In the expanding food delivery sector, particularly in Asia, where motorcycles are preferred for their efficiency, there has been an alarming rise in traffic safety incidents involving delivery riders. This increase highlights the need for a comprehensive understanding of safety outcomes within the industry, encompassing both organizational and personal factors. Our study, using data from 401 motorcycle delivery riders in Vietnam, addresses this gap with a conceptual model based on the Safety Climate Model. This model assesses the impact of safety climate, knowledge, and motivation on rider safety performance. Our findings reveal that factors like management values, effective safety communication, and quality safety equipment are crucial in creating a positive safety climate. This climate significantly boosts safety participation and compliance among riders. Furthermore, the study confirms that safety climate indirectly influences safety outcomes through safety knowledge and motivation. These results illustrate the dynamic between organizational practices and individual behaviors in determining safety in the food delivery industry. The study underscores the need for a holistic approach to safety, extending beyond equipment provision to include management commitment, communication, and motivational incentives. Implementing such comprehensive strategies is vital for enhancing rider safety, contributing to a safer work environment, and reducing safety–critical incidents among food delivery riders.

The rise of on-demand food delivery services, operating on gig economy models, has gained popularity worldwide. However, this surge has led to a concerning increase in road traffic crashes involving delivery riders. From this, an urgent need has emerged for a comprehensive study to explore the complex traffic safety issues that this vulnerable group faces daily. Therefore, this study aims to provide in-depth insights into the unsafe riding practices of food delivery riders and to identify effective countermeasures to mitigate the risks they commonly encounter. To address this need, the study has proposed a theoretical framework based on the job demands-resources (JD-R) model. In addition, two constructs, including safety compliance and intention to violate traffic rules, are incorporated into the JD-R model to examine their impact on negative safety outcomes. A survey was conducted in Danang city, Vietnam, gathering responses from 419 delivery riders. Partial Least Squares Structural Equation Modeling was employed to analyze the relationships among the constructs in the developed model. The results highlight the significance of all job aspects as predictors of safety compliance and intentions to violate traffic rules. Furthermore, the study's findings reveal that safety compliance serves as a mediator between job demands and job resources, influencing negative safety outcomes. Based on these research findings, platform firms can strategically consider implementing tailored solutions to enhance traffic safety, discourage participation in unsafe riding practices, and promote sustainable travel behavior patterns among delivery riders.

Promoting public transport is widely regarded as a key strategy for advancing sustainability. However, concerns about women's safety continue to pose a significant barrier to its regular use. A growing number of studies have highlighted the vulnerability of female commuters to harassment and crime, yet there is limited evidence on how these experiences –and the fears they generate– translate into changes in travel behavior. This knowledge gap makes it difficult to develop evidence-based interventions. Accordingly, this study examined the interrelations between sexual harassment, fear of crime, and travel-related behavioral adaptations among female public transport users in Spain. The analysis was based on a cross-sectional sample of 720 female public transport commuters. The average age of participants was 29 years. They responded to an e-survey addressing commuting patterns, perceptions of safety, and behavioral responses. Our results suggest that both direct and indirect experiences of harassment are consistently associated with higher levels of fear of crime, which in turn influence changes in travel behavior. Specifically, fear of crime was found to partially mediate the relationship between harassment and travel-related adaptations. These findings provide further insight into how psychological and contextual factors shape women's use of public transport, and highlight the need to address not only actual incidents but also the broader perception of insecurity.

In recent years, the relationship between academia and the fossil fuel industry has become a focal point of intense debate. This concern arises from the fear that corporate funding might skew research activities. A significant development in this area is the adoption of policies by a Dutch university, and discussions in several others, prohibiting research funded by the fossil fuel industry. These policies aim to safeguard academic freedom and integrity. Despite this, there has been little discussion on the myriad challenges, implications, and possible unintended consequences, particularly in the realm of safety-and-security research. As such, this manuscript delves into the complex transition towards a fossil-fuel-free society, examining it through the lenses of safety science and sociotechnical systems. It emphasizes the vital importance of collective responsibility in ensuring systemic safety and security as we navigate towards achieving the sustainable development goals. This journey requires a delicate balance between the objectives of safety and sustainability, along with a deep understanding of the security implications of decreasing our dependence on the fossil fuel industry. The strategy of distancing academic research from fossil fuel industries, commonly seen as a positive step, also demands a nuanced consideration of its broader impacts, including the setting of precedents for addressing other existential and systemic risks. Instead, we argue for the establishment of robust governance structures rooted in restorative justice principles. Such frameworks can facilitate productive dialogue with underrepresented groups, motivate the fossil fuel industry towards sustainable practices, and safeguard the integrity of scholarly research. This approach not only addresses immediate concerns related to fossil fuels but also lays the groundwork for a more inclusive and equitable model of climate risk research, essential for tackling the multifaceted challenges of our era.

Distracted driving continues to be a significant risk to road safety. While effective legislation and education are essential for preventing distracted driving, there is evidence showing that current official information and road rules related to distracted driving may not provide drivers with a comprehensive understanding of the issue. Therefore, this study aimed to explore drivers’ perspectives on how official information and road rules could be improved to effectively address distracted driving. Semi-structured interviews were conducted with 35 drivers from Queensland, Australia, with thematic analysis employed to extract key themes from the discussions. The results showed that official information on distracted driving could benefit from more comprehensive content, including underrepresented distraction sources (e.g., using a smartwatch, interacting with passengers, and looking at advertisement billboards), the safety risks, and impacts on driving performance. Participants emphasised the need for distracted driving legislation to address the risks posed by a broader range of technological devices (e.g., infotainment systems, wearable devices), not just hand-held mobile phones. The results suggested a need for improved presentation of information, with future distracted driving content suggested to be presented visually, along with more targeted messaging for high-risk drivers such as young drivers. Further, social media, short training, and outdoor media were perceived by participants as the most effective delivery mechanisms for distracted driving resources. The findings provide valuable guidance for policymakers in establishing and communicating information and road rules for distracted driving.

There is a plethora of technology currently available that have the ability to notify individuals of traffic enforcement locations while they are driving. This technology has the potential to undermine legal deterrent efforts for preventing risky driving behaviours. However, drivers’ experiences using this technology and the trajectories through which this might interfere with deterrence for road rule violations are largely unexplored areas. As such, the present study aimed to explore two research questions: 1) what type of technology is used and how is it used, and 2) how does drivers’ use of this technology influence deterrence for road rule violations. In total, 58 Queensland licenced drivers who use technology that informs them of legal enforcement while driving participated in focus groups. To consider differences in use between ages, the sessions were conducted in three different age groups: 17–25 years, 26–49 years, and 50+ years. Reflexive thematic analysis was applied to the data, resulting in eight recognised themes. The findings highlighted that for most drivers, the primary purpose of using the technology was for navigation, while being notified of enforcement locations was a secondary purpose. In addition, the use of this technology encouraged road rule compliance for some yet was used as a strategy to avoid being caught for road rule violations for others. The findings have a number of practical and theoretical implications, demonstrating the complex interplay between technology used for enforcement notifications, its role in deterring road rule violations, and the principles of responsible innovation.

Population aging is a macrosocial trend with growing implications for mobility and public health. In the coming decades, many countries are expected to experience a marked increase in the average age of their populations, raising new challenges for healthcare and mobility systems. The promotion of active mobility, widely supported in the literature for its role in maintaining health in later life, has gained visibility. However, it remains unclear whether existing digital tools, such as lifestyle apps, effectively contribute to this goal. Methods: This study examined the effectiveness of applications and tools designed to promote walking among older adults through a systematic literature review, complemented by additional sources, including sentiment analysis of user reviews. Results: Many walking apps offer features such as step tracking and personalization, but few address both physical activity and social isolation simultaneously. Available evidence suggests potential benefits in gait quality, balance, and reduced sedentary behavior in specific contexts. User feedback also points to high satisfaction, especially with simple and accessible interfaces. However, the scientific literature supporting these outcomes remains limited in scope and generalizability. Conclusion and practical insights: This multi-source review suggests that walking apps may support more active lifestyles among older adults, though current evidence is not yet conclusive. Future app development should prioritize usability and incorporate features that address both physical and social well-being, while ensuring accessibility and affordability for a broader range of users.

Large Language Models have attracted global attention due to their capabilities in understanding, knowledge synthesis, and generating contextually relevant responses, mimicking certain aspects of human reasoning. Although LLMs have demonstrated feasibility in performing autonomous driving tasks in simulated and real-world environments, little is known about their safety and ethical decision-making. To address these questions, we propose a novel framework for evaluating and interpreting the ethical decision-making mechanism of LLM-driven autonomous vehicles. Our study investigates the ethical dilemma of prioritizing saving pedestrians or passengers inspired by the Moral Machine Experiment. We used a stated preference survey to include factors of group size, age, gender, fatality risk, and pedestrian behavior to create 13,122 choice scenarios (a full factorial design) to analyze responses from advanced LLMs, including the GPT-4 series models from OpenAI and Mistral-Large from Mistral AI. Our findings reveal significant differences in the decision-making process and preferences for saving road users among these LLMs. Using a binary logit model to interpret GPT-4′s decisions, we found that the estimated number of deaths, age, and gender significantly affect the model's choices. The decision tree method was also applied to analyze LLMs’ decision-making processes, uncovering potential ethical standards and conditions considered by the models. This study provides valuable insights into ethical considerations in AI systems and thus facilitates the responsible development of AI in autonomous vehicles.

The rise of ChatGPT has prompted concerns over users’ agency when revealing personal data to artificial intelligence. This study examined users’ likelihood of disclosing their data to ChatGPT in physical and mental health scenarios. Participants (N = 216) completed a repeated measures survey where they viewed four vignettes of hypothetical scenarios and were asked to imagine disclosing health information (physical and mental health) at two sensitivity levels (low and high self-disclosure). A repeated measures ANOVA revealed participants were significantly more likely to provide their data when the information required low-disclosure than high-disclosure. Furthermore, participants were significantly more likely to report uploading their health information in the physical health scenario than in the mental health scenario. The findings suggest ChatGPT users exercise caution in disclosing data to the platform. Reluctance to upload information in sensitive scenarios reduces the training data for large language models, resulting in potential stagnation in technology development.

In low- and middle-income countries, electric motorcycles (EMs) are not generally well accepted in the community as many infrastructural, technological, and psychosocial barriers remain unaddressed. A greater understanding of adoption barriers perceived by motorcycle riders can help devise strategies, such as policy and behavioural change interventions, to increase the uptake of EMs. This study aimed to investigate the risk dimensions of EM adoption and integrate them into the Theory of Planned Behaviour to model users’ intention to adopt EMs. A multi-group analysis was also conducted to examine the moderating effect of demographic characteristics on the proposed model. The data were collected from two cities in Vietnam, making this one of the region's first theory-based studies on the electrification of the transport system. The outcomes of the structural equation modeling affirmed that the psychosocial variables outlined in the Theory of Planned Behaviour (i.e., attitudes, perceived behavioural control, and social norms) and perceived risk significantly influence the behavioural intention to adopt EMs. These findings hold significance for policymakers and manufacturers as they provide valuable insights into the factors that can be targeted to enhance the adoption of EMs. This represents a crucial step towards advancing sustainability goals in low- and middle-income countries.

The rise of ChatGPT has emphasized the need for an improved conceptual understanding of users’ agency when interacting with artificial intelligence (AI) systems for healthcare. Australian ChatGPT users (N = 216) completed a repeated measures online survey. Hierarchical regression analyses assessed the influence of demographic factors (age and gender), Technology Acceptance Model constructs (perceived usefulness and perceived ease of use), and extended variables (trust, privacy concerns) on users' behavioral intentions to use ChatGPT for physical and mental healthcare. The proposed model was partially supported: the findings emphasized the need to establish user trust in ChatGPT and its perceived usefulness in both areas of healthcare. Privacy concerns were a significant predictor of intentions to use ChatGPT for mental healthcare with perceived ease of use predicting intentions to use ChatGPT for physical healthcare. The findings indicate predictors of uses of AI cannot be generalized across healthcare types and unique drivers should be considered.

Perceived accessibility refers to individuals’ subjective perception of how easy it is to reach destinations using a specific mode of transport. As such, understanding the effect of perceived accessibility on travel behavior is essential for creating transport systems and urban environments that are efficient, equitable, and sustainable. This study develops a new integrated model by combining the Norm Activation Model (NAM), the Theory of Planned Behavior (TPB), perceived risk, and perceived accessibility. This enhanced model offers a comprehensive understanding of the factors influencing individuals’ intentions to switch to urban train systems. Additionally, the moderating effects of perceived accessibility on the link between personal, contextual factors and switching intention are also explored. The model developed is tested using data obtained from a sample of 535 individuals in Hanoi, Vietnam. This is particularly important because more research in low- and middle-income countries (LMICs) is needed to address the sustainability challenges these nations face due to their dependency on motorized private transport. The findings show that subjective norms have the strongest effect on the intention, followed by personal norms, attitude, and perceived accessibility. This study also confirms the moderating role of perceived accessibility on the link between attitude and switching intention, while the other hypotheses regarding the moderating effects of perceived accessibility are not supported by the findings. These insights aim to inform policymakers and public transport authorities in developing targeted strategies to promote sustainable urban mobility in Vietnam.

Mobile phone distraction is a critical global road safety issue, contributing to crashes and subsequent injuries and fatalities. This issue has led to calls for effective interventions. Based on neuropsychological research indicating that colour stimuli play a significant role in driving phone engagement, one potential strategy to reduce road user phone use while on the road is activating greyscale on phones. By removing colour, the sensory reward associated with phone use may be diminished, potentially reducing usage. However, this approach has yet to be empirically tested. As such, the aim of this study is to investigate how greyscale influences phone use behaviours while driving and walking. Participants were asked to switch their phone interface from colour to greyscale for a duration of 2-weeks. A mixed-methods approach, including surveys and interviews, was employed to gather insights from participants regarding their perceptions of greyscale on their phone use behaviour while driving and walking. The quantitative results showed that greyscale decreased the frequency of participants glancing at their phone screens in a cradle while driving. However, using the greyscale feature did not lead to significant changes in the frequency of participants picking up the phone and looking at the screen while driving, nor did it increase participants’ use of other devices such as the in-vehicle infotainment system, smartwatches, or voice commands. Additionally, greyscale significantly reduced the probability of pedestrians using handsfree phones while walking, although greyscale did not influence the likelihood of looking at the screen of a handheld phone. The qualitative results revealed that the greyscale had a complex impact on road users’ phone behaviour. Greyscale altered how they used their phones, made them less appealing and enjoyable, and added complexity to phone use. However, some participants found work-around, though not everyone adopted them. Overall, the findings suggest that while greyscale effectively reduced some phone-related behaviours over a 2-week period, its impact on phone use behaviours while driving or walking was limited in scope, with mixed effectiveness across different contexts and with some users finding work-around.

Objectives: Understanding the risks associated with electric motorcycles (EMs) is essential for developing effective mobility and safety strategies in an era of increasing motorcycle use and the shift toward electric vehicles. In this research, we investigate the prevalence of crashes among EM and conventional motorcycle (CM) users, as well as factors contributing to the crashes. Methods: This study uses primary survey data from 972 motorcyclists (481 EM and 491 CM riders) collected in December 2023 in Hanoi, Vietnam. It compares the frequency of risky riding behaviors and crash types between the 2 groups. Additionally, 2 binary logit regression models are applied to identify factors associated with crashes in the past 12 months for EM and CM riders. Results: The results suggest that the prevalence of respondents who did not experience crashes (56.1%), minor crashes (68.8%), serious crashes with injury (80.9%), and hospitalization (91.1%) for EM riders was significantly higher than that for CM users. CM riders tend to engage in many risky riding behaviors more frequently than EM riders. Higher frequencies of speeding, smoking, and neglecting turn signals were related to greater crash risk in both groups. Red light running was a particular risk factor of crash prevalence for EMs only. Older EM users were more likely to experience a crash, and CM users traveling longer and living in urban districts were found to be linked to higher crash prevalence. Conclusions: Transitioning from CMs to EMs in Vietnam may offer some safety benefits, such as cautious behavior by EM riders and lower speeds, but there are no major differences in crash prevalence between the groups. Risky behaviors like speeding, smoking, and neglecting turn signals increase crash risks for both; red light running is a particular concern for EM riders and longer travel distances and urban residency for CM users. Targeted interventions, proper training, and licensing are essential, with attention to older EM riders’ vulnerabilities and the risks faced by CM users in urban areas and on long trips.

The present study examines the question of whether certain humor styles predict self-esteem. Men and women in 15 countries (NTOTAL = 4701) completed self-report measures assessing self-esteem and the four humor styles of affiliative, aggressive, self-defeating, and self-enhancing. Each of the country samples had self-esteem averages at or above the midpoint of the scale, but did vary. The samples from Colombia and Serbia had the highest self-esteem values and Russia had the lowest. For all of the country samples, with the exception of Russia, the multiple regression results demonstrated that a greater level of the self-enhancing humor style positively predicted higher self-esteem scores. As the self-enhancing humor style involves improving one’s mood with humor, the results suggest that for the majority of the participants, self-enhancing humor styles also help to increase self-esteem. The results are discussed both within countries and across the samples. In particular, the unique finding that not a self-enhancing humor style but an aggressive humor style predicts self-esteem in the Russian sample is discussed. The chapter ends with a discussion of how humor styles correlate with mental health indicators and how the understanding of humor style profiles are related to well-being across countries adds to the global understanding of individual differences.

Large Language Models (LLMs) are expected to significantly impact various socio-technical systems, offering transformative possibilities for improved interaction between humans and technology. However, their integration poses complex challenges due to the intricate interplay between societal structures, human behaviour, and technological innovation. This research explores these multifaceted challenges, emphasising the need for a human-centered approach in integrating LLMs to ensure that technological advancements are aligned with ethical standards and societal needs. Utilizing a structured methodology comprising a workshop, literature analysis, and expert collaborations, the study uses a multi-dimensional human-centered AI framework to guide the responsible integration of LLMs. Key insights include the importance of inclusive data, considering unintended consequences, maintaining privacy, and respecting intellectual property rights. The paper identifies and advocates for principles like human-in-the-loop, continuous longitudinal studies, proactive awareness campaigns, and regular audits to develop LLMs that are ethically sound, adaptable, and effectively integrated into various socio-technical systems, thus addressing user needs and broader societal impacts. The paper also underlines the importance of collaboration among academia, industry, and policymakers to develop LLMs that are ethically aligned, socially beneficial, and adaptable to future societal needs. The findings offer valuable insights into the strategic integration of LLMs, advocating for a broader research perspective beyond industrial motivations to fully understand and leverage LLMs in socio-technical landscapes.

Recognizing the potential transformative impact on transportation systems, safety perceptions of Shared Automated Vehicles (SAVs) have gained significant attention from researchers in recent years. Yet, the critical factors influencing perception changes and the willingness to re-ride (WTR) have not been extensively studied despite their relevance to SAV operations. This study applied Bayesian Networks (BNs) and Text Network (TN) methodologies to analyze survey data from a shared automated passenger shuttle (SAPS) pilot program conducted between March and April 2023, at Fred G. Bond Metro Park in Cary, North Carolina. Participants in the survey provided feedback on their safety perceptions of the SAPS before and after riding, as well as their willingness to ride again. Key findings reveal that shuttle operations, especially timely arrival and drop-off, significantly affect both perceptional change and WTR. Furthermore, users who accessed the shuttle by walking, biking, or public transportation were more likely to positively change their perception and express a willingness to ride the shuttle again. Also, individuals with initial perceptions of the SAPS as very unsafe or unsafe showed a higher likelihood of perception change. Conversely, older respondents were less likely to experience safety perception changes and WTR. Text network analysis further illuminated that the primary motivations for WTR were the enjoyable experience and convenience offered by the shuttle. The study contributes to the growing body of literature on SAVs by providing practical implications for the future development and testing of SAPSs. These insights are invaluable for policymakers and planners in optimizing SAPS operations, providing a deeper understanding of user experiences and expectations.

Background: Many factors are associated with pedestrian injuries and accidents. If a pedestrian is injured in an outdoor public space, we are talking about a “pedestrian fall”. Pedestrian falls are a more common cause of pedestrian injuries than traffic crashes but have received less attention and the literature on this topic is scarce. Aims and methods: The aim of this work is to describe at a general level the prevalence and consequences of pedestrian falls and injuries, to make international comparisons of pedestrian falls and to identify risk factors and not least to examine the relationships between the prevalence of falls and pedestrian risk behaviour. A total of 6,373 participants from 15 different countries were recruited to take part in this study. To collect data a questionnaire was used. To cover the risky behaviour of pedestrians we used a short version of Pedestrians Behaviour Scale (PBS). In order to identify groups of countries with a similar pedestrian transport situation, a hierarchical cluster analysis was performed. The analysis produced four groups of countries based on pedestrians’ safety level, popularity of walking and GDP. Results and conclusions: As for the results, we can conclude that young people and older people are more frequently involved in falls and that women report more frequent involvement in falls than males. However, the risk of getting injured in a fall is not higher than that of men. Frequent walking is associated with a lower risk of falling while walking. In contrast to this, physical activity increases such risk. The prevalence of falls and injuries seems to be weakly related to pedestrians’ risky behaviour, thus other factors such as safety infrastructure probably play an important role.

Road corridors contain countless sources of distraction, each carrying the potential to draw drivers’ eyes and minds off roads, thus increasing the risk of a crash. While the impact of billboards on driver distraction has received considerable attention, empirical data for other types of roadside advertising signs is very limited. Furthermore, the existing research examining other potential external sources of distraction is fragmentary, which makes it difficult to develop evidence-based road safety policies to mitigate risk. Therefore, the aim of this study was to conduct an exploratory review to ascertain and synthesise the available distraction-related literature for various types of roadside advertising signs (excluding billboards) and other potential external sources of distraction in the road corridor. Based on distraction-related theory and existing literature, 58 predefined categories of potential distraction sources were developed to guide an exploratory literature search using the Scopus database. Fourteen documents relating to external distraction sources were identified in the database search with a further five studies found using a backwards citation chaining search (N=19). However, no studies for non-billboard types of roadside advertising signs were found. Studies included those that investigated driver distraction in relation to construction zones, commercial logos contained within official traffic management Dynamic Message Signs (DMS) and service (logo) signs, drones, murals, roadside memorials and wind turbines. While one study investigated whether an external source of distraction can have a positive effect on driver behaviour, the remainder focused on the potential negative impacts on road safety of these sources of distraction. A key finding of the review is that crash risk increases when drivers continue to visually and cognitively engage with a source of distraction. Overall, the studies provide insights into the types of distractions that can be encountered in road corridors and the impact they can have on driver behaviour. However, more research is required before the mechanisms and pathways involved in these types of distractions can be effectively conceptualised, and thereby mitigated to reduce the burden of distraction risk and road trauma.