Introduction: Older adults are often prescribed oral anticancer agents (OAAs). Technology-based interventions may offer medication and symptom support. We aimed to evaluate technology ownership, use, and preferred design features of a supportive web-based program using a multimethod design utilizing surveys and semi-structured interviews.
View Article and Find Full Text PDFObjectives: To explore to what degree providing patients warning information about the long-term risks of a medication would affect their subsequent desire to discontinue it.
Methods: We conducted a vignette-based online experiment in which participants aged ≥ 65 years from the United States were asked to imagine starting and subsequently stopping omeprazole. Participants were randomized to one of four vignettes about starting omeprazole (potential long-term harms or no harm information; OTC vs.
Background: Given the public release of large language models, research is needed to explore whether older adults would be receptive to personalized medication advice given by artificial intelligence (AI) tools.
Objective: This study aims to identify predictors of the likelihood of older adults stopping a medication and the influence of the source of the information.
Methods: We conducted a web-based experimental survey in which US participants aged ≥65 years were asked to report their likelihood of stopping a medication based on the source of information using a 6-point Likert scale (scale anchors: 1=not at all likely; 6=extremely likely).
This qualitative sub-study investigated household practices affecting orally shed infections using Kaposi's sarcoma-associated herpesvirus (KSHV) as a focus. Participants enrolled from 50 households in rural south-western Uganda were followed monthly up to three times. At enrolment, in-depth interviews were completed, and venous blood collected.
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