Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Behavioural data analytics and user log analysis can be useful to gain insight into how users interact with technologies. In this study, data analytics were conducted on maternal mental health data generated from the Moment Health app to address the question: What is the temporal behaviour of users when completing ecological momentary assessments (EMA) on a mental health app, with EMAs in the form of full mental health scales versus EMAs in the form of mood logs? The Health Interaction Log Data Analytics (HILDA) pipeline was used to analyse 1,461 users of the app. More users completed single mood logs EMAs (n=6,993) compared to scaled EMAs (n=2,129). Distinct temporal patterns were identified, with more users willing to log moods at 9am and 12pm as opposed to completing a scale. The most common hours for users to complete scaled EMAs are between 8pm and 10pm. The least number of mood logs and scale completions take place on Saturday. Whilst happiness is the dominant mood during day times, anxiety and sadness peak during the night at 1am and 4am respectively. The data indicates that postnatal depression decreases over time for some users (r = -0.23, p-value < 0.01). The overall finding from this work are that users prefer simple EMA approaches and that the temporal behavior of users engaging with the two forms of EMA are distinctly different.

LanguageEnglish
Title of host publicationECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics
Subtitle of host publication''Design for Cognition''
EditorsMaurice Mulvenna, Raymond Bond
Place of PublicationNew York, NY, USA
Pages203-206
Number of pages4
ISBN (Electronic)978-1-4503-7166-7
DOIs
Publication statusPublished - 10 Sep 2019
Event31st European Conference on Cognitive Ergonomics: Design for Cognition - Belfast, United Kingdom
Duration: 10 Sep 201913 Sep 2019
https://www.ulster.ac.uk/conference/european-conference-on-cognitive-ergonomics

Publication series

NameICPS
PublisherACM

Conference

Conference31st European Conference on Cognitive Ergonomics
Abbreviated titleECCE 2019
CountryUnited Kingdom
CityBelfast
Period10/09/1913/09/19
Internet address

Fingerprint

Smartphones
Application programs
Health
Pipelines

Keywords

  • Behaviour analytics
  • User tenure
  • digital well-being
  • ecological momentary assessment
  • experience sampling method
  • mental health scales
  • mood logs
  • apps
  • Digital well-being
  • Experience sampling method
  • Mental health scales
  • Apps
  • Ecological momentary assessment
  • Mood logs

Cite this

Bond, RR., Moorhead, A., Mulvenna, M., O'Neill, S., Potts, C., & Murphy, N. (2019). Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App. In M. Mulvenna, & R. Bond (Eds.), ECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics: ''Design for Cognition'' (pp. 203-206). (ICPS). New York, NY, USA. https://doi.org/10.1145/3335082.3335111
Bond, RR ; Moorhead, Anne ; Mulvenna, Maurice ; O'Neill, Siobhan ; Potts, Courtney ; Murphy, Nuala. / Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App. ECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics: ''Design for Cognition''. editor / Maurice Mulvenna ; Raymond Bond. New York, NY, USA, 2019. pp. 203-206 (ICPS).
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abstract = "Behavioural data analytics and user log analysis can be useful to gain insight into how users interact with technologies. In this study, data analytics were conducted on maternal mental health data generated from the Moment Health app to address the question: What is the temporal behaviour of users when completing ecological momentary assessments (EMA) on a mental health app, with EMAs in the form of full mental health scales versus EMAs in the form of mood logs? The Health Interaction Log Data Analytics (HILDA) pipeline was used to analyse 1,461 users of the app. More users completed single mood logs EMAs (n=6,993) compared to scaled EMAs (n=2,129). Distinct temporal patterns were identified, with more users willing to log moods at 9am and 12pm as opposed to completing a scale. The most common hours for users to complete scaled EMAs are between 8pm and 10pm. The least number of mood logs and scale completions take place on Saturday. Whilst happiness is the dominant mood during day times, anxiety and sadness peak during the night at 1am and 4am respectively. The data indicates that postnatal depression decreases over time for some users (r = -0.23, p-value < 0.01). The overall finding from this work are that users prefer simple EMA approaches and that the temporal behavior of users engaging with the two forms of EMA are distinctly different.",
keywords = "Behaviour analytics, User tenure, digital well-being, ecological momentary assessment, experience sampling method, mental health scales, mood logs, apps, Digital well-being, Experience sampling method, Mental health scales, Apps, Ecological momentary assessment, Mood logs",
author = "RR Bond and Anne Moorhead and Maurice Mulvenna and Siobhan O'Neill and Courtney Potts and Nuala Murphy",
year = "2019",
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doi = "10.1145/3335082.3335111",
language = "English",
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Bond, RR, Moorhead, A, Mulvenna, M, O'Neill, S, Potts, C & Murphy, N 2019, Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App. in M Mulvenna & R Bond (eds), ECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics: ''Design for Cognition''. ICPS, New York, NY, USA, pp. 203-206, 31st European Conference on Cognitive Ergonomics, Belfast, United Kingdom, 10/09/19. https://doi.org/10.1145/3335082.3335111

Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App. / Bond, RR; Moorhead, Anne; Mulvenna, Maurice; O'Neill, Siobhan; Potts, Courtney; Murphy, Nuala.

ECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics: ''Design for Cognition''. ed. / Maurice Mulvenna; Raymond Bond. New York, NY, USA, 2019. p. 203-206 (ICPS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Mulvenna, Maurice

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AU - Potts, Courtney

AU - Murphy, Nuala

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N2 - Behavioural data analytics and user log analysis can be useful to gain insight into how users interact with technologies. In this study, data analytics were conducted on maternal mental health data generated from the Moment Health app to address the question: What is the temporal behaviour of users when completing ecological momentary assessments (EMA) on a mental health app, with EMAs in the form of full mental health scales versus EMAs in the form of mood logs? The Health Interaction Log Data Analytics (HILDA) pipeline was used to analyse 1,461 users of the app. More users completed single mood logs EMAs (n=6,993) compared to scaled EMAs (n=2,129). Distinct temporal patterns were identified, with more users willing to log moods at 9am and 12pm as opposed to completing a scale. The most common hours for users to complete scaled EMAs are between 8pm and 10pm. The least number of mood logs and scale completions take place on Saturday. Whilst happiness is the dominant mood during day times, anxiety and sadness peak during the night at 1am and 4am respectively. The data indicates that postnatal depression decreases over time for some users (r = -0.23, p-value < 0.01). The overall finding from this work are that users prefer simple EMA approaches and that the temporal behavior of users engaging with the two forms of EMA are distinctly different.

AB - Behavioural data analytics and user log analysis can be useful to gain insight into how users interact with technologies. In this study, data analytics were conducted on maternal mental health data generated from the Moment Health app to address the question: What is the temporal behaviour of users when completing ecological momentary assessments (EMA) on a mental health app, with EMAs in the form of full mental health scales versus EMAs in the form of mood logs? The Health Interaction Log Data Analytics (HILDA) pipeline was used to analyse 1,461 users of the app. More users completed single mood logs EMAs (n=6,993) compared to scaled EMAs (n=2,129). Distinct temporal patterns were identified, with more users willing to log moods at 9am and 12pm as opposed to completing a scale. The most common hours for users to complete scaled EMAs are between 8pm and 10pm. The least number of mood logs and scale completions take place on Saturday. Whilst happiness is the dominant mood during day times, anxiety and sadness peak during the night at 1am and 4am respectively. The data indicates that postnatal depression decreases over time for some users (r = -0.23, p-value < 0.01). The overall finding from this work are that users prefer simple EMA approaches and that the temporal behavior of users engaging with the two forms of EMA are distinctly different.

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KW - experience sampling method

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KW - Digital well-being

KW - Experience sampling method

KW - Mental health scales

KW - Apps

KW - Ecological momentary assessment

KW - Mood logs

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Bond RR, Moorhead A, Mulvenna M, O'Neill S, Potts C, Murphy N. Behaviour Analytics of Users Completing Ecological Momentary Assessments in the Form of Mental Health Scales and Mood Logs on a Smartphone App. In Mulvenna M, Bond R, editors, ECCE 2019 - Proceedings of the 31st European Conference on Cognitive Ergonomics: ''Design for Cognition''. New York, NY, USA. 2019. p. 203-206. (ICPS). https://doi.org/10.1145/3335082.3335111