35
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Predictors of nursing workers’ intention to leave the work unit, health institution and profession *

      Revista Latino-Americana de Enfermagem
      Escola de Enfermagem de Ribeirão Preto / Universidade de São Paulo
      intention, employment, occupations, nursing, nurses, workplace violence, intenção, emprego, ocupações, enfermagem, enfermeiras e enfermeiros, violência no trabalho, intención, empleo, ocupaciones, enfermería, enfermeros, violencia laboral

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective: to identify the factors related to the nursing workers’ intention to leave the work unit, health institution and profession. Method: cross-sectional study with quantitative approach was carried out with 267 nursing workers from seven emergency units in Brazil. For data collection, we used the Questionnaire of socio-demographic, life style and work and health aspects as well as the Work Ability Index, Workplace violence questionnaire, questions about intention to leave and the Turnover Intention Scale. The predictors of intentions to leave were evaluated through Poisson regression models. Results: workplace violence increased and better satisfaction with current job decreased the probability of greater intention to leave the unit, institution and profession. Better work ability decreased the probability of greater intention to leave the unit and profession. The more qualified workers and those who had been working in the institution longer was more likely to greater intention to leave the profession. Conclusion: promoting job satisfaction, work ability and a violence-free environment is possible to decrease the workers’ intention to leave the job or profession, but nursing managers need to understand the three phenomena of intention to quit individually for retention strategies.

          Related collections

          Most cited references54

          • Record: found
          • Abstract: found
          • Article: not found

          Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

          Background Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio. Methods We compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated. Results Three outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified. Conclusions Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Post-operative mortality, missed care and nurse staffing in nine countries: A cross-sectional study

            Background Variation in post-operative mortality rates has been associated with differences in registered nurse staffing levels. When nurse staffing levels are lower there is also a higher incidence of necessary but missed nursing care. Missed nursing care may be a significant predictor of patient mortality following surgery. Aim Examine if missed nursing care mediates the observed association between nurse staffing levels and mortality. Method Data from the RN4CAST study (2009–2011) combined routinely collected data on 422,730 surgical patients from 300 general acute hospitals in 9 countries, with survey data from 26,516 registered nurses, to examine associations between nurses’ staffing, missed care and 30-day in-patient mortality. Staffing and missed care measures were derived from the nurse survey. A generalized estimation approach was used to examine the relationship between first staffing, and then missed care, on mortality. Bayesian methods were used to test for mediation. Results Nurse staffing and missed nursing care were significantly associated with 30-day case-mix adjusted mortality. An increase in a nurse’s workload by one patient and a 10% increase in the percent of missed nursing care were associated with a 7% (OR 1.068, 95% CI 1.031–1.106) and 16% (OR 1.159 95% CI 1.039–1.294) increase in the odds of a patient dying within 30 days of admission respectively. Mediation analysis shows an association between nurse staffing and missed care and a subsequent association between missed care and mortality. Conclusion Missed nursing care, which is highly related to nurse staffing, is associated with increased odds of patients dying in hospital following common surgical procedures. The analyses support the hypothesis that missed nursing care mediates the relationship between registered nurse staffing and risk of patient mortality. Measuring missed care may provide an ‘early warning’ indicator of higher risk for poor patient outcomes.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Effects of nurse work environment on job dissatisfaction, burnout, intention to leave.

              The nursing shortage is a critical issue in many countries. High turnover rates among nurses is contributing to the shortage, and job dissatisfaction, intention to leave, and burnout have been identified as some of the predictors of nurse turnover. A well-established body of evidence demonstrates that the work environment for nurses influences nurse job dissatisfaction, intention to leave, and burnout, but there never has been a study undertaken in Thailand to investigate this relationship.
                Bookmark

                Author and article information

                Journal
                31826161
                6896814
                10.1590/1518-8345.3280.3219
                https://creativecommons.org/licenses/by/4.0/

                intention,employment,occupations,nursing,nurses,workplace violence,intenção,emprego,ocupações,enfermagem,enfermeiras e enfermeiros,violência no trabalho,intención,empleo,ocupaciones,enfermería,enfermeros,violencia laboral

                Comments

                Comment on this article