Exploring the impact of "soft blocking" on smartphone usage of young drivers

Assessing the effectiveness of psychoeducational interventions on driving behavior: A systematic review and meta-analysis

This review aimed to quantitatively summarize the evidence concerning the effectiveness of psychoeducational interventions on driving behavior. A final pool of 138 studies, totaling approximately 97,000 participants, was included in the analyses and covered all types of driving behavior targeted by the interventions. Using a random effects model, significant results were found for almost all driving outcomes, both post-intervention and long-term. The strongest effect was for reducing distracted driving at post-intervention (d = 1.87 [1.12, 2.60], Z = 4.94, p < 0.001). The only non-significant effects were for reducing errors in the long term (d = 0.50 [-0.87, 1.86], Z = 0.71, p = 0.48) and driving under the influence at post-intervention (d = 0.35 [0.00, 0.71], Z = 1.96, p = 0.05). Concerning which type of intervention was more effective, feedback, training and motivational ones appear to work best. Educational interventions show only weak effects, while awareness interventions seem mostly ineffective. Overall, our results show that most interventions can reduce different types of driving behaviors, but there are specific aspects to be considered based on the targeted behavior.

Exploring the Behaviour Change Wheel and the Theoretical Domains Framework in interventions for mobile phone driver distraction: A scoping review

Mobile phone use while driving remains a significant traffic safety concern. Although numerous interventions have been developed to address it, there is a gap in the synthesis of relevant information through a comprehensive behaviour change lens. This scoping review uses the Behaviour Change Wheel (BCW) and the Theoretical Domains Framework (TDF) to examine the literature to (a) identify behavioural constructs targeted in interventions for mobile phone use while driving, (b) determine if the intervention success varied by sociodemographic group (e.g., age, gender, driving experience), and (c) map interventions to TDF domains to highlight areas for future research. Following the PRISMA extension for scoping reviews, we searched seven databases and identified 5,202 articles. After screening, 50 articles detailing 56 studies met the following inclusion criteria: (a) intervention studies, (b) providing details on methods and results, (c) written in English, and (d) targeting any driver behaviour related to mobile phone use while driving with a bottom-up approach, using not regulation or law enforcement, but individuals' psychological processes, such as cognitive, behavioural, and emotional. Findings show that most interventions targeted young drivers and were typically effective. Except for a few studies, the effectiveness of interventions targeting different sociodemographic groups either remained untested or revealed nonsignificant differences. This finding points to a gap in the literature, indicating a need for further investigation into the efficacy of interventions for different groups, and for tailoring and testing them accordingly. The interventions also often targeted multiple TDF domains, complicating the interpretation of the relative efficacy of specific domains. Most frequently targeted domains included beliefs and consequences, emotions, knowledge, social influence, social/professional role and identity, and behavioural regulation. Physical skills and optimism domains were not targeted in any intervention. Further, almost all interventions addressed deliberate engagement in mobile phone distractions, while the automatic and fast processes involved in such behaviours were often overlooked. Mobile phone distractions are in part habitual behaviours, yet the existing mitigation efforts mostly assumed intentional engagement. More focus on the habitual nature of mobile phone distractions is needed.

Cell phone-related driver distraction: Habits predict behavior over and above the theory of planned behavior variables

INTRODUCTION

Habits have often been overlooked in studies investigating cell phone-related driver distractions. This paper examines the association between habits and cell phone-related driver distractions within a mediation model based on the Theory of Planned Behavior (TPB). Additionally, it explores potential differences in behaviors across urban and rural driving environments and between males and females.

METHOD

We conducted an online survey in China with 1,016 respondents, measuring attitudes, subjective norms, perceived behavioral control, self-reported behavior, and habits associated with cell phone use while driving.

RESULTS

Data was analyzed using a two-stage structural equation modeling approach. Results indicate that the measurement model provided a good fit to the data and was invariant across urban and rural driving environments, as well as across genders. The latent path model investigating mediation also demonstrated a good fit and revealed that TPB variables (attitudes, subjective norms, and perceived behavioral control) partially mediated the relationship between cell phone-related habits and cell phone use while driving. The structural model was invariant across driving environments but not across genders, for which the extent of the differences were limited. Moreover, habits were strongly associated with subjective norms and perceived behavioral control, emerging as the strongest predictor of cell phone-related distractions.

CONCLUSIONS

The findings suggest that habits should be considered in research on phone-related distracted driving behaviors and in the development of intervention designs.

Targeting young driver emotions can reduce their cellphone distractions

OBJECTIVE

This study sought to evaluate the relationship between young drivers' intention to engage in cellphone distractions while driving and their emotions towards the associated risks. First, we assessed whether the emotions of guilt, shame, and fear are associated with young drivers' intention to engage in cellphone distractions, through an extended Theory of Planned Behavior (TPB) model. Second, we evaluated whether road signs that may evoke these negative emotions reduce cellphone use intentions among young drivers.

METHODS

An online survey was conducted with young drivers (18 to 25 years old) from Ontario, Canada. 403 responses were collected, of which, 99 responses were used to evaluate the first objective and all 403 responses were used to evaluate the second objective.

RESULTS

Anticipating feelings of guilt, shame, and fear negatively predicted the intention to engage in cellphone distractions, above and beyond the standard TPB constructs (i.e., attitudes, subjective norms, and perceived behavioral control). When prompted with potentially emotion-evoking road signs (children crossing, my mom/dad works here), an increase in anticipated feelings of these emotions corresponded with lower intention to engage in cellphone distractions.

CONCLUSION

Countermeasures that target young driver emotions toward distracted driving risks may be effective in reducing their distraction engagement. Future studies in more controlled environments can investigate causal relationships between emotions and distracted driving among young drivers.

Visual and cognitive demands of manual and voice-based driving mode implementations on smartphones

Mobile phone apps and operating systems are increasingly adopting driving mode functions that attempt to reduce driver visual and cognitive demand by limiting functionality, using larger buttons and icons, and adding voice-based interactions. The present study assessed the visual and cognitive demands and the subjective level of distraction from two driving mode implementations (voice or manual) on an Android™ mobile phone using Google Assistant™, compared to a typical mobile phone operating system experience. While driving on a test track, participants performed several trials of five tasks on each of three interfaces: A mobile operating system interface, a manual driving mode interface, and a voice driving mode interface. Visual demand was measured with eye-gaze recordings, cognitive load was measured with the detection response task, and a Likert scale was used to rate the perceived level of distraction. The voice driving mode resulted in the lowest visual attention demand and lowest subjective ratings of distraction. The manual driving mode condition also reduced visual demand and subjective ratings of distraction relative to the mobile operating system condition. The cognitive load results were inconsistent across the task and interaction mode conditions. Overall, the results of this study provide positive evidence in support of voice-based driving mode implementations for reducing visual demand and subjective levels of distraction from mobile devices while driving. Moreover, the results suggest that manual driving mode implementations also have the potential to reduce visual demand and subjective levels of distraction, relative to the mobile operating system condition.

The use of risk homeostasis theory to reduce smartphone use during low-speed driving

Driving while distracted by smartphones is an unsafe behavior and constitutes a serious worldwide road safety issue. In line with the risk homeostasis theory, during high-speed driving, drivers perceive smartphone usage as an unwarranted risk and in most cases refrain from doing so. During low-speed driving, however, drivers often use their smartphones, as they do not perceive this as inherently unsafe, even though it is. The goal of this study was to examine an intervention, based on the risk homeostasis theory, aimed at decreasing the use of smartphones while driving at low speeds. Thirty-seven young drivers participated in the research group that aimed to alter drivers' risk perceptions, decision making, and behavior. The study also included a control group of 33 young drivers. All of the participants' smartphone usage was monitored using a dedicated application that measured both the number of times drivers touched their smartphone screens while driving and the driving speed each time the screen was touched. The results indicate that drivers in the research group decreased their smartphone usage while driving, unlike the control group drivers who did not alter their behavior. In conclusion, a risk homeostasis-based intervention can decrease dangerous and unsafe driving behavior, even when such behavior is not perceived as significantly dangerous. Furthermore, additional types of risky and unsafe driving behaviors may be decreased using this type of intervention.

"It is frustrating to not have control even though I know it's not legal!": A mixed-methods investigation on applications to prevent mobile phone use while driving

Mobile phone distracted driving is a major risk factor for crashes. However, this behaviour has been increasing in recent years. Effective enforcement of mobile phone bans while driving faces several obstacles; as such, it is important to consider additional countermeasures. Applications designed to prevent distracted driving are a promising solution, yet more research is needed that examines their effectiveness in reducing dangerous phone use while driving behaviours. Additionally, these applications are voluntary in nature; therefore, an understanding of drivers' perceptions of the applications is necessary to determine how to improve uptake. A mixed methods design was utilised to examine these factors in a comprehensive manner. A total of 40 participants used the smartphone application "Do Not Disturb While Driving" for iOS phone operating systems or "Android Auto" for Android phone operating systems for approximately one week and completed three diary entries reporting on their experience. Two questionnaires that examined phone use while driving behaviours were also administered to participants; one before and one after completing the study. The quantitative results found that engagement in 1) visual-manual, 2) cognitive-auditory and 3) music mobile phone interactions significantly decreased while using the application. Distraction engagement and mental workload while driving also significantly decreased while using the application. The qualitative results identified a number of areas of improvement that need to be addressed, e.g. activation of the application and Bluetooth connection reliability. The features that required improvement presented an obstacle for effective use of the applications, and in some cases resulted in drivers deciding to stop using the application. Positive perceptions of the application were associated with the experiences of the application functioning appropriately and activating automatically. These results show that applications designed for voluntary use to prevent mobile phone distracted driving are a promising countermeasure, although current applications require several improvements.

Assessing driver acceptance of technology that reduces mobile phone use while driving: The case of mobile phone applications

The nature of the road environment requires drivers to be vigilant and attentive. Distracted driving is a primary concern, as it threatens the safety of road users. However very little research has been conducted into interventions to combat such an issue. Existing interventions such as police enforcement and legislation appear to have limited effect. The use of mobile phone applications to assist in limiting driver distraction is an alternative intervention that is currently gaining traction. With a great array of potential benefits, such as reducing road toll, these applications can be readily available to all road users. Despite the positive implications, it is vital that drivers accept the use of such a technology for the intervention to be effective. Therefore, understanding driver acceptance is an important step in implanting such applications. To assess this, the present study examines the utility of two versions of the Technology Acceptance Model (TAM), the Theory of Planned Behaviour (TPB) and the Unified Theory of Acceptance and Use of Technology (UTAUT) for understanding the acceptance of technology designed to reduce distraction. Participants were presented with two different applications and responded to questions that indicated their attitudes towards the factors included in the TAM, TPB and UTAUT, alongside their intent to use the technology. A total of 731 participants responded to the survey, and their responses analysed. The results indicated that overall, Davis' (1985) TAM was slightly better in explaining behavioural intent for both Mobile Phone Application (MPA) 1 and MPA 2, explaining 66.1% and 68.7% of the variance, respectively. Davis' (1989) TAM and the TPB were close behind, while the UTAUT explained the least variance in behavioural intent of all the models. Overall, the findings of this study provide support for using psychological theories to assess the acceptance of mobile phone applications.