Cin-Computers Informatics Nursing最新文献

Predicting Sleep Quality in Family Caregivers of Dementia Patients From Diverse Populations Using Wearable Sensor Data.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-16 DOI: 10.1097/CIN.0000000000001192

Jung In Park, Seyed Amir Hossein Aqajari, Amir M Rahmani, Jung-Ah Lee

{"title":"Predicting Sleep Quality in Family Caregivers of Dementia Patients From Diverse Populations Using Wearable Sensor Data.","authors":"Jung In Park, Seyed Amir Hossein Aqajari, Amir M Rahmani, Jung-Ah Lee","doi":"10.1097/CIN.0000000000001192","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001192","url":null,"abstract":"This study aimed to use wearable technology to predict the sleep quality of family caregivers of people with dementia among underrepresented groups. Caregivers of people with dementia often experience high levels of stress and poor sleep, and those from underrepresented communities face additional burdens, such as language barriers and cultural adaptation challenges. Participants, consisting of 29 dementia caregivers from underrepresented populations, wore smartwatches that tracked various physiological and behavioral markers, including stress level, heart rate, steps taken, sleep duration and stages, and overall daily wellness. The study spanned 529 days and analyzed data using 70 features. Three machine learning algorithms-random forest, k nearest neighbor, and XGBoost classifiers-were developed for this purpose. The random forest classifier was shown to be the most effective, boasting an area under the curve of 0.86, an F1 score of 0.87, and a precision of 0.84. Key findings revealed that factors such as wake-up stress, wake-up heart rate, sedentary seconds, total distance traveled, and sleep duration significantly correlated with the caregivers' sleep quality. This research highlights the potential of wearable technology in assessing and predicting sleep quality, offering a pathway to creating targeted support measures for dementia caregivers from underserved groups. The study suggests that such technology can be instrumental in enhancing the well-being of these caregivers across diverse populations.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830764","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}

引用次数: 0

Visualized Pattern-Based Hypothesis Testing on Exhaustion, Resilience, Sleep Quality, and Sleep Hygiene in Middle-Aged Women Transitioning Into Menopause or Postmenopause. 对进入更年期或更年期后的中年女性的疲惫、恢复力、睡眠质量和睡眠卫生进行可视化模式假设检验。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-11 DOI: 10.1097/CIN.0000000000001215

Mi Yang Jeon, Seonah Lee

{"title":"Visualized Pattern-Based Hypothesis Testing on Exhaustion, Resilience, Sleep Quality, and Sleep Hygiene in Middle-Aged Women Transitioning Into Menopause or Postmenopause.","authors":"Mi Yang Jeon, Seonah Lee","doi":"10.1097/CIN.0000000000001215","DOIUrl":"10.1097/CIN.0000000000001215","url":null,"abstract":"Exploratory data analysis involves observing data in graphical formats before making any assumptions. If interesting relationships or patterns among variables are identified, hypotheses are developed for further testing. This study aimed to identify significant differences in the levels of exhaustion, resilience, sleep quality, and sleep hygiene according to the personal characteristics of middle-aged women transitioning into menopause or postmenopause through exploratory data analysis. A total of 200 women aged 44 to 55 years were recruited online in August 2023. Data were collected using valid instruments and analyzed through data visualization, pattern identification in the visualized data, and hypothesis establishment based on the visualized patterns. Hypotheses were tested through the independent-samples t test, analysis of variance, and the Kruskal-Wallis test. A total of 11 patterns and corresponding hypotheses were identified. According to the statistically supported pattern-based hypotheses, middle-aged women who were in their perimenopausal period perceived themselves as unhealthy, had professional occupations, and had the highest level of exhaustion and the lowest levels of resilience, sleep quality, and sleep hygiene. This study demonstrated that data visualization is an efficient way to explore relationships or patterns between data. Data visualization should be considered an informatics solution that can provide insight in the field of healthcare.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142741181","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}

引用次数: 0

Data Trauma: A Concept Analysis.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-11 DOI: 10.1097/CIN.0000000000001218

Erica Smith, Darryl Somayaji

{"title":"Data Trauma: A Concept Analysis.","authors":"Erica Smith, Darryl Somayaji","doi":"10.1097/CIN.0000000000001218","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001218","url":null,"abstract":"Today's healthcare landscape is becoming increasingly data-centric, with artificial intelligence and advanced computer algorithms becoming inextricably embedded in patient care. Although these technologies promise to make care more efficient and effective, they heighten the risk for unintended consequences. Using Walker and Avant's framework for concept analysis, we propose and explicate the emerging concept of iatrogenic data trauma, or ways in which the collection, storage, and use of sensitive and potentially stigmatizing patient data can cause harm. We conducted a careful and exhaustive review of traditional academic publications, as well as nontraditional digital sources to generate a rich and intersectional corpus of information pertaining to data justice, digital rights, and potential risks associated with the \"datafication\" of individuals. Using evidence synthesis and practical examples, we discuss how flawed data processes in healthcare settings can lead to data trauma among patients and explore how its presence can perpetuate health disparities, marginalization, loss of privacy, and breach of trust in patient-provider relationships. We discuss how this phenomenon arises and manifests across the healthcare continuum and is an important issue for professionals in multiple disciplines. We conclude by suggesting future opportunities for research through a trauma-informed lens.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142814959","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}

引用次数: 0

Examining the Role of System Acceptance and Community Feeling in Predicting Nursing Students' Online Learning Satisfaction.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-06 DOI: 10.1097/CIN.0000000000001228

Nesrin Çunkuş Köktaş, Gülseren Keskin, Gülay Taşdemir

{"title":"Examining the Role of System Acceptance and Community Feeling in Predicting Nursing Students' Online Learning Satisfaction.","authors":"Nesrin Çunkuş Köktaş, Gülseren Keskin, Gülay Taşdemir","doi":"10.1097/CIN.0000000000001228","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001228","url":null,"abstract":"Online learning has transitioned from being optional to a mandatory experience in nursing education. Consequently, it is crucial to understand nursing students' satisfaction and the factors influencing it to create and implement a successful online learning environment. This study aimed to examine the roles of system acceptance and community feeling in predicting nursing students' online learning satisfaction. The sample of the relational and cross-sectional study consisted of 451 nursing students studying online in the two universities in Western Turkey. Data were collected using the Personal Information Form, Online Learning Systems Acceptance, Community Feeling Scale, and Satisfaction Scale. A positive correlation was found between the perceived ease and benefit variables and satisfaction levels of nursing students in the study within the scope of online learning systems acceptance. A positive correlation was found between the actional and affective components of community feeling and satisfaction levels of nursing students in the study. Besides, the affective component was found to be the most significant factor in explaining satisfaction with online learning. The learning environment can be improved by increasing the diversity and interaction of nursing students with methods or instruments such as online collaborative learning approaches and online community building.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142803028","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}

引用次数: 0

Implementation of Diabetic Remote Patient Monitor for Underserved Population.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-06 DOI: 10.1097/CIN.0000000000001236

Tonya Judson, Bela Patel, Alison Hernandez, Michele Talley

引用次数: 0

Needs Assessment of Virtual Nursing Implementation Using the Donabedian Framework.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-05 DOI: 10.1097/CIN.0000000000001229

Saif Khairat, Jennifer Morelli, Barbara S Edson, Julia Aucoin, Cheryl B Jones

{"title":"Needs Assessment of Virtual Nursing Implementation Using the Donabedian Framework.","authors":"Saif Khairat, Jennifer Morelli, Barbara S Edson, Julia Aucoin, Cheryl B Jones","doi":"10.1097/CIN.0000000000001229","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001229","url":null,"abstract":"Nursing shortages are a significant problem that affects healthcare access, outcomes, and costs and challenges the delivery of care in hospitals. The virtual nursing delivery model enables the provision of expert nursing care from a remote location, using technology such as audio/video communication, remote monitoring devices, and access to the electronic health record. However, little is known about the structure and processes supporting the implementation of virtual nursing in healthcare systems. This study examined the requirements for implementing a virtual nursing care team by characterizing the structure and processes of virtual nursing, using the Donabedian framework. The study conducted an observational and qualitative evaluation of a virtual nursing care team at a major Southeastern health center in the United States. The study found that key aspects for implementing a virtual nursing program include the number of available virtual nurses per shift, the availability of appropriate virtual nursing equipment, the physical layout of the virtual nursing center, the training of virtual nursing nurses on best practices of virtual encounters, simultaneous use of electronic health record, creation, and training of nurses on policies and procedures such as escalation of technical issues, and available support resources for problem resolution. The study provides valuable insights into the structure and processes of virtual nursing care that can be used to improve healthcare delivery and address nursing shortages.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142787596","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}

引用次数: 0

Frequency and Characteristics of Flowsheet Documentation Recorded Utilizing Documentation Efficiency Tools.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-04 DOI: 10.1097/CIN.0000000000001232

John Will, Deborah Jacques, Denise Dauterman, Lisa Groom, Glenn Doty, Kerry O'Brien

引用次数: 0

The State of Nursing Informatics Specialty in 2024: Practice, Research, and Education.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-02 DOI: 10.1097/CIN.0000000000001225

Olga Kagan, Kathryn Owen, Whende Carroll

引用次数: 0

Exploring Objective Simulation Competency Assessment Experience E-Learning Module Analytics: A Mixed-Methods Study to Improve Nursing Faculty Feedback. 探索客观模拟能力评估体验电子学习模块分析：改进护理教师反馈的混合方法研究。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-01 DOI: 10.1097/CIN.0000000000001164

Suhasini Kotcherlakota, Elizabeth Mollard, Kevin Kupzyk, Jennifer Cera

{"title":"Exploring Objective Simulation Competency Assessment Experience E-Learning Module Analytics: A Mixed-Methods Study to Improve Nursing Faculty Feedback.","authors":"Suhasini Kotcherlakota, Elizabeth Mollard, Kevin Kupzyk, Jennifer Cera","doi":"10.1097/CIN.0000000000001164","DOIUrl":"10.1097/CIN.0000000000001164","url":null,"abstract":"Abnormal uterine bleeding is a common clinical concern for adolescent women. This research study aims to improve the clinical reasoning skills of advanced practice nursing students instructed in blended Objective Simulation Competency Assessment clinical experiences by enhancing feedback loops given to students during simulated experiences. A sequential explanatory mixed-methods study design was conducted with two cohorts of first-year women's health nurse practitioner graduate nursing students enrolled in the Women's Health Program at a large Midwestern university. Data were collected across 2 years from two separate cohorts, and analyses included data from 15 participants. The Abnormal Uterine Bleeding module designed with decision pathways was a worthy effort, and faculty value using data analytics from the e-learning module to evaluate student learning. This study describes how nursing faculty created abnormal uterine bleeding content in an online module format that can aid the diagnostic reasoning process and enable feedback to students.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":"862-871"},"PeriodicalIF":1.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447489","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}

引用次数: 0

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults. 基于机器学习的中国社区老年人跌倒风险概率预测模型。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-12-01 DOI: 10.1097/CIN.0000000000001202

Zhou Zhou, Danhui Wang, Jun Sun, Min Zhu, Liping Teng

引用次数: 0