University students´┐Ż experiences of Fitbit use and interpretations of digital health data (Preprint) Academic Article uri icon

abstract

  • BACKGROUND

    Wearable fitness trackers are becoming increasingly affordable and accessible making them an alluring tool for mHealth interventions and strategies. Research to date has focused primarily on issues of efficacy, accuracy and acceptability with equivocal conclusions, yet little is known about how individuals interpret and make sense of their personalized data in relationship to health. This knowledge could elaborate on existing understandings of user experience and enhance the design and implementation of mHealth initiatives involving self-tracking technology.

    OBJECTIVE

    The objective of this study was to gain an in-depth understanding of how university students respond to and interpret personalized data generated by wearable activity-trackers in relation to health.

    METHODS

    Data were collected through four focus groups (N=26) with university students in New Zealand who voluntarily wore a Fitbit for 7 days for a separate research study. Focus group questions sought to explore how students engaged with and made sense of their digital data in relationship to health and physical activity and their perceptions of the value of the Fitbit.

    RESULTS

    Findings suggest wearing an activity tracker can prompt both positive and negative emotional responses that influence interpretation of data and have implications for behavior change. Results also show that data interpretation is highly dependent on contextual factors and that meanings of health are highly individual. Participants suggested that the knowledge gained through self-tracking was not sufficient to prompt behavior change, and that further support around navigating barriers to physical activity was needed.

    CONCLUSIONS

    Acknowledging the emotional responses evoked by digital data may enhance the design of future mHealth initiatives involving self-tracking technologies. Providing guidance and support around data interpretation may also help maximize the usefulness of these technologies, as the meanings of health-related data appear to be contingent upon the context in which it is generated and interpreted.