JMIR nursing最新文献

{"title":"Self-Health Monitoring by Smart Devices and Ontology Technology for Older Adults With Uncontrolled Hypertension: Quasi-Experimental Study.","authors":"Sutteeporn Moolsart, Khajitpan M Kritpolviman","doi":"10.2196/73386","DOIUrl":"https://doi.org/10.2196/73386","url":null,"abstract":"<p><strong>Background: </strong>Hypertension is a prevalent concern among older adults, often leading to complex cardiovascular complications when uncontrolled. Telenursing technology facilitates self-management, and the integration of domain-specific ontology allows real-time interpretation of behavioral and biometric data to provide personalized recommendations, enhancing patient engagement and self-care.</p><p><strong>Objective: </strong>This study aimed to examine the within-group and between-group effects of self-health monitoring using smart devices combined with ontology technology on hypertension-controlling behavior and mean arterial pressure among older adults with uncontrolled hypertension.</p><p><strong>Methods: </strong>The quasi-experimental design was conducted with 91 older adults in Bangkok, Thailand (46 experimental and 45 comparison participants). Participants in the experimental group used the \"HT GeriCare@STOU\" app on smartphones, linked to smartwatches for blood pressure monitoring, step count, and sleep pattern, with telenursing support via video calls. Data on hypertension-controlling behavior were collected using a validated questionnaire (Cronbach α=0.83; content validity index=0.98). Descriptive statistics and t tests were used to analyze within-group and between-group differences.</p><p><strong>Results: </strong>Within-group analysis revealed that experimental participants showed improved hypertension-controlling behavior and reduced mean arterial pressure after the program. Between-group comparisons indicated that mean arterial pressure in the experimental group was significantly lower than in the comparison group (P<.05), although hypertension-controlling behavior did not differ significantly between groups. Older adult participants and nurses reported high satisfaction, noting that real-time feedback increased awareness of blood pressure and motivated independent health behavior adjustments.</p><p><strong>Conclusions: </strong>Self-health monitoring using smart devices integrated with ontology technology effectively improved physiological outcomes and supported self-management in older adults with uncontrolled hypertension. The ontology framework enabled personalized, real-time decision support, highlighting its novelty, and potential to enhance nursing practice. Future studies with larger samples and longer follow-up are recommended to further evaluate the intervention's effectiveness and scalability.</p>","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e73386"},"PeriodicalIF":4.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145294614","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":"Stress and Well-Being Intervention and mHealth Delivery Adaptation for Latinx Millennial Caregivers: Qualitative User-Centered Design Approach.","authors":"Megan Thomas Hebdon, Galilea D Dupree, Janice Hernandez, Heather Cuevas, Michael Thomas, Shane Burt, Neil Peterson, Sharon D Horner","doi":"10.2196/73621","DOIUrl":"10.2196/73621","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;This study aimed to adapt a stress and well-being intervention delivered via a mobile health (mHealth) app for Latinx millennial caregivers. This demographic, born between 1981 and 1996, represents a significant portion of caregivers in the United States, with unique challenges due to higher mental distress and poorer physical health than noncaregivers. Latinx millennial caregivers face additional barriers, including higher rates of being uninsured and increased caregiving burdens.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We used a community-informed and user-centered design approach to tailor an existing mHealth app to better meet the stress and well-being needs of Latinx millennial caregivers.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We used a 2-step, multifeedback approach. In step 1, Latinx millennial caregivers participated in focus groups to evaluate wireframes for the proposed mHealth app. In step 2, participants engaged in usability testing for 1 week, concluding with short interviews for feedback. Participants were recruited through various channels, including social media and community clinics. Data were analyzed inductively using a rapid qualitative content analysis approach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 29 caregivers (n=20, 69% women) participated in the study. Participants had a mean age of 31 (SD 4.10) years, with most (n=28, 97%) caring for an adult and 3% (1/29) caring for children with chronic conditions. All participants completed the step 1 focus groups, with a subset of 10% (3/29) of the caregivers completing the usability testing in step 2. The most liked features included (1) the stress rating scale because it helped them understand stress and mental health; (2) the mindfulness options, which allowed for flexible timing of activities; (3) the journaling prompts for addressing daily challenges and positive experiences; and (4) the resource list for its employment and financial content. One concern was that the journaling prompts may take too much time to complete after a long and hard day. Some suggestions for improvement included a better tracking system, gamification, caregiving education, a checklist of emotions to use with the journal, tailored resources, and ways to connect with other caregivers. During step 2, participants noted that the app was user-friendly but had some glitches and unclear privacy policies. Participants liked the meditation options, resource variety, and daily stress log but wanted more journaling space, longer meditations, and additional relaxation activities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Future iterations should consider integrating more personalized and community-specific resources, leveraging platforms such as podcasts for broader engagement, and the use of information-based videos to support caregiver skill acquisition. Caregivers expressed needs beyond the scope of the app, such as resource access, demonstrating the need for upstream and downstream intervent","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e73621"},"PeriodicalIF":4.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Intention of Primary Health Nurses to Participate in Internet Plus Nursing Service: Cross-Sectional Survey.","authors":"Bin Xu, Suyuan Li, Keyu Chen, Lei Ding, Longxiu Liu","doi":"10.2196/72846","DOIUrl":"10.2196/72846","url":null,"abstract":"<p><strong>Background: </strong>\"Internet Plus Nursing Service\" (IPNS) offers innovative solutions for China's growing home health care demands. Understanding primary care nurses' participation intentions is crucial for service optimization.</p><p><strong>Objective: </strong>This study evaluates primary health nurses' intention to participate in IPNS-a technology-mediated home care model combining mobile health platforms with in-person visits-and examines how digital readiness, safety perceptions, and organizational factors influence participation decisions, to guide policy optimization for scalable digital home health care delivery.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted in Jiangsu Province, China (December 2023-December 2024) using the validated Participation Intention of Nurses on IPNS Scale. Convenience sampling enrolled 3952 nurses from 13 prefecture-level cities in Jiangsu-the second-tier administrative divisions in China that typically encompass both urban and rural areas, each with independent health care systems governed by municipal health authorities. Statistical analyses included t tests and ANOVA with SPSS 22.</p><p><strong>Results: </strong>A total of 3952 surveys were completed. The participation intention scale yielded a mean (SD) total score of 66.13 (7.89) across respondents. Subscale analysis revealed mean (SD) scores of 18.57 (2.68) for participation attitude, 18.87 (2.49) for subjective norms, and 25.67 (3.48) for perceived behavioral control. Significant demographic predictors of participation intention were identified through statistical analysis. Male nurses demonstrated stronger intention (t72.974=-23.139, P<.0001), as did those over 30 years old (F39,51=27.215, P<.0001) and bachelor's degree holders (t2185.018=-4.994, P<.0001). Workplace characteristics also showed significant associations, with nursing management department staff (F39,51=45.877, P<.0001) and those with less organizational workloads (F39,51=9.829, P<.0001) displaying greater intention. Professional factors including higher positional rank (F39,51=37.32, P<.0001), more advanced titles (F39,51=30.176, P<.0001), and over 11 years of experience (F39,51=5.242, P=.001) predicted stronger participation intent. Finally, nurses earning 5000-10,000 RMB (a currency exchange rate of RMB 1=US $0.71 is applicable) monthly showed significantly higher intention scores (F39,51=16.141, P<.0001).</p><p><strong>Conclusions: </strong>Policymakers should prioritize 3 interventions: (1) develop IPNS-specific safety protocols and legal safeguards, (2) optimize workload allocation through intelligent scheduling systems, and (3) establish tiered incentive mechanisms targeting middle-income nurses and experienced practitioners.</p>","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e72846"},"PeriodicalIF":4.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12488169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145208534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Gamification as a Tool for Understanding Mental Disorders in Nursing Students: Qualitative Study.","authors":"Pablo Del Pozo-Herce, Alberto Tovar-Reinoso, Eva García Carpintero-Blas, Ana Casaux Huertas, Regina Ruiz de Viñaspre-Hernández, Antonio Martínez-Sabater, Elena Chover-Sierra, Marta Rodríguez-García, Raul Juarez-Vela","doi":"10.2196/83237","DOIUrl":"10.2196/83237","url":null,"abstract":"","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e83237"},"PeriodicalIF":4.0,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nurses' Intention to Integrate AI Into Their Practice: Survey Study in Canada.","authors":"Guy Pare, Louis Raymond, Faustin Armel Etindele Sosso","doi":"10.2196/76795","DOIUrl":"10.2196/76795","url":null,"abstract":"<p><strong>Background: </strong>The integration of artificial intelligence (AI) into health care is set to revolutionize the sector, offering opportunities to enhance diagnostic accuracy, personalize treatment, and improve patient outcomes. However, little is known about nurses' readiness to integrate AI into their professional practice.</p><p><strong>Objective: </strong>This study aimed to identify the key factors influencing nurses' intention to integrate AI into their practice.</p><p><strong>Methods: </strong>An online survey was distributed to 3000 members of the professional order of nurses in Quebec, Canada. A total of 312 nurses participated, with 307 completing the full questionnaire. Data were analyzed using descriptive statistics and partial least squares structural equation modeling.</p><p><strong>Results: </strong>Nurses' beliefs about the role of AI and trust in AI were found to predict intention to integrate AI significantly. Facilitating conditions influenced beliefs and familiarity with AI, which in turn shaped perceptions of AI's impact. The model explained 65% of the variance in behavioral intention.</p><p><strong>Conclusions: </strong>The findings highlight the importance of enhancing nurses' familiarity with AI and fostering positive beliefs and attitudes to promote effective integration. Educational strategies targeting these beliefs can facilitate AI adoption in nursing.</p>","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e76795"},"PeriodicalIF":4.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12413143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stress and Well-Being Intervention and mHealth Delivery Adaptation for Latinx Millennial Caregivers: A Qualitative User-Centered Approach.","authors":"Megan Thomas Hebdon, Galilea D Dupree, Janice Hernandez, Heather Cuevas, Michael Thomas, Shane Burt, Neil Peterson, Sharon D Horner","doi":"10.2196/73621","DOIUrl":"10.2196/73621","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The study aimed to adapt a stress and well-being intervention delivered via a mobile health (mHealth) app for Latinx Millennial caregivers. This demographic, born between 1981 and 1996, represents a significant portion of caregivers in the United States, with unique challenges due to higher mental distress and poorer physical health compared to non-caregivers. Latinx Millennial caregivers face additional barriers, including higher uninsured rates and increased caregiving burdens.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We used a community-informed and user-centered design approach to tailor an existing mHealth app to better meet the stress and well-being needs of Latinx Millennial caregivers.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We employed a two-step, multi-feedback approach. In step one, Latinx Millennial caregivers participated in focus groups to evaluate wireframes for the proposed mHealth app. In step two, participants engaged in usability testing for one week, concluding with short interviews for feedback. Participants were recruited through various channels, including social media and community clinics. Data were analyzed inductively using a rapid qualitative content analysis approach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 29 caregivers (69% women, mean age 31) participated in the study. Participants had a mean age of 31 (SD=4.10), with most (n=28, 96%) caring for an adult and one (4%) caring for children with chronic conditions. All participants completed the step one focus groups, with a subset of 3 caregivers completing usability testing in step two. The most liked features included the: 1) stress rating scale because it helped them understand stress and mental health, 2) mindfulness options because it allowed for flexible timing of activities, 3) journaling prompts because it was a way to address daily challenges and contemplate positives, and 4) resource list for its employment and financial content. One concern was that the journaling prompts may take too much time or effort to complete after a long and hard day. Some suggestions for improvement included: a better tracking system, gamification, caregiving education, a checklist of emotions to use on the journal, tailored resources, and ways to connect with a community of similar caregivers. During step two, participants noted the app was user-friendly but had some glitches and unclear privacy policies. Participants liked the meditation options, resource variety, and daily stress log but wanted more journaling space, longer meditations, and additional relaxation activities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Caregivers highlighted the need for tailored resources and additional stress-relief activities. Future iterations should consider integrating more personalized and community-specific resources, leveraging platforms like podcasts for broader engagement, and the use of information-based videos to support caregiver skill acquisition. Caregivers expressed ne","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145031204","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":"Assessing the Use of Welfare Technology in Social Care for Older Adults Through Assistant Nurses' Perceptions of Upskilling and Care Delivery Outcomes: Cross-Sectional Study.","authors":"Mahwish Naseer, Lotta Dellve","doi":"10.2196/65641","DOIUrl":"https://doi.org/10.2196/65641","url":null,"abstract":"<p><strong>Background: </strong>The implementation of welfare technologies, a broad array of technologies that have the potential to maintain or improve individuals' safety, independence, and participation, has increased rapidly in recent years, offering new ways of delivering care. However, studies of welfare technology use in the social care sector are scarce.</p><p><strong>Objective: </strong>This study aims to explore the use of different types of welfare technologies, training in the use of these technologies, and to identify their associations with outcomes for care recipients and frontline care workers in the social care of older adults.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted based on a nationwide randomized sample of assistant nurses employed in social care for older adults in Sweden (N=1163; response rate 23%). Dependent variables were outcomes for care recipients (continuity of care, participation, and reduction in loneliness) and upskilling for frontline care workers. The exposure variables were types of welfare technologies and training in the use of such technologies. Associations between exposure and dependent variables were assessed through logistic regression models.</p><p><strong>Results: </strong>According to the perceptions of care workers, interactive technologies were significantly positively associated with continuity of care (odds ratio [OR] 1.58, 95% CI 1.15-2.18), participation (OR 2.01, 95% CI 1.48-2.74), and reduction in loneliness among care recipients (OR 1.92, 95% CI 1.41-2.62). In addition, there was a significant positive association between interactive technologies and upskilling of care workers (OR 2.44, 95% CI 1.58-3.79). Despite the benefits of welfare technology, the effects can also be negative, as shown by the findings on the use of digital documentation (OR 0.69, 95% CI 0.49-0.96), digital locks or cameras or sensors (OR 0.62, 95% CI 0.46-0.84), and the lower likelihood of participation. Training in the use of welfare technology was significantly associated with outcomes for care recipients (continuity of care: OR 2.02, 95% CI 1.53-2.66; participation: OR 1.91, 95% CI 1.45-2.51; reduction in loneliness: OR 1.74, 95% CI 1.31-2.30), as well as upskilling of care workers (OR 4.59, 95% CI 3.28-6.42). The interaction analyses showed that participants who had not received any training but used digital documentation reported favorable views on continuity of care and upskilling, whereas those who had received training expressed concerns about participation and addressing loneliness.</p><p><strong>Conclusions: </strong>The potential outcomes of welfare technology use in social care for older adults can vary with the types of technologies used. Care workers hold positive perceptions toward interactive technologies to improve care delivery outcomes and skill development. The findings on training and improved outcomes suggest that investing resources to promote training can reinforce pos","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e65641"},"PeriodicalIF":4.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12379745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144981286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models in Nursing Education: Concept Analysis.","authors":"Julia Harrington, Richard G Booth, Kimberley T Jackson","doi":"10.2196/77948","DOIUrl":"https://doi.org/10.2196/77948","url":null,"abstract":"<p><strong>Background: </strong>Large language models (LLMs) are increasingly used in nursing education, yet their conceptual foundations remain abstract and underexplored. This concept analysis addresses the need for clarity by examining the relevance, meaning, contextual applications, and defining attributes of LLMs in nursing education, using Rodgers' evolutionary method.</p><p><strong>Objective: </strong>This paper aims to explore the evolutionary concept of LLMs in nursing education by providing a concept analysis through a comprehensive review of the existing published literature.</p><p><strong>Methods: </strong>Rodgers' evolutionary concept analysis method was used. PubMed, CINAHL, PsycINFO, Scopus, and Google Scholar were used to search for relevant publications. A total of 41 papers were included based on inclusion criteria that focused on studies published in English within the last 5 years to ensure relevance to the current use of LLMs exclusively in nursing education. Studies were excluded if they focused on clinical nursing applications, were not available in English, lacked full-text accessibility, or examined other artificial intelligence (AI) technologies unrelated to LLMs (eg, robotics).</p><p><strong>Results: </strong>As a result of this analysis, a proposed definition of LLMs in nursing education has been developed, describing them as accessible, personalized, innovative, and interactive tools that create revolutionary learning experiences, often leading to enhanced cognitive and skill development and improvement in learning and teaching quality.</p><p><strong>Conclusions: </strong>This concept analysis highlights LLMs' transformative potential to enhance access to resources, support individualized learning, and augment nursing education. While promising, careful attention must be given to their limitations and ethical implications, ensuring their integration aligns with the values and goals of nursing education, particularly in specialized areas such as graduate nursing programs.</p>","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e77948"},"PeriodicalIF":4.0,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144981259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunities, Challenges, and Future Directions for the Integration of Automation in Nursing Practice: Discursive Study.","authors":"Joseph Andrew Pepito, Neilan John Acaso, Rommel Merioles, Judith Ismael","doi":"10.2196/72674","DOIUrl":"10.2196/72674","url":null,"abstract":"<p><strong>Background: </strong>Global health care systems are under increasing strain due to aging populations, workforce shortages, and rising patient complexity. In response, automation technologies are being explored as a means to optimize nursing workflows, reduce burdens, and improve patient outcomes. However, the integration of such technologies raises complex ethical, legal, and professional considerations that remain insufficiently addressed in current literature.</p><p><strong>Objective: </strong>This study aims to critically examine the integration of automation into nursing practice through a discursive analysis. Specifically, it seeks to (1) identify nursing tasks most amenable to automation; (2) evaluate the benefits and drawbacks of automating these tasks; (3) explore ethical and legal implications; (4) propose strategies for ethical and equitable integration; and (5) outline future directions for research, practice, and policy.</p><p><strong>Methods: </strong>An integrative review and conceptual analysis were conducted, grounded in sociotechnical systems theory and the ethics of care. A structured search across PubMed, CINAHL, Scopus, Web of Science, and JMIR Publications identified 73 peer-reviewed papers published between 2019 and 2025. Thematic synthesis was performed to identify key domains relevant to automation in nursing.</p><p><strong>Results: </strong>Five major categories of automatable nursing tasks were identified: administrative documentation, medication management, patient monitoring, infection control, and mobility support. Automation in these areas was associated with improved efficiency, enhanced patient safety, and reduced physical and cognitive workload for nurses. Nevertheless, challenges such as deskilling, dehumanization of care, inequitable access, and unclear legal accountability were prominent. The study proposes the Integration of Automation Technologies in Nursing Practice Conceptual Framework.</p><p><strong>Conclusions: </strong>The ethical integration of automation into nursing practice requires more than technological readiness; it demands policy development, targeted education, and inclusive governance. When guided by professional values and human-centered design, automation can complement nursing practice and improve care delivery. Future research should prioritize longitudinal impact assessments, legal clarity, and equitable infrastructure investment to support sustainable adoption.</p>","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e72674"},"PeriodicalIF":4.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352802/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Knowledge Base for an Integrated Older Adult Care Model (SMART System) Based on an Intervention Mapping Framework: Mixed Methods Study.","authors":"Rongrong Guo, Shuqin Xiao, Fangyu Yang, Huan Fan, Yanyan Xiao, Xue Yang, Ying Wu","doi":"10.2196/59276","DOIUrl":"10.2196/59276","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Although mobile health apps integrated with Internet of Things-enabled devices are increasingly used to satisfy the growing needs for home-based older adult care resulting from rapid population aging, their effectiveness is constrained by 3 key challenges: a focus on specific functions rather than on holistic and integrated support, absence of a solid theoretical framework for development, and a lack of personalized, real-time feedback to address diverse care needs. To overcome these limitations, we developed a knowledge-based clinical decision support system using mobile health technology-an intelligent and integrated older adults care model (SMART system).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to systematically outline the development process and outcomes of a knowledge base and trigger rules for the SMART system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Our study adopted a user-centered approach guided by the nursing process and intervention mapping (IM) framework. We first identified older adult care needs through semistructured, in-depth interviews. Guided by the nursing process and informed by guidance from the World Health Organization's Integrated Care for Older People and World Health Organization International Classification of Functioning, Disability, and Health, along with the North American Nursing Diagnosis Association-I nursing diagnosis, we then determined care problems along with their underlying causes and risk factors and diagnostic criteria. Building on these findings, we applied the first 3 steps of the intervention mapping framework to formulate corresponding long-term and short-term care objectives, select appropriate evidence-based interventions, and match practical implementation approaches, which were grounded in rigorous evidence derived from systematic literature reviews, clinical guidelines, and expert insights. We also developed a set of trigger rules to link abnormalities in older adults with corresponding care problems and interventions in the SMART knowledge base.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The semistructured in-depth interviews identified 5 types of care needs-daily life care, health care, external support, social participation, and self-development-which formed the foundation of the SMART knowledge base. Based on this, we identified 138 care problems, each with associated causes and risk factors and diagnostic criteria. The objective matrix comprised 138 long-term and 195 short-term care objectives. Guided by 15 expert-defined selection criteria, we then selected 450 evidence-based interventions, each paired with at least 1 feasible and practical implementation approach. Additionally, we developed diagnostic rules to match the assessment data with relevant care problems and their causes and risk factors and intervention trigger rules to formulate personalized interventions based on individual characteristics, ensuring tailored care aligned with specific care objectives.&lt;/p","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e59276"},"PeriodicalIF":4.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}