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Outcomes Associated With Chlamydia Prevention Programs in the U. S.

First, Chlamydia is not a widely investigated STI compared to other sexually transmitted diseases, for example, HIV infection. Intervention programs have been biased towards women due to associated cost-effectiveness, and the reason why most studies on STIs focus on women. Hence, this could be the reason for the continued increases in the incidence rate of Chlamydia infection in the United States (Centers for Disease Control and Prevention, CDC, 2014). Statistics indicate that the prevalence of Chlamydia infection from 1992 to 2012 was 182.3 to 456.7 cases per 100,000 population, respectively. Therefore, there is a problem somewhere; either there is sluggishness in devising more effective intervention programs, or the implementation of proposed programs has not been well implemented. Therefore, I aim to determine the current active intervention programs for Chlamydia infection, activities entailed within the programs, including targeted groups, and associated Chlamydia outcomes. This study is meant to enlighten the already prevailing Chlamydia prevention programs on the future direction to envisage more effective strategies that will help realize a reduction in the persistently high Chlamydia prevalence and incidence rates.

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There is ample literature on screening for Chlamydia, which could be attributed to its asymptomatic nature. Hence, there is a need to find out if more attention is given to screening tests in comparison to preventive programs. CDC (2015) states that preventive programs for Chlamydia focus on screening tests, which, in as much as they may be associated with increased awareness, other interventions on positive living should be integrated. Therefore, the a greater need for determining the nature of Chlamydia prevention programs that are underway, and their impact on the population because as stated by the Centers for Disease Control and Prevention (2011), more focus is on the screening programs. Thus, this will help to delineate the adamantly high prevalence rates of Chlamydia are either due to the effectiveness of the screening tests or inadequate preventive programs. In addition, this will help to answer the question of varying incidence rates for Chlamydia among different ethnic groups. In the two reviews I conducted in the week 2 assignment, high-intensity risk-reduction counseling was effective in reducing STIs where Chlamydia was part. On the other hand, this high-intensity risk-reduction was individualized; yet, individualized counseling might be time-consuming and not feasible for large populations. The available evidence has solely focused on behavioral counseling, yet other methods are just as effective. In a study by Davey-Rothwell, Tobin, Yang, Sun, & Latkin (2011), peer-based mentorship has been used to instill long-term behavior change based on HIV studies; yet, there is limited evidence on the use of this intervention to prevent Chlamydia. Thus, this study will help to decipher the novelty and diversity of Chlamydia-specific prevention programs.

This study will be guided by the following research questions:

  1. What is the number of the current prevention programs for Chlamydia?
  2. What is the coverage rate for each Chlamydia prevention program?
  3. What activities define each Chlamydia prevention program?
  4. What is the relationship between the current Chlamydia prevention programs and the occurrence of Chlamydia?


This is a quantitative study that will seek to identify the current intervention programs for STIs operating within the United States and their influence on Chlamydia outcomes. Commensurate with Harwell’s (2011) description of quantitative studies, this study will collect quantitative data that is viable for both descriptive and inferential statistical analysis. This study will entail an online search of the current programs used to prevent Chlamydia using keywords such as ‘prevention programs’, ‘Chlamydia’, ‘effective prevention strategies the USA, US’, ‘ongoing’, and ‘’current’. Also, the researcher will make personalized visits to institutions that keep account of the prevention programs for STIs and Chlamydia in particular. The researcher will only include programs or sub-programs that focus on Chlamydia.

According to Israel (2009), the researcher will adopt the concept of proportions when determining sample size; hence, Yamane’s formula as shown below will suffice. Upon identifying the programs to be included in the study, the researcher will determine the total population size by adding aggregate values from each program. Subsequently, the researcher will use proportionate sampling to recruit the sample from the different programs. A questionnaire will be developed and administered to the respondents online. The variables of concern will be coverage of the program by identifying the areas where the program has been implemented about sociodemographic characteristics of the region covered and group (s) targeted activities defining each program, and success indicators for each program based on coverage, behavior change, knowledge and attitudes, and substance use. These variables will rely on records from the programs’ performance records. These will be correlated with the prevalence rates of Chlamydia within the regions where different programs are stationed. Descriptive statistics will define the variables about proportions of interest, for example, coverage rate, knowledge and attitude, behavior change, and substance use. Inferential statistics will help to determine the correlation between the prevalence rate of Chlamydia and knowledge and attitude, coverage rate, behavior change, and substance use through regression analysis while chi-square will determine the association between categorical. ANOVA will be used to determine differences among samples (Vogt, Vogt, Gardner, & Haeffele, 2014).


Centers for Disease Control and Prevention (CDC). (2014). Chlamydia. Atlanta, GA: CDC.

Centers for Disease Control and Prevention. (2011). CDC grand rounds: chlamydia prevention: challenges and strategies for reducing disease burden and sequelae. Morbidity and Mortality Weekly Report (MMWR). Atlanta, GA: CDC.

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Davey-Rothwell, M. A., Tobin, K., Yang, C., Sun, C. J., & Latkin, C. A. (2011). Results of a randomized controlled trial of a peer mentor HIV/STI prevention intervention for women over an 18 month follow-up. AIDS and Behavior, 15(8), 1654–1663. Web.

Harwell, M.R. (2011). Research design: Qualitative, quantitative, and mixed methods. In C. Conrad & R.C. Serlin (Eds.), The Sage handbook for research in education: Pursuing ideas as the keystone of exemplary inquiry (2nd ed.) (pp. 147-163). Thousand Oaks, CA: Sage.

Israel, G. (2009). Determining Sample Size. Gainesville, FL: Florida State University.

Vogt, W. P., Vogt, E. R., Gardner, D. C., & Haeffele, L. M. (2014). Selecting the right analyses for your data: Quantitative, qualitative, and mixed methods. London: The Guilford Press.

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