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SPSS: Health Status--The U. S. Military
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"Active Duty" Link

The link above ("Active Duty") presents a detailed examination of self-reported health status of member of the United States military (all services) that was collected on the DoD Customer Satisfaction Survey.  Significant differences were identified between the three reported serivces (Army, Air Force, and Navy).  All graphs and table as well as the report presented below are link (Word document). 
 

Research Question:  Are there significant differences between the different U.S. active duty military services reported health status?

 

Introduction

             Perception can many times be reality.  The self-report of health perception has been validated as a form of determining health status.  Active duty military members are some of the most important components of protecting the United States against foreign aggressors.   In 1997-1998 the military health system queried a sample military service beneficiaries regarding various measures of patient satisfaction.  One of the question (17) asked the beneficiary what was their perceived health status (1 = Poor thru 5 = Excellent).  This paper is a written representation analyzing the hypothesis that there are significant difference (alpha = .01) between active duty military members (Army, Navy, and Air Force).

            The literature suggests that there are differences in the health status of active duty members.  One study identifies there are some significant differences in the dental health between active duty military forces.  The Army, Navy, and Marines (50-60% range) were significantly lower than the Air Force (89.5%). 

 

Methodology

            Utilizing SPSS (version 11.5) syntax function was utilized to select only active duty service member (i.e., no dependents / retirees).   The active duty (n= 4127) file was saved for further evaluation.  To get a good view of the data (e.g., dispersion, missing data point, frequencies) descriptive statistics were calculated for the number of active duty.  The mean health status (with SD) was computed for all active duty services.   Crosstab was then utilized to obtain the dispersion of active duty by service and reported health status.  Then the general linear model was utilized to see if there were any significant differences in the services by agean ANOVA was utilized to test for significance of the model.  Health status (dependent variable) was tested for significance as a function of branch of military service (A/F/N) and age category.  Significant differences were found between services.  A post-hoc test was conducted (Sheffes) to see where the significance existed.  All supporting computations and graphs are attached to the end of this report.

 

Results

            There were 142 missing cases (no health status reported).  Greater than half of the active duty members reported their health status was very good or excellent.  The general linear model reported that there are significant differences in reported health status between the services.  The post hoc test (Sheffe) indicated that there were significant differences between all three active duty services.  The Air Force (3.79) reported the highest mean health status, followed by the Navy (3.66) then Army (3.43).  The graph of the three services health status by age revealed that the Army and the Navy were virtually the same at age 18 to 24 years and the Navy was virtually the same as the Air Force at 35 to 44 years.  In all other age categories the Air Force had the highest mean health status followed respectively by the Navy and the Army.               

            The impact of the results of this study could be that further study is warranted to determine why the armed services do not have relatively the same health status.  Are the factors demographic or possibly environmental.  e.g., Air Force might have less demanding jobs or more access to health services/health promotion services.

 

Limitations

            There are not really any inferences that can be extended to all of the active duty forces.  This study was performed utilizing the data from only one TRICARE Region and might be flawed or biased because of it.  There were significantly less Air Force members than Navy or Army in the model.  This model might not be representative of all active duty services as a result.  A random sample of all active duty members may produce a more valid model.

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