@inproceedings{10.1145/3605655.3622796,
author = {Cer\'{o}n-Guzm\'{a}n, Jhon Adri\'{a}n and Tetteroo, Daniel and Hu, Jun and Markopoulos, Panos},
title = {Toward Designing for Social Connectedness in Cardiovascular Disease Self-Care},
year = {2023},
isbn = {9798400708756},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3605655.3622796},
doi = {10.1145/3605655.3622796},
abstract = {When people with chronic conditions are confronted with gaps in their understanding of their health status, they turn to their peers to make sense of their own situation. And yet, little is known about how to design to facilitate locating others in similar situations. Sharing personal health information with their peers is a strategy the sense-maker employs in constructing a new normal after health-related life disruptions. Even so, research on how to design digital health technology that leverages information-sharing behavior is lacking. This paper elaborates on a peer data-sharing model to inform digital health technology design. Based on this model, we herein propose a prototype that promotes social connectedness in cardiovascular disease self-care as a means to advance our understanding of how we might design to facilitate locating peers and gaining new insights into self-care from them.},
booktitle = {Proceedings of the European Conference on Cognitive Ergonomics 2023},
articleno = {22},
numpages = {5},
keywords = {data sharing, peer recommendations, personal health data},
location = {Swansea, United Kingdom},
series = {ECCE '23}
}