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What would people think? Perceived social norms, willingness to serve as a surrogate, and end-of-life treatment decisions

Published online by Cambridge University Press:  15 July 2020

Rachael Spalding*
Affiliation:
Department of Psychology, West Virginia University, MorgantownWV, USA
JoNell Strough
Affiliation:
Department of Psychology, West Virginia University, MorgantownWV, USA
Barry Edelstein
Affiliation:
Department of Psychology, West Virginia University, MorgantownWV, USA
*
Author for correspondence: Rachael Spalding, Department of Psychology, West Virginia University, Morgantown, WV26505, USA. E-mail: rls0046@mix.wvu.edu

Abstract

Background

Population aging has increased the prevalence of surrogate decision making in healthcare settings. However, little is known about factors contributing to the decision to become a surrogate and the surrogate medical decision-making process in general. We investigated how intrapersonal and social-contextual factors predicted two components of the surrogate decision-making process: individuals’ willingness to serve as a surrogate and their tendency to select various end-of-life treatments, including mechanical ventilation and palliative care options.

Method

An online sample (N = 172) of adults made hypothetical surrogate decisions about end-of-life treatments on behalf of an imagined person of their choice, such as a parent or spouse. Using self-report measures, we investigated key correlates of willingness to serve as surrogate (e.g., decision-making confidence, willingness to collaborate with healthcare providers) and choice of end-of-life treatments.

Results

Viewing service as a surrogate as a more typical practice in healthcare was associated with greater willingness to serve. Greater decision-making confidence, greater willingness to collaborate with patients’ physicians, and viewing intensive, life-sustaining end-of-life treatments (e.g., mechanical ventilation) as more widely accepted were associated with choosing more intensive end-of-life treatments.

Significance of results

The current study's consideration of both intrapersonal and social-contextual factors advances knowledge of two key aspects of surrogate decision making — the initial decision to serve as surrogate, and the surrogate's selection of various end-of-life treatment interventions. Providers can use information about the role of these factors to engage with surrogates in a manner that better facilitates their decision making. For instance, providers can be sensitive to potential cultural differences in surrogate decision-making tendencies or employing decision aids that bolster surrogates’ confidence in their decisions.

Type
Original Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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References

Allen-Burge, R and Haley, WE (1997) Individual differences and surrogate medical decisions: Differing preferences for life-sustaining treatments. Aging & Mental Health 1(2), 121131.CrossRefGoogle Scholar
Angus, D, Barnato, A, Linde-Zwirble, W, et al. (2004) Robert Wood Johnson Foundation ICU End-of-Life Peer Group. Use of intensive care at the end of life in the United States: an epidemiologic study. Critical Care Medicine 32, 638643.CrossRefGoogle Scholar
Arora, NK and McHorney, CA (2000) Patient preferences for medical decision making: Who really wants to participate?. Medical Care, 335341.CrossRefGoogle ScholarPubMed
Azoulay, É, Pochard, F, Chevret, S, et al. (2003) Family participation in care to the critically ill: Opinions of families and staff. Intensive Care Medicine 29(9), 14981504.CrossRefGoogle Scholar
Bettenhausen, K and Murnighan, JK (1985) The emergence of norms in competitive decision-making groups. Administrative Science Quarterly, 350372.CrossRefGoogle Scholar
Buhrmester, M, Kwang, T and Gosling, SD (2011) Amazon's Mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science 6(1), 35.CrossRefGoogle ScholarPubMed
Carleton, RN, Norton, MPJ and Asmundson, GJ (2007) Fearing the unknown: A short version of the Intolerance of Uncertainty Scale. Journal of Anxiety Disorders 21(1), 105117.CrossRefGoogle Scholar
Deutsch, M and Gerard, HB (1955) A study of normative and informational social influences upon individual judgment. The Journal of Abnormal and Social Psychology 51(3), 629.CrossRefGoogle Scholar
Ditto, PH, Danks, JH, Smucker, WD, et al. (2001) Advance directives as acts of communication: a randomized controlled trial. Archives of Internal Medicine 161(3), 421430.CrossRefGoogle ScholarPubMed
Eid, ME and Diener, EE (2006) Handbook of Multimethod Measurement in Psychology. Washington, DC: American Psychological Association.CrossRefGoogle Scholar
Field, A (2013) Discovering Statistics Using IBM SPSS Statistics. Thousand Oaks, CA: Sage.Google Scholar
Freeston, MH, Rhéaume, J, Letarte, H, et al. (1994) Why do people worry? Personality and Individual Differences 17(6), 791802.CrossRefGoogle Scholar
Frosch, DL and Kaplan, RM (1999) Shared decision making in clinical medicine: Past research and future directions. American Journal of Preventive Medicine 17(4), 285294.CrossRefGoogle ScholarPubMed
Gámez, W, Chmielewski, M, Kotov, R, et al. (2011) Development of a measure of experiential avoidance: The Multidimensional Experiential Avoidance Questionnaire. Psychological Assessment 23(3), 692.CrossRefGoogle ScholarPubMed
Gámez, W, Chmielewski, M, Kotov, R, et al. (2014) The brief experiential avoidance questionnaire: Development and initial validation. Psychological Assessment 26(1), 35.CrossRefGoogle ScholarPubMed
Ganzini, L, Lee, MA, Heintz, RT, et al. (1994) The effect of depression treatment on elderly patients’ preferences for life-sustaining medical therapy. The American Journal of Psychiatry 151(11), 1631.Google ScholarPubMed
Garvelink, MM, Boland, L, Klein, K, et al. (2019) Decisional conflict scale findings among patients and surrogates making health decisions: Part II of an anniversary review. Medical Decision Making 39(4), 316327.CrossRefGoogle ScholarPubMed
Goldstein, NJ, Cialdini, RB and Griskevicius, V (2008) A room with a viewpoint: Using social norms to motivate environmental conservation in hotels. Journal of Consumer Research 35(3), 472482.CrossRefGoogle Scholar
Goodman, JK, Cryder, CE and Cheema, A (2013) Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. Journal of Behavioral Decision Making 26(3), 213224.CrossRefGoogle Scholar
Gosling, SD, Vazire, S, Srivastava, S, et al. (2004) Should we trust web-based studies? A comparative analysis of six preconceptions about internet questionnaires. American Psychologist 59(2), 93.CrossRefGoogle ScholarPubMed
Grisso, T and Appelbaum, PS (1995) Comparison of standards for assessing patients’ capacities to make treatment decisions. American Journal of Psychiatry 152(7), 10331037.Google ScholarPubMed
Hare, J, Pratt, C and Nelson, C (1992) Agreement between patients and their self-selected surrogates on difficult medical decisions. Archives of Internal Medicine 152(5), 10491054.CrossRefGoogle ScholarPubMed
Howell, JL, Ratliff, KA and Shepperd, JA (2016) Automatic attitudes and health information avoidance. Health Psychology 35(8), 816.CrossRefGoogle ScholarPubMed
Howell, JL and Shepperd, JA (2016) Establishing an information avoidance scale. Psychological Assessment 28(12), 1695.CrossRefGoogle ScholarPubMed
Joireman, J, Shaffer, MJ, Balliet, D, et al. (2012) Promotion orientation explains why future-oriented people exercise and eat healthy: Evidence from the two-factor consideration of future consequences-14 scale. Personality and Social Psychology Bulletin 38(10), 12721287.CrossRefGoogle ScholarPubMed
Kohn, NA (2015) Matched preferences and values: A new approach to selecting legal surrogates. San Diego Law Review 52, 399.Google Scholar
Li, K, Fei, M, Irwin, GW, et al. (2007). Bio-Inspired Computational Intelligence and Applications: International Conference on Life System Modeling, and Simulation, LSMS 2007, Proceedings (Vol. 4688), Shanghai, China, September 14–17. Springer Science & Business Media.Google Scholar
Libbus, MK and Russell, C (1995) Congruence of decisions between patients and their potential surrogates about life-sustaining therapies. Image: The Journal of Nursing Scholarship 27(2), 135140.Google ScholarPubMed
Lord, K, Livingston, G and Cooper, C (2015) A systematic review of barriers and facilitators to and interventions for proxy decision-making by family carers of people with dementia. International Psychogeriatrics 27(8), 13011312.CrossRefGoogle ScholarPubMed
Majesko, A, Hong, SY, Weissfeld, L, et al. (2012) Identifying family members who may struggle in the role of surrogate decision maker. Critical Care Medicine 40(8), 2281.CrossRefGoogle ScholarPubMed
Marks, MA and Arkes, HR (2008) Patient and surrogate disagreement in end-of-life decisions: Can surrogates accurately predict patients’ preferences? Medical Decision Making 28(4), 524531.CrossRefGoogle ScholarPubMed
Maxwell, SE, Kelley, K and Rausch, JR (2008) Sample size planning for statistical power and accuracy in parameter estimation. Annual Review of Psychology 59, 537563.CrossRefGoogle ScholarPubMed
National POLST Paradigm. (2018). http://polst.org/ (accessed January 31, 2018).Google Scholar
Parks, SM, Winter, L, Santana, AJ, et al. (2011) Family factors in end-of-life decision-making: Family conflict and proxy relationship. Journal of Palliative Medicine, 14(2), 179184.CrossRefGoogle ScholarPubMed
Patient Protection and Affordable Care Act (2010). Public Law No. 111-148, Section 3506.Google Scholar
Postmes, T, Spears, R and Cihangir, S (2001) Quality of decision making and group norms. Journal of Personality and Social Psychology 80(6), 918.CrossRefGoogle ScholarPubMed
Qiao, S, Li, X, Zhou, Y, et al. (2015) Factors influencing the decision-making of parental HIV disclosure: a socio-ecological approach. AIDS (London, England) 29(0 1), S25.CrossRefGoogle ScholarPubMed
Reno, RR, Cialdini, RB and Kallgren, CA (1993) The transsituational influence of social norms. Journal of Personality and Social Psychology 64(1), 104.CrossRefGoogle Scholar
Riley, G and Lubitz, J (2010) Long-term trends in Medicare payments in the last year of life. Health Service Research 45, 565576.CrossRefGoogle ScholarPubMed
Roth, S and Cohen, LJ (1986) Approach, avoidance, and coping with stress. American Psychologist 41(7), 813.CrossRefGoogle ScholarPubMed
Shalowitz, DI, Garrett-Mayer, E and Wendler, D (2006) The accuracy of surrogate decision makers: a systematic review. Archives of Internal Medicine 166(5), 493497.CrossRefGoogle ScholarPubMed
Shapiro, SP (2007) When life imitates art: Surrogate decision making at the end of life. Topics in Stroke Rehabilitation 14(4), 8092.CrossRefGoogle ScholarPubMed
Spalding, R and Edelstein, B (2019) Factors predicting collaborative willingness of surrogates making medical decisions on the Physicians Order for Scope of Treatment (POST). Aging and Mental Health, 110.Google Scholar
Speilberger, CD, Gorsuch, RL, Lushene, R, et al. (1983) State-trait Anxiety Inventory for Adults. Redwood City: Mind Garden Inc.Google Scholar
Stacey, D, Légaré, F, Lewis, K, et al. (2017). Decision aids for people facing health treatment or screening decisions. Cochrane Database of Systematic Reviews, (4).CrossRefGoogle ScholarPubMed
Stone, ER, Choi, YS, Bruine de Bruin, W, et al. (2013) I can take the risk, but you should be safe: Self-other differences in situations involving physical safety. Judgment and Decision Making 8, 250267.Google Scholar
Strathman, A, Gleicher, F, Boninger, DS, et al. (1994) The consideration of future consequences: Weighing immediate and distant outcomes of behavior. Journal of Personality and Social Psychology 66(4), 742.CrossRefGoogle Scholar
Suhl, J, Simons, P, Reedy, T, et al. (1994) Myth of substituted judgment: Surrogate decision making regarding life support is unreliable. Archives of Internal Medicine 154(1), 9096.CrossRefGoogle ScholarPubMed
Sword, W (1999) A socio-ecological approach to understanding barriers to prenatal care for women of low income. Journal of Advanced Nursing 29(5), 11701177.CrossRefGoogle ScholarPubMed
Tejwani, V, Wu, Y, Serrano, S, et al. (2013) Issues surrounding end-of-life decision-making. Patient Preferences and Adherence 7, 771.Google ScholarPubMed
Torke, AM, Alexander, GC and Lantos, J (2008) Substituted judgment: The limitations of autonomy in surrogate decision making. Journal of General Internal Medicine, 23(9), 15141517.CrossRefGoogle ScholarPubMed
Turner, JC (1991) Social Influence. Milton Keynes, England: Open University Press.Google Scholar
United States Census Quick Facts (2017). https://www.census.gov/data.html (accessed October 4, 2018).Google Scholar
Van Ness, PH, Towle, VR, O'Leary, JR, et al. (2008) Religion, risk, and medical decision making at the end of life. Journal of Aging and Health 20(5), 545559.CrossRefGoogle ScholarPubMed
Vig, EK, Starks, H, Taylor, JS, et al. (2007) Surviving surrogate decision-making: what helps and hampers the experience of making medical decisions for others. Journal of General Internal Medicine 22(9), 12741279.CrossRefGoogle ScholarPubMed
Vig, EK, Taylor, JS, Starks, H, et al. (2006) Beyond substituted judgment: How surrogates navigate end-of-life decision-making. Journal of the American Geriatrics Society 54(11), 16881693.CrossRefGoogle ScholarPubMed
Visser, M, Deliens, L and Houttekier, D (2014) Physician-related barriers to communication and patient-and family-centred decision-making towards the end of life in intensive care: A systematic review. Critical Care 18(6), 604.CrossRefGoogle ScholarPubMed
Washington, PK, Burke, NJ, Joseph, G, et al. (2009) Adult daughters’ influence on mothers’ health-related decision making: An expansion of the subjective norms construct. Health Education & Behavior 36(5_suppl), 129S144S.CrossRefGoogle ScholarPubMed
Zhang, J, Yang, D, Deng, Y, et al. (2015). The willingness and actual situation of Chinese cancer patients and their family members participating in medical decision-making. Psycho Oncology 24(12), 16631669.CrossRefGoogle ScholarPubMed
Zikmund-Fisher, BJ, Windschitl, PD, Exe, N, et al. (2011) ‘I'll do what they did”: Social norm information and cancer treatment decisions. Patient Education and Counseling 85(2), 225229.CrossRefGoogle ScholarPubMed