Journal of Nursing Scholarship最新文献

{"title":"Effectiveness of integrated care models for stroke patients: A systematic review and meta-analysis.","authors":"Beixue Liu, Jingyi Cai, Lanshu Zhou","doi":"10.1111/jnu.13027","DOIUrl":"https://doi.org/10.1111/jnu.13027","url":null,"abstract":"<p><strong>Introduction: </strong>Given that stroke is a leading cause of disability and mortality worldwide, there is an urgent need for a coordinated healthcare approach to mitigate its effects. The objectives of this study were to perform a systematic review and meta-analysis of stroke integrated care models and develop recommendations for a representative model.</p><p><strong>Design: </strong>A systematic review and meta-analysis.</p><p><strong>Methods: </strong>The literature search identified randomized controlled trials comparing integrated care models with standard care for stroke patients. The included studies followed PICOs inclusion criteria. The qualitative analysis included creating a flowchart for the literature screening process, and tables detailing the basic characteristics of the included studies, the adherence to the ten principles and the results of the quality assessments. Subsequently, quantitative meta-analytical procedures were conducted to statistically pool the data and quantify the effects of the integrated care models on stroke patients' health-related quality of life, activities of daily living, and depression. The China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Chinese Science and Technology Periodical Database (VIP), China Biology Medicine Disc (CBMDISC), Cochrane Library, Cumulated Index to Nursing and Allied Health Literature (CINAHL), PubMed, Web of Science, Embase, Google Scholar, and Clinical Trials were searched from inception to March 13, 2024.</p><p><strong>Results: </strong>Of the 2547 obtained articles, 19 were systematically reviewed and 15 were included in the meta-analysis. The integrated care models enhanced stroke patients' health-related quality of life, ability to perform activities of daily living, and reduced depression. Adherence to the 10 principles varied: comprehensive services, patient focus, and standardized care delivery had strong implementation, while gaps were noted in geographic coverage, information systems, governance structures, and financial management.</p><p><strong>Conclusion: </strong>Integrated care models improve outcomes for stroke patients and adherence to the 10 principles is vital for their implementation success. This study's findings call for a more standardized approach to implementing integrated care models, emphasizing the need for integrated services, patient-centred care, and interdisciplinary collaboration, while also addressing the identified gaps in terms of integration efforts.</p><p><strong>Clinical relevance: </strong>This study provides evidence-based recommendations on the most effective integrated care approaches for stroke patients, potentially leading to better patient outcomes, reduced healthcare costs, and improved quality of life.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142309055","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":"Decoding machine learning in nursing research: A scoping review of effective algorithms.","authors":"Jeeyae Choi,Hanjoo Lee,Yeounsoo Kim-Godwin","doi":"10.1111/jnu.13026","DOIUrl":"https://doi.org/10.1111/jnu.13026","url":null,"abstract":"INTRODUCTIONThe rapid evolution of artificial intelligence (AI) technology has revolutionized healthcare, particularly through the integration of AI into health information systems. This transformation has significantly impacted the roles of nurses and nurse practitioners, prompting extensive research to assess the effectiveness of AI-integrated systems. This scoping review focuses on machine learning (ML) used in nursing, specifically investigating ML algorithms, model evaluation methods, areas of focus related to nursing, and the most effective ML algorithms.DESIGNThe scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines.METHODSA structured search was performed across seven databases according to PRISMA-ScR: PubMed, EMBASE, CINAHL, Web of Science, OVID, PsycINFO, and ProQuest. The quality of the final reviewed studies was assessed using the Medical Education Research Study Quality Instrument (MERSQI).RESULTSTwenty-six articles published between 2019 and 2023 met the inclusion and exclusion criteria, and 46% of studies were conducted in the US. The average MERSQI score was 12.2, indicative of moderate- to high-quality studies. The most used ML algorithm was Random Forest. The four second-most used were logistic regression, least absolute shrinkage and selection operator, decision tree, and support vector machine. Most ML models were evaluated by calculating sensitivity (recall)/specificity, accuracy, receiver operating characteristic (ROC), area under the ROC (AUROC), and positive/negative prediction value (precision). Half of the studies focused on nursing staff or students and hospital readmission or emergency department visits. Only 11 articles reported the most effective ML algorithm(s).CONCLUSIONThe scoping review provides insights into the current status of ML research in nursing and recognition of its significance in nursing research, confirming the benefits of ML in healthcare. Recommendations include incorporating experimental designs in research studies to optimize the use of ML models across various nursing domains.CLINICAL RELEVANCEThe scoping review demonstrates substantial clinical relevance of ML applications for nurses, nurse practitioners, administrators, and researchers. The integration of ML into healthcare systems and its impact on nursing practices have important implications for patient care, resource management, and the evolution of nursing research.","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256746","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":"The effects of applying artificial intelligence to triage in the emergency department: A systematic review of prospective studies","authors":"Nayeon Yi, Dain Baik, Gumhee Baek","doi":"10.1111/jnu.13024","DOIUrl":"https://doi.org/10.1111/jnu.13024","url":null,"abstract":"IntroductionAccurate and rapid triage can reduce undertriage and overtriage, which may improve emergency department flow. This study aimed to identify the effects of a prospective study applying artificial intelligence‐based triage in the clinical field.DesignSystematic review of prospective studies.MethodsCINAHL, Cochrane, Embase, PubMed, ProQuest, KISS, and RISS were searched from March 9 to April 18, 2023. All the data were screened independently by three researchers. The review included prospective studies that measured outcomes related to AI‐based triage. Three researchers extracted data and independently assessed the study's quality using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) protocol.ResultsOf 1633 studies, seven met the inclusion criteria for this review. Most studies applied machine learning to triage, and only one was based on fuzzy logic. All studies, except one, utilized a five‐level triage classification system. Regarding model performance, the feed‐forward neural network achieved a precision of 33% in the level 1 classification, whereas the fuzzy clip model achieved a specificity and sensitivity of 99%. The accuracy of the model's triage prediction ranged from 80.5% to 99.1%. Other outcomes included time reduction, overtriage and undertriage checks, mistriage factors, and patient care and prognosis outcomes.ConclusionTriage nurses in the emergency department can use artificial intelligence as a supportive means for triage. Ultimately, we hope to be a resource that can reduce undertriage and positively affect patient health.Protocol RegistrationWe have registered our review in PROSPERO (registration number: CRD 42023415232).","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221969","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":"Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.","authors":"Robin R Austin, Ratchada Jantraporn, Martin Michalowski, Jenna Marquard","doi":"10.1111/jnu.13025","DOIUrl":"https://doi.org/10.1111/jnu.13025","url":null,"abstract":"<p><strong>Background: </strong>A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ability to collect data between clinical care visits. Machine learning/artificial intelligence methods have the potential to uncover insights into healthy aging. Nurses and nurse informaticians have a unique lens to shape the future use of this technology.</p><p><strong>Methods: </strong>The purpose of this research was to apply machine learning methods to MyStrengths+MyHealth de-identified data (N = 988) for adults 45 years of age and older. An exploratory data analysis process guided this work.</p><p><strong>Results: </strong>Overall (n = 988), the average Strength was 66.1% (SD = 5.1), average Challenges 66.5% (SD = 7.5), and average Needs 60.06% (SD = 3.1). There was a significant difference between Strengths and Needs (p < 0.001), between Challenges and Needs (p < 0.001), and no significant differences between average Strengths and Challenges. Four concept groups were identified from the data (Thinking, Moving, Emotions, and Sleeping). The Thinking group had the most statistically significant challenges (11) associated with having at least one Thinking Challenge and the highest average Strengths (66.5%) and Needs (83.6%) compared to the other groups.</p><p><strong>Conclusion: </strong>This retrospective analysis applied machine learning methods to de-identified whole person health resilience data from the MSMH application. Adults 45 and older had many Strengths despite numerous Challenges and Needs. The Thinking group had the highest Strengths, Challenges, and Needs, which aligns with the literature and highlights the co-occurring health challenges experienced by this group. Machine learning methods applied to consumer health data identify unique insights applicable to specific conditions (e.g., cognitive) and healthy aging. The next steps involve testing personalized interventions with nurses leading artificial intelligence integration into clinical care.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156577","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":"Are we making the most of safe staffing research.","authors":"Alison Steven, Rafael A Bernardes, Monica Bianchi, Nicola Cornally, Ana Inês Costa, Katja Pursio, Marco Di Nitto, Milko Zanini, Marie-Louise Luiking","doi":"10.1111/jnu.13021","DOIUrl":"https://doi.org/10.1111/jnu.13021","url":null,"abstract":"<p><strong>Introduction: </strong>The uptake of research evidence on staffing issues in nursing by nursing leadership, management and into organizational policies seems to vary across Europe. This study wants to assess this uptake of research evidence.</p><p><strong>Design: </strong>Scoping survey.</p><p><strong>Method: </strong>The presidents of twelve country specific Sigma Chapters within the European Region answered written survey questions about work organisation, national staffing levels, national skill mix levels, staff characteristics, and education.</p><p><strong>Results: </strong>Seven of the 12 chapters could not return complete data, reported that data was unavailable, there was no national policy or only guidance related to some settings.</p><p><strong>Conclusion: </strong>Enhancing the awareness of nursing research and of nursing leaders and managers regarding staffing level evidence is not enough. It seems necessary to encourage nurse leaders to lobby for staffing policies.</p><p><strong>Clinical relevance: </strong>Research evidence on staffing issues in nursing and how it benefits health care is available. In Europe this evidence should be used more to lobby for change in staffing policies.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142114473","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":"The impact of gender on the nursing figure and nurses' interprofessional relationships: A multimethod study.","authors":"Loredana Piervisani, Maddalena De Maria, Sabrina Spagnuolo, Patrizia Nazzaro, Gennaro Rocco, Ercole Vellone, Rosaria Alvaro","doi":"10.1111/jnu.13020","DOIUrl":"https://doi.org/10.1111/jnu.13020","url":null,"abstract":"<p><strong>Aims: </strong>To identify the current presence of stereotypes about the nursing profession in Italy and to understand how gendered processes and modalities are regulated and expressed in the physician-nurse dyad, and the implications for professional identity and autonomy.</p><p><strong>Design: </strong>Qualitative multimethod design.</p><p><strong>Methods: </strong>Forty-five interviews were conducted with nurses and physicians. The collected qualitative data underwent automatic textual data analysis using a multidimensional exploratory approach and a gender framework analysis.</p><p><strong>Results: </strong>In Italy, nurses' roles are still associated with gender stereotypes stemming from the predominant male culture, which affects sexual and gender identity, the division of labor, and access to career paths. This leads to disadvantages in the nursing profession, which is heavily dominated by women.</p><p><strong>Conclusion: </strong>Biological differences between sexes generate an unconscious yet shared symbolic gender order composed of negative stereotypes that influence nurses' professional roles and activities. They follow behaviors that enter the work routine and institutionalize organizational processes. These effects are also seen in the asymmetric, limited, and reciprocal interprofessional relationships between male physicians and female nurses, where the former hinders the latter's professional autonomy and access to top positions.</p><p><strong>Implications for the profession: </strong>This survey raises awareness of gender issues and stimulates reflection. It also enables health and nursing organizations to take action to raise gender awareness and education by countering the image of a non-autonomous profession. The analysis of gender processes allows us to identify interventions that can counteract forms of oppression in the work environment that lead to the emergence of nursing as a non-autonomous profession.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142094053","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 during war: Profiles-based risk and protective factors.","authors":"Hamama Liat, Amit Inbal, Itzhaki Michal","doi":"10.1111/jnu.13019","DOIUrl":"https://doi.org/10.1111/jnu.13019","url":null,"abstract":"<p><strong>Introduction: </strong>Nurses in southern Israel's public hospitals were exposed to unusual traumatic events following the October 7, 2023, Hamas attack on Israel, and the ensuing Swords of Iron War. This study aimed to clarify the complexity of wartime nursing by identifying profiles based on risk factors (i.e., psychological distress and adjustment disorders) and protective factors (i.e., positive affect (PA), resilience, and perceived social support [PSS]).</p><p><strong>Design: </strong>This study utilizes a cross-sectional design.</p><p><strong>Method: </strong>Two hundred nurses at a major public hospital in southern Israel completed self-report questionnaires. A latent profile analysis (LPA) was conducted to identify distinct profiles based on nurses' risk and protective factors. Differences in profiles were examined alongside sociodemographic and occupational variables and traumatic event exposure. The LPA was conducted using MPlus 8.8 Structural Equation Modeling (SEM) software.</p><p><strong>Findings: </strong>Two distinct profiles were identified: \"reactive\" and \"resilient.\" The \"reactive\" group included nurses who had higher risk factor scores (psychological distress and adjustment disorder), whereas the \"resilient\" group included nurses who had higher protective factor scores (PA, resilience, and PSS). Furthermore, nurses in the \"reactive\" group were younger, with greater seniority, worse self-rated health, and a higher frequency of kidnapped family members compared to nurses from the \"resilient\" group.</p><p><strong>Conclusion: </strong>Nurses in wartime are at risk if identified as \"reactive.\" Identifying these profiles can assist in developing effective support practices to help nurses cope with wartime challenges and maintain their mental well-being.</p><p><strong>Clinical relevance: </strong>Healthcare organizations should tailor interventions to prepare and support nurses of various ages and experience levels, during and after conflicts. This approach aims to reduce risk factors and promote protective factors among nurses during wartime.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142074444","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":"Implementation of a structured oral hygiene program through nursing assistant education to address non-ventilator hospital-acquired pneumonia: A quasi-experimental study.","authors":"Elizabeth Kozub, Emily Gorzycki, Abbey Sidebottom, Sandra Castro-Pearson, Ruth Bryant","doi":"10.1111/jnu.13018","DOIUrl":"https://doi.org/10.1111/jnu.13018","url":null,"abstract":"<p><strong>Introduction: </strong>Non-ventilator hospital-acquired pneumonia (NV HAP) is a common complication for hospitalized patients. NV HAP develops when patients aspirate oral secretions containing pathogenic bacteria. Appropriate oral hygiene can help mitigate NV HAP development. Hospital staff, including nursing assistants, play an important role in ensuring that these cares are completed.</p><p><strong>Design: </strong>A quasi-experimental pre-post design was used to evaluate outcomes before and after implementation of a structured oral hygiene education program.</p><p><strong>Methods: </strong>A structured oral hygiene program was developed and implemented in a large quaternary hospital. Change in NA knowledge, attitudes, and behaviors before and after implementation of the oral hygiene program was evaluated. Retrospective patient outcomes before and after the intervention were analyzed to detect changes in NV HAP rates.</p><p><strong>Results: </strong>Following the education, nursing assistant knowledge of recommended frequency of oral care for patients who are NPO increased (67.2% vs. 82.1%, p = 0.003). NAs were more likely to report oral hygiene tools including oral suctioning (80.8% vs. 90.2%, p = 0.005) and toothbrushes (89.3% vs. 95.3%, p = 0.031). The unadjusted incidence of NV HAP was significantly lower in the post-intervention cohort (0.25%) compared to the pre-intervention cohort (0.74%), p < 0.001. In the adjusted model, non-invasive positive pressure ventilation increased the odds of NV HAP by nearly sevenfold (AOR = 6.88, 95% CI: 3.99, 11.39).</p><p><strong>Conclusion: </strong>Focused education for NAs is an effective strategy to increase knowledge related to oral hygiene. Implementing a structured oral hygiene program for NAs appears to be a promising practice to decrease NV HAP.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142057251","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":"Evaluating the combination of in-person and electronic social networking services for family caregivers of stroke survivors: A quasi-experimental analysis.","authors":"Wen-Yu Kuo, Chen-Yin Chen, Jeng Wang, Chin-Man Wang, Min-Chi Chen, Ting-Yu Chang","doi":"10.1111/jnu.13022","DOIUrl":"https://doi.org/10.1111/jnu.13022","url":null,"abstract":"<p><strong>Introduction: </strong>The effectiveness of health interventions delivered via a combination of in-person and electronic social networking services for caregivers of stroke survivors remains uncertain. This study evaluates the feasibility of implementing educational and peer support programs for these caregivers through such platforms.</p><p><strong>Design: </strong>Quasi-experimental design.</p><p><strong>Methods: </strong>This study included 105 caregiver-survivor dyads, with 54 dyads allocated to the intervention group and the remaining 51 to the control group. The LINE intervention comprised a combination of in-person and electronic social networking services including stroke and rehabilitation education, problem-solving skills training, long-term care information support, and 24-h peer and professional support for caregivers. The outcomes were assessed at baseline, after 1 month, and after 3 months, and encompassed caregivers' care burden, depressive symptoms, perceived social support, and quality of life, as well as the rehabilitation adherence and depressive symptoms of stroke survivors. Generalized estimating equations were used to examine group differences. The data were collected between August 2021 and October 2022.</p><p><strong>Results: </strong>The average age of the caregivers was 48.3 years. Caregivers in the intervention group reported reduced care burdens and enhanced perceptions of social support and quality of life as compared to those in the control group. Additionally, stroke survivors in the intervention group were less likely to exhibit high-risk depressive symptoms.</p><p><strong>Conclusion: </strong>Delivering a stroke caregiver support intervention via in-person and electronic social networking services, such as LINE, effectively reduced the care burden for caregivers of stroke survivors. Additionally, it enhanced caregivers' perceived social support and quality of life.</p><p><strong>Clinical relevance: </strong>This study demonstrated that caregiver education and peer support programs administered through a combination of in-person and electronic social networking services can serve as an effective support system for the psychosocial health of stroke caregivers. These findings support the integration of such interventions into standard clinical practice by healthcare providers or governmental bodies.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142074496","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":"\"Doing the right thing\": Moral conflicts and ethical issues experienced by military nurses during wartime.","authors":"Janice Agazio, Diane L Padden","doi":"10.1111/jnu.13011","DOIUrl":"https://doi.org/10.1111/jnu.13011","url":null,"abstract":"<p><strong>Introduction: </strong>The War on Terrorism, which included Operation Enduring Freedom (OEF) in Afghanistan from 2001 to 2014 and the concurrent Operation Iraqi Freedom (OIF) from 2003 to 2011, exposed military nurses to situations and challenges for which many reported feeling unprepared. Clinically, nurses faced multi-trauma injuries and devastating wounds suffered by military troops and civilians alike. Cultural issues and harsh living conditions added further complications to the care environment. The purpose of this study was to address the research question: How do military nurses identify, assess, manage, and personally resolve ethical issues occurring in nursing practice during wartime deployments?</p><p><strong>Design: </strong>Qualitative grounded theory provided the design for this study.</p><p><strong>Methods: </strong>Using the constant comparative method, data collection, and data analysis occurred simultaneously to build a theory of ethical issues management during wartime. Using a focused interview guide responsive to emerging themes and developing theory, interviews were conducted until theoretical saturation was achieved. Participants represented primarily Army (55%) active duty (83%) female nurses (71%) who had deployed to Iraq (52%), Afghanistan (32%), or both (16%). A sampling grid was used to recruit nurses representative of the demographics deployed in support of OIF and OEF. Data analysis used grounded theory methods to identify a core construct to detail proposed relationships and concepts. Rigor was maintained in study methods and analysis using established tenets to support trustworthiness.</p><p><strong>Results: </strong>The nurses shared stories regarding their experiences during deployment. Many struggled to find internal resolutions regarding the care of detainees, cultural differences, end-of-life decision-making, pain management, and care of civilian casualties.</p><p><strong>Conclusion: </strong>The study described the ethical issues military nurses encountered during wartime and the strategies used to mitigate moral conflict. By better understanding how nurses define, assess, and manage ethical situations, we can better prepare our deploying nurses for future conflicts.</p><p><strong>Clinical relevance: </strong>Military nurses returning from wars with unresolved moral conflicts are at risk for moral distress. Moral distress has been associated with burnout, dissatisfaction with and leaving the nursing profession, compassion fatigue, and disinterest in the provision of quality patient care. In the interest of preserving the health of military nurses, steps need to be taken to provide resources for helping them prepare for, encounter, and cope with the ethical situations inherent in wartime nursing care.</p>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037699","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}