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| http://dx.doi.org/10.1073/pnas.2119887119 | DOI Listing |
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214500 | PMC |
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Background: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence-driven adaptive trial-Vibe Up.
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Author Affiliations: Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina (Ms Draper, Dr Younginer, and Mr Samin); Center for Excellence in Public Health, University of New England, Portland, Maine (Dr Rodriguez and Ms Bruno); and Department of Nutrition and Food Sciences, University of Rhode Island, Providence, Rhode Island (Dr Balestracci).
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During public health crises such as pandemics, governments must rapidly adopt and implement wide-reaching policies and programs ("public policy interventions"). A key takeaway from the coronavirus disease 2019 (COVID-19) pandemic was that although numerous randomized controlled trials (RCTs) focussed on drugs and vaccines, few policy experiments were conducted to evaluate effects of public policy interventions across various sectors on viral transmission and other consequences. Moreover, many quasi-experimental studies were of spurious quality, thus proving unhelpful for informing public policy.
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