The article under investigation is based on the research carried out on HIV Testing in a household population consisting of both men and women aged between 15 years and 44 years living in the United States of America (Chandra et al, 2012). It should be noted that this report was generated with the help of data obtained from a research study dubbed the National Survey of Family Growth (NSFG). Done under the auspices of the Centres for Disease Control and Prevention (CDC), the NSFG was conducted from June 2006 to June 2010 and approximately 22,682 interviews were held (Chandra et al, 2012).
The main focus of this survey was to establish the estimates and trends that represent HIV testing prevalence in the aforementioned population group. In particular, the survey concentrated on determining the prevalence of HIV testing outside blood donations, including testing done during prenatal checks (Chandra et al, 2012). The social or demographic characteristics that were considered during the representation of data included: academic level, age, metropolitan residence, marital or cohabiting status, coverage of health insurance, household poverty index, and race (especially Hispanic affiliation). From the research, it was established that during 2006 and 2010 the number of people tested for HIV outside blood donation grew by 4% in women and fell by 5% in men (Chandra et al, 2012).
The data obtained in this survey was used in explaining the importance of people knowing their HIV status. Statistics from this study indicate that knowledge of individuals’ HIV status was responsible for decreasing infections. The study has also demonstrated the disparities in voluntary HIV testing among the different categories of the population, e.g. races, gender, class, literacy levels, and other demographic factors (Chandra et al, 2012). Furthermore, the statistical data within the study was used to demonstrate the growth that had been achieved in voluntarily HIV testing in the span of four years that formed the duration of the study. The use of statistical data in creating this study was appropriate in the sense that the report was easily understood and its extrapolation was an approximate representation of the entire population (Chandra et al, 2012).
Statistically speaking, it is clear that there was fulfilment of conditions that define t-tests. To begin with, all the observations and data that were harnessed from the survey were originally drawn from normally distributed populations (Plichta & Kelvin, 2012). The population sample used in this survey was able to generate a normal distribution curve. It should also be noted that the observations and data collected during the survey were independent. The fulfilment of the conditions was further demonstrated by the similarity of variance in the populations and the additive or numerical nature of the measures (Plichta & Kelvin, 2012).
The data obtained from the research was displayed using bar charts. A variety of colours was used to differentiate entities in all the bar charts represented in this article. These colours were used to differentiate between gender, race, literacy levels, health insurance, and other factors. The use of bar charts was specifically relevant and appropriate for this type of study (Plichta & Kelvin, 2012). This is true because it was necessary to compare the results obtained from different years, races, and gender and represent the same in a way that the differences could easily be seen. However, it could have been prudent if line graphs had been included in order to demonstrate the gradual growth of populations attending HIV testing over the four years (Plichta & Kelvin, 2012).
References
Chandra, A., Billioux, V. G., Copen, C. E., Balaji, A. & DiNenno, E. (2012), HIV testing in the U.S. household population aged 15–44: Data from the National Survey of Family Growth, 2006–2010. Hyattsville, MD: Centres for Disease Control and Prevention.
Plichta, S. K. & Kelvin, E. A. (2012), Munro’s statistical methods for health care research. (6th ed.), New York, NY: Lippincott Williams & Wilkins.