Quality and Reporting of Cluster Randomized Controlled Trials Evaluating Occupational Therapy Interventions

Abstract

Growing use of cluster randomized control trials (RCTs) in health care research requires careful attention to study designs, with implications for the development of an evidence base for practice. The objective of this study is to investigate the characteristics, quality, and reporting of cluster RCTs evaluating occupational therapy interventions to inform future research design. An extensive search of cluster RCTs evaluating occupational therapy was conducted in several databases. Fourteen studies met our inclusion criteria; four were protocols. Eleven (79%) justified the use of a cluster RCT and accounted for clustering in the sample size and analysis. All full studies reported the number of clusters randomized, and five reported intercluster correlation coefficients (50%): Protocols had higher compliance. Risk of bias was most evident in unblinding of participants. Statistician involvement was associated with improved trial quality and reporting. Quality of cluster RCTs of occupational therapy interventions is comparable with those from other areas of health research and needs improvement.

Bayesian statistics in the design and analysis of cluster randomised controlled trials and their reporting quality: a methodological systematic review

“…However, in 2013, Diaz-Ordaz presented a summary of reviews of CRCT quality, in which the percentage of studies accounting for clustering in the sample size calculation and statistical analysis ranged from 0% to 71% and 37% to 92%, respectively [ 15 ]. We have identified an additional review of reporting and methodological quality of CRCTs published in 2016 [ 16 ]. Including the data from the more recent review together with Diaz-Ordaz’s summary, the mean (SD) percentage of studies accounting for clustering in the sample size calculation and analysis was 34.6 (23.7) and 64.2 (16.3), respectively.…”

“…A separate recently published review of the same sample of CRCTs examined the impact of the 2004 CONSORT extension on more general methodological quality and concluded that adherence to published reporting guidelines and quality remains low [14]. Similar reviews of CRCT reporting quality have been conducted and produced comparable conclusions [15,16]. However, to our knowledge, none have focussed specifically on CRCTs which incorporated Bayesian methods, and so both the quantity and quality of these are unknown.…”

Methodological approaches to the design and analysis of nonrandomized intervention studies for the prevention of child and adolescent obesity

“…Nearly all of the identified studies included clusters, such as schools, school districts and cities, but few studies accounted for clustering in their analysis (Bleich et al 2018). Since individuals within a cluster are likely to be more similar to one another compared with a sample population from the general public, the correlations and dependency of subjects within a cluster need to be considered (Tokolahi et al 2016). Failure to do so can lead to incorrect P values or confidence intervals and biased estimates of the effect of the intervention on BMI and may reduce the statistical power to detect differences (Zyzanski et al 2004).…”

Frailty Intervention through Nutrition Education and Exercise (FINE). A Health Promotion Intervention to Prevent Frailty and Improve Frailty Status among Pre-Frail Elderly—A Study Protocol of a Cluster Randomized Controlled Trial

“…With a hypothesized intra-cluster correlation coefficient (ICC) 0.02 [ 1 ], fixed cluster size of 4 [ 45 ], and a minimum of 15 respondents required under individual randomization, the calculated minimum required cluster size and sample size is 4 and 16 per arm, respectively. After an adjustment for the estimated response rate, a sample size of 30 respondents per arm is required to provide of 80%, with α = 0.05.…”