Nursing Research最新文献

{"title":"Mediation of Smoking and Cardiometabolic Factors on Diabetic Peripheral Neuropathy.","authors":"Siti Fadlilah, Untung Sujianto, Ratsiri Thato, Mei-Ling Yeh, Hsiu Ting Tsai","doi":"10.1097/NNR.0000000000000943","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000943","url":null,"abstract":"<p><strong>Background: </strong>Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes, yet the combined roles of smoking behavior and cardiometabolic factors in shaping neuropathy risks remain insufficiently understood.</p><p><strong>Objectives: </strong>To examine the associations of smoking behavior and cardiometabolic factors with DPN risk and evaluate their independent, combined, and mediating effects.</p><p><strong>Methods: </strong>This cross-sectional study included 905 adults with type 2 diabetes attending primary care services in Indonesia. DPN risk was assessed using the Michigan Neuropathy Screening Instrument. Tobacco smoking behavior was assessed using a structured questionnaire, while cardiometabolic factors were obtained from clinical examinations and laboratory measurements. Associations were analyzed using multinomial logistic regression, and mediation pathways were examined using partial least squares-structural equation modeling.</p><p><strong>Results: </strong>Both active smoking and secondhand smoke exposure were associated with an increased DPN risk, particularly among active smokers also exposed to secondhand smoke. Cardiometabolic factors, including elevated glycated hemoglobin, high fasting blood glucose, and an abnormal ankle-brachial index, showed independent associations with neuropathy risks. Combined exposure analyses demonstrated a cumulative pattern, with increasing numbers of abnormal risk factors associated with progressively higher odds of neuropathy. A pathway analysis indicated that the association between smoking behaviors and DPN was primarily mediated through metabolic dysfunction and impaired peripheral perfusion, whereas the mediating role of blood pressure was limited.</p><p><strong>Discussion: </strong>These findings support the multifactorial nature of DPN and suggest that behavioral and cardiometabolic factors interact in shaping neuropathy risks. Integrating smoking exposure assessments with glycemic and vascular risk management may strengthen prevention strategies in primary care populations with type 2 diabetes.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148809270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Considerations for Research Reproducibility: Strategies for Building Transparent Analytic Workflows.","authors":"Laura K Kaizer, Zahra Ali, Grace N Bosma, Dawn M Aycock, Matthew J Hayat, Sarah J Schmiege","doi":"10.1097/NNR.0000000000000940","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000940","url":null,"abstract":"<p><strong>Background: </strong>Reproducibility, the ability for independent investigators to obtain consistent results using the same data and analytic procedures, is foundational to scientific integrity, yet remains a challenge across research settings. Common practices such as manual data cleaning, point-and-click analyses, and creating tables by manually copying and pasting values from output to table shells increase the likelihood of error, reduce transparency, and impede efficient collaboration. As data become more complex and expectations for reproducibility from journals, funders, and the scientific community grow, researchers need practical, accessible guidance on implementing reproducible workflows.</p><p><strong>Objectives: </strong>To provide actionable steps to improve the reproducibility of data management, statistical analyses, and reporting, and demonstrate reproducible workflows using both R and IBM SPSS Statistics.</p><p><strong>Methods: </strong>We outline five steps toward reproducibility: (1) project organization and file structure, (2) use of ReadME documentation, (3) clear traceability from raw to analytic data sets, (4) use of syntax for all data cleaning and management, and (5) reproducible generation of tables and reports. A synthetic data set is used to illustrate these principles in both R and SPSS, highlighting how fully syntax-based workflows in R and syntax-supported workflows in SPSS can move researchers toward greater transparency and efficiency.</p><p><strong>Results: </strong>Implementing reproducible workflows reduces error, saves time, and strengthens scientific rigor. Syntax-based approaches create a complete, defensible record of every analytic decision, supporting clearer team communication and easier project hand off. Even small changes, such as maintaining untouched raw data, standardizing folder structures, and documenting decisions in ReadMe files, substantially improve transparency. Across platforms, the guiding principle holds: anything that is done manually can be done with syntax, enabling faster, more accurate, and fully repeatable results.</p><p><strong>Discussion: </strong>Reproducibility is both an ethical and methodological imperative. Incremental improvements can reshape research culture, producing more trustworthy work. Integrating reproducibility into education, mentorship, and team science can help ensure that rigorous, transparent analytic practices become standard in research.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148800873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vibe Coding for Statistical Analysis Using Large Language Models.","authors":"Dante Anthony Tolentino, Elizabeth Kohout, Paul Boy, Hafifa Siddiq","doi":"10.1097/NNR.0000000000000942","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000942","url":null,"abstract":"<p><strong>Background: </strong>Large language models have accelerated the adoption of generative artificial intelligence (AI), making AI tools more widely accessible through conversational prompting. One emerging application is vibe coding, in which users use natural-language prompts to generate code and desired outputs rather than manually writing traditional code.</p><p><strong>Objective: </strong>To examine AI-assisted, human-in-the-loop (HITL) vibe coding as a proof of concept for data analysis, describe its components and a proposed workflow with explicit safeguards, and present a case study illustrating its use and potential failure points.</p><p><strong>Methods: </strong>We used a proposed workflow that included framing research questions, operationalizing variables, organizing project folders, documenting decisions, applying retrieval-augmented generation, and using prompt engineering techniques. We used Cursor (v1.5.11) on a limited, clean admissions data set, in which admission status was modeled as a function of the Graduate Record Exam, grade point average, and undergraduate rank. Logistic regression was generated via conversational prompts, implemented in R, and the results were compared with a published reference output on a publicly available website.</p><p><strong>Results: </strong>AI-assisted, HITL vibe coding produced statistical codes that included schema checks, range validations, data cleaning, exploratory analyses, regression modeling, and visualization. There were mixed results of both valid and invalid outputs. Regression coefficients, p values, and model fit statistics matched the outputs posted on the published reference output website. However, an error was identified in the predicted-probability confidence interval output, which was missed during the initial review of outputs.</p><p><strong>Discussion: </strong>While vibe coding has the potential to reduce barriers to data analysis for researchers, this case study demonstrated that it can produce both valid and invalid outputs and that foundational statistical training, knowledge, understanding, and methodological expertise remain paramount when using it. Future studies should address important empirical questions about the use of vibe coding, such as under what conditions it can be safely used in research and what kinds of errors are most commonly generated when using it. AI-assisted HITL vibe coding should be used with caution and only with structured verification and safeguards, transparent reporting, and appropriate statistical and methodological oversight.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148800892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence, Sociodemographic Differences, and Comorbidity in Pediatric Obesity.","authors":"Maharaj Singh, Sylvia Peña, Wendy Bauer, Abir Bekhet, Maria Peña, Kristin Haglund, Shanna Doucette Knierim, Marilyn Frenn","doi":"10.1097/NNR.0000000000000941","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000941","url":null,"abstract":"<p><strong>Background: </strong>Pediatric obesity is a major public health concern with important implications for acute care and long-term health outcomes. National estimates of obesity among hospitalized children using recent data are limited.</p><p><strong>Objectives: </strong>To estimate the prevalence of documented obesity among hospitalized children and examine associated sociodemographic differences and comorbidity patterns using the 2021 National Inpatient Sample.</p><p><strong>Methods: </strong>We conducted a cross-sectional analysis of pediatric discharges (ages 2-17 y) in the 2021 National Inpatient Sample. Obesity was defined using the International Classification of Diseases, 10th Revision, Clinical Modification codes. Survey-weighted analyses were used to estimate prevalence and examine comorbidity patterns. Multivariable logistic regression models were used to evaluate sociodemographic correlates of obesity.</p><p><strong>Results: </strong>Among an estimated 961,529 pediatric hospitalizations, 6.29% had a documented obesity diagnosis. Obesity prevalence was higher among Black, Hispanic, and Native American children and increased with decreasing neighborhood income. In adjusted analyses, older age and Medicaid coverage were associated with higher odds of obesity, while females had lower odds than males. Children with obesity had substantially higher prevalence of cardiometabolic, respiratory, and mental health comorbidities compared with nonobese children.</p><p><strong>Discussion: </strong>Pediatric obesity among hospitalized children is associated with significant sociodemographic disparities and a high burden of comorbidities. Hospitalization represents a vital opportunity for identification and linkage to care.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148800863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerated Biological Age as an Early Pregnancy Risk Factor for Preeclampsia.","authors":"Cindy M Anderson, John Lesniak, Shannon L Gillespie, Joyce E Ohm, Joshua J Joseph, Nathan P Helsabeck, Shili Lin","doi":"10.1097/NNR.0000000000000937","DOIUrl":"10.1097/NNR.0000000000000937","url":null,"abstract":"<p><strong>Background: </strong>The inability to predict risk in early pregnancy for preeclampsia represents a major limitation in prenatal care.</p><p><strong>Objectives: </strong>We used machine-learning approaches to identify early pregnancy features that distinguish women who develop preeclampsia from those with normotensive pregnancies, specifically focusing on the influence of maternal biological age.</p><p><strong>Methods: </strong>Data were analyzed from a prospective cohort of pregnant women living in the upper Midwest (Midwest cohort) and from a cohort using publicly available data from the Prenatal Exposures & Preeclampsia Prevention Project (PEPP3). In both data sets, DNA methylation (DNAm) was quantified from blood samples collected in early pregnancy. Biological aging was estimated using established epigenetic clocks including Hannum, Horvath, and PhenoAge. Maternal data across pregnancy were collected via medical record abstraction. Predictors of preeclampsia were identified using LASSO regression and Random Forest. The potential predictive capacity of the selected features was evaluated by building logistic regression models with leave-one-out cross-validation and reporting performance metrics.</p><p><strong>Results: </strong>In the Midwest cohort, accelerated biological aging per Hannum's epigenetic clock as well as higher chronological age and higher gestational weight gain were identified as important predictors of preeclampsia. Interestingly, only Hannum's epigenetic clock showed predictive power for preeclampsia. In the PEPP3 cohort, accelerated biological aging, as measured by Hannum's epigenetic clock, and chronological age were also identified as significant predictors of preeclampsia.</p><p><strong>Discussion: </strong>Among women who developed preeclampsia, accelerated biological aging during early pregnancy may represent a risk biomarker that can be leveraged in clinical care. These findings identify a promising clinical indicator for preeclampsia risk, addressing a critical gap in screening and early diagnosis.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148702432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disaggregating 15-Year Trends in Cardiovascular Risk among U.S. Asian Subgroups.","authors":"Xiaoyue Liu, Emerson Ea, Gail Melkus, Arum Lim, Chitchanok Benjasirisan, Binu Koirala, Tiwaloluwa Ajibewa, Bei Wu","doi":"10.1097/NNR.0000000000000936","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000936","url":null,"abstract":"<p><strong>Background: </strong>Asian adults in the U.S. face increased burdens of cardiovascular risk factors and cardiovascular disease (CVD). However, trends in cardiovascular health among Asian subgroups remain understudied.</p><p><strong>Objectives: </strong>The purpose of this study was to examine 15-year trends in CVD risk factors and CVD among Chinese, Filipino, and Asian Indian adults living in the U.S.</p><p><strong>Methods: </strong>We conducted a retrospective secondary analysis using data from the 2004-2018 National Health Interview Survey. Age-standardized prevalence rates were calculated for eight variables: hypertension, type 2 diabetes, overweight/obesity, short sleep, alcohol use, smoking, insufficient physical activity (PA), and CVD (defined as having coronary heart disease, heart attack, stroke, or other cardiovascular conditions). Annual percent change and average annual percent change were employed to summarize and compare the trends of each variable over 15 years.</p><p><strong>Results: </strong>The sample consisted of 14,073 adults, with the majority aged 65 years or older and half being female. Filipino adults showed the highest prevalence for most variables, except for diabetes and insufficient PA, compared to Chinese and Asian Indian adults. From 2004 to 2018, Asian adults overall experienced increases in the prevalence of diabetes, overweight/obesity, and alcohol use, and decreases in the prevalence of smoking and insufficient PA. Specifically, Chinese adults exhibited significant upward trends in short sleep. Asian Indian adults exhibited upward trends in overweight/obesity and alcohol use, but downward trends in smoking and insufficient PA. Filipino adults demonstrated similar trends to Asian Indian adults in alcohol use and smoking. No significant trends were found for other study variables in all three groups.</p><p><strong>Discussion: </strong>U.S. Asian adults from different cultural backgrounds experience varying patterns of cardiovascular health. Public health strategies are recommended to be customized to address the specific cardiovascular risk profiles of each Asian subgroup.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing a Cut Point for the Control Attitudes Scale-Revised in an International Sample of Patients With Cardiac Disease.","authors":"Debra K Moser, Ashmita Thapa, Xiuzhen Fan, Miyuki Makaya, Abigail Latimer, Misook Lee Chung, Jia-Rong Wu","doi":"10.1097/NNR.0000000000000934","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000934","url":null,"abstract":"<p><strong>Background: </strong>Perceived control is a construct relevant to emotional and clinical outcomes among individuals with chronic illnesses. We previously demonstrated the reliability and validity of the Control Attitudes Scale-Revised (CAS-R), and it has been used extensively in research to measure perceived control. Yet, there is a gap in interpretation of CAS-R scores. A standardized cut point has not yet been established to facilitate classification of patients into distinct high- and low-perceived control categories. Identifying this cut-off point will be of significant value to clinicians and researchers.</p><p><strong>Objectives: </strong>To identify an evidence-based cut point for the CAS-R to define lower and higher levels of perceived control among patients with a variety of cardiac diagnoses.</p><p><strong>Methods: </strong>In this psychometric secondary analysis, we used data from patients with heart failure or coronary heart disease, which included 4,555 patients from three countries. Data were collected on perceived control, depression and/or anxiety, and/or cardiac events (cardiac hospitalization and cardiac death). We used receiver operating characteristic (ROC) curves and area under the ROC area under the curve (AUC) to test the accuracy of using the CAS-R scores to separate the patients into anxious or non-anxious groups and depressed or non-depressed groups. Kaplan-Meier plots with log-rank tests and Cox-survival analyses were used to compare cardiac event-free survival outcomes between higher and lower perceived control groups.</p><p><strong>Results: </strong>Two possible cut points were identified using ROC curves and AUC. Cut points were identified using anxiety or depression as the state variable and CAS-R scores as the test variable. Using Kaplan-Meier analyses and log-rank tests, we determined that 29 was the cut point that demonstrated patients in the higher CAS-R group had significantly better cardiac event-free survival than those in the lower CAS-R group. Using the cut point of 30, the differences in cardiac event-free survival between groups did not reach a significant level.</p><p><strong>Discussion: </strong>Identifying a CAS-R cut point enhances the practical application of the CAS-R and makes it a valuable instrument for assessing the effect of targeted interventions among cardiac patients with lower perceived control.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148690265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised Learning Identifies Sleep Disturbance Subtypes Among Dementia Caregivers.","authors":"Eunbee Angela Kim, Jiuchen Zhang, Amir M Rahmani, Sanghyuk Shin, Adeline Nyamathi, Jung-Ah Lee","doi":"10.1097/NNR.0000000000000935","DOIUrl":"10.1097/NNR.0000000000000935","url":null,"abstract":"<p><strong>Background: </strong>Sleep disturbance is highly prevalent among caregivers of persons with dementia (PWD), affecting approximately 67% of the more than 10 million adults in this role in the United States. Accurately characterizing these disturbances is essential to identify individuals at increased risk for chronic sleep problems and related health consequences. However, few studies have examined how sleep disturbance manifests across diverse caregiver characteristics and contexts.</p><p><strong>Objectives: </strong>To address this gap, we applied clustering analyses using wearable sleep data to identify distinct subtypes of sleep disturbance among dementia caregivers.</p><p><strong>Methods: </strong>Clustering analyses were conducted using sleep parameters-total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), and sleep onset latency (SOL)-derived from 14 days of Oura Ring data collected from 143 caregivers of PWD. For each participant, the minimum, maximum, mean, and standard deviation of each sleep metric were computed during the 14-day period. Subsequent one-way ANOVA and chi-square tests were performed to explore differences in caregiver characteristics, caregiving demands, and caregiving support availability across the identified subgroups.</p><p><strong>Results: </strong>The analytic sample included 143 adults. Three distinct sleep disturbance subtypes emerged. Cluster 1 (Optimal Sleep) demonstrated the least nocturnal wakefulness, the most efficient sleep, and ease in falling asleep relative to the other clusters. Cluster 2 (Disturbed Onset & Maintenance) exhibited the greatest difficulty both falling and staying asleep, whereas Cluster 3 (Insufficient Sleep) was characterized by markedly reduced sleep duration. Key contextual characteristics differentiated the clusters. Cluster 2 had the highest prevalence of comorbid conditions, including hypertension, diabetes, and other chronic illnesses, whereas Cluster 3 was predominantly male and had the lowest support availability.</p><p><strong>Discussion: </strong>Findings highlight the potential of wearable-derived nocturnal data to characterize distinct sleep disturbance subtypes using clustering analyses. This work underscores the value of building a risk-profiling framework that integrates sleep disturbance subtypes, caregiver characteristics, caregiving demands, and caregiving support availability to inform the development of more precise and effective sleep interventions for dementia caregivers.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13551671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Randomized Controlled Trial Nurse-Led, Home Lymphatic Exercises on Fluid Overload with Heart Failure.","authors":"Rida Gharzeddine, Brigitte Cypress, Elizabeth Cerceo, Timothy Marks, Mei Rosemary Fu","doi":"10.1097/NNR.0000000000000932","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000932","url":null,"abstract":"<p><strong>Background: </strong>Fluid overload is a major contributor to symptoms and hospitalization in patients with heart failure (HF). Home-based exercise interventions designed to enhance lymphatic drainage may reduce thoracic congestion and fluid overload symptoms, yet limited research has investigated the effectiveness of these exercises using objective measures of thoracic fluid content and body water composition in this population.</p><p><strong>Objective: </strong>To evaluate the effectiveness of The-Optimal-Lymph-Flow (TOLF) intervention, a nurse-led, home-based, and structured exercise program designed to enhance lymphatic drainage and fluid overload, in patients with HF.</p><p><strong>Methods: </strong>A parallel randomized clinical trial design was used. A total of 80 participants were recruited, randomly assigned to either the TOLF intervention or usual care and followed for 4 weeks. Primary outcomes included thoracic fluid content measured by a dielectric sensing device; total body water and extracellular water measured by a bioimpedance device; fluid overload symptom prevalence and burden assessed using a self-reported questionnaire; and hospital readmission rates. Mixed-effects models were used to estimate treatment effects, adjusting for health behaviors.</p><p><strong>Results: </strong>Compared with the control group, participants receiving the TOLF intervention demonstrated significantly greater reductions in thoracic fluid content at 4 weeks post-intervention. Significant treatment effects were also observed for fluid overload symptom prevalence and symptom burden. These effects remained substantial after adjustment for health behaviors. A sizable reduction in rehospitalization rates was observed in participants receiving intervention. No significant treatment effects were observed for body water composition, although within-group reductions were noted in the intervention arm. In addition, findings also demonstrated feasibility and acceptability with 79% retention, > 80% protocol adherence, and 98% participant satisfaction.</p><p><strong>Discussion: </strong>The home-based lymphatic exercise intervention is effective in reducing thoracic congestion, fluid overload symptoms, and hospital readmission. These findings align with the emerging evidence supporting the role of lymphatic system in HF and warrant further evaluation in a larger trial.</p>","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148702474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENRS President's Message.","authors":"","doi":"10.1097/NNR.0000000000000925","DOIUrl":"https://doi.org/10.1097/NNR.0000000000000925","url":null,"abstract":"","PeriodicalId":49723,"journal":{"name":"Nursing Research","volume":"75 4","pages":"E214-E215"},"PeriodicalIF":2.5,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148310146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}