To begin with, testing appears to be the most appropriate method that could contribute to the health programs seeking a reduction in racial disparities in maternal and infant mortality cases. Speaking of this data collection strategy, it is vital to explain that it requires participants to complete examinations measuring skills, knowledge, and so on (Teddlie & Tashakkori, 2009). Drawing one’s attention to the combination of data techniques, tests appear to be a mixture of standardized and researcher-developed closed-ended test items and open-ended essay questions (Teddlie & Tashakkori, 2009). Answering the question of how testing could contribute to the problem solution, Taylor, Novoa, Hamm, and Phadke point out that “by focusing on five easily identifiable characteristics—heart rate, respiratory effort, muscle tone, reflex irritability, and color—the Apgar score introduces consistency in how infants are assessed and eliminates some of the medical personnel’s subjectivity and potential biases” (2019, p. 73). In other words, testing seems to be the number one method that could become a significant factor in decreasing the disparities in the rates of maternal and infant fidelity.
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What is more, a questionnaire is another means that could facilitate the elimination of such disparities in the aspect of the healthcare system under discussion. This method’s idea is that participants complete instruments measuring attitudes, behaviors, and others (Teddlie & Tashakkori, 2009). According to Taylor, Novoa, Hamm, and Phadke, healthcare providers can screen the risk factors through a questionnaire (2019). Moreover, in some states like Florida, ” State law requires every prenatal care provider to offer a Healthy Start Risk Screen to all pregnant women to assess risk for preterm birth and referral services.” (Taylor et al., 2019, p. 38). Thus, the practice is already applied due to its rationally explained effect on the issue under discussion.
Another point to be made deals with the sampling model. Firstly, there are various types of the approach mentioned above: probability, purposive, convenience, and mixed-method (Teddlie & Tashakkori, 2009). Secondly, describing this touch requires explaining the techniques that vary from random and cluster sampling to sampling for unique cases, and the one aimed to achieve representativeness and comparability. In a word, the sampling approach can serve various research objectives.
Finally, it is essential to address the question of racial disparities in the realm. To illustrate the current situation in the United States, one should focus on the statistics: “Non-Hispanic black women are three to four times more likely to die from pregnancy-related causes than Non-Hispanic white women” (Howell, 2018, p. 388). Racial disparities in the field of maternal and infant health in the United States are comparable to developing countries (Novoa & Taylor, 2018). Moreover, what seems to be even more illustrative is that “Non-Hispanic black women…had the fastest rate of increase in maternal deaths between 2007 and 2014 and have maternal death rates up to 12 times higher in some cities than Non-Hispanic white women” (Howell, 2018, p. 389). Some seek an explanation in African-Americans’ exposure to risk factors – for instance, lower socio-economic status or even poverty that leads to limited access to prenatal care (Novoa & Taylor, 2018). Therefore, it is fair to claim that the problem of higher maternal and infant death rates is present in the United States. Hence, the application of the techniques mentioned above is necessary for society.
Howell, E. (2018). Reducing disparities in severe maternal morbidity and mortality. Clin Obstet Gynecol, 61(2), 387 – 399.
Novoa, C., and Taylor, J. (2018). Exploring African Americans’ high maternal and infant death rates. Center for American Progress.
Taylor, J., Novoa, C., Hamm, K., and Phadke, S. (2019). Eliminating racial disparities in maternal and infant mortality. Center for American Progress.
Teddlie, C., and Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioural sciences. Sage.