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Traumatic brain injury (TBI) is one of the primary causes of morbidity and mortality globally, with around 1.7 million affected in the United States. This comprises thirty (30%) of the total deaths due to injuries annually (Jassam et al., 2017). Young adults are at higher risk of TBI, where motor vehicular accidents (MVA) are the leading causes, resulting in significant morbidity CITATION Cen16 \l 1033 (Center for Disease Control and Prevention, 2016). However, TBI is more commonly seen in young children and older adults due to their fall and accident risks ( CITATION Cen192 \l 1033 (Center for Disease Control and Prevention, 2019). To analyze the etiology and epidemiology of TBI in the young adult population, ages 18 to 35, the iceberg model will be used in this paper to examine the more and less evident factors that contribute to the numbers. This model helps clinicians understand the events' root cause before and after TBI CITATION Lon15 \l 1033 (London Leadership Academy, 2015). This paper aims to enhance clinicians’ understanding of the factors that influence the incidence of TBI using the iceberg model.
Background
Traumatic brain injury (TBI) is one of the primary causes of morbidity and mortality globally, with around 1.7 million affected in the United States. This comprises thirty (30%) of the total deaths due to injuries annually (Jassam et al., 2017).
TBI has complex pathogenesis due to primary and secondary damage to the brain, resulting in temporary or permanent neurologic problems. The primary damage is associated with the force outside the brain, while the secondary damage happens minutes to days after the primary external force. This results in a sequence of inflammatory, chemical, and molecular events that enhance neurologic deficits (Galgano et al., 2017; Silver et al., 2018).
The Center for Disease Control and Prevention (2019) states that there is a fifty-three percent (53%) increase in the number of TBI-related emergencies, hospitalizations, and mortalities from 2006 to 2014. Furthermore, an average of 155 people in the United States dies from the adverse effects of TBI in 2014. Among the causes of TBI, MVAs account for the leading cause of hospitalization in ages 15 to 44 years old, where it comprises 20% of all the TBI-associated hospitalizations.
Risk Analysis
The iceberg model shall be used to analyze the risks that accompany MVAs that result in TBIs. Various people portray diverse characteristics, and all of these factors influence people’s actions, knowledge, skills, social roles, self-image, and personal attributes. Diversity can be explained at various levels of consciousness including, intrapersonal, interpersonal, organizational, community, and societal. Some of these levels are not evident and are mostly submerged under an undiscovered environment CITATION Lon15 \l 1033 (London Leadership Academy, 2015). Therefore, to make risk analysis comprehensive, it is essential to evaluate all the levels associated with MVAs in TBI in the young adult population.
Intrapersonal Level
The intrapersonal level encompasses physiological, psychological, and behavioral factors of the individual. Bener et al. (2017) studied the drivers' intrapersonal characteristics that are more likely to become reckless or aggressive drivers. The most significant factors found were mobile phones, drug and alcohol use, slower driver reactions, inattention, and driving while drowsy or fatigued. These drivers are more inclined to careless driving, incurring traffic violations, and excessive speed, leading to pedestrian and property damage injuries. Another significant factor is the aggressive lane-changing behavior. For both lane-changing and non-lane changing behaviors, young adults have been found to have the most significant risk. Sleep deprivation and exhaustion contribute to the six-fold increase in traffic accidents in high-income and middle-income countries. Furthermore, these variables are associated with a 90% increased risk of MVA-associated deaths, especially in low- to middle-income countries (Bener et al., 2017; Rolison et al., 2018; Ma et al., 2018). Biological factors are due to the immature brain development or the lack of maturation of cognitive processes. Findings suggest that younger or immature drivers are usually angry and aggressive on the road. Alexythimia is also highly associated with young drivers (Banz et al., 2019).
Intrapersonal factors are vital in assessing MVAs that lead to TBIs because accidents can be minimized by reducing the occurrences of these aggressive behaviors. Prevention strategies can be constructed and implemented to avoid reckless driving secondary to alcohol and drug use and driving while fatigued and sleep-deprived. The research results can be reported to the authorities and government to make the necessary adjustments to prevent such instances.
Interpersonal Level
Family and peer influences are considered as interpersonal factors that affect the decisions and actions of an individual. Family factors influence driving behaviors by inspiring a particular driving style (i.e., reckless, careful, anxious, angry). The influence of the family begins during adolescents when they start to learn how to drive. The family also influences youngsters by observing road behaviors and family cohesion (Giquel et al., 2017). Another factor in dangerous driving is peer pressure, which is intended to show off. Young male drivers are more likely to be pressured by their peers, increasing risk-taking behaviors (Rolison et al., 2018).
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