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Power calculation in stepped-wedge cluster randomized trial with reduced intervention sustainability effect
Jing Li1, Ying Zhang2, Laura J Myers3,4
1a Department of Biostatistics, Richard M. Fairbanks School of Public Health, Indiana University , Indianapolis , IN , USA.
This study introduces a new power analysis formula for stepped-wedge designs in pragmatic clinical trials. It addresses scenarios with reduced intervention effects during a sustainability phase, crucial for health service research.
Area of Science:
- Clinical Trials Methodology
- Health Services Research
- Biostatistics
Background:
- Stepped-wedge designs are increasingly used in pragmatic clinical trials for health services research.
- These designs are favored when interventions are known to be effective and safe, or due to logistical/financial constraints necessitating sequential implementation.
- Existing literature lacks methods for stepped-wedge trials with distinct active implementation and sustainability phases where intervention effects may diminish.
Purpose of the Study:
- To address the gap in power analysis for stepped-wedge cluster randomized trials experiencing a reduced intervention effect during a sustainability phase.
- To develop an analytical formula for power calculations tailored to this specific trial scenario.
Main Methods:
- The study focuses on developing a novel analytical formula for power analysis.
- This formula is designed to accommodate stepped-wedge designs with a two-part study period (active implementation and sustainability phase).
Main Results:
- An analytical formula for power analysis has been derived for stepped-wedge designs with a sustainability phase.
- This formula aids in the design of cluster randomized trials where intervention effects may wane over time.
Conclusions:
- The developed formula provides a crucial tool for researchers designing stepped-wedge trials in health services, particularly those with extended study periods and potential for effect modification.
- This methodology supports more accurate power estimations, enhancing the rigor of pragmatic clinical trials evaluating interventions in real-world settings.
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