A newly developed tool for classifying study designs in systematic reviews of interventions and exposures showed substantial reliability and validity

J Clin Epidemiol. 2016 Feb:70:200-5. doi: 10.1016/j.jclinepi.2015.09.013. Epub 2015 Sep 25.

Abstract

Objective: To develop a study Design Algorithm for Medical Literature on Intervention (DAMI) and test its interrater reliability, construct validity, and ease of use.

Study design and setting: We developed and then revised the DAMI to include detailed instructions. To test the DAMI's reliability, we used a purposive sample of 134 primary, mainly nonrandomized studies. We then compared the study designs as classified by the original authors and through the DAMI. Unweighted kappa statistics were computed to test interrater reliability and construct validity based on the level of agreement between the original and DAMI classifications. Assessment time was also recorded to evaluate ease of use.

Results: The DAMI includes 13 study designs, including experimental and observational studies of interventions and exposure. Both the interrater reliability (unweighted kappa = 0.67; 95% CI [0.64-0.75]) and construct validity (unweighted kappa = 0.63, 95% CI [0.52-0.67]) were substantial. Mean classification time using the DAMI was 4.08 ± 2.44 minutes (range, 0.51-10.92).

Conclusions: The DAMI showed substantial interrater reliability and construct validity. Furthermore, given its ease of use, it could be used to accurately classify medical literature for systematic reviews of interventions although minimizing disagreement between authors of such reviews.

Keywords: Algorithm; Intervention studies; Reliability; Research design; Systematic review; Validity.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Algorithms*
  • Consensus
  • Evidence-Based Medicine / classification*
  • Humans
  • Peer Review, Research / standards*
  • Quality Control
  • Reproducibility of Results
  • Research Design / standards*
  • Review Literature as Topic*