Journal of Doctoral Nursing Practice最新文献

{"title":"Reducing Stress, Anxiety, and Depression in Nursing Students With a Cognitive-Behavioral Skills-Building Intervention.","authors":"Sarah L Campbell, Bernadette Mazurek Melnyk","doi":"10.1891/JDNP-2023-0004","DOIUrl":"https://doi.org/10.1891/JDNP-2023-0004","url":null,"abstract":"<p><p><b>Background:</b> While it is well known that nursing students experience high levels of stress, few programs provide targeted interventions to minimize the effects of prolonged, excessive stress, including anxiety and depression. <b>Objective:</b> The objective of this project was to evaluate the implementation of an evidence-based intervention aimed to reduce stress, anxiety, and depression in prelicensure nursing students by bolstering coping skills through the delivery of a cognitive-behavioral therapy (CBT)-based skills-building program called MINDSTRONG^© <b>Methods:</b> A total of 21 prelicensure nursing students were recruited on a voluntary basis from both the undergraduate and graduate nursing programs at a large university in Southern California. A program manual was provided, and students participated in seven weekly online interactive sessions, based on key concepts of CBT. Outcomes were measured using the Perceived Stress Scale, the Generalized Anxiety Disorder-7, and the Patient Health Questionnaire-2. <b>Results:</b> The MINDSTRONG intervention produced statistically significant reductions in anxiety, decreasing scores from moderate to mild levels (<i>p</i> < .00, Cohen's <i>d</i> = 1.0), while depression showed meaningful improvements approaching significance (<i>p</i> = .10, Cohen's <i>d</i> = 0.38) and stress demonstrated positive effects particularly among high-severity participants (Cohen's <i>d</i> = 1.83). Participants with elevated baseline symptoms across all three domains experienced substantial improvements, with effect sizes ranging from 1.28 to 2.77. <b>Conclusion:</b> After receiving MINDSTRONG, participants reported lower stress, anxiety, and depressive symptoms with the largest reductions in students who started the project with elevated symptom levels. <b>Implications for Nursing:</b> Findings suggest that MINDSTRONG is a feasible and effective program to assist prelicensure nursing students to cope with stress, anxiety, and depression. Providing this intervention to all nursing students could prevent serious adverse events in this high-risk population.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145811679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging Artificial Intelligence to Enhance Screening, Brief Intervention, and Referral to Treatment Training for Psychiatric Mental Health Nurse Practitioner Students: A Case Study and Future Directions for Virtual Reality Integration.","authors":"Nicole Peters Kroll, Jinsil Hwaryoung Seo, Kimberly Belcik, Cindy Weston, Elizabeth Wells-Beede","doi":"10.1891/JDNP-2025-0057","DOIUrl":"10.1891/JDNP-2025-0057","url":null,"abstract":"<p><p><b>Background:</b> Psychiatric mental health nurse practitioners (PMHNPs) play a vital role in addressing substance use disorders, particularly in underserved regions. <b>Objective:</b> This article aimed to explore the effectiveness of artificial intelligence (AI)-generated Screening, Brief Intervention, and Referral to Treatment (SBIRT) screen-based simulation in enhancing PMHNP training by using a large language model to process and understand human language. <b>Methods:</b> Three PMHNP students in a second-semester adult mental health course piloted a web-based AI simulation. Two completed postsimulation surveys assessing ease of use, realism, and educational impact. <b>Results:</b> Students reported increased confidence and found the simulation engaging, user-friendly, and realistic. They noted the absence of nonverbal cues but praised responsiveness and relevance. All respondents recommended the simulation for broader use. <b>Conclusions:</b> AI-based SBIRT training tools are promising for scalable, consistent, and effective PMHNP education. <b>Implications for Nursing:</b> Integration of AI and future virtual reality platforms utilizing a 3D display in a headset may improve mental health provider preparedness, access to simulation in rural areas, and educational outcomes while maintaining the foundational principles of therapeutic communication.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":"189-195"},"PeriodicalIF":0.8,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145507626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preparing Doctoral Nurse Leaders to Champion Artificial Intelligence in Nursing Education.","authors":"Cheryl A Fisher, Cory W Stephens, David J Bunnell, Amanda N Roesch, Veronica A Quattrini","doi":"10.1891/JDNP-2025-0056","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0056","url":null,"abstract":"<p><p><b>Background:</b> Artificial intelligence (AI) presents transformative opportunities in nursing education, particularly in Doctor of Nursing Practice (DNP) programs, where preparing graduates for technology-enhanced clinical practice is essential. However, faculty face challenges related to ethical concerns, technical proficiency, and workload demands. <b>Objective:</b> This quality improvement project evaluated the Faculty AI Champion Program, designed to build faculty competence and confidence in integrating AI tools into DNP curricula and across the health professions. <b>Methods:</b> A mixed-method, single-site pilot using a one-group pretest-posttest design was implemented, guided by the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) framework. Seven faculty members participated in completing the full program, which included workshops, hands-on training, and peer support. <b>Results:</b> Participants reported increased AI understanding (mean score improvement from 3.4 to 4.25) and enhanced self-efficacy (67% stated \"yes\") in identifying and applying AI tools. Faculty rated program satisfaction highly (mean score 9.5/10). Qualitative feedback highlighted interest in practical AI applications. <b>Conclusions:</b> The Faculty AI Champion Program effectively enhanced faculty knowledge and confidence in AI integration, supporting both productivity and pedagogical innovation. <b>Implications for Nursing:</b> Scaling this program can help address faculty shortages, reduce workload pressures, and strengthen competency-based DNP education through responsible AI use. Institutional support is critical for faculty development and ethical AI integration.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":"18 3","pages":"181-188"},"PeriodicalIF":0.8,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145764032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reimagining Graduate Study With Generative Artificial Intelligence-Supported Study Strategies: A Doctor of Nursing Practice Student's Perspective.","authors":"Katie A Silva, Deanna M Sheets","doi":"10.1891/JDNP-2025-0058","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0058","url":null,"abstract":"<p><p><b>Background:</b> Artificial intelligence (AI) is transforming higher education by offering accessible tools that enhance comprehension and efficiency. While AI use in clinical decision-making is expanding, little research explores how Doctor of Nursing Practice (DNP) students use AI to support their academic learning. <b>Objective:</b> The aim of the study was to describe a DNP student's experience using a generative AI tool to supplement traditional study strategies and improve learning outcomes. <b>Methods:</b> This case narrative outlines how Chat Generative Pre-trained Transformer (ChatGPT), an AI tool, was integrated into a first-year DNP student's daily study routines for concept simplification, reinforcement through repetition, and clarification of complex content. The approach is evaluated against academic performance, clinical feedback, and alignment with the American Association of Colleges of Nursing Essentials. <b>Results:</b> ChatGPT improved study efficiency, enhanced understanding of complex material, and supported academic and clinical performance. The tool aligned with core nursing competencies by promoting critical thinking, personalized learning, and ethical technology use. <b>Conclusions:</b> When used responsibly and verified against reliable sources, AI tools can supplement traditional learning methods in nursing education. <b>Implications for Nursing:</b> By using AI as a study tool, graduate-level nursing students can strengthen critical thinking, improve knowledge retention, and support the development of confident, self-directed advanced practice nurses who are prepared for modern clinical practice.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":"18 3","pages":"196-204"},"PeriodicalIF":0.8,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145764088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing the Objective Structured Clinical Examination Using Artificial Intelligence.","authors":"Sun Jones, Linnea M Axman, Erich Widemark, Carol Bafaloukos, Evangeline Tejada Sabado, Chesley Cranch-Kaniut, Margo S Patterson","doi":"10.1891/JDNP-2025-0061","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0061","url":null,"abstract":"<p><p><b>Background:</b> Artificial intelligence (AI) offers promising solutions for nurse practitioner education, especially in addressing challenges related to evaluating Objective Structured Clinical Examinations (OSCEs), such as examiner bias and delayed feedback. AI tools employing natural language processing and generative AI have the potential to enhance the accuracy and efficiency of clinical assessments. <b>Objective:</b> This product evaluation was conducted to determine whether AI-generated OSCE assessments align with faculty evaluations. <b>Methods:</b> A descriptive correlational design was used to assess product acceptability, feasibility, and agreement between AI and faculty assessments. A convenience sample of 13 nurse practitioner students was randomly divided into either a traditional evaluation group or an AI-assisted group. The AI-generated transcripts were scored using the same rubric used by faculty, and agreement was measured with Spearman's correlation, Cohen's Kappa, and interrater reliability percent agreement (IRR%). <b>Results:</b> Spearman's correlations ranged from negligible to moderate, with the highest in the physical/mental health exams category (<i>r</i> = .54, <i>p</i> < .05). However, Cohen's Kappa (.14-.41) and IRR% (31%-54%) showed weak agreement. <b>Conclusions:</b> These results suggest that AI feedback was inconsistent with faculty assessments, possibly due to technical issues and limitations in the rubric. Despite these limitations, this product evaluation demonstrated that the AI tool was easy to use and that faculty believed it could improve feedback quality. <b>Implications for Nursing:</b> These findings underscore both the promise and the current limitations of AI-supported clinical assessment. With thoughtful attention to these shortcomings, the ease of integration and capacity for enhanced learning offered by AI tools can help advance clinical competence and foster excellence in nurse practitioner and doctoral nursing education.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145726650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal Palliative Education Integrated With Cutting-Edge Technology for Acute Care Nurses.","authors":"Lauren Assayag, Christine King, Angela Jun","doi":"10.1891/JDNP-2024-0014","DOIUrl":"10.1891/JDNP-2024-0014","url":null,"abstract":"<p><p><b>Background:</b> The lack of palliative care education and communication among frontline nurses impacts care for patients with advanced chronic diseases. Literature suggested that additional educational approaches positively influence nurses' knowledge and communication. <b>Objective:</b> The aim of this study was to augment their understanding of palliative care and enhance their self-efficacy in palliative care communication by an innovative educational intervention tailored for acute care nurses. <b>Methods:</b> A total of 13 participants completed multimodal education, including a 50-minute recorded lecture, a virtual reality-based clinical vignette, and a laminated infographic badge. Four outcomes were measured pre- and postimplementation. <b>Results:</b> Engagement in palliative care discussions was increased by approximately 24.4%. More than 60% of participants expressed extreme presence in a virtual reality environment, and 92% of them would use virtual reality again in the future. <b>Conclusion:</b> Multimodal palliative education integrated with cutting-edge technology successfully helped acute care nurses engage in more palliative care discussion. Virtual reality was well accepted as an educational method. Expanding this educational approach may increase utilization of palliative care services, reduce health care costs, and prevent human suffering from unnecessary medical services near the end of life. <b>Implications for Nursing:</b> Innovative approaches to palliative care education such as virtual reality can be used as a successful educational modality for registered nurses.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilience and Burnout in Middle-Aged Climacteric Women: A Cross-Sectional Study.","authors":"Seonah Lee","doi":"10.1891/JDNP-2025-0008","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0008","url":null,"abstract":"<p><p><b>Background:</b> Adverse symptoms associated with menopause can resemble burnout symptoms. Resilience and menopausal symptom-related burnout have not been addressed in middle-aged climacteric women. <b>Objectives:</b> The aim of the study is to investigate the association between resilience and burnout in middle-aged climacteric women. <b>Methods:</b> Two hundred middle-aged women aged 44-55 years were recruited through an online survey panel developed by a survey company. Data were collected using Korean versions of the Copenhagen Burnout Inventory's Personal Burnout Instrument and Brief Resilience Scale. <b>Results:</b> Resilience, living alone, and the absence of menopausal symptoms were significantly associated with reduced burnout. In contrast, the perception of oneself as unhealthy and a body mass index range representing underweight were significantly associated with increased burnout. Findings using mean analysis showed that the more severe the menopausal symptoms are, the higher the burnout score is. <b>Conclusions:</b> Resilience, menopausal symptoms, living alone, the perception of unhealthiness, and a very low body weight should be considered important factors when addressing burnout among middle-aged climacteric women in community and clinical practice. <b>Implications for Nursing:</b> The relationships among burnout, menopausal symptoms, and resilience should be considered in clinical practice.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Personal Reflection on an Artificial Intelligence Revolution in Nursing.","authors":"Grace H Sun","doi":"10.1891/JDNP-2025-0089","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0089","url":null,"abstract":"","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145507604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNP Faculty 2.0: Transforming Teaching, Research, and Professional Development in the Age of Artificial Intelligence.","authors":"Amanda Roesch, Emily Fox, Elizabeth Gatewood, Lisa Taylor, Bernita Armstrong, Veronica Quattrini","doi":"10.1891/JDNP-2025-0052","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0052","url":null,"abstract":"<p><p><b>Background:</b> The rapid integration of artificial intelligence (AI) into health care and education is reshaping the landscape of nursing practice. For Doctor of Nursing Practice (DNP) educators, this evolution demands a reimagining of how faculty teach, lead, conduct research, and prepare future nurse leaders. <b>Objective:</b> This manuscript examines the transformative role of AI in DNP education, emphasizing strategies to support faculty development and successful integration. <b>Methods:</b> Drawing on current literature and expert insights, the manuscript outlines institutional strategies to support faculty in adopting AI. Key barriers addressed include ethical concerns, data security, and resistance to change. <b>Results:</b> AI enhances teaching strategies, research capacity, leadership development, and professional growth. Recommendations are offered for embedding AI literacy in DNP curricula and strengthening faculty competencies in ethical and effective AI use. <b>Conclusions:</b> Faculty teaching in DNP programs must be prepared to lead AI integration. Faculty development and institutional support are critical to ensure alignment with nursing's professional and ethical standards. <b>Implications for Nursing:</b> DNP educators are uniquely positioned to champion AI adoption, ensuring innovations in nursing remain grounded in the core values of integrity, equity, and humanism. Building AI literacy among faculty is essential for sustaining excellence in education and advancing the profession in the digital age.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145507643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating Ethical, Legal, and Social Implications of Artificial Intelligence in Advanced Practice Nursing.","authors":"Sara Gleasman-DeSimone, Angel Anthamatten, Wanda Hilliard, Aimee Vael, Tracie Kirkland, Susan Conaty-Buck","doi":"10.1891/JDNP-2025-0047","DOIUrl":"https://doi.org/10.1891/JDNP-2025-0047","url":null,"abstract":"<p><p><b>Background:</b> The rapid integration of artificial intelligence (AI) into health care systems offers new opportunities for advanced practice registered nurses (APRNs). However, this innovation also introduces a variety of concerns regarding ethical and responsible use and implications for patient care, privacy, data integrity, clinical systems, and professional practice. Ethical implications associated with the integration of AI in health care require critical examination by APRNs. <b>Objective:</b> This article examines ethical, legal, and social implications of integrating AI in advanced practice nursing. Grounded in the American Nurses Association Code of Ethics and the American Association of Colleges of Nursing Essentials, it provides practical strategies for APRNs to engage with AI technologies in ways that uphold core values such as patient autonomy, equity, trust, and human connection. <b>Methods:</b> A narrative review of the literature was conducted, supplemented by an analysis of current AI tools and illustrative case studies, to identify ethical considerations and educational strategies for implementing AI in advanced practice nursing. Real-world examples, including clinical decision support systems, predictive analytics, and AI-assisted documentation, were examined to highlight the potential benefits and risks of AI integration. <b>Results:</b> AI tools can enhance diagnostic accuracy, streamline documentation, and improve patient care. However, ethical risks include biased algorithms, privacy breaches, and depersonalized care. Case examples from inpatient emergency care, outpatient primary care, and academic settings illustrate how APRNs can mitigate these risks through transparent communication, interdisciplinary collaboration, and targeted technology training. Key themes that emerged from the literature highlight the potential of AI to enhance diagnostic accuracy, streamline clinical documentation, and improve patient education. However, significant ethical concerns were also identified, including algorithmic bias, data privacy risks, and the potential for depersonalized care. <b>Conclusions:</b> APRNs will play a critical role in ensuring that AI is used ethically, responsibly, and effectively. By actively engaging in implementation efforts, they help balance technological innovation with preserving human interaction and clinical judgment. <b>Implications for Nursing:</b> APRNs must take the lead in driving the ethical integration of artificial intelligence by shaping policies, advancing education, and implementing clinical strategies that protect patient safety, promote equity, and uphold professional values. To lead effectively in this rapidly changing landscape, they must actively develop AI competencies, engage in interdisciplinary collaboration, and advocate for responsible, patient-centered innovation in practice.</p>","PeriodicalId":40310,"journal":{"name":"Journal of Doctoral Nursing Practice","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145507174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}