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This study aimed to gain a better understanding of nursing/midwifery students' perspectives on a pedagogy of caring and online learning during the COVID-19 pandemic. In addition, it aimed to determine if the COVID-19 pandemic impacted students' perceptions and experience of online learning and students' desire to enter the nursing/midwifery workforce.
Mixed methods.
A multi-centre cross-sectional survey of Australian nursing and midwifery students was undertaken to explore students’ experience of learning during the COVID-19 pandemic.
There are several key findings from this study that may be relevant for the future delivery of undergraduate health education, students transitioning to practice and healthcare workforce retention. The study found that although students were somewhat satisfied with online learning during COVID-19, students reported significant issues with knowledge/skill acquisition and barriers to the learning process. The students reported feeling less prepared for practice and identified how clinical staff were unable to provide additional guidance and support due to increased workloads and stress. The textual responses of participants highlighted that connection/disconnection, empathy and engagement/disengagement had an impact on learning during COVID-19.
Connection, engagement and isolation were key factors that impacted nursing students’ online learning experiences. In addition, graduates entering the workforce felt less prepared for entry into practice due to changes in education delivery during COVID-19 that they perceived impacted their level of clinical skills, confidence and ability to practice as new graduate nurses/midwives.
Not applicable.
Attention must be given to the transition of new graduate nurses and midwives whose education was impacted by pandemic restrictions, to support their professional career development and to ensure retention of future healthcare workforce. Connection, engagement and isolation were key factors that impacted nursing students' online learning experiences. Educators should consider how connection and engagement can be actively embedded in the online learning environment.
This study aimed to explore the mediating effect of self-management (SM) on the relationship between illness perception and quality of life (QOL) among Human immunodeficiency virus (HIV)-positive men who have sex with men (MSM).
A cross-sectional study.
We explored the effect of illness perception and self-management on QOL using the multiple regression model. Moreover, we conducted a simple mediation analysis to examine the role of SM in the relationship between illness perception and QOL. In addition, a parallel mediation analysis was performed to investigate the differences in domains of SM on the relationship between illness perception and QOL.
Among 300 Chinese HIV-positive MSM, the mean score of SM was 39.9 ± 6.97, with a range of 14.0–54.0. The higher score in SM indicated a higher level of HIV SM. SM was negatively related to illness perception (r = −0.47) while positively related to QOL (r = 0.56). SM partially mediated the relationship between illness perception and QOL, accounting for 25.3% of the total effect. Specifically, both daily self-management health practices and the chronic nature of the self-management domain played a parallel role in mediating the relationship between illness perception and QOL.
Our study demonstrated that SM was a significant factor influencing QOL among HIV-positive MSM. Focusing on daily self-management health practices and the chronic nature of self-management could be the potential key targets for enhancing HIV self-management strategies.
This study emphasized the role of SM in the well-being of HIV-positive MSM and underscored the importance of developing interventions that integrate SM strategies to improve QOL in this population.
No patient or public contribution.
To examine the relationships between nurses' exposure to workplace violence and self-reports of workplace cognitive failure.
A cross-sectional study.
An online questionnaire was administered in April 2023 to nurses in Michigan, US. Structural equation modelling was used to examine effects of physical and non-physical workplace violence (occupational stressors) and work efficiency and competence development (occupational protective factors) on workplace cognitive failure.
Physical violence was a significant predictor of the action subscale of cognitive failure. There were no direct effects of non-physical violence, workplace efficiency, or competence development on any of the workplace cognitive failure dimensions. Both types of violence and efficiency had significant indirect effects on workplace cognitive failure via work-related exhaustion. Work-related exhaustion predicted significantly higher scores for workplace cognitive failure.
Workplace violence and work efficiency exhibited primarily indirect effects on workplace cognitive failure among nurses via work-related exhaustion.
Nurses experiencing workplace violence may be at increased risk for workplace cognitive failure, especially if they are also experiencing work-related exhaustion. Workplaces that nurses perceive as more efficient can help to mitigate the effects of violence on nurses' cognitive failure.
This study addressed the possible effects of workplace violence as well as work efficiency and competence development on nurses' cognitive failure at work. Analyses revealed primarily indirect effects of workplace violence, and indirect protective effects of work efficiency, on nurses' cognitive failure via work-related exhaustion. This research has implications for healthcare organizations and suggests that efforts made by healthcare workplaces to prevent violence and work-related exhaustion, and to enhance work efficiency, may help to mitigate workplace cognitive failure among nurses.
We have followed the STROBE checklist in reporting this study.
No Patient or public contribution.
This study aims to investigate the mediating role of regulatory emotional self-efficacy and self-compassion in the relationship among anxiety, depression, body image distress and subjective well-being among women with polycystic ovary syndrome.
A cross-sectional study.
The study recruited 510 women with polycystic ovary syndrome from a tertiary hospital affiliated with a university in Hunan Province, China. The study employed several tools to collect data, including the Generalized Anxiety Scale, the Patient Health Questionnaire-9, the Body Image States Scale, the Self-Compassion Scale, the Regulatory Emotional Self-Efficacy Scale and the Index of Well-being questionnaire. Data analysis was carried out using descriptive analysis, spearman correlation analysis, ordinary least squares regression and bootstrapping.
The study's findings indicate that regulatory emotional self-efficacy and self-compassion both act as mediators in the connection between anxiety, depression, body image distress and subjective well-being among women with polycystic ovary syndrome.
The study emphasizes the significance of regulatory emotional self-efficacy and self-compassion in promoting well-being among women with polycystic ovary syndrome. It also implies that interventions targeted at enhancing these factors could potentially enhance the subjective well-being of women affected by PCOS.
Our study's primary contribution is to underscore the crucial mediating roles of regulatory emotional self-efficacy and self-compassion in the relationship among anxiety, depression, body image distress and subjective well-being. Our study indicates that clinical practitioners should prioritize improving the regulatory emotional self-efficacy and self-compassion of women with polycystic ovary syndrome, reducing their anxiety, depression and body image distress and improving their subjective well-being.
This study was reported according to the Standards for Reporting Qualitative Research (SRQR).
No patient or public contribution outside of participation in the actual study for purposes of data collection.
To analyse whether the harmful effect of job demands on recovery can be alleviated by healthy lifestyle, psychological recovery experiences and job resources. We also describe their prevalence among employees in different types of eldercare service and in the health and social services sector in general.
Cross-sectional study.
The data were collected using a self-report survey in 2020 in the health and social services sector organizations (n = 4478). Employees were classified as the following service types: general health and social services (N = 3225), home care (N = 452), service housing (N = 550) and outpatient and ward care (N = 202). The data were analysed using percentages, cross-tabulations and logistic regression analysis.
Poor recovery, high job demands, low appreciation and low autonomy in terms of worktime and breaks were more prevalent in eldercare. Employers could alleviate the risk of high job demands by offering job resources—appreciation, autonomy in terms of worktimes and breaks—and motivating employees to maintain healthy lifestyle habits and use recovery experiences such as relaxation.
The study emphasizes the importance of appreciation in the health and social services sector context. Even with moderate levels of appreciation employers can protect employees from poor recovery from work in the demanding health and social services work environment.
Eldercare employees face continuous and accumulating work strain at the same time as the sector struggles against a labour shortage. One way to prevent the harmful consequences of strain is to enhance recovery from work.
Employers could alleviate the risk of high job demands and poor recovery by showing appreciation and giving employees more autonomy in terms of work time and breaks during the workday. This could also motivate employees to keep up healthy lifestyle habits and use their recovery experiences. Results are important especially in the daily management of HSS work.
Managers in the health and social services sector and eldercare can use these findings to promote recovery from work.
STROBE checklist.
No patient or public contribution.
This study aims to investigate the epidemiological characteristics of COVID-19 infection among healthcare workers, including the severity, duration of infection, post-infection symptoms and related influencing factors.
A self-administered questionnaire was utilized to assess the post-infection status of primary healthcare workers in Jiangsu Province. The questionnaire collected information on demographic characteristics, lifestyle habits, post-infection clinical manifestations, work environment and recovery time of the respondents. Customized outcome events were selected as dependent variables and logistic regression models were employed to analyse the risk factors. Phi-coefficient was used to describe the relationship between post-infection symptoms.
The analysis revealed that several factors, such as female, older age, obesity, previous medical history, exposure to high-risk environments and stress, were associated with a higher likelihood of experiencing more severe outcomes. On the other hand, vaccination and regular exercise were found to contribute to an earlier resolution of the infection. Among the post-infection symptoms, cough, malaise and muscle aches were the most frequently reported. Overall, there was a weak association among symptoms persisting beyond 14 days, with only cough and malaise, malaise and dizziness and headache showing a stronger correlation.
The study findings indicate that the overall severity of the first wave of infection, following the complete lifting of restrictions in China, was low. The impact on primary healthcare workers was limited, and the post-infection symptoms exhibited similarity to those observed in other countries. It is important to highlight that these conclusions are specifically relevant to the population infected with the Omicron variant.
This study helps to grasp the impacts of the first wave of COVID-19 infections on healthcare workers in China after the national lockdown was lifted.
Primary healthcare workers in Jiangsu Province, including doctors, nurses, pharmacists and other personnel from primary healthcare units such as community health service centres and health centres.
Examine profiles of safety attitudes among novices and explore whether profiles moderate the occupational identity–turnover pathway.
Novice nurses face unique challenges in adopting positive safety attitudes, which influence outcomes like turnover. However, past research found only average levels of safety attitudes among novices, ignoring possible heterogeneity. Exploring whether meaningful subgroups exist based on safety perspectives and factors shaping them can provide insights to improve safety attitudes and retention.
This study was designed as a cross-sectional investigation.
Data were collected through the distribution of questionnaires. Descriptive statistics were first conducted, followed by latent profile analysis. We then carried out univariate analysis and ordinal multinomial regression to explore the factors shaping the different profiles. Finally, we examine the moderating effect of nurses' safety attitudes with different latent profiles on the relationship between professional identification and turnover intention.
A total of 816 novice nurses were included. Three profiles were identified: high, moderate and low safety attitudes – higher attitudes were associated with lower turnover intention. Interest in nursing, health status, identity and turnover predicted profile membership. Moderate profile had a stronger buffering effect on the identity–turnover link versus high profile.
Multiple safety attitude profiles exist among novice nurses. Certain factors like interest in nursing and occupational identity are associated with more positive safety profiles. Targeting these factors could potentially improve safety attitudes and reduce turnover among novice nurses. The moderating effects suggest that tailored interventions matching specific subgroups may maximize impact.
Assessing subgroup attitudes enables tailored training for novices' specific needs, nurturing continuous improvement. Supporting early career development and role identity may strengthen retention intentions.
Nurses, assuming a wide range of clinical and patient care responsibilities in a healthcare team, are highly susceptible to direct and indirect exposure to traumatic experiences. However, literature has shown that nurses with certain traits developed a new sense of personal strength in the face of adversity, known as post-traumatic growth (PTG). This review aimed to synthesize the best available evidence to evaluate personal and work-related factors associated with PTG among nurses.
Mixed studies systematic review.
Studies examining factors influencing PTG on certified nurses from all healthcare facilities were included. Published and unpublished studies were identified by searching 12 databases from their inception until 4th February 2023. Two reviewers independently screened, appraised, piloted a data collection form, and extracted relevant data. Meta-summary, meta-synthesis, meta-analysis, as well as subgroup and sensitivity analyses were performed. Integration of results followed result-based convergent design.
A total of 98 studies with 29,706 nurses from 18 countries were included. These included 49 quantitative, 42 qualitative, and seven mixed-methods studies. Forty-six influencing factors were meta-analyzed, whereas nine facilitating factors were meta-summarized. A PTG conceptual map was created. Four constructs emerged from the integration synthesis: (a) personal system, (b) work-related system, (c) event-related factors, and (d) cognitive transformation.
The review findings highlighted areas healthcare organizations could do to facilitate PTG in nurses. Practical implications include developing intervention programs based on PTG facilitators. Further research should examine the trend of PTG and its dynamic response to different nursing factors.
Research on trauma-focused therapies targeting nurses' mental health is lacking. Therefore, findings from this review could inform healthcare organizations on the PTG phenomenon and developing support measures for nurses through healthcare policies and clinical practice.
Cancer screening is a pivotal method for reducing mortality from disease, but the screening coverage is still lower than expected. Telehealth interventions demonstrated significant benefits in cancer care, yet there is currently no consensus on their impact on facilitating cancer screening or on the most effective remote technology.
A network meta-analysis was conducted to detect the impact of telehealth interventions on cancer screening and to identify the most effective teletechnologies.
Six English databases were searched from inception until July 2023 to yield relevant randomized controlled trials (RCTs). Two individual authors completed the literature selection, data extraction, and methodological evaluations using the Cochrane Risk of Bias tool. Traditional pairwise analysis and network meta-analysis were performed to identify the overall effects and compare different teletechnologies.
Thirty-four eligible RCTs involving 131,644 participants were enrolled. Overall, telehealth interventions showed statistically significant effects on the improvement of cancer screening. Subgroup analyses revealed that telehealth interventions were most effective for breast and cervical cancer screening, and rural populations also experienced benefits, but there was no improvement in screening for older adults. The network meta-analysis indicated that mobile applications, video plus telephone, and text message plus telephone were associated with more obvious improvements in screening than other teletechnologies.
Our study identified that telehealth interventions were effective for the completion of cancer screening and clarified the exact impact of telehealth on different cancer types, ages, and rural populations. Mobile applications, video plus telephone, and text message plus telephone are the three forms of teletechnologies most likely to improve cancer screening. More well-designed RCTs involving direct comparisons of different teletechnologies are needed in the future.
Telehealth interventions should be encouraged to facilitate cancer screening, and the selection of the optimal teletechnology based on the characteristics of the population is also necessary.
We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care. As of now, a model for predicting the survival of patients with out-of-hospital cardiac arrest has not been established. This study aimed to develop a model for identifying predictors of survival over time in patients with out-of-hospital cardiac arrest during their stay in the emergency department, using ensemble-based machine learning. A total of 26 013 patients from the Korean nationwide out-of-hospital cardiac arrest registry were enrolled between January 1 and December 31, 2019. Our model, comprising 38 variables, was developed using the Survival Quilts model to improve predictive performance. We found that changes in important variables of patients with out-of-hospital cardiac arrest were observed 10 minutes after arrival at the emergency department. The important score of the predictors showed that the influence of patient age decreased, moving from the highest rank to the fifth. In contrast, the significance of reperfusion attempts increased, moving from the fourth to the highest rank. Our research suggests that the ensemble-based machine learning model, particularly the Survival Quilts, offers a promising approach for predicting survival in patients with out-of-hospital cardiac arrest. The Survival Quilts model may potentially assist emergency department staff in making informed decisions quickly, reducing preventable deaths. To assess the level of mental workload (MWL) of intensive care unit (ICU) nurses in performing different human-machine tasks and examine the predictors of the MWL.
A cross-sectional questionnaire study.
Between January and February 2021, data were collected from ICU nurses (n = 427) at nine tertiary hospitals selected from five (east, west, south, north, central) regions in China through an electronic questionnaire, including sociodemographic questions, the National Aeronautics and Space Administration Task Load Index, General Self-Efficacy Scale, Difficulty-assessing Index System of Nursing Operation Technique, and System Usability Scale. Descriptive statistics, t-tests, one-way ANOVA and multiple linear regression models were used.
ICU nurses experienced a medium level of MWL (score 52.04 on a scale of 0–100) while performing human-machine tasks. ICU nurses' MWL was notably higher in conducting first aid and life support tasks (using defibrillators or ventilators). Predictors of MWL were task difficulty, system usability, professional title, age, self-efficacy, ICU category, and willingness to study emerging technology actively. Task difficulty and system usability were the strongest predictors of nearly all typical tasks.
ICU nurses experience a medium MWL while performing human-machine tasks, but higher mental, temporal, and effort are perceived compared to physical demands. The MWL varied significantly across different human-machine tasks, among which are significantly higher: first aid and life support and information-based human-machine tasks. Task difficulty and system availability are decisive predictors of MWL.
This is the first study to investigate the level of MWL of ICU nurses performing different representative human-machine tasks and to explore its predictors, which provides a reference for future research. These findings suggest that healthcare organizations should pay attention to the MWL of ICU nurses and develop customized management strategies based on task characteristics to maintain a moderate level of MWL, thus enabling ICU nurses to perform human-machine tasks better.
No patient or public contribution.
To investigate the relationship between work readiness and work well-being for newly graduated nurses and the mediating role of emotional labor and psychological capital in this relationship.
A cross-sectional survey was conducted in mainland China. A total of 478 newly graduated nurses completed the Work Readiness Scale, Emotional Labour Scale, Psychological Capital Questionnaire, and Work Well-being Scale. Descriptive statistical methods, Pearson correlation analysis, and a structural equation model were used to analyze the available data.
Newly graduated nurses' work readiness was significantly positively correlated with work well-being (r = 0.21, p < 0.01), deep acting (r = 0.11, p < 0.05), and psychological capital (r = 0.18, p < 0.01). Emotional labor and psychological capital partially mediated the relationship between work readiness and work well-being. Additionally, emotional labor and psychological capital had a chain-mediating effect on the association.
Work readiness not only affects newly graduated nurses' work well-being directly but also indirectly through emotional labor and psychological capital. These results provide theoretical support and guidance for the study and improvement of newly graduated nurses' work well-being and emphasize the importance of intervention measures to improve work readiness and psychological capital and the adoption of deep-acting emotional-labor strategies.
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approach. We retrospectively gathered medical data from 13 440 pediatric patients slated for surgery from 2018 to 2021. Following data preprocessing, we utilized random forests, logistic regression, linear support vector machines, gradient boosting trees, and extreme gradient boosting trees to predict these abrupt cancellations. The efficacy of these models was assessed through performance metrics. The analysis revealed that key factors influencing last-minute cancellations included the impact of the coronavirus disease 2019 pandemic, average wind speed, average rainfall, preanesthetic assessments, and patient age. The extreme gradient boosting algorithm outperformed other models in predicting cancellations, boasting an area under the curve value of 0.923 and an accuracy of 0.841. This algorithm yielded superior sensitivity (0.840), precision (0.837), and F1 score (0.838) relative to the other models. These insights underscore the potential of machine learning, informed by EMRs and meteorological data, in forecasting last-minute surgical cancellations. The extreme gradient boosting algorithm holds promise for clinical deployment to curtail healthcare expenses and avert adverse patient-family experiences. New nurses must acquire accurate knowledge of medication administration, as it directly affects patient safety. This study aimed to develop a microlearning-based self-directed learning chatbot on medication administration for novice nurses. Furthermore, the study had the objective of evaluating the chatbot feasibility. The chatbot covered two main topics: medication administration processes and drug-specific management, along with 21 subtopics. Fifty-eight newly hired nurses on standby were asked to use the chatbot over a 2-week period. Moreover, we evaluated the chatbot's feasibility through a survey that gauged changes in their confidence in medication administration knowledge, intrinsic learning motivation, satisfaction with the chatbot's learning content, and usability. After using the chatbot, participants' confidence in medication administration knowledge significantly improved in all topics (P Patients with impaired kidney function and increased albuminuria are at risk of developing cardiovascular disease (CVD). Previous research has revealed that a substantial proportion of patients with chronic kidney disease (CKD) do not get a registered diagnosis in the electronic health record of the general practitioner. The aim of this study was to investigate the association between non-registration of CKD and all-cause mortality and cardiovascular outcome.
A retrospective study in primary care.
The analyses were carried out in the INTEGO database, a general practice-based morbidity registration network in Flanders, Belgium. The study used INTEGO data from the year 2018 for all patients ≥18 years old, including 10 551 patients. To assess the risk of mortality and CVD, a time-to-event analysis was performed. Cox proportional hazard model was used to evaluate the association between non-registration and incidence of all-cause mortality and cardiovascular events with mortality as a competing risk. Subgroup analyses were performed for estimated glomerular filtration rate stages (3A, 3B, 4 and 5). Multiple imputation was done following the methodology of Mamouris et al.
Mortality was higher in patients with non-registered CKD compared with patients with registered CKD (HR 1.29, 95% CI 1.19 to 1.41). Non-registration of CKD was not associated with an increased risk for the development of CVD (HR 0.92, 95% CI 0.77 to 1.11).
An association between non-registration and all-cause mortality was identified, although no such association was apparent for CVD.
A Community of Practice is briefly defined as a group of people with a shared interest in a given area of practice who work collaboratively to grow collective knowledge. Communities of Practice have been used to facilitate knowledge exchange and improve evidence-based practice. Knowledge translation within the residential aged care sector is lacking, with barriers such as inadequate staffing and knowledge gaps commonly cited. In Australia, a Federal inquiry into residential aged care practices led to a recommendation to embed pharmacists within residential aged care facilities. Onsite practice in aged care is a new role for pharmacists in Australia. Thus, support is needed to enable pharmacists to practice in this role.
The primary aim is to evaluate the processes and outcomes of a Community of Practice designed to support pharmacists to work in aged care.
A longitudinal, single-group, pretest–post-test design in which the intervention is a Community of Practice. The Community of Practice will be established and made available for 3 years to all Australian pharmacists interested in, new to or established in aged care roles. The Community of Practice will be hosted on online discussion platforms, with additional virtual meetings and annual symposia. The following data will be collected from all members of the Community of Practice: self-evaluation of the processes and outcomes of the Community of Practice (via the CoPeval scale) and confidence in evidence-based practice (EPIC scale), collected via online questionnaires annually; and discussion platform usage statistics and discussion transcripts. A subset of members will be invited to participate in annual semi-structured individual interviews.
Data from the online questionnaire will be analysed descriptively. Discussion transcripts will be analysed using topic modelling and content analysis to identify the common topics discussed and their frequencies. Qualitative data from individual interviews will be thematically analysed to explore perceptions and experiences with the intervention for information/knowledge exchange, impact on practice, and sharing/promoting/implementing evidence-based practice.
Human ethics approval has been granted by the University of Western Australia’s Human Ethics Committee (2023/ET000000). No personal information will be included in any publications and reports to funding bodies.
Findings will be disseminated to all members of the Community of Practice, professional organisations, social and mass media, peer-review journals, research and professional conferences and annual reports to the funding body.
More than 170 countries have implemented disability-targeted social protection programmes, although few have been rigorously evaluated. Consequently, a non-randomised controlled trial is being conducted of a pilot ‘cash-plus’ programme implemented by UNICEF Laos and the Laos government for children with disabilities in the Xiengkhouang Province in Laos. The intervention combines a regular cash transfer with provision of assistive devices and access for caregivers to a family support programme.
The non-randomised controlled trial will involve 350 children with disabilities across 3 districts identified by programme implementers as eligible for the programme (intervention arm). Implementers have also identified approximately 180 children with disabilities in neighbouring districts, who would otherwise meet eligibility criteria but do not live in the project areas (control arm). The trial will assess the impact of the programme on child well-being (primary outcome), as well as household poverty, caregiver quality of life and time use (secondary outcomes). Baseline data are being collected May–October 2023, with endline 24 months later. Analysis will be intention to treat. A complementary process evaluation will explore the implementation, acceptability of the programme, challenges and enablers to its delivery and mechanisms of impact.
The study has received ethical approval from the London School of Hygiene and Tropical Medicine and the National Ethics Committee for Health Research in Laos. Informed consent and assent will be taken by trained data collectors. Data will be collected and stored on a secure, encrypted server and its use will follow a detailed data management plan. Findings will be disseminated in academic journals and in short briefs for policy and programmatic actors, and in online and in-person events.
FreshRSS 