Frontiers in Emergency Medicine

Exploring drivers' willingness to pay for safer roads in Iran: a discrete choice experiment on reducing injury and mortality risks

2026-02-15T12:47:56+0330

Background: Road traffic injuries (RTIs) are a leading global health challenge, with Iran facing significant economic and social costs due to these incidents. This study investigates Iranian drivers' preferences for road safety and their willingness to pay (WTP) to reduce injury and mortality risks. It also examines the influence of demographic and driving-related factors on these preferences. Method: A discrete choice experiment (DCE) was conducted among Shiraz residents to analyze route preferences. Participants evaluated hypothetical commuting scenarios characterized by variations in travel time, cost, injury risk, and fatality risk. Using a D-efficient fractional factorial design, 10 two-alternative choice scenarios were developed. Data were collected through interviews in five districts, achieving an 81% response rate. A mixed logit regression model was employed to assess how route attributes influenced participants' decisions. Results: Key factors driving route choices included the number of deaths, injury rates, travel time, and cost, with fatalities being the most influential. Participants were willing to pay $7.07 extra for routes with travel times under 30 minutes, $8.98 for routes with fewer than 10 annual injuries, and $11.83 for routes with fewer than 5 annual deaths. WTP varied significantly across demographic groups: men prioritized reduced travel time, while women emphasized safety. Personal-use drivers exhibited higher WTP compared to professional drivers like taxi operators. Larger family sizes correlated with lower WTP, whereas individuals in excellent health or with supplementary health insurance displayed higher WTP for safer and faster routes. Conclusion: This study underscores the utility of DCEs in capturing drivers' preferences for road safety and efficiency in Iran. By highlighting the trade-offs drivers are willing to make and identifying key factors, these findings offer actionable insights for policymakers to design transportation systems that align with public safety and mobility priorities.

Development and psychometric testing of the quality of care for trauma patients scale using exploratory and confirmatory factor analysis

2026-02-15T12:47:27+0330

Objective: Identifying trauma care quality from the trauma victims' viewpoints is key to patient-centered care, identifying service gaps, developing effective protocols, and building trust in medicine. The current study aims to establish a new quality of trauma care questionnaire and to assess its psychometric characteristics within the hospital context in Iran. Methods: First, items were developed through a combination of literature review and interviews. Then, the validity of the items, including content, face, and internal consistency, was evaluated. Construct validity was assessed using exploratory factor analysis (EFA) on a sample of 220 patients, followed by confirmatory factor analysis (CFA) with a separate group of 253 patients from August to October 2022. Results: Content validity, as measured using modified Kappa, was 0.95. Cronbach's alpha for internal consistency was 0.91, and test-retest reliability over two weeks was 0.94. The EFA revealed four factors: interpersonal quality, technical quality, outcome quality, and non-medical quality, which collectively accounted for 67% of the total variance in measuring the quality of care in trauma victims. Using CFA, researchers validated the final version of the trauma quality scale from patients' perspective (TQS-PP), which includes 22 items across four dimensions. The CFA model of the TQS-PP demonstrated an acceptable fit, with χ2/df = 2.064, RMSEA=0.058, CFI=0.912, and NNFI=0.920. Conclusion: Psychometric evaluations demonstrated sufficient validity and reliability for TQS-PP application in quality research involving trauma victims in Iran. The developed and evaluated TQS-PP serves as a reliable measure of health care quality from the perspective of trauma victims. The new tool could assist public health researchers in assessing the quality of care in emergency departments (EDs) and similar contexts.

Patient presentations at medical clinics during the martyrdom anniversary of Imam Ali bin Abi Talib mass gathering, Najaf, Iraq, 2024: a cross-sectional study

2026-02-15T12:47:31+0330

Objective: Religious mass gatherings in Iraq attract millions of pilgrims and have significant public health challenges. The martyrdom anniversary of Imam Ali bin Abi Talib (peace be upon him) in Najaf involves high population density and potential health risks. However, limited data exists on the spectrum of patient presentations during this event. Methods: It was a cross-sectional study in 12 health facilities (10 temporary mobile clinics and 2 fixed centers) established in Najaf for the event. The study was conducted from March 29 to April 1, 2024 (18–21 Ramadan 1445H). Data was collected by convenience sampling, entered via KoboToolbox, and analyzed in SPSS version 26 using descriptive statistics and chi-squared tests. Results: A total of 8,959 patients were registered. Most were aged 31–60 years (58.2%) and Iraqi nationals (80.8%). The most common acute infectious presentation was pharyngitis (16.7%: 95% CI: 15.9,17.4), followed by acute diarrhea (3.2%: 95% CI: 2.9,3.6). Noncommunicable conditions included hypertension (11.5%; 95% CI: 10.9,12.2), and diabetes mellitus (7.9%; 95% CI: 7.3,8.4). Patient presentations varied significantly by age group and nationality (P< 0.001). Conclusion: Pharyngitis was the leading acute presentation, suggesting a risk of respiratory disease transmission. Chronic conditions, particularly hypertension and diabetes, especially among adults over 31 years. These findings highlight the need for preparedness of temporary clinics to manage both communicable and noncommunicable diseases during religious mass gatherings in Iraq.

Unethical leadership can lower the quality in resuscitation teams: a randomized simulation study

2026-02-15T12:47:33+0330

Objective: The aim of this study was to evaluate whether verbal pressure from the team leader distracted students during a critical care simulation scenario. Particularly, examining the influence of unethical leadership on CPR quality was the objective of this work. Methods: Eighty students were randomized into study (n=40) and control group (n=40). They participated in a short cardiac arrest simulation scenario, each one separately. The scenario consisted of two tasks. Firstly, they were asked to bring to the team leader one ampule of a particular drug. A variety of drugs in their original packaging were placed on a shelf, but the handicap of this task was that the ampullae were mixed up between boxes. The second task was to perform 30 good-quality chest compressions. Study group participants were experiencing verbal pressure during the first part. Results: Study group participants fulfil the first task faster (require less time to bring the ampulla), but fewer of them find out that medications are mistaken (in comparison with the control group). Moreover, the study group reports higher stress levels (as assessed in 1 - 10 scores), and more participants perform too fast chest compressions (faster than 120 times per minute) in this group. Conclusion: Verbal pressure from a team leader increases participants' stress levels and decreases their effectiveness (chest compression quality and the ability to identify that ampullae are mistaken).

Decision tools for diagnosing spontaneous bacterial peritonitis: a systematic review and meta-analysis

2026-02-15T12:47:36+0330

Backgound: Approximately one-third of the spontaneous bacterial peritonitis (SBP) are missed due to the absence of paracentesis, and any delay in antibiotic initiation significantly increases mortality. Clinical decision tools may help to rule out or rule in the diagnosis without paracentesis. This study systematically reviewed the performance of available decision tools for diagnosing SBP in adult patients with cirrhosis. Methods: We included all original studies that evaluated clinical decision tools for SBP diagnosis. Search was conducted in MEDLINE, Embase, Scopus, and Web of Science Core Collection from inception to September 2024. Study quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS 2). Results: From 2038 records, 44 articles were scrutinized in full text. Twenty-four studies ultimately met eligibility criteria. Most of the studies were at low risk of bias. Several tools relied on laboratory findings with clinical features. In meta-analysis the Mansoura scoring system (cut-off of 4) showed a pooled sensitivity of 70.96% (95% CI: 42.06%,99.86%) and a negative predictive value 92.27% (95% CI: 88.80%,95.74%). The Wehmeyer’s scoring system achieved pooled specificity and positive predictive value of 98.43% (95% CI: 95.29,101.58%) and 90.26% (95% CI: 70.28,110.23%). A MELD score >15 yielded had pooled sensitivity of 83.85% (95% CI: 78.50%,89.20%) and negative predictive value of 87.56% (95% CI: 81.29%,93.84%). Conclusion: Several decision tools, particularly laboratory-based (e.g. procalcitonin) tools, showed high sensitivity to potentially rule out SBP. Some other tools (e.g. Mansoura, Wehmeyer rules) can reliably rule in the diagnosis. However, tools all the tools need further validation before widespread adoption.

Impact of verbal pressure on CPR and AED performance: a randomized simulation study

2026-02-15T12:47:40+0330

Objective:The aim of this randomized-controlled simulation study was to evaluate the impact of external verbal pressure on the effectiveness and safety of automatic external defibrillator (AED) use and hands-on cardiopulmonary resuscitation (CPR). Methods: Sixty-two first-year nursing students were recruited. Participants were split into pairs (n=31), randomly assigned to the study and control groups. Subsequently, each pair took part in a brief simulation scenario. One student was responsible for performing chest compressions, whilst the second was responsible for using an AED. The researcher verbally pressed the participants responsible for AED use in the study group. Students performing chest compressions were not the addressee of any comments. Participants in the control group acted without the researcher's pressure. Results: Only 2 participants in the control group used AED incorrectly, compared with 8 participants in the study group who incorrectly performed defibrillation. The rate of hands-on CPR was significantly faster in the study group compared to the control group (124±29.7 versus 104±20.8; P=0.028). Conclusion: Verbal pressure in simulation settings significantly diminishes the quality of performance during AED use. The pressure affected not only the participants to whom it was directly addressed but also their teammates, who performed worse compared to those without additional stressors.

Acute mesenteric infarction presenting with portomesenteric venous gas: a case report

2026-02-15T12:47:46+0330

A 72-year-old woman presented to the emergency department with fatigue and epigastric pain. Imaging revealed pneumatosis intestinalis and portomesenteric venous gas (PMVG), ultimately diagnosed as mesenteric infarction. The case highlights PMVG as an urgent radiological sign requiring prompt recognition and surgical consultation in emergency settings.

New technologies are on our side: Designing AI-Based Protocols for Emergency Departments

2026-02-15T12:47:49+0330

As a nurse in a bustling emergency department (ED), I’ve seen firsthand the chaos and intensity that define our daily work. The constant influx of patients, each with unique needs, creates a high-pressure environment where every second counts. Over the past year, our hospital began integrating artificial intelligence (AI)-based protocols into our workflow, and I’ve witnessed how this technology is reshaping the way we deliver care. It’s been a transformative experience, one that’s brought both promise and challenges, but ultimately, it’s made me hopeful for the future of emergency care.

Bridging performance and practice: the next step for artificial intelligence in basic life support education

2026-02-15T12:47:53+0330

Recent studies show that artificial intelligence (AI) has performed well on standardized basic life support (BLS) examinations. King et al. report that GPT-4V achieved 96% and 90% accuracy on the 2016 AHA BLS and advanced cardiac life support (ACLS) exams, respectively, including competent electrocardiograph (ECG) interpretation. This finding reflects substantial progress in multimodal model reasoning and suggests potential use in assessment and personalized learning.

Nevertheless, multiple evaluations of large-language models demonstrate highly variable accuracy in BLS scenarios—ranging from approximately 48% in question-based assessments to 85% in adult cardiac-arrest simulations and poor performance in pediatric and infant cases. Even GPT-4, the most consistent performer (κ ≈ 0.65), exhibits incomplete guideline adherence and limited reliability for unsupervised application. Thus, success in static examinations does not ensure reliable or safe behavior in dynamic clinical settings.

In contrast, Semeraro et al. highlight persistent weaknesses of current multimodal systems such as Qwen 2.5-Max and ChatGPT-4o, whose automatically generated cardiopulmonary resuscitation (CPR) training materials often lack anatomical accuracy, clinical validity, and adherence to professional standards. This discrepancy underscores the translational gap between algorithmic performance and genuine educational reliability.

The broader literature supports that AI, while capable of improving early cardiac arrest detection, compression precision, and feedback interactivity in simulation-based training, still yields inconsistent educational results. These mixed findings indicate that high exam scores do not necessarily guarantee pedagogically sound or clinically applicable training outcomes.

To enable responsible integration of AI in resuscitation education, three priorities should be addressed.
First, structured collaboration between AI developers and certified resuscitation educators is required to align algorithmic outputs with American heart association (AHA) and European Resuscitation Council (ERC) standards.
Second, expansion of curated, medically verified multimodal datasets—including high-fidelity ECG and procedural imagery—should support model training and validation.
Third, independent quality-assurance frameworks are essential to evaluate AI-generated educational content for factual, ethical, and pedagogical integrity before dissemination.

Artificial intelligence demonstrates significant potential to augment BLS education and improve preparedness for cardiac arrest. However, this promise will be realized only through rigorous interdisciplinary oversight, transparent evaluation, and sustained commitment to evidence-based implementation.