New guidance was published this week to aid researchers and practitioners in the design and conduct of randomised controlled trials (RCTs) of complex interventions.
Developed through a series of consultations with the global ANH community, including at special ANH Academy Week sessions between 2019 and 2021, the article - authored by Jef Leroy, Ed Frongillo and colleagues, in BMJ-Global Health - discusses key problems and misconceptions, and presents clear ways to ensure that trials of complex interventions are conducted to the highest scientific standards while maximising the evidence that can be extracted.
Rationale for this work
Randomized controlled trials (RCTs) are increasingly used to evaluate the impact of complex interventions which are designed to affect multiple outcomes through several mechanisms. Researchers conducting RCTs of complex interventions are often faced with design and analytic challenges that are not fully addressed in existing guidance and that are exacerbated by the belief that guidance for trials of non-complex interventions should be strictly applied to trials of complex interventions.
The objective was to demystify these common challenges and provide useful, practical guidance; starting with basic principles to formulate key recommendations. For instance, demonstrating that limiting causal inference to a few primary outcomes is inappropriate when interventions are complex. Each of potentially many primary outcomes, whether intermediate or end outcomes, however, should be based on the intervention theory of change, linked to a stated hypothesis, registered before trial start, adequately powered, and fully and transparently reported. Inference on all undeclared and underpowered outcomes should be considered exploratory.
Read the paper:
Jef L Leroy; Edward A Frongillo; Bezawit E Kase; Silvia Alonso; Mario Chen; Ian Dohoo; Lieven Huybregts; Suneetha Kadiyala; Naomi M Saville.BMJ Global Health 2022;7:e008597.
Explore the sequence of key ANH events which helped to shaped this work
Learn more about how this work is being taken forward, at the ANH2022 Learning Lab:
Photo credit: Tom Fisk