Abstract
Background: The recent surge in commercially available wearable technology has allowed real-time self-monitoring of behavior (eg, physical activity) and physiology (eg, glucose levels). However, there is limited neuroimaging work (ie, functional magnetic resonance imaging [fMRI]) to identify how people’s brains respond to receiving this personalized health feedback and how this impacts subsequent behavior.
Objective: Identify regions of the brain activated and examine associations between activation and behavior.
Methods: This was a pilot study to assess physical activity, sedentary time, and glucose levels over 14 days in 33 adults (aged 30 to 60 years). Extracted accelerometry, inclinometry, and interstitial glucose data informed the construction of personalized feedback messages (eg, average number of steps per day). These messages were subsequently presented visually to participants during fMRI. Participant physical activity levels and sedentary time were assessed again for 8 days following exposure to this personalized feedback.
Results: Independent tests identified significant activations within the prefrontal cortex in response to glucose feedback compared with behavioral feedback (P<.001). Reductions in mean sedentary time (589.0 vs 560.0 minutes per day, P=.014) were observed. Activation in the subgyral area had a moderate correlation with minutes of moderate-to-vigorous physical activity (r=0.392, P=.043).
Conclusion: Presenting personalized glucose feedback resulted in significantly more brain activation when compared with behavior. Participants reduced time spent sedentary at follow-up. Research on deploying behavioral and physiological feedback warrants further investigation.
Original language | English |
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Article number | e384 |
Number of pages | 15 |
Journal | Journal of Medical Internet Research |
Volume | 19 |
Issue number | 11 |
DOIs | |
Publication status | Published - 8 Nov 2017 |
Externally published | Yes |
Bibliographical note
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.Fingerprint
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Maxine Whelan
- Centre for Healthcare and Communities - Assistant Professor Research
Person: Teaching and Research