Literature DB >> 15130201

Measuring patient treatment preferences in end-of-life care research: applications for advance care planning interventions and response shift research.

Carolyn E Schwartz1, Melanie P Merriman, George W Reed, Bernard J Hammes.   

Abstract

Understanding the dynamics of patient treatment preferences can be important for end-of life are research, and has particular salience not only to guide a process of advance care planning (ACP) but also as an outcome measure. Ascertaining the reliability and responsiveness of preferences for life-sustaining treatments within and between patients is a necessary foundation for utilizing patient-agent congruence as an outcome for ACP interventions. This study validated a modified version of the Emanuel and Emanuel Medical Directive for use in both research and clinical applications. Seriously ill patients (n = 168) were asked at baseline and 21 days to consider four common end-of-life health state scenarios, to indicate their goals for treatment, and to state their preferences for six specific treatments. We investigated the reliability and validity of this tool. We found that preferences for life-sustaining treatments were highly intercorrelated, and internally consistent across treatments by scenario and across scenarios by treatment. Preferences for pain medications were, however, distinct from preferences for other treatments. Preference scores exhibited stability over follow-up, and demonstrated both concurrent and discriminant validity. We detected a small effect size for change in preferences as a function of health state change, suggesting that re-prioritization response shifts do occur but are small in magnitude in these patient samples over this time frame. We conclude that this measure is reliable and valid for use in clinical settings and for evaluating interventions designed to improve patient-agent congruence about patient preferences for life-sustaining treatments. Clinical applications of the tool are discussed.

Entities:  

Keywords:  Death and Euthanasia; Empirical Approach

Mesh:

Year:  2004        PMID: 15130201     DOI: 10.1089/109662104773709350

Source DB:  PubMed          Journal:  J Palliat Med        ISSN: 1557-7740            Impact factor:   2.947


  16 in total

1.  Teaching advance care planning to medical students with a computer-based decision aid.

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Journal:  J Cancer Educ       Date:  2011-03       Impact factor: 2.037

Review 2.  The clinical significance of adaptation to changing health: a meta-analysis of response shift.

Authors:  Carolyn E Schwartz; Rita Bode; Nicholas Repucci; Janine Becker; Mirjam A G Sprangers; Peter M Fayers
Journal:  Qual Life Res       Date:  2006-09-26       Impact factor: 4.147

Review 3.  A systematic review of measures of end-of-life care and its outcomes.

Authors:  Richard A Mularski; Sydney M Dy; Lisa R Shugarman; Anne M Wilkinson; Joanne Lynn; Paul G Shekelle; Sally C Morton; Virginia C Sun; Ronda G Hughes; Lara K Hilton; Margaret Maglione; Shannon L Rhodes; Cony Rolon; Karl A Lorenz
Journal:  Health Serv Res       Date:  2007-10       Impact factor: 3.402

4.  Guidelines for secondary analysis in search of response shift.

Authors:  Carolyn E Schwartz; Sara Ahmed; Richard Sawatzky; Tolulope Sajobi; Nancy Mayo; Joel Finkelstein; Lisa Lix; Mathilde G E Verdam; Frans J Oort; Mirjam A G Sprangers
Journal:  Qual Life Res       Date:  2013-04-10       Impact factor: 4.147

5.  Method variation in the impact of missing data on response shift detection.

Authors:  Carolyn E Schwartz; Tolulope T Sajobi; Mathilde G E Verdam; Veronique Sebille; Lisa M Lix; Alice Guilleux; Mirjam A G Sprangers
Journal:  Qual Life Res       Date:  2014-07-10       Impact factor: 4.147

6.  Response shift in patients with multiple sclerosis: an application of three statistical techniques.

Authors:  Carolyn E Schwartz; Mirjam A G Sprangers; Frans J Oort; Sara Ahmed; Rita Bode; Yuelin Li; Timothy Vollmer
Journal:  Qual Life Res       Date:  2011-11-13       Impact factor: 4.147

7.  Fluctuations in appraisal over time in the context of stable versus non-stable health.

Authors:  Carolyn E Schwartz; Brian R Quaranto; Bruce D Rapkin; Brian C Healy; Timothy Vollmer; Mirjam A G Sprangers
Journal:  Qual Life Res       Date:  2013-07-13       Impact factor: 4.147

8.  Evaluating quality of life and response shift from a couple-based perspective: a study among patients with colorectal cancer and their partners.

Authors:  Marjan J Traa; Johan Braeken; Jolanda De Vries; Jan A Roukema; Ricardo G Orsini; Brenda L Den Oudsten
Journal:  Qual Life Res       Date:  2014-11-28       Impact factor: 4.147

9.  Changes in quality of life from a homelessness intervention: true change, response shift, or random variation.

Authors:  Guido Antonio Powell; Carol E Adair; David L Streiner; Nancy Mayo; Eric Latimer
Journal:  Qual Life Res       Date:  2017-02-24       Impact factor: 4.147

10.  Assessment of preferences for treatment: validation of a measure.

Authors:  Souraya Sidani; Dana R Epstein; Richard R Bootzin; Patricia Moritz; Joyal Miranda
Journal:  Res Nurs Health       Date:  2009-08       Impact factor: 2.228

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