NURS 8201 Week 3 Sampling Reference

NURS 8201 Week 3 Sampling Reference

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.