Large Scale, Long-Term, High Granularity Measurement of Active Travel Using Smartphones Apps

Abstract

Accurate, long-term data are needed in order to determine trends in active travel, to examine the effectiveness of any interventions and to quantify the health, social and economic consequences of active travel. However, most studies of individual travel behaviour have either used self-report (which is limited in detail and open to bias), or provided logging devices for short periods, so lack the ability to monitor long-term trends. We have developed apps using participants' own smartphones (Android or iOS) that monitor and feed-back individual user's physical activity whilst the phone is carried or worn. The nature, time and location of any physical activity are uploaded to a secure survey and allow researchers to identify large scale behaviour. Pilot data from almost 2000 users have been logged and are reported. This constitutes a natural experiment, collecting long-term physical activity, transport mode and route choice information across a large cross-section of users.

Proof of concept and feasibility of the app-based ‘#SWPMoveMore Challenge’: Impacts on physical activity and well-being in a police population

“…The NCSEM partnership committed to a vision and 5-year whole-systems plan to transform Sheffield into the most active city in the UK (Copeland, 2020). Mass participation events that engage individuals, communities and organizations are a key part of the Move More TM plan, manifested in one way through an annual physical activity challenge called the Move More TM Month (see Heller et al ., 2018). The Move More TM Month signposts, supports and connects people and families with opportunities to be active; and, in 2016 a first iteration of a Move More TM App was developed to facilitate a physical activity challenge linked to the Rio Olympic Games.…”