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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming popular, given their potential for providing rich data on symptom change and indicators of future state in recurrent conditions such as major depressive disorder (MDD). Understanding recruitment into RMT research is fundamental for improving historically small sample sizes, reducing loss of statistical power, and ultimately producing results worthy of clinical implementation. There is a need for the standardisation of best practices for successful recruitment into RMT research. The current paper reviews lessons learned from recruitment into the Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study, a large-scale, multi-site prospective cohort study using RMT to explore the clinical course of people with depression across the UK, the Netherlands, and Spain. More specifically, the paper reflects on key experiences from the UK site and consolidates these into four key recruitment strategies, alongside a review of barriers to recruitment. Finally, the strategies and barriers outlined are combined into a model of lessons learned. This work provides a foundation for future RMT study design, recruitment and evaluation.<\/jats:p>","DOI":"10.1038\/s41746-022-00680-z","type":"journal-article","created":{"date-parts":[[2022,9,3]],"date-time":"2022-09-03T11:03:55Z","timestamp":1662203035000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder"],"prefix":"10.1038","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1480-917X","authenticated-orcid":false,"given":"Carolin","family":"Oetzmann","sequence":"first","affiliation":[]},{"given":"Katie M.","family":"White","sequence":"additional","affiliation":[]},{"given":"Alina","family":"Ivan","sequence":"additional","affiliation":[]},{"given":"Jessica","family":"Julie","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9512-752X","authenticated-orcid":false,"given":"Daniel","family":"Leightley","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3768-1797","authenticated-orcid":false,"given":"Grace","family":"Lavelle","sequence":"additional","affiliation":[]},{"given":"Femke","family":"Lamers","sequence":"additional","affiliation":[]},{"given":"Sara","family":"Siddi","sequence":"additional","affiliation":[]},{"given":"Peter","family":"Annas","sequence":"additional","affiliation":[]},{"given":"Sara Arranz","family":"Garcia","sequence":"additional","affiliation":[]},{"given":"Josep Maria","family":"Haro","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5443-7596","authenticated-orcid":false,"given":"David C.","family":"Mohr","sequence":"additional","affiliation":[]},{"given":"Brenda W. 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The programme receives support from Janssen, Biogen, MSD, UCB and Lundbeck. D.C.M. has accepted honoraria and consulting fees from Apple, Inc., Otsuka Pharmaceuticals, Pear Therapeutics, and the One Mind Foundation, royalties from Oxford Press, and has an ownership interest in Adaptive Health, Inc. P.A. is employed by the pharmaceutical company H. Lundbeck A\/S. V.N. is an employee of Janssen Research & Development, LLC and hold company stocks\/stock options. C.O. is supported by the UK Medical Research Council (MR\/N013700\/1) and King\u2019s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences. All other authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"133"}}