Discussion: The Effect of Electroacustimulation on Postoperative Nausea, Vomiting, and Pain in Outpatient Plastic Surgery Patients: A Prospective, Randomized, Blinded, Clinical Trial

R controlled trials are now widely recognized as the standard of evidence for evaluating various forms of therapies in medicine.1,2 The evolution of the design, conduct, and reporting of randomized controlled trials is reflected in the exponential increase in publications and the efforts dedicated to improving the quality of randomized controlled trials in the literature. The earliest modern randomized controlled trial investigated the treatment of tuberculosis in a multicenter clinical trial comparing streptomycin to the standard of care, bed rest.3 This landmark study was praised for aspects of its study design; specifically, randomization, patient selection, and blinding. These criteria are now considered key components to evaluating the quality of a randomized controlled trial. Careful planning in designing a randomized controlled trial is critical to ensure that a quality study is conducted to yield valid results.1 In brief, key methodologic components of a randomized controlled trial that strengthen the validity of the results should include the method of randomization, blinding, defining the treatment and the patient population, method of recruitment, reporting an a priori power analysis and effect size, and adhering to an explicitly delineated research protocol. The importance of these criteria is reflected in the numerous quality scales proposed in the literature for evaluating randomized controlled trials. Moher and colleagues identified 25 different scales and nine checklists in a literature search extending to 1993.4 In line with the Cochrane Collaboration recommendations, many reviewers now formally use these checklists to assess the internal and external validity of the study.5 Internal validity of a trial assesses the extent to which the study yields accurate results and examines whether the difference in outcomes is attributable to the intervention rather than influenced by biases. Four primary types of biases are addressed when evaluating for internal validity: selection bias, performance bias, detection bias, and attrition bias6 (Table 1). Selection bias occurs when there are systematic differences in the chosen samples and results in samples not representative of the target population. Performance bias occurs when unequal care, apart from the designated treatment under investigation, is provided preferentially to the comparison group. Detection bias occurs when the outcomes of the investigation is assessed by a researcher who has knowledge of the treatment assignment. Lastly, attrition bias occurs when subjects who are lost to follow-up after being allocated to the treatment group are excluded from further analysis. Typically, all subject withdrawals should be explained. To avoid attrition bias, investigators can use the intention-to-treat principle, which states that all participants randomly allocated to the initial intervention group are followed up and analyzed as part of that original intervention group, regardless of whether the participant received that intervention. External validity of a study addresses the degree to which the study can be generalized to a broader population.6 The difference between a sample and a population must be clear to the investigators and the readers. Because collecting data from the population is almost logistically pro-