Conectar
To examine the relationships among perceived organisational support, perceived job security, self-efficacy and job engagement among newly recruited nurses and the mediating role of perceived job security and self-efficacy in the relationship between perceived organisational support and job engagement.
Cross-sectional study.
This study employed a multicentre cross-sectional survey design and used the Perceived Job Security Scale, General Self-Efficacy Scale, Perceived Organisational Support Scale and Job Engagement Scale to survey 536 newly recruited nurses (from September 2023 to April 2024). Structural equation modelling was used to test the effects of perceived organisational support, perceived job security and self-efficacy on job engagement.
In the study model, perceived organisational support, perceived job security and self-efficacy all directly affect job engagement among newly recruited nurses. Additionally, perceived organisational support can be used to predict job engagement through self-efficacy and perceived job security.
Perceived organisational support, job security and self-efficacy are positive predictors of job engagement among newly recruited nurses. Furthermore, perceived job security and self-efficacy mediate the relationship between perceived organisational support and job engagement.
Newly recruited nurses, as key agents in clinical nursing practice, play a crucial role in reducing nursing errors and improving work efficiency. The results of this study show that perceived organisational support, perceived job security and self-efficacy positively predict job engagement among newly recruited nurses. Clinical nursing managers and educators should assist newly recruited nurses in enhancing their perceived organisational support to foster job engagement by bolstering their perceived job security and self-efficacy.
This study adhered to the STROBE guidelines.
No patient or public contribution.
Stroke incidence has increased recently, causing functional impairments in most patients. Augmented reality(AR) is frequently employed as an interactive and repetitive technology to facilitate functional rehabilitation. Therefore, this study aimed to examine the current evidence in the effect of AR for stroke rehabilitation.
Systematic review with meta-analysis.
Seven electronic databases including PubMed, Medline, CINAHL, Web of Science, Scopus, Embase and Cochrane were searched by MeSH terms and keywords such as ‘Stroke’ ‘Augmented reality’ up to December 1, 2024.
The Cochrane Risk of Bias tool was used to evaluate potential bias. Meta-analysis and Trial Sequence Analysis were used to analyse by the datastata15.0 software and TSA v0.9 software.
We searched 11 studies in a systematic review and 8 in a meta-analysis. The AR training group exhibited a significantly superior Berg Balance Scale scores(BBS) to those of the traditional training group. The Z-value curve of the sixth study crossed the traditional and TSA boundary values. Subgroup analysis revealed that BBS was significantly influenced in the hospital compared to the home intervention. The Timed Up and Go Test scores(TUG) and the 10-Meter Walk Test scores(10MWT) were similar in the AR and traditional training groups.
AR technology is beneficial for the lower limb balance functional rehabilitation of stroke patients. However, further exploration and verification are necessary due to an insufficient number of trials.
The findings provide clinical references for implementing AR in rehabilitation interventions for stroke patients.
This paper is helpful for nurses in the rehabilitation training process of stroke patients, to make personalised plans for their rehabilitation, implement rehabilitation, provide health education and address other aspects of efforts, to provide patients with comprehensive support and help, to promote the functional recovery of patients and improve the quality of life.
PRISMA guidelines.
PROSPERO number: CRD42024533761.
MJEditor (www.mjeditor.com) provided English editing services during the preparation of this manuscript.
FreshRSS 