When a child is hospitalized, existing support networks spring into action. In this unanticipated, stressful situation, parents must quickly absorb complicated clinical information and take on new caregiving tasks, without abandoning other responsibilities. Furthermore, within-family communication and coping strategies of the parents, or dyad, are significant predictors of post-hospitalization health outcomes. Human-Computer Interaction and Computer-Supported Cooperative Work researchers are actively studying how technology can support coordination between children and their care team, and between parents and children. However, little research has focused on how technology can support and augment the parenting dyad during hospitalization. Current technologies are not optimized for these contexts, and may even compound family stress if not carefully designed and implemented.
The long-term goal of this project is to establish fundamental design strategies for social computing that enable effective dyadic caregiving coordination in unanticipated, stressful situations, such as the hospitalization of one's child, and show how those technologies could support decision-making and information sharing amid high degrees of uncertainty. The specific objective of this proposal is to identify and demonstrate how social technologies can support and augment the ability of parenting dyads to effectively communicate and coordinate during hospitalization. Through a combination of rigorous qualitative investigations, parent-driven design sessions, and hospital-based pilot technology deployments, the investigator will address two specific aims: 1) Characterize current communication and coordination practices within parenting dyads, and 2) Envision, demonstrate, and verify dyadic caregiving support technologies. This work will be grounded in the case of pediatric cancer, the leading cause of disease-related deaths in youth. However, the proposed work has implications for dyadic caregiving in diverse healthcare contexts.
This project is funded by the National Science Foundation's Smart and Connected Health program. Read more