Abstract
Smartphone-based digital phenotyping can provide insight into mood, cognition and behaviour. In this study, data analytics was carried out with data generated from a maternal mental health app to address the following question: what is the temporal behaviour of users when completing ecological momentary assessments (EMAs) with EMAs in the form of mental health scales versus EMAs in the form of mood logs? The methodology involved using the Health Interaction Log Data Analytics (HILDA) pipeline to analyse 1461 app users. Clustering was used to characterise archetypical user engagement with the two forms of EMA. Users preferred mood log EMAs, with 6993 mood log completions compared to 2129 scale completions. Users are more willing to log moods at 9am and 12pm and complete mental health scales between 8pm and 10pm. The fewest number of mood logs and scale completions take place on Saturday followed by a Sunday. Whilst ‘happiness’ is the dominant mood during day times, ‘anxiety’ and ‘sadness’ peak during night times. The overall findings are that users prefer completing mood log EMAs and that the temporal behaviour of users engaging with EMAs in the form of mental health scales are distinctly different from how they engage with mood logs.
Original language | English |
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Pages (from-to) | 1016-1027 |
Number of pages | 12 |
Journal | Behaviour and Information Technology |
Volume | 38 |
Issue number | 10 |
Early online date | 8 Aug 2019 |
DOIs | |
Publication status | Published (in print/issue) - 3 Oct 2019 |
Keywords
- Behaviour analytics
- digital phenotyping
- user tenure
- ecological moment
- mental health scales
- mood logs
- ecological momentary assessment
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Raymond Bond
- School of Computing - Professor of Human Computer Systems
- Faculty Of Computing, Eng. & Built Env. - Full Professor
Person: Academic