Canadian adaptive platform trial of treatments for COVID in community settings (CanTreatCOVID): recruitment strategies of a decentralized, national randomized controlled trial for acute SARS-CoV-2

Geil Han Astorga; Andrew D. Pinto; Kawsika Sivayoganathan; Kevin Maruthananth; Banafshe Hosseini

Geil Han Astorga, Andrew D Pinto, Kawsika Sivayoganathan, Kevin Maruthananth, Banafshe Hosseini

Frontiers in Public Health, doi:10.3389/fpubh.2026.1698604

Background: Recruitment remains a challenge in clinical trials. This study describes the use of digital and traditional recruitment channels in a national, community-based adaptive platform trial for COVID-19 in Canada. Methods: Self-reported recruitment sources were collected from participants of a remote, national adaptive platform trial of COVID-19 treatments conducted across six Canadian provinces using a secure web-based application. Recruitment channels were analyzed using descriptive statistics, chi-square tests, and logistic regression to explore associations with province. Results: From January 2023 to September 2024, 1,515 participants completed the pre-screening process, and 720 were randomized. Of them, 416 were recruited through traditional channels, 303 through digital channels, and one through an undetermined source. Recruitment channels varied by province (χ 2 (5) = 81.30, p < 0.001; Cramér's V = 0.34), and digital channels were associated with higher odds of recruitment compared with traditional channels (adjusted OR = 2.78, 95% CI 2.20-3.52). The most frequently reported referral source was 'family, friends, or colleagues' (20%), followed by provincial government websites and health lines (16.25%), online channels (10.56%), and public communications (9.86%). Conclusion: Combining traditional and digital recruitment methods supports recruitment. Trials can raise awareness of the study by leveraging both digital and traditional channels and can move information to action through trusted social groups and institutions. Further research is needed to evaluate the cost-effectiveness, reach, and demographic differences across platforms, informing recruitment strategies in future decentralized and adaptive trials beyond COVID-19.

Frontiers in Public Health 07 frontiersin.org The increased utilization of online platforms during the COVID-19 pandemic introduced affordances for mixed traditional and digital recruitment in trials (13, 24) . While leveraging various channels reaches broad audiences, understanding geographical and other relevant contexts is equally important for successful recruitment (22, 23) . The observed variation in traditional and digital recruitment channel distribution across CanTreatCOVID sites aligns with the moderate association identified in the analysis. Two of the provinces that generated 77% of the recruitment results had different primary sources: traditional for ON and digital for BC, whereas other sites relied on traditional channels. The heterogeneity across provinces suggests that geographical and other characteristics influence recruitment rather than uniform reliance on a single recruitment strategy, and highlights the potential complementary role of traditional and digital channels. A key limitation of this analysis is that recruitment strategies were not randomized, and participants may have been exposed to multiple recruitment channels. As a result, the findings should be interpreted as descriptive comparisons and associations rather than causal or inferential effects of specific recruitment approaches. This study reports on a wide range of recruitment channels and provides insights into their effectiveness in engaging with potential participants. Future..

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DOI record: { "DOI": "10.3389/fpubh.2026.1698604", "ISSN": [ "2296-2565" ], "URL": "http://dx.doi.org/10.3389/fpubh.2026.1698604", "abstract": "\n Background\n Recruitment remains a challenge in clinical trials. This study describes the use of digital and traditional recruitment channels in a national, community-based adaptive platform trial for COVID-19 in Canada.\n \n \n Methods\n Self-reported recruitment sources were collected from participants of a remote, national adaptive platform trial of COVID-19 treatments conducted across six Canadian provinces using a secure web-based application. Recruitment channels were analyzed using descriptive statistics, chi-square tests, and logistic regression to explore associations with province.\n \n \n Results\n \n From January 2023 to September 2024, 1,515 participants completed the pre-screening process, and 720 were randomized. Of them, 416 were recruited through traditional channels, 303 through digital channels, and one through an undetermined source. Recruitment channels varied by province (\n χ\n 2\n (5) = 81.30,\n p\n  &lt; 0.001; Cramér’s\n V\n  = 0.34), and digital channels were associated with higher odds of recruitment compared with traditional channels (adjusted OR = 2.78, 95% CI 2.20–3.52). The most frequently reported referral source was ‘family, friends, or colleagues’ (20%), followed by provincial government websites and health lines (16.25%), online channels (10.56%), and public communications (9.86%).\n \n \n \n Conclusion\n Combining traditional and digital recruitment methods supports recruitment. Trials can raise awareness of the study by leveraging both digital and traditional channels and can move information to action through trusted social groups and institutions. Further research is needed to evaluate the cost-effectiveness, reach, and demographic differences across platforms, informing recruitment strategies in future decentralized and adaptive trials beyond COVID-19.\n \n \n Clinical trial registration\n \n https://clinicaltrials.gov/study/NCT05614349\n , Identifier NCT05614349.\n \n ", "alternative-id": [ "10.3389/fpubh.2026.1698604" ], "article-number": "1698604", "author": [ { "affiliation": [ { "name": "Upstream Lab, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] } ], "family": "Astorga", "given": "Geil Han", "sequence": "first" }, { "affiliation": [ { "name": "Upstream Lab, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Department of Family and Community Medicine, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Department of Family and Community Medicine, Faculty of Medicine, University of Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Division of Clinical Public Health, Dalla Lana School of Public Health, University of Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto", "place": [ "Toronto, ON, Canada" ] } ], "family": "Pinto", "given": "Andrew D.", "sequence": "additional" }, { "affiliation": [ { "name": "Upstream Lab, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] } ], "family": "Sivayoganathan", "given": "Kawsika", "sequence": "additional" }, { "affiliation": [ { "name": "Upstream Lab, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] } ], "family": "Maruthananth", "given": "Kevin", "sequence": "additional" }, { "affiliation": [ { "name": "Upstream Lab, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Department of Family and Community Medicine, Faculty of Medicine, University of Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Division of Clinical Public Health, Dalla Lana School of Public Health, University of Toronto", "place": [ "Toronto, ON, Canada" ] }, { "name": "Institute of Medical Science, Faculty of Medicine, University of Toronto", "place": [ "Toronto, ON, Canada" ] } ], "family": "Hosseini", "given": "Banafshe", "sequence": "additional" } ], "container-title": "Frontiers in Public Health", "container-title-short": "Front. 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