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Participants who completed the demographics survey could be randomized to the TR-D condition, which showed participants a nontailored message (ie, brief description of PHQ-9 results) and featured resources tailored to age and LGBTQ+ status. A pool of 3 to 4 possible resources for each age group was chosen by an algorithm that identified the most popular resources within each age group.
JMIR Ment Health 2025;12:e73188
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ETHICS of AI Adoption and Deployment in Health Care: Progress, Challenges, and Next Steps
JMIR AI 2025;4:e67626
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Lessons Learned Identifying and Controlling Fraudulent Participation in Online Randomized Trials
J Med Internet Res 2025;27:e77512
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To better distinguish spatial boundaries, county borders were then layered on top for both states and cities, followed by additional boundaries for zip code borders for cities (Figures 1 D, 2 C and D). The next layer was a dot density plot for pharmacies, where one point corresponded to five pharmacy locations to better visualize locations given the generally large number of existing pharmacies (Figures 1 E and 2 E).
JMIR Public Health Surveill 2025;11:e75077
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NHS D: GDPPR data from the NHS Digital Trusted Research Environment.
In our bias analysis, for a hypothetical VE study, we assumed an analytic dataset of 10,000 individual records. In Scenario A (reference case), we correctly excluded all inactive records, analyzing only the 9700 active patients. With 60% vaccination coverage, a 1% event rate among vaccinated and a 5% event rate among unvaccinated individuals, we calculated a true VE of 70%.
JMIR Public Health Surveill 2025;11:e64788
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