Developing a prediction model of career plateau for nurses: A cross‐sectional study

• Published in: Nursing open 2023-12, Vol.10 (12), p.7631-7638
• Main Authors: Zhu, Hongmei, Li, Mingzi
• Format: Article
• Language: English
• Subjects: career mobility; Careers; Cronbach's alpha; Emergency communications systems; Employee turnover; Job satisfaction; Likert scale; Maternity & paternity leaves; Nurses; Nursing; organizational culture; prediction; Questionnaires; Research Methodology: Discussion Paper ‐ Methodology; Social exchange theory; Sociodemographics
• ISSN: 2054-1058; 2054-1058
• DOI: 10.1002/nop2.2002

AimThe study aimed to understand the current situation regarding career plateaus experienced by nurses. The objectives were to analyze factors influencing career plateau, and develop a prediction model for career plateau for nurses.DesignA cross-sectional survey was conducted using convenience sampling.MethodsParticipants were 2680 nurses from six tertiary hospitals. Univariable and multivariable logistic regression analyses were carried out to investigate the influencing factors and develop a prediction model of career plateau.ResultsThe overall incidence rate of nurses reaching a career plateau was 34%. Logistic regression analysis showed that age, position, whether specialized nurses, life satisfaction, organizational support, personal ability and selection tendency were the factors influencing career plateau. The prediction model indicates that older nurses are more likely to reach a career plateau than their younger counterparts, and those who think they have strong personal ability and do not value their work very much are more likely to have a career plateau. Giving nurses more promotion space and learning opportunities, improving life satisfaction, and organizational support are conducive to reducing the occurrence of career plateau.