Assessing The Impact Of Sexual Violence Screening On Health Care Usage, Savings And Quality Of Life Afterward

Research Question

The screening for sexual violence is especially important in institutions of higher learning where stigmatization plays a huge factor in preventing victims from reporting instances of sexual assault and seeking specialized treatment (Logan, Walker, & Cole, 2015). The victims often conceal the real cause (in this case, being assaulted sexually) of their injuries. Through screening for sexual violence, the victims of sexual assault can be identified and subsequently encouraged to open up and seek specialized screening (Henry & Powell, 2018).

Assessing the effectiveness and accompanying impacts of screening for sexual violence is important in determining what policies should be adopted when it comes to patient screening. It is also important in the development of approaches in medical practice regarding patient screening. This assessment is also vital in theory and research since it will provide more information on the subject, hence forming the basis for development of theories and further research.

The research question for this research is: What impact does sexual violence screening have on the health care usage, health care savings and the excellence of victims’ lives thereafter?

The screening for sexual violence might encourage a patient to seek further medical care especially if the screening affirms existence of sexual assault. The patient will be encouraged to open up about the sexual violence that they are exposed to. The care giver can then recommend the patient to specialists for both physical and psychological treatment. Whereas this is the ideal situation, the research will aim at establishing whether screening for sexual violence encourages sexual assault victims to seek more health care services.

The same case as for the health care usage applies for the health care savings. Ideally, seeking of further health care services lead to increase in health care spending and consequently a decrease in the health care savings. This research will evaluate the impact of the screening for sexual violence on health care savings.

Also ideally, we would expect that the screening for sexual violence would help the sexual assault victim to open up about the assault and hence their lives would be better thereafter. We cannot guarantee that if the screening for sexual violence affirms existence or history of assault, then the victim will seek the specialized treatment. We also cannot guarantee that if the victim seeks specialized treatment they will actually have a better life thereafter. Hence, we have to examine whether the screening for sexual violence affects the quality of the lives of the victims thereafter.

This research will test three hypotheses for the research question. The first hypothesis (Hypothesis One) will check for the relationship between the sexual violence screening and health care usage:

H₀: The sexual violence screening and health care usage are related to each other.

H₁: The sexual violence screening and health care usage are independent of each other.

The second hypothesis (Hypothesis Two) will check for the relationship between the sexual violence screening and health care savings:

H₀: The sexual violence screening and health care savings are related to each other.

H₁: The sexual violence screening and health care savings are independent of each other.

The third hypothesis (Hypothesis Three) will check for the relationship between the sexual violence screening and quality of life of victims’ lives thereafter:

H₀: The sexual violence screening and quality of life thereafter are related to each other.

H₁: The sexual violence screening and quality of life thereafter are independent of each other.

This research will apply a correlation research design. The correlation design is a quantitative research method which is applied when there is interest in determining what form of relationship exists between two or more factors of interest in a research (Everitt & Skrondal, 2010; Howitt & Cramer, 2010). This research design is appropriate for this research since the research is interested in examining the relationship between the sexual violence screening and the other factors in this research (health care usage, health care savings and quality of life).

The Pearson Correlation Coefficient Test will be the correlation test that will be applied for this research. The value the Pearson Correlation Coefficient ranges between -1 and 1 (O’Neil & Schutt, 2013). Values close to 0 indicate weak correlation, positive values indicate positive correlation, negative values indicate negative correlation and values close to the extremes indicate strong correlation (Shaffer, 2011).

Table 1: Variable Description Table

Variable Name	Variable Description	Variable Type	Measurement Scale
Sexual Violence Screening	Categorical Variable which represents information on whether a sexual assault victim underwent screening. Yes (1) or No (0).	Independent Variable	Nominal
Health Care Usage	Categorical Variable on whether a sexual assault victim sort health care services regardless of screening. Yes (1) or No (0).	Dependent Variable	Nominal
Health Care Savings	Numerical Variable representing amount of money spent on health care by the victim of sexual assault.	Dependent Variable	Ratio
Quality of Life	Categorical Variable representing the description of the life after assault by the victim on a Likert scale.	Dependent Variable	Ordinal

The population of study for this research will be the victims of sexual assault at the university. This population of study is appropriate since this research is interested in investigating sexual assault in institutions of higher learning. The data will be collected from volunteer participants through an online survey, which will be a cross-sectional survey.

This research will use the Cochran’s Sample Size Formula for sampling. The Cochran’s Sample Size Formula gives consideration to the ratio of population of study to the overall population which makes it advantageous (Ulf-Dietrich & Uwe, 2014). This formula applies the equation below (Cochran, 1977):

Z is value observed from probability tables, p is the estimated percentage of sexual assault victims at the university, q = p – 1 while e represents margin of error.

Information on the estimated percentage of sexual assault at the university can be collected from the relevant agencies at the university such as security and medical services.

Conclusion

We can conclude that the correlation research design presents the best research design for addressing the research question in this research. This is since this research design provides for the evaluation of the nature of relationship between factors.

We also conclude that the Cochran’s Sample Size Formula will be best fit in determining the sample size for the research. This formula will produce a sample size that can be considered representative of the entire university population. This would allow the findings from this research to be acceptable and reliable.

References

Cochran, W. G. (1977). Sampling Techniques (3rd ed.). New York: John Wiley & Sons.

Everitt, B. S., & Skrondal, A. (2010). Cambridge Dictionary of Statistics (4th ed.). London: Cambridge University Press.

Henry, N., & Powell, A. (2018). Technology-Facilitated Sexual Violence: A Literature Review of Emperical Research. Trauma, Violence & Abuse, 195-208.

Howitt, D., & Cramer, D. (2010). Introduction to Descriptive Statistics in Psycology, 5th Edition. New York: Prentice Hall.

Logan, T. K., Walker, R., & Cole, J. (2015). Silenced Suffering: The Need for a Better Understanding of Patner Sexual Violence. Trauma, Violence & Abuse, 16(2), 111-135.

O’Neil, C., & Schutt, R. (2013). Doing Data Science (3rd ed.). London: O’Reily.

Shaffer, C. A. (2011). Data Structures and Algorithms Analysis. Mineola: Dover.

Ulf-Dietrich, R., & Uwe, M. (2014). Mining “Big Data” Using Big Data Services. International Journal of Internet Science, 1(1), 1-8.