Search (3 results, page 1 of 1)

  • × author_ss:"Boyd, K."
  • × year_i:[2020 TO 2030}
  1. Lindau, S.T.; Makelarski, J.A.; Abramsohn, E.M.; Beiser, D.G.; Boyd, K.; Huang, E.S.; Paradise, K.; Tung, E.L.: Sharing information about health-related resources : observations from a community resource referral intervention trial in a predominantly African American/Black community (2022) 0.00 
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    Abstract
    CommunityRx is a theory-driven, information technology-based intervention, developed with and in a predominantly African American/Black community, that provides patients with personalized information (a "HealtheRx") about self-management and social care resources in their community. We described patient and clinician information sharing after exposure to the intervention during a clinical trial. Survey data from 145 patients (ages 45-74) and 121 clinicians were analyzed. Of patients who shared information at least once (49%), 47% reported sharing =3 times (range 1-14). Patient sharers were in poorer physical health (mean PCS 37.6 vs. 40.8, p = .05) than nonsharers and more likely to report going to a resource on their HealtheRx (79 vs. 41%, p = .05). Most patient sharers provided others a look at or copy of their HealtheRx, keeping the original. Patients used the HealtheRx to promote credibility of the information and communicate that resources were disease-specific and local. Half of clinicians shared HealtheRx resource information with peers; sharers were 3 times more likely than nonsharers to feel they were well-informed about resources to address social needs (55 vs. 18%, p < .01). Information sharing by clinicians and patients is an understudied mechanism that could amplify the effects of a growing class of community resource referral information technologies.
    Type
    a
  2. Oesterlund, C.; Jarrahi, M.H.; Willis, M.; Boyd, K.; Wolf, C.T.: Artificial intelligence and the world of work : a co-constitutive relationship (2021) 0.00 
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    Abstract
    The use of intelligent machines-digital technologies that feature data-driven forms of customization, learning, and autonomous action-is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information professionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination network (note: https://waim.network).
    Type
    a
  3. Jarrahi, M.H.; Lutz, C.; Boyd, K.; Oesterlund, C.; Willis, M.: Artificial intelligence in the work context (2023) 0.00 
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    Type
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