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Related Experiment Videos

Assessing sensitivity to change: choosing the appropriate change coefficient.

Paul W Stratford1, Daniel L Riddle

  • 1School of Rehabilitation Science, McMaster University, Hamilton, ON, L8S 1C7 Canada. stratfor@mcmaster.ca

Health and Quality of Life Outcomes
|April 7, 2005
PubMed
Summary

Evaluating health status measures requires rigorous methods. This study identifies conflicts in using multiple change coefficients, suggesting pilot studies to determine population characteristics for accurate measure selection.

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Area of Science:

  • Health Outcomes Research
  • Biostatistics
  • Psychometrics

Background:

  • Numerous health status measures have been developed over the past two decades.
  • Methodological standards for evaluating the sensitivity to change of these measures are less stringent than those for clinical intervention trials.
  • A lack of a criterion standard for health status change contributes to this methodological gap.

Purpose of the Study:

  • To identify and describe the conceptual conflict arising from applying multiple change coefficients to the same patient sample.
  • To highlight the implications of different assumptions about sample composition on the interpretation of change coefficients.
  • To provide guidance on selecting appropriate change coefficients for health status measures.

Main Methods:

Related Experiment Videos

  • Categorization of change coefficients into three families based on assumptions about sample homogeneity and individual patient change.
  • Analysis of how the 'signal' of a measure's ability to detect change can be obscured by the 'noise' (measurement error) of other coefficients.
  • Illustrative analyses demonstrating the conflict between different change coefficient families.

    • Main Results:

    • A major conceptual conflict exists when multiple change coefficients are applied to the same patient sample.
    • The true ability of a measure to detect change (signal) for one coefficient can be part of the measurement error (noise) for another.
    • This conflict is likely due to insufficient preparatory work, such as pilot studies, to understand population change characteristics.

    Conclusions:

    • Uncertainty in choosing the correct change coefficient can be resolved by conducting pilot studies.
    • Pilot studies should aim to ascertain the likely change characteristics of the patient population.
    • Clearly identifying population change characteristics will facilitate the appropriate selection of change coefficients for health status measures.