Exploring Temporal Behaviour of App Users Completing Ecological Momentary Assessments using Mental Health Scales and Mood Logs

Research output: Contribution to journalArticle

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.
LanguageEnglish
Number of pages12
JournalBehaviour and Information Technology
Early online date8 Aug 2019
DOIs
Publication statusE-pub ahead of print - 8 Aug 2019

Fingerprint

Application programs
mood
Mental Health
mental health
Health
Smartphones
Pipelines
Ecological Momentary Assessment
Mood
Happiness
happiness
Cognition
Cluster Analysis
cognition
Anxiety
anxiety
methodology
interaction
health

Keywords

  • Behaviour analytics
  • digital phenotyping
  • user tenure
  • ecological moment
  • mental health scales
  • mood logs
  • ecological momentary assessment

Cite this

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title = "Exploring Temporal Behaviour of App Users Completing Ecological Momentary Assessments using Mental Health Scales and Mood Logs",
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.",
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