JMIR nursing最新文献

Background: The growing demand for older adults care due to aging populations and health care workforce shortages requires innovative solutions. Socially assistive robots (SARs) are increasingly explored for their potential to reduce workload by handling routine tasks. Yet, adoption can be hindered by various health care workers' concerns.

Objective: This study examined the perceptions of health care workers toward SARs before and after a pilot use in a clinical nursing care setting. The study focused on SAR usability, emotional appropriateness, and readiness for adoption.

Methods: A mixed methods pilot study was conducted at the East Tallinn Central Hospital's Nursing Care Clinic in collaboration with Tallinn University of Technology. The TEMI v3 (Robotemi) robot was used for 2 weeks for visitor guidance, goods delivery, and patrolling tasks. Health care workers filled in pre- and postintervention questionnaires with Likert-scale items and a broad open-ended question. Quantitative data were analyzed for changes in perceived safety, trust, and usability. Qualitative data underwent thematic analysis to understand participants' opinions.

Results: Out of 45 involved health care workers, 20 completed the pretest questionnaire, and 5 completed the posttest questionnaire (a 75% attrition). Pretest results show that 17 of 20 (85%) participants had limited previous exposure to SARs and mixed perceptions of their role, with 9 (45%) viewing SARs as machines and 6 (30%) as somewhat human-like. Although 60% believed SARs could become mainstream within 5-10 years, there were concerns about the robot's emotional adequacy and job displacement. Posttest findings showed increased confidence in SARs, with all respondents perceiving them as safe tools. Qualitative results indicate improved trust and readiness to integrate SARs into daily routines, with 4 out of 5 (80%) being willing to advocate for SAR use. Still, participants noted limited impact on facilitating their jobs.

Conclusions: The study indicates that short-term collaboration with SARs can enhance health care workers' confidence and their readiness for adoption. However, actual use would need proper emotional adequacy from the robot and aligning its functionalities with specific care needs. The future studies need to examine long-term impacts on care quality and job satisfaction, and also strategies to address generational differences and technophobia among health care staff. Transparent communication and proper training are required to ensure acceptance.

Background: The rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of nursing students as future health care professionals to adopt AI-based health care technologies, along with the factors influencing these attitudes, are critical for facilitating the effective integration of AI in health care settings.

Objective: This study aimed to assess the readiness and acceptance of nursing students regarding the use of AI-based health care technologies in the nursing skills training in Saudi Arabia.

Methods: A descriptive cross-sectional research design was used. A convenience sampling technique was applied to recruit 322 participants. Data were collected between June and September 2023 using a self-administered questionnaire that included the technology readiness index (TRI) and the technology acceptance scale.

Results: Approximately 92.2% (297/322) of participants exhibited positive attitudes toward AI, and 74.8% (241/322) demonstrated innovativeness, indicating a generally favorable perception of AI. However, more than half of the students (59% [190/322] and 59.3% [191/322], respectively) reported feelings of discomfort and negative perceptions regarding AI use. Regarding TRI, 69.6% (224/322) of participants showed moderate readiness, while 30.4% (98/322) exhibited a high level of TRI. A substantial majority (320/322 99.4%) expressed acceptance of AI-based technologies in their training, with only 0.6% (2/322) reporting nonacceptance. Older students (aged >22 y) exhibited significantly higher levels of AI acceptance and readiness compared to younger students (P<.001). In addition, female students demonstrated significantly greater readiness and acceptance levels than male students (P=.003). Further, third-level students reported the highest mean scores in both acceptance and readiness (66.77 and 16.69, respectively; P=.002), while first-level students had the lowest (60.59 and 15.15). Among course groups, students enrolled in Maternal and Child Health Nursing reported the highest mean scores (65.19 and 16.30), whereas those in Community Health Nursing reported the lowest (57.50 and 14.38; P<.001).

Conclusions: The findings indicate that nursing students demonstrated a generally positive level of readiness and acceptance toward the use of AI and related technologies in education and training. However, these levels remained moderate overall, highlighting the need to enhance awareness and deepen students' understanding of AI's potential to improve training effectiveness and health care quality.

Background: The current information and communication technologies, digital literacy, and ease of access to communication and information devices by nurses provide them with new ways and intention to access information for technical-scientific updating, ensuring the quality and safety of health care. Mobile learning (m-learning) offers a flexible and accessible alternative for continuing professional education, overcoming barriers such as time constraints and financial burden.

Objective: This study aimed to evaluate the effectiveness of m-learning in nurses' knowledge retention of chronic obstructive pulmonary disease self-management, using a Massive Open Online Course with integrated virtual clinical simulation.

Methods: A quasi-experimental pre- and posttest study was conducted, with no control group, among 168 nurses from a Portuguese hospital. The intervention included an asynchronous online course with 13 modules. Knowledge retention was assessed by comparing the mean scores before and after the course.

Results: The results indicated a significant increase in knowledge retention. The participants' average score increased from 59.97% in the initial assessment to 84.05% in the final assessment (P<.001). Nurses with a master's degree exhibited a higher level of basic knowledge than those with a bachelor's degree. The course completion rate was 93.45%, reflecting significant engagement attributed to gamification and clinically relevant content.

Conclusions: This study confirms the effectiveness of m-learning in improving knowledge retention in nursing. This strategy is a valuable approach to lifelong learning, promoting quality and safety in delivering health care. m-learning is useful in nurses' lifelong learning, offering flexibility and more effective support for clinical practice. Integrating virtual simulation and gamification boosted motivation and reduced drop-out rates, highlighting the potential of m-learning in lifelong learning in health care.

Background: Technological innovations make significant impacts on nursing education. New teaching strategies are constantly emerging, offering students a dynamic and interactive educational experience. The Question-Embedded Movie Clips Learning program used in this study was developed based on the drill and practice learning principle, aiming to facilitate nursing students' skills and build their confidence before entering real clinical settings.

Objective: This study aims to investigate the comparative effect between the newly developed Question-Embedded Movie Clips Learning program and the current practice of mind mapping exercises on students' learning outcomes and study satisfaction.

Methods: This study adopted a quasi-experimental design using a pretest-posttest approach with nonequivalent groups. The study sample consisted of 132 third-year nursing students who enrolled in one of two class sections of the psychiatric nursing course at a university in Thailand. By flipping a coin, the first study section (n=62) was assigned to the intervention, and the second section (n=70) was assigned to the control group. During the 2-hour class sessions, students received identical learning structure and sequence, except for group exercises of either the Question-Embedded Movie Clips Learning program or the mind mapping. The data were collected through the pretest-posttest questionnaire, the perceived satisfaction with the learning experience scale, and the open-ended reflective questions.

Results: A statistically significant increase was observed in the learning outcome scores of both the intervention group (t61=-30.48, 95% CI -10.59 to -9.28; P<.001) and the control group (t69=-27.04, 95% CI -8.19 to -7.07; P<.001); all t statistics reported are based on 2-tailed tests. There was, however, a statistically significant difference in the outcome scores between the 2 groups. Even after controlling for pretest scores, students in the experimental group had a significantly higher adjusted mean score than those in the control group (F1,129=67.67, P<.001).

Conclusions: The study has provided empirical evidence that using the Question-Embedded Movie Clips Learning program along with traditional instruction in teaching therapeutic relationships and communication significantly improves learning outcomes.

Background: Burnout among health care workers affects their well-being and decision-making, influencing patient and public health outcomes. Health care workers' health beliefs and COVID-19 vaccine decisions may affect the risks of burnout. Therefore, understanding the interplay between these crucial factors is essential for identifying at-risk staff, providing targeted support, and addressing workplace challenges to prevent further escalation of burnout-related issues.

Objective: This study examines how burnout is impacted by health beliefs and COVID-19 vaccine decisions among health care workers. Building on our previously developed Health Belief Model (HBM) classifier based on the HBM framework, which explains how individual perceptions of health risks and benefits influence behavior, we focused on key HBM constructs, including the perceived severity of COVID-19, perceived barriers to vaccination, and their relationship to burnout. We aim to leverage natural language processing techniques to automatically identify theoretically grounded burnout symptoms from comments authored by nurses in a large-scale, national survey and assess their associations with vaccine hesitancy and health beliefs.

Methods: We analyzed 1944 open-ended comments written by 1501 vaccine-hesitant nurses, using data from the Nurses' Health Study surveys. We fine-tuned LLaMA 3, an open-source large language model with few-shot prompts and enhanced performance with structured annotation guidance and reasoning-aware inference. Comments were classified into burnout dimensions-Emotional Exhaustion, Depersonalization, and Inefficacy-based on the Maslach Burnout Inventory framework.

Results: The model achieved a high weighted accuracy of 92% and an F1-score of 91% for Depersonalization. Emotional Exhaustion was identified in 52% (1003/1944) of comments, correlating strongly with perceived severity (189/323, 59%) and barriers to vaccination (281/650, 43%). Demographic analyses revealed significant variations in burnout prevalence, with older age groups reporting greater burnout.

Conclusions: This study highlights the relationship between burnout and vaccine decision-making among health care workers, uncovering areas for further exploration. By exploring the complex interplay between psychological strain and vaccine hesitancy, this study sets the stage for developing transformative interventions and policies that could redefine workforce resilience and public health strategies.

Background: Professionals across caring disciplines have played a significant role in the development of virtual care, which uses remote technologies to offer support and services from a distance. As virtual care becomes increasingly essential, instructors must ensure that students are equipped with both interpersonal abilities and digital competencies, merging traditional hands-on methods with web-based learning. Despite its growing importance, there is a lack of comprehensive frameworks to guide the design and delivery of web-based learning experiences that foster the development of virtual caring skills and competencies among students in caring professions.

Objective: This study aims to develop an evidence-informed framework to support web-based teaching and learning of virtual caring skills and competencies.

Methods: We present a synthesis of our research resulting in an evidence-informed framework. We integrated findings from an evidence synthesis, surveys, and semistructured interviews with students and educators, and consultations with key stakeholders.

Results: Principles of this framework include (1) connection and interaction; (2) compassion, empathy, and care; (3) vulnerability; (4) a client-centered focus; (5) inclusivity and accessibility; and (6) flexibility. The framework's four main domains are (1) virtual caring skills; (2) teaching and learning methods; (3) barriers to teaching, learning, and providing virtual care; and (4) facilitators of teaching, learning, and providing virtual care.

Conclusions: This framework was developed by and for students and educators to aid in planning, promoting, and enhancing virtual caring skills development. It can be used to better equip students to provide virtual care, thereby positively impacting client care and outcomes. This framework can support educators, students, decision makers, and practice partners to build learning experiences aimed at preparing students to provide virtual care effectively.

Background: Gamification has emerged as an innovative pedagogical strategy in the educational field, transferring game tools to the teaching-learning process to improve students' motivation and engagement.

Objective: This study aims to describe nursing students' perceptions of mental disorders using interactive cards as a gamification tool.

Methods: This research was carried out at the Nursing School of a University in Madrid, Spain, with the participation of 50 first-year students enrolled in the nursing degree's general and developmental psychology course. Data were collected through focus groups and reflective narratives with semistructured interview questions between March and April 2024. After data collection, transcripts were generated and subjected to thematic analysis following the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist.

Results: A total of three themes emerged from the analysis: (1) perception and stigma of mental disorders, (2) emotional connection and personal reflection in learning about mental disorders, and (3) gamification tools and their impact on learning.

Conclusions: Gamification, especially through interactive cards, is valuable for teaching psychology and mental disorders in nursing education. It enables students to gain a deeper clinical understanding of mental illnesses and explore their emotional and social dimensions. This methodology fosters emotional reflection, reduces stigma, and encourages active engagement, contributing to developing more empathetic, reflective, and better-prepared nursing professionals. Its integration into educational programs enhances academic and humanistic competencies essential for mental health care.

Background: Midwifery students often experience anxiety due to several factors, such as the clinical experiences faced. Simulation-based learning in nursing and midwifery studies using extended reality (XR) tools offers the opportunity to manage better educational processes while reducing this anxiety.

Objective: This study aims to evaluate the current knowledge and understanding of how the use of XR gesture-simulation-based tools allows a better understanding of the anxiety levels of midwives and nurses in educational settings.

Methods: We conducted a systematic review, a scientific literature search following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Using PubMed, IEEE, Scopus, and Web of Science, up to March 2024, 1005 articles were found to identify studies that reported the effectiveness of these technologies for gesture simulation in education and training on nursing and midwifery student anxiety. The inclusion-exclusion criteria were based on the PICO (population, intervention, control, and outcomes) framework. The population included nurses, midwives, and nursing and midwifery students of any kind using any virtual or augmented or mixed reality simulation training tool to perform a procedure aimed at reducing anxiety. In addition, the Cochrane risk of bias tool was used to evaluate the quality of the systematic review and the bias in the included studies. A narrative synthesis was conducted due to the heterogeneity of study designs and outcome measures. Key findings were summarized in a structured table and grouped according to the learning objective, simulating and performing procedures in an educational setting.

Results: Overall, 7 articles, involving a total of 428 participants, were included in this review. The findings indicate that XR can effectively reduce anxiety in midwifery and nursing education. However, the limited number of studies highlights a research gap in the field, particularly in the area of mixed reality, which warrants further exploration.

Conclusions: This systematic review highlights the potential of XR-based gesture-simulation tools in reducing anxiety among midwifery and nursing students. The included studies suggest that XR-enhanced training provides a more immersive and controlled learning environment, helping students manage stress and improve procedural confidence. However, the limited number of studies, methodological variations, and the underrepresentation of mixed reality applications indicate the need for further research. Future studies should focus on standardized anxiety measurement tools, larger sample sizes, and long-term impact assessments to strengthen the evidence base. Expanding research in this field could enhance the integration of XR technologies into midwifery and nursing education, ultimately improving both learning experiences and

Background: Diabetes has become a significant global health issue, particularly imposing a deep economic burden on low-income countries. Innovative and integrated digital solutions can reduce the impact of diabetes and enhance the quality of care. However, digital solutions have not been utilized before in Myanmar.

Objective: This study aimed to demonstrate the novel integrated effect of diabetes knowledge and registry tools on the performance of front-line health workers in primary health care settings.

Methods: A quasi-experimental study with an intervention and a control group was conducted in two townships from October 2022 to April 2023. For the first time, researchers trained the intervention group to use digital tools for diabetes control and performed monthly follow-ups. The study employed multiple linear regression models to explore the novel impact of digital tools on knowledge and performance scores, their correlations, and their association with covariates. Additionally, it assessed the cost-effectiveness of the intervention by using self-administered questionnaires as measurement tools formulated based on the National Diabetes Guidelines.

Results: A total of 96 participants were enrolled in the study, divided evenly into the two groups. The intervention group exhibited a significant increase in the mean knowledge scores from 85.81 to 99.25 (P<.001) and performance scores from 71.22 to 107.16 (P<.001). The intervention accounted for 43.2% of the variance in knowledge scores and 62.5% in performance scores (P<.001). A positive correlation was found between knowledge and performance scores (r=0.45, P<.001). The intervention was also cost-effective, with a cost-effectiveness analysis value of 0.711 and an incremental cost-effectiveness ratio of 10127.04 Kyats (US$ 4.83).

Conclusions: As the new integrated intervention yields significant economic gains and positive effects, researchers suggest policy makers replicate this intervention as a nationwide program and recommend scaling up the use of digital tools to improve knowledge and performance for diabetes control in frontline health workers.