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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 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.
Populations are ageing, making the quality of old age a crucial issue. Some adversity in old age, such as loss of loved one or loss of physical function, is often experienced, as is the need for recovery from such adversity. Resilience in later life has become an important topic and has accumulated much empirical research. However, the research has mainly centred on individual factors, such as personality, rather than social factors, such as family relationships or community engagement. There is no systematic review of the social dimensions of resilience in old age, a focus that should be especially important for policy and practice seeking to create supporting environments.
Our review comprises quantitative and qualitative empirical original English language studies, published 2013–2023, using predefined search phrases including ‘resilience’ and various terms for old age and social dimensions. Titles and abstracts are screened by the first two authors using registered exclusion criteria. Final inclusion, based on full-text reading, is decided using registered inclusion criteria, and verified by co-authors. Qualitative articles are read by authors specialized in qualitative research and quantitative articles by authors specialized in quantitative research. Due to large expected heterogeneity, meta-analysis is not conducted, but weighted effect sizes or funnel plots may be prepared if parallel quantitative studies are encountered. Qualitative studies are synthesized using meta-aggregation. The risk of bias is evaluated with applicable Joanna Briggs Institute checklists for each study design. A narrative synthesis brings together the qualitative and quantitative studies.
Methodological strengths and weaknesses of the included studies are reported to assess the quality of the research. Summary of the most significant social dimensions of resilience in old age is prepared, emphasizing interactions between contexts, stressors, mechanisms and outcomes; and research gaps are identified.
Protocol is registered in PROSPERO (CRD42023412532).
The objective of this scoping review was to survey the literature on the use of AI/ML applications in analyzing inpatient EHR data to identify bundles of care (groupings of interventions). If evidence suggested AI/ML models could determine bundles, the review aimed to explore whether implementing these interventions as bundles reduced practice pattern variance and positively impacted patient care outcomes for inpatients with T2DM. Six databases were searched for articles published from January 1, 2000, to January 1, 2024. Nine studies met criteria and were summarized by aims, outcome measures, clinical or practice implications, AI/ML model types, study variables, and AI/ML model outcomes. A variety of AI/ML models were used. Multiple data sources were leveraged to train the models, resulting in varying impacts on practice patterns and outcomes. Studies included aims across 4 thematic areas to address: therapeutic patterns of care, analysis of treatment pathways and their constraints, dashboard development for clinical decision support, and medication optimization and prescription pattern mining. Multiple disparate data sources (i.e., prescription payment data) were leveraged outside of those traditionally available within EHR databases. Notably missing was the use of holistic multidisciplinary data (i.e., nursing and ancillary) to train AI/ML models. AI/ML can assist in identifying the appropriateness of specific interventions to manage diabetic care and support adherence to efficacious treatment pathways if the appropriate data are incorporated into AI/ML design. Additional data sources beyond the EHR are needed to provide more complete data to develop AI/ML models that effectively discern meaningful clinical patterns. Further study is needed to better address nursing care using AI/ML to support effective inpatient diabetes management. No abstract available 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 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.
This study aimed to identify the main themes from exit interviews of adult patients with type 2 diabetes after completion of a diabetes education program. Eighteen participants with type 2 diabetes completed an exit interview regarding their program experience and satisfaction. Semistructured interview questions were used, and the interviews were auto-recorded. The interview transcripts were preprocessed and analyzed using four natural language processing–based text-mining techniques. The top 30 words from the term frequency and term frequency–inverse document frequency each were derived. In the N-gram analysis, the connection strength of “diabetes” and “education” was the highest, and the simultaneous connectivity of word chains ranged from a maximum of seven words to a minimum of two words. Based on the CONvergence of iteration CORrelation (CONCOR) analysis, three clusters were generated, and each cluster was named as follows: participation in a diabetes education program to control blood glucose, exercise, and use of digital devices. This study using text mining proposes a new and useful approach to visualize data to develop patient-centered diabetes education. 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 Vector borne diseases (VBDs) present significant public health challenges in Southeast Asia (SEA), and the increasing number of cases threatens vulnerable communities. Inadequate vector control and management have been linked to the spread of VBDs. To address these issues, community participation has been proposed as a promising approach to enhance health programmes and control of VBDs. This article outlines a protocol for a scoping review of the published literature on community-participation approaches to control VBDs in the SEA region. The primary research question is ‘How does community participation complement the control of VBDs in SEA?’ This review aims to provide an overview of various approaches and identify barriers and facilitators to effective implementation.
The research questions will guide the scoping review. In stage 1, peer-reviewed publications from PubMed, Web of Science and Scopus will be searched using predefined search terms related to community-based approaches and VBDs in the SEA region, English, Indonesian and Malay published between 2012 and 2022. In stage 2, the references from relevant articles will be screened for eligibility. In stage 3, eligible articles will be charted in Microsoft Excel to facilitate the review process, and studies will be characterised based on the investigated diseases; this review will also highlight the methodological context of these studies. In stage 4, a thematic analysis will be conducted to derive meaningful findings from the dataset relevant to the research inquiry, followed by writing the results in stage 5. This scoping review aims to be the first to explore community participation in VBD control in the SEA population, providing valuable insights for future research and stakeholders involved in disease control.
This scoping review does not require ethical approval because the methodology synthesises information from available articles. This review is planned for dissemination in academic journals, conference presentations and shared with stakeholders as part of knowledge sharing among those involved in VBD control.
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.
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