Elementary School-Aged Obesity
Introduction
The topic of the study is about the elementary school-aged children who are identified as obese. The study was a review of the efficacy of school-based intervention and home-based strategies to address the underlying effects and issues in obesity. Furthermore, the study shows that school-based interventions may reduce the BMI score of the elementary school-aged children (between six and eleven years of age), but such approach serve as a short-term intervention. On the other hand, it was stated in the study that in home setting can provide significant strategies that can help in halting obesity among these children. The role of parents is important in forming a better dietary and weight loss habits. The study also emphasized the importance of integrated approach in order to halt obesity among the elementary school-aged children. This can be done through school-based intervention with the participation of parents and the community in order to increase both the children and parent’s awareness about the proper way to prevent obesity at a younger age. Learning these interventions will increase my skills and competitiveness as a family nurse practitioner. Thus, it will benefit me from becoming a better educator towards my patients in relation to obesity prevention.
Data Analysis Plans
Data analysis serves as the process of cleaning, inspecting, and transforming data in order to discover various useful information. These pieces of information will help in the development of a conclusive idea about the involved issue. In order to obtain them, comparative analysis will be conducted using a parametric statistical test, so as to support the hypothesis of the study. On the other hand, non-parametric test may be used in the drawing a null hypothesis. In the data analysis plan, two factors will be involved, one is the plan for demographic variables and the other is the plan for study variables. These plans will focus on analyzing both the dependent and independent variables as well as the utilization of quantitative research approach.
Plan for Demographic Variables
According to its description, the descriptive statistical test or descriptive data analysis guides the researcher about how the data looks as well as the connections between the different variables within the set of data (Podesva & Sharma, 2013). Thus, it measures, min, max, median, mean, and the standard deviation (Stack Exchange Inc., 2016). On the other hand, demographic variables include gender, racial/ethnic status, educational level, and age (Jelenc, Pisapia, and Ivanusic, 2015). Therefore, for the data analysis plan for demographic variables will describe the essential information about the demographics, such as their age and racial status. In relation to the issue of obesity among elementary school-aged children, quantitative approach of data analysis will be conducted. Using the descriptive statistical test method will help in the understanding the issue with less detailed and complex data that is normally done in a qualitative approach. Additionally, quantitative approach will help in analyzing the data as it also tests both hypotheses and theories. Therefore, this research method serves as the best approach that will contribute to the development of research hypothesis. Additionally, this approach will lead to further description of demographics. For example, the analysis includes the prevalence of obesity data between girls and boys across this age group. Also, racial status will be included to analyze if cultural background influences the prevalence of obesity among these children. Demographic variables will be measured through standard deviation, as it is the most important measurement for my data, thus it is a useful guide of variability
Plan for Study Variables
For the data analysis plan for study variables, descriptive and inferential tests will be conducted. The descriptive approach will describe both the significance of dependent and independent variables. These will be all in relation to the occurrence of obesity between the ages of six and eleven years old. For the inferential statistical test, both the description of the issue and the gathered data will be used to develop an inference about the research hypothesis and null hypothesis. Specifically, the research hypothesis will be tested using the t-test, as it defines any difference between the two groups in the study. Data will be analyzed in aid of the research hypothesis, showing that the integrated intervention approach are sustainable in addressing the elementary school-aged obesity. Thus, the analogy will also develop an inference, showing a null hypothesis that integrated intervention approach is not sustainable in addressing the obesity issue.
Ethical Issues
The issue of obesity among children should have various ethical considerations. These include the assurance of low risk, from which the subjects will be exposed to. That is why, children who participate in any research must be protected at all times (Cline et al., 2013). For instance, the study of obesity among children as subjects must not create an environment that would trigger social vulnerabilities, such as the risk of experiencing discrimination or the risk for developing any related negative psychological effects. In addition, any involved research trials must not adversely affect the subjects’ health and well-being just for the sake of achieving the desired objective. When it comes to protecting their human rights, the children’s personal identity will not be included in the data gathering as well as on the data analysis process. This will ensure that the subjects’ privacy and the gathered information are to be kept confidential.
Limitation of the Proposed Study
The study aims to improve the physical activities of the participants. However, there are some limitations that were identified. First, the study is limited due to lack parents’ participation with the proposed intervention. Second, there is also a limitation in terms of an increased dropout rate due to psychological effects of obesity. Lastly, the lack of behavioral patterns towards addressing obesity is another limitation of this study.
Implication for Practice
The study creates implications towards the practice of family nurse practitioner. Since the profession involves a broad scope of practice, such as prescribing medication, diagnosing illness, and working throughout the patients’ lives, understanding the obesity will help in increasing the competitiveness of the practitioner. The family nurse will also have a better chance to educate parents as to how they can prevent the prevalence of such medical condition.
Conclusion
An integrated approach to addressing obesity is an ideal method in developing a long-term solution about the issue. However, ethical considerations must be applied in order to protect the welfare of children as subjects. Then again, the proposed research is effective for the development of sustainable solutions against child obesity.
References
Jelenc, L., Pisapia, J., & Ivanusic, N. (2015). Demographic Variables Influencing Individual Entrepreneurial Orientation and Strategic Thinking Capability. International Scientific Conference on Economic and Social Development.
Podesva, R., & In Sharma, D. (2013). Descriptive Statistics. In Research methods in linguistics. Cambridge, UK: Cambridge University Press.
Roth-Cline, M. D., & Nelson, R. M. (2013). Ethical Considerations in Conducting Pediatric Research. Pediatric Drug Development, 83-93. doi:10.1002/9781118312087.ch08
Stack Exchange Inc. (2016). Terminology - What is the difference between descriptive and inferential statistics? - Cross Validated. Retrieved from http://stats.stackexchange.com/questions/71962/what-is-the-difference-between-descriptive-and-inferential-statistics
