A Framework for Recruiting into a Remote Measurement Technologies (RMTs) study: Experiences from a major depressive disorder cohort

The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming increasingly popular, given their potential for high-frequency symptom monitoring outside of routine clinical appointments. However, many RMT studies fail to report on engagement and recruitment statistics, with the few who do citing a wide range of recruitment rates. There is a need for the standardisation of best practices for successful recruitment into RMT research, critical for both research validity and reproducibility. The current paper aims to create a framework for successful recruitment into RMT studies, reflecting on the experience of RADAR-MDD, a large-scale, multi-site prospective cohort study utilising RMT to explore the clinical course of people with major depressive disorder across the UK, Netherlands, and Spain. More specifically, the paper assesses four key strategies for successful recruitment, alongside a review of the common barriers to participation and how to avoid them. Finally, the strategies and barriers outlined are combined into a single model of recruitment, that can be used as a framework to inform future study design and evaluation. Such a model will be applicable to a variety of stakeholders using RMT in healthcare research and practice.