"Mate! I'm running 10 min late": An investigation into the self-regulation of mobile phone tasks while driving.

The adaptive behaviour of mobile phone distracted drivers has been a topic of much discussion in the recent literature, but the mechanisms of behavioural adaptation are still unclear. This study investigated the influence of driving demands, secondary task characteristics, and personal characteristics on behavioural adaptation of mobile phone distracted drivers. In particular, distracted drivers' self-regulation at strategic, tactical, and operational levels was investigated through a driving simulator experiment. In a high-fidelity driving simulator, participants driving through various driving conditions (e.g. interactions with pedestrian crossings, signalized intersections, merging ramps, roundabouts, etc.) needed to decide where and how to perform the following four mobile phone tasks: (a) ring a doctor and cancel an appointment, (b) text a friend and tell him/her that the participant will be arriving 10 min late, (c) share the doctor's phone number with a friend, and (d) take a 'selfie'. At a strategic level, the decision to pull over was modelled as a function of self-reported personal/attitudinal characteristics with a logistic regression model. Similarly, tactical self-regulation (decision to engage in a task while driving in a specific situation) and operational self-regulation (decision to temporarily stop the mobile phone task) were modelled as a function of driving demands and personal/attitudinal characteristics using a random-effects logistic regression model, which accounts for correlations resulting from multiple observations of a driver. Results suggest that tactical self-regulation is more common among distracted drivers followed by operational and strategic self-regulation. Personal beliefs regarding how safe it is to use the mobile phone for texting/browsing while driving were predictors of self-regulation for all levels. Drivers were observed to use the mobile phone more when the driving demands are low, e.g. while stopped at an intersection. This research suggests that distracted drivers engage in various levels of self-regulation, and future research could be focused on further theoretical refinement and development of technology-based interventions.