Publications by authors named "Megan Olsen"

Mobile sensing applications that collect active, Ecological Momentary Assessment data, and passive, Global Positioning System data provide reliable, longitudinal assessments of community integration. Ensuring their acceptability by vulnerable populations is warranted. Acceptability-related perceptions of a mobile sensing application were gathered via focus groups with homeless-experienced Veterans with serious mental illness (n = 19) and individual interviews with providers (n = 5) to inform subsequent application tailoring and testing.

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Recruiting children and families for research studies can be challenging, and re-recruiting former participants for longitudinal research can be even more difficult, especially when a study was not prospectively designed to encompass continuous data collection. In this article, we explain how researchers can set up initial studies to potentially facilitate later waves of data collection; locate former study participants using newer, often digital, tools; schedule families using recruitment phone/email/mail scripts that highlight the many benefits to continued study participation; and confirm appointments with other digital tools. We draw from prior methodological and longitudinal pieces to provide suggestions to others wishing to re-recruit families for longitudinal studies.

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Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network.

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Computational models in the field of cancer research have focused primarily on estimates of biological events based on laboratory generated data. We introduce a novel in-silico technology that takes us to the next level of prediction models and facilitates innovative solutions through the mathematical system. The model's building blocks are cells defined phenotypically as normal or tumor, with biological processes translated into equations describing the life protocols of the cells in a quantitative and stochastic manner.

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