Army Safety Essay Example

do not include family member injuries.

The numbers are much larger in scale. There is also no way to truly measure the loss of productivity in a unit when a soldier is out because of injuries or taking care of a family member’s injuries. The question is now identified. What is the maximum financial benefit to the Army when balancing spending additional money on the Army Safety Program and the expense of life insurance for those who die off duty in accidents? Stage 2 (Research Proposal) There are many sources available that provides statistics on accidents and fatalities within the Army.

The research will bring together several of these resources and show a bigger picture of the problems that the Army Safety Program should focus on improving. Judging by the current knowledge already obtained by acquiring a baseline of knowledge about the subject the following hypothesis is going to be tested. The null hypothesis is that the Army will prevent ore accidents if it places more financial emphasis on training Army soldiers and their families about possible dangers (Cooper& Schindler, 2008, p. 470).

This extra money will be offset by the savings in soldier readiness, lower medical expenses and the lower cost of life insurance payouts. The alternative hypothesis is that the extra money spent will only be an extra expense that will not bring forth the offset financially and save people from having more accidents (Cooper& Schindler, 2008, p. 470). This hypothesis and alternative hypothesis results will be determined after the research is compiled and analyzed. Stage 3 (Research Design Strategy) The design that is most useful for this project is the data collection

design.

The data collection design is most useful here for many reasons (Cooper& Schindler, 2008, p. 192). To name a few, the data is already collected and the Army has already spent its time and resources compiling it. By using data collection instead of sampling to only risk is the possibility that the Army has tampered with the information which is highly unlikely. But only raw data will be used to increase confidence in the results. Some investigative questions a required in order to ensure that relevant data is used to test the hypothesis (Cooper& Schindler, 2008, p. 83). The sample size is a pool that covers the entire Army. Thanks to the information available from Army sources the information is available. The data is reliable, valid and practical so the project meets the characteristics of good measurement (Cooper& Schindler, 2008, p. 289-95). Stage 4 (Data collection) The data being collected is data between 2007 and 2009. There have been several changes in some of the categories. The changes in these trends have significantly changed the amount of accidents and fatalities over the last four years.

Here is a quote from the Army Risk Management Information System. “In 2001, 366 people were injured, including 35 who died, in motorcycle accidents. In 2008, 474 people were injured, including 105 who died, according to the Armed Forces Health Surveillance Center’s June Medical Surveillance Monthly Report” (Kennedy, 2009) A statement like this indicates that it may be necessary for the army Safety Program to increase its focus on certain aspects of safety they may bring forth a lower number of accidents and fatalities.

Soldiers that ride motorcycles are

required to follow some additional safety guidelines that go above and beyond normal Department of Transportation Laws (Department of the Army, 2008) The Army’s approach to gathering this information is through observation (Cooper& Schindler, 2008, p. 193). Although, individual situations are kept personal all soldiers and family members are aware that data is collected for statistical purposes. Each soldier and family member signs a Privacy Act Statement that is kept inside the files (Army Field Band, n. d. ).

Information available from the Army Risk Management Information System website shows the numbers of accidents in several categories. The information is also categorized by classifications. The classifications go by the amount of money in damage caused by the accidents. Appendix A shows some of the most important excerpts from the reports. The special point of interest for this project is off duty fatalities and accidents involving soldiers and family members. The 2007-2009 off duty privately owned vehicle category shows that the trend line is lower in 2009 than in both 2007 and 2008.

Other categories of interest are also showing the same results. Off Duty Class A Privately Owned Vehicles is another category that shows a lowering trend (U. S. Army Accident Information, 2010). This is an indicator of several possibilities. The first correlating possibility is that soldiers are on duty more and that is why there are less off-duty accidents and fatalities. Another possibility is with the economy. With everyone trying to save money they may be staying home more. Factors like these certainly do affect the outcome.