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

      Latent profile analysis of nurses’ perceived professional benefits in China: a cross-sectional study

      research-article

      Read this article at

      Bookmark
          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 profiles of nurses’ perceived professional benefits as well as their predictors.

          Design

          Cross-sectional study.

          Setting

          The study was carried out online in China.

          Methods

          From 6 July to 27 July 2022, a total of 1309 registered nurses participated in the survey by convenient sampling. We collected the Nurses’ Perceived Professional Benefits Questionnaire and demographic data. Using latent profile analysis (LPA), subgroups of nurses’ perceived professional benefits were identified. Moreover, univariate and multinomial logistic regression analyses were conducted to find the factors that were linked with the profiles.

          Results

          The survey was validly completed by 1309 nurses, with a 92.9% effective return rate. The findings of the LPA demonstrated three unique profiles: low-perceived professional benefits (11.8%), moderate-perceived professional benefits (57.1%) and high-perceived professional benefits (31.1%). There was a correlation between marital status, the number of night shifts per month and leadership role.

          Conclusions

          According to our research, registered nurses have three unique professional benefit profiles. In order to sustain the nursing workforce, despite the fact that nurses get a high level of professional benefits, interventions are necessary to increase nurses’ perception of their professional value.

          Related collections

          Most cited references36

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies.

          Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found
              Is Open Access

              Latent profile analysis: A review and “how to” guide of its application within vocational behavior research

                Bookmark

                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2023
                2 November 2023
                : 13
                : 11
                : e078051
                Affiliations
                [1 ]The Third Affiliated Hospital of Zunyi Medical University , Zunyi, Guizhou, China
                [2 ]Ringgold_66367Zunyi Medical University , Zunyi, Guizhou, China
                Author notes
                [Correspondence to ] Hu Jiang; jianghuchn@ 123456163.com
                Author information
                http://orcid.org/0000-0001-6301-0829
                http://orcid.org/0000-0003-4424-1749
                Article
                bmjopen-2023-078051
                10.1136/bmjopen-2023-078051
                10626806
                37918934
                60df2da9-e5e7-469b-9ad4-9479f9bc4018
                © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 22 July 2023
                : 18 October 2023
                Funding
                Funded by: the Science and Technology Joint Funds of Zunyi Science and Technology Bureau;
                Award ID: 2023-73
                Categories
                Occupational and Environmental Medicine
                1506
                1716
                Original research
                Custom metadata
                unlocked

                Medicine
                burnout, professional,burnout,china
                Medicine
                burnout, professional, burnout, china

                Comments

                Comment on this article