Children with disabilities and medical conditions are at an increased risk of injury or death during road vehicle transportation. In 2020, a national Australian survey of health professionals and organisations involved in the safe transport of children with disabilities and medical conditions identified a critical need for improved access to training, education, and resources. In response, Mobility and Accessibility for Children and Adults (MACA) Ltd developed targeted information and training resources. This study examined the impact of these resources on current road safety practices in Australia. A follow-up national survey was conducted with health professionals (n=126) and organisations (n=40) involved in supporting the safe transport of children with disabilities and medical conditions. Respondents included 74 participants (health professionals, n=56 health organisations, n=18) who also completed the 2020 survey, enabling direct comparison over time. Statistical and descriptive analyses of repeat participants reported greater confidence in their knowledge and more frequent assessment of transport needs for children with disabilities and medical conditions. The results reported a reduced frequency of barriers like lack of specialised knowledge, difficulty gaining funding for equipment, insufficient training and professional support, and unclear processes. However, many challenges persisted, with most respondents still reporting barriers. Health professionals and organisations that accessed the resources generally found them helpful, suggesting their potential benefits. Overall, the findings indicate promising improvements in the safe transport for children with disabilities and medical conditions, but additional efforts are required.
Injuries from road crashes remain a significant public health concern globally with a disproportionate burden in low- and middle-income countries like Ghana. While climate factors have been linked to crashes, the impact of injuries across different road user categories in urban Ghanaian settings remains poorly understood. This study sought to investigate the association between climate factors (temperature and rainfall) and non-fatal road traffic injuries among pedestrians, motorcyclists/tricyclists, and vehicle occupants in the Greater Kumasi Metropolitan Area of Ghana. The analysis combined road traffic injury data (N=8,772) (2010-2021) with climate data for the same period. Vehicle occupants were the largest proportion of injuries (42.4%, n=3,720), followed by pedestrians (33.5%, n=2,936) and motorcyclists/tricyclists (24.1%, n=2,030). Each millimetre increase in monthly rainfall was associated with increased injury risk across all road user types: pedestrians (1.7%, 95% CI: 0.6-3.0), motorcyclists/tricyclists (1.7%, 95% CI: 0.2-3.1), and vehicle occupants (1.6%, 95% CI: 0.4-2.7). The Kwadaso district experienced increase injury risk from 2010 to 2021, with relative risks increasing approximately sevenfold across all road user types, while the Kumasi Metropolitan area maintained consistently lower risk levels (RR: 0.4; 95% CI: 0.3-0.5). This study demonstrates significant associations between rainfall and non-fatal road traffic injuries across all road user types in Greater Kumasi Metropolitan Area of Ghana, with distinct spatial patterns of risk. These findings suggest the need for weather-responsive traffic management systems and user-specific safety interventions, particularly in high-risk districts with major highways.
Climate change, characterised by long-term shifts in temperature, precipitation patterns and increased frequency of extreme weather events, poses substantial challenges to road safety. Understanding how these changes impact road safety is crucial for developing effective mitigation strategies and enhancing infrastructure resilience. The aim of this systematic review was to evaluate and synthesise existing research on the relationship between climate change-induced weather conditions and road crashes. Using the PRISMA protocol, a systematic search was conducted across three indexed databases (Web of Science, PubMed, Scopus). From the initial 352 records following the removal of duplicates and the application of inclusion and exclusion criteria, 15 studies were selected. The review identified a consistent association between increased rates of trauma from crashes and extreme weather conditions such as heavy rainfall, snowfall, icy conditions, heatwaves, storms, dense fog and hailstorms. Heavy rainfall and storms were particularly impactful, significantly deteriorating road conditions and reducing visibility. Snow and ice increased the crash risk due to reduced traction, while heatwaves affected driver behaviour and vehicle performance. The control variables, including time of day, road type, traffic volume, geographic location, vehicle type, driver demographics, and seasonal variations, ensured that the observed effects were attributable to the weather conditions. The findings underscore the urgent need for targeted policy interventions and infrastructure adaptations to mitigate the adverse effects of climate change on road safety.
Work-related road traffic crashes continue to impose significant risks on employees, particularly in low- and middle-income countries where rapid urbanisation, long commuting distances and operational mobility demands intensify daily exposure to road hazards. Although Work-Related Road Safety (WRRS) has gained increasing attention, sector-specific variations in safety management systems remain insufficiently examined. This study evaluated WRRS implementation across 48 organisations representing the transportation, manufacturing and public services sectors in Malaysia. Data were collected through site visits and structured self-assessment questionnaires covering organisational characteristics, designated WRRS personnel, fleet composition, crash involvement and practices across five WRRS dimensions: management systems, monitoring and assessment, driver management, vehicle management and journey management. Descriptive analysis, one-way ANOVA and Bonferroni post hoc tests were used to identify sectoral differences. Findings indicate significant variations across several WRRS components, with the manufacturing sector consistently demonstrating lower compliance in management systems, monitoring and assessment, journey management and overall WRRS scores. Public service organisations showed stronger monitoring mechanisms but reported higher commuting-related crash rates, likely attributable to their extensive fleet operations and service demands. The transportation sector exhibited greater performance variability, consistent with its high mobility exposure and diverse operational requirements. No significant differences were observed in driver or vehicle management, suggesting these areas are uniformly implemented across sectors. Overall, the results highlight how organisational structures, regulatory environments and sector-specific operational patterns shape WRRS performance. Strengthening organisational governance, enhancing monitoring frameworks and developing sector responsive WRRS strategies are crucial steps toward reducing work-related road crashes and improving occupational road safety outcomes in Malaysia.
Injuries from crashes on the road remain a global public health crisis. The International Road Assessment Programme (iRAP) addresses the safer roads pillar of the Safe System approach to road safety through a standardised star rating system. In line with UN Road Safety Goals, the Brunei Department of Roads (DOR) conducted iRAP assessments of over 500 kilometres of road in 2015 and 2024. Performance tracking revealed a substantial increase in strategic roads that are rated 3-star or better (from 46% to 76%), primarily due to reductions in operating speeds and improvements in road conditions. Vulnerable road user star ratings were a concern, with most routes rated 1- or 2-star. While the number of fatalities or serious injuries involving pedestrians or cyclists was low, this is likely to be the result of few people walking or cycling on strategic routes. Next steps include implementing the recommended Safer Roads Improvement Plans (SRIPs) for the remaining 24% of the network that is 2-star. To address limitations in the traditional iRAP methodology, including potential coding inconsistencies, Brunei DOR are also considering using AiRAP for future assessments. This paper demonstrates how performance tracking can be used by a country to assess the effectiveness of their past road safety infrastructure programs and identify how they can make their roads safer going forward.
Road traffic crashes remain a significant cause of mortality among older adults, yet there is a lack of standardised instruments to assess their pedestrian behaviour. This study aimed to develop and validate a psychometric tool specifically tailored for older pedestrians to capture their unique behaviours in traffic behaviours and risk patterns. A cross-sectional study was carried out in Tabriz, Iran, from May 2023 to April 2024, involving 600 participants aged 60 years and older. Using a multistage cluster sampling method, individuals were recruited from four distinct socioeconomic regions of the city. The original 29-item Pedestrian Behaviour Questionnaire (PBQ) was expanded to 39 items through literature review and expert consultation to address age-specific traffic contexts and mobility challenges not covered in the previous version. The questionnaire was refined to 18 items following content and face validity evaluations. Construct validity was assessed using exploratory factor analysis (EFA) with principal component analysis and varimax rotation on half the sample (n = 300), followed by confirmatory factor analysis (CFA) on the remaining participants (n = 300). The final Older Adult Pedestrian Behaviour Questionnaire (OAPBQ) consisted of 16 items grouped into four domains: Traffic Rule Compliance, Preferences, Distraction, and Positive Behaviours, accounting for 53.8% of the total variance. CFA results indicated acceptable model fit (GFI = 0.91, CFI = 0.88, RMSEA = 0.09). Reliability, measured by Cronbach’s alpha, was 0.500. Higher scores indicated a greater frequency of engaging in specific behaviours with the highest behavioural scores observed in the Preferences domain and the lowest scores in the Distraction domain. The OAPBQ provides a valid and reliable instrument for assessing older adult pedestrian behaviours and addresses a long-standing gap in older adult pedestrian safety research in Iran. These findings offer valuable insights for policymakers and clinicians to develop targeted safety interventions and educational programs aimed at reducing injury risk among aging populations.
The concept of a ‘self-explaining road’ supports road design for safe road use by all modes to prevent crashes. Law supports self-explaining roads by creating the framework for road and vehicle design standards and establishes legal rules that guide road user behaviour (i.e. road rules). Alignment between different parts of this legal framework is important to achieve road safety objectives but is not always guaranteed. This study examined alignment between road and vehicle design standards and road rules from a legal perspective. A doctrinal research method is applied to explain legal principles and structures that contribute to alignment between laws affecting parts of the self-explaining road. Key findings illustrate that misalignment can occur between road design standards and road rules that apply to traffic management devices. Alignment could be improved by understanding discipline-specific approaches to obligation-setting, terminology and technical reference points. In practice, alignment can be promoted by locating road design standards, vehicle design standards, and road rules from their authoritative source, checking for discipline-specific explanatory guides and interpretive tools, and taking care when exercising discretion to apply standards according to local circumstances. Actionable recommendations for road authorities and lawmakers include: a comprehensive review of relevant laws to identify and resolve existing misalignment, and creating tools to minimise risks of future misalignment (e.g., cross-referencing systems, standardised terms, interpretative guides). Acting on these recommendations will allow law to better contribute to self-explaining roads and minimise liability risks for road users that breach road rules despite following road design.
The Bengaluru Metropolitan Region (BMR) in India includes both urban and rural areas, which predictably vary in terms of road fatalities and factors related to the road, road users, and post-crash care response. For Example, since highways often pass through rural areas, the speed limits on highways in rural areas range from 70 to 100 km/h. In contrast, speed limits on urban roads vary between 25 and 80 km/h, depending on the type of road. This paper presents cross-sectional analyses of differentials in observed median speeds and prevalence and factors related to speeding in urban and rural parts of the Bengaluru Metropolitan Region (BMR). Vehicular speed was measured. Data on vehicles, roads, and road user types were recorded. A total of 172,164 motor vehicles were observed in 25 locations, with the median speed in rural areas being significantly higher than in urban areas (p<0.05). The prevalence of drivers who were speeding was higher in rural areas compared to urban areas. In the logistic regression model, various factors, including vehicle types (i.e., four wheelers: adjusted OR= 5.85; p<0.001), as well as different road types (i.e., state highway: adjusted OR= 2.21; p<0.001) were associated with speeding in rural areas of BMR. Given the close link between speed and fatality crashes and the disparities in health infrastructure between rural and urban areas, there is a need for stricter enforcement of evidence-based speed calming measures in rural areas.
This study investigates the interrelationships between pedestrian safety perceptions, attitudes towards traffic safety, and self-reported behaviours. A comprehensive understanding of these behavioural and perceptual factors in local contexts is necessary for effective road safety interventions. A questionnaire survey was conducted in Bengaluru City, India (n = 693). Using exploratory factor analysis (EFA), the study identified three key dimensions influencing pedestrian behaviour: violations and errors, pedestrian awareness, and positive behaviours. EFA identified three factors accounting for 55.2 percent of the variance, revealing a strong association between awareness and safe pedestrian behaviour. This study is among the first empirical investigations in Bengaluru City to explore the psychological underpinnings of pedestrian behaviour specifically attitudes, perceptions, and self-reported practices within the framework of traffic safety and addresses a significant research gap in urban Indian settings. Violation tendencies were higher among younger and student participants, and awareness was positively associated with safer self-reported behaviour, although these relationships are correlational and not causal. Findings point to the importance of awareness campaigns and behavioural nudges, particularly in high footfall zones like education campuses. Moreover, patterns were consistent with a potential mediating pathway; however, mediation was not tested, and this remains a hypothesis for future confirmatory analysis. These insights inform development and future evaluation of behavioural and infrastructure based approaches to pedestrian safety in Bengaluru City and similar urban settings. The study makes a unique contribution by focusing on a culturally and infrastructurally distinct context, offering a nuanced understanding that can inform targeted interventions and policy reforms.
School-zone crosswalks in low- and middle-income countries often rely on infrastructure alone, leaving children exposed to speeding motor vehicles and low driver compliance. This field-based observational study evaluated how visible monitoring and enforcement cues, individually and in combination, influence drivers to stop (i.e., yielding behaviour) at a school-zone crosswalk in Mahasarakham, Thailand. Four real-world scenarios were compared: 1) no control, 2) visible monitoring through radar speed-display signs and CCTV, 3) traffic police enforcement, and 4) a combined treatment. Drone and CCTV footage recorded 1,646 pedestrian-vehicle interactions, which were analysed using descriptive statistics and binary logistic regression. Under the no-control condition, 24.9% of drivers yielded at a mean approach speed of 37.5 km/h. Visible monitoring alone increased driver compliance to 39.4%, police presence to 60.6%, and the combined intervention package to 71.7%, with corresponding mean approach speeds of 31.8 km/h, 30.6 km/h, and 28.3 km/h, respectively. Relative to the no-control condition, all intervention scenarios significantly improved yielding compliance, with the combined monitoring-and-enforcement treatment showing the strongest effect. In a separate multivariable model, vehicle speed, pedestrian-vehicle gap distance, pedestrian volume, and pedestrian crossing speed were significant predictors of yielding-related outcomes, whereas vehicle type was not significant after adjustment. Higher vehicle speeds, longer pedestrian-vehicle gaps, and faster pedestrian crossing speeds were associated with greater odds of driver not yielding. Higher pedestrian volumes were associated with lower odds of drivers not yielding. These findings indicate that conspicuous monitoring and enforcement can meaningfully improve compliance and reduce approach speed at school-zone crossings.
Children with disabilities and medical conditions are at an increased risk of injury or death during road vehicle transportation. In 2020, a national Australian survey of health professionals and organisations involved in the safe transport of children with disabilities and medical conditions identified a critical need for improved access to training, education, and resources. In response, Mobility and Accessibility for Children and Adults (MACA) Ltd developed targeted information and training resources. This study examined the impact of these resources on current road safety practices in Australia. A follow-up national survey was conducted with health professionals (n=126) and organisations (n=40) involved in supporting the safe transport of children with disabilities and medical conditions. Respondents included 74 participants (health professionals, n=56 health organisations, n=18) who also completed the 2020 survey, enabling direct comparison over time. Statistical and descriptive analyses of repeat participants reported greater confidence in their knowledge and more frequent assessment of transport needs for children with disabilities and medical conditions. The results reported a reduced frequency of barriers like lack of specialised knowledge, difficulty gaining funding for equipment, insufficient training and professional support, and unclear processes. However, many challenges persisted, with most respondents still reporting barriers. Health professionals and organisations that accessed the resources generally found them helpful, suggesting their potential benefits. Overall, the findings indicate promising improvements in the safe transport for children with disabilities and medical conditions, but additional efforts are required.
Climate change, characterised by long-term shifts in temperature, precipitation patterns and increased frequency of extreme weather events, poses substantial challenges to road safety. Understanding how these changes impact road safety is crucial for developing effective mitigation strategies and enhancing infrastructure resilience. The aim of this systematic review was to evaluate and synthesise existing research on the relationship between climate change-induced weather conditions and road crashes. Using the PRISMA protocol, a systematic search was conducted across three indexed databases (Web of Science, PubMed, Scopus). From the initial 352 records following the removal of duplicates and the application of inclusion and exclusion criteria, 15 studies were selected. The review identified a consistent association between increased rates of trauma from crashes and extreme weather conditions such as heavy rainfall, snowfall, icy conditions, heatwaves, storms, dense fog and hailstorms. Heavy rainfall and storms were particularly impactful, significantly deteriorating road conditions and reducing visibility. Snow and ice increased the crash risk due to reduced traction, while heatwaves affected driver behaviour and vehicle performance. The control variables, including time of day, road type, traffic volume, geographic location, vehicle type, driver demographics, and seasonal variations, ensured that the observed effects were attributable to the weather conditions. The findings underscore the urgent need for targeted policy interventions and infrastructure adaptations to mitigate the adverse effects of climate change on road safety.
Every day there are over 100 transport-related deaths in Brazil. With a focus on São Paulo, the largest city in South America, this study examined the commuting habits of haemodialysis patients with the aim of providing recommendations to health and transportation authorities to enhance safety and quality of life for these patients. A traffic medicine specialist interviewed 439 haemodialysis patients (56.0% males). Before haemodialysis, 243 patients (55.3%) were actively driving for their commute, and after beginning treatment, 157 (64.6%) continued driving. Among those who continued driving, 19.8% held a motorcycle licence, 29.9% reported minor collisions, and 10.2% drove without a valid licence. On dialysis days, patients (non-drivers and former drivers), rely on cars and buses for transportation. Hypertension, diabetes, and sleep disorders are frequent comorbidities and can also negatively impact driving abilities. Authorities in both law enforcement and health need to recognise the increased risk of traffic crashes among this population and reconsider driver licensing standards accordingly.
Road safety is a growing concern in rapidly urbanising cities, particularly in South Asia and regions with similar urban development challenges. This study developed a data-driven framework for assessing road safety risks, applied to three major roads in Kathmandu, Nepal: Kalimati to Balkhu, Chabahil to Boudha, and Durbar Marg to Kesar Mahal. Using two models, Branch Index Risk (BIR) and Section Index Risk (SIR), high-risk segments were identified. The findings indicate that Kalimati to Balkhu Road has the highest risk (BIR: 37.82%), followed by Chabahil to Boudha Road (BIR: 36.28%) and Durbar Marg to Kesar Mahal Road (BIR: 15.71%). Key contributing factors include inadequate pedestrian infrastructure, poor visibility, steep slopes, and missing signage. The study highlights the need for targeted interventions, such as improved crossings and enhanced signage, to safeguard vulnerable road users (VRUs). While based in the Kathmandu, Nepal context, the proposed framework and findings are applicable to cities in regions experiencing similar urbanisation and infrastructure deficits. Future studies should integrate behavioural and environmental factors to provide a more comprehensive understanding of road safety risks.
Injuries from road crashes remain a significant public health concern globally with a disproportionate burden in low- and middle-income countries like Ghana. While climate factors have been linked to crashes, the impact of injuries across different road user categories in urban Ghanaian settings remains poorly understood. This study sought to investigate the association between climate factors (temperature and rainfall) and non-fatal road traffic injuries among pedestrians, motorcyclists/tricyclists, and vehicle occupants in the Greater Kumasi Metropolitan Area of Ghana. The analysis combined road traffic injury data (N=8,772) (2010-2021) with climate data for the same period. Vehicle occupants were the largest proportion of injuries (42.4%, n=3,720), followed by pedestrians (33.5%, n=2,936) and motorcyclists/tricyclists (24.1%, n=2,030). Each millimetre increase in monthly rainfall was associated with increased injury risk across all road user types: pedestrians (1.7%, 95% CI: 0.6-3.0), motorcyclists/tricyclists (1.7%, 95% CI: 0.2-3.1), and vehicle occupants (1.6%, 95% CI: 0.4-2.7). The Kwadaso district experienced increase injury risk from 2010 to 2021, with relative risks increasing approximately sevenfold across all road user types, while the Kumasi Metropolitan area maintained consistently lower risk levels (RR: 0.4; 95% CI: 0.3-0.5). This study demonstrates significant associations between rainfall and non-fatal road traffic injuries across all road user types in Greater Kumasi Metropolitan Area of Ghana, with distinct spatial patterns of risk. These findings suggest the need for weather-responsive traffic management systems and user-specific safety interventions, particularly in high-risk districts with major highways.
Machine learning and deep learning methods show promise for injury severity prediction, but comprehensive synthesis of their effectiveness, appropriate evaluation metrics, and optimal methodological approaches are lacking. This study was a systematic review and meta-analysis of machine learning and deep learning methods for predicting traffic crash injury severity conducted following PRISMA 2020 guidelines and TRIPOD+AI standards for prediction model reporting. Eligible studies were published between 2014 and 2025 that met the inclusion criteria of: observational studies using neural networks for crash injury severity prediction with reported F1-score, G-mean, sensitivity, or confusion matrix data. In total, 74 studies were analysed including 2,127,059 crash cases. Pooled macro F1-score was 78.6 percent (95% CI: 76.2-81.0%, I²=84%). Transfer learning achieved highest performance (83.2%), followed by transformer/LLM methods (84.7%), hybrid CNN-RNN (81.8%), RNN/LSTM (81.2%), CNN (79.5%), shallow neural networks (76.8%), and conventional machine learning (73.5%). Deep learning significantly outperformed conventional ML (pooled difference 7.7 percentage points, 95% CI: 4.9-10.5, p<0.001). Sample size showed moderate correlation with F1-score (r=0.524, p<0.001). Combined imbalance handling (SMOTE/ADASYN plus class weighting) achieved 81.3% F1 versus 69.8% without handling (difference 11.5 percentage points, p<0.001), raising fatal crash sensitivity from 42.1 to 73.6 percent. Meta-regression explained half (56%) of between-study heterogeneity through sample size, imbalance handling, algorithm type, and study quality. Machine learning and deep learning effectively predict crash injury severity when using appropriate evaluation metrics and adequate samples. Transfer learning and transformers represent state-of-the-art. Sample requirements depend on model complexity rather than fixed thresholds. Combined imbalance handling is essential for minority class detection. Future research should adopt TRIPOD+AI standards, emphasise minority class metrics, assess fairness, and explore multimodal approaches. Implementation should prioritise interpretability and continuous monitoring.
Crashes on toll roads can be extremely hazardous, resulting in fatalities and serious injuries due to the high speeds involved. Although multi-vehicle crashes are more commonly observed on Indonesian toll roads, single-vehicle (run-off-road) crashes also pose a substantial risk of fatal outcomes. To identify the factors contributing to the occurrence of single-vehicle crashes on Indonesian toll roads, this study developed a crash prediction model or safety performance function (SPF) incorporating both geometric and traffic characteristics of the toll road segments using Negative Binomial regression model. The results indicate that higher average daily traffic, segments without roadside crash barrier, and segments with median concrete barrier are associated with a higher frequency of single-vehicle crashes. Conversely, the presence of a nearby ramp, bridge piers, and segments with rigid pavement are associated with a lower frequency of single-vehicle crashes. The findings may assist road operators in identifying high-risk segments for single-vehicle crashes, enabling them to take appropriate measures to enhance road safety.
Road traffic crashes can have severe consequences including death, making it essential to manage post-crash responses effectively. The aim of this study was to identify indicators and main factors that support post-crash response management within Thailand’s Eastern Economic Corridor that includes the provinces of Chachoengsao, Chon buri, and Rayong. Each province faces challenges with a high number of fatal and serious crashes, especially during holiday periods (Chachoengsao); frequent collisions due to heavy tourism and industrial traffic (Chon buri), and a rise in crashes, especially in industrial zones and densely trafficked areas (Rayong). The study was conducted in two phases. The first phase was a content analysis of the academic literature, alongside a review of secondary data from government and international reports related to post-crash responses. The second phase was a survey of professionals involved in road traffic incidents (n=196). Responses were analysed using Exploratory Factor Analysis (EFA) to identify and validate the factors informing post-crash response indicators. The findings identified 25 indicators grouped into two factors: Post-Crash Response Information (PRI) and Post-Crash Injury Care and Legislation Support (PRILS) that were used to create a framework to manage and improve the post-crash response. Post-crash response includes prompt assistance as well as preventing secondary crashes, saving lives, treating injuries, and ultimately reducing road traffic crashes. This approach contributes to improving the efficiency and effectiveness of post-crash response systems in alignment with international standards for road safety management.
In this study, we determine and quantify systematic factors influencing the number of crashes involving vulnerable road users (VRU) in administrative districts of Germany as a basis to develop a more targeted approach for traffic safety initiatives and activities. Generalised linear models are used to quantify the effect of climate, land use, demography and vehicle traffic on VRU crashes on the macro-scale of administrative districts in Germany. Considering only differences in population size may lead to an overestimation of the safety of VRU, especially in large cities. Differences such as precipitation, modal share, age distributions, land use and tourism were identified as significant causes for differences in the safety of VRU on the macro-scale. Disregarding these differences may lead to a false assessment of the safety of VRU. The models create a baseline of crash frequencies to be expected in statistical districts for cyclists and pedestrians, and to further highlight conspicuous districts where targeted traffic safety activities should be implemented.
This study developed and validated the “DINA HALO SAFETY” road safety education model, grounded in the Theory of Planned Behaviour and Social Cognitive Theory. Designed to boost road safety awareness and promote safer motorcycle riding among university students, it addresses gaps between theoretical knowledge and real-world practice through interactive, culturally relevant videos disseminated on social media. Using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) framework, researchers surveyed 416 students selected via proportional stratified sampling and conducted focus group discussions to refine content. Pilot testing to evaluate immediate outcomes was subsequently conducted (n=32 participants). Findings showed that almost all participants (98.8%) preferred succinct educational videos, highlighting TikTok and Instagram as prime delivery platforms. Expert validation yielded high Content Validity Index (CVI) scores, and pilot testing demonstrated statistically significant gains in both knowledge retention and behavioural intent. By integrating digital outreach, engaging material, and psychological constructs, “DINA HALO SAFETY” holds promise for broad application across diverse cultural and demographic settings. Strategic collaborative efforts with influencers, educational institutions, and law enforcement agencies could significantly amplify its impact. Future research should employ multi-institutional, larger-sample designs, utilise objective riding measures, and explore extended, longitudinal interventions that incorporate evolving technologies like augmented and virtual reality.
