Abstract
The Experience Sampling Method (ESM) introduces in-situ sampling of human behaviour, and provides researchers and behavioural therapists with ecologically valid and timely assessments of a person’s psychological state. This, in turn, opens up new opportunities for understanding behaviour at a scale and granularity that was not possible just a few years ago. The practical applications are many, such as the delivery of personalised and agile behaviour interventions. Mobile computing devices represent a revolutionary platform for improving ESM. They are an inseparable part of our daily lives, context-aware, and can interact with people at suitable moments. Furthermore, these devices are equipped with sensors, and can thus take part of the reporting burden off the participant, and collect data automatically. The goal of this survey is to discuss recent advancements in using mobile technologies for ESM (mESM), and present our vision of the future of mobile experience sampling.
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Notes
- 1.
Every effort has been made to provide truthful descriptions of the listed mESM frameworks, however, due to limited documentation and publications related to some of the frameworks the listed properties should be taken with caution.
- 2.
The goal of this article is to suggest guidelines for future research in the field, thus we concentrate on free open-source software developed in academia, as such software can serve as a basis for next generation mESM frameworks. Commercial products for supporting mESM are outside the scope of our article.
- 3.
InterruptMe is available as a free open-source software at http://bitbucket.org/veljkop/intelligenttrigger.
- 4.
The following URL lists currently running experience sampling projects using the Ohmage framework: http://ohmage.org/projects.html.
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Acknowledgments
This work was supported through the EPSRC grants “UBhave: ubiquitous and social computing for positive behaviour change” (EP/I032673/1) and “Trajectories of Depression: Investigating the Correlation between Human Mobility Patterns and Mental Health Problems by means of Smartphones” (P/L006340/1).
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Pejovic, V., Lathia, N., Mascolo, C., Musolesi, M. (2016). Mobile-Based Experience Sampling for Behaviour Research. In: Tkalčič, M., De Carolis, B., de Gemmis, M., Odić, A., Košir, A. (eds) Emotions and Personality in Personalized Services. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-31413-6_8
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