Top

Quality of Life Research

Gepubliceerd in:

19-11-2016

Does the EQ-5D capture the effects of physical and mental health status on life satisfaction among older people? A path analysis approach

Auteurs: Eithne Sexton, Kathleen Bennett, Tom Fahey, Caitriona Cahir

Gepubliceerd in: Quality of Life Research | Uitgave 5/2017

Abstract

Purpose

To examine the extent to which EQ-5D utility scores capture the effect of mental and physical health status on life satisfaction (LS) in older adults.

Methods

Retrospective cohort study of 884 patients aged ≥70 years from 15 general practices in Ireland, including medical records, pharmacy claims, and self-completion questionnaire. Path analysis was used to evaluate the direct and indirect effects of: (1) chronic disease burden (based on medications data); (2) activity limitation (basic and instrumental activities of daily living); (3) anxiety symptoms and; (4) depressive symptoms (Hospital Anxiety and Depression Scale) on LS (Life Satisfaction Index Z), via a utility score based on responses to the EQ-5D scale. Utility scores were calculated using UK time trade-off utility weights. Covariates included age and socioeconomic status.

Results

The final path model fitted the data well (goodness of fit χ² = 7.5, df (7), p = 0.37). The direct effects of chronic disease burden and disability on LS were not statistically significant and were excluded from the final model, indicating that EQ-5D score mediated 100% of the total effect on LS. The direct and indirect effects of anxiety and depression on LS were statistically significant, but the size of the indirect effect was small (4% of the total effect for anxiety and 6% of the total effect for depression).

Conclusion

The EQ-5D does not adequately capture the effects of anxiety and depression on LS among older adults, suggesting that it may lead to inaccurate assessments of the effectiveness of interventions in this cohort.

vorige artikel Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L

volgende artikel Using EQ-5D-3L and OAB-5D to assess changes in the health-related quality of life of men with lower urinary tract symptoms associated with benign prostatic hyperplasia

Alleen toegankelijk voor geautoriseerde gebruikers

EuroQoL Group. (1990). EuroQol—a new facility for the measurement of health-related quality of life. Health Policy, 16, 199–208. doi:10.1016/0168-8510(90)90421-9.CrossRef

Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA: The Journal of the American Medical Association, 273(1), 59–65. http://www.ncbi.nlm.nih.gov/pubmed/7996652.

Ferrans, C. E., Zerwic, J. J., Wilbur, J. E., & Larson, J. L. (2005). Conceptual model of health-related quality of life. Journal of Nursing Scholarship, 37(4), 336–42. http://www.ncbi.nlm.nih.gov/pubmed/16396406.

Camfield, L., & Skevington, S. M. (2008). On subjective well-being and quality of life. Journal of Health Psychology, 13(6), 764–775. doi:10.1177/1359105308093860.CrossRefPubMed

Ryff, C. D., & Singer, B. H. (2008). Know thyself and become what you are: A eudaimonic approach to psychological well-being. Journal of Happiness Studies, 9(1), 13–39. doi:10.1007/s10902-006-9019-0.CrossRef

Mulhern, B., Mukuria, C., Barkham, M., Knapp, M., Byford, S., Soeteman, D., & Brazier, J. (2012). Using preference based measures in mental health conditions: The psychometric validity of the EQ-5D and SF-6D (No. 13/04). HEDS Discussion Paper.

Peasgood, T., Brazier, J., & Papaionnou, D. (2011). A sysyematic review of the validity and responsiveness of EQ-5D and SF-6D for depression and anxiety (No. 12/15). HEDS Discussion Paper. http://eprints.whiterose.ac.uk/74892.

Burström, K., Johannesson, M., & Diderichsen, F. (2001). Swedish population health-related quality of life results using the EQ-5D. Quality of Life Research, 10, 621–635. http://link.springer.com/article/10.1023/A:1013171831202.

Brazier, J. (2010). Is the EQ-5D fit for purpose in mental health? British Journal of Psychiatry, 197(5), 348–349. doi:10.1192/bjp.bp.110.082453.CrossRefPubMed

10.

Dolan, P. (2013). Addressing misconceptions in valuing health. Expert Review of Pharmacoeconomics and Outcomes Research, 13(1), 1–3. doi:10.1586/erp.12.90.CrossRefPubMed

11.

Dolan, P., & Metcalfe, R. (2012). Valuing health: A brief report on subjective well-being versus preferences. Medical Decision Making, 32,578–582. doi:10.1177/0272989X11435173

12.

Peeters, Y., & Stiggelbout, A. M. (2010). Health state valuations of patients and the general public analytically compared: A meta-analytical comparison of patient and population health state utilities. Value in Health, 13(2), 306–309. doi:10.1111/j.1524-4733.2009.00610.x.CrossRefPubMed

13.

Gerhards, S. A., Evers, S. M., Sabel, P. W., & Huibers, M. J. (2011). Discrepancy in rating health-related quality of life of depression between patient and general population. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 20(2), 273–279. doi:10.1007/s11136-010-9746-x.CrossRef

14.

Pyne, J. M., Fortney, J. C., Tripathi, S., Feeny, D., Ubel, P., & Brazier, J. (2009). How bad is depression? Preference score estimates from depressed patients and the general population. Health Services Research, 44(4), 1406–1423. doi:10.1111/j.1475-6773.2009.00974.x.CrossRefPubMedPubMedCentral

15.

Papageorgiou, K., Vermeulen, K. M., Schroevers, M. J., Stiggelbout, A. M., Buskens, E., Krabbe, P. F. M., et al. (2015). Do individuals with and without depression value depression differently? And if so, why? Quality of Life Research, 24(11), 2565–2575. doi:10.1007/s11136-015-1018-3.CrossRefPubMedPubMedCentral

16.

Ubel, P. A., Loewenstein, G., Schwarz, N., & Smith, D. (2005). Misimagining the unimaginable: The disability paradox and health care decision making. Health Psychology, 24(4), S57–S62. doi:10.1037/0278-6133.24.4.S57.CrossRefPubMed

17.

Ubel, P. A., Loewenstein, G., & Jepson, C. (2003). Whose quality of life? A commentary exploring discrepancies between health state evaluations of patients and the general public. Quality of Life Research, 12(6), 599–607.CrossRefPubMed

18.

Graham, C., Higuera, L., & Lora, E. (2011). Which health conditions cause the most unhappiness. Health Economics, 20, 1431–1447. doi:10.1002/hec.CrossRefPubMed

19.

Böckerman, P., Johansson, E., & Saarni, S. I. (2011). Do established health-related quality-of-life measures adequately capture the impact of chronic conditions on subjective well-being? Health policy (Amsterdam, Netherlands), 100(1), 91–95. doi:10.1016/j.healthpol.2010.10.008.CrossRef

20.

Richardson, J., Chen, G., Khan, M. A., & Iezzi, A. (2015). Can multi-attribute utility instruments adequately account for subjective well-being? Medical Decision Making, 35(3), 292–304. doi:10.1177/0272989X14567354.CrossRefPubMed

21.

Cahir, C., Bennett, K., Teljeur, C., & Fahey, T. (2014). Potentially inappropriate prescribing and adverse health outcomes in community dwelling older patients. British Journal of Clinical Pharmacology, 77(1), 201–210. doi:10.1111/bcp.12161.CrossRefPubMed

22.

Rabin, R., & de Charro, F. (2001). EQ-5D: A measure of health status from the EuroQol Group. Annals of Medicine, 33(5), 337–343. doi:10.3109/07853890109002087.CrossRefPubMed

23.

Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108. http://www.jstor.org/stable/10.2307/3767472.

24.

Neugarten, B. L., Havinghurst, R. J., & Tobin, S. S. (1961). The measurement of life satisfaction. Journal of Gerontology, 16, 134–143. doi:10.1093/geronj/16.2.134.CrossRefPubMed

25.

Adams, D. (1969). Analysis of a life satisfaction index. Journal of Gerontology, 24, 470–474.CrossRefPubMed

26.

McDowell, I. (2010). Measures of self-perceived well-being. Journal of Psychosomatic Research, 69(1), 69–79. doi:10.1016/j.jpsychores.2009.07.002.CrossRefPubMed

27.

Wallace, K. A., & Wheeler, A. J. (2002). Reliability generalization of the life satisfaction index. Educational and Psychological Measurement, 62(4), 674–684. doi:10.1177/0013164402062004009.CrossRef

28.

Sloan, K. L., Sales, A. E., Liu, C.-F., Fishman, P., Nichol, P., Suzuki, N. T., et al. (2003). Construction and characteristics of the RxRisk-V: A VA-adapted pharmacy-based case-mix instrument. Medical Care, 41(6), 761–774. doi:10.1097/01.MLR.0000064641.84967.B7.PubMed

29.

WHO Collaborating Centre for Drug Statistics Methodology. (2010). Anatomical therapeutic classification (ATC) classification index. Oslo: WHO Collaborating Centre for Drug Statistics Methodology.

30.

Fishman, P. A., Goodman, M. J., Hornbrook, M. C., Meenan, R. T., Bachman, D. J., & Rosetti, M. C. O. (2003). Risk adjustment using automated ambulatory pharmacy data. Medical Care, 41(1), 84–99. doi:10.1097/00005650-200301000-00011.CrossRefPubMed

31.

Saliba, D., Elliott, M., Rubenstein, L. Z., Solomon, D. H., Young, R. T., Kamberg, C. J., et al. (2001). The vulnerable elders survey: A tool for identifying vulnerable older people in the community. Journal of the American Geriatrics Society, 49(12), 1691–1699. doi:10.1046/j.1532-5415.2001.49281.x.CrossRefPubMed

32.

Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67(6), 361–370. doi:10.1111/j.1600-0447.1983.tb09716.x.CrossRefPubMed

33.

Snaith, R. P. (2003). The hospital anxiety and depression scale. Health and quality of life outcomes, 1, 29. doi:10.1186/1477-7525-1-29.CrossRefPubMedPubMedCentral

34.

Kelly, A., & Teljeur, C. (2007). The national deprivation index for health and health services research. Dublin: Small Area Health Research Unit.

35.

Central Statistics Office. (2006). Census 2006. Dublin: Central Statistics Office, Information Section.

36.

Sousa, K. H., & Kwok, O.-M. (2006). Putting Wilson and Cleary to the test: Analysis of a HRQOL conceptual model using structural equation modeling. Quality of Life Research, 15(4), 725–737. doi:10.1007/s11136-005-3975-4.CrossRefPubMed

37.

Sullivan, M. D., Kempen, G. I., Van Sonderen, E., & Ormel, J. (2000). Models of health-related quality of life in a population of community-dwelling Dutch elderly. Quality of Life Research, 9(7), 801–810. http://www.ncbi.nlm.nih.gov/pubmed/11297022.

38.

Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Multivariate applications series. New York: Routledge.

39.

Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods, 16(2), 93–115. doi:10.1037/a0022658.CrossRefPubMed

40.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.CrossRefPubMed

41.

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press.

42.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.CrossRef

43.

Kind, P., Hardman, G., & Macran, S. (1999). UK population norms for EQ-5D (No. 172). Centre for Health Economics Discussion Paper Series. York: Centre for Health Economics. http://www.york.ac.uk/che/pdf/DP172.pdf.

44.

McTaggart-Cowan, H., Tsuchiya, A., O’Cathain, A., & Brazier, J. (2011). Understanding the effect of disease adaptation information on general population values for hypothetical health states. Social Science and Medicine, 72(11), 1904–1912. doi:10.1016/j.socscimed.2011.03.036.CrossRefPubMed

45.

Richardson, J., Iezzi, A., Khan, M. A., Chen, G., & Maxwell, A. (2015). Measuring the sensitivity and construct validity of 6 utility instruments in 7 disease areas. Medical Decision Making,. doi:10.1177/0272989X15613522.

46.

National Institute for Health and Care Excellence. (2013). Guide to the methods of technology appraisal 2013. National Institute for Health and Care Excellence. http://www.nice.org.uk/media/D45/1E/GuideToMethodsTechnologyAppraisal2013.pdf.

47.

Health Information and Quality Authority. (2010). Guidance on developing key performance indicators and minimum data sets to monitor healthcare Quality. Health (San Francisco). http://www.hiqa.ie/media/pdfs/HI_KPI_Guidelines.pdf.

48.

American Geriatrics Society Expert Panel on the Care of Older Adults with Multimorbidity. (2012). Patient-centered care for older adults with multiple chronic conditions: A stepwise approach from the American Geriatrics. Journal of the American Geriatrics Society, 60, 1957–1968. doi:10.1111/j.1532-5415.2012.04187.x.CrossRefPubMedCentral

49.

Patten, S. B., Williams, J. V., Lavorato, D. H., Bulloch, A. G. M., Currie, C., & Emery, H. (2014). Depression and painful conditions: Patterns of association with health status and health utility ratings in the general population. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 23(1), 363–371. doi:10.1007/s11136-013-0449-y.CrossRef

50.

Makai, P., Brouwer, W. B. F., Koopmanschap, M. A., Stolk, E. A., & Nieboer, A. P. (2014). Quality of life instruments for economic evaluations in health and social care for older people: A systematic review. Social Science and Medicine (1982), 102, 83–93. doi:10.1016/j.socscimed.2013.11.050.CrossRef

51.

Al-Janabi, H., Flynn, T. N., & Coast, J. (2012). Development of a self-report measure of capability wellbeing for adults: The ICECAP-A. Quality of Life Research, 21(1), 167–176. doi:10.1007/s11136-011-9927-2.CrossRefPubMed

52.

Al-Janabi, H., Peters, T. J., Brazier, J., Bryan, S., Flynn, T. N., Clemens, S., et al. (2013). An investigation of the construct validity of the ICECAP-A capability measure. Quality of Life Research, 22(7), 1831–1840. doi:10.1007/s11136-012-0293-5.CrossRefPubMed

53.

Flynn, T. N., Huynh, E., Peters, T. J., Al-Janabi, H., Clemens, S., Moody, A., et al. (2015). Scoring the ICECAP-A capability instrument. Estimation of a UK general population tariff. Health Seconomics, 24, 258–269.

54.

55.

Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736. doi:10.1007/s11136-011-9903-x.CrossRefPubMedPubMedCentral

56.

Agborsangaya, C. B., Lahtinen, M., Cooke, T., & Johnson, J. A. (2014). Comparing the EQ-5D 3L and 5L: Measurement properties and association with chronic conditions and multimorbidity in the general population. Health and Quality of Life Outcomes, 12(1), 74. doi:10.1186/1477-7525-12-74.CrossRefPubMedPubMedCentral

57.

Janssen, M. F., Pickard, A. S., Golicki, D., Gudex, C., Niewada, M., Scalone, L., et al. (2013). Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study. Quality of Life Research, 22(7), 1717–1727. doi:10.1007/s11136-012-0322-4.CrossRefPubMed

Titel: Does the EQ-5D capture the effects of physical and mental health status on life satisfaction among older people? A path analysis approach
Auteurs: Eithne Sexton
Kathleen Bennett
Tom Fahey
Caitriona Cahir
Publicatiedatum: 19-11-2016
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 5/2017
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-016-1459-3

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Purpose

Methods

Results

Conclusion

Log in om toegang te krijgen

Andere artikelen Uitgave 5/2017

Quality of life, psychological characteristics, and adjustment in parents of children with Attention-Deficit/Hyperactivity Disorder

Education as a predictor of antidepressant and anxiolytic medication use after bereavement: a population-based record linkage study

Employing quality control and feedback to the EQ-5D-5L valuation protocol to improve the quality of data collection

Investigating acculturation orientations of patients with an immigration background and doctors in Canada: implications for medical advice adherence

The validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study

Evaluating and establishing national norms for mental wellbeing using the short Warwick–Edinburgh Mental Well-being Scale (SWEMWBS): findings from the Health Survey for England