![]() ![]() During such analysis, we try to stamp out these biases by taking notes of the individuals’ backgrounds and putting ourselves in their shoes, to the extent possible. First, the qualitative analysis that we have conducted builds on comparing and contrasting the categories and themes that emerged during the analysis. In order to mitigate the potential biases, we implemented two strategies. We, therefore, decided to implement the snowball driven sampling methodology. Furthermore, the nature of the interview and the sensitivity of the content of the discussions about intentions to quit their job or problems with their workplace leads the potential participants to be very reluctant to enrol in the study. 40 In our case, it was very difficult to determine the size and boundaries of the population of nursing home staff, especially given the fact that the nursing homes’ staff so frequently quit their jobs. Despite such potential biases, the snowball sampling is an appropriate sampling methodology in cases where a representative sample is impossible to be obtained either because no sampling frame exists, or the individuals have significant privacy concerns and do not want to be sampled easily. In our case, the staff that were selected in our sample may be more connected to other staff members or be more extrovert and willing to share their experiences with others. As a result, the participating individuals may be systematically different from others. Snowball sampling leads to biased samples that may not be representative of the population of interest as we did not strive to randomly select individuals to be included in our study. Study population and final sample of study participants. This research intended to bridge the aforementioned gaps and reveal the key challenges and areas for intervention through a series of semistructured interviews with the staff who worked at the long-term care facilities in the USA during the COVID-19 pandemic. Given the unforeseen challenges created by the pandemic and how significantly it changed the work circumstances in the nursing homes, it is imperative to study the experiences of nursing homes’ staff in the midst of the pandemic and re-examine our understanding of the turnover factors during this unique period. 36 As Bern-Klug and Beaulieu 37 put it, the pandemic ‘forced a new psychosocial playbook in nursing homes across the country as fears run high, emotions run hot, and distress runs rampant’. 35 These facilities were further devastated with severe shortages in staffing and personal protection equipment. They are also narrow in scope and methodology as they focus on a limited set of factors, solely using quantitative approaches.īy the end of January 2022, more than 145 000 deaths had occurred in the US nursing homes and other long-term care facilities, accounting for nearly 17% of all COVID-19-related fatalities nationwide. While prior work is critically important in the struggle to understand and interdict staff turnover, their conclusions are mostly limited by correlational analysis of dated data. 34 On the other hand, larger and for-profit facilities tend to have higher rates of staff turnover. 15 27 28 Staff who are empowered, 15 29 more involved 16 30 31 and receive better support from management 16 32 are also shown to be less likely to leave their jobs.įacilities that have established a reward-based administrative climate, 33 implemented higher levels of communication openness 17 33 and assigned retention specialists also experience lower turnover. Stability of leadership team has been found to be directly correlated with the turnover of staff at lower ranks. Better wages and benefits, 15–19 higher levels of staffing, 15 17 18 20–22 fewer job responsibilities, 23 lower stress 16 and higher job satisfaction have all been shown to reduce staff turnover. Given the important implications of staff turnover, researchers have made significant attempts to understand its underlying reasons and devise solutions to decrease it. 6 7 Prior investigations have shown that high rate of staff turnover is associated with an array of negative quality outcomes, including higher rates of infections and lower scores in patient safety culture. ![]() 5 Staffing level is an important dimension for evaluating the overall quality of nursing homes. ![]() 1 This has been a persistent challenge for nursing homes, 2–4 and is possibly exacerbated by the complexities and stressful circumstances created by the COVID-19 pandemic. The rate of staff turnover at long-term care facilities in the USA is staggering. ![]()
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