The Use of the Intention-to-Treat Principle in Nursing Clinical Trials

Denise F. Polit, Brigid M. Gillespie
2009 Nursing Research  
1 Background: In randomized controlled trials (RCTs), the intention-to-treat (ITT) 2 principle, which involves maintaining study participants in the treatment groups to 3 which they were randomized regardless of post-randomization withdrawal, is the 4 recommended analytic approach for preserving the integrity of randomization; yet, little 5 is known about the use of ITT in nursing RCTs. 6 O bjectives: The purposes of this study were to describe the extent to which nurse 7 researchers who
more » ... RCTs state that they have used ITT, the extent to which they 8 actually adhere to ITT principles, and the methods they use to handle missing data. 9 Method: Data regarding ITT analysis, participant flow, rates of attrition, and methods 10 of handling missing data were extracted and coded from a consecutive sample of 124 11 RCTs published in 16 nursing journals in 2007 and 2008. 12 Results: ITT was declared in only 15.3% of the nursing RCTs, and fewer than half of 13 these studies offered a definition of ITT. Based on authors' description of analytic 14 procedures, we concluded that 10.5% of those claiming ITT use had actually used a per 15 protocol rather than an ITT analysis. Overall, we classified 46.8% of the RCTs as 16 having used either a classic or modified ITT analysis, indicating that many nurse 17 researchers are not stating their actual adherence to ITT, despite advice to do so in the 18 CONSORT guidelines. 19 Conclusions: Nurse researchers conducting RCTs should be more diligent in following 20 CONSORT guidelines about ITT, documenting ITT use in their reports, clarifying their 21 definition of ITT, and presenting flowcharts that describe subject flow. Readers of 22 nursing reports, in evaluating evidence from RCTs, should not rely on stated use of 23 ITT, but should examine how analyses were actually conducted. 24 K eywords: randomized controlled trials; intention-to-treat; missing values; attrition; 25 data analysis, statistical; bias, statistical 26 *Manuscript (Including Abstract, References and Figure Legends)
doi:10.1097/nnr.0b013e3181bf1505 pmid:19918150 fatcat:ue3nock6abcdxdeorjwbcrpaq4