TY - GEN
T1 - Prehabilitation
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
AU - Zhu, Haining
AU - Moffa, Zachary J.
AU - Gui, Xinning
AU - Carroll, John M.
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Millions of surgeries are performed in the US annually, and numbers are trending upwards. Traditional rehabilitative interventions are struggling to meet current demands, and researchers have turned to pre-operative interventions, or prehabilitation, to improve patient functions. However, existing literature primarily discusses efficacy or the use of commercial sensing devices, and lacks a clear comprehension of healthcare professionals' (HPs') needs and perspectives. User-centered stakeholder understandings are crucial for a technology's adoption, but prehabilitation literature lacks such understandings. Therefore we conduct semi-structured interviews with 12 prehabilitation healthcare professionals (HPs) to offer descriptions of care challenges, tool usage, and perspectives regarding suitable and effective technologies. These data can assist designers in fostering prehabilitation processes via tailored prehabilitation tools which meet HPs' needs and expectations.
AB - Millions of surgeries are performed in the US annually, and numbers are trending upwards. Traditional rehabilitative interventions are struggling to meet current demands, and researchers have turned to pre-operative interventions, or prehabilitation, to improve patient functions. However, existing literature primarily discusses efficacy or the use of commercial sensing devices, and lacks a clear comprehension of healthcare professionals' (HPs') needs and perspectives. User-centered stakeholder understandings are crucial for a technology's adoption, but prehabilitation literature lacks such understandings. Therefore we conduct semi-structured interviews with 12 prehabilitation healthcare professionals (HPs) to offer descriptions of care challenges, tool usage, and perspectives regarding suitable and effective technologies. These data can assist designers in fostering prehabilitation processes via tailored prehabilitation tools which meet HPs' needs and expectations.
UR - http://www.scopus.com/inward/record.url?scp=85091323146&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091323146&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376594
DO - 10.1145/3313831.3376594
M3 - Conference contribution
AN - SCOPUS:85091323146
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -