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.

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.

To translate and validate the Thai Self-Care of Chronic Illness Inventory version 4.c (Thai SC-CII v4.c) in individuals with chronic illnesses. A scale translation and cross-sectional validation study was conducted. The English version was translated for Thai involved nine steps: preparation, forward translation, reconciliation, back-translation, back-translation review, harmonization, cognitive debriefing, review of cognitive debriefing and finalization, and proofreading. A cross-sectional study was conducted from July to November 2022 at 16 primary care centers in southern Thailand, involving 410 participants with at least one chronic condition. Validity assessments included structural, convergent, and discriminant validity. Concurrent validity examined correlations between SC-CII v4.c with the Self-Care Self-Efficacy Scale (SCSES) and self-perceived health. Internal coherence reliability was calculated using Cronbach’s α coefficient, item-total correlation coefficients, and the composite reliability (CR) index. Thai SC-CII v4.c demonstrated excellent translational validity (κ = 0.99). The specified Self-Care Maintenance model fit well, with minor differences in health promoting behavior and illness-related behavior items compared to the original model. The original Self-Care Monitoring, and Self-Care Management models fit well with Thai data. Simultaneous confirmatory factor analysis confirmed a satisfactory fit of the full SC-CII v4.c. Convergent validity had partial support (average variance extracted = 0.23–0.51), and discriminant validity was established (heterotrait-monotrait ratios = 0.37–0.88). Concurrent validity was supported by positive correlations between each scale and overall SC-CII v.4c with SCSES (r = 0.25–0.65) and self-perceived health (r = 0.09–0.35). The Cronbach’s α coefficient were adequate for all scales except the Self-Care Maintenance scale (Cronbach’s α = 0.68), but the CR estimate improved the reliability of all three scales (ranging 0.80–0.82). All items had satisfactory item-total correlation coefficients (ranging 0.34–0.71), except the one pertaining to sleep. The Thai SC-CII v4.c is valid and reliable for assessing self-care in various chronic illnesses. Further testing is recommended for patients with specific diseases.

Aim: To test the validity and reliability of the Caregiver Self‐Efficacy in Contribution to Self‐Care Scale Thai Version (CC‐Self Efficacy Scale (Thai)) for Stroke.Design: A cross‐sectional study was undertaken from September to December 2022.Methods: Four hundred thirty‐four caregivers of people with stroke were selected from the registry of stroke patients in primary care units or hospitals following inclusion criteria. The research assistants collected information when the caregiver took a patient for a doctor's appointment or visited the patient's and caregiver's home.Results: The 434 caregivers had a mean age of 48 years, female 77.67%, 51.97% child or grandchild of patients, and 72.85% living with the patient. Ten items of the CC‐Self Efficacy Scale (Thai) were normally distributed and appropriate for exploratory factor analysis (EFA). EFA suggested three‐factor model. The confirmatory factor analysis (CFA) of the three‐factor model was an unfit model, with the root mean square error of approximation (RMSEA) = 0.09. We regrouped items based on content to create six‐factor model. CFA supported the six‐factor model of CC‐Self Efficacy Scale (Thai) questionnaire with the reliability judged by McDonald's omega being 0.87. The 434 sample size was enough for EFA and CFA. The CC‐Self Efficacy Scale (Thai) with the six‐factor model is appropriate for evaluating the caregiver confidence of people with stroke.

To evaluate the psychometric characteristics of the Thai version of Caregiver Contribution to Self-Care (CC-SC) of Chronic Illness Inventory version 2 (CC-SC-CII-v2) in stroke caregivers. We conducted a multicenter, cross-sectional study following the COSMIN guidelines, evaluating validity and reliability of three separate scales, CC-SC Maintenance, CC-SC Monitoring, and CC-SC Management, as well as overall CC-SC-CII-v2. From September to December 2022, we enrolled 422 stroke caregivers from primary care centers in southern Thailand. Structural validity was assessed through confirmatory factor analysis (CFA), while concurrent validity was evaluated using Pearson’s correlation r coefficients between CC-SC-CII-v2 and the Caregiver Self-Efficacy in Contributing to Patient Self-Care Scale (CSE-CSC). Internal coherence reliability was assessed using Cronbach’s α coefficient, the composite reliability index, and the McDonald’s ω coefficient. Additionally, test-retest reliability was assessed with intraclass correlation coefficients (ICCs). The study included mostly middle-aged women who cared for their parent. CFA supported the two-factor structure of the CC-SC Maintenance and Management scales and the one-factor structure of the CC-SC Monitoring scale. A simultaneous CFA on the combined set of items supported the more general model. The concurrent validity of CC-SC-CII-v2 with CSE-CSC was established (r ranging 0.47–0.65, all P < 0.001). Reliability estimates supported adequate Cronbach’s α coefficient (ranging 0.83–0.89), composite reliability (ranging 0.84–0.85), McDonald’s ω coefficients (ranging 0.83–0.85), and ICCs (ranging 0.86–0.90) across the three scales. The Thai CC-SC-CII-v2 demonstrated strong psychometric properties among stroke caregivers. It can be a valuable instrument to investigate the role of caregivers in contributing to stroke patients’ self-care in diverse cultural contexts like Thailand.

Health promotion and disease prevention (P&P) are essential components of primary health care. This study investigated the coverage of P&P services and barriers to services among primary care units in Thailand before and during the coronavirus disease 2019 (COVID-19) pandemic. A web-based cross-sectional survey was conducted to compare the data from primary care units across the 13 health regions in two fiscal years: October 2018 to September 2019 (before the pandemic) and October 2019 to September 2020 (during the pandemic). A total of 340 primary care units responded to the questionnaire. While most participating primary care units provided basic P&P services (n = 327, 96.2%) and community-based P&P services (n = 244, 71.8%), fewer offered area-based P&P services (n = 120, 35.3%) for all target populations. The high coverage of basic P&P services remained in place during the pandemic, while coverage of community-based P&P services for vulnerable and at-risk populations improved during the pandemic. Area-based P&P services improved for pregnant and postpartum women, preschoolers, children and adolescents, adults, and older people. Lack of human resources, materials and equipment, and financial support were cited as the primary challenges to offering P&P services. The higher coverage of P&P services in several target populations during the pandemic contributed to a heavy workload. Effective resource allocation, capacity building, and support from relevant parties, such as government and local agencies, are required to maintain high P&P service coverage.