Essay Example on Freshly Graduated Fairfax Nurses: Examining Sampling Approach

Introduction

The target population for the research is nurses, specifically the ones who have just graduated. The sample population will be all Fairfax nurses who are freshly graduated and employed in the year 2019 and 2018. This group will help bring a final report for all nurses.

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Sampling Approach

Cluster sampling will be used in the research. Nurses will be grouped by gender, both female and male, and the random sample will be used in each group. The main advantage of using this sampling method is that every subgroup of the sample size is presented (Etikan, & Bala, 2017). Additionally, the process is more feasible and does not require many resources. Even though the technique has disadvantages, which include the likeliness of being biased and can result in more sampling errors, it is an effective method in this study. This is because the sample size proposition is finite, and there are only two classifications of the population. Therefore, the sampling method is more convenient in this case.

Inclusion and Exclusion Criteria

There are various inclusion and exclusion criteria in this study. One of the factors of consideration is the qualification of the people. One needs to be a nurse. Hence, the study will exclude people who are not nurses. Additionally, one should be employed within the period specified by the research. The research stipulates that nurses used in the study should be the ones employed in 2018 and 2019. Those employed in the year 2017 are not included in the study since they are considered to be part of the experienced groups. Finally, one should be new employees in Fairfax hospital; the population from this group will represent the entire population.

Factors of Consideration in Sample Size Determination

The critical factor in determining the sample size is the level of accuracy needed (Hopkins, 2017). The research is focused on optimum efficiency, hence, it is aimed at using the largest sample size possible. Other factors of consideration include the population size; if the population is too large, then a large sample size is necessary. Additionally, in case it is too small, the entire community could be used as the sample population. Finally, on needs to be logical in sample selection, the researcher should choose the manageable sample size. To appropriately develop a broad conclusion, at least 100 nurses will be selected as the sample size 50 from 2018 employees and 50 from 2019.

Potential Threat

The study involves interview and questioner administration; such research requires utmost privacy between the interviewer and the people being interviewed. This will be done to ensure the rights of human participants have been protected. The potential internal threat is the failure of the nurses to give accurate information during the study. This could skew the data resulting in spurious results. Other factors include the inability of participants to show up for the study. People have the right not to turn up for any research, and researchers have to accept their choices. External challenges include the hospitals' management; they may not allow researchers to do the study. Finally, the COVID 19 pandemic that makes Nurses too busy to be involved in the research; this will require research to be done after the virus pandemic is over.

Cosmic Question

The primary research purpose is to determine the impact of continuous training to Nurses in dealing with nurses and comparing the Nurses employed in 2018 and the 2019 employees. Therefore the cosmic question is considering whether training help in preparing the Nurses to deal with emergency cases? If so, how do they influence the 2019 graduates who are newly employed as compared to the one used in 2018? By answering this, a valid conclusion will be established.

References

Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 00149.

Hopkins, W. G. (2017). Estimating Sample Size for Magnitude-Based Inferences. Sportscience, 21.