Cin-Computers Informatics Nursing最新文献_第2页

Using Virtual Reality in Mental Health Nursing to Improve Behavioral Health Equity. 在心理健康护理中使用虚拟现实技术改善行为健康平等。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-31 DOI: 10.1097/CIN.0000000000001195

Sheri Howard, Meghan Meadows-Taylor

{"title":"Using Virtual Reality in Mental Health Nursing to Improve Behavioral Health Equity.","authors":"Sheri Howard, Meghan Meadows-Taylor","doi":"10.1097/CIN.0000000000001195","DOIUrl":"10.1097/CIN.0000000000001195","url":null,"abstract":"Nursing students often experience anxiety, stress, and fear during a clinical rotation in a mental health setting due to stressors and biases toward the setting as well as lack experience in caring for patients with mental health conditions. One in four people worldwide suffers from a mental disorder; therefore, it is critical that nurses feel confident interacting with these patients to provide equitable care. Undergraduate training is a critical period for changing students' attitudes toward this population. This study's goal was twofold. First, we offered students' exposure to common behaviors and symptoms displayed by a patient with mental illness through an engaging and immersive virtual reality simulation experience before taking care of patients in a clinical setting. Second, we aimed to determine if a virtual reality simulation will change students' attitude and stigma, favorably, toward patients with mental health conditions. We used a mixed-method comparative analysis to collect information and identify themes on undergraduate students' attitudes and stigma toward patients with mental health conditions. Our findings demonstrate that virtual reality simulations enhance awareness and sensitivity to the situations of others (empathy) while improving their communication skills. The use of virtual reality in a baccalaureate curriculum deepens the understanding of health equity in behavioral health for nursing students.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548741","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

Nursing in the Age of Artificial Intelligence. 人工智能时代的护理。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-31 DOI: 10.1097/CIN.0000000000001204

Janet H Davis

引用次数: 0

Perceptions of Cognitive Load and Workload in Nurse Handoffs: A Comparative Study Across Differing Patient-Nurse Ratios and Acuity Levels. 对护士交接工作中认知负荷和工作量的看法：不同病人-护士比例和严重程度的比较研究。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-31 DOI: 10.1097/CIN.0000000000001216

Benjamin J Galatzan, Liang Shan, Elizabeth Johnson, Patricia A Patrician

{"title":"Perceptions of Cognitive Load and Workload in Nurse Handoffs: A Comparative Study Across Differing Patient-Nurse Ratios and Acuity Levels.","authors":"Benjamin J Galatzan, Liang Shan, Elizabeth Johnson, Patricia A Patrician","doi":"10.1097/CIN.0000000000001216","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001216","url":null,"abstract":"Medical errors, often resulting from miscommunication and cognitive lapses during handoffs, account for numerous preventable deaths and patient harm annually. This research examined nurses' perceived workload and cognitive load during handoffs on hospital units with varying patient acuity levels and patient-nurse ratios. Conducted at a southeastern US medical facility, the study analyzed 20 handoff dyads using the National Aeronautics and Space Administration Task Load Index to measure perceived workload and cognitive load. Linear regressions revealed significant associations between patient acuity levels, patient-nurse ratios, and National Aeronautics and Space Administration Task Load Index subscales, specifically mental demand (P = .007) and performance (P = .008). Fisher exact test and Wilcoxon rank sum test showed no significant associations between these factors and nurses' roles (P > .05). The findings highlight the need for targeted interventions to manage workload and cognitive load, emphasizing standardized handoff protocols and technological aids. The study underscores the variability in perceived workload and cognitive load among nurses across different units. Medical-surgical units showed higher cognitive load, indicating the need for improved workload management strategies. Despite limitations, including the single-center design and small sample size, the study provides valuable insights for enhancing handoff communications and reducing medical errors.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548740","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

New Zealand Nurses' Ongoing Concerns of Using Digital Technologies During and After the COVID-19 Pandemic. 新西兰护士在 COVID-19 大流行期间和之后对使用数字技术的持续关注。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-31 DOI: 10.1097/CIN.0000000000001208

Michelle L L Honey, Emma Collins

引用次数: 0

Effectiveness of Mobile Application-Based Intervention on Medication Adherence Among Pulmonary Tuberculosis Patients: A Systematic Review. 基于移动应用程序的干预对肺结核患者坚持服药的效果：系统回顾

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-25 DOI: 10.1097/CIN.0000000000001213

Syahrul Syahrul, Andi Masyitha Irwan, Ariyanti Saleh, Yuliana Syam, Andi Muhammad Fiqri, St Nurfatul Jannah

{"title":"Effectiveness of Mobile Application-Based Intervention on Medication Adherence Among Pulmonary Tuberculosis Patients: A Systematic Review.","authors":"Syahrul Syahrul, Andi Masyitha Irwan, Ariyanti Saleh, Yuliana Syam, Andi Muhammad Fiqri, St Nurfatul Jannah","doi":"10.1097/CIN.0000000000001213","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001213","url":null,"abstract":"Objectives: To analyze the effectiveness of mobile application-based interventions on medication adherence among pulmonary tuberculosis patients.Eligibility criteria: Intervention articles involving patients with pulmonary tuberculosis and/or their families, utilizing mobile application-based intervention research designs, assessing patients individually or in groups with or without a control group, using mobile application-based interventions that can be accessed via a browser, utilizing adherence to treatment as the primary outcome, and written in English and Indonesian were included.Information sources: The articles published from 2012 to 2022 were obtained from EBSCO Host, ProQuest, GARUDA, PubMed, Scopus, and Cochrane Online Library databases.Risk of bias: The Critical Assessment Standards Program was used to assess the trustworthiness, relevance, and results of the published articles. The quality of the articles was assessed according to Johns Hopkins Nursing Evidence-Based Practice guidelines.Results: Seven studies reported that mobile application-based interventions can improve medication adherence, including treatment success, number of missed drugs, correct intake of medications, adherence to health programs, timeliness, and frequency of clinic visits.Discussion: This review only analyzed the impact of mobile application-based interventions on patients, and their effects on the family, social, and health services were not covered.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512362","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

Best Practices in Supporting Inpatient Communication With Technology During Visitor Restrictions: An Integrative Review. 在访客限制期间利用科技支持住院病人交流的最佳实践：综合评述。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-22 DOI: 10.1097/CIN.0000000000001200

Stephanie Brown, Jamie Guillergan, Eric Beedle, Andre Gnie, Sterling Wilmer, Kristy Wormack, Nadine Rosenblum

{"title":"Best Practices in Supporting Inpatient Communication With Technology During Visitor Restrictions: An Integrative Review.","authors":"Stephanie Brown, Jamie Guillergan, Eric Beedle, Andre Gnie, Sterling Wilmer, Kristy Wormack, Nadine Rosenblum","doi":"10.1097/CIN.0000000000001200","DOIUrl":"10.1097/CIN.0000000000001200","url":null,"abstract":"Background: Since the onset of the COVID-19 pandemic, healthcare workers around the world have experimented with technologies to facilitate communication and care for patients and their care partners.Methods: Our team reviewed the literature to examine best practices in utilizing technology to support communication between nurses, patients, and care partners while visitation is limited. We searched four major databases for recent articles on this topic, conducted a systematic screening and review of 1902 articles, and used the Johns Hopkins Nursing Evidence-Based Practice for Nurses and Healthcare Professionals Model & Guidelines to appraise and translate the results of 23 relevant articles.Results: Our evaluation yielded three main findings from the current literature: (1) Virtual contact by any technological means, especially video visitation, improves satisfaction, reduces anxiety, and is well-received by the target populations. (2) Structured video rounding provides effective communication among healthcare workers, patients, and offsite care partners. (3) Institutional preparation, such as a standardized checklist and dedicating staff to roles focused on facilitating communication, can help healthcare workers create environments conducive to therapeutic virtual communication.Discussion: In situations that require healthcare facilities to limit visitation between patients and their care partners, the benefits of virtual visitation are evident. There is variance in the types of technologies used to facilitate virtual visits, but across all of them, there are consistent themes demonstrating the benefits of virtual visits and virtual rounding. Healthcare institutions can prepare for future limited-visitation scenarios by reviewing the current evidence and integrating virtual visitation into modern healthcare delivery.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479873","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 Systematic Review of Features Forecasting Patient Arrival Numbers. 对预测患者到达人数特征的系统性回顾。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-21 DOI: 10.1097/CIN.0000000000001197

Markus Förstel, Oliver Haas, Stefan Förstel, Andreas Maier, Eva Rothgang

{"title":"A Systematic Review of Features Forecasting Patient Arrival Numbers.","authors":"Markus Förstel, Oliver Haas, Stefan Förstel, Andreas Maier, Eva Rothgang","doi":"10.1097/CIN.0000000000001197","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001197","url":null,"abstract":"Adequate nurse staffing is crucial for quality healthcare, necessitating accurate predictions of patient arrival rates. These forecasts can be determined using supervised machine learning methods. Optimization of machine learning methods is largely about minimizing the prediction error. Existing models primarily utilize data such as historical patient visits, seasonal trends, holidays, and calendars. However, it is unclear what other features reduce the prediction error. Our systematic literature review identifies studies that use supervised machine learning to predict patient arrival numbers using nontemporal features, which are features not based on time or dates. We scrutinized 26 284 studies, eventually focusing on 27 relevant ones. These studies highlight three main feature groups: weather data, internet search and usage data, and data on (social) interaction of groups. Internet data and social interaction data appear particularly promising, with some studies reporting reduced errors by up to 33%. Although weather data are frequently used, its utility is less clear. Other potential data sources, including smartphone and social media data, remain largely unexplored. One reason for this might be potential data privacy challenges. In summary, although patient arrival prediction has become more important in recent years, there are still many questions and opportunities for future research on the features used in this area.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479894","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

Use of the Electronic Health Record to Improve Nursing Chart Preparation. 使用电子健康记录改进护理病历的准备工作。

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-02 DOI: 10.1097/CIN.0000000000001196

Laura M Sherburne, Jessica M Runge, Abby L Larson

引用次数: 0

The Impact of a Digital Cancer Survivorship Patient Engagement Toolkit on Older Cancer Survivors' Health Outcomes. 数字癌症幸存者患者参与工具包对老年癌症幸存者健康结果的影响》（The Impact of a Digital Cancer Survivorship Patient Engagement Toolkit on Older Cancer Survivors' Health Outcomes.

IF 1.3 4区医学

Cin-Computers Informatics Nursing Pub Date : 2024-10-02 DOI: 10.1097/CIN.0000000000001199

Eun-Shim Nahm, Mary McQuaige, Katarina Steacy, Shijun Zhu, Hohyun Seong

{"title":"The Impact of a Digital Cancer Survivorship Patient Engagement Toolkit on Older Cancer Survivors' Health Outcomes.","authors":"Eun-Shim Nahm, Mary McQuaige, Katarina Steacy, Shijun Zhu, Hohyun Seong","doi":"10.1097/CIN.0000000000001199","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001199","url":null,"abstract":"Cancer predominantly affects older adults. An estimated 62% of the 15.5 million American cancer survivors are 65 years or older. Provision of supportive care is critical to this group; however, limited resources are available to them. As older survivors increasingly adopt technology, digital health programs have significant potential to provide them with longitudinal supportive care. Previously, we developed/tested a digital Cancer Survivorship Patient Engagement Toolkit for older adults, Cancer Survivorship Patient Engagement Toolkit Silver. The study examined the preliminary impact of the Cancer Survivorship Patient Engagement Toolkit Silver on older survivors' health outcomes. This was a 2-arm randomized controlled trial with two observations (baseline, 8 weeks) on a sample of 60 older cancer survivors (mean age, 70.1 ± 3.8 years). Outcomes included health-related quality of life, self-efficacy for coping with cancer, symptom burden, health behaviors, and patient-provider communication. Data were analyzed using descriptive statistics, linear mixed models, and content analysis. At 8 weeks, the Cancer Survivorship Patient Engagement Toolkit Silver group showed more improved physical health-related quality of life (P < .001, effect size = 0.64) and symptom burden (P = .053, effect size = -0.41) than the control group. Self-efficacy (effect size = 0.56), mental health-related quality of life (effect size = 0.26), and communication (effect size = 0.40) showed clinically meaningful effect sizes of improvement. Most participants reported benefits on health management (mean, 19.41 ± 2.6 [3-21]). Further research is needed with larger and more diverse older cancer populations.","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373470","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 : 2024-10-02 DOI: 10.1097/CIN.0000000000001202

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

引用次数: 0