NURS 8201 Week 3 Sampling
Walden University NURS 8201 Week 3 Sampling-Step-By-Step Guide
This guide will demonstrate how to complete the Walden University NURS 8201 Week 3 Sampling 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 8201 Week 3 Sampling
Whether one passes or fails an academic assignment such as the Walden University NURS 8201 Week 3 Sampling 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 8201 Week 3 Sampling
The introduction for the Walden University NURS 8201 Week 3 Sampling 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 8201 Week 3 Sampling
After the introduction, move into the main part of the NURS 8201 Week 3 Sampling 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 8201 Week 3 Sampling
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 8201 Week 3 Sampling
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 8201 Week 3 Sampling
Indeed, sampling enables a researcher to use a section of the larger population to represent the entire group. The sampling technique assumes that the sample has the same properties as the remaining part of the population (Andrade, 2021). The assumption has, however, generated mixed reactions from researchers, with others claiming that some samples have a wrong representation of the whole group. There are different sampling methods, including random sampling, stratified sampling, systematic sampling, convenience sampling, purposive sampling, and cluster sampling (Campbell et al., 2020). Based on taste and preference, researchers choose their most preferred sampling techniques. Also, the data type collected dictates the choice of a suitable sampling method. Different sampling methods have unique validity outcomes; due to that, researchers ensure that they select a sampling method with the desired validity results. Accessing the proper sample and the hectic encounter during sampling are among the challenges researchers experience.
References
Andrade, C. (2021). The inconvenient truth about convenience and purposive samples. Indian Journal of Psychological Medicine, 43(1), 86-88. https://doi.org/10.1177/0253717620977000Links to an external site.
Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., … & Walker, K. (2020). Purposive sampling: complex or simple? Research case examples. Journal of research in Nursing, 25(8), 652-661. https://doi.org/10.1177/1744987120927206Links to an external site.
Sample Answer 2 for NURS 8201 Week 3 Sampling
In the world of data collection, sampling can be defined as a tool that is used to indicate how much data to collect and how often it should be collected. It defines the samples to take in order to quantify a system, process, issue, or problem. Sampling is used to represent a section of the population data gathered for research and study. It is used to represent a specific member of population to be represented within a study. According to Barratt & Shantikuma (2018), sampling is a method that allows researchers to infer information about a population based on the results in of a subset of the population, without investigating every individual. Individuals selected are representative of the whole population, making it easier to obtain high quality and balanced information.
In the current island of Guam, it is home to a diverse population and the researchable populations that are present in my area of practice include the high percentage of Chamorro, Filipinos, and Micronesian residents within the population of 170,000. Stratified sampling is one of the more appropriate approaches for my research study because in this method, the population can be divided into subgroups with different measures expected to vary and ensure representation from all groups of population. It is a probability sampling technique in which the total population is divided into homogenous groups or strata to complete a sampling process. The sample selected may be based on several factors such as scale, practicality, and accuracy. I choose this sampling criterion because the studying of health outcomes differs from the different population and is considered proper for an island that has only three hospitals. This results into more realistic, accurate estimation, and reduce chances of bias.
According to Qualtrics (2021), stratified sampling helps analyze a chosen sample population that reflects the groups in the chosen participant population. One example towards my research study would include demographic studies to determine which population is commonly susceptible to sepsis, if they would benefit with an implementation of a sepsis protocol, and studying their likelihood of being admitted in the intensive care unit. According to an observational research study by Yeun et.al., stratified sampling is the choice of random sampling when deciding whether patients should be admitted in the ICU relative to age, sex, income, and eligibility status (predictive of mortality, co-morbidity, and cognitive function status), and their high risk or low risk sub-groups for ICU triage (diagnosis, medical treatment, inpatient or outpatient).
Stratified sampling advantages include helping analyze differences based on shared characteristics such as race, gender, nationality, level of education, and age group. These sample sizes would then assist in defining the ratio sample so that it is proportionately measured, decreasing overlap, and allows researchers to draw an effective size from each strata or subgroups from different demographic factors (Elfil & Negida, 2017). Also, it would assist in obtaining samples representing the minority/under-represented populations. Some of its disadvantages include increased of selection bias due to holding prior knowledge about population, the random sampling may not accurately represent the full population or the population being represented and this type of sampling strategy may be time consuming.
Reference(s)
Barratt, H & Shantikumar, S. (2018). Methods of sampling from a population. Epidemiology
Health Knowledge Studies. Retrieved from https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population
Elfil, M. & Negida, A. (2017). Sampling methods in clinical research: An educational review.
Archives of Academic Emergency Nursing. 5(1). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325924/
Qualtrics (2021). How to use stratified random sampling to your advantage. Experience
Management Article. Retrieved from https://www.qualtrics.com/experience-management/research/stratified-random-sampling/
Yuen, K., Hyun, L., Yeon, L., Bo Ram, Y., & Hyun, K. (2019). Survival rates following medical
intensive care unit admission from 2003-2013: An observational study based on representative population based sample cohort of Korean patients. Medicine. 98(37). Retrieved from https://journals.lww.com/md-journal/fulltext/2019/09130/survival_rates_following_medical_intensive_care.22.aspx
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Sample Answer 3 for NURS 8201 Week 3 Sampling
This is insightful the sampling method is part of the quantitative research methodology that involves the collection of samples from the study population. The samples selected should always be a representation of the population under the study. Stratified sampling is one of the methods that can be used to draw a sample from the population under the study (Lynn, 2019). To address challenges associated with the use of stratified sampling, there is the need; there is need for researchers to identify the right population and develop appropriate tools for data collection (Ureña & Georgiev, 2018). Identifying the homogeneous groups for the research process is also necessary for enhancing the challenges associated with the stratified sampling process. Besides Chamorro and Filipinos, Polynesia and Micronesia may be considered the ideal population of study for the research problem. One of the strengths of the stratified sampling method is greeter precision compared to other methods. One of the main problems associated with the data collection or sampling method is difficulty identifying appropriate strata (Cao & Shen, 2020). Simple random sampling would be the best alternative data collection method in the research.
References
Cao, L., & Shen, H. (2020). CSS: Handling imbalanced data by improved clustering with stratified sampling. Concurrency and Computation: Practice and Experience, e6071. https://doi.org/10.1002/cpe.6071
Lynn, P. (2019). The advantage and disadvantage of implicitly stratified sampling. Methods, data, analyses: a journal for quantitative methods and survey methodology (mda), 13(2), 253-266. https://doi.org/10.12758/mda.2018.02
Ureña, C., & Georgiev, I. (2018, July). Stratified sampling of projected spherical caps. In Computer Graphics Forum (Vol. 37, No. 4, pp. 13-20). https://doi.org/10.1111/cgf.13471
Sample Answer 4 for NURS 8201 Week 3 Sampling
In conducting a research study on the prevalence of addiction, I would apply the systematic sampling and data collection approach. The systematic method of data analysis organizes data in a methodical manner (Winsett & Cshion, 2013). For example, studying the rate of heroin addiction among students in a particular university would be necessary to use questionnaires in data collection. Confidential ways of collecting feedback from the questionnaires are used to ensure the answers given are accurate. Systematic counsellors understand that the victims of drug addiction are autonomous and competent persons. The behavior of addicts makes perfect sense to them from their point of view. This humane ideology of the study population lays the basis for rehabilitation (Lempp, 2020).
Ethical challenges may be encountered during the study on addiction. Such challenges manifest as researchers compare studies of drug use across a different population with inhabitants from diverse backgrounds. This challenge is common when forming an exotic capacity for ethical analysis and apparatus for oversight and confidentiality of participants. The susceptibility of participants, communication on freedoms during the study, problems with disclosure, and authentication issues are some of the study’s challenges. Race and language barrier is other obstacles that researchers may encounter in obtaining a sample from this population (United Nations, 2004).
In addressing these challenges, I would draft highly confidential questionnaires. For example, a dropbox may be used by the study population in an institution to drop questionnaires once they have recorded responses. In addition, the questionnaires should not require the participant to fill in their details to maintain anonymity. Before undertaking the study, it would be advisable to explain their rights to privacy and discretion to the participants. In this way, any infringement can lead to legal action. Lastly, the researchers may post the questionnaires in different languages according to the population that is being studied. Another step may involve hiring translators to help the researchers break the language obstacle with participants.
In conclusion, it is essential to understand that systematic counseling is more effective than other methods because it creates a calm environment. Drug dependency victims do not feel the pressure to quit immediately. As a result, its success is attributed to rational decision-making by clients and willingness to change on one’s terms.
References
Lempp, H.P. 2020. Drug Addiction, the Systemic Approach, and the Concept of “Acceptance.” published in Journal of Systemic Therapies Vol. 15, 2/1996, p. 24-35. https://www.researchgate.net/publication/305187577_Drug_Addiction_the_Systemic_Approach_and_the_Concept_of_Acceptance
United Nations. 2004. Ethical Challenges in Drug Epidemiology: Issues, Principles, and Guidelines. https://www.unodc.org/pdf/gap_toolkit_module7.pdf
Winsett, P.R. & Cashion, K.A. 2013. The Nursing Research Process. https://www.researchgate.net/publication/5647190_The_nursing_research_process
Sample Answer 5 for NURS 8201 Week 3 Sampling
Sampling is a process in statistical analysis through which researchers select a predefined number of subjects from a larger population (Berndt, 2020). It involves the selection of a statistical sample to represent the whole population affected by research (Berndt, 2020). The sample may be a group of people, events, or behaviors, among other elements that help make inferences and draw conclusions about the entire population (Gray & Grove, 2020). There are different sampling methods, including random sampling, stratified sampling, systematic sampling, convenience sampling, purposive sampling, and cluster sampling (Berndt, 2020). Different sampling methods have varying validity outcomes, and the outcome of a research study is dependent on the population samples (Gray & Grove, 2020). This discussion reflects on a population in my area of practice and describes the most appropriate sampling method for use in my study. The paper will also identify the challenges of obtaining a sample from this population and recommend strategies to overcome them.
My area of practice is mental health and wellness. The most appropriate sampling method for use among patients with mental health disorders is stratified sampling. Stratified sampling is a probability that divides the population under study into homogeneous subgroups based on specific characteristics and samples them independently (Mishra & Alok, 2022). Additionally, this sampling method is useful when the population varies significantly (Mishra & Alok, 2022). Therefore, the stratified sampling method is the most appropriate for use among patients with mental health disorders. This is because participants can be grouped based on characteristics such as the type of mental health disorder and severity of symptoms. Also, it facilitates a comprehensive representation of the entire population and ensures that each subgroup is adequately represented (Mishra & Alok, 2022).
There are various challenges I might potentially experience while obtaining a sample from patients with mental health disorders using a stratified sampling method. The first challenge is ensuring that there is no significant variation within any given strata (Mitani et al., 2021). This means ensuring that each subgroup of the population is homogeneous based on the criterion used. The other challenge that I may potentially encounter is difficulty grouping individuals with similar characteristics into a stratum so that the result is not biased (Mitani et al., 2021). This is partly because some of the individuals with mental health issues may belong to more than one stratum. Moreover, I may experience time constraints in obtaining a sample from patients with mental health disorders using stratified sampling (Mitani et al., 2021). This is because identifying members of a subgroup, determining the sample size, and ensuring that the sample selected is a true reflection of the selected population may take a lot of time. Besides, using stratified sampling to obtain information from people with mental health disorders may be more costly than doing so using other sampling methods (Mitani et al., 2021). This is true, especially when dealing with a diverse population.
I would address this challenge by clearly outlining the rationale for selection for each subgroup and mentioning the potential biases associated with the study. I would also take time to collect additional information about each stratum to understand how different one is from another. I would address this challenge by identifying cheaper alternatives for data collection in each stratum. I would address this challenge by combining similar strata and using accurate data to group subgroups.
The approach I would recommend to collect data using stratified sampling has various steps. The first step is to define the study population clearly, and an example is individuals with mental health disorders. The second step is grouping the population into specific groups, say patients exhibiting depressive symptoms and aged 18 and above. The next step is identifying the study population, say 80 participants. The next step in my approach involves selecting individuals for each subgroup using a random sampling technique. The other step is ensuring that the sample truly reflects the entire population. The next step is data collection using various techniques such as interviews, surveys, and observation. This step is followed by an analysis of the collected information and, later on, reporting the findings.
References
Berndt A. E. (2020). Sampling Methods. Journal of human lactation : official journal of
International Lactation Consultant Association, 36(2), 224–226.
https://doi.org/10.1177/0890334420906850
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research:
Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
Mishra, S. B., & Alok, S. (2022). Handbook of research methodology.
Mitani, A. A., Mercaldo, N. D., Haneuse, S., & Schildcrout, J. S. (2021). Survey design and
analysis considerations when utilizing misclassified sampling strata. BMC medical
research methodology, 21(1), 145. https://doi.org/10.1186/s12874-021-01332-8
Sample Answer 6 for NURS 8201 Week 3 Sampling
The diagnosis of autism is extensive. Autism is a broad spectrum condition making the processing for testing and diagnoses extensive. The growing population of autistic individuals is increasing (Alimanova, et al 2020). In this discussion, we will discuss the researchable population presented for students 3.9 years and up to 13 years old diagnosed with autism.
Population
Depending on the spectrum, autism can take years to diagnose. The symptoms of autism include a lack of social interaction, repetitive pattern behaviors, language difficulties, and other behavioral issues (Alimanova, et al 2020). This population is most affected when receiving medical treatment due to communication barriers associated with autism. Nursing visit length may lengthen from needing to take time to ensure needs are met and assessment is conducted through various modes of communication.
Challenges
Diagnosing autism is cumbersome and complicated. The Sally Anne test is used to diagnose autism when suspected (Alimanova, et al 2020). Because autism is displayed through behavior, observing behaviors are what often prompts parents, healthcare providers, and or teachers to the suspicion of autism. Moreover, the biggest challenge of autism is the process of diagnosis. It can take years to finally diagnose one with autism.
Addressing issue
Addressing the issue of communication for children with autism is a huge task, but a necessary one. Collecting information by creating a survey to verify different techniques allows different inputs and may create other modes of communication to develop.
Data collection
Data collection is important during the process of research. It allows a conclusion to be drawn between the efficacy of the research being conducted (Gray & Grove, 2020). Using Snap, the electronic medical record is the method I will use to collect the data necessary to verify time spent with students with autism during nursing visits. During each visit, I will enter the student’s name as a start on the note. I will complete notes while the student is still in the office providing an accurate time stamp.
Conclusion
Providing effective communication options for students with autism during nursing visits cuts visit time significantly. Furthermore, allowing staff to share ideas on different communication strategy allow better communication strategies for autistic students with different communication need. Data collection will show time stamps on nursing visits. Datta can be compared to previous visits and allow changes to take place for efficacy
Reference
Alimanova, M., Soltiyeva, A., Urmanov. M., Adikhan, S. ( 2020). Developing an
Immersive Virtual Reality Training System to Enrich Social Interaction and
Communication Skills for Children With Autism Spectrum Disorder. 1-5
Bruce, N., Pope, D., & Stanistreet, D. (2018). Quantitative methods for health research :Links to an external site.
Links to an external site.Links to an external site. A practical interactive guide to epidemiology and
statistics (2nd ed.). Wiley.
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence(9th ed.). Elsevier.
Sample Answer for NURS 8201 Week 3 Sampling
Researchable Populations
As a Nurse Practitioner, I have a wide variety of researchable populations that may be present. First, I could focus my research on vulnerable populations as they are at increased risk for healthcare inequities. The healthcare inequities that they experience are due to factors such as racial, gender, cultural, and/or economic characteristics. Next, I could focus my research to cover more specialized populations such as neonatal, pediatric acute and/or primary care, psychiatric, women’s health, or family/across the lifespan. (Bekemeier et al., 2021). Lastly, I could choose my researchable population based on demographics and statistics such as age, ethnicity, gender, and geographical distribution.
Most Appropriate Researchable Population
I chose to specify my research based on age and gender, so my researchable population will reflect the male adolescent age group. More specifically, I chose to research the relationship between obesity in adolescents and the risk of type 2 diabetes. Type 2 diabetes has been increasingly diagnosed at younger ages and is a public health concern as it is associated with increased risk of morbidity, hospitalization, and mortality. Addressing adolescent obesity is crucial to mitigate the risk of early-onset type 2 diabetes. Severe obesity significantly increases the risk for incidence of type 2 diabetes (Twig et al., 2020). Identifying the relationship between obesity and type 2 diabetes in the adolescent stage allows us the opportunity to implement interventions during that can impact future health outcomes. Severe obesity is likely to increase in adolescents in the upcoming years, thus, increasing diabetes incidence in young adults.
Challenges in Obtaining Sample
There is potential for several challenges to arise in obtaining a sample from the male adolescent population. First, given the age of the population, parental or legal guardian consent will be required as minors cannot provide consent for themselves. Data collection becomes complicated due to both parent and child needing to be contacted (Lenhart, 2020). Next, there are potential complications in obtaining an accurate and comprehensive sampling frame. For example, my research is aimed to study adolescents so I would need to get a list of all schools in the area to obtain my sample from. Also, technological advancements would require me to adapt my survey method using a QR code which increases the cost of my research. The necessity for two interviews of both parent and adolescent increases the complexity and cost. Lastly, the most important potential complication is ensuring that I have an all-inclusive representative sample to include all socio-economic backgrounds.
Addressing Challenges in Obtaining Sample
First, I would address the challenge of parental consent by ensuring that I explain the purpose of the study in full transparency. Reminders and personalization communication has been shown to encourage participation (Lenhart, 2020). Next, I will address the challenge of obtaining an accurate sample frame by selecting groups as sample clusters if the list proves to be inadequate. The most challenging potential issue to address is the effort and cost that it will take to interview both the parent and adolescent. The only advice that I have for myself is to set time aside for both interviews and to plan accordingly. Lastly, technological advancements may involve increased costs for things such as a QR code but can also speed up data collection and reduce costs.
Recommended Approach for Data Collection
I came to this decision after weighing the cost and time factors which include testing instruments, fees, consultations, travel, time to recruit participants, obtaining consent, and collecting data (Gray & Grove, 2020). My recommended approach would be obtaining a list of schools in the geographical area. After obtaining the lists, I would send out a consent form to all students to be signed by a parent or legal guardian. Of the students who returned a consent form, I would provide a QR code for the student to complete an online survey within 7 days of receiving the code that would include socio-economic background questions to ensure that my sample would be accurate. After the results are in, I would ensure the data was equally divided by socioeconomic backgrounds per school.
References
Bekemeier, B., Kuehnert, P., Zahner, S., Johnson, K., Kaneshiro, J., & Swider, S. (2021). A critical gap: Advanced practice nurses focused on the public’s health. Nursing Outlook, 69(5). https://doi.org/10.1016/j.outlook.2021.03.023
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
Lenhart, A. (2020). The challenges of conducting surveys of youth. Pew Research Center. https://www.pewresearch.org/short-reads/2013/06/21/the-challenges-of-conducting-surveys-on-youths/
Twig, G., Zucker, I., Afek, A., Cukierman-Yaffe, T., Bendor, C. D., Derazne, E., Lutski, M., Shohat, T., Mosenzon, O., Tzur, D., Pinhas-Hamiel, O., Tiosano, S., Raz, I., Gerstein, H. C., & Tirosh, A. (2020). Adolescent Obesity and Early-Onset Type 2 Diabetes. Diabetes Care, 43(7). https://doi.org/10.2337/dc19-1988