USING RESEARCH IN CLINICAL PRACTICE: HOW TO READ RANDOMISED TRIALS
Evidence-based practice is physical therapy informed by relevant, high-quality clinical research (1). The best type of clinical research to evaluate the effects of intervention is the randomised controlled trial (or systematic reviews of randomised controlled trials) . The good news for physical therapists wanting to use trials to guide their practice is that there are now over 36,000 published trials evaluating physical therapy interventions . Challenges faced by physical therapists include: choosing the best trial to read; making sense of the methods and results reported; and applying the results to an individual patient. Trials use a series of methods in order to reduce bias (or enhance the robustness) of the results, including how subjects are allocated to groups, how outcomes are collected, and how data are analysed and reported. Unfortunately, not all trials implement and/or communicate these important design features – just 38% of trials evaluating physical therapy interventions contain 6 or more of 10 design features known to reduce bias or provide results in a way to aid clinical decision-making . Clinicians need to understand these design features, and be able to identify them quickly in articles reporting trial results, in order to select and understand the best trial to answer their clinical questions. In this workshop, participants will develop knowledge and skills in reading randomised controlled trials. We will delve into some key design features used in trials, including random and concealed allocation, blinding of therapists, subjects and assessors, intention to treat analysis, and reporting of between-group comparisons using estimation (confidence intervals) rather than hypothesis testing. Participants will gain some practical experience in reading and appraising published reports of trials.
- Understand the value of using randomised trials to guide practice
- Describe key features that reduce bias and increase usefulness of trials
- Explore the latest methods for analysing and reporting treatment effects in trials