приносит жизнь;
— согласованность между поставленными и достигнутыми целями. Высокие показатели отражают убежденность человека в том, что он достиг или способен достичь тех целей, которые считает для себя важными.
Confirmatory Factor Analysis of the Life Satisfaction Index
Abstract
Factor models of the construct of well-being in later life have shown mixed results. Here we evaluated the factor structure of the Life Satisfaction Index A (LSIA), a widely used measure. Confirmatory factor analyses using a sample of community living aged people (N = 187) suggested that a unidimensional model was not appropriate for the scale. Moreover, only two of the 10 models previously proposed for the LSIA was found to fit reasonably well. These models (Bigot, 1974; Hoyt and Creech, 1983) consisted of only eight of the 20 LSIA items. Models which utilized all 20 LSIA items tended to fit poorly, whereas, those based on subsets of items generally showed improved fit. Allowing correlated factors also improved the fit. Throughout, fit indices were computed using the Satorra-Bentler scaled test statistic because the data were not normally distributed. These results highlight the importance of theory and construct development prior to actual scale development in social indicators research.
This is a preview of subscription content, access via your institution.
Life Satisfaction Index A
Citation : Neugarten BL, Havighurst RJ, Tobin SS. The measurement of life satisfaction. J Gerontol 1961;16;134-143.
Main positive psychological well-being construct measured : Psychological well-being
Sub-constructs measured: N/A
Available subscales : N/A
Description : The Life Satisfaction Index A (LSIA) measures the psychological well-being in elderly, with dimensions such as zest for life, fortitude, congruence between desired and achieved goals, physical, psychological and social self-concept.
Number of items : 20
Example of statement/item : “I am just as happy as I was when I was younger”
Response options : 0 “Disagree”, 1 “Agree”
Total score : Items are summed, yielding a range from 0 to 20, with higher scores indicating greater levels of satisfaction.
Other forms available (and related citation):
A) Life Satisfaction Index for the Third Age (LSITA-SF); (Barrett, A. J., & Murk, P. J. (2009). Life Satisfaction Index for the Third Age (LSITA): A measurement of successful aging. https://scholarworks.iupui.edu/handle/1805/1160)
B) Life Satisfaction Index for the Third Age – Short Form (LSITA-SF); (Barrett, A. J., & Murk, P. J. (2009). Life Satisfaction Index for the Third Age – Short Form (LSITA-SF): An improved and briefer measure of successful aging. Paper presented at the Midwest Research-to-Practice Conference in Adult, Continuing, Community and Extension Education.)
Examples of studies:
1. Roos, N. P., & Havens, B. (1991). Predictors of successful aging: a twelve-year study of Manitoba elderly. Am J Public Health, 81(1), 63-68.
2. Collins, A. L., Glei, D. A., & Goldman, N. (2009). The role of life satisfaction and depressive symptoms in all-cause mortality. Psychol Aging, 24(3), 696-702.
3. Kimm, H., Sull, J. W., Gombojav, B., Yi, S. W., & Ohrr, H. (2012). Life satisfaction and mortality in elderly people: the Kangwha Cohort Study. BMC Public Health, 12, 54.
Confirmatory Factor Analysis of the Life Satisfaction Index
Abstract
Factor models of the construct of well-being in later life have shown mixed results. Here we evaluated the factor structure of the Life Satisfaction Index A (LSIA), a widely used measure. Confirmatory factor analyses using a sample of community living aged people (N = 187) suggested that a unidimensional model was not appropriate for the scale. Moreover, only two of the 10 models previously proposed for the LSIA was found to fit reasonably well. These models (Bigot, 1974; Hoyt and Creech, 1983) consisted of only eight of the 20 LSIA items. Models which utilized all 20 LSIA items tended to fit poorly, whereas, those based on subsets of items generally showed improved fit. Allowing correlated factors also improved the fit. Throughout, fit indices were computed using the Satorra-Bentler scaled test statistic because the data were not normally distributed. These results highlight the importance of theory and construct development prior to actual scale development in social indicators research.
This is a preview of subscription content, access via your institution.
Life satisfaction, fear of death, and ego identity in elderly adults
Abstract
Erikson’s eighth developmental stage, ego integrity vs. despair, was examined using the Life Satisfaction Index-A (LSIA) as a measure of ego integrity, the Death Anxiety Scale (DAS) as a measure of despair, and the Ego Identity Scale (EIS) as a measure of the successful resolution of the first six stages of psychosocial development. Three hypotheses were tested: (1) A positive correlation would exist for performance on the LSIA and the EIS, (2) a negative correlation would exist for performance on the DAS and on the LSIA, and (3) a negative correlation would exist for performance on the DAS and on the EIS. The subjects were 100 men and women 61-89 years of age. The first hypothesis was supported, and the second and third were supported with men but not with women.
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References
Adams, D. L. Analysis of a life satisfaction index. Journal of Gerontology, 1969, 24, 470–474.
Erikson, E. H. Childhood and society. New York: Norton, 1950.
Erikson, E. H. Identity and the life cycle: Selected papers. Psychological Issues, 1959, 1, 1–171.
Rasmussen, J. E. Relationship of ego identity to psychosocial effectiveness. Psychological Reports, 1964, 15, 815–825.
Templer, D. I. The construction and validation of a death anxiety scale. Journal of General Psychology, 1970, 82, 165–177.
Author information
Authors and Affiliations
Department of Psychology, University of Arkansas, Fayetteville, Arkansas, 72701
Nina Woods & Kenneth L. Witte
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Additional information
This article is based on a thesis submitted by the first author in partial fulfillment of the requirements for the MA degree at the University of Arkansas.
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Cite this article
Woods, N., Witte, K.L. Life satisfaction, fear of death, and ego identity in elderly adults. Bull. Psychon. Soc. 18, 165–168 (1981). https://doi.org/10.3758/BF03333593
Received : 12 August 1981
Published : 05 November 2013
Issue Date : October 1981
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Life satisfaction, fear of death, and ego identity in elderly adults
Abstract
Erikson’s eighth developmental stage, ego integrity vs. despair, was examined using the Life Satisfaction Index-A (LSIA) as a measure of ego integrity, the Death Anxiety Scale (DAS) as a measure of despair, and the Ego Identity Scale (EIS) as a measure of the successful resolution of the first six stages of psychosocial development. Three hypotheses were tested: (1) A positive correlation would exist for performance on the LSIA and the EIS, (2) a negative correlation would exist for performance on the DAS and on the LSIA, and (3) a negative correlation would exist for performance on the DAS and on the EIS. The subjects were 100 men and women 61-89 years of age. The first hypothesis was supported, and the second and third were supported with men but not with women.
Download to read the full article text
References
Adams, D. L. Analysis of a life satisfaction index. Journal of Gerontology, 1969, 24, 470–474.
Erikson, E. H. Childhood and society. New York: Norton, 1950.
Erikson, E. H. Identity and the life cycle: Selected papers. Psychological Issues, 1959, 1, 1–171.
Rasmussen, J. E. Relationship of ego identity to psychosocial effectiveness. Psychological Reports, 1964, 15, 815–825.
Templer, D. I. The construction and validation of a death anxiety scale. Journal of General Psychology, 1970, 82, 165–177.
Author information
Authors and Affiliations
Department of Psychology, University of Arkansas, Fayetteville, Arkansas, 72701
Nina Woods & Kenneth L. Witte
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
Additional information
This article is based on a thesis submitted by the first author in partial fulfillment of the requirements for the MA degree at the University of Arkansas.
Rights and permissions
About this article
Cite this article
Woods, N., Witte, K.L. Life satisfaction, fear of death, and ego identity in elderly adults. Bull. Psychon. Soc. 18, 165–168 (1981). https://doi.org/10.3758/BF03333593
Received : 12 August 1981
Published : 05 November 2013
Issue Date : October 1981
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Life Satisfaction Index – Z
Last Updated
Purpose
Life Satisfaction Index – Z is a 13-item subjective measure developed to assess well-being in the elderly population.
Link to Instrument
Area of Assessment
Assessment Type
Administration Mode
Actual Cost
Populations
Key Descriptions
Number of Items
Equipment Required
Time to Administer
Required Training
Age Ranges
Instrument Reviewers
Muna Bhattarai, MA, MNS, University of Wisconsin-Madison
Mirang Park, MS, University of Wisconsin-Madison
Susan Miller Smedema, Ph.D., CRC, LPC, University of Wisconsin-Madison
ICF Domain
Measurement Domain
Professional Association Recommendation
Considerations
Older Adults and Geriatric Care
Standard Error of Measurement (SEM)
Elderly population: (Baiyewu & Jegede, 1992; n = 945; mean satisfaction with life score = 18.26 (5.12), Nigerian Sample)
Calculated from standard deviation (Baiyewu & Jegede, 1992)
Minimal Detectable Change (MDC)
Elderly population: (Baiyewu & Jegede, 1992; n = 945; mean satisfaction with life score = 18.26 (5.12))
Calculated from standard deviation (Baiyewu & Jegede, 1992)
Normative Data
Older Adults: Stock, 1982, n=325, age = 73 (8.2)
Older Adults: Morgan, 1987, n=986)
Elderly population (Nigeria): (Baiyewu & Jegede, 1992; n = 945)
Internal Consistency
Elderly population: (Wood et al., 1969; n = 100)
Older Adults: Stock, 1982, n=325, age = 73 (8.2)
Older Adults: Morgan, 1987, n=986)
Elderly population (Nigeria): (Baiyewu & Jegede, 1992; n = 945)
Elderly (Iran): (Tagharrobi et al., 2011; n = 75)
Elderly with frailty and depression: (Abraham, 1992; n = 76)
Construct Validity
Elderly population: (Wood et al., 1969; n = 100)
Older Adults: Stock, 1982, n=325, age = 73 (8.2)
Older Adults: Morgan, 1987, n=986)
“LSI-Z scores were significantly different among the 5 known groups (p=0.0001, f=121.66); so, the known-groups approach revealed that this tool is valid” (Tagharrobi et al., 2011)
*Retrieved from abstract since the original article is in the Persian language.
Women in menopausal ages: (Dennerstein et al., 2002; n = 395)
Bibliography
Abraham, I. L. (1992). Longitudinal reliability of the life satisfaction index (short form) with nursing home residents: A cautionary note. Perceptual and Motor skills, 75(2), 665-666.
American Thoracic Society. (1999). Life satisfaction inventory. Retrieved from https://qol.thoracic.org/sections/instruments/ko/pages/lsia.html
Baiyewu, O. & Jegede, R. O. (1992). Life satisfaction in elderly Nigerians: Reliability and factor composition of the life satisfaction Index Z. Age and Ageing, 21(4), 256-261.
Dennerstein, L., Dudley, E., Guthrie, J., & Barrett-Connor, E. (2000). Life satisfaction, symptoms, and the menopausal transition. Medscape Women’s Health, 5(4), E4-E4.
Wood, V., Wylie, M. L., & Sheafor, B. (1969). An analysis of a short self-report measure of life satisfaction: Correlation with rater judgments. Journal of Gerontology, 24(4), 465-469.
Morgan K, Dallass HM, ArieT, ByneES, Jones R, Waite J. Mental health and psychological well being among the old and very old living at home. Br J Psychiatry 1987;150:801-7.
Stock, William A. PhD, Morris A. Okun, PhD, The Construct Validity of Life Satisfaction among the Elderly, Journal of Gerontology, Volume 37, Issue 5, September 1982, Pages 625–627, https://doi-org.ezproxy.galter.northwestern.edu/10.1093/geronj/37.5.625
More Instruments Like This
We have reviewed nearly 300 instruments for use with a number of diagnoses including stroke, spinal cord injury and traumatic brain injury among several others.
Life satisfaction, fear of death, and ego identity in elderly adults
Abstract
Erikson’s eighth developmental stage, ego integrity vs. despair, was examined using the Life Satisfaction Index-A (LSIA) as a measure of ego integrity, the Death Anxiety Scale (DAS) as a measure of despair, and the Ego Identity Scale (EIS) as a measure of the successful resolution of the first six stages of psychosocial development. Three hypotheses were tested: (1) A positive correlation would exist for performance on the LSIA and the EIS, (2) a negative correlation would exist for performance on the DAS and on the LSIA, and (3) a negative correlation would exist for performance on the DAS and on the EIS. The subjects were 100 men and women 61-89 years of age. The first hypothesis was supported, and the second and third were supported with men but not with women.
Download to read the full article text
References
Adams, D. L. Analysis of a life satisfaction index. Journal of Gerontology, 1969, 24, 470–474.
Erikson, E. H. Childhood and society. New York: Norton, 1950.
Erikson, E. H. Identity and the life cycle: Selected papers. Psychological Issues, 1959, 1, 1–171.
Rasmussen, J. E. Relationship of ego identity to psychosocial effectiveness. Psychological Reports, 1964, 15, 815–825.
Templer, D. I. The construction and validation of a death anxiety scale. Journal of General Psychology, 1970, 82, 165–177.
Author information
Authors and Affiliations
Department of Psychology, University of Arkansas, Fayetteville, Arkansas, 72701
Nina Woods & Kenneth L. Witte
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
Additional information
This article is based on a thesis submitted by the first author in partial fulfillment of the requirements for the MA degree at the University of Arkansas.
Rights and permissions
About this article
Cite this article
Woods, N., Witte, K.L. Life satisfaction, fear of death, and ego identity in elderly adults. Bull. Psychon. Soc. 18, 165–168 (1981). https://doi.org/10.3758/BF03333593
Received : 12 August 1981
Published : 05 November 2013
Issue Date : October 1981
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Satisfaction with Life Index
This chart shows the Satisfaction with Life Index by country.
Satisfaction with Life Index was created by Adrian G. White, an analytic social psychologist at the University of Leicester, using data from a metastudy.It is an attempt to show life satisfaction in different nations. In this calculation, subjective well being correlates most strongly with health wealth and access to basic education.This is an example of directly measuring happiness—asking people how happy they are—as an alternative to traditional measures of policy success such as GDP or GNP. Some studies suggest that happiness can be measured effectively.
This Index, however, is not solely based on directly asking «how people feel», but also on its social and economic development.
Life satisfaction is the way persons evaluate their lives and how they feel about where they are going in the future. It is a measure of well-being and may be assessed in terms of mood, satisfaction with relations with others and with achieved goals, self-concepts, and self-perceived ability to cope with daily life. It is having a favorable attitude of one’s life as a whole rather than an assessment of current feelings. Life satisfaction has been measured in relation to economic standing, amount of education, experiences, and residence, as well as many other topics.
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Build a linear regression based on OECD’s life satisfaction data and the IMF’s GDP per capita data.
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Build a linear regression based on OECD’s life satisfaction data and the IMF’s GDP per capita data.
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Build a linear regression based on OECD’s life satisfaction data and the IMF’s GDP per capita data.
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Life Satisfaction Index (LSI)
Neugarten‚ B.J.‚ Havighurst‚ R.J.‚ & Tobin‚ S.S. (1961). The Measurement of Life Satisfaction. Journal of Gerontology‚ 16‚ 134-143.
Wood‚ V.‚ Wylie‚ M.L.‚ & Sheafor‚ B. (1969). An Analysis of a Short Self-Report Measure of Life Satisfaction: Correlation With Rater Judgments. Journal of Gerontology‚ 24‚ 465-469.
Adams‚ D.L. (1969). Analysis of a Life Satisfaction Index. Journal of Gerontology‚ 24‚ 470-474.
Harris‚ L. (1975). The myth and reality of aging in America. Washington‚ DC: National Council on the Aging.
Helmes‚ E.‚ Goffin‚ R.D.‚ Chrisjohn‚ R.D. (1988). Confirmatory factor analysis of the Life Satisfaction Index. Soc Indicat Res‚ 45:371–390.
Abraham‚ I.L. (1992). Longitudinal reliability of the Life Satisfaction Index (short form) with nursing home residents: a cautionary note.Percept Mot Skills‚ 75:665–666.
Stock‚ W.A.‚ Okun‚ M.A.‚ Gómez‚ Benito. J. (1994). Subjective well-being measures: reliability and validity among Spanish elders. Int J Aging Hum Devel‚ 38:221–235.
Barrett‚ A.J.‚ & Murk‚ P.J. (2006). Life Satisfaction Index for the Third Age (LSITA): A Measurement of Successful Aging. In E. P. Isaac (Ed.)‚ Proceedings of the 2006 Midwest Research-to-Practice Conference in Adult‚ Continuing‚ and Community Education (pp. 7-12). St. Louis: University of Missouri-St. Louis.
McDowell‚ Ian. (2006). Measuring Health: A Guide to Rating Scales and Questionnaires‚ Third Edition. OXFORD UNIVERSITY PRESS
Satisfaction with Life Scale
The Satisfaction with Life Scale (SWLS)16 is a 5-item scale that uses a 7-point Likert scale response format.
Related terms:
Cleft and craniofacial orthognathic surgery
Outcomes, prognosis, and complications
Accurate assessment of orthognathic surgical outcomes is essential to maintaining safe practices, maximizing patient satisfaction, and effectively evaluating an ever-changing field. Indeed, this importance is echoed in the ways investigators have analyzed postoperative results. These range from measurement tools such as three-dimensional CT scanning and volumetric analyses (used to evaluate postoperative changes in bony and soft tissues immediately and over time) to questionnaires assessing patient-reported satisfaction scales and quality of life. While there is currently no universally accepted tool to demonstrate patient outcomes after orthognathic surgery accurately and reliably, with reasoned and reasonable expectations on the part of the patient, family, and surgeon alike, orthognathic surgery can result in high levels of satisfaction from both a functional and aesthetic level.
Of particular importance to the cleft and craniofacial population is the effect of orthognathic surgery on speech. It is generally accepted that the etiology of velopharyngeal insufficiency (VPI) in the cleft patient is due to the malalignment or shortening of the palatal musculature, as well as growth, development, and/or surgical sequelae that can lead to abnormal structural relationships. Given the intricate attachment of the muscular apparatus of the velum to the maxilla, it follows that movement of the maxilla can change the preoperative velopharyngeal function.
Other published studies have shown similar results or no change in VPI function following jaw surgery. In their study, Phillipset al. 8 showed that the extent of anteroposterior movement of the maxilla is unrelated to velopharyngeal deterioration and is not a useful predictor. In their study of 26 cleft patients (16 unilateral complete and 9 bilateral complete cleft lips and palates), Phillipset al. demonstrated that all patients with perceived hypernasal speech preoperatively had hypernasality after advancement. Furthermore, 9 of 12 patients who had preoperative nasopharyngoscopy showing borderline or inadequate VP closure developed postoperative VPI. Based on these results, Phillipset al. conclude that preoperative assessment can predict postoperative speech and velopharyngeal function.
Positive Psychological Tests and Measures
3.4.1 Psychometric Properties of the Satisfaction with Life Scale
The Satisfaction with Life Scale is reported to have very good internal consistency, with an alpha of 0.87 and excellent test–retest reliability, with a correlation of 0.82 across a two-month time period. Concurrent validity has been established for this measure as well, with scores on the Satisfaction with Life Scale correlating positively with scores on nine other measures of well-being and a self-esteem inventory. Negative correlations were also found between the Satisfaction with Life Scale and measures of neuroticism, emotionality, and a checklist of clinical symptoms ( Diener et al., 1985 ).
Measures of Life Satisfaction Across the Lifespan
Validity
Convergent/Concurrent
Divergent/Discriminant
The SWLS exhibited negative correlations with Bradburn’s (1969) measure of negative affect (r=−.32 to r=−.37). The SWLS also exhibited a non-significant relationship (r=.02) with the Marlowe–Crown scale ( Crowne & Marlowe, 1964 ), suggesting that SWLS scores are unrelated to a socially desirability response style (sample 2; Diener et al., 1985 ).
Construct/Factor Analytic
Factorial validity was estimated via a principal axis factor analysis of the item intercorrelations in sample 1 (N=176). A Cattell scree plot of eigenvalues ( Cattell, 1978 ) suggested that the five items of the SWLS formed a single factor ( Diener et al., 1985 ).
Criterion/Predictive
Quality of Life After Spinal Cord Injury
Global Measures
Although the Satisfaction with Life Scale (SWLS), 15 was developed for use in the general population, it has been used far more than any other global measure in SCI research. It defines life satisfaction as the global assessment of QOL on the basis of each individual’s uniquely selected criteria, which are appraised by a cognitive judgmental process. 50 Because life satisfaction is experienced globally, the SWLS approach to appraisal is to query respondents about their overall life experiences rather than about the various facets of life. The instrument has five questions; scores can range from 5 to 35.
Goodness-of-Fit Testing
Continuous Data
We model the responses of 438 US respondents to the five items of the satisfaction with life scale (SWLS). The items are rating scales with seven response alternatives and will be treated as continuous. A two-factor model where “In most ways my life is close to my ideal,” “The conditions of my life are excellent,” and “I am satisfied with my life,” are taken as indicators of the factor satisfaction with present life, the and “I am satisfied with my life,” “So far I have gotten the important things I want in life,” and “If I could live my life over, I would change almost nothing,” are taken as indicators of the factor of satisfaction with past life. The factors are correlated. Table 3 lists a number of GOF statistics obtained using the maximum-likelihood fitting function either under normality assumptions (NT) or under asymptotically distribution-free (ADF) assumptions.
| NT | ADF | ||||||
|---|---|---|---|---|---|---|---|
| Stat | Value | df | p | Stat | Value | df | p |
| T | 10.38 | 3 | 0.02 | TB | 8.72 | 3 | 0.03 |
| TB | 10.38 | 3 | 0.02 | TYB | 8.55 | 3 | 0.04 |
| TS | 7.17 | 3 | 0.04 | ||||
| Ta | 6.90 | 2.89 | 0.07 | ||||
The model does not fit very well, and there is not much difference between the results under NT or ADF assumptions. All statistics yield similar p-values. Inspection of the z-scores for the residual covariances reveals significant residual covariances among items from different factors. The magnitude of the residuals is not large, however. The average standardized residual is SRMSR = 0.015, and the largest standardized residual is 0.04. It appears that the model yields a close enough fit. Indeed, the RMSEA ( eqn. [15] obtained is 0.056, and the p-value for testing whether the population RMSEA is smaller than 0.05, is 0.35.
Redressing the balance: A systematic review of positive psychology in the intellectual disability literature
3.4 Positive psychology measures
| PP construct | Measure | Studies that used measure | Measure characteristics | Previously used with ID | Administration adaptations in included studies | ||
| Mode of administration | Item/subscale description | Response options/scoring | |||||
| Theme: Virtues and character strengths | |||||||
| Character strengths | Assessment Scale for Positive Character Traits—Developmental Disabilities ( Woodard, 2009 ) | Carter et al. (2015) and Woodard (2009) | Proxy-report | – | |||
26-item scale of 10 traits: courage, empathy, forgiveness, gratitude, humor, kindness, optimism, resilience, self-control, and self-efficacy
5-point Likert-type scale (from 1 = “Not at all characteristic” to 5 = “Extremely characteristic”)
Overall mean or sum
96-item scale of 24 strengths within six overarching virtues: wisdom, courage, humanity, justice, temperance, transcendence
5-point Likert-type scale (from 1 = “Very much like me” to 5 = “Very much unlike me”)
Mean score of each strength
25-item scale of participation frequency
Three subscales: home (10 items), school (5 items), and community (10 items)
8-point scale (from 1 = “Daily” to 8 = “Never”)
Subscale mean scores
12-item scale of agency (4 items) and pathway thinking (4 items) with 4 filler items
4-point Likert-type scale (anchors not reported)
Repetition/explanation of items when needed
6-item scale of agency (3 items) and pathways thinking (3 items)
6-point Likert-type scale (1 = “None of the time” to 5 = “All of the time”)
24-item scale of career adaptability
Four subscales: concern, control, curiosity, and confidence
5-point Likert-type scale (ranging from 1 = “Not strong” to 5 = “Strongest”)
Repetition/explanation of items when needed
40-item scale assessing locus of control
10-item scale of optimism (6 items) with 4 filler items
5-point Likert-type scale (anchors not reported)
31-item scale of elements of workplace culture (e.g., workers eating lunch together), and participation in elements
Yes/no response for individual participation
Calculate proportion of elements present in the workplace to individual participation
4-item scale of global happiness
7-point Likert-type scale (anchors vary by item)
Explanation of items when needed
16-item scale of job satisfaction
4-point Likert-type scale (1 = “Never” to 4 = “Always”)
Scoring procedure not reported
Questionnaire read aloud
Pictorial representation of response options (e.g., emoticon faces, bar charts)
Supplemental examples and appendices to support understanding
Adapted for individual need
5-item scale of global job satisfaction
5-point Likert-type scale (1 = “Totally agree” to 5 = “Totally disagree”)
Began interview with three test-items to check understanding, practice and ease
Simple words used. Ambiguous or complex phrasings avoided
Visual aids to clarify response scale
Choice for interview instead of self-report, possibility to elaborate
18-item scale of fulfillment of basic work-related psychological needs
Three subscales (6 items each): autonomy, relatedness, and competence
5-point Likert-type scale (1 = “Totally agree” to 5 = “Totally disagree”)
47-item scale of life satisfaction
One global domain (7 items) and five specific domains (7 items each): family, friends, school, living environment, and self
6-point Likert-type scale (anchors not reported)
5-item scale assessing global life satisfaction
7-point Likert-type scale (ranging from 1 = “Strongly disagree” to 7 = “Strongly agree”)
Overall mean or sum
Repetition/explanation when needed ( Rey et al., 2013 ; Santilli et al., 2014 )
Response options N/A (drawing task)
Presence of 30 emotional indictors in the drawings
5-item scale of subjective wellbeing in five domains: overall appraisal of happiness with life, confidence, sadness/worry, isolation, and helplessness
4-point Likert-type scale for first item (ranging from 1 = “Very happy” to 4 = “Mostly unhappy”)
Three response options for other four items: (1) “Never,” (2) “Sometimes,” (3) “A lot”
Each item analyzed as a separate indicator
Opportunity of being supported in interview by support person
Specific training for all interviewers (included trainers with ID)
Visual response cue cards
Amended question format
Encouraged interviewers to rephrase questions
Item and subscale description not reported
Response options and scoring procedure not reported
21-item scale of self-determination
Two subscales: opportunity (6 items) and capacity (15 items on two indices: “Things I do” (8 items) and “How I feel” (7 items))
5-point Likert-type scale (ranging from 1 = “Never” to 5 = “Always”)
Added three items to delineate between constructs in double-barreled items
Removed “Opportunities at home” index to reduce time demands
Visual aid for items and response scale
Five practice statements for training on Likert-type scales
Rephrased items into interrogative format to help comprehension
Alternated between the “What I do” and “How I feel” indexes to clarify difference between items
61-item scale of self-determination—Four subscales: autonomy (25 items), self-regulation (12 items), empowerment (14 items), self-realization (10 items)
Autonomy subscale: 3-point scale (ranging from 1 = “I never do” to 3 = “I always do”)
Remaining subscales: 4-point Likert-type scale (ranging from 1 = “Disagree strongly” to 4 = “Agree strongly”)
Scoring procedure not reported
Support with completing survey as needed
45-item scale of the essential characteristics of self-determined actions
Three domains and seven sub-domains: volitional action (13 items: autonomy [6 items], self-initiation [7 items]); agentic action (10 items: self-direction [6 items], pathways thinking [4 items]); action-control beliefs (22 items: control expectancy [9 items], psychological empowerment [7 items], self-realization [6 items])
Paper version: 5-point Likert-type scale (ranging from 1 = “Disagree” to 5 “Agree”)—Online version: 10-point slider bar (ranging from 0 = “I disagree” to 10 = “I agree,” with two-decimals precision)
Scoring procedure not reported
Sample questionnaires sent to teachers to identify students capable of understanding questions ( Mumbardó-Adam, Guàrdia-Olmos, Giné, Raley, & Shogren, 2018 ; Mumbardó-Adam, Guàrdia-Olmos, Giné, Shogren, & Vicente Sánchez, 2018 )
Provided more time ( Mumbardó-Adam, Guàrdia-Olmos, Giné, Shogren, & Vicente Sánchez, 2018 )
Additional support offered (e.g., reading questions)
6-item scale assessing positive youth development
5-point Likert-type scale (ranging from 1 = “Strongly disagree” to 5 = “Strongly agree”)
Notes. N/A = Not applicable.
With regards to measure characteristics, the majority (81.8%, n = 18) involved self-report. Three measures used proxy-report (two of which specifically included parent-report) and one measure was task-based (Human Figure Drawing; Koppitz, 2000 ). Four studies administered self-report measures using an interview format as an adaptation for working with individuals with intellectual disability. Measures varied greatly in length, ranging from 4 to 96 items (M = 25.2, SD = 23.4). Details regarding the original target population for which the measure was developed were provided for 81.8% of measures (n = 18; target population for four measures was not described). Most measures were originally developed for use with the general population (61.1%, n = 11), and of these, three were reported to have been used in previous research involving individuals with intellectual disability (previous use was reported for two other measures, but references were not provided); empirical evidence supporting validity of use with intellectual disability samples was provided for two measures. Only four measures (22.2%) were originally developed for use with individuals with intellectual disability, and an additional three (16.7%) were developed for use with people with or without disabilities (including intellectual disability). Adaptations to test structure (e.g., number of items), administration, and/or testing procedure were reported for 11 measures, four of which were measures originally developed for individuals without intellectual disability. Adaptations included: repetition or explanation of items when needed, reading questions aloud for participants, offering to scribe for participants, adding or eliminating items, using simplified or concrete language, allowing participants to be accompanied by a support person of their choice, and providing intellectual disability-specific training to interviewers.
Psychosocial Issues in Chronic Kidney Disease Patients
Mental Health Disparities
Fischer et al. 23 examined data from the Chronic Renal Insufficiency Cohort (CRIC) and Hispanic-CRIC (H-CRIC) studies. CRIC enrolled Hispanics and non-Hispanics at seven centers, and H-CRIC enrolled Hispanics at the University of Illinois. Twenty-seven percent of participants (n = 3853) had evidence of elevated depressive symptoms (greater than 11 on BDI). Only 31% of those with elevated depressive symptoms were taking antidepressants. They found a relationship between the prevalence of elevated depressive symptoms and level of kidney function. Decreased eGFR was associated with a greater risk for elevated depressive affect. In regression analyses, BDI score, Hispanic ethnicity, non-Hispanic Black race, and higher urine albumin levels were each associated with decreased odds of antidepressant use. Women had greater odds of antidepressant use.
Although more research on the mental health disparities within CKD are urgently needed, certain points are clear. 80 Elevated depressive symptoms are common in individuals with CKD. Individuals of racial and ethnic minority background and CKD have a substantial burden of elevated depressive symptoms. In general, depression treatment utilization is low and appears to be lower for men, Hispanics and Blacks.
Psychosocial Issues in Chronic Kidney Disease Patients
Mental Health Disparities
Fischer et al. 20 examined data from the Chronic Renal Insufficiency Cohort (CRIC) and Hispanic-CRIC (H-CRIC) studies. CRIC enrolled Hispanics and non-Hispanics at 7 centers, and H-CRIC enrolled Hispanics at the University of Illinois. Twenty-seven percent of participants (n=3853) had evidence of elevated depressive symptoms (greater than 11 on BDI). Only 31% of those with elevated depressive symptoms were taking antidepressants. They found a relationship between the prevalence of elevated depressive symptoms and level of kidney function. Decreased eGFR score was associated with a greater risk for elevated depressive affect. In regression analyses, BDI score, Hispanic ethnicity, non-Hispanic black race, and higher urine albumin levels were each associated with decreased odds of antidepressant use. 20 Women had greater odds of antidepressant use. While more research on the mental health disparities within CKD are urgently needed, certain points are clear. Elevated depressive symptoms are common in individuals with CKD. Individuals of racial and ethnic minority background and CKD have a substantial burden of elevated depressive symptoms. In general, depression treatment utilization is low, and appears to be lower for men, Hispanics and blacks.
Humor and Well-Being
Measures of Subjective Well-Being
Health Psychology
8.04.3.1.4 Quality of life
Although the construct of quality of life (QL) is widely used in assessing the consequences of disease, there are quite divergent schools of thought regarding definition and measurement. On the one hand, it is argued that the measures should assess the quality objectively, while on the other it is proposed that QL can only be evaluated according to the individual’s expectations and values. Measures such as the Quality Adjusted Life Year (QALY) ( Kind & Rosser, 1988; Rosser & Kind, 1978 ) or the SF-36 ( Jenkinson, Coulter, & Loright, 1993 ) assume a universal value system, and so by assessing the individual’s limitations it is possible to give an overall value to QL. By contrast, the Patient Generated Index (PGI) ( Ruta, Garratt, Leng, Russell, & MacDonald, 1994 ) and the SEIQOL ( O’Boyle, McGee, & Joyce, 1994 ) assess the individual’s value system as well as the current levels of achievement in valued areas. The values are combined with the levels of achievement to generate an index reflecting quality of life according to the individual’s own value system. Whereas the PGI requires the individual to respond in the context of their illness, the SEIQOL is one of the few measures of QL in current use in health psychology which could be used equally readily with healthy and ill individuals. Measures in other fields, such as the Satisfaction with Life Scale ( Diener et al., 1985 ), assess QL without reference to illness and can be used successfully with individuals who are ill.
Some measures have been developed specifically for some diseases, including the AIMS ( Meenan et al., 1980 ) for arthritis and the Rotterdam Symptom Check List ( de Haes, Van Knippenberg, & Neijt, 1990 ) for cancer. The authors argue that a more sensitive and acceptable measure of QL can be obtained in this way. This reflects the design of disease-related QL measures, depending on assessment of symptoms and limitations in function as a major factor in QL. Where health-related QL measures assume a value system, this is usually based on assessment of emotional state, symptoms, and disability and the measure offers a method of combining these values. So, for example, the QALY gives values for each combination of distress and disability, and this can be done for individuals with diverse diseases.
Life satisfaction index a lsia
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Life satisfaction index a lsia
В данной статье представлены результаты эмпирических оценок экономической идентичности (ЭИР) в различных регионах РФ, основанных на результатах прошедшего в 2016 году междисциплинарного комплексного исследования «Снизу вверх: как экономическая идентичность региона проявляется в социально-экономическом поведении индивидуума». Данное исследование основывается на экспертном опросе учёных в шести федеральных округах Российской Федерации по направлениям: «Поволжье» (ПФО), «Север России» (СЗФО), «Юг России» (СКФО, ЮФО), «Урал» (УФО) и «Центр России» (ЦФО).
Основной целью данного экспертного опроса являлась фиксация проявлений экономической идентичности региона в социально-экономическом поведении индивидуумов в регионах России. Объектом экспертного опроса по направлению «Юг России» являлись четыре основные группы:
1. «Славяне/православные» (русские), разделённые на три подгруппы: «северные (северяне)», «центральные», «южные (южане)».
2. «Тюрки/мусульмане» (татары, башкиры и пр.).
3. «Кавказцы/мусульмане» (дагестанцы, чеченцы и др.).
4. «Финно-угры/православные» (мордва, коми и др.).
Предметом являлся характер взаимосвязей феномена экономической идентичности и моделей экономического поведения с социокультурными факторами у представителей этих групп.
Теоретическая основа. Процесс глобализации подвергает многие части мира особому воздействию [13], вследствие которых индивидуумы и локальные сообщества становятся все менее привязаны к конкретной территории. Это, закономерно приводит к конвергенции, ослабляет традиционные культурные границы и образ жизни в результате «униформизации». Региональная идентичность оказывается под угрозой. Индивидуум начинает чувствовать себя неуверенно, так как его традиционные культурные устои ослабляются.
Ранее было отмечено, что идентичность тесно взаимосвязана с образованием региона, и рост региональной идентичности следует рассматривать в более широком контексте образования области [13]. Существуют два основных подхода к формированию региона: (1) структурно-ориентированный, в котором перспективы роста региона являются логическим результатом более широких тенденций и тотальных изменений, таких как глобализация, реструктуризация и расширение городов и пр. В другом, (2) агент-ориентированном или социально-конструктивистском подходе, регионы рассматриваются как социальные конструкты, определяющие и формирующие себя через различные социальные и дискурсивные практики [14]. Используя конструктивистский подход, формирование региона можно описать как процесс его институционализации [15]. Здесь, институционализация является результатом четырёх одновременных и взаимосвязанных сил: (i) территориальных, (ii) институциональное, (iii) символических и (iv) идентифицирующих.
При этом мы разделяем явления «идентичность региона» и «региональная идентичность». Идентификатор региона относится к тем отличительным физическим, культурным и историческим особенностям, которые делают один регион отличным от другого. Региональная идентичность (или региональное сознание) относится в большей степени к тому, как индивидуум идентифицирует себя с регионом, через институционализированные практики, дискурсы и символы. Пока они существуют одновременно как часть процесса общественного воспроизводства, это различие помогает понять и проанализировать структуру и базовые элементы, скрытые в дискурсах региональной идентичности и регионального сознания [15].
Под экономической идентичностью региона (ЭИР) было предложено понимать «результат агрегирования взаимно наложенных полей, создаваемых экономической и региональной идентичностями индивидуумов, формирующийся на когнитивном уровне социально-экономической системы региона и проявляющийся в экономическом поведении региональных субъектов и их социальном самочувствии».
В качестве рабочей гипотезы было принято считать, что «феномен ЭИР имеет междисциплинарный и многоаспектный характер, её формирование осуществляется в двух направлениях: «снизу вверх» от нано- и микросоциального уровня путём агрегирования до уровня региона, и «сверху вниз» от мега- и макросоциального уровня на уровень региона путём определённого позиционирования идентифицируемого региона в различных социально-экономических пространствах» [13]. Ранние исследования феномена экономической идентичности региона [1, 2] показали, что он имеет междисциплинарный и многоаспектный характер, соответственно, требует адекватного познавательного инструментария для его дальнейших исследований, основанного на междисциплинарном научном подходе [10].
Методология опроса. Согласно методологии проведения качественных социологических исследований [11], для уточнения подходов к определению понятия «экономическая идентичность региона», её структуры, выявления определённых закономерностей её проявления в экономическом поведении на индивидуальном уровне в регионах России, наиболее адекватным было признано проведение точечного (разового) исследования, способного обеспечить получение информации об ЭИР на момент его изучения. По глубине анализа предмета это было аналитическое исследование, которое выявило причинно-следственные связи, лежащие в основе распространённости, динамики, стабильности/нестабильности ЭИР. По методам сбора эмпирической информации исследование носило форму социологического опроса, который незаменим при сборе ограниченного объёма информации у большого числа людей, а сам опрос был проведён в виде экспертного опроса учёных путём заочного онлайн-анкетирования, когда респондент сам заполнял анкету, в удобный для него момент времени [12]. Сам экспертный опрос, как разновидность социологического опроса на эмпирическом уровне, позволял проверить достоверность и объективность полученной информации на основе мнения специалистов в исследуемой области [6]. Далее был проведён контент-анализ полученной первичной информации, с целью уменьшения субъективности качественного анализа и повышения репрезентативности данных и достоверности информации [16]. Для этого использовались программа анализа социологической информации IBM SPSS Statistics V21, а также программа Microsoft Excel 2016 с подпиской на Office 365.
Формально экспертный опрос проводился в рамках четырёх дисциплинарных научных традиций: экономической, социологической, психологической и культурологической. При этом принималось во внимание, что данные научные традиции обладают в значительной степени несопоставимым теоретическим и методологическим аппаратом, различными представлениями об объекте исследования, поэтому обобщающим методологическим основанием была выбрана системная экономическая теория Г. Клейнера [7].
Методика экспертного опроса. Для сбора первичной социологической информации был использован экспертный опрос [5]. Основные подходы к логистике опроса были заимствованы из проведённого ранее экспертного опроса учёных «Феномен «экономической идентичности региона»: определение понятия, структура, механизмы формирования» [2]. При подборе экспертов применялся метод первоначальной целевой выборки, а также метод «снежного кома» [6]. Также была осуществлена оценка компетентности потенциальных респондентов [4, 8, 9], при этом два эксперта были исключены из числа релевантных респондентов. Всего в исследовании приняли участие 118 учёных из шести федеральных округов РФ.
Проведение опроса. Опрос экспертов проводился в 2016 году в шести федеральных округах Российской Федерации:
1. Южном (Астрахань, Волгоград, Краснодар, Майкоп, Ростов-на-Дону, Симферополь, Сочи).
2. Северо-Кавказском (Владикавказ, Грозный, Махачкала, Нальчик, Ставрополь, Пятигорск, Черкесск).
3. Приволжском (Ижевск, Казань, Нижний Новгород, Оренбург, Пенза, Пермь, Саратов, Самара, Уфа).
4. Центральном (Воронеж, Москва, Ярославль).
5. Северо-Западном (Архангельск, Калининград, Санкт-Петербург).
6. Уральском (Екатеринбург, Тюмень, Челябинск).
Общее число респондентов составило 118 человек (71,8 % – мужчины, 28,2 % – женщины), такое количество можно считать достаточным для обобщения и анализа экспертных оценок [8]. Все отобранные эксперты имели высшее образование, учёную степень, учёное звание по специальностям «экономика», «психология», «социология», «философия» и «культурология». Средний стаж работы в связанной с темой экспертного опроса сфере составляет 10,4 лет.
Для разработки анкеты были использованы следующие инструменты:
1) авторская методика [2];
2) опросник «Исследования ценностей Шварца» (The Schwartz Value Survey, SVS);
3) методика «Оценка удовлетворённости жизнью»;
4) опросник «Индекс жизненной удовлетворённости» (Life Satisfaction Index A, LSIA);
5) опросник «Шкала сформированности идентичности» (Identity Achieved Scale, IAS);
6) опросник «Объективное измерение статуса эго-идентичности» (Objective Measure of Status Ego-Identity, OMEIS);
7) опросник «Выявление стиля идентичности» (Identity Style Inventory, ISI-3);
8) опросник «Аспекты идентичности» (Aspects of Identity, AIQ-IV);
9) методика «Who Am I?»;
10) методика «Незаконченные предложения» (Ego Identity Incomplete Sentences Blank, EI-ISB) и др.
Также для разработки анкеты были частично использованы разработки российских учёных:
1) опросник «Диагностика структуры и статусов эго-идентичности – СЭИ-тест»;
2) методика, разработанная на основе модификации опросника EI–ISB;
3) опросник, разработанный на основе опросника AIQ-IV;
4) методика «Кто Я?», разработанная на основе модификации методики «Who Am I»;
5) методика «Оценка экономических представлений и установок» и др.
Результаты опроса. Полученные от экспертов первичные данные были обработаны методами качественного контент-анализа, для анализа вторичной информации был применён междисциплинарный теоретический анализ литературы по проблемам исследования, из общенаучных методов был применён логический и сравнительный анализ.
Экспертами было выявлено, что на макроуровне (уровне общества) все указанные различия являются шаблонными представлениями о типичности поведения представителей своей группы или подгруппы. Так, не было отмечено значимых различий между представителями всех групп по показателям социального капитала, которые на макроуровне взаимосвязаны с установками на различные виды экономического поведения. При этом именно с социальным капиталом связаны внутригрупповые установки на «продуктивные» паттерны экономического поведения для всех групп.
Было выявлено, что для массового сознания представителей всех групп наиболее характерен экстернальный локус контроля, что является несомненным проявлением российской идентичности. Были выявлены межкультурные различия в моделях экономического поведения исследуемых групп. В частности, наиболее значительными оказались различия в групповых парах «славяне» – «тюрки» и «финно-угры» – «кавказцы», а также в подгрупповой паре «славяне/северяне» – «славяне/южане». Мнения экспертов подтвердили рабочую гипотезу, что большинство различий лежит в оценках типичных для групп актуальных моделей экономического поведения. Так, например, в своём типичном экономическом поведении «южане» ориентированы на экономический патернализм и демонстрируют большую, по сравнению с «северянами», эмоциональную вовлеченность в потребление, а равно принятие и готовность к спонтанной расточительности.
Были выявлены межконфессиональные различия в сценариях экономического поведения исследуемых групп. Так фактор конфессиональной принадлежности в России оказался менее значительным по влиянию на экономическое поведение, чем фактор этнической принадлежности. Так на уровне эмоционального предпочтения в групповых парах «мусульмане» – «православные» для представителей первой группы соблюдение закона является более приоритетным, чем получение прибыли.
Были выявлены тесные взаимосвязи между моделями экономического поведения, а также феноменами экономического сознания, такими как установки и экономические представления, и основными социокультурными факторами, такими как базовые ценности, религиозная идентичность. Характер этих взаимосвязей различен у представителей всех выделенных групп и подгрупп.
Было выявлено, что экономическая идентичность коррелирует с установками на различные виды экономического поведения, при этом для групп «славяне» и «финно-угры» она связана с внутренними установками на интерес к экономике, а для групп «кавказцы» и «тюрки» она связана с установками на экономический патернализм, экономическую «небрежность» и расточительность, а мотивирующим основанием нерационального расходования денег является отсутствие стремления к рациональной экономии. Было выявлено, что для представителей всех подгрупп стремление приумножения денежных средств связано в первую очередь с отрицанием базовых устоев общества и взаимопомощи, а также со стремлением к достижению успеха и получению удовольствия от жизни.
Полученные результаты показали, что выбранные для анализа группы и подгруппы имеют различные ценностные приоритеты. Экспертами было подтверждено, что на микроуровне (уровне индивидуума) в индивидуальных ценностях во всех группах существуют значимые межкультурные и межконфессиональные различия. Так, ценности, которые способствуют сохранению групповой стабильности более значимы для «тюрков» и «кавказцев», а ценности, способствующие индивидуальным целям, – для всей группы «славяне», что объясняется большей традиционностью кавказских и тюрских культур в сравнении с более модернизированными русской и финно-угорской.
При анализе различий в индивидуальных ценностях была выявлена определённая взаимосвязь выраженности религиозной идентичности с разными экономическими установками и представлениями у каждой группы, также были подтверждены различия в степени выраженности религиозной идентичности в группах «православные» – «мусульмане».
Выводы
В целом, проведённое междисциплинарное комплексное исследование «Снизу вверх: как экономическая идентичность региона проявляется в социально-экономическом поведении индивидуума» позволило уточнить подходы к определению понятия «экономическая идентичность региона», выявить структуру, определённые закономерности её проявления в экономическом поведении на индивидуальном уровне в российских регионах, позволило получить весомое подтверждение важности и актуальности исследования ЭИР на современном этапе, а более подробный анализ результатов может стать основой для дальнейших публикаций.
Статья подготовлена при поддержке Российского гуманитарного научного фонда, грант № 15-02-00441/15 «Экономическая идентичность российских регионов: концептуализация понятия, разработка инструментария измерения и сравнения, включение в систему регионального бренд-менеджмента».
Life satisfaction
From Wikipedia, the free encyclopedia
Life satisfaction (LS) is the way in which people show their emotions, feelings, and moods. It is how they feel about their directions and options for the future. [1] [ page needed ] It is a measure of well-being assessed in terms of mood, satisfaction with relationships, achieved goals, self-concepts, and self-perceived ability to cope with one’s daily life. Life satisfaction involves a favorable attitude towards one’s life—rather than an assessment of current feelings. Life satisfaction has been measured in relation to economic standing, degree of education, experiences, residence, and among many other topics. [2] [3] [4] [5]
Life satisfaction is a key part of subjective well-being. There are many factors, both internal and external (such as socio-demographic and psychosocial) that contribute to one’s subjective well-being and life satisfaction. Socio-demographic factors include gender, age, marital status, income, and education. Psychosocial factors include health and illness, functional ability, activity level, and social relationships. [6]
People are more likely to experience higher levels of life satisfaction the older they become. [7]
Gender Differences in the Relationship Between Marital Status Transitions and Life Satisfaction in Later Life
Judith G. Chipperfield, Betty Havens, Gender Differences in the Relationship Between Marital Status Transitions and Life Satisfaction in Later Life, The Journals of Gerontology: Series B, Volume 56, Issue 3, 1 May 2001, Pages P176–P186, https://doi.org/10.1093/geronb/56.3.P176
This study examined life satisfaction among individuals who had undergone a transition in marital status and those whose marital status remained stable over a 7-year period. In particular, using data from a large-scale, longitudinal study we assessed life satisfaction as measured in 1983 and 1990 among 2,180 men and women between the ages of 67 and 102. Groups of individuals were identified on the basis of whether a spouse was present or absent at the two measurement points. This allowed for a classification of groups who experienced stability or transitions in marital status. Among those individuals whose marital status remained stable over the 7 years, women’s life satisfaction declined and men’s remained constant. Among those who experienced a transition—in particular, the loss of a spouse—a decline in life satisfaction was found for both men and women, decline being more predominant for men. In addition, men’s life satisfaction increased over the 7-year period if they gained a spouse, whereas the same was not true for women. Generally, these findings imply that the relationship between marital status transitions or stability differs for men and women.
Decision Editor: Margie E. Lachman, PhD
AS people age, many face the traumatic experience of losing their spouses, either through death or institutionalization. Evidence suggests that individuals who lose a spouse are more likely to die than their counterparts who do not experience this stressful event (e.g., Bowling 1987 ). An equally important issue is the quality of life following the loss of a spouse. Some individuals adjust well to the loss; others do not. Attempting to understand the experience, researchers have studied everything from bereavement (e.g., Herriott and Kiyak 1981 ; Lund 1989 ) and depression (e.g., Osterweis, Solomon, and Green 1984 ; Stroebe and Stroebe 1983 ) following the loss of a spouse to use of health services (e.g., Wolinsky and Johnson 1992 ). This emphasis on widowhood, however, has overshadowed the need to study stability in marital status or marital status transitions other than the loss of a spouse. For example, marriage in later life, whether for the first time or following the loss of a spouse, has important implications for quality of life.
The goal of the present study was to explore life satisfaction among seniors who had undergone both types of transitions (i.e., those who gained spouses and those who lost spouses) and seniors who retained marital status stability. In particular, we examined life satisfaction among various groups of seniors differing in marital status, thereby adding to the literature on life satisfaction among those who are single (Chappell and Badger 1989 ), divorced (Farnsworth, Pett, and Lund 1989 ), remarried (Bulcroft, Bulcroft, Hatch, and Borgatta 1989 ; Burks, Lund, Gregg, and Bluhm 1988 ), or married and widowed (e.g., D’Amato 1987 ; Fengler, Danigelis, and Little 1983 ; Geis and Klein 1990 ).
Marital Status and Well-Being
Taken together, these findings suggest that the presence of a marriage partner has positive implications for life satisfaction. As Dykstra 1995 pointed out, «Many activities are couple-companionate, undertaken as a couple, with other couples» (p. 321). Thus, to the extent that social interaction facilitates psychological well-being, the availability of a spouse may offer a «protective» function. Interestingly, some of the existing research has pointed to the possibility that the presence of a spouse affords a relatively greater advantage for men than for women. For example, in a study of retirement satisfaction, the beneficial impact of marriage on satisfaction with retirement was greater for men than for women (Calasanti 1996 ). Moreover, researchers have shown an increased risk of dying among widowers, but not among widows, following their spouses’ deaths (e.g., Biondi and Picardi 1996 ; Bowling and Windsor 1995 ; Martikainen and Valkonen 1996 ). This implies that the implications of marriage and widowhood are different for men and women.
Although numerous studies of aging have explored the «loss-of-spouse» transition (i.e., death, divorce, institutionalization), fewer studies have examined the remarriage transition. This is, in part, because small numbers of people tend to remarry late in life (Zick and Smith 1988 ). Likewise, with a few exceptions (e.g., Barrett 1999 ; Bennett and Morgan 1992 ; Dykstra 1995 ; Strain and Payne 1992 ), never-married seniors have been largely ignored when examining the relationship between marital status and well-being.
Stability versus transitions in marital status.
The important distinction between marital status stability versus marital status transition has received little attention in past research. A potentially useful approach would allow for a two-dimensional classification that distinguishes between the presence of a spouse (present vs absent) and transitions in marital status (yes vs no). Within this framework, never-married and still-married individuals are similar on the transition dimension (i.e., they have not experienced a transition in marital status) and different on the presence dimension (i.e., never-married individuals do not have spouses present, and still-married individuals do have spouses present). This classification would allow for a consideration of whether undergoing a transition in marital status has more serious consequences for life satisfaction than the mere presence or absence of a spouse.
Longitudinal designs are essential in order to directly study the role of marital status transitions. However, in the few longitudinal studies that exist, it is difficult to summarize the impact of marital status transitions on changes in life satisfaction because the comparison groups differ across studies (e.g., married vs widowed; remarried vs widowed). In one study of seniors who had lost spouses, those who remarried displayed higher levels of life satisfaction after 2 years than those who did not (Burks et al. 1988 ). In another 10-year study, those who remarried were relatively happier with their lives than those who did not, but this happiness diminished with time (Bulcroft et al. 1989 ).
Finally, Bennett and Morgan 1992 found that patterns of psychological change over 4 years differed for women who had been widowed, had never married, or were still married. Overall, morale decreased; however, the magnitude of this decrease was strongest among widowed women. Also, those who experienced a transition (i.e., the widowed women) had significantly lower levels of morale after 4 years than those whose status remained stable (i.e., still-married and never-married women). Despite differences in the presence or absence of a spouse, the groups who experienced stability expressed similar levels of morale. In other words, morale appeared to be more affected by a transition than by the mere availability or presence of a spouse.
The Present Study
Using a longitudinal design, we directly addressed the question of whether patterns of life satisfaction differed for seniors who underwent a transition in marital status (e.g., death of spouse, remarriage) compared with those who experienced stability (i.e., remained married, remained never married, remained divorced or widowed). First, we predicted that, over time, life satisfaction would remain relatively unchanged among those who experienced stability in marital status. This prediction was based on Bennet and Morgan’s (1992) finding that those who experienced marital status stability expressed similar levels of morale over time and on the findings from several large-scale longitudinal studies of well-being, one involving a 9-year follow-up (Costa et al. 1987 ) and another involving a 14-year follow-up (Stacey and Gatz 1991 ).
Second, we predicted that life satisfaction would change among those who underwent a marital status transition. In particular, within the marital status transition groups, we expected that those who lost spouses would experience a decline in life satisfaction, whereas those who gained spouses would enjoy heightened satisfaction. More important, we expected that, relative to women, for men the magnitude of change in life satisfaction would be larger. Women’s life satisfaction, on the other hand, was expected to be relatively more stable than men’s, despite changes in marital status. These predictions are in keeping with research that has shown an increased risk of dying among widowers but not among widows following the death of a spouse (e.g., Bowling and Windsor 1995 ).
Of course, an evaluation of changes in life satisfaction would be inadequate without attention to other factors. For the present purpose, potentially important variables were identified by drawing from the literature on the predictors of life satisfaction (Davis 1991 ; D’Amato 1987 ; Fengler et al. 1983 ; Girzadas, Counte, Glandon, and Tancredi 1993 ; Riddick 1985 ; Spreitzer and Snyder 1974 ). We included measures of health, which is consistently shown to be the strongest predictor of life satisfaction (D’Amato 1987 ; Farnsworth et al. 1989 ; Girzadas et al. 1993 ; Lubben 1989 ; Morris 1997 ). Also included were age (e.g., Geis and Klein 1990 ; Lund, Caserta, and Dimond 1986 ), education and income (e.g., Farnsworth et al. 1989 ), social support (e.g., Fengler et al. 1983 ; Strain and Chappell 1982 ), and activities of daily living (Girzadas et al. 1993 ), variables that have been shown to predict life satisfaction.
The majority of the existing work in this area has used cross-sectional designs, obtaining only posttransition measures of well-being. Unlike these past studies, which do not allow for a direct analysis of marital status transitions and accompanying changes in well-being, the present study systematically assessed these changes across 7 years, from 1983 to 1990. Participants were part of the longitudinal Aging in Manitoba (AIM) Project, and because of the representative nature of the study sample, it was possible to track those individuals who experienced both types of marital status transitions (e.g., widowed, remarried) as well as those who retained stability (e.g, married, never married, remained widowed or divorced). As such, our assessment expands on the previous work, which has only indirectly addressed marital status transitions versus stability primarily by comparing groups that are married versus widowed. As such, it provides an opportunity to extend the existing description of the relationship between marital status and life satisfaction that has arisen from those studies that focus on specific comparison groups.
Methods
AIM Database
The AIM database contains data from interviews conducted with older people in Manitoba at five points in time: 1971, 1976, 1983, 1990, and 1996. The individuals who agreed to participate (or in some cases proxies) were interviewed in their home, in their language of choice (e.g., Ukrainian, French, Italian, Icelandic, Yiddish, Portuguese, Polish, German, Chinese, Sioux, Chippewa, and Cree). The interviews lasted approximately 1 to 1.5 hr and assessed a variety of variables, including demographics, social networks, perceptions, health, well-being, and so forth.
To obtain sufficient numbers of individuals who experienced marital status transitions and large enough numbers to examine each of the stability–transition groupings (e.g., see subsequent description of stability–transition groups), the present analysis focused on a subset of individuals who were interviewed over a 7-year period. This included AIM participants who were interviewed in 1983 and again in 1990. Thus, the following description is restricted to these two measurement points. A full description of the methodology of the AIM studies can be found elsewhere (Chipperfield, Havens, and Doig 1997 ).
In 1983, a total of 5,273 individuals were interviewed; some of these (n = 2,780) were first-time participants. Using an age–gender stratified area-probability sampling technique, these first-time participants were randomly selected from Manitoba Health’s computerized registry, which contains information on all Manitoba residents (e.g., age, gender, and area of residence) who are covered under the universal medical insurance program. Because this registry represents the most comprehensive listing of residents available in the province of Manitoba, samples drawn from it can be considered representative of the overall provincial population. Other 1983 participants were part of a longitudinal follow-up panel (n = 2,403), having begun the AIM study at an earlier time (i.e., in 1971 or 1976). Again, the initial 1971 and 1976 samples were selected from Manitoba Health’s registry using the same age–gender stratified area-probability sampling technique. Interviews were completed by 95% of the potential surviving participants (Chipperfield et al. 1997 ).
In 1990, a second follow-up study was conducted, reinterviewing all of the individuals who had participated in 1983, excluding those who had died. At this time, interviews were again conducted with 95% (n = 3,218) of potential participants (Chipperfield et al. 1997 ). Rigorous steps were taken to determine the status of a small percentage of individuals (n = 170, or 5%) who could not be interviewed in 1990 for a variety of reasons and to compare these nonrespondents with respondents. No significant differences were found on a variety of demographic variables, indicating that the nonrespondents and respondents were similar (Chipperfield et al. 1997 ).
Present Study Sample
To consider the relationship between marital status and life satisfaction, only a subset of the 1990 AIM survivors were included. The sample was restricted to those individuals who, in 1983 and 1990, completed Neugarten, Havighurst, and Tobin 1961 Life Satisfaction Index A (LSIA), thus excluding individuals who were not interviewed at both times, those who required assistance from a proxy, and those who were cognitively incapable of responding to these items. The participants retained for analyses (n = 2,180) consisted of 1,321 women and 859 men ranging in age from 67 to 102 (M = 77.7). One half (50%) were married, 40% were widowed, 3% were divorced, and 7% were single. Formal education ranged from a low of 0 (2%) to a high of 16 or more years (2%). The majority lived in a house (68%) with at least one other person (56%) and described their ethnic descent as British (41%).
Measures
Demographic variables.
Social support.
On the basis of Cumming and Henry 1961 Social Lifespace Measure, we created two variables to reflect monthly social interaction in 1983. These variables were constructed from respondents’ reports of the numbers of people they saw every day, once a week, a few times a month, once a month, and less than once a month. First, interaction with relatives was assessed by responses to the question «Of the relatives (including any in household) you feel closest to, how many do you see and how often?» As suggested by Cumming and Henry, the number of people seen was multiplied by a weighting factor so that a large score would mean more social contact. The mean score for interaction with relatives in 1983 was 44.3 (SD = 47.18).
Second, interactions with friends was assessed by responses to the following question: «Of the friends (including any in household) you feel closest to, about how often do you get together with any of them?» Again, the number of people seen was multiplied by a weighting factor. The mean score for interaction with friends in 1983 was 48.6 (SD = 88.3).
Finally, an interaction with neighbors variable was assessed by responses to «How often do you get together with the neighbour which you see most frequently?» The respondents could choose between every day (1), at least once a week (2), a few times a month (3), about once a month (4), and anything less than once a month (5). Scores on this 4-point scale were reverse coded such that high scores reflected more interaction. The mean interaction-with-neighbor score was 3.8 (SD = 1.4) in 1983.
Change in health status variables.
On the basis of participants’ responses to the interview questions, three measures were created to assess changes that occurred in health status over 7 years. Perceived health was assessed both in 1983 and in 1990 by asking, «For your age, would you say, in general, your health is good, fair, or poor?» The responses were provided on a 5-point scale ranging from 1 (excellent) to 5 (bad for your age). These scores were subsequently reverse coded such that high scores reflected excellent health and low scores, poor health. By subtracting the 1983 score from the 1990 score, a variable was created to measure change in perceived health (M = −0.1, SD = 0.88). Scores ranged from −3.0 to 4.0, with higher (i.e., positive) scores reflecting improvements in perceived health.
Morbidity was assessed in 1983 and again in 1990 by summing the number of health problems. Individuals identified these problems from a list of problems or diseases encountered within the past year: arthritis or rheumatism; palsy; problems with eyes, ears, teeth, stomach, feet, skin, and other areas; heart-related problems (e.g., hardening of arteries, hypertension, heart attack); lung problems (e.g., emphysema, tuberculosis, breathing problems); stroke; kidney problems; and diabetes. A low score reflected low morbidity and a high score, high morbidity. Again, the 1983 score was subtracted from the 1990 score to create a change in morbidity score. Higher scores indicated increased morbidity; lower scores, decreased morbidity (M = 1.01, SD = 2.24).
Functional independence was determined by asking the participants about their ability to perform basic activities of daily living as identified in other standardized measures (Branch, Katz, Kniepman, and Papsidero 1984 ; Branch and Myers 1987 ; Katz, Ford, Moskowitz, Jackson, and Jaffee 1963 ): going up and down the stairs; getting about the house; getting in and out of bed; washing or bathing or grooming; dressing and putting shoes on; and eating. A functional independence score was created by summing the activities that respondents were able to perform independently. Thus, higher scores reflected greater independence. By subtracting the 1983 score from the 1990 score, a change score was created such that higher scores reflected increasing independence and lower scores, decreasing independence (M = −0.16, SD = 0.89).
Stability–transition groups.
The major independent variable, marital stability–transition, was determined by asking respondents about who lived in their households in 1983 and again in 1990. For the purposes of this study, four groups were identified on the basis of presence (P) or absence (A) of a spouse. Spousal presence obviously referred to the presence of a spouse who lived in the home. Spousal absence from the household could be due to having never been married, the death or institutionalization of a spouse, or divorce or separation. The P or A groups were further classified as having stability in marital status or as having experienced a transition.
Respondents who were not living with a spouse in either 1983 or 1990 were classified into the absent–absent (AA) stability group. The absence of a spouse was for a variety of reasons (e.g., never married, divorced or widowed before 1983; see Appendix, Note 1). Although some of these individuals had undergone a transition before 1983, they had all retained at least recent stability in marital status.
The present–absent (PA) transition group included individuals who were living with a spouse in 1983 but not in 1990. The loss of a spouse was most often due to death (87%). However, for a small percentage of the participants, it was due to divorce (3%) or other reasons (11%) such as institutionalization of a spouse.
The final, absent–present (AP) transition group consisted of those respondents who were not living with a spouse in 1983 but were in 1990. In the majority of cases (83%), the presence of a spouse in 1990 was due to remarriage or being reunited with a separated spouse, although for 5 individuals (17%) the presence of a spouse in 1990 was indicative of a first marriage. It is worth noting that fewer than 1% of both men and women in this study gained a spouse in late life.
Life satisfaction.
Results
Preliminary Analyses: Identifying Covariates
Before addressing the major question of whether changes in life satisfaction varied depending on the stability of or transition in marital status, preliminary correlational analyses were undertaken to identify potential covariates. Potential variables included demographics (age, education, and income), social support (interaction with relatives, neighbors, and friends), and heath status (perceived health, morbidity, and functional capacity). Each of these variables was assessed in relation to the change in LSIA scores over time, which was measured by subtracting a respondent’s LSIA score in 1990 from his or her LSIA score in 1983. A positive difference score indicated an increase and a negative difference score indicated a decline in life satisfaction over time.
Repeated Measures
A significant main effect emerged for the between factor, Stability–Transition Group, F(3,2172) = 30.79, p Table 3 ). However, the main effect for Stability–Transition (ST) Group is qualified by its interaction with Year, F(3,2172) = 16.70, p Fig. 1 and Fig. 2, indicates that changes in life satisfaction over time were not equivalent for women and men within specific stability–transition groups.
Stability in martial status.
Transitions in marital status
Subsequent Analyses
A final issue that we addressed involved a more refined analysis to consider possible differences between the «always single» (AS) and those who were only «recently single» (RS), that is, those who had lost a spouse before 1983. In our basic group classification, all of these individuals were classified as AA because they had no spouse in 1983 or 1990. However, recent research has suggested the importance of studying always single or never married individuals as a special group of interest (e.g., Barrett 1999 ; Ferguson 2000 ).
We compared these two groups (AS, RS) by using an analysis similar to that shown in Table 3 ; however, the four-level stability–transition group variable was replaced with the two-level AS–RS group variable. The results revealed a significant effect for the AS–RS comparison, F(1,806) 6.47, p ; Lund and colleagues 1986 ). Some of our results suggest that transitions and stability in marital status have different implications for older men and women. Among men, life satisfaction remained constant for those whose marital status remained stable over 7 years, and it changed for those who experienced marital status transitions. The pattern was not as simple for women.
Transitions in Marital Status
The overall examination of life satisfaction among those who lost a spouse and those who gained a spouse produced a nearly mirror-image pattern ( Fig. 2 and Fig. 2), suggesting an overall decline in life satisfaction for those who lost a spouse and an increase for those who gained a spouse. However, further exploration of the patterns provided some evidence for gender differences. The decline in life satisfaction following the loss of a spouse was found to be significantly more pronounced for men than for women, with a correspondingly large effect size (.445). This may suggest that the loss of a spouse is relatively more detrimental to men than women. Although men typically experience widowhood at a later age than women, leaving them relatively less time to adjust to their loss (Barer 1994 ), the recency of loss in the present study could not account for men’s more pronounced decline in life satisfaction following the loss of their wives.
Although men may suffer more psychological consequences than women following the loss of a spouse, our results suggest that, unlike women, they derive benefit when marrying late in life. It must, however, be noted that the small cell size of this group who gained a spouse in late life limits our ability to draw conclusions. Nonetheless, the large effect size (−.893) suggests the importance of the finding that men experience an increase in life satisfaction with remarriage late in life. In addition, it is interesting that the magnitude of increases in men’s life satisfaction after gaining a spouse (AP group) appeared to be approximately equal to the magnitude of their declines in satisfaction after losing a spouse (PA group), as is illustrated in Fig. 2 by the mirror-image patterns of changing life satisfaction for men who experienced opposing transitions in marital status.
The gain in life satisfaction for men following the attainment of a spouse may also be due to changes in the social relationships that accompany the presence of a spouse. Whether the role of a wife is direct (e.g., access to a confidant) or indirect (promotion of interactions outside the spousal relationship), the enhanced exposure to social networks and increased social activity may foster a more fulfilling social experience for men. The potential for psychological gain is consistent with the fact that men are more likely than women to remarry (Burch 1990 ) and they remarry more quickly than women (Wu 1995 ), implying, perhaps, a greater motivation to do so.
Although the positive benefit in life satisfaction for men is likely partly due to the social facilitation effect of a wife, other factors are surely involved. For example, although we did not find age to relate significantly to life satisfaction and we did statistically adjust for health, we cannot entirely rule out the possibility that our results partly reflect a selection bias in which younger and healthier men may be more likely to remarry. Another interesting possibility is that men marry more compatible mates than women and therefore are happier and more content in their late-life marriages. This «compatibility» hypothesis is derived from the work of Wu 1995 and others who have pointed out that, due to the cultural norms that dictate that men marry younger women who are often less educated, there is an oversupply of available mates from which men can select. In contrast, for women, who tend to marry older, more educated men, there is an undersupply of men in the potential late-life marriage-partner pool. This implies that men have more opportunity than women to select a compatible mate, thereby enhancing their satisfaction with life.
Still another possible reason for men’s gains in life satisfaction following late-life marriage is that a wife may have a health-promoting influence, in turn leading to greater life satisfaction. This is consistent with the findings of a recent study (Steinberg Schone and Weinick 1998 ) in which marriage had a relatively larger positive impact on health behaviors for elderly men than for elderly women. In short, there are numerous potential explanations for men’s gains in life satisfaction following late-life marriage that are worth examining in future research.
Stability in Marital Status
The present findings also showed that among those individuals whose marital status remained stable, men’s life satisfaction remained consistent over time, whereas women’s declined. The stability in men’s life satisfaction is congruent with the results from several large-scale longitudinal studies of well-being, one involving a 9-year follow-up (Costa and colleagues 1987 ) and another, a 14-year follow-up (Stacey and Gatz 1991 ). The declining life satisfaction for women in the present study is congruent with some findings, such as the declining life satisfaction over a 12-year period (1971 to 1983) in our earlier analyses of very old women in the AIM study. On the other hand, the declining satisfaction is incongruent with findings from Costa and colleagues’ and Stacey and Gatz’s studies. Age variation in samples may partly explain the inconsistency in findings across these studies; the present study focused on older individuals compared with Costa and associates’ study of 25- to 74-year-olds and Stacey and Gatz’s study of 15- to 100-year-olds. In fact, Barrett 1999 analysis of never-married adults showed that the effects of never being married were greatest among elderly individuals, suggesting inconsistent findings may well occur across studies of different age groups.
Clearly, our findings suggest that life satisfaction deteriorates for older women who remain in a stable marital condition (i.e., never married, always married). What would explain their deterioration in life satisfaction over the 7 years of this study? One explanation is based on women’s roles as caregivers and the burdens associated with caregiving. Providing care in later life is associated with severe psychological burdens (Jones and Peters 1992 ; Wijeratne and Lovestone 1996 ; Zanetti, Magni, Sandri, Frisoni, and Bianchetti 1996 ), and women are more likely than men to be in caregiver roles (e.g., Davis 1991 ) and to suffer from the burden (Grafstrom, Fratiglioni, and Winblad 1994 ). Thus, women’s declining reports of life satisfaction could be a reaction to the psychological costs of providing care. A related possible explanation for women’s declining satisfaction is that they may have increasing unmet needs. This is consistent with the finding that women report more unmet needs for help than men (Chipperfield 1996 ).
Cautions
Fifth, selective mortality complicates our understanding of how life satisfaction changes over time, just as it does in any research that examines survivors. Because measures of 1990 life satisfaction were obviously unavailable for those AIM participants who died before 1990, they were excluded from the present analysis. Nonetheless, due to rigorous attempts to acquire representative samples, the present AIM sample of survivors remains representative of survivors in the overall provincial and national population (Chipperfield et al. 1997 ). Thus, the patterns of life satisfaction that emerged in this study are likely to generalize to the broader population of survivors.
Conclusions
Our study demonstrated different patterns of life satisfaction for men and women, for both those who experienced marital status transitions and those who retained stability in their marital status. These results can be interpreted pessimistically or optimistically. With respect to women, the pessimistic view is that life satisfaction generally declined over time, the declines occurring for those women who lost their husbands but also for those whose marital status remained stable over the study. Thus, for the majority of women, life satisfaction may be at risk in old age. The optimistic view of our findings is that life satisfaction did not decline among older women who marry, suggesting that later life marriage may offset the expected decline in life satisfaction. For men, the pessimistic view is that they appear to be at a relatively greater risk than women for suffering psychological consequences following the loss of a spouse. This finding is consistent with the reported gender differences in survival following the death of a spouse (e.g., Biondi and Picardi 1996 ; Bowling and Windsor 1995 ). The need to assist men in their adjustment to the loss of a spouse is underscored by the elevated rate of widowhood among men that has occurred in the past decade (Martin Matthews 1994 ) and that will likely continue in the future. Ultimately, men’s ability to adapt to widowhood will likely also influence their physical health in later life and perhaps their longevity. On a more optimistic note, with the exception of those who lost spouses, men generally experienced either stability or increased life satisfaction over the 7 years of our study. This implies that, with the exception of those men who lost spouses, men are likely to maintain their psychological health in later life.
Taken together, these findings are consistent with the notion that the presence of a spouse buffers men against declining life satisfaction in late life, highlighting the importance of a spouse for men in late life. However, for women, satisfaction with life appears to deteriorate if they remain married as well as if they lose their spouses. Despite women’s relatively greater social interaction than men, all social interactions may be decreasing at older ages, thus contributing to declining satisfaction with life. It may also be that women’s dissatisfaction with life is less firmly connected to their marital status and that their declining satisfaction is influenced by a broader range of factors associated with growing old in contemporary society. A careful analysis of these issues is required before a more precise understanding of the relationship between marital status transitions and life satisfaction will emerge. What is clear from the present study is that the implications of marital status stability–transitions are likely to differ for men and women.
1. Within the AA group, 20% (n = 161) had never married and 79% (n = 636) had either been widowed or divorced before 1983. Fewer than 1% (n = 8) indicated that they were married in 1990 but that they had not lived with their spouse in 1983 or 1990. In the latter case, it is assumed that the spouse was still alive but living elsewhere, perhaps in a long-term care facility.
Marital Status Group Sizes (Frequences and Percentages)
Life Satisfaction
Greater life satisfaction was most strongly associated with being in control of one’s health and living a normally active life with satisfying emotional relationships.
Related terms:
Life Satisfaction
Focus of Life Satisfaction Research
Life satisfaction is one of the oldest research issues in the social scientific study of aging. Initially, this research focused on pathology and coping, but later the issue became perceptions of quality of life. Life satisfaction and other subjective well-being measures have been of considerable importance in gerontology. Researchers and policy makers are attempting to better understand the impact on quality of life of disability, changes in health status, caregiving, bereavement, retirement, role transitions and loss, diminishing social networks, modifications in activity involvement, and personality development over the life course.
Two issues have dominated research on subjective well-being in the field of gerontology. The first concerns how best to conceptualize and measure subjective well-being. Life satisfaction is only one of several competing subjective well-being constructs, and researchers continue to work at developing appropriate measures. The second issue involves the identification of those factors in people’s lives that influence their subjective well-being. A substantial amount of research focusing on this issue and using the life satisfaction construct has been reported. The impact on life satisfaction of various interventions, programs, and policies directed at older adults has also been of recent interest.
Measures of Life Satisfaction Across the Lifespan
Convergent/Concurrent
The LSITA scores correlate positively with the Salamon-Conte Life Satisfaction in the Elderly Scale (SCLSES; Salamon & Conte, 1984 ). For example, Barrett and Murk (2006) reported a correlation of r=.78 between the total scores of the LSITA and SCLSES. The corresponding domain scores showed correlations between r=.56 (LSITA congruence of goals – SCLSES goals) and r=.75 (LSITA zest vs. apathy – SCLSES daily activities). The correlation between the LSITA and the SWLS ( Diener et al., 1985 ) also exceeded r=.50 ( Barrett & Murk, 2006 ).
Successful Aging in Women
The Life Satisfaction Inventory
The Life Satisfaction Index-version A (LSIA) 51 is a 20-item questionnaire providing a cumulative score acknowledged as a valid index of quality of life. Dimensions of the scale include zest for life; resolution and fortitude; congruence between desired and achieved goals; high physical, psychological, and social self-concept; and a happy, optimistic mood. Participants agree or disagree with the statements and a total scale score is based on number of agreements such that higher scores indicate better life satisfaction. Specific test items include questions such as: ‘as I grow older, things seem better than I thought they would be’ and ‘as I look back on my life, I am fairly well satisfied’. It is a widely used instrument and has prior evidence of an inter-rater reliability of 0.78 and validity based on relationships with other measures of life satisfaction. 51
Well-being (Subjective), Psychology of
5 Cultural Differences in SWB
Certain variables predict life satisfaction in some cultures, but not in others (Diener and Suh 2000 ). For example, self-esteem is a strong correlate of satisfaction in highly westernized, individualistic cultures, but not in collectivistic societies where the group is more important in defining who one is. Similarly, consistency and acting in congruence with the self are stronger predictors of SWB in individualistic than in collectivistic cultures. Also, individualists on average heavily use their own emotional feelings to judge their life satisfaction, whereas collectivists are more likely to weight normative prescriptions for happiness, and the views of others. For collectivists, SWB must include the belief that significant others evaluate one’s life well. The explanation for these differences between nations is that various cultures emphasize different values and goals, and therefore tend to make certain information chronically salient so that it is used when people judge their lives.
Not only are there cultural differences in the correlates of SWB, but average SWB levels differ across nations as well. For instance, high levels of SWB are currently reported in northern European nations, whereas much lower levels are reported in eastern European countries. Several factors seem to account for the differences between nations in SWB: wealth versus poverty, political stability versus instability and social disruption, and culture. In terms of culture, some societies seem to emphasize a positive approach to life, and the desirability of happiness. In these ‘positivity cultures’ there are higher levels of satisfaction than are predicted based on wealth or objective factors alone.
Set Point Theory and Public Policy
Data and Methods
As mentioned, the SWB data are for April–May 2007, a date prior to the onset of the Great Recession. Public policies for the unemployed may be temporarily expanded in the face of rising unemployment, and such actions may distort basic policy differences among countries due to differences in the severity of a recession and the policy responses thereto. For virtually all of the countries included here, however, unemployment rates were declining prior to the date when SWB was observed; hence, the policy measures should be indicative of fundamental differences in policy. NRR and ALMP measure policies as of the year 2006; the strictness measure is for 2011, the only year for which an estimate has been made.
Three macroeconomic variables that are typically found to be significantly related to SWB are also included in the analysis. The first is GDP per capita in the year 2006, measured in 2005 dollars of purchasing power ( Heston, Summers, & Aton, 2012 ). The second is the inflation rate, the percentage change in the level of prices from 2005 to 2006. The third is the unemployment rate for April–May 2007, the month in which life satisfaction was surveyed.
Note that the unemployment rate may itself be viewed as a labor market policy variable. Differences among countries in the unemployment rate may reflect, in part, differences in fiscal and monetary policies aimed at achieving full employment. But unemployment differences may also be due to nonpolicy factors underlying aggregate demand and supply.
The net replacement rate and benefit strictness indicator are measures based on legislation in each country establishing the policies relating to each. The active labor market policies variable, however, is based on spending on such policies, and may not be an accurate indicator of actual policy differences among countries. Two countries may have the same policies, but if one has a higher unemployment rate, this will induce more ALMP expenditure and lead to the impression of a policy difference on ALMP. Hence, in assessing ALMP differences across countries, it is desirable to control for unemployment, as is done in the multivariate regressions described in the following sections.
One would expect that life satisfaction would vary directly with the net replacement rate and active labor market policies, and inversely with the strictness indicator. Higher NRR and ALMP contribute to maintaining one’s income, whereas strict eligibility requirements operate in the opposite direction. With respect to the macroeconomic variables, the expectation is that life satisfaction would vary directly with GDP per capita, and inversely with both the unemployment and inflation rates. In what follows, the bivariate OLS regression relationship between life satisfaction and each of the six variables is first examined and then the multivariate relationships.
Improving Participation and Quality of Life through Occupation
Does Happiness Change? Evidence from Longitudinal Studies
Understanding Change through Stability Coefficients
A common approach to studying whether life satisfaction can change is to study stability of individual differences in life satisfaction. This approach can inform us about the extent to which rank-ordering between individuals is preserved over time. For example, if Samantha was happier than Jonathan when they were kids, will she still be happier in adulthood? Traditionally, questions such as this one are studied by examining test–retest correlations of life satisfaction over time. Higher retest correlations would indicate that rank-order was preserved to a greater degree than lower correlations. In turn, these high retest correlations would suggest that happiness does not change much, at least over the time period being studied.
Early studies on stability of individual differences in life satisfaction were almost exclusively based on two-wave designs. Moreover, they generally examined correlations over relatively short retest intervals—weeks, months, at best up to a few years (e.g., Pavot & Diener, 1993 ). Information from these studies can tell us about the extent to which individual differences are preserved over such time periods. However, they do not allow for broad conclusions about stability over time because two-wave retest correlations obscure influences of different factors on life satisfaction, some of which lead to stability and some of which lead to change ( Conley, 1984; Fraley & Roberts, 2005 ). This leads to difficulties in interpreting two-wave retest correlations in the context of stability.
Personality and Life Outcomes
Schimmack et al. assessed personality and life satisfaction in people from two relatively individualist countries (the USA and Germany) and in people from three relatively collectivist countries (Japan, Ghana, and Mexico). Their results showed that within all five countries, people who were higher in Extraversion and Emotional Stability tended to report more satisfaction with life. (This relation was due to the fact that these persons generally experienced positive emotions much more than negative emotions, a situation that usually makes people feel satisfied with their lives.) However, the link between personality and life satisfaction was somewhat stronger in the individualist countries than in the collectivist countries.
National Panel Studies Show Substantial Minorities Recording Long-Term Change in Life Satisfaction
The Dependent/Outcome Variable: Life Satisfaction
In the German and Australian panels, life satisfaction is measured on a 0–10 scale (German mean=7.0, standard deviation=1.8; Australian mean=7.8, SD=1.5). A response of 0 means “totally dissatisfied,” and 10 means “totally satisfied.” In Britain, a 1–7 scale is used (mean=5.2, SD=1.2).
Single-item measures of life satisfaction are plainly not as reliable or valid as multi-item measures, but are widely used in international surveys and have been reviewed as acceptably reliable and valid ( Diener, Suh, Lucas, & Smith, 1999; Lucas & Donnellan, 2007 ).
Public Policies and the Next Steps in the Evolution of Women’s Aging
4 Scales to Measure Satisfaction with Life (SWLS)
Reflecting on our sense of happiness in different key areas of life can be difficult, especially if our life is seemingly all going well.
Sometimes feelings of unhappiness or dissatisfaction just seem to find us, and it’s up to us to take the time to explore why this might be.
How you do that will depend on a number of different things, but if you’re struggling to get to grips with it, there are plenty of psychology tools and resources to help.
One of those tools is the Satisfaction With Life Scale (SWLS), and in this article, we’re going to take a closer look at what this is and what it can do for you.
Before you continue, we thought you might like to download our three Positive Psychology Exercises for free. These science-based exercises explore fundamental aspects of positive psychology, including strengths, values, and self-compassion, and will give you the tools to enhance the wellbeing of your clients, students, or employees.
This Article Contains:
The Satisfaction With Life Scale
The Satisfaction With Life Scale (SWLS) was first created by researchers Diener, Emmons, Larsen, and Griffin (1985) and published in an article in the Journal of Personality Assessment.
The scale was developed as a way to assess an individual’s cognitive judgment of their satisfaction with their life as a whole. The SWLS is a very simple, short questionnaire made up of only five statements.
Participants completing the questionnaire are asked to judge how they feel about each of the statements using a seven-point scoring system, with 1 being “strongly disagree” and 7 being “strongly agree.”
Below, I’ve outlined what these statements are:
Once you’ve assigned a score from 1 to 7 to each of the statements, you tally up your final score for an indication of how satisfied you are overall with life.
As you can see, the SWLS won’t take up a lot of your time to complete! But it can be a really useful instrument in supporting you to reflect on your life, overall satisfaction, and in beginning to think about areas you might need to spend a bit more time exploring.
You can download a full copy of the SWLS, including how to tally and score.
What Does the Questionnaire Measure Exactly?
When it comes to a sense of subjective wellbeing, researchers have asserted that it consists of two main components: the emotional component and the cognitive component (Diener, 1984; Veenhoven, 1984).
The cognitive component has been more closely conceptualized with life satisfaction (Andrews & Withey, 1976), yet despite this, had not previously received much attention for research. Diener et al. (1985) sought to address this and through developing the SWLS, they created a strong tool in the measurement of the cognitive components they felt reflected a subjective sense of wellbeing and life satisfaction.
The SWLS is not designed to help you understand satisfaction in any one specific domain of life, such as your job or relationships; instead, it has been developed to help you get a sense of your satisfaction with your life as a whole.
Although the questionnaire doesn’t measure individual components, it can be an excellent starting point, encouraging deeper thought and exploration of the specific areas of life that may be causing you a sense of dissatisfaction.
How Does the Scoring Work?
The scoring for the SWLS works quite simply, by adding up the total of the numbers you score against each of the statements. So, remembering that 1 = strongly disagree and 7 = strongly agree, the higher your score, the higher your sense of life satisfaction as a whole.
As a guide, your total score means:
Pavot and Diener (2013) created a more in-depth description of what your score means for your sense of life satisfaction. Very briefly, we’ve written up what they had to say, but it’s worth accessing the original documents.
If you score this high on the SWLS, it means you have a strong love of your life and feel that things are going really well for you. This does not mean to say that you feel your life is perfect, but you are content with how things are and/or feel any challenges are temporary and can be managed.
A high score does not indicate that you are complacent about your sense of satisfaction, and it is likely you understand that challenge is a pathway to growth and greater satisfaction.
If you score in this range, you likely feel that most things in your life are going really well, but there may be one or two key areas you wish to change. You understand that your life is not perfect and respect that any challenges are also an area for further growth and exploration.
If you score in this margin, you’re in good company. The researchers assert that this is where the majority of people score themselves. This score means you are generally satisfied, on an average day-to-day basis; however, there are areas you’d really like to improve.
Rather than there being one or two things that you feel would give you greater satisfaction, you might feel that small improvements across all domains of your life would lead to a higher sense of life satisfaction.
A score of 20 – bang in the middle of the scale – means you’re likely pretty neutral about your sense of satisfaction about your life. You might not give too much thought to what does or doesn’t need improving, and you’re quite content where you are.
A score in this range might mean that you tend to feel dissatisfied more than satisfied on a day-to-day basis, and there are several significant areas for improvement. It might also indicate that you’re generally content, but there is one area of life where you feel deeply unsatisfied, which is creating a lower score.
A score in this margin requires further thought and reflection on where improvements need to be made to increase your sense of satisfaction.
A dissatisfied score tends to mean you’re feeling substantially dissatisfied about your current circumstances. This might be deep dissatisfaction across all areas of life or that two or three areas are far worse than the others.
It’s worth reflecting to see if your dissatisfaction is due to a recent event or situation, which may be temporary, or if this is a chronic experience because you are not living the life you truly want.
As you may have guessed, a score at the very low end of the scale means that you are extremely dissatisfied with your current life circumstances. Again, if this score is due to a recent hard blow in life, such as bereavement, then things may get better over time with the right support.
However, a score this low tends to be an indication of dissatisfaction across multiple areas of life and is a good starting point to begin reflecting on why that might be.
A Look at the Reliability and Validity of the Test
The SWLS is one of the most widely used measurements for life satisfaction. The shortness and ease of being able to administer the scale to achieve foundation results is key to this, but how reliable does that actually make it?
In developing the scale, Diener et al. (1985) tested it widely and reported that it does have good psychometric properties, as well as a high test–retest coefficient (meaning participants who completed the scale more than once demonstrated the same results consistently).
Further research has confirmed this reliability against other measures of life satisfaction (Pavot et al., 1991, Pavot & Diener, 2008) as well as other measures for happiness (Lyubomirsky & Lepper, 1999). It has also correlated well with scales measuring the meaning of life (Steger et al., 2006) and scales measuring hope (Bailey & Synder, 2007).
Several other studies have also sought to use the scale across different cultural groups to test its validity, with positive results. Galankis et al. (2017) used the scale across a sample of 1,797 Greek natives and found their results in line with the original researcher’s studies, as well as other studies exploring cross-cultural uses for the SWLS.
The only part of the scale that has been questioned in the research is the use of the fifth statement, as researchers believe it has a weaker association with life satisfaction and instead causes participants to reflect on the desire to change rather than their current sense of life satisfaction (Pavot & Diener, 1993).
About Ed Diener and the Authors
Lead researcher for the SWLS, professor Ed Diener, was sometimes referred to by his nickname ‘Dr. Happiness,’ owing to his astonishing body of research and academic contributions to the study of happiness and wellbeing.
He was a professor of psychology at the University of Virginia and University of Utah, as well as a senior scientist with the Gallup Organization. He published over 350 academic articles and books and was also the editor of three scientific journals.
As well as happiness and life satisfaction, Diener studied the factors that influence these two areas, including financial health, family upbringing, personality, relationships, and work. He studied these topics across 166 different nations and explored some of the cultural components behind individual happiness.
The other researchers and authors of the SWLS include:
Where Can You Find the SWLS?
The SWLS is widely available for free online, and while there are a few slight variations, each has the same outcome or measurement at its heart.
One of the best places to find the scale and its scoring is on the Ed Diener Lab website.
The Wheel of Life by PositivePsychology.com
While the SWLS can offer you an indication of your life satisfaction on a more overall scale, there are other tools and resources that can help you to further explore your sense of satisfaction in specific domain areas of your life.
One such tool is the wheel of life (Whitworth et al., 1998).
Once you have your score from the SWLS, you can then begin to reflect more fully on where you might like to make changes to build a greater sense of life satisfaction.
This tool will help you do that, as it requires that you identify the different life domains that are important to you – such as career, family, and relationships – and to then give each of these individual domains a rating from 1 to 10, with 1 being “not at all satisfied” and 10 being “completely satisfied.”
PositivePsychology.com has put together a free ready-to-use resource with a Wheel of Life containing 10 key domains for life satisfaction.
The wheel is a fantastic resource from the SWLS, as not only does it encourage you to think more deeply about where you might be dissatisfied with life, it also creates a great visual representation.
Once you have your scores for each of the 10 domains, you can reflect on where you have given the lowest scores, why these are low scores, and what you might be able to do to start making positive changes and improve your sense of life satisfaction.
Student’s Life Satisfaction Scale (SLSS)
The Student’s Life Satisfaction Scale (SLSS) is relatively similar to the SWLS, except it was purposefully designed to be used with children and young people aged 8–18 years old (Huebner, 1991).
It contains seven statements and asks young people to give each statement a score from 1 to 6, with 1 being “strongly disagree” and 6 being “strongly agree.”
The exception with the SLSS is that the last two questions are reverse scored (so 1 becomes “strongly agree” and 6 becomes “strongly disagree”).
There are a few different variants, but the statements are along the following lines:
As with the SWLS, when each statement has been assigned a score, a summary total is calculated to provide a numerical guide to the student’s sense of life satisfaction.
The Multidimensional Student’s Life Satisfaction Scale (MSLSS)
Following on from the SLSS, Huebner (1994) went on to create the Multidimensional Student’s Life Satisfaction Scale (MSLSS). The MSLSS is a longer scale assessment for measuring students’ satisfaction with life.
It contains 40 items/statements and can be used either with individuals or in a group setting.
Participants are asked to rate their response to the statements using the following numerical grading scale:
1 = Never
2 = Sometimes
3 = Often
4 = Almost always
The MSLSS was developed in response to a growing interest in promoting positive psychological wellbeing among young people and students (Sarason, 1997). With its use, Huebner hoped to:
Below, I have provided a brief outline of the types of statements that it includes:
To score the MSLSS, you tally up the total score for each specific domain. A higher score indicates a higher level of life satisfaction – similar to the SWLS.
You can also compare domains by tallying the individual scores and then dividing the score by the number of statements in that specific section, to create a mean score.
You can find out more about the MSLSS and get a copy of the full 40 statements and scoring instructions.
A Take-Home Message
I hadn’t come across the SWLS before researching and writing this article, and I have found it a great tool to use personally. Its ease and accessibility mean everyone can benefit from the foundational insights it might offer you about how you feel about your current life situation.
If there’s one thing I’d like you to take away from this article, it’s that the SWLS and the wheel of life are just the beginning. Use them as resources to help your thought processes and be sure to reflect on your results. We are all in control of our own life satisfaction; if yours isn’t quite where you’d like it to be, you have the ability to change that.
What did you think of the SWLS, and has it helped you? I’d love to hear your thoughts in the comments.
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