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Skip search results from other journals and go to results- 2 JMIR Aging
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Due to potential limited computing infrastructures available to generate real-time predictions based on ML algorithms (eg, random forest) in some clinical settings, we also implemented a simplified version of the prediction approach described above in which we restricted the library of candidate predictors to a main-term logistic regression using training data pooled across all 8 quarters. This is equivalent to a classical discrete-time survival model with a logit link function [36].
JMIR Diabetes 2025;10:e60141
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Qualitative methods are ideal for this purpose, as they can provide a deep understanding of caregivers’ lived experiences and of caregiver and staff interactions with the EHR and generate hypotheses about how health systems can better use the EHR as a tool to support caregivers.
This analysis was done as part of a study designed to develop a tool to identify caregivers of people living with dementia through the EHR for pragmatic trials related to medication management.
JMIR Aging 2024;7:e59584
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During health technology trials, many participants never use the technology available to them, and those who adopt the technology, commonly use the tool only a few times. However, once enrolled in a trial, older adults are more likely to complete a health technology intervention to manage their health than younger patients [9]. The initial adoption of health technologies is key to successful ongoing use.
JMIR Aging 2019;2(1):e13713
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The theory posits that a person’s intent to use (acceptance of technology) and usage behavior (actual use) of a technology is predicated by the person’s perceptions of the specific technology’s usefulness (benefit from using the technology) and ease of use. Simply, users are more likely to adopt a new technology with high-quality UX design (ie, usable, useful, desirable, and credible).
J Med Internet Res 2019;21(4):e11604
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