Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care

Philipp Reindl-Spanner; Barbara Prommegger; Jochen Gensichen; Helmut Krcmar

doi:10.24251/hicss.2025.429

Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care

Philipp Reindl-Spanner
, Barbara Prommegger
, Jochen Gensichen
, Helmut Krcmar

Technical University of Munich
Ludwig-Maximilians-Universität München

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025
Editors	Tung X. Bui
Publisher	IEEE Computer Society
Pages	3573-3582
Number of pages	10
ISBN (Electronic)	9780998133188
DOIs	https://doi.org/10.24251/hicss.2025.429
State	Published - 2025
Event	58th Hawaii International Conference on System Sciences, HICSS 2025 - Honolulu, United States Duration: 7 Jan 2025 → 10 Jan 2025

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)	1530-1605

Conference

Conference	58th Hawaii International Conference on System Sciences, HICSS 2025
Country/Territory	United States
City	Honolulu
Period	7/01/25 → 10/01/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Health information technology (HIT)
Mental Health Care
Mobile Applications
Patient-Centered Care

Access to Document

10.24251/hicss.2025.429

Cite this

Reindl-Spanner, P., Prommegger, B., Gensichen, J., & Krcmar, H. (2025). Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care. In T. X. Bui (Ed.), Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025 (pp. 3573-3582). (Proceedings of the Annual Hawaii International Conference on System Sciences). IEEE Computer Society. https://doi.org/10.24251/hicss.2025.429

Reindl-Spanner, Philipp ; Prommegger, Barbara ; Gensichen, Jochen et al. / Trackable Me : Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care. Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025. editor / Tung X. Bui. IEEE Computer Society, 2025. pp. 3573-3582 (Proceedings of the Annual Hawaii International Conference on System Sciences).

@inproceedings{54fdbcdeffc14f8ab5be6e017139dfa9,

title = "Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care",

abstract = "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.",

keywords = "Health information technology (HIT), Mental Health Care, Mobile Applications, Patient-Centered Care",

author = "Philipp Reindl-Spanner and Barbara Prommegger and Jochen Gensichen and Helmut Krcmar",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE Computer Society. All rights reserved.; 58th Hawaii International Conference on System Sciences, HICSS 2025 ; Conference date: 07-01-2025 Through 10-01-2025",

year = "2025",

doi = "10.24251/hicss.2025.429",

language = "English",

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Reindl-Spanner, P, Prommegger, B, Gensichen, J & Krcmar, H 2025, Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care. in TX Bui (ed.), Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025. Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE Computer Society, pp. 3573-3582, 58th Hawaii International Conference on System Sciences, HICSS 2025, Honolulu, United States, 7/01/25. https://doi.org/10.24251/hicss.2025.429

Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care. / Reindl-Spanner, Philipp; Prommegger, Barbara; Gensichen, Jochen et al.
Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025. ed. / Tung X. Bui. IEEE Computer Society, 2025. p. 3573-3582 (Proceedings of the Annual Hawaii International Conference on System Sciences).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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.

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ER -

Reindl-Spanner P, Prommegger B, Gensichen J, Krcmar H. Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care. In Bui TX, editor, Proceedings of the 58th Hawaii International Conference on System Sciences, HICSS 2025. IEEE Computer Society. 2025. p. 3573-3582. (Proceedings of the Annual Hawaii International Conference on System Sciences). doi: 10.24251/hicss.2025.429

Trackable Me: Relevant Data and User Types for the Tracking of Patient-Generated Health Data in Depression Care

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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