NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES

Walden University NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES-Step-By-Step Guide

This guide will demonstrate how to complete the Walden University NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES                           

Whether one passes or fails an academic assignment such as the Walden University NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES                         

The introduction for the Walden University NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES                         

After the introduction, move into the main part of the NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES                         

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES                           

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES

Data plays a significant role in research to study phenomena of importance to populations and organizations. As such, there is always a great need for data. However, the lack of sufficient funding to support the collection of primary data means that secondary data and data sources are of great importance as they can also be used to drive research in the needed direction, for instance, studying particular population health problem to gain deeper insights into it (Pederson et al.,2020). As such, healthcare professionals and stakeholders can then come up with appropriate strategies to prevent and manage the condition and ensure better outcomes. Therefore, the purpose of this assignment is to explore secondary data sources and datasets with information regarding a chosen population health problem.

The Selected Population Health Problem

The selected population health problem is obesity in children. This condition has shown to be a multifaceted and complex health problem. The condition is associated with body fat accumulation, leading to being overweight and eventually obesity. Recent research shows that obesity, especially among children, has substantially increased in the last few decades globally, causing a major health concern (Poorolajal et al.,2020). Indeed, various factors have led to such a trend, including cultural aspects, socioeconomic status, physical activity levels, diet, environmental factors, and genetic predisposition. One of the main aspects of the condition is that children who use beverages and low-nutrient and high-calorie foods usually are at a higher risk of obesity (Liberali et al.,2020). It is important to note that obesity has several negative impacts, which are also far more than the physical health effects. Indeed, it also impacts a person’s social and psychological well-being.

Childhood obesity is also known to expose individuals to the risk of developing other comorbidities such as respiratory issues, dyslipidemia, hypertension, and diabetes, among other conditions. In addition, such children are also more likely to suffer from other negative aspects, such as low self-esteem, discrimination, and bullying, which can negatively affect their life quality. These negative impacts only add to the need to use appropriate strategies to prevent and manage the condition. Early intervention is particularly key in the management as appropriate steps should be taken to ensure that the health risks do not progress into adulthood (Horesh et al.,2021). Therefore, research plays a significant role, where various variable are studied and explored to find out how they are associated with obesity among children

The Selected Data Set, Associated Variables and Validity

Several data sets exist where valuable data on childhood obesity can be obtained to further enhance research in this area. One of the data sets for childhood obesity is the National Health and Nutrition Examination (NHANES). This is a dataset that allows individuals to mainly access the nutritional and health status of children and adults (“CDC,” n.d). NHANES has various variables that can be used to study obesity in children. The variables include health behaviors, socioeconomic status, physical activities, dietary intake, age, weight, and Body Mass Index. All these variables have various relationships with obesity. Hence, they can be used to describe the nature of obesity in this selected population.

NHANES is valid since the methods used in obtaining data are comprehensive and robust. For example, it uses a multistage sampling design, which ensures the representation of the non-institutionalized civilian. It also has a large sample size and uses standardized procedures and protocols. This data set has also been used for prior studies and publications. For example, a recent study by Uche et al. (2020) focused on childhood obesity in the US as impacted by environmental factors, where researchers obtained up to 200 environmental factors.

The next data set is the Behavioral Risk Factor Surveillance System (BRFSS), which contains data collected through telephone surveys. The data include chronic health conditions and health-related risk behaviors.  The dataset is created through a collaboration between the Centers for Disease Control and every state. It also has various variables used in the study of childhood obesity. The variables include socioeconomic factors, access to healthcare, physical activity level, dietary habits, demographic variables, BMI, and self-reported weight and height.

The Behavioral Risk Factor Surveillance System is also valid due to various reasons. For example, a large sample size is involved since thousands of individuals complete the survey each year to obtain the data. It also uses standardized questionnaires which have been formulated in conjunction with the state health departments and CDC. This data set also undergoes regular peer review by experts drawn from epidemiology and public health, which helps in the assessment of the reliability and validity of the findings and the methods used. The BRFSS data set has also been used for prior studies and publications. For example, a study carried out by Wang et al. (2021). The study used BRFSS data sets to study the prevalence of obesity in the US.

The next data set which can be used in the study of childhood obesity the National Survey of Children’s Health (NSCH). This data set has information on the emotional and physical health of children aged between zero to seventeen. The data is usually collected using paper-based and self-administered web questionnaires. The variables from this data set that can be used to study childhood obesity include the neighborhood environment, socioeconomic factors, access to healthcare, individual dietary behaviors, physical activity levels, height, and weight. These variables are related to childhood obesity. Hence, they can be used to enhance the study regarding childhood obesity.

The National Survey of Children’s Health is also valid for various reasons. For example, this dataset uses a comprehensive data collection strategy to collect a wide range of data, which enhances its validity. Standardized questionnaires are also used. These questionnaires are developed by the CDC in collaboration with various experts and federal agencies. This dataset also usually undergoes regular peer review by experts in various fields such as epidemiology and child health. These aspects make the data set valid and reliable. As in the previous data sets, this data set has also been used for prior studies and publications. For instance, in a recent study, Yusuf et al. (2020) explored the social determinants associated with obesity and overweight among children in the United States of America. This use the National Survey of Children’s Health of 2016-17 data set.

Challenges in Identifying A Proper Data Set or Securing Permission to Use It

It is so far evident that data sets are important since they contain valuable data that can be used in research. However, there are various challenges that can be faced in identifying a proper data set or securing permission to use it. One of the challenges is that not every data set is publicly available, so an individual may have to enter into special agreements or seek permission to use them. Accessing some of the data sets has cost implications since, in some cases, license fees, purchasing fees, or subscription fees may be required.

Conclusion

Secondary data plays a crucial role in research since it can be obtained using a relatively lower budget as compared to the collection of primary data. Therefore, it is important for individuals to know where they can obtain the needed and relevant data. This assignment has focused on datasets for childhood obesity.

References

CDC. (n.d). About the national health and nutrition examination survey. https://www.cdc.gov/nchs/nhanes/about_nhanes.htm

Horesh, A., Tsur, A. M., Bardugo, A., & Twig, G. (2021). Adolescent and childhood obesity and excess morbidity and mortality in young adulthood—a systematic review. Current Obesity Reports, 10(3), 301–310. Doi: 10.1007/s13679-021-00439-9

Liberali, R., Kupek, E., & Assis, M. A. A. D. (2020). Dietary patterns and childhood obesity risk: a systematic review. Childhood Obesity, 16(2), 70-85. https://doi.org/10.1089/chi.2019.0059

Pederson, L. L., Vingilis, E., Wickens, C. M., Koval, J., & Mann, R. E. (2020). Use of secondary data analyses in research: Pros and Cons. J. Addict. Med. Ther. Sci, 6, 58-60. https://doi.org/10.17352/2455-3484.000039

Poorolajal, J., Sahraei, F., Mohamdadi, Y., Doosti-Irani, A., & Moradi, L. (2020). Behavioral factors influencing childhood obesity: a systematic review and meta-analysis. Obesity Research & Clinical Practice, 14(2), 109-118. https://doi.org/10.1016/j.orcp.2020.03.002

Uche, U. I., Suzuki, S., Fulda, K. G., & Zhou, Z. (2020). Environment-wide association study on childhood obesity in the US. Environmental Research, 191, 110109. https://doi.org/10.1016/j.envres.2020.110109

Wang, Y., Beydoun, M. A., Min, J., Xue, H., Kaminsky, L. A., & Cheskin, L. J. (2020). Has the prevalence of overweight, obesity and central obesity levelled off in the United States? Trends, patterns, disparities, and future projections for the obesity epidemic. International Journal of Epidemiology, 49(3), 810-823. https://doi.org/10.1093/ije/dyz273

Yusuf, Z. I., Dongarwar, D., Yusuf, R. A., Bell, M., Harris, T., & Salihu, H. M. (2020). Social determinants of overweight and obesity among children in the United States. International Journal of Maternal and Child Health and AIDS, 9(1), 22. https://doi.org/10.21106%2Fijma.337

Sample Answer 2 for NURS 8310 WEEK 2 STRENGTHS AND LIMITATIONS OF SECONDARY DATA SOURCES

Population health problems pertain to health issues identified within a specific group of people. Various data sources can provide insights into population health issues. The data enables informed decisions, including interventions to address the population health issue (Boers et al., 2023). This assignment will concentrate on chronic lung disease as the chosen population health issue to determine relevant data sets and variables that can help assess the extent of chronic lung disease. The assignment evaluates the accuracy of the chosen data sets and the difficulties encountered in selecting an appropriate data set.

Population Health Problem

Asthma and chronic obstructive pulmonary disease (COPD) are substantial public health concerns that make substantial contributions to worldwide morbidity and mortality. Globally prevalent chronic respiratory conditions like asthma and COPD are distinguished by their unique physiological mechanisms and natural progressions. Chronic airway inflammation and persistent respiratory difficulties are hallmarks of COPD, whereas chronic airway inflammation is generally considered a defining feature of asthma. According to a study by Safiri et al. (2022), global age-standardized mortality rate data indicates that COPD was the second most prevalent cause of death in 1990. As of 2019, this rank had declined to the third most common cause. From 2007 to 2017, the prevalence of COPD increased by 15.6%, while the age-standardized prevalence among men decreased by 10.1%. COPD is acknowledged as a systemic disorder that is more commonly observed in individuals with a history of smoking. A multitude of comorbidities and risk factors necessitate immediate attention to tackle these health issues: genetics, smoking, infections, nutritional deficiency, aging, occupational exposures, indoor and ambient pollutants, asthma, and low-income levels.

Identification of each Data Set

The first data set that may be used to define the population and scale of chronic lung illness as the chosen population issue is the data set that is provided by government agencies, such as the Centers for Illness Control and Prevention (CDC). The World Health Organization (WHO) is the source of the second collected data collection, which includes global and international information. The American Lung Association contributes the third data collection, which comes from a private source.

Variable in each Data Set

The initial data set was acquired from the CDC in 2023. Four main factors are associated with chronic pulmonary disease, according to the CDC. Morbidity, mortality, visits to medical offices, and visits to emergency rooms are examples of these factors. Since 2021, chronic pulmonary disease, emphysema, and chronic bronchitis have been identified in 4.6% of the global population, as measured by morbidity. COPD patients constitute an estimated 4.2% of the total number of visits to office-based physicians. 1.2 million visits to emergency departments are attributed to COPD as the primary diagnosis. The COPD-related mortality rate is 42.9 per 100,000 individuals. The CDC classifies COPD as the sixth most significant cause of death in 2023.

The World Health Organization provides statistics on both global and international levels. The primary variables that are displayed are the proportion of deaths, age at death, symptoms, and factors contributing to COPD (World Health Organization, 2023). As per the World Health Organization (2023), 3.23 million deaths in 2019 were attributed to COPD. Globally, COPD is the third-most common cause of mortality. The World Health Organization (2023) reports that 90% of COPD-related deaths in those under 70 occur in low- and middle-income countries. Approximately 70% of COPD cases in high-income nations are caused by smoking.

The American Lung Association finances lung disease research, empowers talented scientists, and expands industrial cooperation to accelerate discovery and innovation. The primary variables outlined by the American Lung Association (n.d.) include the incidence of COPD, the prevalence of long-term bronchitis and emphysema in 2018, and the demographic groups most impacted. In 2020, approximately 12.5 million individuals were reported to have been diagnosed with COPD, as stated by the American Lung Association. COPD is more common in non-Hispanic white persons than in other ethnic groups. Another aspect to take into account is the age bracket. The most affected age group comprises persons aged 65 and older.

The validity of each data set

The data from the CDC (2023) is valid, consistent, and comprehensive in terms of validity. Previous research and publications, including the National Health Interview Survey, 2019–2021, and the National Ambulatory Medical Care Survey 2019, have utilized the COPD data from the CDC. The World Health Organization’s (2023) data is comprehensive and reliable, yet it hasn’t been used in any earlier research or publications. Lastly, the statistics from the National Health Interview Survey (NHIS) and the CDC are compatible with the data from the American Lung Association (n.d.). The Centers for Disease Control and Prevention, the National Health Interview Survey, and the National Centre for Health Statistics have all utilized data variables, including the prevalence of COPD provided in the American Lung Association data collection.

Challenges in identifying proper data set

Identifying a suitable data set can be challenging and is influenced by the data source. These challenges encompass the concern of obtaining consent for participation and the risk of harm to individual participants. Identifying a significant amount of information poses a time-consuming challenge. One challenge is the absence of identifying information in the data (Adeloye et al., 2021). Obtaining permission for the continued use of data may be a challenge if the data is not readily accessible online, in books, or from other public sources. Researchers may need to acquire the data through purchase or subscription.

Conclusion

In the field of epidemiology and population health, a wide variety of secondary data sources are available to inform practice. Secondary data sources from reputable organizations like government agencies, the Centers for Disease Control and Prevention, and the World Health Organization are considered reliable. The American Lung Association Research Institute is enhancing its funding for lung disease research, supporting talented scientists, and fostering collaboration with the industry to speed up advancements in discovery and innovation.

References

Adeloye, D., Agarwal, D., Barnes, P. J., Bonay, M., Van Boven, J. F. M., Bryant, J., Caramori, G., Dockrell, D. H., D’Urzo, A., Ekström, M., Erhabor, G. E., Esteban, C., Greene, C. M., Hurst, J. R., Juvekar, S., Khoo, E. M., Ko, F. W. S., Lipworth, B. J., López-Campos, J. L., . . . Rudan, I. (2021). Research priorities to address the global burden of chronic obstructive pulmonary disease (COPD) in the next decade. Journal of Global Health, 11. https://doi.org/10.7189/jogh.11.15003

American Lung Association. (n.d.). COPD Trends Brief. https://www.lung.org/research/trends-in-lung-disease/copd-trends-brief

Boers, E., Barrett, M. A., Su, J., Benjafield, A., Sinha, S., Kaye, L., Zar, H. J., Vuong, V., Tellez, D., Gondalia, R., Rice, M. B., Nuñez, C. M., Wedzicha, J. A., & Malhotra, A. (2023). Global burden of chronic Obstructive Pulmonary Disease through 2050. JAMA Network Open, 6(12), e2346598. https://doi.org/10.1001/jamanetworkopen.2023.46598

CDC. (2023). Chronic obstructive pulmonary disease (COPD). CDC. https://www.cdc.gov/copd/index.html

Safiri, S., Carson‐Chahhoud, K., Noori, M., Nejadghaderi, S. A., Sullman, M. J. M., Heris, J. A., Ansarin, K., Mansournia, M. A., Collins, G. S., Kolahi, A., & Kaufman, J. S. (2022). Burden of chronic obstructive pulmonary disease and its attributable risk factors in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019. The BMJ, e069679. https://doi.org/10.1136/bmj-2021-069679

World Health Organization. (2023). Chronic obstructive pulmonary disease (COPD). World Health Organization: WHO. https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(COPD)