Publication: Is it just a score? understanding training load management practices beyond sports tracking
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KU-Authors
KU Authors
Co-Authors
Karahanoğlu, Armağan
Postma, Dees
Scheltinga, Bouke Leonard
Gouveia, Rúben
Reidsma, Dennis
Reenalda, Jasper
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Abstract
Training Load Management (TLM) is crucial for achieving optimal athletic performance and preventing chronic sports injuries. Current sports trackers provide runners with data to manage their training load. However, little is known about the extent and the way sports trackers are used for TLM. We conducted a survey (N=249) and interviews (N=24) with runners to understand sports tracker use in TLM practices. We found that runners possess some understanding of training load and generally trust their trackers to provide accurate training load-related data. Still, they hesitate to strictly follow trackers' suggestions in managing their training load, often relying on their intuitions and body signals to determine and adapt training plans. Our findings contribute to SportsHCI research by shedding light on how sports trackers are incorporated into TLM practices and providing implications for developing trackers that better support runners in managing their training load.
Source
Publisher
Association for Computing Machinery
Subject
Computer science
Citation
Has Part
Source
Conference on Human Factors in Computing Systems - Proceedings
Book Series Title
Edition
DOI
10.1145/3613904.3642051