Objectives: This study aims to assess the perception and attitude of emergency medical services (EMS) providers toward working during disease outbreaks, and the factors that may influence their decisions to ultimately work or not.Methods: This is a cross-sectional study assessing the attitude of EMS providers to work during disease outbreaks. Descriptive statistics and regression analyses were performed to assess attitudes toward reporting for duty and factors that influence providers’ decisions.Results: Of the 500 surveys distributed, 466 (93.2%) were complete and included for analysis. The majority of participants (70.2%) are male with a mean age of 27 (SD 4.3) years. The study found that the majority (71.1%) of participants are willing to come to work during disease outbreaks. The study found 7 predictors of reporting for duty. Confidence that employer will provide adequate protective gear was the most significant predictor (odds ratio [OR], 3.95; 95% confidence interval [CI] = 2.31-5.42). Concern for family safety was the most important barrier against coming to work (OR, 0.40; 95% CI = 0.21-0.73).Conclusions: Providing adequate supplies of protective gear along with knowledge and training for disease outbreak are the main factors that enhance providers to fulfill their work expectations.

Objective This study aimed to explore the prevalence and factors associated with depression, anxiety and insomnia among frontline healthcare workers (HCWs) in Jordan. Methods A cross-sectional design was conducted among 122 frontline HCWs who have dealt with suspected or confirmed cases of COVID-19. The study survey included standardised questionnaires of the 7-item Generalized Anxiety Disorder (GAD-7) Scale, 9-item Patient Health Questionnaire (PHQ-9) and the Insomnia Severity Index (ISI). Data were collected online during the active surge period of cases from 11 May 2020 to 13 June 2020. The statistical analysis included descriptive statistics, analysis of variance, bivariate correlation and multivariate linear regression analyses. Results A total of 122 HCWs participated in the study (response rate=64.2%). Among the participants, 44.3% were physicians, 32.8% were nurses and 17.2% were paramedics. The mean age of participants was 32.1 (±5.8) years, and the majority were males (80.3%). The mean scores for GAD-7, PHQ-9 and ISI were 8.5 (±5.2), 9.5 (±5.7) and 11.2 (±6.4), respectively. Results showed that the participants reported severe symptoms of anxiety (29.5%), depression (34.5%) and insomnia (31.9%), with no observed differences based on gender, job title, marital status or educational level. Moreover, in the multivariate linear regression, none of the independent factors were associated with GAD-7, PHQ-9 or ISI scores, and the only exception was increased severity of insomnia among paramedics. Conclusion The COVID-19 pandemic has exerted strenuous emotional, psychological and physical pressures on the health of frontline HCWs.

Objectives: This study aimed to assess the cardiopulmonary resuscitation (CPR) knowledge and willingness of schoolteachers in Jordan.Design: This was a cross-sectional study conducted using an online questionnaire.Setting: For inclusion in this study, schoolteachers must be currently teaching at any level in schools across the country. Responses were collected from 1 April 2021 to 30 April 2021.Participants: All schoolteachers actively working in public or private schools were included in our study.Primary and secondary outcome measures: Continuous variables were summarised as means and SD, whereas categorical variables were reported as frequencies and percentages (%). A χ²test for independence, independent sample t-tests and analysis of variance were used appropriately. A p-value less than 0.05 was used to determine statistical significance.Results: A total of 385 questionnaires were eligible for analyses. Only 14.5% of the participants received CPR training and overall correct knowledge answers were 18.8% of the total score. Those participants with previous CPR training had higher mean knowledge scores (2.34 vs 1.15, p<0.001). Trained participants were also more likely to provide hands-only CPR to various patient groups than untrained participants (p<0.05). Participants were more willing to provide standard CPR to family members than hands-only CPR (p<0.001), but more willing to provide hands-only CPR to friends (p<0.001), students (75.1% vs 58.2%, p<0.001), neighbour (p<0.001), stranger (p=0.001) and patient from the opposite gender (p<0.001).Conclusions: Schoolteachers in Jordan possess limited knowledge of CPR. However, the study participants showed a positive attitude towards performing CPR. The study revealed that they were more inclined to provide hands-only CPR than standard CPR. Policymakers and public health officials can take advantage of these findings to incorporate CPR training programmes for schoolteachers, either as a part of their undergraduate studies or as continuing education programmes with an emphasis on hands-only CPR.

Objective: The aim of this study was to summarize the literature on the applications of machine learning (ML) and their performance in Emergency Medical Services (EMS).Methods: Four relevant electronic databases were searched (from inception through January 2024) for all original studies that employed EMS-guided ML algorithms to enhance the clinical and operational performance of EMS. Two reviewers screened the retrieved studies and extracted relevant data from the included studies. The characteristics of included studies, employed ML algorithms, and their performance were quantitively described across primary domains and subdomains.Results: This review included a total of 164 studies published from 2005 through 2024. Of those, 125 were clinical domain focused and 39 were operational. The characteristics of ML algorithms such as sample size, number and type of input features, and performance varied between and within domains and subdomains of applications. Clinical applications of ML algorithms involved triage or diagnosis classification (n = 62), treatment prediction (n = 12), or clinical outcome prediction (n = 50), mainly for out-of-hospital cardiac arrest/OHCA (n = 62), cardiovascular diseases/CVDs (n = 19), and trauma (n = 24). The performance of these ML algorithms varied, with a median area under the receiver operating characteristic curve (AUC) of 85.6%, accuracy of 88.1%, sensitivity of 86.05%, and specificity of 86.5%. Within the operational studies, the operational task of most ML algorithms was ambulance allocation (n = 21), followed by ambulance detection (n = 5), ambulance deployment (n = 5), route optimization (n = 5), and quality assurance (n = 3). The performance of all operational ML algorithms varied and had a median AUC of 96.1%, accuracy of 90.0%, sensitivity of 94.4%, and specificity of 87.7%. Generally, neural network and ensemble algorithms, to some degree, out-performed other ML algorithms.Conclusion: Triaging and managing different prehospital medical conditions and augmenting ambulance performance can be improved by ML algorithms. Future reports should focus on a specific clinical condition or operational task to improve the precision of the performance metrics of ML models.

Objectives Emergency medical services (EMSs) personnel are at high risk for developing work-related musculoskeletal disorders (WMSDs). However, no studies have yet investigated the prevalence and effect of these disorders on the Jordanian EMS personnel. Therefore, this study aimed to determine the prevalence of WMSDs among Jordanian EMS personnel and its associated factors. Design This study used a cross-sectional design. Participants were asked to complete a self-administrated and validated questionnaire to measure the WMSDs, including a demographic survey and the Nordic Musculoskeletal Questionnaire. Descriptive and multivariable regression analyses were used. Setting The Jordanian Civil Defence stations in the main cities of Jordan. Participants The sample consisted of 435 EMS workers which were obtained across the country of Jordan. A total of 79.0% of the participants were male, with a mean age of 27.9 (±4.3 SD) years. Results The pain in the lower back (308, 70.8%) and neck (252, 57.9%) were the most reported in the last 12 months. Furthermore, about half of the participants reported having pain in their upper back (234, 53.8%), knee (227, 52.2%) and shoulder (226, 52.0%) pain in the last 12 months. Overall, WMSDs in at least one body part were significantly associated with age, experience, being a male, increased body mass index and lower educational level. Conclusions There is a high prevalence of musculoskeletal complaints among EMS personnel. Multiple variables may be incorporated into a national prevention campaign and professional development programme to educate EMS personnel on avoiding WMSDs.