Predicting the monitoring/reading of communications on a smartphone among young drivers using an extended theory of planned behaviour

Murphy, Georgia; Gauld, Cassandra; Lewis, Ioni · 2020 · Crossref

DOI: 10.1016/j.aap.2019.105403

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the psychological predictors of young drivers’ intention to monitor or read social interactive technology on smartphones while driving, as well as their subsequent engagement in this behavior. The research is motivated by the high prevalence of smartphone use among young drivers (aged 17–25) in Australia, a demographic over-represented in road crashes. Although monitoring/reading is often perceived as less risky than initiating or responding to communications, it remains a significant distraction. The authors aim to determine whether an extended Theory of Planned Behaviour (TPB), incorporating habit, mindfulness, and cognitive capture, better explains these behaviors than the standard TPB constructs alone. The researchers employed a two-wave survey design with young drivers in Queensland, Australia. In Time 1, 167 participants completed an online survey assessing their intention to monitor/read social media while driving, along with standard TPB constructs (attitude, subjective norm, perceived behavioral control [PBC]) and the additional variables of habit, mindfulness, and cognitive capture. One week later, 95 participants completed a Time 2 survey reporting their actual engagement in the behavior during that period. Hierarchical multiple regression analyses were used to test the predictive power of these constructs on both intention and reported behavior. Results indicated that the standard TPB constructs accounted for 77% of the variance in intention. Adding habit, mindfulness, and cognitive capture significantly increased the explained variance to 79%. In the final model, attitude, PBC efficacy, PBC control, habit, mindfulness, and cognitive capture were all significant predictors of intention, while subjective norm was not. PBC efficacy emerged as the strongest predictor. Regarding actual behavior, intention was the only significant predictor in the initial model, accounting for 15% of the variance. When attitude and subjective norm were added, the model explained 27% of the variance, with intention remaining the sole significant predictor. The addition of habit, mindfulness, and cognitive capture did not significantly improve the prediction of reported behavior. The study concludes that while habit, mindfulness, and cognitive capture help explain young drivers’ intentions to monitor/reading phones while driving, intention remains the primary driver of actual behavior. The findings suggest that interventions aimed at reducing this distraction should focus on modifying intentions, particularly by addressing perceptions of control and efficacy, as well as the automatic nature of smartphone checking habits. The results support the utility of extending the TPB to include cognitive and habitual factors when predicting risky driving behaviors.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• mobile phones
• passenger effects
• temporal
• acceptance adoption
• telematics ubi feedback

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: observational prevalence, behavioral performance data
• Theoretical Contribution: theory or model