制裁
违反直觉
忧虑
危害
感知
心理学
社会心理学
吓阻理论
威慑(心理学)
计算机安全
应用心理学
政治学
犯罪学
法学
计算机科学
哲学
认识论
神经科学
认知心理学
作者
Verity Truelove,James Freeman,Elizabeth Szogi,Sherrie-Anne Kaye,Jeremy D. Davey,Kerry Armstrong
标识
DOI:10.1016/j.trf.2017.08.008
摘要
The effectiveness of countermeasures to reduce the incidence of speeding is extremely important when considering the impact the behaviour has on the road toll. Deterrence-based sanctions such as fines and licence loss are heavily utilised to deter drivers from exceeding the speed limit as well as emphasising the threat of physical harm (e.g., media campaigns). However, surprisingly little research has actually examined the extent to which legal and non-legal sanctions influence speeding behaviours. This paper reports on an examination of 1253 Queensland drivers' perceptions of legal and non-legal speeding sanctions and the corresponding deterrent impact of such perceptions on self-reported offending behaviour. Participants volunteered to complete either an online or paper version of the questionnaire. The self-reported frequency of speeding behaviours was consistent with previous research, as was the significant link found between speeding and being a younger male with greater exposure to the road. Encouragingly, perceptions of apprehension certainty were not only the highest rated factor, but were also found to be a predictor of avoiding speeding behaviours. However, an expected link between perceptual severity and offending was counterintuitive in nature (e.g., positive) and participants generally did not consider penalties were applied swiftly. Fearing being injured was the only non-legal sanction predictive of reduced speeding behaviours, as the threat of social sanction or internal loss (e.g., shame) had a limited impact. While researchers have long proposed that a range of legal and non-legal sanctions can influence speeding behaviours (which are also utilised in complementary media campaigns), a strong link between deterrent forces and offending behaviours with self-reported data remains lacking. This paper further considers the findings in regards to the need for further research.
科研通智能强力驱动
Strongly Powered by AbleSci AI