HIV Treatment Compliance and Social Support for African American Women

Abstract

The proposed research tends to prove that social support affects HIV treatment compliance. To conduct it, a sample that includes African American women with HIV will be recruited. This paper provides some background information about the topic and justifies the study. It focuses on the description of the target population and sample and defines several ways to minimize selection bias.

Background

Since the end of the previous century, the issue of HIV has frequently been addressed by the healthcare professional, scientists, and even politics. As a result, the understanding of its criticalness spread worldwide rather quickly. A lot of various interventions were implemented to take this problem under control and minimalize it. Still, some vulnerable populations remain in a crucial situation. George et al. (2009) claim that Latinos and African Americans are the most prominent representatives of these groups. This idea is supported by the Centers for Disease Control and Prevention that underline that even though the number of people with HIV tends to reduce currently, African Americans are still the most affected population in the USA. They support this information with statistics of 2014, according to which, African Americans with HIV comprise 12% of the whole US population (CDC, 2016). More than a half of these individuals are gay and bisexual men. However, women are also in poor condition. Regardless of the fact that the number of African American females with HIV has reduced by about 40% since 2005, they still comprise 26% of HIV-positive people of their racial/ethnic group and are the most affected in comparison with women of other races/ethnicities (CDC, 2016).

In the majority of cases (89%), the reason for becoming HIV-positive turns out to be heterosexual contact (Ivy, Miles, Le, & Paz-Bailey, 2014). Less often this virus is transmitted by injection drug use. Professionals believe that the epidemic does not stop because women are not aware of their partners’ HIV. They also have overlapping sexual relations more often than European Americans. Poor access to health care, lack of proper housing, bad HIV prevention education, stigma, and discrimination also have enormous influence (Ivy et al., 2014).

Having no support and being affected by risk factors, African American women tend to ignore the problem of HIV. They are afraid that people will acknowledge their problem or will think badly about them, so they do not pay enough attention to it. This paper presupposes that there is the relationship between HIV treatment compliance and social support among African American Women with HIV. Thus, it will try to prove that family, friends and other significant individuals can encourage them to adhere to their medicines, which will prevent further spreading of HIV at least partially.

Target Population and Sample Size

This research study tries to find out how social support of African American women with HIV influences their HIV treatment compliance. Thus, it can be stated from the very beginning that its targeted population includes African American women with HIV. However, it is impossible to work with the sample that consists of all representatives of this group and to obtain accurate results. Thus, it is critical to specify more characteristics of the sample. The inclusion criteria for the study will focus on age and connection with social workers. Women who are 18 – 66 years old are typically diagnosed with HIV. Still, in the majority of cases, those who are 25 – 40 years old have HIV, as they tend to maintain more active sexual life than others, which increases their chances of being affected. To contact the sample, healthcare professionals could be approached. However, patients tend to obtain treatment and go away until the next time they require assistance, which means that it can be rather complicated to contact with them. Cooperating with social workers, in this perspective, seem to be more advantageous, as people come to them more than once, share their concerns including those not related to health, and even take part in anonymous meetings that help them to adapt to the situation. In this way, it tends to be easier to reach these people. Exclusion criteria will deal with the time HIV-positive women know about their status, as those who have just acknowledged that they have HIV maybe just going to tell their support system about this condition so that the results will not be true to life. In addition to that, individuals with other serious health conditions will not be considered because of the possibility to obtain biased information.

A snowball sample will be used to recruit participants, because they are not likely to interact with researchers. This technique allows reaching only a few representatives of the targeted population so that they will attract other participants themselves (Valerio et al., 2016). First of all, the researcher will contact social workers, asking them for a possibility to get in touch with the most socially active African American women with HIV. Each of them will recruit several more participants so that eventually their number will reach approximately 30-40 individuals. Such a number of participants tends to be enough for this research because the sample will represent the targeted population appropriately and there will be only several distinctions. Then, depending on the situation, they will meet face-to-face or contact by email. This will happen as soon as a list of questions for the interview will be created.

The interview will be the best data collection method for this study because it provides an opportunity to create positive relations with the sample, which is critical to obtain true to life answers. Of course, a list of questions will be developed beforehand, but there will be an opportunity to include some corrections when needed. For example, if a participant lacks some family members or has just moved and does not have any friends nearby yet. In this way, there will be a chance to clarify some information and reread it later as well, which will have a positive influence on the results of research. Taking into consideration the fact that it will be an epidemiological cross-sectional study, the participants will be contacted only once, which means that it is critical to obtain as many details as possible (Szklo & Nieto, 2014). Paxton, Williams, Bolden, Guzman, and Harawa (2013) support such approach, as they used interviews in their research, which focused on a similar topic. Considering the relatively small size of the sample, interviews tend to be appropriate, as it will be possible to conduct them even in one or two days. Traditional interviews are expected to last for about 15-20 minutes each, as they will be focused on a concrete issue. If some participants are willing to communicate using email, interviews may require more time, due to the necessity to type messages and wait for responses but the process can be streamlined because several interviews can be maintained at the same time.

Selection Biases

It is significant to focus on the selection bias when developing research because it can affect the validity of results. Trying to answer the research question, the researcher may refer to a sample that does not represent the targeted population appropriately and can “lead to inflated overall effect sizes and/or inaccurate findings” (Hegedus & Moody, 2010). This is an error that can affect any research and, unfortunately, it is impossible to ensure that it will not occur at all. Scientists only have an opportunity to minimize selection bias to some degree. The reduction of selection bias requires the identification of numerous details regarding the sample (Pannucci & Wilkins, 2010).

This very study tends to be rather valid. The targeted population is already reduced not only to HIV positive individuals but to African American women, which is beneficial. In addition to that, the sample is defined even better due to the implementation of inclusion and exclusion criteria. In addition to that, the information from non-participants will be used to consider possible future biases so that they can be addressed beforehand. For example, some information regarding the diversity of the targeted population will be obtained from the literature sources and some from social workers. The questions considering these differences will be included in the interviews so that they can be used as variables during research. In addition to that, the sample will be gathered in groups so that the bias that occurred because of the age can be reduced. Using snowball sampling, the researcher will have a chance to reach random participants, which will make generalization more successful. Of course, it would also be advantageous to make the sample as large as possible. Still, for this study, it seems to be more appropriate to limit enrollment and focus on the obtained information.

References

CDC. (2016). HIV among African Americans. Web.

George, S., Garth, B., Wohl, A., Galvan, F., Garland, W., & Myers, H. (2009).Sources and types of social support that influence engagement in HIV care among Latinos and African Americans. Journal of Health Care for the Poor and Underserved, 20(4), 1012–1035.

Hegedus, E., & Moody, J. (2010). Clinimetrics corner: the many faces of selection bias. The Journal of Manual & Manipulative Therapy, 18(2), 69–73.

Ivy, W., Miles, I., Le, B., & Paz-Bailey, G. (2014). Correlates of HIV infection among African American women from 20 cities in the United States. AIDS Behavior, 18(3), 266-275.

Pannucci, C., & Wilkins, E. (2010). Identifying and avoiding bias in research. Plastic and Reconstructive Surgery, 126(2), 619–625.

Paxton, K., Williams, J., Bolden, S., Guzman, Y., & Harawa, N. (2013). HIV risk behaviors among African American women with at-risk male partners. Journal of AIDS & Clinical Research, 4(7), 221.

Szklo, M., & Nieto, F. J. (2014). Epidemiology: Beyond the basics (3rd ed.). Sudbury, MA: Jones and Bartlett.

Valerio, M., Rodriguez, N., Winkler, P., Lopez, J., Dennison, M., Liang, Y., & Turner, B. (2016). Comparing two sampling methods to engage hard-to-reach communities in research priority setting. BMC Medical Research Methodology, 16, 146.