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

Bordignon, Maiara; Monteiro, Maria Inês

doi:10.1590/1518-8345.3280.3219

Cited by 35 publications

(57 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Outras estratégias são os programas de resiliência, que visam lidar com os impactos dos estressores no local de trabalho. Além disso, as barreiras organizacionais e os riscos para o bem-estar da equipe também precisam ser abordados para criar uma força resiliente 34 , particularmente, por compreender que uma melhor capacidade para o trabalho reduz a chance do trabalhador de enfermagem de deixar a profissão, como demonstrado em um estudo: para cada ponto no ICT há uma redução de 5% na intenção de abandonar a profissão 35 .…”

Section: Resultsunclassified

Resiliência e capacidade para o trabalho em trabalhadores de enfermagem [Resilience and work ability in nursing workers] [Resiliencia y capacidad laboral en trabajadores de enfermería]

Silva

Baptista

et al. 2019

Rev. enferm. UERJ

View full text Add to dashboard Cite

Objetivo: verificar a associação da resiliência com a capacidade para o trabalho em trabalhadores de enfermagem. Método: estudo transversal realizado com 375 trabalhadores de enfermagem de um hospital universitário, na cidade de São Paulo, Brasil, por meio de três instrumentos autoaplicáveis: um para caracterização sociodemográfica e profissional, a Escala de Resiliência e o Índice de Capacidade para o Trabalho. Os dados foram analisados por meio de regressão linear múltipla. O projeto foi aprovado por Comitê de Ética em Pesquisa da instituição. Resultados: Entre os trabalhadores participantes, 15,2% apresentaram baixa resiliência e 30,4% mostraram capacidade para o trabalho comprometida. Quanto maior o escore do Índice de Capacidade para o Trabalho, maior a pontuação da Escala de Resiliência (b=0,722; p<0,001). Conclusão: a resiliência foi associada de forma positiva à capacidade para o trabalho.ABSTRACTObjective: to verify the association of resilience with work ability in nursing workers. Method: cross-sectional study carried out with 375 nursing workers from a university hospital in the city of São Paulo, Brazil, using three self-applicable instruments: one for sociodemographic and professional characterization, the Resilience Scale and the Work Ability Index. Data were analyzed using multiple linear regression analysis. The research project was approved by the Institution’s Research Ethics Committee. Results: Among participants workers, 15.2% showed low resilience and 30.4% have some level of impaired work ability. The higher the Work Ability Index score, the higher the Resilience Scale score (b=0.722; p<0.001). Conclusion: resilience was positively associated with the work ability.RESUMENObjetivo: verificar la asociación de resiliencia con capacidad laboral en trabajadores de enfermería. Método: estudio transversal realizado con 375 trabajadores de enfermería de un hospital universitario en la ciudad de São Paulo, Brasil, utilizando tres instrumentos auto-aplicables: uno para caracterización sociodemográfica y profesional, la Escala de Resiliencia y el Índice de Capacidad Laboral. Los datos se analizaron mediante análisis de regresión lineal múltiple. El proyecto de investigación fue aprobado por el Comité de Ética de Investigación de la Institución. Resultados: Entre los trabajadores participantes, el 15.2% mostró baja capacidad de recuperación y el 30.4% tiene algún nivel de capacidad laboral deteriorada. Cuanto más alto sea el puntaje del Índice de Habilidad de Trabajo, más alto será el puntaje de la Escala de Resiliencia ( = 0.722; p <0.001). Conclusión: la resiliencia se asoció positivamente con la capacidad de trabajo.

show abstract

Section: Resultsunclassified

Resiliência e capacidade para o trabalho em trabalhadores de enfermagem [Resilience and work ability in nursing workers] [Resiliencia y capacidad laboral en trabajadores de enfermería]

Silva

Baptista

et al. 2019

Rev. enferm. UERJ

View full text Add to dashboard Cite

show abstract

“…In October 2018, we delivered 300 copies each to six medical centers in Taiwan, inviting novice nurses(i.e., nurse hierarchy at N0 and N1 only) to complete the 100-item questionnaires (Figure 1 and Additional File1) related to NIQJ [10][11][12][13]. A total of 1,104 nurses participated, with a return rate of 61.3% (Additional File2).…”

Section: Study Sample and Demographic Datamentioning

confidence: 99%

“…True positive (TP)=the number of predicted NIQJ to the true NIQJ, 1True negative (TN)= the number of predicted Non-NIQJ to the true Non-NIQJ, 2False-positive (FP)= the number of Non-NIQJ minuses TN, 3False-negative (FN)= the number of NIQJ minuses TP, (4) Sensitivity = true positive rate (TPR)=TP(TP+FN), (5) Speci city= true negative rate (TNR)=TN(TN+FP), (6) Precision= positive predictive value (PPV)=TP(TP+FP), 7F1 score=2 (8) ACC= accuracy=(TP+TN) N, (9) N=TP+TN+FP+FN, (10) AUC=(1-Speci city)SensitivitySpeci city, (11) SE for AUC==, (12) 95%CI=AUC ± 1.96, (13) The stability was determined by observing the AUC changes in both training and testing sets. The fewer AUC changes in a prediction model imply better stability.…”

Section: Tasks For Performing Ann and Cnn Task 1: Comparison Of Accurmentioning

confidence: 99%

An App Developed for Predicting Nurse Intention to Quit the Job (NIQJ) Using the Artificial Neural Networks(ANN) in Microsoft Excel: Population-Based Questionnaire Study

Jen

Chien

Yeh

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Studies in the past have identified factors related to the nursing staff’s intention to leave the unit, institution, and profession. However, none has successfully predicted the nurse's intention to quit the job (NIQJ). Whether NIQJ can be predicted be predicted is an interesting topic in healthcare management. A model to predict the NIQJ for novice nurses in hospitals should be investigated and developed in this mobile computer age. Objective: The aim of this study is to build a model to develop an app for automatic prediction and classification of NIQJ using a smaller number of items to help assess NIQJ and take necessary actions before nurses quit the job.Methods: We recruited 1104 novice nurses working in six medical centers in Taiwan to complete 100-item questionnaires related to NIQJ in October 2018. The k-mean was used to divide nurses into two classes (i.e., NIQJ and Non- NIQJ) based on five- NIQJ items regarding leave intention. Feature variables were chosen from 100 relevant items. Two models, including artificial neural network (ANN) and convolutional neural network (CNN), were compared across four scenarios made up by two training sets (n=1104 and n=804B) and their corresponding testing (n=300a) sets to verify the model accuracy (e.g., sensitivity, specificity, area under the receiver operating characteristic curve, AUC) and stability and generalization (e.g., using the training set to predict the testing set). An app predicting NIQJ was then developed involving the model's estimated parameters as a website assessment.Results: We observed that (1) 24 feature variables extracted from this study in ANN model yielded a higher AUC of 0.82 (95% CI 0.80-0.84) based on the total 1104 cases, (2) the ANN performed better than CNN on both accuracy, stability and generalization, and (3) an ready and available app for predicting NIQJ was successfully developed in this study.Conclusions: The 24-item ANN model with the 53 parameters estimated by the ANN for improving the accuracy of NIQJ has been developed with the use of Excel (Microsoft Corp). The app would help team leader and HR department to pick up nurse’s NIQJ before actions are taken, allowing them to make plans accordingly.

show abstract

“…Worldwide, there is a deficit of nursing employees [ 1 ]. As highly trained and experienced registered practical staff are key personnel in any health care establishment, a sufficient number of these staff is critical to providing patient-centered health services [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring factors influencing the retention of nurses in a religious hospital in Taiwan: a cross-sectional quantitative study

Chiao

Tzeng

et al. 2021

BMC Nurs

View full text Add to dashboard Cite

Background Long-term deficits in the nursing labor force and high turnover rates are common in the Taiwanese medical industry. Little research has investigated the psychological factors associated with the retention of nursing staff. However, in practice, religious hospitals often provide nursing staff with education in medicine or the medical humanities to enhance their psychological satisfaction. The objective of this study was to explore factors influencing nursing staff retention in their work in relation to different levels of needs. A further objective was to investigate whether medical humanities education was associated with the retention of nursing staff. Methods This study used self-administrated questionnaires to survey nurses working in northern areas of Taiwan. The questionnaire design was based on the six levels of Maslow’s hierarchy of needs. Participation was voluntary, and the participants signed informed consent documents. Self-administrated questionnaires were distributed to a total of 759 participants, and 729 questionnaires were returned (response rate 96.04%). Logistic regression analysis was used to estimate the impact of seniority on nurses’ reported intention to stay after adjustment for nurse characteristics (gender and age). Results In the Pearson correlation analysis, nurses’ willingness to stay was moderately correlated with “physical needs”, “safety needs”, “love and belonging needs”, and “esteem needs” (r = 0.559, P < 0.001; r = 0.533, P < 0.001; r = 0.393, P < 0.001; and r = 0.476, P < 0.001, respectively). Furthermore, nurses’ willingness to stay was highly correlated with “self-actualization needs”, “beyond self-actualization needs” and “medical humanities education-relevant needs” (r = 0.707, P < 0.001; r = 0.728, P < 0.001; and r = 0.678, P < 0.001, respectively). We found that the odds ratios (ORs) of retention of nursing staff with less than 1 year (OR = 4.511, P = 0.002) or 1–3 years (OR = 3.248, P = 0.003) of work experience were significantly higher than that of those with 5–10 years of work experience. Conclusions With regard to medical humanities education, we recommend adjusting training, as the compulsory activities included in the official programs are inadequate, and adjusting the number of required hours of medical humanities education. Tailoring different educational programs to different groups (especially nurses who have worked 3–5 years or 5–10 years in the case study hospital) might improve acceptance by nursing staff.

show abstract

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

Cited by 35 publications

References 43 publications

Resiliência e capacidade para o trabalho em trabalhadores de enfermagem [Resilience and work ability in nursing workers] [Resiliencia y capacidad laboral en trabajadores de enfermería]

Resiliência e capacidade para o trabalho em trabalhadores de enfermagem [Resilience and work ability in nursing workers] [Resiliencia y capacidad laboral en trabajadores de enfermería]

An App Developed for Predicting Nurse Intention to Quit the Job (NIQJ) Using the Artificial Neural Networks(ANN) in Microsoft Excel: Population-Based Questionnaire Study

Exploring factors influencing the retention of nurses in a religious hospital in Taiwan: a cross-sectional quantitative study

Contact Info

Product

Resources

About