Thailand has the second-highest rates of road traffic mortality globally. Detailed information on the combination of human, vehicle, and environmental risks giving rise to each incident is important for addressing risk factors holistically. This paper presents the result of forensic road traffic investigation reports in Thailand and determines risk factor patterns for road traffic injuries. Detailed forensic reports were extracted for 25 serious traffic accident events. The Haddon matrix was used to analyze risk factors in three phases stratified by four agents. The 25 events analyzed involved 407 victims and 47 vehicles. A total of 65.8% of victims were injured, including 14.5% who died. The majority (66.1%) of deaths occurred at the scene. Human-error-related factors included speeding and drowsiness. Passenger risks included not using the seat belt, sitting in the cargo area and the cab of pickups. Overloaded vehicles, unsafe car modifications, no occupant safety equipment and having unfixed seats were vehicular risks. Environmental risks included fixed objects on the roadside, no traffic lights, no guard rails, no traffic signs, and road accident black spots. At present, traffic accidents cause much avoidable severe injury and death. The outcome of this paper identifies a number of preventable risk factors for traffic injury, and importantly examines them in conjunction. Road traffic safety measures need to consider how human, vehicle, and environmental risks intersect to influence injury likelihood and severity. The Haddon matrix is useful in identifying these pre- and post-accident risk factors. Furthermore, the sustainable preventions of road traffic injury need to address these risks together with active law enforcement.

This study aimed to create an appropriate model using verbal autopsy (VA) data to estimate transport accident deaths from vital registration data in Thailand. A sample of 9644 VA deaths was obtained from the Thai Ministry of Public Health. VA assessed transport accidents accounted for 546 deaths (5.7% of sample). Logistic regression was used to model transport accident deaths classified by 9 provinces, 16 gender-age groups, 14 combinations of vital reported cause groups, and place of death (in or outside hospital). The receiver operating characteristic curve was used to match the number of reported transport accident deaths to the number predicted by the model with sensitivity 73.8% and false positive rate 1.6%. The estimated transport accident deaths ranged from 1.68 to 2.65 times higher than the vital registration data reported according to gender-age groups.

In Thailand and worldwide, smartphone addiction among university students is a growing concern. This study aims to investigate behaviors of smartphone use, the prevalence of smartphone addiction, the duration of smartphone use, and their associated factors among pharmacy students at a university in northern Thailand. This cross-sectional study was conducted using an online self-administered questionnaire to collect data from January to February 2021. Smartphone addiction was measured using the Smartphone Addiction Scale: Thai Short Version (SAS-SV-TH). Of 281 students (70% female, average age of 21.1 (2.0), year 1 to 5), 87% used smartphones and tablets. Their average time spent on a smartphone was 7.5 (±3.1) hours daily on weekdays and 8.1 (±3.1) on weekends. The top three reasons for using smartphones were social networking (92.9%), education (90.3%) and entertainment (89.6%). Health-related problems associated with smartphone use were insomnia (51.3%), anxiety (41.3%), headache (38.8%) and stress (38.4%). The prevalence of smartphone addiction was 49% (95% CI: 44–55%); the associated factor comprised time spent on smartphones (>5 h/day). The prevalence of spending more than five hours daily on smartphones was 75% (95% CI: 70–80%) during weekdays and 81% (95% CI: 77–86%) during weekends; associated factors for during weekdays included a monthly smartphone bill of more than 500 THB (adjusted odds ratio: 4.30 (95% CI: 2.00–9.24) and for senior students (adjusted OR: 3.31 (95% CI: 1.77–6.19). The results remained the same for the weekend. In short, the results show that half of the pharmacy students were addicted to their smartphone; time spent on smartphones (>5 h/day) was associated with addiction. Therefore, university students should be encouraged to adopt healthy habits for smartphone use (such as limiting screen time and maintaining good posture while using a smartphone or tablet) and to increase their awareness of health-related problems.

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Background – Thailand has the second highest rates of road traffic mortality globally. Detailed information on the combination of human, vehicle and environmental risks giving rise to each incident is important for addressing risk factors holistically. This paper presents the result of forensic road traffic investigation reports in Thailand and determines risk factor patterns for road traffic injuries.Methods – Detailed forensic reports were extracted for 25 serious traffic accident events. For each report, accidents were characterized by the number of vehicles, number and type of injuries and deaths, road user types, involvement of roadside hazards, medical care provided, and human, vehicular and environmental influences on the incident. The Haddon matrix was used to analyse risk factors in three phases (pre-event, event, post-event) stratified by four agents (human, vehicle, physical and socio-economic environment).Results - The 25 events analyzed involved 407 victims and 47 vehicles. 65.8% of victims were injured, including 22.0% who died. Median age of those injured was 27 years, and 28 years for fatalities. Vehicles crashing with fixed objects, and pickup-related crashes, accounted for the majority of accidents and deaths. Head or neck trauma was the main cause of death. The majority (61%) of deaths occurred at the scene. Human error-related factors included speeding, and drowsiness from night and long-distance driving. Passenger risks included not using seat belt, sitting in cargo area and the cab of pickups. Not having anyone trained in first aid on the scene, first aid being provided by bystanders, and delayed calls to Emergency Medical Services increased injury risk. Overloaded vehicles, unsafe car modifications, no occupant safety equipment, and having unfixed seats were vehicular risks. Environmental risks included fixed objects on the roadside, no traffic lights, no guard rails, no traffic sign, road accident black spots, and hazardous objects roadside.Conclusions - Thailand must address all three temporal phases of the Haddon model and all three factors – human, vehicle and environment. At present traffic accidents cause much avoidable severe injury and death. The Haddon matrix is useful to structure road traffic investigations, revealing multi-level factors common on Thai roads. Keywords: Road traffic injury, Risk factor, Road traffic investigation, Haddon matrix