Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/36158
Title: The effect of non-personalised tips on the continued use of self-monitoring mHealth applications
Author(s): Unnikrishnan, Vishnu
Schleicher, Miro
Shah, Yash
Jamaludeen, Noor
Pryss, Ruediger
Schobel, Johannes
Kraft, Robin
Schlee, Winfried
Spiliopoulou, Myra
Issue Date: 2020
Type: Article
Language: English
URN: urn:nbn:de:gbv:ma9:1-1981185920-363927
Subjects: Ecological momentary assessments
Physician feedback
Tinnitus
Self-monitoring
Abstract: Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients’ quality of life. Recent advances in mHealth have enabled patients to maintain a ‘disease journal’ of ecologically-valid momentary assessments, improving patients’ own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients’ perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A & Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.
URI: https://opendata.uni-halle.de//handle/1981185920/36392
http://dx.doi.org/10.25673/36158
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Sponsor/Funder: DFG-Publikationsfonds 2020
Journal Title: Brain Sciences
Publisher: MDPI AG
Publisher Place: Basel
Volume: 10
Issue: 12
Original Publication: 10.3390/brainsci10120924
Page Start: 1
Page End: 13
Appears in Collections:Fakultät für Informatik (OA)

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