Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-22T18:17:09.957Z Has data issue: false hasContentIssue false

Surrogate inaccuracy in predicting older adults’ desire for life-sustaining interventions in the event of decisional incapacity: is it due in part to erroneous quality-of-life assessments?

Published online by Cambridge University Press:  06 March 2017

Gina Bravo*
Affiliation:
Department of Community Health Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada Research Centre on Aging, University Institute of Geriatrics of Sherbrooke, Sherbrooke, Quebec, Canada
Modou Sene
Affiliation:
Research Centre on Aging, University Institute of Geriatrics of Sherbrooke, Sherbrooke, Quebec, Canada
Marcel Arcand
Affiliation:
Research Centre on Aging, University Institute of Geriatrics of Sherbrooke, Sherbrooke, Quebec, Canada Department of Family Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Quebec, Canada
*
Correspondence should be addressed to: Gina Bravo, PhD, Research Centre on Aging, University Institute of Geriatrics of Sherbrooke, 1036 South Belvedere Street, Sherbrooke Quebec, J1H 4C4, Canada. Phone: +1-819-780-2220, ext. 45244; Fax: +1-819-829-7141. E-mail: [email protected].
Get access

Abstract

Background:

Family members are often called upon to make decisions for an incapacitated relative. Yet they have difficulty predicting a loved one's desire to receive treatments in hypothetical situations. We tested the hypothesis that this difficulty could in part be explained by discrepant quality-of-life assessments.

Methods:

The data come from 235 community-dwelling adults aged 70 years and over who rated their quality of life and desire for specified interventions in four health states (current state, mild to moderate stroke, incurable brain cancer, and severe dementia). All ratings were made on Likert-type scales. Using identical rating scales, a surrogate chosen by the older adult was asked to predict the latter's responses. Linear mixed models were fitted to determine whether differences in quality-of-life ratings between the older adult and surrogate were associated with surrogates’ inaccuracy in predicting desire for treatment.

Results:

The difference in quality-of-life ratings was a significant predictor of prediction inaccuracy for the three hypothetical health states (p < 0.01) and nearly significant for the current health state (p = 0.077). All regression coefficients were negative, implying that the more the surrogate overestimated quality of life compared to the older adult, the more he or she overestimated the older adult's desire to be treated.

Conclusion:

Discrepant quality-of-life ratings are associated with surrogates’ difficulty in predicting desire for life-sustaining interventions in hypothetical situations. This finding underscores the importance of discussing anticipated quality of life in states of cognitive decline, to better prepare family members for making difficult decisions for their loved ones.

Trial Registration number:

ISRCTN89993391

Type
Paper of the Month
Copyright
Copyright © International Psychogeriatric Association 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716723.CrossRefGoogle Scholar
Albrecht, G. L. and Devilieger, P. J. (1999). The disability paradox: high quality of life against all odds. Social Science in Medicine, 48, 977988.CrossRefGoogle ScholarPubMed
Banerjee, S. et al. (2009). What do we know about quality of life in dementia? A review of the emerging evidence on the predictive and explanatory value of disease specific measures of health related quality of life in people with dementia. International Journal of Geriatric Psychiatry, 24, 1524.Google Scholar
Barrio-Cantalejo, I. M. et al. (2009). Advance directives and proxies’ predictions about patients’ treatment preferences. Nursing Ethics, 16, 93109.Google Scholar
Bravo, G. et al. (2012). Promoting advance directives for health care and research among older adults: a randomized controlled trial. BMC Medical Ethics, 13, doi: 10.1186/1472-6939-13-1.CrossRefGoogle ScholarPubMed
Bravo, G. et al. (2016a). Promoting advance care planning among community-based older adults: a randomized controlled trial. Patient Education & Counseling, 99, 17851797. doi: 10.1016/j.pec.2016.05.009.CrossRefGoogle ScholarPubMed
Bravo, G., Sene, M. and Arcand, M. (2017). Reliability of health-related quality-of-life assessments made by older adults and significant others for health states of increasing cognitive impairment. Health and Quality of Life Outcomes 15, 4, doi: 10.1186/s12955-016-0579-3.CrossRefGoogle ScholarPubMed
Bravo, G., Sene, M., Arcand, M. and Dubois, M. F. (2016b). To what extent do quality-of-life ratings influence older adults’ preferences regarding future health care and research participation? International Journal of Health Preference Research, 1, 1626.Google Scholar
Ditto, P. H. et al. (2001). Advance directives as acts of communication: a randomized controlled trial. Archives of Internal Medicine, 161, 421430.Google Scholar
Evans, S. and Huxley, P. (2005). Adaptation, response shift and quality of life ratings in mentally well and unwell groups. Quality of Life Research, 14, 17191732.CrossRefGoogle ScholarPubMed
Fagerlin, A., Ditto, P. H., Danks, J. H., Houts, R. M. and Smucker, W. D. (2001). Projection in surrogate decision about life-sustaining medical treatments. Health Psychology, 20, 166175.Google Scholar
Fagerlin, A. and Schneider, C. E. (2004). Enough. The failure of the living will. Hastings Center Report, 34, 3042.CrossRefGoogle ScholarPubMed
Gifford, J. M., Husain, N., Dinglas, V. D., Colantuoni, E. and Needham, D. M. (2010). Baseline quality of life before intensive care: a comparison of patient versus proxy responses. Critical Care Medicine, 38, 855860.Google Scholar
Hickman, S. E., Hammes, B. J., Moss, A. H. and Tolle, S. W. (2005). Hope for the future: achieving the original intent of advance directives. Hastings Center Report, Nov-Dec, Spec No: S26–S30.Google Scholar
Kirchhoff, K. T., Hammes, B. J., Kehl, K. A., Briggs, L. A. and Brown, R. L. (2010). Effect of a disease-specific planning intervention on surrogate understanding of patient goals for future medical treatment. Journal of the American Geriatrics Society, 58, 1233–1140.CrossRefGoogle ScholarPubMed
McCulloch, C. E. and Searle, S. R. (2001). Generalized, Linear, and Mixed Models. Wiley Series in Probability and Statistics. New York: John Wiley & Sons, Inc. pp. 156186.Google Scholar
Moorman, S. M. and Carr, D. (2008). Spouses’ effectiveness as end-of-life health care surrogates: accuracy, uncertainty, and errors of overtreatment or undertreatment. The Gerontologist, 48, 811819.Google Scholar
Moyle, W., Murfield, J. E., Griffiths, S. G. and Venturato, L. (2011). Assessing quality of life of older people with dementia: a comparison of quantitative self-report and proxy accounts. Journal of Advanced Nursing, 68, 22372246.CrossRefGoogle ScholarPubMed
Pearlman, R. A., Starks, H., Cain, K. C. and Cole, W. G. (2005). Improvements in advance care planning in the veterans affairs system. Results of a multifaceted intervention. Archives of Internal Medicine, 165, 667674.CrossRefGoogle ScholarPubMed
Pruchno, R. A., Lemay, E. P. Jr, Field, L. and Levinsky, N. G. (2005). Spouse as health care proxy for dialysis patients: whose preferences matter?. The Gerontologist, 45, 812819.CrossRefGoogle ScholarPubMed
Schwartz, C. E. et al. (2002). Early intervention in planning end-of-life care with ambulatory geriatric patients. Archives of Internal Medicine, 162, 16111618.Google Scholar
Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461464.CrossRefGoogle Scholar
Selya, A. S., Rose, J. S., Dierker, L. C., Hedeker, D. and Mermelatein, R. J. (2012). A practical guide to calculating cohen's f(2), a measure of local effect size, from PROC MIXED. Frontiers in Psychology, 3, 111. doi: 10.3389/fpsyg.2012.00111.Google Scholar
Shalowitz, D. I., Garrett-Mayer, E. and Wendler, D. (2006). The accuracy of surrogate decision makers. A systematic review. Archives of Internal Medicine, 166, 493497.Google Scholar
Sneeuw, K. C., Sprangers, M. A. and Aaronson, N. K. (2002). The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease. Journal of Clinical Epidemiology, 55, 11301143.Google Scholar
Sudore, R. L. and Fried, T. R. (2010). Redefining the “planning” in advance care planning: preparing for end-of-life decision making. Annals of Internal Medicine, 153, 256261.Google Scholar
Torke, A. M. et al. (2014). Scope and outcomes of surrogate decision making among hospitalized older adults. JAMA Internal Medicine, 174, 370377.Google Scholar
Verbeke, G. and Molenberghs, G. (Eds.). (1997). Linear Mixed Models in Practice: A SAS-Oriented Approach (Vol. 126). New York: Springer Science & Business Media.Google Scholar
Winter, L. and Parks, S. M. (2012). Elders’ preferences for life-prolonging treatment and their proxies’ substituted judgment: influence of the elders’ current health. Journal of Aging & Health, 24, 11571178.Google Scholar
Zettel-Watson, L., Ditto, P. H., Danks, J. and Smucker, W. D. (2008). Actual and perceived gender differences in the accuracy of surrogate decisions about life-sustaining medical treatment among older spouses. Death Studies, 32, 273290.Google Scholar
Supplementary material: File

Bravo supplementary material

Table S1

Download Bravo supplementary material(File)
File 14.6 KB