Purpose Post-traumatic stress disorder (PTSD) is a frequent psychiatric complication in road accident survivors. However, it remains under-explored and is not taken into account in health policies in Benin. The purpose of this study was to determine the prevalence and risk factors of PTSD after a road traffic accident. This will help to improve its diagnosis and management in Benin hospitals. Materials and Methods An institution-based cross-sectional study was conducted from November 2020 to January 2021. Consenting victims of road traffic accidents from three hospitals across Benin, aged 18 years and above, living in the south of the country, were administered various questionnaires at 12-month follow-up. Data on PTSD were collected using a pre-tested, structured and standardized post-traumatic stress disorder questionnaire, the PTSD Checklist (specific version) (PCL-S). A logistic regression model was fitted to identify factors associated with PTSD. An adjusted odds ratio (AOR) followed by a 95% confidence interval was calculated to determine the level of significance with a p-value less than 0.05. Results Out of 865 patients in the cohort eligible for the 12-month follow-up, 734 (85%) participated in the study. The prevalence of PTSD was 26.43% (95% CI: 23.36–29.75). Factors associated with PTSD on multivariate analysis were female gender (adjusted odds ratio (AOR) = 2.14, 95% CI: 1.38–3.33), hospitalization (AOR = 1.87, 95% CI 1.21–2.89), negative impact of the accident on income (AOR = 4.22, 95% CI: 2.16–8.25), and no return to work (AOR = 3.17, 95% CI: 1.99–5.06). Conclusion The prevalence of PTSD is high in road accident survivors in Benin. The results of this study highlight the need for early diagnosis and a multidisciplinary approach to the management of PTSD patients in Benin’s hospitals.

Background In the large cities of Benin, motorcycle taxi drivers, mainly between the ages of 20 and 40, are particularly exposed to accidents due to their profession. User awareness, along with legislative reforms and enforcement measures, would reduce the incidence of crashes and injuries. This study aims to test the effectiveness of an awareness-raising model regarding helmet use for motorcycle taxi drivers. Methods This is a quasi-experimental study that will take place in the cities of Parakou (intervention group) and Porto Novo (control group). Over a three-month period, a package of awareness-raising activities will be implemented in the intervention area, targeting a group of motorcycle taxi drivers. The messages to be developed for awareness-raising will focus on the most frequently influencing factors, as identified by the baseline collection. These key messages will be disseminated through various tools and communication channels (banners, motorcycle stickers and motorcycle taxi uniforms, interactive sessions). Data will be collected prospectively via a self-reported questionnaire and observation, carried out before the intervention, at the end, and 6 months later. The data will relate to knowledge, attitudes and practices regarding helmet use. The analysis will compare the indicators between the groups, as well as between the pre- and post-intervention phase. The KoboCollect software will be used for data entry and processing, and Stata 15 will be used for data analysis. Chi-square or Fisher, Student’s or Kruskal-Wallis tests will be used for the comparisons. The difference-in-difference method will be used to determine the specific effect of the awareness activities. Discussion This study will assess the contribution of awareness messages to changing the behaviour of motorcycle taxi drivers by determining the specific effect of the intervention.

Background This study aims to test the effectiveness of an awareness-raising model designed based on the theory of planned behaviour regarding helmet use for motorcycle taxi drivers. Methods This quasi-experimental study took place in the cities of Parakou (intervention group) and Porto Novo (control group). Over a three-month period, a package of awareness-raising activities, based on the theory of planned behaviour, have been implemented in the intervention area. Data relate to knowledge, attitudes and practices regarding helmet use was collected prospectively before the intervention, at the end, and 6 months later. Stata 15 was used for data analysis. Chi-square or Fisher, Student’s or Kruskal-Wallis tests was carried out. The difference-in-difference method was used to determine the specific effect of the awareness activities. Results After the intervention, there was an improvement in the total score in both groups compared to baseline. The total score increased by 0.2 (0.06–0.3) in the experimental group when the number of sessions attended increased by one (p = 0.005). The difference-in-difference estimator measured among subjects who attended at least one awareness session, controlling for socio-demographic variables, showed a significantly higher difference in the total score of subjects in the experimental group compared to those in the control group both at the end of the interactive sessions and 6 months later. Conclusion This model improves the helmet-wearing behaviour of motorbike taxi drivers in the experimental area. It could be adapted and applied to other socio-professional groups and other types of users.

Background In Benin, motorcycles are the main means of transport for road users and are involved in more than half of crashes. This study aims to determine the effect of wearing a helmet on reducing head injuries in road crashes in Benin. Methods This case-control study took place in 2020 and focused on road trauma victims. The sample, consisting of 242 cases (trauma victims with head injuries) for 484 controls (without head injuries), was drawn from a database of traffic crash victims recruited from five hospitals across the country from July 2019 to January 2020. Four groups of independent variables were studied: socio-demographic and economic variables, history, behavioural variables including helmet use and road-related and environmental variables. To assess the shape of the association between the independent variables and the dependent variable, a descending step-by-step binary logistic regression model was performed using an explanatory approach. Results Fewer of the subjects with a head injury were wearing a helmet at the time of the crash 69.8% (95% CI = 63.6–75.6) compared to those without a head injury 90.3% (95% CI = 87.3–92.8). Adjusting for the other variables, subjects not wearing helmets were at greater risk of head injuries (OR = 3.8, 95% CI (2.5–5.7)); the head injury rating was 1.9 (95% CI = 1.2–3.3) times higher in subjects who were fatigued during the crash than among those who were not and 2.0 (95% CI = 1.2–3.3) times higher in subjects with no medical history. Conclusion Failure to wear a helmet exposes motorcyclists to the risk of head injuries during crashes. It is important to increase awareness and better target such initiatives at the subjects most at risk.