Hasil untuk "Nursing"

G. Stuart

A. Meléis

N. Burns, S. Grove

Yu-Chien Ning, Xin Zhou, Francine Laden et al.

We introduce the SoftBart approach from Bayesian ensemble learning to estimate the relationship between multipollutant mixtures and health on chronic exposures in epidemiology research. This approach offers several key advantages over existing methods: (1) it is computationally efficient and well-suited for analyzing large datasets; (2) it is flexible in estimating various correlated nonlinear functions simultaneously; and (3) it accurately identifies active variables within highly correlated multipollutant mixtures. Through simulations, we demonstrate the method's superiority by comparing its accuracy in estimating and quantifying uncertainties for both main and interaction effects with the commonly used method, BKMR. Last, we apply the method to analyze a multipollutant dataset with 10,110 participates from the Nurses' Health Study.

Zohaib Hasan Siddiqui, Dayam Nadeem, Mohammad Masudur Rahman et al.

Vision language models (VLMs), such as CLIP and OpenCLIP, can encode and reflect stereotypical associations between medical professions and demographic attributes learned from web-scale data. We present an evaluation protocol for healthcare settings that quantifies associated biases and assesses their operational risk. Our methodology (i) defines a taxonomy spanning clinicians and allied healthcare roles (e.g., surgeon, cardiologist, dentist, nurse, pharmacist, technician), (ii) curates a profession-aware prompt suite to probe model behavior, and (iii) benchmarks demographic skew against a balanced face corpus. Empirically, we observe consistent demographic biases across multiple roles and vision models. Our work highlights the importance of bias identification in critical domains such as healthcare as AI-enabled hiring and workforce analytics can have downstream implications for equity, compliance, and patient trust.

Ce Yang, Ning Zhang, Jiaxuan Li et al.

Environmental epidemiologists are often interested in estimating the effect of time-varying functions of the exposure history on health outcomes. However, the individual exposure measurements that constitute the history upon which an exposure history function is constructed are usually subject to measurement errors. To obtain unbiased estimates of the effects of such mismeasured functions in longitudinal studies with discrete outcomes, a method applicable to the main study/validation study design is developed. Various estimation procedures are explored. Simulation studies were conducted to assess its performance compared to standard analysis, and we found that the proposed method had good performance in terms of finite sample bias reduction and nominal coverage probability improvement. As an illustrative example, we applied the new method to a study of long-term exposure to PM2.5, in relation to the occurrence of anxiety disorders in the Nurses Health Study II. Failing to correct the error-prone exposure can lead to an underestimation of the chronic exposure effect of PM2.5.

Muhiyadin Abdi Farah, Sahardiid Ali Abdilahi, Mohamed Omar Osman

Objective: Maintaining a balanced diet throughout pregnancy is difficult for many pregnant women, despite the fact that appropriate nutrition is crucial for the health of both the mother and child. A wide variety of foods is essential to meet the increased nutritional demands during this key period. To shed light on the factors influencing pregnant women's food choices, this study aimed to assess the prevalence of dietary practices and their determinants among pregnant women in Jigjiga, Somali Region, Ethiopia. Methods: A community-based cross-sectional study was conducted from June 1 to July 30, 2023. Pregnant women were selected using multistage sampling. Data were collected via face-to-face interviews using a structured questionnaire. Dietary diversity was assessed using a 24-h recall covering 10 food groups. Data were entered into EpiData version 7 and analyzed with SPSS version 26. Binary and multivariable logistic regression identified factors associated with dietary diversity, with odds ratios (OR) and 95% confidence intervals (CI). Statistical significance was set at P ​< ​0.05. Result: This study revealed that 178 (44.7%) pregnant women had good dietary diversity practices, and 220 (55.3%) had poor dietary diversity practices. High school diploma and above (Adjusted Odds Ratio [AOR] ​= ​6.74, 95% CI ​= ​2.12, 21.37), monthly income of ≥3000 EB (AOR ​= ​2.46, 95% CI ​= ​1.17, 5.16), two or more visits during antenatal care (ANC) follow-up (AOR ​= ​15.29, 95% CI ​= ​6.26, 37.3), and food-secured households (AOR ​= ​2.893, 95% CI ​= ​1.58, 5.29) during pregnancy were factors positively associated with good dietary diversity practices among study areas. Conclusion: Poor dietary diversity was common among pregnant women in Jigjiga. Key determinants included low education, low income, limited ANC visits, and household food insecurity. Health providers should counsel pregnant women to improve meal frequency and dietary diversity during ANC visits.

Guangyuan Chen, Zhonghua Fu, Xulin He et al.

Abstract Glioblastoma (GBM), a highly aggressive malignant brain tumor, leads to poor clinical outcomes and low long-term survival rates. Using bioinformatics approaches, we analyzed single-cell RNA sequencing (scRNA-seq) data (GSE273274) from glioma patient samples in this study. It was found that mesenchymal-like (MES-like) cells in the GBM center (GC) significantly facilitated GBM’s aggressive spread and microenvironmental reprogramming. Further analysis on MES-like cells suggested that these cells may participate in the progression from glial differentiation to invasive metastasis. Differential expression analysis, univariate Cox regression, and LASSO regression identified COL22A1 as a key gene. COL22A1 was highly expressed in GC compared to GBM surrounding tissue (GS) and exhibited potential connection to aberrant phosphatidylinositol 3-kinase (PI3K) signaling activation, indicating that COL22A1 may act as a potential regulator of GBM, promoting malignant processes such as proliferation, apoptosis resistance, migration, and invasion. In vitro experiments showed that COL22A1 overexpression (COL22A1-OE) U-87 cells exhibited enhanced proliferation, viability, migration, and invasion. Moreover, immunoblotting of BCL-2 and BAX revealed that COL22A1-OE increased resistance to apoptosis in U-87 cells. However, all these effects were reversed upon silencing of COL22A1, which suggests COL22A1 could be a promising new target for GBM therapy.

Élida de Fátima Diniz Souza, Ana Paula Ramos Machado, José Danúzio Leite de Oliveira et al.

Abstract Background In Brazil, residency programmes in Family and Community Medicine (FCM) and Multiprofessional Residency in Family Health (MRFH) are two-year specialisation courses, funded by the federal government, which aim to train professionals to work in Primary Health Care (PHC). The aim of this study was to draw up an inventory of the assessed competences of the residency programmes in the state of Paraíba, Brazil. Our study’s hypothesis is that self-assessment of competences can be a useful tool for monitoring the development of competences in the training of health professionals, contributing to the process of transitioning from academic curricula to one that is more responsive to the needs of health systems. Methods This is a cross-sectional study with a quantitative approach, in which a structured questionnaire was applied to 300 residents and preceptors from eleven FCM and MRFH residency programmes. Thirty-four professional competences were assessed, and scores were produced from the sum of the Likert scale scores, ranging from 0 to 170 points. Descriptive statistical analysis showed the frequency of residents and preceptors mastering each of the 34 competences. Bivariate analysis was used to compare the differences between these two groups (residents and preceptors) and to assess the agreement between the residents’ self-assessment and that of their preceptor’s evaluation. Results Most participants were female (69.7%), had no partner (53.7%) and no children (76%). The competency score was higher among preceptors (p = 0.003), males (p = 0.008) and those with more experience in PHC (p = 0.003). Among physicians, the median resident self-assessment score was 123, while the resident assessment by the preceptor was 140 (p < 0.001). In the case of the MFHR, there was no significant difference between the median resident self-assessment (134.5) and the resident assessment by the preceptor (130.0) (p = 0.483). Conclusions The Inventory of self-assessed competences proved to be a useful and quick tool for identifying the training strengths and weaknesses of professionals working in Primary Health Care. Clinical trial number Not applicable.

Asaf Yehudai, Taelin Karidi, Gabriel Stanovsky et al.

Cross-domain alignment refers to the task of mapping a concept from one domain to another. For example, ``If a \textit{doctor} were a \textit{color}, what color would it be?''. This seemingly peculiar task is designed to investigate how people represent concrete and abstract concepts through their mappings between categories and their reasoning processes over those mappings. In this paper, we adapt this task from cognitive science to evaluate the conceptualization and reasoning abilities of large language models (LLMs) through a behavioral study. We examine several LLMs by prompting them with a cross-domain mapping task and analyzing their responses at both the population and individual levels. Additionally, we assess the models' ability to reason about their predictions by analyzing and categorizing their explanations for these mappings. The results reveal several similarities between humans' and models' mappings and explanations, suggesting that models represent concepts similarly to humans. This similarity is evident not only in the model representation but also in their behavior. Furthermore, the models mostly provide valid explanations and deploy reasoning paths that are similar to those of humans.

Takashi Ikeda, Kazunari Ninomiya, Koji Suzuki et al.

Purpose: Frailty and sarcopenia may progressively worsen physical function, and studies have noted the frequent presence of sarcopenia in patients who undergo total hip arthroplasty (THA). This study aimed to examine the prevalence of comorbid frailty and sarcopenia in older patients undergoing THA and to determine the impact of these conditions on lower limb strength and hip function. Methods: Patients aged ≥65 years who had undergone THA at least 1 year previously were divided into five groups according to the presence and severity of frailty and sarcopenia. Lower limb strength [hip abductor (HA) and knee extensor (KE)], balance, and hip function were compared. Results: Sarcopenia and frailty affected lower limb muscle strength and hip function in a staircase-like manner, with mean ​± ​standard deviation values for the five groups as follows: HA muscle strength (in Nm/body weight), robust 0.80 ​± ​0.23, pre-frail ​+ ​non-sarcopenia 0.69 ​± ​0.17, pre-frail ​+ ​sarcopenia 0.58 ​± ​0.20, frail ​+ ​non-sarcopenia 0.54 ​± ​0.16, frail ​+ ​sarcopenia 0.50 ​± ​0.16; KE muscle strength (in kgf/body weight), robust 1.17 ​± ​0.23, pre-frail ​+ ​non-sarcopenia 1.03 ​± ​0.32, pre-frail ​+ ​sarcopenia 0.90 ​± ​0.31, frail ​+ ​non-sarcopenia 0.84 ​± ​0.27, frail ​+ ​sarcopenia 0.74 ​± ​0.21; and Harris Hip Score, robust 96.8 ​± ​4.6, pre-frail ​+ ​non-sarcopenia 94.3 ​± ​7.9, pre-frail ​+ ​sarcopenia 88.6 ​± ​9.6, frail ​+ ​non-sarcopenia 87.5 ​± ​10.3, frail ​+ ​sarcopenia 83.5 ​± ​8.6. Conclusion: Progression of sarcopenia and frailty affects lower limb muscle strength and physical function in a staircase-like fashion, suggesting the need to assess the cumulative effects of the two. Among this population, rather than interventions to improve muscle strength and balance in specific areas, interventions to maintain a comprehensive level of physical fitness and muscle mass (including nutrition and lifestyle changes) may be necessary.

Linda Nchabeleng, Mamare A. Bopape, Ledile E. Manamela et al.

Background: The Nursing Education Programme was affected during the coronavirus disease 2019 (COVID-19) pandemic, resulting in nursing students being unable to participate in the clinical experiential learning required by the South African Nursing Council. Objectives: The study seeks to explore and describe nursing students’ experiences of clinical experiential learning during the COVID-19 pandemic. Method: A qualitative, explorative and descriptive, research design was used in the study. A non-probability purposive sampling method was used, and 55 nursing students participated in the study. Data were collected through six focus group discussions, consisting of 8–12 nursing students in each group. Data were analysed following Tesch’s open coding method. Results: Three themes emerged from the study’s findings: The impact of COVID-19 on the clinical experiential learning of nursing students, the effects of COVID-19 on the mental well-being of nursing students, and nursing students’ experiences of support during the COVID-19 pandemic. Notably, 11 sub-themes emerged. Conclusion: The findings of this study reveal that the COVID-19 pandemic severely disrupted the Nursing Education Programme, highlighting the challenges of inadequate clinical hours, restricted clinical access and the significant psychological impact on students. Contribution: This study adds to the literature on students’ experiences during clinical experiential learning in South Africa during the COVID-19 pandemic.

Christine Webb, J. Kevern

Chengpiao Huang, Kaizheng Wang

We develop a versatile framework for statistical learning in non-stationary environments. In each time period, our approach applies a stability principle to select a look-back window that maximizes the utilization of historical data while keeping the cumulative bias within an acceptable range relative to the stochastic error. Our theory showcases the adaptivity of this approach to unknown non-stationarity. We prove regret bounds that are minimax optimal up to logarithmic factors when the population losses are strongly convex, or Lipschitz only. At the heart of our analysis lie two novel components: a measure of similarity between functions and a segmentation technique for dividing the non-stationary data sequence into quasi-stationary pieces. We evaluate the practical performance of our approach through real-data experiments on electricity demand prediction and hospital nurse staffing.

Jooyoung Lee, Zhibing He, Charlotte Roscoe et al.

In environmental health research, it is of interest to understand the effect of the neighborhood environment on health. Researchers have shown a protective association between green space around a person's residential address and depression outcomes. In measuring exposure to green space, distance buffers are often used. However, buffer distances differ across studies. Typically, the buffer distance is determined by researchers a priori. It is unclear how to identify an appropriate buffer distance for exposure assessment. To address geographic uncertainty problem for exposure assessment, we present a domain selection algorithm based on the penalized functional linear Cox regression model. The theoretical properties of our proposed method are studied and simulation studies are conducted to evaluate finite sample performances of our method. The proposed method is illustrated in a study of associations of green space exposure with depression and/or antidepressant use in the Nurses' Health Study.

Yujie Wu, Molin Wang

In epidemiological studies, participants' disease status is often collected through self-reported outcomes in place of formal medical tests due to budget constraints. However, self-reported outcomes are often subject to measurement errors, and may lead to biased estimates if used in statistical analyses. In this paper, we propose statistical methods to correct for outcome measurement errors in survival analyses with multiple failure types through a reweighting strategy. We also discuss asymptotic properties of the proposed estimators and derive their asymptotic variances. The work is motivated by Conservation of Hearing Study (CHEARS) which aims to evaluate risk factors for hearing loss in the Nurses' Health Studies II (NHS II). We apply the proposed method to adjust for the measurement errors in self-reported hearing outcomes; the analysis results suggest that tinnitus is positively associated with moderate hearing loss at both low or mid and high sound frequencies, while the effects between different frequencies are similar.

Aaron T. Seaman, Julia H. Rowland, Samantha J. Werts et al.

Introduction: Cancer rates increase with age, and older cancer survivors have unique medical care needs, making assessment of health status and identification of appropriate supportive resources key to delivery of optimal cancer care. Comprehensive geriatric assessments (CGAs) help determine an older person’s functional capabilities as cancer care providers plan treatment and follow-up care. Despite its proven utility, research on implementation of CGA is lacking.Methods: Guided by a qualitative description approach and through interviews with primary care providers and oncologists, our goal was to better understand barriers and facilitators of CGA use and identify training and support needs for implementation. Participants were identified through Cancer Prevention and Control Research Network partner listservs and a national cancer and aging organization. Potential interviewees, contacted via email, were provided with a description of the study purpose. Eight semi-structured interviews were conducted via Zoom, recorded, and transcribed verbatim by a professional transcription service. The interview guide explored providers’ knowledge and use of CGAs. For codebook development, three representative transcripts were independently reviewed and coded by four team members. The interpretive process involved reflecting, transcribing, coding, and searching for and identifying themes.Results: Providers shared that, while it would be ideal to administer CGAs with all new patients, they were not always able to do this. Instead, they used brief screening tools or portions of CGAs, or both. There was variability in how CGA domains were assessed; however, all considered CGAs useful and they communicated with patients about their benefits. Identified facilitators of implementation included having clinic champions, an interdisciplinary care team to assist with implementation and referrals for intervention, and institutional resources and buy-in. Barriers noted included limited staff capacity and competing demands on time, provider inexperience, and misaligned institutional priorities.Discussion: Findings can guide solutions for improving the broader and more systematic use of CGAs in the care of older cancer patients. Uptake of processes like CGA to better identify those at risk of poor outcomes and intervening early to modify treatments are critical to maximize the health of the growing population of older cancer survivors living through and beyond their disease.

Zhen Li, Changcheng Wu, Li-An Tang et al.

Metagenomic next-generation sequencing (mNGS) has been widely applied to identify pathogens associated with infectious diseases. However, limited studies have explored the use of mNGS-based dynamic pathogen monitoring in intensive care unit patients with severe pneumonia. Here, we present a clinical case of an 86-year-old male patient with severe pneumonia caused by a fungal infection. During the clinical treatment, four mNGS analyses were performed within two consecutive weeks. Various respiratory fungal pathogens, including Candida orthopsilosis, Candida albicans, and Aspergillus fumigatus were detected by mNGS of bronchoalveolar lavage fluid (BALF). Based on conventional pathogen identification and clinical symptoms, the patient was diagnosed with severe pneumonia caused by a fungal infection. The abundance of fungal species decreased gradually in response to antifungal and empirical therapies, and the fungal infections were effectively controlled. In summary, our results demonstrated that mNGS could effectively identify pathogens in patients with severe pneumonia. Additionally, dynamic pathogen monitoring based on mNGS could assist in the precise diagnosis of complex infections and may facilitate rapid induction of the most appropriate therapy.

W. Molloy, G. Guyatt, R. Russo et al.

Bayan Alilyyani

Background: Nurse leaders have the responsibility to build healthy work environments for staff nurses and enhance nurses’ outcomes. Authentic leadership is one of the leadership theories that have been shown to have positive impacts on nurses’ outcomes. The goal of this study was to test the effect of authentic leadership on trust in managers and job performance among nurses in Saudi Arabia. Methods: A non-experimental, cross-sectional design was applied. A total of 116 nurses who met the inclusion criteria completed the survey. To test the study variables, three different scales were used. The data in this study were analyzed using SPSS version 28.0.1.1. Results: The findings of this study showed that there were significant and positive effects of authentic leadership and its four components on trust in managers. However, no relationships were found between authentic leadership and its four elements, and job performance. Conclusions: Authentic leaders have the ability to improve work environments by building a trustful relationship with nurses. This study focuses on the role of authentic leadership in nursing practice and its essential effects to enhance the work environments. It also provides future researchers in Saudi Arabia with comprehensive knowledge about conducting studies of authentic leadership in nursing and examine its effects on outcomes related to nurses.