Abstract
Planned disruptions such as highway construction typically have negative impact on the health & wellbeing of people living in the surrounding communities due to increased air and noise pollution as well as inconveniences such road closures. Further, these communities typically tend to have low socio-economic status with high unemployment rate and limited resources (Environmental Justice Communities). The goal of this paper is to understand this impact via a smartphone app called PUREmotion providing ecological momentary assessment. We describe the deployment of PUREmotion in a four-month study with people living in the vicinity of a major construction project (C70 project) in North Denver, Colorado. The PUREmotion app is built based on the results of several focus groups and three rounds of usability study with people from these communities. We deployed the PUREmotion app over two time periods of six weeks each with about 100 community participants in each time period. In this paper, we report on our experience of these deployments and provide a detailed analysis of the data we collected to assess the impact of construction on health and wellbeing of the people. Our findings show that living near such construction projects has a direct (negative) impact on people’s wellbeing due to air pollution, bad odor, increased noise, and disruptions in daily commutes.
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References
Ahmed Ali, K., Ahmad, M.I., Yusup, Y.: Issues, impacts, and mitigations of carbon dioxide emissions in the building sector. Sustainability 12(18), 7427 (2020)
Bolaji, B.O., Olanipekun, M.U., Adekunle, A.A., Adeleke, A.E.: An analysis of noise and its environmental burden on the example of Nigerian manufacturing companies. J. Clean. Prod. 172, 1800–1806 (2018)
Chan, L., Swain, V.D., Kelley, C., de Barbaro, K., Abowd, G.D., Wilcox, L.: Students’ experiences with ecological momentary assessment tools to report on emotional well-being. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol. 2(1), 3:1–3:20 (2018)
Chen, H.c., Chung, W., Xu, J., Wang, G., Qin, Y., Chau, M.: Crime data mining: a general framework and some examples. Computer 37, 50–56 (2004)
Choe, E.K., et al.: Semi-automated tracking: a balanced approach for self-monitoring applications. IEEE Perv. Comput. 16(1), 74–84 (2017). ISBN 1536-1268
H, L.: Systematic evaluation and assessment of building environmental performance (SEABEP) (2013). Accessed 30 Mar 2015 T15:49+02:00
Harari, G.M., Lane, N.D., Wang, R., Crosier, B.S., Campbell, A.T., Gosling, S.D.: Using smartphones to collect behavioral data in psychological science: opportunities, practical considerations, and challenges. Pers. Psychol. Sci. 11(6), 838–854 (2016). ISBN 1745-6916
Jones, S.L., Hue, W., Kelly, R.M., Barnett, R., Henderson, V., Sengupta, R.: Determinants of longitudinal adherence in smartphone-based self-tracking for chronic health conditions: evidence from axial spondyloarthritis. Proc. ACM Interact. Mobile Wearable Ubiquit. Technol. 5(1), 16:1–16:24 (2021)
Kim, Y.H., Jeon, J.H., Lee, B., Choe, E.K., Seo, J.: OmniTrack: a flexible self-tracking approach leveraging semi-automated tracking. Proc. ACM Interact. Mob. Wearable Ubiquit. Technolog. 1(3), 67:1–67:28 (2017)
King, Z.D., et al.: Micro-Stress EMA: a passive sensing framework for detecting in-the-wild stress in pregnant mothers. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol. 3(3), 91:1–91:22 (2019)
Knaap, T., Oosterhaven, J.: Measuring the welfare effects of infrastructure: a simple spatial equilibrium evaluation of Dutch railway proposals. Res. Transp. Econ. 31(1), 19–28 (2011)
Li, I., Dey, A.K., Forlizzi, J.: Using context to reveal factors that affect physical activity. ACM Trans. Comput.-Hum. Interact. (TOCHI) 19(1), 1–21 (2012). ISBN 1073-0516
Shen, L.Y., Lu, W.S., Yao, H., Wu, D.H.: A computer-based scoring method for measuring the environmental performance of construction activities. Autom. Constr. 14(3), 297–309 (2005)
To, T., et al.: Health risk of air pollution on people living with major chronic diseases: a Canadian population-based study. BMJ Open 5(9), e009075 (2015)
Tong, C., Craner, M., Vegreville, M., Lane, N.D.: Tracking fatigue and health state in multiple sclerosis patients using connnected wellness devices. Proc. ACM Interact. Mobile Wearable Ubiquit. Technol. 3(3), 106:1–106:19 (2019)
Wang, R., et al.: Tracking depression dynamics in college students using mobile phone and wearable sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(1), 43:1–43:26 (2018)
Xue, X., Zhang, R., Zhang, X., Yang, R.J., Li, H.: Environmental and social challenges for urban subway construction: an empirical study in China. Int. J. Project Manage. 33(3), 576–588 (2015)
Zhang, X., Li, W., Chen, X., Lu, S.: MoodExplorer: towards compound emotion detection via smartphone sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1(4), 176:1–176:30 (2018)
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Hammad, O., Hollo, A.K., Clements, N., Miller, S., Mishra, S., Sullivan, E. (2025). PUREmotion: Understanding the Impact of Highway Construction on People’s Wellbeing. In: Aiello, L.M., Chakraborty, T., Gaito, S. (eds) Social Networks Analysis and Mining. ASONAM 2024. Lecture Notes in Computer Science, vol 15213. Springer, Cham. https://doi.org/10.1007/978-3-031-78548-1_5
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DOI: https://doi.org/10.1007/978-3-031-78548-1_5
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