TY - GEN
T1 - Trackable Me
T2 - 58th Hawaii International Conference on System Sciences, HICSS 2025
AU - Reindl-Spanner, Philipp
AU - Prommegger, Barbara
AU - Gensichen, Jochen
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© 2025 IEEE Computer Society. All rights reserved.
PY - 2025
Y1 - 2025
N2 - Using patient-generated health data (PGHD) in depression care can provide valuable insights into patients' health. Due to the technical possibilities, patients can collect many PGHD types. However, these are not necessarily highly relevant to depression and are not considered relevant by all users. We, therefore, examined the relevance of various PGHD types for the treatment of depression and identified different types of users based on their data preferences. We surveyed 170 participants with depression and created a ranking for the most relevant data types. With subsequent cluster analysis, we identified four different user types: "Track-it-alls", "Medical Trackers", "Psychological Trackers," and "Untrackables". Based on these clusters, we show different possibilities for which user group and which types of PGHD are most suitable. With the results of this paper, we underline the need for tailored PGHD apps to improve personalized care in depression treatment.
AB - Using patient-generated health data (PGHD) in depression care can provide valuable insights into patients' health. Due to the technical possibilities, patients can collect many PGHD types. However, these are not necessarily highly relevant to depression and are not considered relevant by all users. We, therefore, examined the relevance of various PGHD types for the treatment of depression and identified different types of users based on their data preferences. We surveyed 170 participants with depression and created a ranking for the most relevant data types. With subsequent cluster analysis, we identified four different user types: "Track-it-alls", "Medical Trackers", "Psychological Trackers," and "Untrackables". Based on these clusters, we show different possibilities for which user group and which types of PGHD are most suitable. With the results of this paper, we underline the need for tailored PGHD apps to improve personalized care in depression treatment.
KW - Health information technology (HIT)
KW - Mental Health Care
KW - Mobile Applications
KW - Patient-Centered Care
UR - https://www.scopus.com/pages/publications/105005141030
U2 - 10.24251/hicss.2025.429
DO - 10.24251/hicss.2025.429
M3 - Conference contribution
AN - SCOPUS:105005141030
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 3573
EP - 3582
BT - Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025
A2 - Bui, Tung X.
PB - IEEE Computer Society
Y2 - 7 January 2025 through 10 January 2025
ER -