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Published on: August 24, 2019
Evaluating patient-reported outcome measurement comparability between paper and alternate versions, using the lung
Anand A Dalal1, Lauren Nelson, Theresa Gilligan
1GlaxoSmithKline, Durham, NC, USA.
Summary
This study offers a four-step guide to assess measurement comparability for patient-reported outcome (PRO) instruments using a crossover design. The guide helps determine if combining data across different administration methods is valid.
Area of Science:
- Health Services Research
- Biostatistics
- Psychometrics
Background:
- Patient-reported outcome (PRO) instruments are crucial for clinical research.
- Ensuring measurement comparability across different administration modes (e.g., paper, web, IVR, interview) is essential for data integrity.
- Crossover study designs offer a robust framework for comparing these administration types.
Purpose of the Study:
- To present a recommended four-step guide for assessing measurement comparability of PRO instruments.
- To demonstrate the application of this guide using a PRO instrument administered via multiple modes.
- To provide a framework for deciding whether to combine data from different administration versions.
Main Methods:
- A randomized crossover design was employed to administer a PRO instrument via paper, web, interactive voice response (IVR), and interview.
- Data collected included item-level responses, mean scale scores, usability, and administration preferences.
- Statistical analyses involved item-level agreement (kappa statistics) and score comparability (intraclass correlation coefficients).
Main Results:
- Item-level agreement between paper and alternate versions showed good to excellent kappa statistics.
- Intraclass correlation coefficients for mean scores exceeded 0.70.
- Disagreement rates varied from 2% to 14%, with minimal reported difficulties despite participant preferences for certain modes.
Conclusions:
- The proposed four-step guide facilitates the evaluation of measurement comparability for PRO instruments under a crossover design.
- Investigating item-level responses, summary scores, and usability/preference provides comprehensive information for decision-making.
- This approach supports informed decisions on combining data across administration versions to simplify analysis and interpretation.
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