You should respond to your peers by extending, refuting/correcting, or adding additional nuance to their posts.
References MUST be scholarly published in the LAST 5 years
Respond to this discussion posted by another classmate
Procedural Planning
This survey intends to examine the connections between recruitment efficiency, job satisfaction, burnout prevention, turnover reduction, and retention rates among nursing professionals in different medical facilities. The study assesses the impact of recruitment efficiency and job satisfaction on burnout prevention, turnover reduction, and improved retention rates (Xue et al., 2024). The survey will use a cross-sectional design to collect data from registered nurses and nurse managers in hospitals across Miami, Florida. A survey method is preferred in this context because it is cost-effective, allows for quick data collection, and is more feasible compared to alternative experimental designs that may pose challenges or ethical complications. I will collect data through an online survey, taking advantage of its effectiveness in reaching a wide and diverse audience. The survey will be designed in such a way as to assess various aspects of the nursing workforce, such as job satisfaction, burnout levels, turnover rates, and recruitment practices. In support of Henshall et al. (2020), this will provide a detailed understanding of the dynamics within the nursing profession. By utilizing a cross-sectional approach to analyze the factors that influence nursing workforce outcomes, I will capture an overview of the relationships between variables at a specific point in time, resulting in a detailed analysis.
The study’s target population includes nursing professionals working in various healthcare settings throughout Miami, Florida, namely hospitals, clinics, community centers, and nursing homes. One way to estimate the size of this population entails considering the number of registered nurses employed in these settings within Miami. I will easily reach out to this population through the utilization of existing lists and databases of registered nurses who are licensed to practice in Florida. To ensure representation across various healthcare settings in Miami, the population will be stratified based on different types of healthcare facilities (hospitals, clinics, community health centers, and nursing homes) due to the diverse nature of these centers (Kueakomoldej et al., 2022). Sampling will be done within each stratum using a multistage (cluster) sampling procedure. Clusters will be identified as healthcare centers, and registered nurses within these centers will be sampled. I will determine the sample size based on power analysis considerations, ensuring sufficient statistical power to detect significant relationships between variables. Factors such as the desired effect size, alpha (Type I error rate), and beta (Type II error measure). I intend to recruit enough participants from different types of healthcare facilities in Miami’s healthcare sector. I will also use systematic sampling within identified clusters to ensure representation and generalize findings across the nursing workforce.
I will adopt various data collection instruments. For example, the Job Satisfaction Survey (JSS) by Paul E. Spector will be utilized to measure job satisfaction among nursing professionals. This tool has 36 items and has consistently shown strong reliability (Cronbach’s alpha: .80 to .90) and validity in multiple studies. The JSS uses a Likert scale from “strongly disagree” to “strongly agree.” In assessing burnout levels, the Maslach Burnout Inventory (MBI) by Christina Maslach and Susan E. Jackson will be utilized. The MBI has 22 items with strong reliability (Cronbach’s alpha: .70 to .90) and validity in measuring emotional exhaustion, depersonalization, and personal accomplishment. Noteworthy, it uses a Likert scale to rate how often experiences occur. I will conduct a pilot test with a small group of nursing professionals to evaluate the clarity, comprehensibility, and length of the survey instruments. Their feedback will be used to make final revisions. To ensure efficient data collection, Al Sabei et al. (2020) assert that the survey will be conducted online, where participants will be sent an initial email invitation, followed by reminders at strategic intervals to increase response rates. After collecting data, responses will be scored according to the instruments’ guidelines. This will convert raw scores into variables that represent job satisfaction, burnout levels, recruitment efficiency, and turnover rates. The variables will be analyzed using statistical methods like correlation analysis and regression to test the research questions. As a result, it enables the evaluation of the relationships between recruitment efficiency, job satisfaction, burnout prevention, turnover reduction, and retention rates among nursing professionals (Bazinski et al., 2023). The survey will be conducted over eight weeks, following established protocols to ensure high response rates for mailed surveys.
During the data analysis phase of the survey study, I will take several steps to safeguard the thoroughness of the analysis and interpretation of the results. I will assess returns by reporting the number and percentage of respondents and nonrespondents in a tabulated format for a clear understanding of survey participation rates. I will also use wave analysis and respondent/nonrespondent checks to determine potential biases caused by nonresponses. Calculating means, standard deviations, and ranges for independent and dependent variables will be included, along with solving missing data challenges and imputation strategies if needed. Assessing the need for reverse-scoring and calculating total scale scores will enable the combining of survey items into scales. Internal consistency will be ensured through reliability checks using Cronbach’s alpha. I will choose statistical tests for inferential statistics based on the research questions, variables, and data distribution assumptions. Statistical software like IBM SPSS or SAS will be used to analyze data and answer research questions. Correlation, regression, and ANOVA will be used to assess the practical implications of the results. Reporting results will involve providing detailed descriptions, statistical significance (p-values), effect sizes, and confidence intervals, following APA guidelines. The findings will be discussed in relation to the existing literature, highlighting gaps in knowledge and their implications for practice and future research. I will not fail to also consider the study’s limitations and alternative explanations for the findings. My data analysis and interpretation method aims to provide valuable insights into nursing workforce dynamics and support evidence-based practice in healthcare.
References
Al Sabei, S. D., Labrague, L. J., Miner Ross, A., Karkada, S., Albashayreh, A., Al Masroori, F., & Al Hashmi, N. (2020). Nursing work environment, turnover intention, job burnout, and quality of care: The moderating role of job satisfaction. Journal of Nursing Scholarship, 52(1), 95–104. Portico. https://doi.org/10.1111/jnu.12528Links to an external site.
Bazinski, M. A., & Wilson, M. (2023). Challenges recruiting and retaining new members of a professional nursing organization. Pain Management Nursing, 24(5), 513-520. https://doi.org/10.1016/j.pmn.2023.06.007Links to an external site.
Henshall, C., Davey, Z., & Jackson, D. (2020). Nursing resilience interventions–A way forward in challenging healthcare territories. Journal of Clinical Nursing, 29(19-20), 3597. https://doi.org/10.1111/jocn.15276Links to an external site.
Kueakomoldej, S., Liu, J., Pittman, P., Turi, E., & Poghosyan, L. (2022). Practice environment and workforce outcomes of nurse practitioners in community health centers. The Journal of Ambulatory Care Management, 45(4), 289-298. https://doi.org/10.1097/jac.0000000000000427Links to an external site.
Xue, B., Feng, Y., Hu, Z., Chen, Y., Zhao, Y., Li, X., & Luo, H. (2024). Assessing the mediation pathways: How decent work affects turnover intention through job satisfaction and burnout in nursing. International Nursing Review.https://doi.org/10.1111/inr.12939Links to an external site.
