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      The influencing factors of newly employed nurses’ adaptation in Malaysia: a structural equation modelling assessment

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          Abstract

          Background

          Graduate nurses commonly experience the transition phase and are required to adapt quickly to their new workplace, as it is a prerequisite for a successful transition. However, workplace adaptation is extremely challenging and may affect nurses’ future career prospects if not managed properly. Therefore, we aimed to determine the factors that facilitate newly employed nurses’ adaptation and integration at Ministry of Health (MOH)-run state hospitals in Malaysia. The study framework was derived and adapted from the Roy adaptation model and organisational socialisation theories.

          Methods

          This quantitative study was conducted from May 2021 to December 2021. The sample population was newly employed nurses working at state hospitals with 1–2 years of service experience. This study involved 496 newly hired nurses from MOH state hospitals. Questionnaires were distributed through Google Forms. The data were analysed using covariance-based structural equation modelling.

          Results

          The participants perceived that workplace organisation (OC), academic institution contribution (AIC), and new nurse’s personality traits (PT) contributed approximately 36% to newly employed nurses’ adaptation (NENA). PT partially mediated the relationship between OC and NENA and between AIC and NENA.

          Conclusions

          The results could be useful to nursing authorities. We also recommend that a nurse’s personality be developed, emphasised, and enhanced through continuous programmes or training to ensure that they can easily adapt to their new working environment. Furthermore, academic institution and work organisation collaboration should be encouraged to develop improvement cycles that facilitate newly employed nurses’ prompt and efficient adaptation at MOH hospitals during transition.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12912-024-02543-2.

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          Most cited references86

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          Society and the Adolescent Self-Image

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            Practical Issues in Structural Modeling

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              Predictors of actual turnover in a national sample of newly licensed registered nurses employed in hospitals.

              This paper is a report of a study of factors that affect turnover of newly licensed registered nurses in United States hospitals. There is a large body of research related to nursing retention; however, there is little information specific to newly licensed registered nurse turnover. Incidence rates of turnover among new nurses are unknown because most turnover data are not from nationally representative samples of nurses. This study used a longitudinal panel design to obtain data from 1653 registered nurses who were recently licensed by examination for the first time. We mailed surveys to a nationally representative sample of hospital registered nurses 1 year apart. The analytic sample consisted of 1653 nurses who responded to both survey mailings in January of 2006 and 2007. Full-time employment and more sprains and strains (including back injuries) result in more turnover. Higher intent to stay and hours of voluntary overtime and more than one job for pay reduces turnover. When we omitted intent to stay from the probit model, less job satisfaction and organizational commitment led to more turnover, confirming their importance to turnover. Magnet Recognition Award(®) hospitals and several other work attributes had no effect on turnover.   Turnover problems are complex, which means that there is no one solution to decreasing turnover. Multiple points of intervention exist. One specific approach that may improve turnover rates is hospital policies that reduce strains and sprains. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                aniza@hctm.ukm.edu.my
                Journal
                BMC Nurs
                BMC Nurs
                BMC Nursing
                BioMed Central (London )
                1472-6955
                3 December 2024
                3 December 2024
                2024
                : 23
                : 879
                Affiliations
                [1 ]Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, ( https://ror.org/00bw8d226) Kuala Lumpur, 56000 Malaysia
                [2 ]Faculty of Business and Management, Universiti Sultan Zainal Abidin, ( https://ror.org/00bnk2e50) Terengganu, 21300 Malaysia
                [3 ]School of Nursing and Midwifery, La Trobe University, ( https://ror.org/01rxfrp27) Bundoora, VIC 3086 Australia
                [4 ]Department of Nursing, Faculty of Medicine, Universiti Kebangsaan Malaysia, ( https://ror.org/00bw8d226) Kuala Lumpur, 56000 Malaysia
                [5 ]GRID grid.415759.b, ISNI 0000 0001 0690 5255, Pharmacy Policy & Strategic Planning Division, Pharmaceutical Services Programme, , Ministry of Health Malaysia, ; Petaling Jaya, Selangor 46200 Malaysia
                Article
                2543
                10.1186/s12912-024-02543-2
                11613506
                39627761
                9beb5e58-0220-45d2-baa6-02d2e3e67859
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 14 December 2023
                : 21 November 2024
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Nursing
                adaptation,organisation,academic,personality,structural equation modelling
                Nursing
                adaptation, organisation, academic, personality, structural equation modelling

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