Background: The standard approach in a randomized controlled trial (RCT) is to randomize individuals to intervention and control groups. Yet, nursing and other health interventions are often implemented at the levels of health service organizational unit or geographical area. It may be more appropriate to conduct a cluster RCT. However, cluster randomization requires consideration of a number of important issues.
Objective: The objective of this study was to show how critical issues in relation to design and analysis can be addressed.
Approach: Two cluster RCTs conducted by the authors are used as examples. Guidance on the conduct and reporting of cluster RCTs is also offered.
Results: A rationale for choosing this design was provided, and issues in relation to study design, calculation of sample size, and statistical analysis were clarified. A decision tree and checklist are provided to guide researchers through essential steps in conducting a cluster RCT.
Discussion: Cluster RCTs present special challenges in relation to design, conduct, and analysis. Nevertheless, they are an appropriate and potentially powerful tool for nursing research. With careful attention to the issues addressed in this article, researchers can use this approach successfully.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/NNR.0b013e3181900cb5 | DOI Listing |
Alzheimers Dement
December 2024
University College London, London, United Kingdom.
Background: Our authors from around the world met to summarise the available knowledge, decide which potentially modifiable risk factors for dementia have compelling evidence and create the most comprehensive analysis to date for potentially modifiable risk factors to inform policy, give individuals the opportunity to control their risks and generate research.
Method: We incorporated all risk factors for which we judged there was strong enough evidence. We used the largest recent worldwide meta-analyses for risk factor prevalence and relative risk and if not available the best data.
Alzheimers Dement
December 2024
National Ageing Research Institute, Melbourne, VIC, Australia.
Background: The Promoting Independence Through quality Care at Home (PITCH) project aimed to improve outcomes for people with dementia and their carers via a co-designed training intervention for home care workers (HCWs). The results of the primary efficacy analysis of the successful stepped-wedge cluster RCT (n = 172 HCWs in 18 clusters in 7 Australian service providers) were presented at AAIC 2023.
Method: This presentation goes beyond efficacy and discusses the implementation science (process evaluation and behavioural change) and health economic analysis of the intervention.
PLoS One
January 2025
Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, United States of America.
Background: Randomized controlled trials (RCTs) that evaluate the efficacy of an intervention remain underutilized in community-based environmental health research. RCTs that use a pragmatic design emphasize the effectiveness of interventions in complex, real world settings. Pragmatic trials may be especially relevant when community-based interventions address social and environmental determinants that threaten health equity.
View Article and Find Full Text PDFFront Neurol
December 2024
School of Physical Education and Sports Science, South China Normal University, Guangzhou, Guangdong, China.
Background: This study aims to evaluate the optimal rehabilitation regimen for lower limb dysfunction in stroke patients by analyzing the effects of proprioceptive training (PT) in combination with different rehabilitation interventions.
Methods: Randomized controlled trials (RCTs) published up to April 23, 2024, were searched from PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, and SinoMed. The quality of the included studies was assessed using the Cochrane Risk of Bias tool (ROB 2.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!