Skip to main content
Log in

Age Effects of Frames of Reference in Self-Reports of Health, Well-Being, Fatigue and Pain

  • Published:
Applied Research in Quality of Life Aims and scope Submit manuscript

Abstract

Self-reports of health and well-being are central for population monitoring, so it is paramount that they are measured accurately. The goal of this study was to examine the impact of age on the use of the comparison standards or frames of reference (FoRs) in self-reports of health, life-satisfaction, fatigue, and pain, and to determine if the age-health outcome associations were affected by age differences in FoRs. Respondents (n = 2000) selected from the U.S. general population self-rated their life-satisfaction and health outcomes. Following this, they were asked to indicate if they used any comparisons (FoRs) when making their rating and the direction of these comparisons (upward, lateral or downward). Analyses examined (a) whether age groups differed in the type and direction of FoRs, and (b) whether age patterns in health, life-satisfaction, fatigue, and pain were altered when FoRs were statistically controlled. Compared to middle-aged and older people, younger respondents were more likely to compare themselves with other people when self-rating their health and life-satisfaction. They were also more likely to use a hypothetical situation when evaluating their pain and fatigue. Younger participants used lateral comparisons less often and downward comparisons more often than middle-aged and older participants. When these age differences in FoRs were statistically controlled, the observed age patterns in self-reported health outcomes were somewhat reduced. The results show that people of different ages use different FoRs when self-reporting their life-satisfaction and health outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig 1
Fig 2

Similar content being viewed by others

References

  • Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd ed.). New York: John Wiley & Sons.

    Book  Google Scholar 

  • Albert, S. (1977). Temporal Comparison Theory. Psychological Review, 84(6), 485–503. https://doi.org/10.1037//0033-295x.84.6.485.

    Article  Google Scholar 

  • Baron-Epel, O., & Kaplan, G. (2001). General subjective health status or age-related subjective health status: does it make a difference? Social Science & Medicine, 53(10), 1373–1381.

    Article  Google Scholar 

  • Baron-Epel, O., Shemy, G., & Carmel, S. (2004). Prediction of survival: a comparison between two subjective health measures in an elderly population. Social Science & Medicine, 58(10), 2035–2043. https://doi.org/10.1016/S0277-9536(03)00412-X.

    Article  Google Scholar 

  • Baum, C. F. (2006). An Introduction to Modern Econometrics Using Stata (pp. 236–242). College Station: Stata Press.

    Google Scholar 

  • Carstensen, L. L. (1992). Social and emotional patterns in adulthood: support for socioemotional selectivity theory. Psychology and Aging, 7(3), 331–338.

    Article  Google Scholar 

  • Cleeland, C. (1994). Pain assessment: global use of the Brief Pain Inventory. Annals of Academic Medicine Singapore, 23, 129–138.

    Google Scholar 

  • Cote, P., Cassidy, J. D., & Carroll, L. (2001). The treatment of neck and low back pain - Who seeks care? Who goes where? Medical Care, 39(9), 956–967. https://doi.org/10.1097/00005650-200109000-00006.

    Article  Google Scholar 

  • Dening, T. R., Chi, L. Y., Brayne, C., Huppert, F. A., Paykel, E. S., & O'Connor, D. W. (1998). Changes in self-rated health, disability and contact with services in a very elderly cohort: a 6-year follow-up study. Age and Ageing, 27(1), 23–33. https://doi.org/10.1093/ageing/27.1.23.

    Article  Google Scholar 

  • DeSalvo, K. B., Fan, V. S., McDonell, M. B., & Fihn, S. D. (2005). Predicting mortality and healthcare utilization with a single question. Health Services Research, 40(4), 1234–1246. https://doi.org/10.1111/j.1475-6773.2005.00404.x.

    Article  Google Scholar 

  • DeSalvo, K. B., Bloser, N., Reynolds, K., He, J., & Muntner, P. (2006). Mortality prediction with a single general self-rated health question. A meta-analysis. Journal of General Internal Medicine, 21(3), 267–275. https://doi.org/10.1111/j.1525-1497.2005.00291.x.

    Article  Google Scholar 

  • Diener, E., & Chan, M. Y. (2011). Happy People Live Longer: Subjective Well-Being Contributes to Health and Longevity. Applied Psychology: Health and Wellbeing, 3, 1–43.

    Google Scholar 

  • Docking, R. E., Fleming, J., Brayne, C., Zhao, J., Macfarlane, G. J., Jones, G. T., & Cambridge City over-75s Cohort Study, c. (2011). Epidemiology of back pain in older adults: prevalence and risk factors for back pain onset. Rheumatology (Oxford), 50(9), 1645–1653. https://doi.org/10.1093/rheumatology/ker175.

    Article  Google Scholar 

  • Fayers, P. M., Langston, A. L., Robertson, C., & group, P. T. (2007). Implicit self-comparisons against others could bias quality of life assessments. Journal of Clinical Epidemiology, 60(10), 1034–1039. https://doi.org/10.1016/j.jclinepi.2007.03.005.

    Article  Google Scholar 

  • Ferraro, K. F., & Wilkinson, L. R. (2015). Alternative Measures of Self-Rated Health for Predicting Mortality Among Older People: Is Past or Future Orientation More Important? Gerontologist, 55(5), 836–844. https://doi.org/10.1093/geront/gnt098.

    Article  Google Scholar 

  • Festinger, L. (1950). Informal Social Communication. Psychological Review, 57(5), 271–282. https://doi.org/10.1037/h0056932.

    Article  Google Scholar 

  • Festinger, L. (1954). A Theory of Social Comparison Processes. Human Relations, 7(2), 117–140. https://doi.org/10.1177/001872675400700202.

    Article  Google Scholar 

  • Fienberg, S. E., Loftus, E. F., & Tanur, J. M. (1985). Cognitive aspects of health survey methodology: an overview. The Milbank Memorial Fund Quarterly. Health and Society, 63(3), 547–564.

    Article  Google Scholar 

  • Franks, P., Gold, M. R., & Fiscella, K. (2003). Sociodemographics, self-rated health, and mortality in the US. Social Science & Medicine, 56(12), 2505–2514.

    Article  Google Scholar 

  • Hays, R. D., Liu, H. H., & Kapteyn, A. (2015). Use of Internet panels to conduct surveys. Behavior Research Methods, 47(3), 685–690. https://doi.org/10.3758/s13428-015-0617-9.

    Article  Google Scholar 

  • Heckhausen, J., & Brim, O. G. (1997). Perceived problems for self and others: Self-protection by social downgrading throughout adulthood. Psychology and Aging, 12(4), 610–619. https://doi.org/10.1037//0882-7974.12.4.610.

    Article  Google Scholar 

  • Junghaenel, D. U., Broderick, J. E., Schneider, S., May, M., Bolton, A., McCarrier, K. P., . . . Stone, A. A. (2018). Frames of Reference in Self-Reports of Health, Well-being, Fatigue, and Pain: A Qualitative Examination. Applied Research in Quality of Life, 31, 583-601.

    Google Scholar 

  • Kaplan, G., & Baron-Epel, O. (2003). What lies behind the subjective evaluation of health status? Social Science & Medicine, 56(8), 1669–1676.

    Article  Google Scholar 

  • Krause, N. M., & Jay, G. M. (1994). What do global self-rated health items measure? Medical Care, 32, 930–942.

    Article  Google Scholar 

  • Leinonen, R., Heikkinen, E., & Jylha, M. (2001). Predictors of decline in self-assessments of health among older people - a 5-year longitudinal study. Social Science & Medicine, 52(9), 1329–1341. https://doi.org/10.1016/S0277-9536(00)00249-5.

    Article  Google Scholar 

  • MacDonald, P. L., & Gardner, R. C. (2000). Type I error rate comparisons of post hoc procedures for I x J chi-square tables. Educational and Psychological Measurement, 60(5), 735–754. https://doi.org/10.1177/00131640021970871.

    Article  Google Scholar 

  • Mather, M. (2012). The emotion paradox in the aging brain. Annals of the New York Academy of Sciences, 1251, 33–49.

    Article  Google Scholar 

  • McCullagh, P., & Nelder, J. A. (1989). Generalized Linear Models. London: Chapman and Hall.

    Book  Google Scholar 

  • McCullough, M. E., & Laurenceau, J. P. (2004). Gender and the natural history of self-rated health: a 59-year longitudinal study. Health Psychology, 23(6), 651–655. https://doi.org/10.1037/0278-6133.23.6.651.

    Article  Google Scholar 

  • Mendoza, T. R., Wang, X. S., Cleeland, C. S., Morrissey, M., Johnson, B. A., Wendt, J. K., & Huber, S. L. (1999). The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer, 85(5), 1186–1196.

    Article  Google Scholar 

  • Ostbye, T., Krause, K. M., Norton, M. C., Tschanz, J., Sanders, L., Hayden, K., . . . Cache County, I. (2006). Ten dimensions of health and their relationships with overall self-reported health and survival in a predominately religiously active elderly population: the cache county memory study. Journal of the American Geriatrics Society, 54(2), 199-209. https://doi.org/10.1111/j.1532-5415.2005.00583.x

    Article  Google Scholar 

  • Peersman, W., Cambier, D., Maeseneer, J. D., & Willems, S. (2012). Gender, educational and age differences in meanings that underline global self-rated health. International Journal of Public Health, 57, 513–523.

    Article  Google Scholar 

  • Ricci, J., Chee, E., & Lorandeau, A. (2006). Fatigue in the US workforce: Prevalence and cost of lost productive work time. Value in Health, 9(3), A166–A166. https://doi.org/10.1016/S1098-3015(10)64818-8.

    Article  Google Scholar 

  • Ricci, J. A., Chee, E., Lorandeau, A. L., & Berger, J. (2007). Fatigue in the US workforce: Prevalence and implications for lost productive work time. Journal of Occupational and Environmental Medicine, 49(1), 1–10. https://doi.org/10.1097/01.jom.0000249782.60321.2a.

    Article  Google Scholar 

  • Roberts, G. (1999). Age effects and health appraisal: a meta-analysis. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 54(1), S24–S30.

    Article  Google Scholar 

  • Santhouse, A. M., Hotopf, M., & David, A. S. (2010). Chronic fatigue syndrome. BMJ, 340, c738. https://doi.org/10.1136/bmj.c738.

    Article  Google Scholar 

  • Sargent-Cox, K. A., Anstey, K. J., & Luszcz, M. A. (2008). Determinants of self-rated health items with different points of reference: implications for health measurement of older adults. Journal of Aging and Health, 20(6), 739–761. https://doi.org/10.1177/0898264308321035.

    Article  Google Scholar 

  • Sargent-Cox, K. A., Anstey, K. J., & Luszcz, M. A. (2010a). The choice of self-rated health measures matter when predicting mortality: evidence from 10 years follow-up of the Australian longitudinal study of ageing. BMC Geriatrics, 10, 18. https://doi.org/10.1186/1471-2318-10-18.

    Article  Google Scholar 

  • Sargent-Cox, K. A., Anstey, K. J., & Luszcz, M. A. (2010b). Patterns of longitudinal change in older adults' self-rated health: the effect of the point of reference. Health Psychology, 29(2), 143–152. https://doi.org/10.1037/a0017652.

    Article  Google Scholar 

  • Schnittker, J. (2005). When mental health becomes health: age and the shifting meaning of self-evaluations of general health. The Milbank Quarterly, 83(3), 397–423. https://doi.org/10.1111/j.1468-0009.2005.00407.x.

    Article  Google Scholar 

  • Schwarz, N. (1999). Self-reports: how the questions shape the answers. American Psychologist, 54, 93–105.

    Article  Google Scholar 

  • Seitsamo, J., & Klockars, M. (1997). Aging and changes in health. Scandinavian Journal of Work, Environment & Health, 23(Suppl 1), 27–35.

    Google Scholar 

  • Simon, J. G., De Boer, J. D., Joung, I. M. A., Bosma, H., & Mackenbach, J. P. (2005). How is your health in general? A qualitative study on self-assessed health. Perceived Health, 15, 200-208.

  • Srivastava, V. K., & Giles, D. E. A. (1987). Seemingly unrelated regression equations models: estimation and inference. New York: Marcel Dekker.

    Google Scholar 

  • Stone, A. A., Broderick, J. E., Schwartz, J. E., & Schwarz, N. (2008). Context effects in survey ratings of health, symptoms, and satisfaction. Medical Care, 46(7), 662–667. https://doi.org/10.1097/MLR.0b013e3181789387.

    Article  Google Scholar 

  • Suls, J., Marco, C. A., & Tobin, S. (1991). The Role of Temporal Comparison, Social-Comparison, and Direct Appraisal in the Elderly Self-Evaluations of Health. Journal of Applied Social Psychology, 21(14), 1125–1144. https://doi.org/10.1111/j.1559-1816.1991.tb00462.x.

    Article  Google Scholar 

  • Ubel, P. A., Jankovic, A., Smith, D., Langa, K. M., & Fagerlin, A. (2005). What is perfect health to an 85-year-old?: evidence for scale recalibration in subjective health ratings. Medical Care, 43(10), 1054–1057.

    Article  Google Scholar 

  • van't Leven, M., Zielhuis, G. A., van der Meer, J. W., Verbeek, A. L., & Bleijenberg, G. (2010). Fatigue and chronic fatigue syndrome-like complaints in the general population. European Journal of Public Health, 20(3), 251–257. https://doi.org/10.1093/eurpub/ckp113.

    Article  Google Scholar 

  • Vasseljen, O., Woodhouse, A., Bjorngaard, J. H., & Leivseth, L. (2013). Natural course of acute neck and low back pain in the general population: The HUNT study. Pain, 154(8), 1237–1244. https://doi.org/10.1016/j.pain.2013.03.032.

    Article  Google Scholar 

  • Venables, W. N., & Gardner, R. C. (2002). Modern Applied Statistics with S. New York: Springer.

    Book  Google Scholar 

  • Vuorisalmi, M., Lintonen, T., & Jylha, M. (2006). Comparative vs global self-rated health: associations with age and functional ability. Aging Clinical and Experimental Research, 18(3), 211–217.

    Article  Google Scholar 

  • Ware Jr., J. E., & Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Medical Care, 30(6), 473–483.

    Article  Google Scholar 

  • Ware, J. E., Kosinski, M., & Dewey, J. E. (2000). How to Score Version 2 of the SF-36 Health Survey. LincolnI: QualityMetric Incorporated.

    Google Scholar 

  • Williams, R. L. (2000). A note on robust variance estimation for cluster-correlated data. Biometrics, 56, 645–646.

    Article  Google Scholar 

  • Wrzus, C., Hänel, M., Wagner, J. & Neyer, F. J. (2013). Social network changes and life evensta across the life span: a meta-analysis. Psychological Bulletin, 139(1), 53–80.

  • Zhou, L., Lu, J., Chen, G., Dong, L., & Yao, Y. (2017). Is there a paradox of aging: When the negative aging stereotype meets the positivity effect in older adults. Experimental Aging Research, 43, 80–89.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by a grant from the National Institute on Aging (R01 AG042407, PI: Arthur A. Stone, Ph.D.)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ania Filus.

Ethics declarations

Disclosure

Arthur A. Stone is a Senior Scientist with the Gallup Organization, and a consultant for Adelphi Values, inc., and Precision Health Economics.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Filus, A., Junghaenel, D.U., Schneider, S. et al. Age Effects of Frames of Reference in Self-Reports of Health, Well-Being, Fatigue and Pain. Applied Research Quality Life 15, 35–54 (2020). https://doi.org/10.1007/s11482-018-9663-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11482-018-9663-7

Key words

Navigation