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      Job Quality and Job Separation of Direct Care Workers in England

      research-article
      , PhD , , PhD
      , PhD, FGSA
      Innovation in Aging
      Oxford University Press
      Long-term care, Panel data, Staff turnover, Workforce

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          Abstract

          Background and Objectives

          Most job leavers in the long-term care (LTC) sector in England do not leave the sector, but rather move to other LTC employers. Nevertheless, the high “churn” can have a negative impact on continuity and quality of care, care providers’ recruitment and training costs, and the remaining staff workload and motivation. This study aimed to provide quantitative evidence on the drivers of direct care workers’ job separation in England, with a focus on job quality.

          Research Design and Methods

          We used yearly data (2016–19) from the Adult Social Care Workforce Data Set, the leading source of LTC workforce data in England, including information on both LTC workers and employers. The analysis considered panel data econometric methods that accounted for unobserved heterogeneity at worker and employer levels.

          Results

          After controlling for observed individual, organizational, and local market characteristics as well as unobserved worker and employer heterogeneity, we found that everything else being equal, wages and employment conditions (i.e., full-time contracts and contracts with guaranteed working hours) significantly reduce job separation. For example, a 10% wage increase from the sample mean would reduce the job separation rate by about 3 percentage points. This wage effect was more than halved (i.e., downward biased) when not accounting for unobserved effects.

          Discussion and Implications

          The persistent high staff turnover in LTC in England highlights the need for finding practical solutions faced by care providers and policy-makers. Our findings showed that improving pay and employment conditions can be the way forward while methodologically stressing the importance of accounting for unobserved variable bias.

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          Most cited references41

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          Nursing Home Staff Turnover and Retention: An Analysis of National Level Data

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            Job satisfaction of nurse aides in nursing homes: intent to leave and turnover.

            The relationship between job satisfaction of nurse aides and intent to leave and actual turnover after 1 year is examined. Data came from a random sample of 72 nursing homes from 5 states (Colorado, Florida, Michigan, New York, and Oregon). From these nursing homes, we collected 1,779 surveys from nurse aides (a response rate of 62%). We used a job satisfaction instrument specifically developed for use with nurse aides, as well as previously validated measures of intent to leave and turnover. We used ordered logistic regression and logistic regression to examine the data. High overall job satisfaction was associated with low scores on thinking about leaving, thinking about a job search, searching for a job, and turnover. In examining the association between the job satisfaction subscales and intent to leave and turnover, we found that high Work Schedule subscale scores, high Training subscale scores, and high Rewards subscale scores were associated with low scores on thinking about leaving, thinking about a job search, searching for a job, and turnover. High scores on the Quality of Care subscale were associated with low turnover after 1 year. These results are important in clearly showing the relationship between job satisfaction and intent to leave and turnover of nurse aides. Training, rewards, and workload are particularly important aspects of nurse aides' jobs.
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              Organizational characteristics associated with staff turnover in nursing homes.

              The association between certified nurse aide, licensed practical nurse, and registered nurse turnover and the organizational characteristics of nursing homes are examined. Hypotheses for eight organizational characteristics are examined (staffing levels, top management turnover, resident case mix, facility quality, ownership, chain membership, size, and Medicaid census), using Online Survey, Certification, and Reporting (known as OSCAR) data. Turnover information came from primary data collected from 854 facilities in six states (Missouri, Texas, Connecticut, New York, Pennsylvania, and New Jersey). The 1-year turnover rates were 56.4%, 39.7%, and 35.8% for certified nurse aides, licensed practical nurses, and registered nurses, respectively. The results consistently show that, for all caregivers, lower staffing levels, lower quality, for-profit ownership, and higher bed size are associated with higher turnover. Some differences also are found for different levels of turnover, but there are few differences among types of nursing staff. Given that turnover rates are problematic, this study gives us a better understanding of the phenomenon and at the same time helps us further understand the wide variation that is known to exist between nursing homes, based on their organizational characteristics.
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                Author and article information

                Contributors
                Role: Decision Editor
                Journal
                Innov Aging
                Innov Aging
                innovateage
                Innovation in Aging
                Oxford University Press (US )
                2399-5300
                2023
                31 January 2023
                31 January 2023
                : 7
                : 2
                : igad009
                Affiliations
                Personal Social Services Research Unit (PSSRU), University of Kent , Canterbury, UK
                Global Labor Organization (GLO) , Essen, Germany
                Department of Applied Health Research, University College London , London, UK
                National Institute for Health and Care Research (NIHR) Applied Research Collaboration North Thames , London, UK
                Author notes
                Address correspondence to: Florin Vadean, PhD, Personal Social Services Research Unit, University of Kent, Cornwallis Central, Canterbury CT2 7NF, UK. E-mail: f.vadean@ 123456kent.ac.uk
                Author information
                https://orcid.org/0000-0001-7882-3400
                https://orcid.org/0000-0002-5867-2702
                Article
                igad009
                10.1093/geroni/igad009
                10024478
                36941889
                a9506a27-fd58-4424-8937-e89635e0b8fd
                © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 September 2022
                : 09 January 2023
                : 18 March 2023
                Page count
                Pages: 10
                Funding
                Funded by: Health Foundation’s Efficiency Research Programme;
                Award ID: 1325587
                Categories
                Original Research Article
                AcademicSubjects/SOC02600
                Jel/C23
                Jel/J31
                Jel/J63
                Jel/J81

                long-term care,panel data,staff turnover,workforce
                long-term care, panel data, staff turnover, workforce

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