Alcohol and Drugs in Fatally Injured Drivers

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

The intention of the study

The study targeted to examine the relationship between alcohol consumption and accidents. The researchers wanted to understand the prevalence of drugs such as marijuana and alcohol in a huge sample of lethally injured drivers. The study examined how “drugged driving increases the number of grisly accidents today” (Brady and Li 104). This would support the idea of policy implementation.

Was the study descriptive or inferential?

This study is inferential because it begins by identifying the targeted population. The researchers targeted to examine the prevalence of drugs in a sample of drivers. The study focused on drivers involved in a fatal crash. The investigators used a statistical sample to test their hypotheses. The selected sample included fatally hurt drivers. The investigators used the inferential technique because they did not want to extend their findings to a larger population. They also used the inferential to make the best predictions about the targeted population (Brady and Li 106).

What were the variables in the study?

The researchers used different variables for their study. To begin with, the researchers grouped their population into two groups. The drivers were further grouped according to their race, driver type, time of the crash, level of intoxication, sex, race, gender, and age (Brady and Li 105). The other variables included the time of the crash, and fatalities reported after the accident. Other variables included the vehicle type and year of the crash.

Description of the population and its characteristics

The targeted population included drivers involved in fatal accidents. The population was from different backgrounds. The other unique characteristic was their involvement in a fatal road accident. The researchers performed drug testing on fatally harmed drivers (Brady and Li 106).

Methods used to collect data

The investigators used data from the country’s Fatality Analysis Reporting System (FARS). The National Highway Traffic Safety Administration (NHTSA) collects and compiles this kind of data (Brady and Li 105). The collected data was analyzed using the best statistical methods.

Statistical methods used to analyze the data (descriptive and inferential analysis techniques)

The researchers used an inferential technique to analyze the collected data. The study tabulated the prevalence of drug use in injured drivers using drug class. The researchers used multivariable-adjusted prevalence ratios (PR) and Poisson Regression. The scholars analyzed their data using Statistical Analysis Software, version 9.2, and Stata/SE version 11.2 (Brady and Li 106).

Summary of the study’s conclusions

According to Brady and Li (111), the use of various drugs is common among drivers in the country. Alcohol exposes a driver to a possible accident. The conclusions indicated that 57 percent of fatally wounded drivers in the country were using alcohol or other drugs (AOD). The researchers also observed that 20 percent of the victims had been using two or more drugs (Brady and Li 111). The study also indicated how alcohol prevalence varied significantly with crash uniqueness.

My opinion about the conclusions

The article offers useful findings and conclusions about the connection between drug use and road accidents. Studies show how alcohol and other drugs relate to road accidents (Brady and Li, 112). Drugged driving is a major concern in the country today. The article also examines how high-profile accidents arise from drugged driving. The article explains why drug use can increase a person’s chances of having an accident. This study encourages drivers to avoid AODs to reduce the number of accidents. Such conclusions are agreeable because drugs weaken a person’s driving skills.

Works Cited

Brady, Joanne and Guohua Li. “Prevalence of alcohol and other drugs in fatally injured drivers.” Addiction 108.1 (2012): 104-114. Print.

Click Here To Order Now!