How can clinical trials expedite the process of answering treatment-related questions and reduce the number of participants needed?
R. Emsley

TL;DR
This paper discusses how using more efficient trial designs can speed up treatment evaluations and reduce the number of participants needed in clinical trials.
Contribution
The paper introduces the concept of 'efficient trials' in mental health, highlighting opportunities and challenges.
Findings
Efficient trial designs can provide quicker answers in clinical trials.
Mental health research often underutilizes these efficient trial methods.
Such trials can improve patient access to effective treatments.
Abstract
Patients and the research community need better and more cost-effective randomised trials. These are the ‘gold standard’ way of seeing if a new treatment works or not, and take years of effort involving lots of patients and funding. However, around half of trials fail to show that the new treatment is better than what it is being compared with. In cancer, this problem has been recognised. They use trial designs which test multiple treatments, and find out quicker answers to more questions. These ‘efficient trials’ are able to involve patients at a faster rate and to improve the chances of patients receiving a treatment that works. In mental health, the whole toolbox of trial designs is not being used. Sometimes there are valid reasons for this, but sometimes it is simply that researchers do not know about them – this talk will expand on the concept of ‘efficient trials’ in mental…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHealth and Medical Research Impacts
