Unveiling Emotion Regulation with Smartphones In Everyday Life

Primary supervisor

Benjamin Tag

Co-supervisors

The global health crisis has put mental health, emotional well-being, and the risks and importance of digital technologies into the global focus. According to a Lancet Commission report, the number of people with mental disorders is increasing in every country of the world and will cost the global economy US$16 trillion by 2030. Emotions have strong implications not only for mental well-being but also for physical health, e.g., down-regulating negative emotions can lower the risk of heart disease.


This project aims to investigate how smartphones are used for emotion regulation, by deploying biometric sensors (e.g., electrodermal activity, heart rate variability) to detect emotional events that trigger smartphone usage. One of the prerequisites for emotion regulation is the presence of an intention to regulate our emotions. While smartphones offer a plethora of sensors to detect user behaviour, cognitive state changes, and physiological processes, many stimuli influence our emotions to happen in between different smartphone sessions. This project will investigate ways to use physiological sensors to close these information gaps and to detect biometric signal patterns that identify these stimuli.

Student cohort

Single Semester
Double Semester

Aim/outline

The project scope includes:

  • implementation of a smartphone app (Android/iOs) that collects user logs, and triggers ESMs (potential use of other sensors) – frameworks such as https://sema3.com/, and https://www.aware-light.org/ can be used
  • drafting an ethics application for running a user study (together with the supervisor)
  • implementation of a user study protocol
  • conducting a user study in the wild to record biometric and subjective data and smartphone usage information
  • analysis of biometric data recorded during user study
  • optional: development of ML algorithm to detect patterns characteristic of episodes of significant emotional changes, validation study

URLs/references

Recommended Literature:

  • Gross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), Handbook of emotion regulation (pp. 3–20). The Guilford Press.
  • Gross, J. J. (1998). The Emerging Field of Emotion Regulation: An Integrative Review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271
  • Brans, K., Koval, P., Verduyn, P., Lim, Y. L., & Kuppens, P. (2013). The regulation of negative and positive affect in daily life. Emotion, 13(5), 926–939.
  • Wally Smith, Greg Wadley, Sarah Webber, Benjamin Tag, Vassilis Kostakos, Peter Koval, and James J. Gross. 2022. Digital Emotion Regulation in Everyday Life. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 444, 1–15. https://doi.org/10.1145/3491102.3517573
  • Gross, J. J. (1998). The Emerging Field of Emotion Regulation: An Integrative Review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271
  • Tag, B., Sarsenbayeva, Z., Cox, A. L., Wadley, G., Goncalves, J., & Kostakos, V. (2022). Emotion trajectories in smartphone use: Towards recognizing emotion regulation in-the-wild. International Journal of Human-Computer Studies, 166, 102872. https://doi.org/https://doi.org/10.1016/j.ijhcs.2022.102872
  • Tag, B., van Berkel, N., Vargo, A. W., Sarsenbayeva, Z., Colasante, T., Wadley, G., Webber, S., Smith, W., Koval, P., Hollenstein, T., & others. (2022). Impact of the global pandemic upon young People’s use of technology for emotion regulation. Computers in Human Behavior Reports, 100192.

    Required knowledge

    Skills required (one or more are necessary):

    • Programming / Development experience (mobile: Android/iOS)
    • Data analysis – Python/R  (incl. physiological data, ESM data, pattern recognition)
    • optional: Machine Learning

    Beneficial:

    • Academic writing/research skills
    • Interest in running user studies
    • Independent decision making