Impact of the National Nursing Development Plan on nursing human resources in China: An interrupted time series analysis for 1978-2021

Pragmatic, multicentre, randomised controlled trial of a Hospital-Community-Home Tiered Transitional Care (HCH-TTC) programme for individuals with type 2 diabetes: a study protocol

INTRODUCTION

Type 2 Diabetes Mellitus (T2DM) and its complications significantly increase the risk of premature mortality and disability among patients, placing a considerable burden on socioeconomic development. Evidence has shows that effective transitional care can improve health outcomes for patients with T2DM. However, T2DM transitional care faces challenges including service discontinuity, communication breakdowns and a lack of personalised design, leading to potential issues of undertreatment and overtreatment, increasing the risk of improper blood sugar management. To address these challenges, our research team developed the Hospital-Community-Home Tiered Transitional Care (HCH-TTC) programme for patients with T2DM, aiming to evaluate its effectiveness and feasibility through a randomised controlled trial (RCT).

METHOD AND ANALYSIS

The multicentre, pragmatic, double-blind RCT will enrol 180 patients with T2DM from the Jinqiao Medical Union in Pudong New Area, Shanghai, China. Participants will be randomly assigned to either the experimental group or the control group. The experimental group will participate in a 6-month HCH-TTC programme, which provides personalised transitional care strategies tailored to patients' evolving health conditions and nursing needs. This tiered management approach includes follow-up, health education, personalised guidance and health monitoring, with variations in intensity, frequency and type based on individual requirements. The control group will receive Hospital-Community-Home Routine Transitional Care programme, consisting of routine follow-up, health education and health monitoring during the same period. Data collection will be conducted at baseline, 1 month postintervention, 3 months and 6 months. The primary outcomes are glycated haemoglobin (HbA1c). Secondary outcomes include fasting plasma glucose (FPG), 2-hour postprandial blood glucose (2hPPG), diabetes knowledge level, diabetes self-management ability, diabetes treatment adherence, nursing service satisfaction, diabetes complications rate and unplanned readmission rate. Statistical analysis will employ independent sample t-tests and repeated measures analysis of variance.

ETHICS AND DISSEMINATION

The Gongli Hospital Ethics Committee (GLYY1s2021-010) approved the study. Results will be disseminated through publication in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry ChiCTR2200063322.

Interrupted-time-series analysis of the impact of COVID-19 pandemic on blood culture utilization in Shanghai

BACKGROUND

Limited information is available regarding the changes in blood culture utilization following the COVID-19 pandemic. Blood culture utilization rate is a critical indicator of diagnostic efficiency for infectious diseases. This study aims to describe the impact of the COVID-19 pandemic on blood culture utilization rate in Shanghai.

METHODS

We conducted an interrupted time-series analysis based on electronic health records from the Shanghai Changzheng hospital from January 2014 to October 2023. The outcome measure was the rate of blood culture utilization among inpatients with a temperature of ≥ 39.4 °C. The impact of the COVID-19 pandemic on blood culture utilization was quantified by fitting linear segmented regression models and modelling the relative cumulative effect by the end of the study. The pandemic period was defined from February 2020, following the implementation of strict containment measures in Shanghai.

RESULTS

A total of 23,761 inpatients with a temperature of ≥ 39.4 °C were included in the analysis. From 2014 to 2023, the utilization rate of hospital blood cultures increased initially and then declined, with a significant change point following the onset of the COVID-19 pandemic (Cochran-Armitage trend test, P < 0.001). The COVID-19 pandemic was associated with a significant change in the slope of the blood culture utilization rate (pre-COVID-19 vs. during-COVID-19: 0.31% per month vs. -0.30% per month, P < 0.001), resulting in a relative cumulative effect of -12.55% at the end of the study (95% confidence interval, -19.08 to -6.03). This corresponds to 407 inpatients who did not have blood cultures taken during-pandemic, which represents a significant deviation from pre-pandemic trends.

CONCLUSIONS

The upward trend in blood culture utilization rate among inpatients stalled during the COVID-19 pandemic and did not return to pre-pandemic levels following the pandemic. These findings suggest that the pandemic had a lasting impact on diagnostic practices. More targeted intervention measures are needed to promote appropriate utilization of blood cultures.

Research on equity analysis and forecasting of nursing human resource allocation in Jiangxi Province, China

Objectives

This study aimed to assess the equity of nursing human resource allocation in Jiangxi Province, China, and forecast future trends in the next five years.

Methods

We used the related data from the China Statistical Yearbook, China Health Statistics Yearbook, and Jiangxi Statistical Yearbook (2003-2022). The equity of nursing human resource allocation was evaluated using Lorenz curves, Gini coefficients, and Theil index, from the perspective of population and geographical area. Demands for nursing human resource in Jiangxi Province from 2023 to 2027 were forecasted using the Autoregressive Integrated Moving Average (ARIMA) and Grey (1,1) models.

Results

From 2003 to 2022, all the key nursing human resource indicators continuously increased; the number of registered nurses in Jiangxi Province increased by 109,786, with an average annual growth rate of 7.80%. Registered nurses per 1,000 population rose by 2.21, while nurses per square kilometer increased by 0.66. Jiangxi Province has surpassed the national level in several nursing resource indicators, including registered nurses as a percentage of health technicians, registered nurses per square kilometer, and doctor-to-nurse ratio. Within the province, all indicators in cities are higher than those in county-level regions. Among the cities in Jiangxi Province, Ganzhou City had the highest number of registered nurses, Xinyu City led in the doctor-to-nurse ratio, and Nanchang City had the highest bed-to-nurse ratio. In 2022, the Gini coefficients for registered nurses in Jiangxi Province were 0.09 by population and 0.34 by geographical area, reflecting the allocation of registered nurses in Jiangxi Province is highly equitable by population but relatively equitable by geographical area. Forecasting results suggested that the number of registered nurses in Jiangxi Province will reach 170,100 by 2027, indicating continued growth and improvement in nursing resource allocation.

Conclusions

Over the past two decades, the human nursing resources in Jiangxi Province have grown substantially. The absolute fairness of nurse human resources allocation by population highlights significant progress, although regional disparities persist. These findings provide a foundation for optimizing future nursing resource allocation to ensure equitable access to healthcare services.

Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model

Background

Globally, the rates at which the aging population and the prevalence of chronic diseases are increasing are substantial. With declining birth rates and a growing percentage of older individuals, the demand for nursing staff is steadily rising. However, the shortage of nursing personnel has been a long-standing issue. In recent years, numerous researchers have advocated for the implementation of nursing robots as a substitute for traditional human labor.

Objective

This study analyzes hospital visitors' attitudes and priorities regarding the functional areas of artificial intelligence (AI) nursing robots based on the Kano model. Building on this analysis, recommendations are provided for the functional optimization of AI nursing robots, aiming to facilitate their adoption in the nursing field.

Methods

Using a random sampling method, 457 hospital visitors were surveyed between December 2023 and March 2024 to compare the differences in demand for AI nursing robot functionalities among the visitors.

Results

A comparative analysis of the Kano attribute quadrant diagrams showed that visitors seeking hospitalization prioritized functional aspects that enhance medical activities. In contrast, visitors attending outpatient examinations focused more on functional points that assist in medical treatment. Additionally, visitors whose purpose was companionship and care emphasized functional aspects that offer psychological and life support to patients.

Conclusions

AI nursing robots serve various functional areas and cater to diverse audience groups. In the future, it is essential to thoroughly consider users' functional needs and implement targeted functional developments to maximize the effectiveness of AI nursing robots.

A study on regional differences and convergence of nursing human resource levels in the Yangtze River Economic Belt: an empirical study

BACKGROUND

The Yangtze River Economic Belt, as a core economic region in China, is facing the dual challenges of an aging population and growing healthcare demand, and the balanced development and optimal allocation of nursing human resources is crucial to the region's healthcare system. An in-depth study of the regional differences and convergence of nursing human resources in the region will provide a key basis for policy makers to achieve equity and efficiency in healthcare services and meet the growing demand for healthcare.

AIM

To analyze the regional differences and convergence characteristics of nursing human resource levels in the Yangtze River Economic Belt, and to provide scientific references for optimizing regional nursing human resource allocation.

METHODS

Based on the panel data of 107 cities in the Yangtze River Economic Belt from 2010 to 2020, the regional differences and their sources were analyzed by using Dagum's Gini coefficient, and the convergence characteristics were examined by the coefficient of variation and spatial convergence model.

RESULTS

The average value of the number of nursing human resources in the Yangtze River Economic Belt is 2,132,300 people, with obvious regional differences, and the hypervariable density difference (53.01%) is the main source of the regional differences; there are obvious trends of σ-convergence and conditional β-convergence of the level of nursing human resources in the overall and the three major regions of the upstream, midstream, and downstream, and different factors have different moderating effects on the speed of spatial convergence in the other areas.

CONCLUSION

The implementation of precise policies for nursing human resources in different regions of the Yangtze River Economic Belt steadily reduces the regional differences between the upper, middle, and lower reaches and enhances the spatial linkage between regions of nursing human resources to improve the quality of nursing human resources.

Psychometric evaluation of the Chinese version of the Nursing Student Contributions to Clinical Settings scale and analysis of factors influencing nurses' perceptions of nursing students' contributions: a cross-sectional study

BACKGROUND

Most medical organizations accept many nursing students each year who gain clinical practice skills under the supervision of clinical nurses. However, there are no assessment tools to measure the contributions nursing students make to the clinical setting during clinical practicum. This study aimed to translate the 'Nursing Student Contributions to Clinical Settings' scale into Chinese and test its reliability and validity from the perspective of Chinese clinical nurses. And to explore whether nurses' personal and professional characteristics are related to nurses' perception of nursing students' contributions to the clinical settings.

METHODS

The original scale was translated into Chinese following the Brislin translation model. A convenience sample of 935 clinical nurses was selected from January to March 2024 for the survey. The content validity of the scale was assessed by expert consultation and content validity index. Exploratory factor analysis and confirmatory factor analysis were performed to assess the construct validity of the scale. The reliability of the scale was measured using internal consistency, split-half reliability, and test-retest reliability. The measurement quality of the scales was assessed according to the COnsensus-based Standards for the selection of health Measurement INstruments. One-way analysis of variance was used to identify variables related to students' contributions.

RESULTS

The content validity index of the scale was 0.983. Exploratory factor analysis supported a one-factor structure, and the cumulative variance contribution was 71.177%. Confirmatory factor analysis showed that the model fit indicators were all within the acceptable range. The McDonald's Omega coefficient and Cronbach's alpha coefficient for the scale were 0.983. Nurses perceive that nursing students' contribution to the clinical settings is influenced by nurses' personal characteristics, professional characteristics, and the hospital environment.

CONCLUSION

The Chinese version of the Nursing Student Contributions to Clinical Settings scale has good reliability and validity and can effectively and reliably measure the contributions of Chinese nursing students to clinical settings.

Demand Forecasting of Nurse Talents in China Based on the Gray GM (1,1) Model: Model Development Study

BACKGROUND

In a global context, the shortage of nursing personnel has emerged as a significant challenge, particularly in countries such as China experiencing population aging. The inadequacy of nursing human resources has become one of the primary threats affecting the quality of health services available to Chinese residents. Therefore, forecasting the demand for nursing personnel has become an important issue.

OBJECTIVE

This study presents a Gray GM (1,1) forecasting model for predicting the future 10-year demand for nursing workforce and the number of specialized geriatric nurses, aiming to provide a scientific basis for the development of policies in health care institutions in China.

METHODS

Based on data from the China Statistical Yearbook 2022, the Gray GM (1,1) model was used to predict the demand for nursing jobs and geriatric nurses over the next 10 years (2024-2033).

RESULTS

The results indicate that from 2024 to 2033, amidst a continuous growth in the overall population and an increasingly pronounced trend of population aging, the demand for nursing workforce in China, especially for specialized geriatric nurses, is projected to steadily increase.

CONCLUSIONS

The paper provides a reference basis for the establishment of China's health care workforce system and the involvement of government departments in health care workforce planning.

Competency in responding to infectious disease outbreaks among nurses in primary healthcare institutions: a quantitative, cross-sectional multicentre study

Background

Nurses' competencies are crucial for infectious disease prevention and control. We aimed to investigate competencies in responding to infectious disease outbreaks of nurses in primary healthcare institutions and identify their training needs.

Methods

A cross-sectional study was conducted from June to September 2022, recruiting nurses from primary healthcare institutions across Sichuan Province. Their competencies and training needs were assessed using a modified Emergency Response Competency Scale for Infectious Diseases. Additionally, their sociodemographic characteristics and experience in infectious disease outbreak trainings were collected. Univariate analyses were used to compare competencies and training needs by participant characteristics. Multiple linear regression was conducted to identify determinants of their competencies.

Results

A total of 1,439 nurses from 44 primary healthcare institutions participated in this study. The overall competency and training needs had a median of 3.6 (IQR [3.1, 4.0]) and 4.0 (IQR [3.9, 4.7]), respectively. Age (β = -0.074, p = 0.005), experience in higher authority hospitals (β = 0.057, p = 0.035), infectious disease outbreak trainings attended within the last 5 years (β = 0.212, p < 0.001), and regions where the institutions located were determinants of the competencies.

Conclusion

The competencies in responding to infectious disease outbreaks among nurses in primary healthcare institutions were at a moderate level, influenced by varied factors.

Forecast of the number of nursing beds per 1000 older people from 2023 to 2025: Empirical quantitative research

AIM

This research aims to offer a reference point for relevant departments to enhance the allocation of ageing resources and formulate policies accordingly.

DESIGN

This study is designed as empirical quantitative research.

METHODS

Data from the National Bureau of Statistics and the Ministry of Civil Affairs regarding older adults (aged≥60) from 2000 to 2022 and nursing beds from 1978 to 2022 were analysed. The differential autoregressive integrated moving averages model and Monte Carlo simulation were used to predict the growth of nursing beds per 1000 older people in China for the Years 2023-2025.

RESULTS

It is projected that from 2023 to 2025, China will experience a further increase in its ageing population, with an average annual growth rate of 3.1%. By 2025, the number of older people in China is expected to surpass 300 million. Additionally, there will be a rise in the number of nursing beds, with an average annual growth rate of 1.9%, leading to a total of 8.79 million nursing beds by 2025. However, due to the rapid growth of the older population, there will be a slight decline in the number of nursing beds per 1000 older people in China, with an average annual growth rate of -1.00%.

Sliding limited penetrable visibility graph for establishing complex network from time series

This study proposes a novel network modeling approach, called sliding window limited penetrable visibility graph (SLPVG), for transforming time series into networks. SLPVG takes into account the dynamic nature of time series, which is often affected by noise disturbances, and the fact that most nodes are not directly connected to distant nodes. By analyzing the degree distribution of different types of time series, SLPVG accurately captures the dynamic characteristics of time series with low computational complexity. In this study, the authors apply SLPVG for the first time to diagnose compensation capacitor faults in jointless track circuits. By combining the fault characteristics of compensation capacitors with network topological indicators, the authors find that the betweenness centrality reflects the fault status of the compensation capacitors clearly and accurately. Experimental results demonstrate that the proposed model achieves a high accuracy rate of 99.1% in identifying compensation capacitor faults. The SLPVG model provides a simple and efficient tool for studying the dynamics of long time series and offers a new perspective for diagnosing compensation capacitor faults in jointless track circuits. It holds practical significance in advancing related research fields.

The effect of occupational coping self-efficacy on presenteeism among ICU nurses in Chinese public hospitals: a cross-sectional study

Background

Nurses are the largest occupational group in the health field, with inestimable value in realizing universal health coverage, and nurses' physical and mental health has become an ordinary global reality. Compared with explicit absence, nurses' presenteeism has a more lasting impact and significant harm and loss. It has become an essential factor affecting nurses' physical and mental health, declining quality of healthcare services, and elevated healthcare-related risks. There is a lack of research exploring whether occupational coping self-efficacy influences nurses' presenteeism behavior, especially in less-developed regions of China.

Objective

This study aimed to investigate the current status of ICU nurses' occupational coping self-efficacy and presenteeism in public hospitals in western China and to explore the impact of ICU nurses' occupational coping self-efficacy on presenteeism.

Methods

A cross-sectional research design selected 722 ICU nurses in western China from January to February 2023 as survey respondents. A general information questionnaire, Occupational Coping Self-Efficacy Scale (OCSE-N), and Stanford Presenteeism Scale (SPS-6) were used. SPSS 21.0 software was used for statistical analysis. Pearson correlation analysis and multivariate hierarchical regression were used to explore the influence of ICU nurses' occupational coping self-efficacy on presenteeism.

Results

A total of 722 ICU nurses completed the questionnaire. The OCSE-N score of ICU nurses was (22.24 ± 6.15), and the SPS-6 score was (16.83 ± 4.24). The high presenteeism was 67.23%. Correlation analysis showed that in ICU nurses, OCSE-N total score was negatively correlated with SPS-6 total score (r = -0.421, p < 0.05), indicating that the higher the level of occupational coping self-efficacy, the lower the presenteeism. Multiple hierarchical regression analysis showed that occupational coping self-efficacy strongly predicted presenteeism, accounting for approximately 18.35% of the total variance.

Conclusion

There is a correlation between ICU nurses' occupational coping self-efficacy and presenteeism, and nurses' occupational coping self-efficacy affects presenteeism differently. Managers should pay attention to nurses' occupational coping self-efficacy to promote nurses' presenteeism reduction.