André Henriksen
Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
Gunnar Hartvigsen
Department of Computer Science, UiT The Arctic University of Norway, Tromsø, Norway / Norwegian Centre for E-health Research, University Hospital of North Norway (UNN), Tromsø, Norway
Laila Arnesdatter Hopstock
Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway / Department of Health and Care Sciences, UiT The Arctic University of Norway, Tromsø, Norway
Sameline Grimsgaard
Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
Download article
Published in: Proceedings from The 15th Scandinavian Conference on Health Informatics 2017 Kristiansand, Norway, August 29–30, 2017
Linköping Electronic Conference Proceedings 145:5, p. 28-35
Regularly conducted population cohort studies contribute important new knowledge to medical research. A high participation rate is required in these types of studies in order to claim representativeness and validity of study results. Participation rates are declining worldwide, and re-searchers are challenged to develop new data collection strategies and tools to motivate people to participate.
The last years of advances in sensor and mobile technology, and the widespread use of activity trackers and smart watches, have made it possible to privately collect physical activity data, in a cheap, easy and prolonged way. The unstructured way of collecting this data can have other applications than just showing users their activity trends.
In this paper, we describe our plans for how to use these pervasive sensors as new tools for collecting data on physical activity, in a way that can motivate participants to share more information, for a longer time period and with a renewed motivation to participate in a population study.
Cohort studies, Motor Activity, Fitness Trackers, Heart Rate, Photoplethysmograph
[1] Agile Business Consortium. 2014, The DSDM Agile Project Framework Handbook [Online]. Agile Business Consortium. Available: https://www.agilebusiness.org/content/moscowprioritisation [Accessed 2017-04-03].
[2] Allen, J. 2007, Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement, 28, R1-R39.
[3] Dooley, E. E., Golaszewski, N. M. & Bartholomew, J. B. 2017, Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices. JMIR Mhealth Uhealth, 5, e34.
[4] Emaus, A., Degerstrøm, J., Wilsgaard, T., Hansen, B. H., Dieli-Conwright, C. M., Furberg, A.-S., Pettersen, S. A., Andersen, L. B., Eggen, A. E., Bernstein, L. & Thune, I. 2010, Does a variation in self-reported physical activity reflect variation in objectively measured physical activity, resting heart rate, and physical fitness? Results from the Tromsø study. Scandinavian Journal of Public Health, 38, 105-118.
[5] Evenson, K. R., Goto, M. M. & Furberg, R. D. 2015, Systematic review of the validity and reliability of consumer-wearable activity trackers. The International Journal of Behavioral Nutrition and Physical Activity, 12, 159.
[6] Hartge, P. 2006, Participation in population studies. Epidemiology, 17.
[7] Henriksen, A., Hopstock, L. A., Hartvigsen, G. & Grimsgaard, S. in press. Using cloud-based physical activity data from Google Fit and Apple HealthKit to expand recording of physical activity data in a population study. Stud Health Technol Inform.
[8] International Data Corporation (IDC). 2017, Wearables Aren’t Dead, They’re Just Shifting Focus as the Market Grows 16.9% in the Fourth Quarter, According to IDC [Online]. International Data Corporation (IDC). Available: http://www.idc.com/getdoc.jsp?containerId=prUS42342317 [Accessed 2017-03-02].
[9] Jacobsen, B. K., Eggen, A. E., Mathiesen, E. B., Wilsgaard, T. & Njølstad, I. 2012, Cohort profile: The Tromsø Study. International Journal of Epidemiology, 41, 961-967.
[10] Njølstad, I., Mathiesen, E. B., Schirmer, H. & Thelle, D. S. 2016, The Tromsø study 1974–2016: 40 years of cardiovascular research. Scandinavian Cardiovascular Journal, 1-6.
[11] Reid, R. E. R., Insogna, J. A., Carver, T. E., Comptour, A. M., Bewski, N. A., Sciortino, C. & Andersen, R. E. 2016, Validity and reliability of Fitbit activity monitors compared to ActiGraph GT3X+ with female adults in a free-living environment. Journal of Science and Medicine in Sport.
[12] Stahl, S. E., An, H. S., Dinkel, D. M., Noble, J. M. & Lee, J. M. 2016, How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough? BMJ Open Sport Exerc Med, 2, e000106.
[13] UiT - Department of Community Medicine. 2011, EUTRO [Online]. Available:
https://uit.no/om/enhet/artikkel?p_document_id=255991&p_dimension_id=88111 [Accessed 2017-05-04 2017].
[14] Vandrico Inc. 2016, The wearables database. Vandrico Solutions Inc.
[15] Wallen, M. P., Gomersall, S. R., Keating, S. E., Wisloff, U. & Coombes, J. S. 2016, Accuracy of Heart Rate Watches: Implications for Weight Management. PLoS One, 11, e0154420.
