The feasibility of a context aware smoking cessation app (Q Sense): a mixed methods study

Abstract

Background: We investigated the feasibility of a context aware smoking cessation app (Q Sense) which uses a smoking episode reporting system with location sensing to inform support content and delivery. Methods: A mixed methods study using an interpretive integration framework. Participants were smokers (N=15) owning an Android smartphone and willing to set a quit date. App data included smoking reports with geospatial location and ‘end of day’ (EoD) surveys. Semi-structured interviews (n=13) were analysed thematically to explore app usage. Findings: Pre-quit date, mean daily smoking reports was 2.0 (SD 1.1) with 60.0% of EoD surveys completed. Participants underreported smoking episodes on at least 63.3% of days. Forgetting was the primary reason for non-reporting. 95.2% of reports included geospatial location (mean accuracy = 31.8 meters). Of those reaching their app quit date, 44% received geofence (‘high risk’ locations with >4 reports) triggered support and were broadly positive about their value. Discussion: Collecting real-time behaviour to inform a context aware intervention was feasible and seen positively. Underreporting of smoking and handset/app technical interactions preventing geofence support are areas for future focus.