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To explore the competency of nursing graduates from the four dimensions of clinical practice, research ability, teaching ability and management ability, analyse its influencing factors and provide data support for improving the post ability of nurses with a master's degree.
In September 2024, a convenience sampling method was used to administer a self-designed questionnaire regarding post-graduation post-competency to 330 nursing master's degree graduates from 68 tertiary hospitals and five medical universities across China.
The average scores of clinical competence, research competence, teaching competence and management competence of nursing graduates were more than 7 (out of 10 points). Based on the Benner model, all the abilities of the participants were at the level of competent. Multivariate linear regression analysis indicated that marital status (p < 0.001), years since graduation (p < 0.001), major (p < 0.001) and et al., significantly influenced clinical competency. Furthermore, marital status, major, hospital rank and graduate type were key research competency factors. For teaching competency, major, training nature and professional title played a crucial role, whereas major, professional title, marital status and hospital rank were essential for management competency. Multivariate logistic regression analysis indicated that job position (χ 2 = 11.375, p = 0.01) significantly influenced SCI publication, whereas the training nature and type of graduate school were independent factors affecting publication in Chinese core journals. Moreover, years since graduation and professional title were independent factors that influenced the publication of scientific core journals.
The post-competency scores of nursing master's degree graduates in the four dimensions of clinical, research, teaching and management were moderate, indicating substantial potential for enhancement. Managers should develop personalised training programs based on different factors that influence the overall competency of nursing master's degree graduates, thereby improving nursing quality and ensuring patient safety.
To explore the effect of post-stroke fatigue (PSF) on post-stroke depression (PSD) and examine the mediating effects of fear of disease progression (FOP) and resilience between PSF and PSD.
A cross-sectional study.
A total of 315 stroke patients participated in the questionnaire survey between November 2022 and June 2023. Data were collected using the General Information Questionnaire, Fatigue Severity Scale, Fear of Disease Progression Questionnaire-Short Form, Connor–Davidson Resilience Scale-10 Item and Hospital Anxiety and Depression Scale-Depression Subscale. Data were analysed by descriptive analysis, Mann–Whitney U-test, Kruskal–Wallis H-test, Pearson or Spearman correlation, hierarchical regression analysis and mediation analysis.
PSF had a significant positive total effect on PSD (β = .354, 95% CI: .251, .454). Additionally, FOP and resilience played a partial parallel-mediating role in the relationship between PSF and PSD (β = .202, 95% CI: .140, .265), and the total indirect effect accounted for 57.06% of the total effect.
FOP and resilience parallelly mediated the effect of PSF on PSD, which may provide a novel perspective for healthcare professionals in preventing PSD. Targeted interventions aiming at reducing PSF, lowering FOP levels and enhancing resilience may be possible ways to alleviate PSD.
Interventions that tail to reducing PSF, lowering FOP levels and enhancing resilience may be considered as possible ways to alleviate PSD.
This study enriched the literature by exploring the effect of PSF on PSD and further examining the mediating effects of FOP and resilience between PSF and PSD. Findings emphasized the important effects of PSF, FOP and resilience on PSD.
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cross-sectional studies was used to guide reporting.
One tertiary hospital assisted participants recruitment.
FreshRSS 