Skip to main content
NCBI home page
The Journals of Gerontology Series B: Psychological Sciences and Social Sciences logoLink to The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
. 2020 Aug 5;76(7):1408–1414. doi: 10.1093/geronb/gbaa109

Measuring Older Adult Loneliness Across Countries

Lauren Newmyer 1, Ashton M Verdery 1,✉, Rachel Margolis 2, Léa Pessin 1
PMCID: PMC8363044  PMID: 32756903

Abstract

Objectives

The topic of older adult loneliness commands increasing media and policy attention around the world. Are surveys of aging equipped to measure it? We assess the measurement of loneliness in large-scale aging studies in 31 countries by describing the available measures, testing correlations between them, and documenting their construct validity.

Methods

We use data from several “sister studies” of aging adults around the world. In each country, we document available loneliness measures, test for measurement reliability by examining correlations between different measures of loneliness, and assess how these correlations differ by gender and age group. We then evaluate construct validity by estimating correlations between loneliness measures and theoretically hypothesized constructs related to loneliness: living alone and not having a spouse.

Results

There is substantial heterogeneity in available measures of loneliness across countries. Within countries with multiple measures, the correlations between measures are high (range 0.384–0.777, median 0.636). Although we find several statistically significant differences in these correlations by gender and age, the differences are small (gender: range −0.098 to 0.081, median −0.026; age group: range −0.194 to 0.092, median −0.003). Correlations between loneliness measures and living alone and being without a spouse are all positive, almost universally statistically significant, and similar in magnitude across countries, supporting construct validity.

Discussion

This article establishes that even single-item measures of loneliness contribute meaningful information in diverse settings. Similar to the measurement of self-rated health, there are nuances to the measurement of older adult loneliness in different contexts, but it has reliable and consistent measurement properties within many countries.

Keywords: Cross-national, Loneliness, Measurement, Population aging

The topic of older adult loneliness has captivated international policy and media attention. For example, the United Kingdom recently appointed a loneliness minister (Yeginsu, 2018), France developed a “Heatwave Plan” to contact isolated older adults during extreme weather (Jérôme, 2019), and media have highlighted loneliness crises in Italy (Fasano, 2019), Spain (Troya, 2019), Japan (Onishi, 2017), China (Rivers & Lee, 2019), Korea (Park, 2019), India (Ali & Barnagarwala, 2018), and elsewhere. Scholars define loneliness as “an individual’s subjective perception of deficiencies in his or her network of social relationships” (Baumeister & Leary, 1995; Perlman & Peplau, 1981; Russell et al., 1984, p. 1313; Sermat, 1978; Weiss, 1973). The key features are that loneliness (a) results from deficiencies in social relations, (b) is subjective, and (c) is “unpleasant and distressing” (Perlman & Peplau, 1981, p. 32). Loneliness is consistently associated with older adults’ quality of life, poor health, and adverse medical outcomes (Cacioppo et al., 2002; Coyle & Dugan, 2012; Gerst-Emerson & Jayawardhana, 2015; Luo et al., 2012; Nummela et al., 2011).

There is limited scholarship on the cross-national measurement of older adult loneliness. Some countries have higher proportions of older adults reporting being lonely than others (Fokkema et al., 2012; Yang & Victor, 2011), but it is unclear whether loneliness is being measured reliably within countries. By contrast, research consistently finds self-rated health is reliable and valid across contexts (Idler & Benyamini, 1997), with similar associations between self-rated health and objective health indicators and outcomes in diverse settings (Jylhä et al., 1998). Do measures of loneliness have similar properties? If so, researchers and policymakers can carry out cross-national studies of loneliness to devise policy solutions that might alleviate its burdens. Low cross-national reliability and validity, however, would narrow the scope of loneliness studies to particular settings.

There are many available measures of loneliness. The most commonly studied use multiitem scales focused solely on loneliness, ranging from 3 to 20 items (de Jong Gierveld, 1989; de Jong Gierveld & Kamphuls, 1985; de Jong Gierveld et al., 2006; Hughes et al., 2004; Russell et al., 1978). Some of these scales capture social and emotional loneliness (de Jong Gierveld, 1989; de Jong Gierveld & van Tillburg, 2006), but others are unidimensional (Hughes et al., 2004). However, the most commonly fielded measures of loneliness are single items included in larger mental health scales, such as the Center for Epidemiological Sciences—Depression (CES-D) scale (Radloff, 1977) or a scale of social isolation (Cornwell & Waite, 2009). Research has not assessed the alignment between the multi-item scales and the single-item indicators in a broad array of settings.

The reliability and validity of loneliness measures may vary cross-nationally. For example, single-item indicators could map onto multiitem scales better in some countries than others. Existing research on measuring older adult loneliness is primarily concentrated in a few countries. For instance, studies have compared loneliness measures in Canada (Penning et al., 2014), the United States (Hughes et al., 2004; Shiovitz-Ezra & Ayalon, 2012), the United Kingdom, and Australia (Victor et al., 2005). The validity of loneliness measures may also vary across contexts due to variation in urbanization, labor force participation, education, friendship networks, and other cultural factors that shape older adult social life. Several regional studies have assessed key theoretical correlates of loneliness. For example, in Europe, numerous studies find that not being married is associated with older adult loneliness (Fokkema et al., 2012; von Soest et al., 2020) and, in Asia, older adults who live alone report more loneliness (Lim & Kua, 2011; Yang & Victor, 2008).

It is a unique time for research on aging, with large and high-quality surveys of older adults being fielded and made publicly available in a wide variety of contexts. Given these circumstances, we ask: How is loneliness measured in these surveys? Are these measures useful? Do they display similar properties across countries? We assess these questions by describing the available measures in many “sister studies” of aging adults around the world, testing correlations between the available measures within each survey, and documenting their construct validity.

Method

We analyze data from 14 studies covering 31 countries,1 summarized in Table 1. Supplementary Appendix A reviews the key features of each survey’s design.

Table 1.

Summary of Available Loneliness Measures by Survey

Data set Single-Item Measure CES-D Item Measure Three-Item Scale de Jong Gierveld Scale Social Provisions Scale Available measures Countries
CHARLS X 1 China
CRELES 0 Costa Rica
ELSA X X X 3 England
ELSI X X 2 Brazil
HAALSI X 1 South Africa
HART X 1 Thailand
HRS X X X 4 The United States
IFLS X 1 Indonesia
JSTAR X 1 Japan
KLoSA X 1 Korea
LASI X X X 3 India
MHAS X 1 Mexico
NZHWR X X X 3 New Zealand
TILDA X X X 3 Ireland
SHARE X X 2 Austria, Belgium, Croatia, Czech Republic, Denmark, Estonia, France, Germany, Greece, Israel, Italy, Luxembourg, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland
Open in a new tab

Notes: CES-D = Center for Epidemiological Sciences—Depression; CHARLS = Chinese Health and Retirement Longitudinal Survey; CRELES = Costa Rican Longevity and Healthy Aging Study; ELSA = English Longitudinal Study of Aging; ELSI = Brazilian Longitudinal Study of Aging; HAALSI = Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa; HART = Health, Aging, and Retirement in Thailand; HRS = Health and Retirement Study; IFLS = Indonesia Family Life Survey; JSTAR = Japanese Study of Aging and Retirement; KLoSA = Korean Longitudinal Survey of Aging; LASI = Longitudinal Aging Study of India; MHAS = Mexican Health and Aging Study; NZHWR = New Zealand Health, Work, and Retirement Study; SHARE = Survey of Health, Aging, and Retirement in Europe; TILDA = The Irish Longitudinal Study of Aging. See Supplementary Appendix A for survey descriptions; see Supplementary Appendix B for descriptions of loneliness measures.

Measures of Loneliness

Across the studies, there is heterogeneity in the available measures of loneliness (Table 1 and described in more detail in Supplementary Appendix B, which also provides links to documentation). We refer to measures based on the CES-D lonely item, which inquire about feelings of loneliness in a specific time period (e.g., last week), as the “CES-D Item Measure.” Other studies ask a more general question about feelings of loneliness with no time period referenced (Shiovitz-Ezra & Ayalon, 2012); we refer to such measures as the “Single-Item Measure.” Others ask one or more of the multiitem scales referenced above, such as the “Three-Item Scale” (Hughes et al., 2004), which is a shortened derivation of the Revised - University of California, Los Angeles (R-UCLA) Loneliness Scale (Russell et al., 1980), the “de Jong Gierveld Loneliness Scale” a 6-item scale (de Jong Gierveld & van Tilburg, 2006), and/or the “Social Provisions Scale” a 24-item scale (Cutrona & Russell, 1987).

Analysis

We first examine unweighted correlations between the available measures of loneliness within each country (e.g., correlating the Single-Item Measure with the Three-Item Scale) to assess cross-national variation in the strength of these correlations. There are a few differences in results when analyses are weighted. Prior considerations of correlations between measures of loneliness have considered correlations of +0.49 to indicate “high” levels of consistency across measures (Hughes et al., 2004), and we adopt this threshold.

Second, we test for differences in the correlations between measures of loneliness by gender (men vs. women) and age group (younger than age 70 vs. older than age 70) in each country. This test establishes whether there is heterogeneity in how measures of loneliness tap into key constructs by key demographic subgroups; it does not establish prevalence differences or differences in the reasons for loneliness. For instance, if women and men display substantial differences in their correlations between the CES-D Item Measure and the Three-Item Scale, it would suggest that these measures are tapping into different constructs for men and women but offer no conclusion about whether men or women are lonelier. Scholars have used similar approaches to assess self-rated health’s reliability (Jylhä et al., 1998). We focus on the substantive magnitude and statistical significance (Caci, 2000) of the gender and age differences.

Finally, we test the measures’ construct validity by examining their within-country correlations with constructs hypothesized to correlate with loneliness, including marital status (currently married vs. never married, divorced, separated, or widowed) and living arrangements (living with others vs. living alone). Because research consistently demonstrates positive and significant associations between these measures and loneliness, we expect strong relationships. Rather than differences between countries given the cross-national variation in predictors of loneliness, the central considerations are the direction and significance of the correlations in each country and variations between measures. Foundational studies on the measurement of self-rated health consider its range of correlations with mortality (+0.10 to +0.61) to be “impressively consistent” (Idler & Benyamini, 1997, p. 21); others interpret self-rated health “as a global summary measure of health status” (Jylhä et al., 1998, p. 150) on the basis of implied correlations with, to select a few examples, problems with hearing versus not (r = +0.16 to +0.28), moderate versus poor functional ability (r = +0.25 to +0.47), and problems with vision versus not (r = +0.41 to +0.49).2 Building from this logic, we consider correlations weak if less than +0.15, moderate if +0.15 to +0.30, strong if +0.30 to +0.45, and very strong if +0.45 and above.

Results

Table 2 reveals how loneliness measures are correlated with one another in different countries (Supplementary Appendix C contains extended and weighted results). The unweighted correlations for all measures are positively moderate to strong, ranging from 0.384 to 0.777. The strongest correlations are between the Three-Item Scale and the Single-Item Measure (range = 0.589–0.777, median = 0.699). Correlations between the CES-D Item Measure and the Three-Item Scale are more modest (range = 0.399–0.509, median = 0.401), whereas the Single-Item Measure and CES-D Item Measure correlate with each other at moderately high levels (range = 0.386–0.555, median = 0.450). Correlations among different multiitem scales and between them and the CES-D Item Measure are moderate to strong in the one survey that contains multiple multi-item scales (New Zealand).

Table 2.

Summary of Unweighted Correlations Between Different Loneliness Measures, by Country

Measures being compared Min Max Median Mean Countries with measures
CES-D Item vs. Single Item 0.386 (India) 0.555 (England) 0.450 0.472 Brazil, England, India, Ireland, the United States
CES-D Item vs. Three-Item Scale 0.399 (the United States) 0.509 (England) 0.401 0.436 England, India, Ireland, the United States
Single Item vs. Three-Item Scale 0.589 (Germany) 0.777 (Italy) 0.699 0.689 Austria, Belgium, Croatia, Czech Republic, Denmark, England, Estonia, France, Germany, Greece, India, Ireland, Israel, Italy, Luxembourg, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, the United States
CES-D Item vs. de Jong Gierveld Scale 0.478 0.478 0.478 0.478 New Zealand
CES-D Item vs. Social Provisions Scale 0.384 0.384 0.384 0.384 New Zealand
de Jong Gierveld Scale vs. Social Provisions Scale 0.603 0.603 0.603 0.603 New Zealand
Open in a new tab

Notes: CES-D = Center for Epidemiological Sciences—Depression. See Supplementary Appendix Table C1 for detailed results; see Supplementary Appendix Table C2 for a summary of weighted results.

Table 3 measures gender and age differences in these unweighted correlations (Supplementary Appendix C contains extended and weighted results). Although there are numerous statistically significant gender differences, the magnitude of differences is very small (range = −0.098 to 0.081, median = −0.026). In 14 of the 17 statistically significant gender differences, women have a higher positive correlation than men, most commonly for the Single-Item Measure and the Three-Item Scale. Differences by age are similar: Although 21 are statistically significant, most are small (range = −0.194 to 0.092, median = −0.003); correlations are more positive in the older than age 70 population than the younger group. Our findings indicate that the measures perform similarly across these groups, but it is important to keep in mind that these similarities do not imply that loneliness occurs for the same reasons or at similar frequencies for men and women or for older adults who are younger than age 70 or older than age 70.

Table 3.

Summary of Differences in Unweighted Correlations Between Measures of Loneliness by Subgroups.

Measures Gender difference (men minus women) Age group difference (younger than 70 minus older than 70) Countries with measures
Min Max Median Mean # Sig Min Max Median Mean # Sig
CES-D Item vs. Single Item −0.040 0.072 −0.022 −0.005 1 −0.074 0.039 0 −0.018 2 Brazil, England, India, Ireland, the United States
CES-D Item vs. Three-Item Scale −0.044 0.010 −0.033 −0.025 0 −0.194 0.046 0.005 −0.035 2 England, India, Ireland, the United States
Single Item vs. Three-Item Scale −0.098 0.081 −0.027 −0.024 16 −0.087 0.051 −0.017 −0.015 16 Austria, Belgium, Croatia, Czech Republic, Denmark, England, Estonia, France, Germany, Greece, India, Ireland, Israel, Italy, Luxembourg, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, the United States
CES-D Item vs. de Jong Gierveld Scale 0.021 0.021 0.021 0.021 0 0.041 0.041 0.041 0.041 0 New Zealand
CES-D Item vs. Social Provisions Scale −0.021 −0.021 −0.021 −0.021 0 0.059 0.059 0.059 0.059 0 New Zealand
de Jong Gierveld Scale vs. Social Provisions Scale −0.011 −0.011 −0.011 −0.011 0 0.092 0.092 0.092 0.092 1 New Zealand
Open in a new tab

Notes: CES-D = Center for Epidemiological Sciences—Depression. The count of significant differences concentrates on those where p < .05; see Supplementary Appendix Table C2 for detailed results.

Figure 1 shows unweighted correlations between loneliness measures and living alone and being without a spouse (Supplementary Appendix C contains weighted results). Nearly all are significant and positive, and they are remarkably consistent across places at moderate to strong levels. There are more very strong and strong correlations (above +0.30) than weak ones (below +0.15). Correlations with no spouse tend to be slightly more positive and more consistent than those with living alone. Comparing between measures, the correlations are most positive for the Single-Item Measure (with living alone, median = +0.30; with no spouse, median = +0.29), followed by the Three-Item Scale (with living alone, median = +0.22; with no spouse, median = +0.25), and then the CES-D Item Measure (with living alone, median = +0.15; with no spouse, median = +0.18). We see no discernible grouping of the exceptions with weaker associations.

Figure 1.

Figure 1.

Open in a new tab

Unweighted correlations between different measures of loneliness and related constructs, by country. See Supplementary Appendix Figure C1 for a version based on weighted estimates; see Supplementary Appendix Table C6 for detailed results.

Discussion

Our findings have three important implications for future research on loneliness among older adults around the world. First, ongoing surveys of aging are, in general, well equipped to measure loneliness. Although the wording and reference time periods of questions about loneliness vary across surveys, the moderate to strong positive correlations between measures suggest similar capacities to capture the concept. The CES-D is often fielded in surveys even when other more commonly studied measures of loneliness are not. We find that this measure performs similarly to other loneliness measures, which allows researchers to assess loneliness in more contexts. Additionally, we find that single-item measures still asses loneliness well, which adds to the evidence that short loneliness instruments have value in large surveys (Hughes et al., 2004). Second, we find that the correlations across loneliness measures differ only marginally in magnitude by gender and age group. Levels of loneliness may (and likely do) vary across these groups, as do the reasons for loneliness, but the constructs are similarly related and available measures capture them adequately for both men and women as well as younger and older individuals in every country we examined. Researchers should feel confident using these measures among diverse populations. Future studies might adopt psychometric methods to better understand differences in the intercepts and factor loadings of each item in the multi-item scales across contexts. Third, we find consistently moderate to strong positive associations between loneliness measures and factors the literature hypothesizes are associated with both objective social isolation and feelings of loneliness in older adulthood, living alone, and being without a spouse. Though the strength of these associations varies, there is no consistent pattern to suggest that, for instance, measures of loneliness have greater validity in Europe than elsewhere. These associations further strengthen our perception that measures of loneliness are tapping into important constructs that are relatively consistent across places.

Our findings that loneliness measures evince similar measurement properties in 31 diverse countries lend legitimacy to future work on older adult loneliness; however, they are not without the limitations inherent in all cross-national work, such as concerns about the comparability of translations. We believe our results suggest that scholars should treat measures of loneliness similarly to measures of self-rated health: a useful if an imperfect representation of an important concept. Armed with this understanding, researchers can make substantial contributions to quantifying changes in the prevalence of loneliness, explaining what is driving such changes, understanding their ramifications, and devising policies to combat loneliness around the world.

Author Note

1. We selected these data sets from the “International Sister Studies” of the Health and Retirement Study (HRS; https://hrs.isr.umich.edu/about/international-sister-studies), of which there are 18 listed including HRS. We also include the New Zealand Health, Work, and Retirement Study which has a comparable design and numerous measures of loneliness, bringing our potential list of studies to 19. In the end, we provide results from 14 data sets. One sister study, the Costa Rican Longevity and Healthy Aging Study, does not measure loneliness. We also excluded the following sister studies: the Malaysia Ageing and Retirement Survey and the Healthy Aging in Scotland, the World Health Organization Study on Global Ageing and Adult Health (which includes samples from China, Ghana, India, Mexico, Russia, and South Africa), and Northern Ireland Cohort for the Longitudinal Study of Ageing, because the first two do not currently have publicly available data, the third has only one loneliness measure and we have coverage of four of its six countries, and the last requires a full proposal for access.

2. The works of Idler and Benyamini (1997) and Jylhä et al. (1998) report odds ratios (their tables 1 and 3, respectively), which, following the work of Bonett (2007), we converted to correlation coefficients using Digby’s approximation (r = [OR3/4 – 1]/[OR3/4 + 1]); alternative approaches that convert two dichotomous variables into phi coefficients yield similar interpretations, but imply lower thresholds. As such, our interpretations of associational strength may be somewhat conservative when applied to the dichotomous variables in our analyses.

Funding

This work was supported by the National Institute on Aging Award (R01-AG060949); the Penn State Population Research Institute, which is supported by an infrastructure grant by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2C-HD041025) and a NIH training grant (T32HD007514); the Government of Canada—Canadian Institutes of Health Research (grant/award number: MYB-150262); and the Social Sciences and Humanities Research Council of Canada (grant/award number: 435-2017-0618, 890-2016-9000).

Conflicts of Interest

None declared.

Supplementary Material

gbaa109_suppl_Supplementary_Appendix
Click here for additional data file. (135.5KB, docx)

Acknowledgments

We thank Shawn Bauldry for comments on a draft. See Supplementary Appendix A for acknowledgments of data providers.

Author Contributions

L. Newmyer and A. Verdery planned the study; L. Newmyer and A. Verdery analyzed data; and L. Newmyer, A. Verdery, R. Margolis, and L. Pessin wrote the article.

References

  1. Ali, A, & Barnagarwala, T (2018, April 29). You are not the only one: India stares at a loneliness epidemic. The Indian Express. Retrieved from https://indianexpress.com/article/express-sunday-eye/you-are-not-the-only-one-5154976/ [Google Scholar]
  2. Baumeister, R F, & Leary, M R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529. doi: 10.1037/0033-2909.117.3.497 [DOI] [PubMed] [Google Scholar]
  3. Bonett, D G. (2007). Transforming odds ratios into correlations for meta-analytic research. The American Psychologist, 62(3), 254–255. doi: 10.1037/0003-066X.62.3.254 [DOI] [PubMed] [Google Scholar]
  4. Caci, H M. (2000). CORTESTI: Stata module to test equality of two correlation coefficients [Computer software]. Boston College Department of Economics.
  5. Cacioppo, J T, Hawkley, L C, Crawford, L E, Ernst, J M, Burleson, M H, Kowalewski, R B, Malarkey, W. B., Van Cauter, E., & Berntson, G G. (2002). Loneliness and health: Potential mechanisms. Psychosomatic Medicine, 64(3), 407–417. doi: 10.1097/00006842-200205000-00005 [DOI] [PubMed] [Google Scholar]
  6. Cornwell, E Y, & Waite, L J. (2009). Measuring social isolation among older adults using multiple indicators from the NSHAP study. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 64(Suppl. 1), 38–46. doi: 10.1093/geronb/gbp037 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Coyle, C E, & Dugan, E. (2012). Social isolation, loneliness and health among older adults. Journal of Aging and Health, 24(8), 1346–1363. doi: 10.1177/0898264312460275 [DOI] [PubMed] [Google Scholar]
  8. Cutrona, C E, & Russell, D W. (1987). The provisions of social relationships and adaptation to stress. In W. H. Jones & D. Perlman (Eds.), Advances in Personal Relationships, (Vol. 1, pp. 37–67). JAI Press. [Google Scholar]
  9. de Jong Gierveld, J. (1989). Personal relationships, social support, and loneliness. Journal of Social and Personal Relationships, 6, 197–221. doi: 10.1177/026540758900600204 [DOI] [Google Scholar]
  10. de Jong Gierveld, J, & Kamphuls, F. (1985). The development of a Rasch-Type loneliness scale. Applied Psychological Measurement, 9(3), 289–299. doi: 10.1177/014662168500900307 [DOI] [Google Scholar]
  11. de Jong Gierveld, J, & van Tillburg, T. (2006). A 6-item scale for overall, emotional, and social loneliness. Research on Aging, 28(5), 582–598. doi: 10.1177/0164027506289723 [DOI] [Google Scholar]
  12. Fasano, G (2019, September 20). L’isolamento, la malattia, le difficoltà: Essere anziano in Italia. Corriere Della Sera. Retrieved from https://www.corriere.it/cronache/19_settembre_19/isolamento-malattia-difficolta-essere-anziano-italia-7a3d4cd4-db24-11e9-94b9-f72cb5920b7e.shtml?refresh_ce-cp [Google Scholar]
  13. Fokkema, T, De Jong Gierveld, J, & Dykstra, P A. (2012). Cross-national differences in older adult loneliness. The Journal of Psychology, 146(1–2), 201–228. doi: 10.1080/00223980.2011.631612 [DOI] [PubMed] [Google Scholar]
  14. Gerst-Emerson, K, & Jayawardhana, J. (2015). Loneliness as a public health issue: The impact of loneliness on health care utilization among older adults. American Journal of Public Health, 105(5), 1013–1019. doi: 10.2105/AJPH.2014.302427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hughes, M E, Waite, L J, Hawkley, L C, & Cacioppo, J T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on Aging, 26(6), 655–672. doi: 10.1177/0164027504268574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Idler, E L, & Benyamini, Y. (1997). Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior, 38(1), 21–37. doi: 10.2307/2955359 [DOI] [PubMed] [Google Scholar]
  17. Jérôme, B (2019, June 29). Face à la canicule, une veille très inégale des villes auprès des personnes âgées. Le Monde. Retrieved from https://www.lemonde.fr/societe/article/2019/06/29/face-a-la-canicule-une-veille-tres-inegale-des-villes-aupres-des-personnes-agees_5483139_3224.html [Google Scholar]
  18. Jylhä, M, Guralnik, J M, Ferrucci, L, Jokela, J, & Heikkinen, E. (1998). Is self-rated health comparable across cultures and genders? The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 53(3), 144–152. doi: 10.1093/geronb/53b.3.s144 [DOI] [PubMed] [Google Scholar]
  19. Lim, L L, & Kua, E H. (2011). Living alone, loneliness, and psychological well-being of older persons in Singapore. Current Gerontology and Geriatrics Research, 2011, 673181. doi: 10.1155/2011/673181 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Luo, Y, Hawkley, L C, Waite, L J, & Cacioppo, J T. (2012). Loneliness, health, and mortality in old age: A national longitudinal study. Social Science & Medicine (1982), 74(6), 907–914. doi: 10.1016/j.socscimed.2011.11.028 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Nummela, O, Seppänen, M, & Uutela, A. (2011). The effect of loneliness and change in loneliness on self-rated health (SRH): A longitudinal study among aging people. Archives of Gerontology and Geriatrics, 53(2), 163–167. doi: 10.1016/j.archger.2010.10.023 [DOI] [PubMed] [Google Scholar]
  22. Onishi, N (2017, November 30). A generation in Japan faces a lonely death. The New York Times. Retrieved from https://www.nytimes.com/2017/11/30/world/asia/japan-lonely-deaths-the-end.html [Google Scholar]
  23. Park, J (2019, April 3). Lonely in Korea? You’re not alone. The Korea Herald. Retrieved from http://www.koreaherald.com/view.php?ud=20190403000445
  24. Penning, M J, Liu, G, & Chou, P H B. (2014). Measuring loneliness among middle-aged and older adults: The UCLA and de Jong Gierveld loneliness scales. Social Indicators Research, 118(3), 1147–1166. doi: 10.1007/s11205-013-0461-1 [DOI] [Google Scholar]
  25. Perlman, D, & Peplau, L A. (1981). Toward a social psychology of loneliness. In Duck M & Gilmour R (Eds.), Personal relationships in disorder (pp. 31–56). Academic Press. doi: 10.4324/9781315445687 [DOI] [Google Scholar]
  26. Radloff, L S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. doi: 10.1177/014662167700100306 [DOI] [Google Scholar]
  27. Rivers, M, & Lee, L (2019, February 8). Isolated and abandoned: The heartbreaking reality of old age in rural China. CNN. Retrieved from https://www.cnn.com/2019/02/07/asia/china-elderly-people-new-year-intl/index.html [Google Scholar]
  28. Russell, D, Cutrona, C E, Rose, J, & Yurko, K. (1984). Social and emotional loneliness: An examination of Weiss’s typology of loneliness. Journal of Personality and Social Psychology, 46(6), 1313–1321. doi: 10.1037//0022-3514.46.6.1313 [DOI] [PubMed] [Google Scholar]
  29. Russell, D, Peplau, L A, & Cutrona, C E. (1980). The revised UCLA loneliness scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39(3), 472–480. doi: 10.1037//0022-3514.39.3.472 [DOI] [PubMed] [Google Scholar]
  30. Russell, D, Peplau, L A, & Ferguson, M L. (1978). Developing a measure of loneliness. Journal of Personality Assessment, 42(3), 290–294. doi: 10.1207/s15327752jpa4203_11 [DOI] [PubMed] [Google Scholar]
  31. Sermat, V. (1978). Sources of loneliness. Essence, 2(4), 271–276. [Google Scholar]
  32. Shiovitz-Ezra, S, & Ayalon, L. (2012). Use of direct versus indirect approaches to measure loneliness in later life. Research on Aging, 34(5), 572–591. doi: 10.1177/0164027511423258 [DOI] [Google Scholar]
  33. Troya, M S (2019, April 2). Más de 850.000 personas mayores de 80 años viven solas en España. El País. Retrieved from https://elpais.com/sociedad/2019/04/02/actualidad/1554207493_844264.html [Google Scholar]
  34. Victor, C, Grenade, L, & Boldy, D. (2005). Measuring loneliness in later life: A comparison of differing measures. Reviews in Clinical Gerontology, 15, 63–70. doi: 10.1017/S0959259805001723 [DOI] [Google Scholar]
  35. von Soest, T, Luhmann, M, Hansen, T, & Gerstorf, D. (2020). Development of loneliness in midlife and old age: Its nature and correlates. Journal of Personality and Social Psychology, 118(2), 388–406. doi: 10.1037/pspp0000219 [DOI] [PubMed] [Google Scholar]
  36. Weiss, R S. (1973). Loneliness: The experience of emotional and social isolation. MIT Press. [Google Scholar]
  37. Yang, K, & Victor, C. (2011). Age and loneliness in 25 European nations. Ageing and Society, 31, 1368–1388. doi: 10.1017/S0144686X1000139X [DOI] [Google Scholar]
  38. Yang, K, & Victor, C R. (2008). The prevalence of and risk factors for loneliness among older people in China. Ageing and Society, 28, 305–327. doi: 10.1017/S0144686X07006848 [DOI] [Google Scholar]
  39. Yeginsu, C (2018, January 17). UK appoints a “minister for loneliness.” The New York Times. Retrieved from https://www.nytimes.com/2018/01/17/world/europe/uk-britain-loneliness.html [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

gbaa109_suppl_Supplementary_Appendix
Click here for additional data file. (135.5KB, docx)

Articles from The Journals of Gerontology Series B: Psychological Sciences and Social Sciences are provided here courtesy of Oxford University Press

RESOURCES