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Table 1. Recommendations for Advancing the Science of Measurement at the End of Life

Recommendation Number Recommendation
1 Studies should be done that test conceptual models using sophisticated statistical analyses so that pathways among predictive, causal, and dependent relationships of key variables in end-of-life care can be determined.
2 Studies should be done that expand and refine conceptual frameworks to (a) clarify which domains are modifiable; and (b) address symptom clusters, specify covariate relationships between symptoms, and develop or modify measures that can most effectively index symptoms within clusters.
3 Studies should be done that contribute psychometric evaluation to existing end-of-life measures, as well as studies that propose to develop new measures, along with rigorous psychometric evaluation of new measures.
4 Studies should be done that appropriately adapt existing measures to extend the utility of already available measures.
5 Studies should develop multidimensional, comprehensive measures that capture an adequate range of end-of-life domains and control for threats to validity (e.g., response sets, acquiescence bias).
6 Studies are needed that will develop, or adapt and test, culture-specific measures of variables of end-of-life care and that take into account the unique variations of ethnic and cultural groups.
7 Studies should be done that address measurement issues related to (a) settings of care, (b) differences in the dying trajectories, (c) fluctuations in symptom exacerbations, and (d) validity of proxy data at different time points.
8 Studies should be done that assess validity of available national data sets as sources of data about end-of-life care, test innovative approaches to their use, and control for limitations and potential biases of existing data sets.
9 Studies should be done that test the validity of data from proxies. Because questions about the reliability and validity of proxy data may be a function of earlier and more rudimentary measures, the quality of proxy data should be judged with newer and more sensitive measures.
10 Studies should propose innovative sampling plans that will achieve large and representative samples of family proxies.





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