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“Social determinants of health”
Where a person resides, gets the education, and works these conditions mutually impact the health of that person in determining health risks and outcomes. Such conditions are considered as social determinants of health (SDOH) (Social Determinants of Health | CDC, 2016). It is evident that a high education and rich background provide more awareness and opportunities of better nutrition and lifestyle, thus, these are considered as a predictor of better health. Force Field and Well-Being Paradigms of Health model by Blum emphasized on three main components mental, physical and social components. All these components mutually deliver the health outcomes were four main influential force fields are the environment, heredity, healthcare services and lifestyle. Blum’s model highlights the environment is the most effective field. The CDC model identified the similar factors contributed to health, except it identified the medical care as the least significant factor (Social Determinants of Health | CDC, 2016).
According to retrieved data, CDC calculated that half of the premature deaths are linked to lifestyle while only 10% premature deaths are due to inappropriate medical care. These estimations reveal that despite advancements and expenses in US medical care, how the delivery and services of medical care influencing the health status. To address this issue, it is necessary to give importance to medical care in comparison to other SDOH. The Blum model of health status gives the importance to health after the environment. The purpose of the health status is to enhance the health status with all mental physical and social dimensions. WHO defines that health does not mean the absence of disease, but a complete mental, physical and social wellbeing where health care services should be prioritized above all determinants (Social Determinants of Health | CDC, 2016).
“Force fields in Blum’s model” & “Poor Health”
“Force Field and Well-Being Paradigms of Health” model by Blum is based on three primary components that include mental, physical and social components. The Blum model of health status gives the importance to healthcare after the environment. The purpose of the health status is to enhance the health status with all mental physical and social dimensions. WHO defines that health does not mean the absence of disease, but a complete mental, physical and social wellbeing where health care services should be prioritized above all determinants (Social Determinants of Health | CDC, 2016). According to the CDC, “poor health” is linked to low socioeconomic status, lower education, unsafe environs and unstable accommodations. These are described SDOH by CDC for poor health that may not be limited to any particular or poor population. Haynes and Gale (2000) conducted a qualitative study on poor health in rural areas based on inequalities. They found that poor health and social deprivation showed that 570 wards in East Angelia UK were less connected in rural areas. The main reason for poor health in these inaccessible areas was unemployment amongst male (Haynes and Gale, 2000). Another qualitative study on poor health predictors was conducted by Trzesniewski and co-researchers (2006). This study used prospective data from the Dunedin multidisciplinary health study. In this 970 participants based study, the authors analyzed the control variables through statistical analysis. The authors concluded that low self-esteem during adolescence is the main predictor of poor mental and physical health that may lead to criminal behaviors and low income in adulthood (Trzesniewski et al., 2006). Thus, the indicators for the Poor health show a broad spectrum that may vary with the age and the demographic location of the person or population.
Two methods of data collection in a Qualitative Study
There are various approaches for collecting data in a qualitative study. The two main methods for collecting are taking interviews and retrieving observational data.
Observations are performed using a set of various instruments that may involve a single to multiple steps. The advantage of this method is that it provides undeviating information regarding the behavior of the subjects or population and good opportunities to identify unexpected outcomes. It exists in a flexible and unstructured setting. Observational data gathering can be conducted in natural settings and requires a descriptive representation of the occurrence by the researcher. The main problem with this qualitative method is to define the limits to natural settings for the situation and that may generate the problem with validity. The other weaknesses of this method are that it is expensive and time- taking which need well-qualified and highly skilled observers. Moreover, it impacts the participants’ behavior.
The Strength of interview-based qualitative study is that it provides the richest data, minutiae, and novel insights where interaction with the subjects is in a direct face-to-face mode that also reduces the chances of deviation. Conducting a qualitative research using interview approach requires precisely design question relevant to the research topic that can retrieve as much data associated with the research problem as possible. The questions of the interview should be able to address the purpose and aim of the research. In an ideal qualitative interview, the open-ended questions are suggested best that are neutral, responsive and comprehensive. The weakness of this model is, it is also costly and time-consuming with the requirement of highly trained interviewers. The interviewee may convey the wrong information, or create a bias response which can result in inconsistencies across results (Patton, 1990).
Validity Threats
Validity threats to an experimental research are associated with the probability of accuracy of the research outcomes. The validity threats, deal with the question whether the changes in the independent variable are really attributable to the observed discrepancy in the dependent variable, or the dependent variables are altered due to several other causes. The potential threats to experimental validity are of two types, external and internal. Internal validity depicts the whether an experimental condition is different and there are sufficient evidences present to support the proposed hypothesis. While external validity is associated with the characteristics of the outcomes able to generalize to all the populations. The study with stronger variable connections with the precise conclusion shows the results may be applicable to all populations to a specific extent. The study conducted by Trzesniewski et al., (2006) showed an experimental approach towards qualitative analysis where it emphasized that the low self-esteem during the adolescent phase predicts the poor mental and physical health and criminal behavior in adulthood. The study portrayed stronger variable connections with the precise conclusion that shows the results may be applied to all populations to a specific extent. There was less risk of internal validity because what the author proposed, he verified it by thoroughly studying the data by diving into independent, dependent and control variables. But there may exist the risk of external validity because when generalized to other populations there may be several other independent factors that can alter the dependent variables of the study, so it can not be generalized to all populations (Trzesniewski et al., (2006). Thus, to conduct a perfect qualitative study it is imperative to design the study using proper variables and considering the other external factors that can impact the research outcomes.
HIV/AIDS-Related Illness among Hispanic Women living in California
Introduction
Hispanics or Latinos have displayed three times higher AIDS incidence than whites. There are several reasons for these higher rates, including socioeconomic status, socio-cultural determinants, demographics, substance abuse, psychic health problems and options for psycho-social interventions. The AIDS/HIV data for California is 1/268 (Gonzalez et al., 2009). In 2013, this data reached 23% of the new diagnosed HIV cases among which 15% were females (Emlet & Farkas, 2001). In this research, we hypothesize that Hispanic females show high vulnerability as compared to Hispanic males and white people.
Literature Review
The minority communities with low social-economic sources possess the highest burden of HIV/AIDS. The ethnic minority groups such as African-American and Latinos are highly impacted (Bozzette et al., 1998). Socioeconomic factors associated with Hispanic Californians, including low education, language barriers, low income and inappropriate access to health care. The socio-cultural factors for this minority group include beliefs, knowledge and communication with healthcare professionals. These elements are linked with a perspective culture and acculturation where the preferences of language (Spanish Vs English), sexual behaviors and social operation impact the disparities among Latinos (Magana, & Carrier, 1991). The AIDS prevalence in five states, including California contributes to three-quarters of Latino AIDS cases. Among Latino women, the majority (73%) of HIV/AIDS is suffered through heterosexual contact while 23% are found infected via using infected IDU. Latinas are highly vulnerable to infection due to their long-term contract with monogamous relation and the reason of the infection comes through the risky sexual behaviors of their partners. The main problems with Latinas are that the partners with non-monogamous men remain oblivious of their risk factors until they or their partners start showing symptoms or become ill or they are screened for pregnancy (Van Oss Marin & Gomez, 2003).
Methodology
For the proposed hypothesis, we propose a qualitative study based on the female population of Hispanics living in Californian Region.
Population Sampling
For the study, the focus will be only on Californian Latinas or Latino women between the age group of 15-55. This range can be divided into three groups to ease the research analysis. The first group will include the age range of 15 to 18, the second group will cover 19 to 35 while the third group will include 36 to 55 age groups.
Sample size and measurement
An average sized sample will facilitate the evaluation results. The subjects were differentiated into different groups that were further divided into the sub-groups based on the response to the questionnaire. The Selected subjects will further be interviewed on the basis of their feedback to the initial interaction.
Data sources
The Latinas can be reached through the hospital and nursing home settings, college and universities. After taking their consent they will be provided with questionnaires that will include questions regarding their and their partners’ approach to sexual behavior, their awareness regarding health policies and the financial aids provided by the Government.
Data collection method and analysis
The data can be gathered from the interview responses from the participants. For data analysis, regression analysis can be included differentiating the data outcomes into apt variables.
Expected results
The results of this study will help in understanding the Latinas’ perception regarding sexual behaviors, their challenges, and cultural issues.
Conclusion
Based on the literature review, it is confirmed that Hispanic females or Latinas are highly susceptible to HIV/AIDS infections due to several socioeconomic and socio-cultural determinants. Furthermore, in this research, I have proposed a methodology to investigate the Latinas’ Sexual trends and their aspects towards sexual life.
References
Bozzette, S. A., Berry, S. H., Duan, N., Frankel, M. R., Leibowitz, A. A., Lefkowitz, D., &
Shapiro, M. F. (1998). The care of HIV-infected adults in the United States. New
England Journal of Medicine, 339(26), 1897-1904.
Emlet, C. A., & Farkas, K. J. (2001). A descriptive analysis of older adults with HIV/AIDS in
California. Health & social work, 26(4), 226-234.
Gonzalez, J. S., Hendriksen, E. S., Collins, E. M., Durán, R. E., & Safren, S. A. (2009). Latinos
and HIV/AIDS: examining factors related to disparity and identifying opportunities for
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Haynes, R., & Gale, S. (2000). Deprivation and poor health in rural areas: inequalities hidden by
averages. Health & place, 6(4), 275-285.
Magana, J. R., & Carrier, J. M. (1991). Mexican and Mexican American male sexual behavior &
spread of AIDS in California∗. Journal of Sex Research, 28(3), 425-441.
Patton, M. Q. (1990). Qualitative evaluation and research methods .
SAGE Publications, inc.
Social Determinants of Health | CDC. (2016). Cdc.gov. Retrieved 7 May 2016, from
http://www.cdc.gov/socialdeterminants/
Trzesniewski, K. H., Donnellan, M. B., Moffitt, T. E., Robins, R. W., Poulton, R., & Caspi, A.
(2006). Low self-esteem during adolescence predicts poor health, criminal behavior, and
limited economic prospects during adulthood. Developmental psychology, 42(2), 381.
Van Oss Marin, B., & Gomez, C. A. (2003). Latinos and HIV: Cultural issues in AIDS
prevention. San Francisco: University of California. Retrieved May.
