This study examines whether racism exists among Jewish and Arab patients in Israel, as reflected in patient preference for receiving treatment from a nurse with the same ethnic background.
Background
We examine the relationship between racism and the level of trust in a nurse from a different ethnic group than the patient, as well as the preferred level of social distance, in the context of ongoing conflicts between the Jewish majority and the Arab minority in Israel.
Methods
A cross-sectional study was conducted using a unique study questionnaire that asked 534 Jewish and 478 Arab respondents to express their preference for an Arab and a Jewish nurse.
Results
Among both the Jews and the Arabs, there is a similar tendency of racism toward nurses of the dissimilar ethnic group. This racism was also prevalent among participants who live in a mixed environment or those who studied or are studying and worked or work in a mixed environment. As the trust in nursing staff members from the other group increases, the level of racism decreases. The greater the social distance the participants felt from the members of the other group, the more racist the attitudes they expressed.
Conclusions
Both Jews and Arabs preferred to be treated by nurses of their own ethnic group. In contrast to the contact hypothesis theory, participants who live in a mixed environment did not express fewer racist preferences. We conclude with some useful practical suggestions aimed at decreasing racism in health care.
Clinical Relevance
Findings imply that prospective patients prefer to receive nursing care from nurses of their own ethnic group and trust these nurses more than they trust nurses of different ethnic group.
{"title":"Patient racism toward nurses in a divided society: The case of Jews and Arabs in Israel","authors":"Riki Halamish-Leshem PhD, Ya'arit Bokek-Cohen PhD, Mahdi Tarabeih RN, PhD, Pazit Azuri RN, PhD","doi":"10.1111/jnu.13006","DOIUrl":"10.1111/jnu.13006","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study examines whether racism exists among Jewish and Arab patients in Israel, as reflected in patient preference for receiving treatment from a nurse with the same ethnic background.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>We examine the relationship between racism and the level of trust in a nurse from a different ethnic group than the patient, as well as the preferred level of social distance, in the context of ongoing conflicts between the Jewish majority and the Arab minority in Israel.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A cross-sectional study was conducted using a unique study questionnaire that asked 534 Jewish and 478 Arab respondents to express their preference for an Arab and a Jewish nurse.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among both the Jews and the Arabs, there is a similar tendency of racism toward nurses of the dissimilar ethnic group. This racism was also prevalent among participants who live in a mixed environment or those who studied or are studying and worked or work in a mixed environment. As the trust in nursing staff members from the other group increases, the level of racism decreases. The greater the social distance the participants felt from the members of the other group, the more racist the attitudes they expressed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Both Jews and Arabs preferred to be treated by nurses of their own ethnic group. In contrast to the contact hypothesis theory, participants who live in a mixed environment did not express fewer racist preferences. We conclude with some useful practical suggestions aimed at decreasing racism in health care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <p>Findings imply that prospective patients prefer to receive nursing care from nurses of their own ethnic group and trust these nurses more than they trust nurses of different ethnic group.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 6","pages":"843-853"},"PeriodicalIF":2.4,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141621759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jihye Kim Scroggins, Maxim Topaz, Jiyoun Song, Maryam Zolnoori
Background: Identifying health problems in audio-recorded patient-nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource-intensive human annotation.
Objective: To generate synthetic patient-nurse communication and to automatically annotate for common health problems encountered in home healthcare settings using GPT-4. We also examined whether augmenting real-world patient-nurse communication with synthetic data can improve the performance of machine learning to identify health problems.
Design: Secondary data analysis of patient-nurse verbal communication data in home healthcare settings.
Methods: The data were collected from one of the largest home healthcare organizations in the United States. We used 23 audio recordings of patient-nurse communications from 15 patients. The audio recordings were transcribed verbatim and manually annotated for health problems (e.g., circulation, skin, pain) indicated in the Omaha System Classification scheme. Synthetic data of patient-nurse communication were generated using the in-context learning prompting method, enhanced by chain-of-thought prompting to improve the automatic annotation performance. Machine learning classifiers were applied to three training datasets: real-world communication, synthetic communication, and real-world communication augmented by synthetic communication.
Results: Average F1 scores improved from 0.62 to 0.63 after training data were augmented with synthetic communication. The largest increase was observed using the XGBoost classifier where F1 scores improved from 0.61 to 0.64 (about 5% improvement). When trained solely on either real-world communication or synthetic communication, the classifiers showed comparable F1 scores of 0.62-0.61, respectively.
Conclusion: Integrating synthetic data improves machine learning classifiers' ability to identify health problems in home healthcare, with performance comparable to training on real-world data alone, highlighting the potential of synthetic data in healthcare analytics.
Clinical relevance: This study demonstrates the clinical relevance of leveraging synthetic patient-nurse communication data to enhance machine learning classifier performances to identify health problems in home healthcare settings, which will contribute to more accurate and efficient problem identification and detection of home healthcare patients with complex health conditions.
{"title":"Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient-nurse verbal communications in home healthcare settings?","authors":"Jihye Kim Scroggins, Maxim Topaz, Jiyoun Song, Maryam Zolnoori","doi":"10.1111/jnu.13004","DOIUrl":"https://doi.org/10.1111/jnu.13004","url":null,"abstract":"<p><strong>Background: </strong>Identifying health problems in audio-recorded patient-nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource-intensive human annotation.</p><p><strong>Objective: </strong>To generate synthetic patient-nurse communication and to automatically annotate for common health problems encountered in home healthcare settings using GPT-4. We also examined whether augmenting real-world patient-nurse communication with synthetic data can improve the performance of machine learning to identify health problems.</p><p><strong>Design: </strong>Secondary data analysis of patient-nurse verbal communication data in home healthcare settings.</p><p><strong>Methods: </strong>The data were collected from one of the largest home healthcare organizations in the United States. We used 23 audio recordings of patient-nurse communications from 15 patients. The audio recordings were transcribed verbatim and manually annotated for health problems (e.g., circulation, skin, pain) indicated in the Omaha System Classification scheme. Synthetic data of patient-nurse communication were generated using the in-context learning prompting method, enhanced by chain-of-thought prompting to improve the automatic annotation performance. Machine learning classifiers were applied to three training datasets: real-world communication, synthetic communication, and real-world communication augmented by synthetic communication.</p><p><strong>Results: </strong>Average F1 scores improved from 0.62 to 0.63 after training data were augmented with synthetic communication. The largest increase was observed using the XGBoost classifier where F1 scores improved from 0.61 to 0.64 (about 5% improvement). When trained solely on either real-world communication or synthetic communication, the classifiers showed comparable F1 scores of 0.62-0.61, respectively.</p><p><strong>Conclusion: </strong>Integrating synthetic data improves machine learning classifiers' ability to identify health problems in home healthcare, with performance comparable to training on real-world data alone, highlighting the potential of synthetic data in healthcare analytics.</p><p><strong>Clinical relevance: </strong>This study demonstrates the clinical relevance of leveraging synthetic patient-nurse communication data to enhance machine learning classifier performances to identify health problems in home healthcare settings, which will contribute to more accurate and efficient problem identification and detection of home healthcare patients with complex health conditions.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141499568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many papers reporting on QI projects are not publishable for a variety of reasons. We compared manuscripts submitted as QI reports between June 2014 and June 2016 (prior to publication of the revised Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) with papers submitted to the American Journal of Nursing between July 2016 and December 2022). The aim was to evaluate any changes in the quality of manuscripts and identify problems that led to rejection; we also compared the quality of students with non-student submissions.
Methods
We conducted a non-randomized descriptive study to evaluate 349 papers submitted as QI project reports between June 2014 and December 2022 using screening templates based on the SQUIRE 2.0 checklist and findings of the INANE Working Group on Student Papers.
Results
Manuscripts designated as QI reports accepted for publication increased from 4% during 2014–2016 (T1) to 14% during 2016–2022 (T2); one student submission was accepted. There was a slight decrease in submissions designated as QI that were not QI: 36% of student submissions during T1 and 31% of student submissions during T2. Among clinician submissions, 44% in T1 designated as QI reports were not QI versus 31% submitted during T2. There was a decrease in student submissions that followed the SQUIRE guidelines (36% during T1 to 24% during T2).
Conclusions
Findings demonstrate that by following the SQUIRE 2.0 guidelines, authors submit more complete manuscripts with fewer missing components. However, there are still misconceptions about what constitutes QI versus research and how to report QI initiatives. After comparing the findings from both periods, it is noteworthy that there is essentially the same level of inaccuracy and lack of acceptable manuscripts.
Clinical Relevance
Sharing findings from QI activities through presentations and publications is a vital way of helping spread the learnings from these projects and improve health care for a wider audience. Clinicians, academicians, and students must understand the elements of the SQUIRE guidelines and ensure that this framework is used for both designing and submitting QI projects for publication.
{"title":"The quality of clinician and student quality improvement reports: An analysis of 8 years of submissions","authors":"Maureen (Shawn) Kennedy MA, RN, FAAN, Jane Barnsteiner PhD, RN, FAAN","doi":"10.1111/jnu.13003","DOIUrl":"10.1111/jnu.13003","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Many papers reporting on QI projects are not publishable for a variety of reasons. We compared manuscripts submitted as QI reports between June 2014 and June 2016 (prior to publication of the revised Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) with papers submitted to the <i>American Journal of Nursing</i> between July 2016 and December 2022). The aim was to evaluate any changes in the quality of manuscripts and identify problems that led to rejection; we also compared the quality of students with non-student submissions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a non-randomized descriptive study to evaluate 349 papers submitted as QI project reports between June 2014 and December 2022 using screening templates based on the SQUIRE 2.0 checklist and findings of the INANE Working Group on Student Papers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Manuscripts designated as QI reports accepted for publication increased from 4% during 2014–2016 (T1) to 14% during 2016–2022 (T2); one student submission was accepted. There was a slight decrease in submissions designated as QI that were not QI: 36% of student submissions during T1 and 31% of student submissions during T2. Among clinician submissions, 44% in T1 designated as QI reports were not QI versus 31% submitted during T2<i>.</i> There was a decrease in student submissions that followed the SQUIRE guidelines (36% during T1 to 24% during T2).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Findings demonstrate that by following the SQUIRE 2.0 guidelines, authors submit more complete manuscripts with fewer missing components. However, there are still misconceptions about what constitutes QI versus research and how to report QI initiatives. After comparing the findings from both periods, it is noteworthy that there is essentially the same level of inaccuracy and lack of acceptable manuscripts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <p>Sharing findings from QI activities through presentations and publications is a vital way of helping spread the learnings from these projects and improve health care for a wider audience. Clinicians, academicians, and students must understand the elements of the SQUIRE guidelines and ensure that this framework is used for both designing and submitting QI projects for publication.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 6","pages":"836-842"},"PeriodicalIF":2.4,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141472358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joshua Lambert PhD, MS, Sara Arter PhD, RN, Henry Duah PhD, MPH, RN, Teenu Xavier PhD, RN, Jon E. Sprague RPH, PhD
<div> <section> <h3> Introduction</h3> <p>Prenatal opioid exposure (POE) is a major public health consequence of the opioid epidemic. Long-term health outcomes associated with POE remain unclear, especially for children with POE without a diagnosis of neonatal abstinence syndrome (NAS). Here, we aimed to describe the health outcomes of children with POE and with POE and NAS compared to unexposed children during the first 7 years of life.</p> </section> <section> <h3> Design</h3> <p>In this retrospective observational cohort study, children born between 2015 and 2022 were identified from the Maternal and Infant Data Hub (MIDH), a data repository that continuously integrates maternal, neonatal, and pediatric records from two academic medical centers and one pediatric hospital system in the Midwest, USA.</p> </section> <section> <h3> Methods</h3> <p>International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10 CM) chapters A00-N99 served as outcomes of interest. Annual incidence and crude incidence rate ratios were calculated to explore descriptive differences between the exposed and unexposed groups.</p> </section> <section> <h3> Results</h3> <p>The study included 22,002 children, 20,130 (91.5%) of whom were unexposed and 1872 (8.5%) were exposed. Of the 1872 exposed children, 371 (19.8%) received a diagnosis of NAS (POE + NAS) and 1501 were in the POE-NAS group. Across all 7 years, exposed children had a higher incidence of diagnoses in most ICD-10 CM chapters compared to unexposed children. A consistently higher incidence rate ratio of diagnosis was observed in both POE-NAS and POE + NAS groups (vs. unexposed) related to mental and behavioral disorders, eye diagnoses, and diseases of the musculoskeletal system and gastrointestinal systems.</p> </section> <section> <h3> Conclusions</h3> <p>POE is associated with an increased risk of diagnoses in a number of ICD-10 CM chapters throughout childhood. These findings underscore the need for early screening and targeted interventions to support exposed children and improve their well-being. Further research is required to explore underlying mechanisms and develop preventive measures for at-risk populations.</p> </section> <section> <h3> Clinical Relevance</h3> <p>Understanding the conditions more often diagnosed in children with prenatal opioid exposure will help to improve care p
{"title":"Health outcomes in children with prenatal opioid exposure with and without neonatal abstinence syndrome in the first seven years of life: An observational cohort study","authors":"Joshua Lambert PhD, MS, Sara Arter PhD, RN, Henry Duah PhD, MPH, RN, Teenu Xavier PhD, RN, Jon E. Sprague RPH, PhD","doi":"10.1111/jnu.13000","DOIUrl":"10.1111/jnu.13000","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Prenatal opioid exposure (POE) is a major public health consequence of the opioid epidemic. Long-term health outcomes associated with POE remain unclear, especially for children with POE without a diagnosis of neonatal abstinence syndrome (NAS). Here, we aimed to describe the health outcomes of children with POE and with POE and NAS compared to unexposed children during the first 7 years of life.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>In this retrospective observational cohort study, children born between 2015 and 2022 were identified from the Maternal and Infant Data Hub (MIDH), a data repository that continuously integrates maternal, neonatal, and pediatric records from two academic medical centers and one pediatric hospital system in the Midwest, USA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10 CM) chapters A00-N99 served as outcomes of interest. Annual incidence and crude incidence rate ratios were calculated to explore descriptive differences between the exposed and unexposed groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study included 22,002 children, 20,130 (91.5%) of whom were unexposed and 1872 (8.5%) were exposed. Of the 1872 exposed children, 371 (19.8%) received a diagnosis of NAS (POE + NAS) and 1501 were in the POE-NAS group. Across all 7 years, exposed children had a higher incidence of diagnoses in most ICD-10 CM chapters compared to unexposed children. A consistently higher incidence rate ratio of diagnosis was observed in both POE-NAS and POE + NAS groups (vs. unexposed) related to mental and behavioral disorders, eye diagnoses, and diseases of the musculoskeletal system and gastrointestinal systems.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>POE is associated with an increased risk of diagnoses in a number of ICD-10 CM chapters throughout childhood. These findings underscore the need for early screening and targeted interventions to support exposed children and improve their well-being. Further research is required to explore underlying mechanisms and develop preventive measures for at-risk populations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <p>Understanding the conditions more often diagnosed in children with prenatal opioid exposure will help to improve care p","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 6","pages":"767-779"},"PeriodicalIF":2.4,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jnu.13000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ann M Wieben, Bader G Alreshidi, Brian J Douthit, Marisa Sileo, Pankaj Vyas, Linsey Steege, Andrea Gilmore-Bykovskyi
Introduction: The purpose of this study was to explore nurses' perspectives on Machine Learning Clinical Decision Support (ML CDS) design, development, implementation, and adoption.
Design: Qualitative descriptive study.
Methods: Nurses (n = 17) participated in semi-structured interviews. Data were transcribed, coded, and analyzed using Thematic analysis methods as described by Braun and Clarke.
Results: Four major themes and 14 sub-themes highlight nurses' perspectives on autonomy in decision-making, the influence of prior experience in shaping their preferences for use of novel CDS tools, the need for clarity in why ML CDS is useful in improving practice/outcomes, and their desire to have nursing integrated in design and implementation of these tools.
Conclusion: This study provided insights into nurse perceptions regarding the utility and usability of ML CDS as well as the influence of previous experiences with technology and CDS, change management strategies needed at the time of implementation of ML CDS, the importance of nurse-perceived engagement in the development process, nurse information needs at the time of ML CDS deployment, and the perceived impact of ML CDS on nurse decision making autonomy.
Clinical relevance: This study contributes to the body of knowledge about the use of AI and machine learning (ML) in nursing practice. Through generation of insights drawn from nurses' perspectives, these findings can inform successful design and adoption of ML Clinical Decision Support.
导言：本研究旨在探讨护士对机器学习临床决策支持（ML CDS）的设计、开发、实施和采用的看法：设计：定性描述研究：护士（n = 17）参加了半结构化访谈。采用 Braun 和 Clarke 所描述的主题分析方法对数据进行转录、编码和分析：结果：四个主要主题和 14 个次主题突出了护士对决策自主权的看法、先前经验对其使用新型 CDS 工具偏好的影响、明确 ML CDS 有助于改善实践/成果的必要性以及将护理工作纳入这些工具的设计和实施的愿望：本研究深入探讨了护士对 ML CDS 实用性和可用性的看法，以及以往使用技术和 CDS 经验的影响、实施 ML CDS 时所需的变革管理策略、护士认为参与开发过程的重要性、部署 ML CDS 时护士的信息需求，以及 ML CDS 对护士决策自主权的影响：本研究为在护理实践中使用人工智能和机器学习（ML）的知识体系做出了贡献。通过从护士的角度提出见解，这些发现可以为成功设计和采用 ML 临床决策支持提供参考。
{"title":"Nurses' perceptions of the design, implementation, and adoption of machine learning clinical decision support: A descriptive qualitative study.","authors":"Ann M Wieben, Bader G Alreshidi, Brian J Douthit, Marisa Sileo, Pankaj Vyas, Linsey Steege, Andrea Gilmore-Bykovskyi","doi":"10.1111/jnu.13001","DOIUrl":"10.1111/jnu.13001","url":null,"abstract":"<p><strong>Introduction: </strong>The purpose of this study was to explore nurses' perspectives on Machine Learning Clinical Decision Support (ML CDS) design, development, implementation, and adoption.</p><p><strong>Design: </strong>Qualitative descriptive study.</p><p><strong>Methods: </strong>Nurses (n = 17) participated in semi-structured interviews. Data were transcribed, coded, and analyzed using Thematic analysis methods as described by Braun and Clarke.</p><p><strong>Results: </strong>Four major themes and 14 sub-themes highlight nurses' perspectives on autonomy in decision-making, the influence of prior experience in shaping their preferences for use of novel CDS tools, the need for clarity in why ML CDS is useful in improving practice/outcomes, and their desire to have nursing integrated in design and implementation of these tools.</p><p><strong>Conclusion: </strong>This study provided insights into nurse perceptions regarding the utility and usability of ML CDS as well as the influence of previous experiences with technology and CDS, change management strategies needed at the time of implementation of ML CDS, the importance of nurse-perceived engagement in the development process, nurse information needs at the time of ML CDS deployment, and the perceived impact of ML CDS on nurse decision making autonomy.</p><p><strong>Clinical relevance: </strong>This study contributes to the body of knowledge about the use of AI and machine learning (ML) in nursing practice. Through generation of insights drawn from nurses' perspectives, these findings can inform successful design and adoption of ML Clinical Decision Support.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141428230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nurses' safety climate, quality of care, and standard precautions adherence and compliance: A cross-sectional study","authors":"","doi":"10.1111/jnu.12984","DOIUrl":"10.1111/jnu.12984","url":null,"abstract":"","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 4","pages":"621"},"PeriodicalIF":2.4,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141421728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ugo Giulio Sisto MD, Stefano Di Bella MD, Elisa Porta BSN, RN, Giorgia Franzoi BSN, RN, Franco Cominotto MD, Elena Guzzardi RN, Nicola Artusi MD, Caterina Anna Giudice MD, Eugenia Dal Bo MSN, RN, Nicholas Collot MD, Francesca Sirianni MD, Savino Russo MD, Gianfranco Sanson PhD, RN
Background
Early identification of sepsis in the emergency department (ED) triage is both valuable and challenging. Numerous studies have endeavored to pinpoint clinical and biochemical criteria to assist clinicians in the prompt diagnosis of sepsis, but few studies have assessed the efficacy of these criteria in the ED triage setting. The aim of the study was to explore the accuracy of clinical and laboratory markers evaluated at the triage level in identifying patients with sepsis.
Methods
A prospective study was conducted in a large academic urban hospital, implementing a triage protocol aimed at early identification of septic patients based on clinical and laboratory markers. A multidisciplinary panel of experts reviewed cases to ensure accurate identification of septic patients. Variables analyzed included: Charlson comorbidity index, mean arterial pressure (MAP), partial pressure of carbon dioxide (PetCO2), white cell count, eosinophil count, C-reactive protein to albumin ratio, procalcitonin, and lactate.
Results
A total of 235 patients were included. Multivariable analysis identified procalcitonin ≥1 ng/mL (OR 5.2; p < 0.001); CRP-to-albumin ratio ≥32 (OR 6.6; p < 0.001); PetCO2 ≤ 28 mmHg (OR 2.7; p = 0.031), and MAP <85 mmHg (OR 7.5; p < 0.001) as independent predictors for sepsis. MAP ≥85 mmHg, CRP/albumin ratio <32, and procalcitonin <1 ng/mL demonstrated negative predictive values for sepsis of 90%, 89%, and 88%, respectively.
Conclusions
Our study underscores the significance of procalcitonin and mean arterial pressure, while introducing CRP/albumin ratio and PetCO2 as important variables to consider in the very initial assessment of patients with suspected sepsis in the ED.
Clinical Relevance
Early identification of sepsis since the emergency department (ED) triage is challenging
Implementing the ED triage protocol with simple clinical and laboratory markers allows to recognize patients with sepsis with a very good discriminatory power (AUC 0.88)
{"title":"Predicting sepsis at emergency department triage: Implementing clinical and laboratory markers within the first nursing assessment to enhance diagnostic accuracy","authors":"Ugo Giulio Sisto MD, Stefano Di Bella MD, Elisa Porta BSN, RN, Giorgia Franzoi BSN, RN, Franco Cominotto MD, Elena Guzzardi RN, Nicola Artusi MD, Caterina Anna Giudice MD, Eugenia Dal Bo MSN, RN, Nicholas Collot MD, Francesca Sirianni MD, Savino Russo MD, Gianfranco Sanson PhD, RN","doi":"10.1111/jnu.13002","DOIUrl":"10.1111/jnu.13002","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Early identification of sepsis in the emergency department (ED) triage is both valuable and challenging. Numerous studies have endeavored to pinpoint clinical and biochemical criteria to assist clinicians in the prompt diagnosis of sepsis, but few studies have assessed the efficacy of these criteria in the ED triage setting. The aim of the study was to explore the accuracy of clinical and laboratory markers evaluated at the triage level in identifying patients with sepsis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A prospective study was conducted in a large academic urban hospital, implementing a triage protocol aimed at early identification of septic patients based on clinical and laboratory markers. A multidisciplinary panel of experts reviewed cases to ensure accurate identification of septic patients. Variables analyzed included: Charlson comorbidity index, mean arterial pressure (MAP), partial pressure of carbon dioxide (PetCO<sub>2</sub>), white cell count, eosinophil count, C-reactive protein to albumin ratio, procalcitonin, and lactate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 235 patients were included. Multivariable analysis identified procalcitonin ≥1 ng/mL (OR 5.2; <i>p</i> < 0.001); CRP-to-albumin ratio ≥32 (OR 6.6; <i>p</i> < 0.001); PetCO<sub>2</sub> ≤ 28 mmHg (OR 2.7; <i>p</i> = 0.031), and MAP <85 mmHg (OR 7.5; <i>p</i> < 0.001) as independent predictors for sepsis. MAP ≥85 mmHg, CRP/albumin ratio <32, and procalcitonin <1 ng/mL demonstrated negative predictive values for sepsis of 90%, 89%, and 88%, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our study underscores the significance of procalcitonin and mean arterial pressure, while introducing CRP/albumin ratio and PetCO<sub>2</sub> as important variables to consider in the very initial assessment of patients with suspected sepsis in the ED.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <div>\u0000 \u0000 <ul>\u0000 \u0000 \u0000 <li>Early identification of sepsis since the emergency department (ED) triage is challenging</li>\u0000 \u0000 \u0000 <li>Implementing the ED triage protocol with simple clinical and laboratory markers allows to recognize patients with sepsis with a very good discriminatory power (AUC 0.88)</li>\u0000 </ul>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 6","pages":"757-766"},"PeriodicalIF":2.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141421729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: 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.
Design: 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.
Results: 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.
Conclusions: 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.
Clinical relevance: 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.
{"title":"Applying machine learning to construct an association model for lung cancer and environmental hormone high-risk factors and nursing assessment reconstruction.","authors":"Pin-Chieh Lee, Mong-Wei Lin, Hsien-Chi Liao, Chan-Yi Lin, Pei-Hung Liao","doi":"10.1111/jnu.12997","DOIUrl":"https://doi.org/10.1111/jnu.12997","url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Design: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Clinical relevance: </strong>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.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141263290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara Furtado-Eraso RN, PhD, Blanca Marín-Fernández RN, PhD, Paula Escalada-Hernández RN, PhD
<div> <section> <h3> Purpose</h3> <p>The aim of this paper is to develop a preliminary theory that explores in depth into understanding the experiences of women who have suffered a spontaneous perinatal loss during any trimester of their pregnancy regarding their emotional response to this loss.</p> </section> <section> <h3> Design</h3> <p>A grounded theory approach was used, and 25 in-depth interviews were conducted with Spanish women who suffered a spontaneous perinatal loss.</p> </section> <section> <h3> Methods</h3> <p>Theoretical sampling and constant comparative analysis were used to reach theoretical saturation. EQUATOR guidelines were followed, using the COREQ checklist.</p> </section> <section> <h3> Results</h3> <p>The “Perinatal loss, a devastating cyclone,” a situation-specific nursing theory, explains the process that a woman experiences when she loses her baby at any stage of pregnancy, drawing an analogy with tropical cyclones as natural disasters that destroy everything in their path. This situation-specific theory includes three dimensions, explaining the phases identified in the perinatal loss process (phase prior to impact [before the perinatal loss], impact phase [diagnostic moment], emergency phase [hospital care], relief or honeymoon phase [return home], disillusionment or stock-taking phase [after the first postloss days at home], reconstruction and recovery phase [grief construction process] and consequences [with an eye to the future]). Three intervention areas were described around the perinatal loss process: “rescue area” (partner, grandparents, and siblings of the deceased baby), “relief area” (healthcare professionals), and “base camp” (society).</p> </section> <section> <h3> Conclusion</h3> <p>The situation-specific nursing theory “Perinatal loss, a devastating cyclone” is the final product of a grounded theory study that provided an in-depth analysis of women's experiences when they suffer a spontaneous perinatal loss at any point in their pregnancy.</p> </section> <section> <h3> Clinical Relevance</h3> <p>The situation-specific theory “Perinatal loss, a devastating cyclone” with the seven identified phases and the three areas of intervention could be used as a framework for healthcare professionals in their clinical practice as a guide to support women in this disfranchised grief.</p> </section>
{"title":"“Perinatal loss, a devastating cyclone”: A situation-specific nursing theory","authors":"Sara Furtado-Eraso RN, PhD, Blanca Marín-Fernández RN, PhD, Paula Escalada-Hernández RN, PhD","doi":"10.1111/jnu.12996","DOIUrl":"10.1111/jnu.12996","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The aim of this paper is to develop a preliminary theory that explores in depth into understanding the experiences of women who have suffered a spontaneous perinatal loss during any trimester of their pregnancy regarding their emotional response to this loss.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>A grounded theory approach was used, and 25 in-depth interviews were conducted with Spanish women who suffered a spontaneous perinatal loss.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Theoretical sampling and constant comparative analysis were used to reach theoretical saturation. EQUATOR guidelines were followed, using the COREQ checklist.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The “Perinatal loss, a devastating cyclone,” a situation-specific nursing theory, explains the process that a woman experiences when she loses her baby at any stage of pregnancy, drawing an analogy with tropical cyclones as natural disasters that destroy everything in their path. This situation-specific theory includes three dimensions, explaining the phases identified in the perinatal loss process (phase prior to impact [before the perinatal loss], impact phase [diagnostic moment], emergency phase [hospital care], relief or honeymoon phase [return home], disillusionment or stock-taking phase [after the first postloss days at home], reconstruction and recovery phase [grief construction process] and consequences [with an eye to the future]). Three intervention areas were described around the perinatal loss process: “rescue area” (partner, grandparents, and siblings of the deceased baby), “relief area” (healthcare professionals), and “base camp” (society).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The situation-specific nursing theory “Perinatal loss, a devastating cyclone” is the final product of a grounded theory study that provided an in-depth analysis of women's experiences when they suffer a spontaneous perinatal loss at any point in their pregnancy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <p>The situation-specific theory “Perinatal loss, a devastating cyclone” with the seven identified phases and the three areas of intervention could be used as a framework for healthcare professionals in their clinical practice as a guide to support women in this disfranchised grief.</p>\u0000 </section>\u0000 ","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 5","pages":"664-677"},"PeriodicalIF":2.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jnu.12996","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141198535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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