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Evaluating measurement responsiveness

M H Liang1

  • 1Department of Medicine, Harvard Medical School, Robert B. Brigham Multipurpose Arthritis and Musculoskeletal Diseases Center, Bringham and Women's Hospital, Boston, MA 02115, USA.

The Journal of Rheumatology
|June 1, 1995
PubMed
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This review examines strategies for improving quantitative questionnaire responsiveness. Current evaluation methods lack standardization and require further assessment, leading to a proposed conceptual model for responsiveness assessment.

Area of Science:

  • Health Outcomes Research
  • Psychometrics
  • Clinical Assessment

Background:

  • Quantitative questionnaires are crucial for measuring health outcomes.
  • Assessing the responsiveness of these instruments is vital for detecting meaningful changes.
  • Existing methods for evaluating responsiveness are inconsistent and lack empirical validation.

Purpose of the Study:

  • To review existing strategies for enhancing the responsiveness of quantitative questionnaires.
  • To critically evaluate current methods used for assessing questionnaire responsiveness.
  • To propose a conceptual model for a standardized approach to responsiveness assessment.

Main Methods:

  • Systematic literature review of studies on questionnaire responsiveness.
  • Analysis of current methodologies for responsiveness evaluation.

Related Experiment Videos

  • Development of a conceptual framework for responsiveness assessment.

    • Main Results:

    • A range of strategies for improving questionnaire responsiveness were identified.
    • Current responsiveness evaluation methods are not standardized and have not been adequately evaluated.
    • A conceptual model for assessing responsiveness is proposed to address current limitations.

    Conclusions:

    • Standardized and validated methods are needed for evaluating questionnaire responsiveness.
    • The proposed conceptual model offers a framework for consistent and reliable responsiveness assessment.
    • Further research is required to implement and validate the proposed model in practice.