Journal of Military Medicine
Year:2025 | Volume:26 | Issue:6|Papers Count:8

Considering the application of artificial intelligence technology across different fields, we decided to explore the opportunities and risks associated with its use in health. Hence, we will address some of the most significant opportunities and threats identified.

The mental health of military personnel is a top priority in the field of military medicine, as specific conditions of military service, such as war, intense training, and stressful missions, place military personnel at high risk of developing mental disorders. These disorders can manifest in a variety of forms, including anxiety, depression, post-traumatic stress disorder (PTSD), and even psychosomatic disorders. Research has shown that the rates of stress, depression, and anxiety among deployed military personnel are significantly higher than in the civilian population. Furthermore, psychological problems resulting from these conditions can affect the quality of life, social relationships, and job performance of individuals, jeopardizing operational productivity and mission safety. As a result, the need for comprehensive and preventive programs to maintain the mental health of military personnel is inevitable.

Background and Aim: The levels of care in the military medical evacuation chain include self-aid and buddy aid, paramedics, emergency medical technicians, nurses, anesthetists, and physicians, all of which are systematically organized within this chain. Given the challenges of providing high-quality prehospital care, particularly in combat environments, this study aimed to define the required job classifications within the military medical evacuation system in selected countries.Methods: This systematic review was conducted by searching scientific databases, including Scopus, Science Direct, PubMed, Google Scholar, SID, and Magiran, using keywords such as evacuation, training, military medicine, levels of care, and skills for studies published between 1999 and 2024. Article selection was based on Hawker’s quality criteria and the PRISMA checklist. The final selected studies were analyzed to extract job characteristics regarding roles, skills, activity levels within the medical evacuation chain, and training duration. Electronic searches were also conducted to gather data on global experiences and care level characteristics.Results: A total of eight studies were included in the final review. The evacuation chain consists of three non-specialized levels: basic self-aid and buddy aid, advanced self-aid and buddy aid, and operational paramedics. Additionally, four specialized levels were identified: emergency medical technician, nurse, general physician, and specialist physician. Expected skills at each level were determined based on battlefield experiences, progressing from non-specialized to advanced specialized levels, requiring both theoretical and practical training. The educational aspects of each job role within the military medical evacuation chain necessitate completing structured and ongoing training programs, including annual refresher courses.Conclusion: Updating military medical training and defining care levels within this chain enhances combat effectiveness. It is recommended that policymakers, educational authorities, and operational managers at headquarters, field forces, and military universities align existing job classifications with the seven defined levels. Moreover, updating skill training programs and structured educational planning will improve the knowledge, attitudes, and skills of combatants and specialized military medical personnel.

Traditionally, bleeding has been the primary cause of death in war zones. According to recent studies, a significant portion of battlefield fatalities are entirely preventable. Notably, more than 90% of casualties die before reaching the field hospital, making rapid bleeding control on the battlefield crucial. Over the past decade, several agents and devices have been developed to aid in bleeding control. We aimed to review the various aspects of known hemostatic agents, particularly their effectiveness in military applications. For this purpose, a comprehensive search was conducted in electronic databases (PubMed, Web of Science, Scopus, and Google Scholar) using keywords including military, war, battlefield, trauma, bleeding, hemostatic, bandage, and dressing. Hemostatic agents can act through a variety of mechanisms, including wound contraction, concentration of coagulation factors, adhesion to tissues, and release of coagulation factors at the bleeding site. The most important characteristics of an ideal hemostatic agent for controlling urban and battlefield bleeding include the ability to stop bleeding immediately, no need for mixing or processing before use, ease of use, lightweight and durable nature, long shelf life, acceptable safety, and cost-effectiveness. Additionally, it should be biodegradable, non-toxic, easy to remove, and flexible. Since 2003, various compounds such as Chitosan, Zeolite, Kaolin, Fibrin, and Smectite have been used to produce hemostatic products including HemCon, Celox, ChitoFlex, QuikClot, Combat Gauze, FSD, and WoundStat. Some of these products have received FDA approval, particularly for battlefield use. However, achieving the ideal product still requires further studies in the future.

Dengue hemorrhagic fever (DHF) is a viral disease spread by Aedes mosquitoes that causes fever, headache, muscle and joint discomfort, and, in extreme cases, hemorrhage and shock. It is acknowledged as one of the most serious public health risks of the twenty-first century and is rapidly spreading throughout tropical and subtropical countries. This review study sought to investigate the epidemiology of DHF in military personnel. The results show that Aedes mosquitoes, specifically Aedes aegypti, are the primary vectors of the dengue virus, and that environmental and human factors play an important role in the disease's spread. Military personnel are at greater risk due to deployment to endemic areas, and disease outbreaks among them can lead to mission disruption and significant medical costs. DHF has been documented among military personnel in a number of countries, including Vietnam, Somalia, and the Philippines. Given its geographical and climatic characteristics, Iran is likewise vulnerable to the introduction of mosquito vectors and dengue outbreaks. As a result, planning and preventive measures to preserve military personnel's health and control the spread of the disease throughout the country are critical.

Background and Aim: Spiritual health is an indicator of combat readiness to deal with the threats of soft war. Professors, as soft war commanders, are obliged to adjust the social determinants of students' spiritual health. This research was conducted to investigate the social determinants affecting the spiritual health of Iranian students, especially in the conditions of soft war.Methods: This qualitative study was conducted based on the grounded theory approach with the Strauss and Corbin paradigm model at Baqiyatallah University of Medical Sciences from October 2023 to June 2024. To identify the central phenomenon, causal conditions, contextual factors, intervention strategies, and consequences, in-depth interviews were conducted with 25 university professors, along with field observations and notes. The data were analyzed in three stages of coding (open, axial, and selective) using MAXQDA software.Results: Role model-oriented education is essential in the spiritual education of students. The professors only considered social conditions and the way of spiritual upbringing of the family as causal factors. They considered knowledge-acquiring methods, the type of communication with God, self, people, nature, and social motivation as background factors that promote or intervene negatively. Professors considered spiritual health as religious health. They considered the consequences of spiritual health (good behavior and morals) to be only affected by "religiosity”.Conclusion: The attention of spiritual mentor professors (soft war officers) to their role, the necessity of model-oriented education, attention to the hidden curriculum in spiritual education, along with enhancing spiritual knowledge, learning skills, and spiritual motivation is essential for education of Iranian students. Spiritual self-care of professors, reforming spiritual education methods, monitoring the performance of social models, social policy-making to deepen morals and spirituality are strategies for improving the spiritual health of students.

Background and Aim: Post-Traumatic Stress Disorder (PTSD) is one of the common, chronic, and debilitating psychological disorders that not only create psychological issues for affected individuals but also lead to numerous psychological problems among their family members. The present study aimed to compare the levels of emotional regulation, psychological flexibility, irritability, and symptoms of post-traumatic stress disorder among the children of individuals with PTSD and those of the general population.Methods: The present study was descriptive-comparative research. The study included 140 individuals (70 children of military personnel with PTSD and 70 children of military personnel without PTSD) in Yazd, Iran, from 2022 to 2023. They were aged between 15 and 19 years and were selected based on a convenience sampling method. Participants completed the Acceptance and Action Questionnaire - Second Version (AAQ-II), the Difficulties in Emotion Regulation Scale (DERS), the Irritability Questionnaire (CIQ), and the Post-Traumatic Stress Disorder Checklist (PCL). Analysis was conducted using descriptive statistics and inferential statistics by SPSS software version 29.Results: The results of the data analysis using Multivariate Analysis of Variance (MANOVA) indicated that the mean emotional regulation, psychological flexibility, irritability, and post-traumatic stress disorder symptoms in the children of military personnel with PTSD significantly differed from those in the children of non-affected military personnel (P<0.05). Specifically, the children of military personnel with PTSD had a higher mean in all these variables compared to the non-affected group.Conclusion: The results of this research indicate that the levels of emotional regulation, psychological flexibility, irritability, and post-traumatic stress disorder symptoms significantly differ between the children of military personnel with PTSD and those without. Monitoring these variables and raising awareness among children and families about the impact of their fathers' disorders on their psychological well-being can facilitate effective follow-up and therapeutic interventions for these individuals.

Background and Aim: Effective screening can help alleviate the challenges faced by the healthcare and treatment system in diagnosing COVID-19. This study aimed to introduce a machine learning model for predicting the severity of COVID-19 based on symptom records, laboratory factors, and demographic characteristics.Methods: This study was conducted using checklists completed by individuals suffering from coronavirus at Baqiyatalah Hospital in Tehran, Iran. The correlation between data characteristics and the target variable (severity of coronavirus disease) was analyzed using MATLAB 2019b software. Various classification models, such as Support Vector Machine, Decision Tree, Naive Bayes, Ensemble, and K-Nearest Neighbor, were utilized to predict the severity of COVID-19 disease. Precision, accuracy, readability, F1 score, detectability, and the area under the ROC curve for different classification models were calculated as features scored by the MRMR (Maximum Relevance-Minimum Redundancy) algorithm. These models were trained with data from 480 subjects (80% of all subjects in the data collection) and tested with data from 120 subjects (20% of all subjects). The MRMR algorithm was used to score the features related to the severity of COVID-19 disease.Results: The results of the study showed that LDH, CABG, vertigo, MI, rheumatism, obsessive behaviors, recurrence of the disease, diabetes, gender, SGPT, hemoptysis, sleep problems, angiography, and dry cough were the top fifteen characteristics to predict the severity of the coronavirus disease, respectively. The Ensemble model was reported as the best model for detecting the severity of COVID-19 with the highest accuracy, the value of the area under the ROC curve, and the F1 score, 0.72, 0.71, and 0.76, respectively.Conclusion: This study presents a machine learning method to facilitate early clinical decision-making during the COVID-19 outbreak and a COVID-19 severity prediction model capable of efficiently screening and classifying individuals into two groups: severe and mild COVID-19 disease.