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To identify the barriers and facilitators in the implementation of fertility preservation (FP) shared decision-making (SDM) in oncology care.
Qualitative descriptive study.
Qualitative interviews with 16 female patients with cancer and seven healthcare providers were conducted between July 2022 and April 2024. Data were analyzed using directed content analysis, guided by the implementation science framework.
We identified 22 categories comprising 38 codes as barriers to SDM implementation and 17 categories comprising 26 codes as facilitators. Findings revealed that, at the innovation level, accessibility, feasibility, interdisciplinary collaboration, and quality improvement efforts were decisive in the implementation of FP SDM. At the individual level, healthcare providers' awareness and attitudes towards FP and SDM, as well as patients' knowledge, attitudes, and capabilities in FP SDM, were crucial factors in the implementation of FP SDM. In social, economic, and organizational contexts, support from significant others, social awareness about FP, multidisciplinary care, financial assistance, and educational resources were determinants in implementing FP SDM.
Implementing FP SDM among female patients with cancer necessitates a strategic approach that considers barriers and facilitators. Educating and promoting FP SDM among the public and healthcare providers, combined with incentivizing policies, can enhance individual knowledge and awareness while achieving systemic improvements, facilitating its successful implementation.
This study provides insights into barriers and facilitators and proposes strategic approaches to enhancing FP SDM implementation, contributing to improved quality of life for cancer survivors and advancements in clinical practice.
Socially assistive robots (SARs) have been used in group interventions for older adults; however, their effectiveness remains unclear. This systematic review aimed to synthesize evidence on the efficacy of group interventions with SARs on various outcomes (physical, cognitive, psychological, quality of life, therapeutic engagement, and sociality) for older adults, and the factors that influence their effectiveness.
A literature search was conducted using five databases (Web of Science, PubMed, Scopus, PsycINFO, and MEDLINE) in October 2024. The research team selected and analyzed the studies applying a narrative synthesis.
In all, 25 articles were identified, 15 of which were deemed of good quality. We found that companion robots are commonly used in group interventions for older adults that consist of physical, cognitive, and combined physical and cognitive activities. Insufficient evidence was identified on the effectiveness of physical interventions and groups with physical and cognitive activities on health outcomes (i.e., physical, cognitive, psychological, and quality of life). Regarding the cognitive group interventions, positive physical outcomes (i.e., improved sleep quality, decreased pulse rate, and increased pulse oximetry), improved cognitive function, positive psychological outcomes (i.e., decreased agitation, depression, anxiety, and loneliness, and increased positive emotions) were found; however, the positive effects in terms of cognitive level and certain psychological outcomes were comparable to the control groups. Mixed results were reported for quality of life in older adults. Across the three types of interventions, robots facilitated engagement and increased the sociality of most older adults. The effectiveness depended on the cognitive function of the older adults, the presence of staff, the type of robot, and the schedule of the interventions.
Research gaps have been identified, and more rigorous studies investigating the effectiveness of different types of group interventions in older adults are needed before applying SARs in group interventions on a large scale.
Given the importance of group interventions in nursing care of older adults, healthcare professionals can use socially assistive robots in such interventions to assist in caring for older adults.
Patients with advanced cancer often face numerous physical, psychological, and practical challenges from their disease and treatments, yet interventions addressing their specific unmet needs remain limited.
This study aimed to evaluate the effectiveness of a tailored psychoeducational intervention (PEI) on stress, anxiety, depression, coping, and fatigue among advanced cancer patients in Indonesia.
A randomized controlled trial was conducted from August 2022 to March 2023 in Indonesia.
A total of 151 advanced cancer patients from a referral hospital in Indonesia were randomized into intervention and control (conventional management) groups. Participants were assessed using validated questionnaires including the Depression, Anxiety, and Stress Scale (DASS-21), Fatigue Severity Scale (FSS), and Brief COPE at three time points: baseline (T0, before intervention), after first intervention (T1), and after second intervention (T2). The PEI was delivered face-to-face with telephone follow-up calls. Generalized Estimating Equations (GEE) analysis was used to evaluate the intervention's effectiveness.
The intervention was significantly associated with improved coping and reduced fatigue scores. Significant time effects were observed for depression, stress, coping, and fatigue scores. For anxiety, a significant impact was found at the second time point but not at the third, compared to the baseline. The difference-in-difference (DID) analysis revealed significant effects on coping and fatigue scores, while anxiety only showed significance at the second time point.
This study provides evidence for the potential effectiveness of PEI in improving coping strategies, relieving stress, anxiety, and depression, and reducing fatigue among advanced cancer patients in Indonesia.
The tailored PEI, including follow-up phone calls, can be independently implemented by nurses. Focusing on patients' unmet needs and spirituality, this intervention can help manage mental health issues and strengthen coping mechanisms, potentially leading to positive effects on physical conditions such as fatigue.
To identify the prevalence of musculoskeletal disorders among hospital nurses and explore their effects on productivity loss.
An analytical cross-sectional study with secondary data analysis was conducted.
Data were collected via an online survey of 607 registered nurses working in general and tertiary hospitals in South Korea. Multivariate logistic regression analysis was performed to examine the association between musculoskeletal disorders and four productivity loss indicators: absenteeism, presenteeism, perceived productivity loss, and work limitations.
Musculoskeletal disorders were highly prevalent among hospital nurses, with 83.9% of participants reporting musculoskeletal disorder symptoms in the past week. Lower back complaints had the highest prevalence. Nurses with musculoskeletal disorders were 3.74 times more likely to experience presenteeism than those without musculoskeletal disorders. They were also 3.00 times more likely to report perceived productivity loss and 2.24 times more likely to experience work limitations. However, no significant relationship was observed between musculoskeletal disorders and absenteeism.
Musculoskeletal disorders contribute to presenteeism, productivity loss, and work limitations among hospital nurses. Targeted interventions for preventing and managing musculoskeletal disorders are essential to mitigate productivity losses and improve nurses' health and job performance. Strategies such as ergonomic workplace modifications, early detection, and effective management of musculoskeletal disorders can help maintain nurses' productivity and well-being.
Addressing musculoskeletal disorders is critical for enhancing nurse productivity and for ensuring the delivery of high-quality patient care. Healthcare organizations can safeguard nurses' health and patient outcomes by reducing presenteeism and work limitations.
Dementia notably increases fall risk in older adults, leading to major injuries and considerable concerns from health-care professionals. However, comprehensive evidence regarding the prevalence, incidence rate, and moderating factors of falls in institutional settings is limited. This study aimed to evaluate the prevalence, incidence rates, and moderating factors of falls among older adults with dementia in nursing homes and dementia-specialized care units.
A meta-analysis.
We searched CINAHL, PubMed, Embase, ProQuest, Scopus, Web of Science, and PsycINFO from database inception to April 30, 2024. Older adults with dementia in nursing homes or dementia-specialized care units were included. The pooled prevalence was analyzed using a generalized linear mixed model with random effects using R software. Incidence rates were reported per person-year using comprehensive meta-analysis software. Study quality was assessed using Hoy's criteria. Variations in the pooled prevalence of falls were explored through moderator analyses.
This meta-analysis included 21 studies involving 35,449 participants. The pooled prevalence of falls was 45.6%, with subtypes showing 39.2%, 35.2%, and 29.0% among Alzheimer's dementia, vascular dementia, and mixed dementia subtypes, respectively. Falls were more prevalent in dementia-specialized care units (53.0%) than in nursing homes (42.6%). The overall incidence rate was 3.61 per person-year, higher in dementia-specialized care units (5.80) than in nursing homes (3.17). Subgroup analyses revealed higher fall prevalence in women (70.0%) than in men (30.6%). Meta-regression indicated that comorbidities, including delirium, visual impairment, and arthritis, increased fall risk.
This meta-analysis revealed a high incidence of falls in nearly half of older adults with dementia, particularly among those in dementia specialized care units.
Healthcare professionals should prioritize regular fall risk assessments, tailored interventions, and environmental safety modifications, particularly in dementia-specialized care units, to reduce fall-related injuries and improve patient outcomes.
The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool.
We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note–derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians.
Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing–driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions.
This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF.
This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.
The aim of the study was to develop a prediction model using deep learning approach to identify breast cancer patients at high risk for chronic pain.
This study was a retrospective, observational study.
We used demographic, diagnosis, and social survey data from the NIH ‘All of Us’ program and used a deep learning approach, specifically a Transformer-based time-series classifier, to develop and evaluate our prediction model.
The final dataset included 1131 patients. We evaluated the deep learning prediction model, which achieved an accuracy of 72.8% and an area under the receiver operating characteristic curve of 82.0%, demonstrating high performance.
Our research represents a significant advancement in predicting chronic pain among breast cancer patients, leveraging deep learning model. Our unique approach integrates both time-series and static data for a more comprehensive understanding of patient outcomes.
Our study could enhance early identification and personalized management of chronic pain in breast cancer patients using a deep learning-based prediction model, reducing pain burden and improving outcomes.
To utilize machine learning techniques to develop an association model linking lung cancer and environmental hormones to enhance the understanding of potential lung cancer risk factors and refine current nursing assessments for lung cancer.
This study is exploratory in nature. In Stage 1, data were sourced from a biological database, and machine learning methods, including logistic regression and neural-like networks, were employed to construct an association model. Results indicate significant associations between lung cancer and blood cadmium, urine cadmium, urine cadmium/creatinine, and di(2-ethylhexyl) phthalate. In Stage 2, 128 lung adenocarcinoma patients were recruited through convenience sampling, and the model was validated using a questionnaire assessing daily living habits and exposure to environmental hormones.
Analysis reveals correlations between the living habits of patients with lung adenocarcinoma and exposure to blood cadmium, urine cadmium, urine cadmium/creatinine, polyaromatic hydrocarbons, diethyl phthalate, and di(2-ethylhexyl) phthalate.
According to the World Health Organization's global statistics, lung cancer claims approximately 1.8 million lives annually, with more than 50% of patients having no history of smoking or non-traditional risk factors. Environmental hormones have garnered significant attention in recent years in pathogen exploration. However, current nursing assessments for lung cancer risk have not incorporated environmental hormone-related factors. This study proposes reconstructing existing lung cancer nursing assessments with a comprehensive evaluation of lung cancer risks.
The findings underscore the importance of future studies advocating for public screening of environmental hormone toxins to increase the sample size and validate the model externally. The developed association model lays the groundwork for advancing cancer risk nursing assessments.
The aims of this study are to examine the trajectories of nursing hours per patient day (NHPPD) over the course of hospitalization according to the patient's length of stay (LOS) and to estimate changes in the total nursing hours during hospitalization, average NHPPD, and the number of nurses additionally required when the LOS was reduced by 1 day.
This retrospective longitudinal study analyzed patient data collected from a tertiary university hospital located in Seoul, South Korea. The study sample included 11,316 inpatients who were discharged between September 1 and October 31, 2022.
NHPPD over the course of each patient's hospitalization was estimated using the total score of the Korean Patient Classification System-1 (KPCS-1), which nurses evaluated and recorded every day from admission to discharge. The NHPPD trajectories were examined using linear mixed models to analyze repeated KPCS-1 measurements and control for the effects of patient characteristics. The changes in the average NHPPD when LOS was reduced by 1 day were estimated using maximum and minimum estimations. The impact of a 1-day reduction in LOS on staffing requirements was calculated as the number of nurses additionally required to work each shift and to be hired.
The average LOS was 5.6 days, and the short (1–6 days) and medium (7–14 days) LOS groups accounted for 78.9% and 14.3% of patients, respectively. The NHPPD trajectories showed a “rise-peak-decline” pattern. Patients in the short LOS group received the most NHPPD on day 1 (day of admission) or day 2, whereas the NHPPD for patients in the medium LOS group peaked on days 3–6. After peaking, the NHPPD tended to decrease toward the end of hospitalization, with the least NHPPD on the day of discharge, followed by the day before discharge. When LOS was reduced by 1 day, the average NHPPD was estimated to increase by 7.7–50.0% in the maximum estimation, and 0.9–12.5% in the minimum estimation. In response to a 1-day reduction, 1.10–7.44 nurses were additionally required to care for 100 patients each shift and 5.28–35.70 additional nurses needed to be hired in the maximum estimation. In the minimum estimation, these values were 0.13–1.85 additional nurses per shift and 0.65–8.90 additional nurses to be hired, respectively.
Since NHPPD exhibited a “rise-peak-decline” trajectory, reducing the LOS by 1 day was estimated to increase the average NHPPD and lead to additional staffing requirements. The additional nurse requirement for a 1-day reduction was not constant; instead, it increased with each day subtracted from an already shorter LOS.
Sufficient nurse staffing is necessary to provide increased NHPPD as a result of shortened LOS. Changes in the LOS should be considered when determining nurse staffing requirements.
In the rapidly evolving healthcare landscape, the capacity to foster innovative work behavior among nurses is increasingly important. This study examined the dynamics between inclusive leadership, psychological safety, collectivism, and innovative work behavior among nurses.
The study used a cross-sectional, correlational design.
This study utilized data from 730 medical-surgical nurses who provided direct care to patients. Standardized instruments were used to assess key study variables. Statistical analyses, including moderated mediation regressions, were employed to investigate the complex interplay among these variables.
We found a positive association between inclusive leadership and innovative work behavior, and psychological safety mediated this relationship. Collectivism moderated inclusive leadership's direct relationship with psychological safety and its indirect relationship with innovative work behavior. The results revealed that nurses with lower levels of collectivism were more responsive to their managers' inclusive behaviors, strengthening the relation between inclusive leadership, psychological safety, and innovative work behavior.
Our findings suggest that promoting inclusive leadership behaviors among nurse managers to create a psychologically safe environment can motivate nurses to engage in innovative work behavior. However, it is also important to understand that the effectiveness of leadership may differ depending on the collectivist values of individual nurses.
Nurse managers should adopt inclusive leadership behaviors, such as valuing trust, open communication, and diversity, in order to foster psychological safety and innovative work behavior among nurses.
Inpatients need to recognize their fall risk accurately and objectively. Nurses need to assess how patients perceive their fall risk and identify the factors that influence patients' fall risk perception.
This study aims to explore the congruency between nurses' fall risk assessment and patients' perception of fall risk and identify factors related to the non-congruency of fall risk.
A descriptive and cross-sectional design was used. The study enrolled 386 patients who were admitted to an acute care hospital. Six nurses assessed the participants' fall risk. Congruency was classified using the Morse Fall Scale for nurses and the Fall Risk Perception Questionnaire for patients.
The nurses' fall risk assessments and patients' fall risk perceptions were congruent in 57% of the participants. Underestimation of the patient's risk of falling was associated with gender (women), long hospitalization period, department (orthopedics), low fall efficacy, and history of falls before hospitalization. Overestimation of fall risk was associated with age group, gender (men), department, and a high health literacy score. In the multiple logistic regression, the factors related to the underestimation of fall risk were hospitalization period and department, and the factors related to the overestimation of fall risk were health literacy and department.
Nurses should consider the patient's perception of fall risk and incorporate it into fall prevention interventions.
Nurses need to evaluate whether patients perceive the risk of falling consistently. For patients who underestimate or overestimate their fall risk, it may be helpful to consider clinical and fall-related characteristics together when evaluating their perception of fall risk.
The emergence of novel infectious diseases has amplified the urgent need for effective prevention strategies, especially ones targeting vulnerable populations such as children. Factors such as the high incidence of both emerging and existing infectious diseases, delays in vaccinations, and routine exposure in communal settings heighten children's susceptibility to infections. Despite this pressing need, a comprehensive exploration of research trends in this domain remains lacking. This study aims to address this gap by employing text mining and modeling techniques to conduct a comprehensive analysis of the existing literature, thereby identifying emerging research trends in infectious disease prevention among children.
A cross-sectional text mining approach was adopted, focusing on journal articles published between January 1, 2003, and August 31, 2022. These articles, related to infectious disease prevention in children, were sourced from databases such as PubMed, CINAHL, MEDLINE (Ovid), Scopus, and Korean RISS. The data underwent preprocessing using the Natural Language Toolkit (NLTK) in Python, with a semantic network analysis and topic modeling conducted using R software.
The final dataset comprised 509 journal articles extracted from multiple databases. The study began with a word frequency analysis to pinpoint relevant themes, subsequently visualized through a word cloud. Dominant terms encompassed “vaccination,” “adolescent,” “infant,” “parent,” “family,” “school,” “country,” “household,” “community,” “HIV,” “HPV,” “COVID-19,” “influenza,” and “diarrhea.” The semantic analysis identified “age” as a key term across infection, control, and intervention discussions. Notably, the relationship between “hand” and “handwashing” was prominent, especially in educational contexts linked with “school” and “absence.” Latent Dirichlet Allocation (LDA) topic modeling further delineated seven topics related to infectious disease prevention for children, encompassing (1) educational programs, (2) vaccination efforts, (3) family-level responses, (4) care for immunocompromised individuals, (5) country-specific responses, (6) school-based strategies, and (7) persistent threats from established infectious diseases.
The study emphasizes the indispensable role of personalized interventions tailored for various child demographics, highlighting the pivotal contributions of both parental guidance and school participation.
The study provides insights into the complex public health challenges associated with preventing and managing infectious diseases in children. The insights derived could inform the formulation of evidence-based public health policies, steering practical interventions and fostering interdisciplinary synergy for holistic prevention strategies.
Previous systematic reviews and meta-analyses have mainly focused on improvements in the number of metabolic syndrome risk factors and individual changes in each risk factor, making it challenging to examine the impact of comprehensive lifestyle modification interventions on adherence to recommended health behaviors. To address this gap, we conducted a systematic and meta-analysis aimed at identifying clinical parameter levels associated with lifestyle modification outcomes and adherence to recommended health behaviors for individuals with metabolic syndrome.
A total of seven studies retrieved from four databases (CINAHL, Medline via PubMed, American Psychological Association PsycINFO, and Embase) were included in the review. The selected studies, which demonstrated improvements in health behaviors, all included diet and exercise as main factors of comprehensive lifestyle modification in home settings.
Our findings suggest that a 6-month comprehensive intervention including diet and exercise can be effective in decreasing glucose levels and systolic blood pressure. However, given the limited available data, further studies investigating the efficacy of interventions of varying durations are needed.
Although our review included a small number of studies, comprehensive lifestyle modifications consisting of at least two components (primarily diet and exercise) can improve health behaviors and some clinical parameters among individuals with metabolic syndrome. Future studies are needed to investigate the long-term effects of lifestyle modifications on health behavior adherence and explore effective interventions to address certain clinical parameters, such as high-density lipoprotein levels. Also, we recommend using objective and quantifiable measure to compare adherence to recommended lifestyle modifications across studies.
This research provides empirical evidence of the effectiveness of comprehensive lifestyle modification and emphasizes the need to develop long-term nursing strategies in public health that can be used to effectively manage metabolic syndrome.
The COVID-19 pandemic has had a tremendous impact on healthcare systems worldwide. In particular, long-term care facilities have proved more susceptible to infection as they care for vulnerable populations at high risk of chronic illness. How this impacts the role and core competencies of health and care workers in these facilities remains less understood.
Describe how health and care workers contribute to the prevention of emerging infectious diseases in long-term care facilities.
A scoping review.
A systematic search of literature dating from 2002 to 2022 was conducted in the following databases: EMBASE, Medline (Ovid), Cochrane Library, CINAHL Plus with Full Text (EBSCOhost), Web of Science, and AgeLine. Studies were selected if they focused on health and care workers in long-term care facilities, offered a perspective on the prevention of emerging infectious diseases or infection prevention and control, and were original qualitative or quantitative studies in English. Data were extracted, cross-checked and analyzed by two researchers, and any difference in views regarding the appropriateness of literature would be resolved by consulting a third researcher. An inductive descriptive approach was applied for the analysis of results, and themes were established via consensus meetings.
A total of fourteen studies from Asia, Europe, and the Americas were included. Three themes emerged from the review: “The roles of health and care workers evolve with the times”, “The core competencies of health and care workers are essential for preventing emerging infectious diseases in long-term care facilities” and “The key to successful prevention of emerging infectious diseases in long-term care facilities is through a systematic, comprehensive effort that mobilize health and care workers at all levels”. Health and care workers had to take on increasingly complex roles and rely on their core competencies to cope with epidemic changes, and facility resources, employee quality and management models were found to have significantly improved infection prevention and control outcomes.
The roles of health and care workers are evolving, and effective infection prevention within long-term care facilities depends on their ability to perform core competencies with skill and confidence. Moreover, a systematic, comprehensive framework, for which this paper proposes three guidelines, is urgently needed to ensure consistent policy implementation within the facility as well as support and access to resources for health and care workers.
Infection prevention efforts within long-term care facilities must take into account the evolving roles of health and care workers, with a focus on guaranteeing access to resources, training and support that will help them gain the core competencies necessary for juggling those roles. In addition, there is an urgent need for research instruments that will help assess those competencies and identify areas of improvement.
Using software for self-management interventions can improve health outcomes for individuals with low back pain, but there is a dearth of research to confirm its effectiveness. Additionally, no known research has evaluated the effective elements of software-based interventions for low back pain self-management components. This study aimed to synthesize the effectiveness of software-based interventions to promote self-management health outcomes among individuals with low back pain.
A systematic review and meta-analysis was conducted.
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement, relevant studies up to July 2022 were searched via four electronic databases: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, and Web of Science.
4908 adults with low back pain who participated in 23 studies were included. Software-based interventions were effective in reducing fear avoidance (mean difference [MD] = −0.95, 95% CI: −1.45 to −0.44), pain catastrophizing (MD = −1.31, 95% CI: −1.84 to −0.78), disability (MD = −8.21, 95% CI: −13.02 to −3.39), and pain intensity (MD = −0.86, 95% CI: −1.17 to −0.55). Specifically, interventions that included an exercise component were more effective in reducing pain and disability. Additionally, cognitive behavioral therapy (CBT) intervention significantly reduced fear avoidance and pain catastrophizing but had no noticeable impact on disability and pain compared to standard treatment. The certainty of the evidence in this review varied from very low to high across outcomes. The heterogeneity of the study results was significant, suggesting that future studies in this area could optimize the design, time points, measures, and outcomes to strengthen the evidence.
Low back pain self-management interventions delivered through software-based programs effectively reduce pain intensity, disability, fear avoidance, and pain catastrophizing.
Low back pain is among the most common reasons for seeking healthcare visits. Combining exercise and counseling through soft-based programs may effectively address this issue and its associated suffering and disability.
This study aims to identify longitudinal patterns and predictors of cognitive function trajectories among Korean older adults with cardiovascular diseases.
This study is a longitudinal panel analysis based on secondary data. Data from the the Korean Longitudinal Study of Ageing (KLoSA) were used for analysis.
The KLoSA is a representative panel survey of older Koreans. We analyzed responses from 301 participants aged ≥65 years who completed the same survey more than three times out of five waves between 2012 and 2020.
Latent class growth modeling identified two trajectories of cognitive function in older people with cardiovascular diseases: “low and declining” (n = 81, 26.9%) and “high and declining” (n = 220, 73.1%). Participants in “the low and declining trajectory group” were more likely to have a low educational level, weak handgrip strength, depression, and low social participation at baseline than those in “the high and declining trajectory group.”
Our results indicate a need to develop community-based tailored interventions for improving handgrip strength, mental health, and social participation in delaying cognitive decline in older people with cardiovascular diseases considering their educational level.
Healthcare providers should be more concerned about older people with a weaker handgrip, depression, and low social activities as a high-risk group for cognitive decline over time in cardiovascular care. Therefore, it is necessary to evaluate them early with standardized tools and make subsequent strategies for the older population with cardiovascular diseases.
The literature cites many factors that influence a nurse's decision when choosing their workplace. However, it is unclear which attributes matter the most to newly graduated nurses. The study aimed to identify the relative importance of workplace preference attributes among newly graduated nurses.
A cross-sectional study.
We conducted an online survey and data were collected in June 2022. A total of 1111 newly graduated nurses in South Korea participated. The study employed best–worst scaling to quantify the relative importance of nine workplace preferences and also included questions about participants' willingness to pay for each workplace preferences. The relationships between the relative importance of the workplace attribute and the willingness to pay were determined using a quadrant analysis.
The order according to the relative importance of workplace preferences is as follows: salary, working conditions, organizational climate, welfare program, hospital location, hospital level, hospital reputation, professional development, and the chance of promotion. The most important factor, salary, was 16.67 times more important than the least important factor, the chance of promotion, in terms of choosing workplace. In addition, working conditions and organizational climate were recognized as high economic value indicators.
Newly graduated nurses nominated better salaries, working conditions, and organizational climate as having a more important role in choosing their workplace.
The findings of this study have important implications for institutions and administrators in recruiting and retaining newly graduated nurses.
This study aimed (1) to describe how trends in pediatric palliative care (PPC) utilization changed from 2002 to 2017, and (2) to examine factors predicting PPC utilization among decedent children in Taiwan.
This retrospective, correlational study retrieved 2002–2017 data from three national claims databases in Taiwan.
Children aged 1 through 18 years who died between January 2002 and December 2017 were included. Pediatric palliative care utilization was defined as PPC enrollment and PPC duration, with enrollment described by frequency (n) and percentage (%) and duration described by mean and standard deviation (SD). Logistic regression was used to examine the associations of various demographic characteristics with PPC enrollment; generalized linear regression was used to examine associations of the demographic characteristics with PPC duration.
Across the 16-year study period, PPC enrollment increased sharply (15.49 times), while PPC duration decreased smoothly (by 29.41%). Cause of death was a continuous predictor of both PPC enrollment and PPC duration. The children less likely to be enrolled in PPC services were those aged 1 to 6 years, boys, living in poverty, living in rural areas, and diagnosed with life-threatening noncancer diseases.
This study used nationwide databases to investigate PPC enrollment and PPC duration among a large sample of deceased children from 2002 to 2017. The findings not only delineate trends and predictors of PPC enrollment and PPC duration but also highlight great progress in PPC as well as the areas still understudied and underserved. This information could help the pediatric healthcare system achieve the core value of family-centered care for children with life-threatening diseases and their families.
Pediatric palliative care should be widely and continuously implemented in routine pediatric clinical practice to enhance quality of life for children and their families at the end of life.
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