The use of self-monitoring solutions amongst cyclists: An online survey and empirical study |
| |
| Institution: | 1. University of South Australia, Adelaide, Australia;2. Shiraz University, Shiraz, Iran;3. University of Transport and Communications, Hanoi, Viet Nam;1. Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA;2. Brown School, Washington University in St. Louis, St. Louis, MO, USA;3. Prevention Research Center in St. Louis, Washington University in St. Louis, St. Louis, MO, USA;4. Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA;1. Research Institute for East Asia Environments, Kyushu University, W2-1023, 744, Motooka, Nishi-ku, Fukuoka 819-0395, Japan;2. Department of International Development Engineering, Tokyo Institute of Technology, 2-12-1-I4-4, O-okayama, Meguro-ku, Tokyo 152-8550, Japan;1. NZ Centre for Sustainable Cities, Department of Public Health, University of Otago Wellington, P.O. Box 7343, Wellington South, New Zealand;2. NZ Centre for Sustainable Cities, and Victoria University of Wellington, Environmental Studies Programme, SGEES, P.O. Box 600, Wellington, New Zealand;3. NZ Centre for Sustainable Cities, and Victoria University of Wellington, P.O. Box 600, Wellington, New Zealand;1. MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 200 Renfield Street, Glasgow G2 3QB, United Kingdom;2. Centre for Research on Environment, Society and Health (CRESH), Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ, United Kingdom |
| |
| Abstract: | Self-monitoring has been shown to be one of the most efficient behaviour change techniques to promote physical activity. However, there has been no research on the exact nature and impact of using various self-monitoring solutions (e.g. cycle computer, cadence monitor, smartphone’ physical activity apps) amongst cyclists. Initially, an online survey was conducted with 227 adults who did or did not use self-monitoring solutions with their cycling. We found that the most important features for cyclists who use self-monitoring are: time it takes to travel, cycling speed, and distance covered. In contrast, cyclists who do not use self-monitoring perceived features related to location (e.g. directions with maps) as the most important ones. In a subsequent study we included self-monitoring solutions as a part of mixed-design, small-scale, longitudinal intervention aimed at changing transportation patterns. We found that self-monitoring is mainly suitable for performance oriented cyclists rather then recreational cyclists. We discuss the implications of those results for designing interventions to promote cycling. |
| |
| Keywords: | Cycling Bicycling Self-monitoring Intervention Wearable computing |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
