Creative solutions are needed to enhance mobility activities in the ICU to combat the sequela of prolonged bed rest. Virtual reality has gained favor for use in outpatient areas, yet the user experience of the ICU patient is relatively unknown. This qualitative study aimed to explore the patient experience of ICU mobility as it relates to the critically ill patient. Human-centered design methodology was used to generate a list of user needs. Analysis revealed the need for a progressive experience that builds on standard rehabilitation practices with dynamic elements that balance stimulation and relaxation that may effectively promote mobility for a challenging at-risk population.

Mobile applications are effective tools for health education in cardiometabolic diseases, enhancing patient's self-care, self-management, self-efficacy, and treatment adherence. This study describes the development, validation, and evaluation of the usability of a mobile application aimed at health education of individuals with cardiometabolic diseases. This is a methodological study developed using the theoretical-methodological framework of Systematic Instructional Design. The validity of the educational technology was assessed using the content validity index, with a threshold of 80% or higher. The application's usability was evaluated through the System Usability Scale. The Viva+ application was developed using Flutter, with Dart programming language and Firebase database. It comprises 49 screens and features functionalities such as registration, login, usage instructions, quizzes, note-taking, and health guidance pages covering topics such as contextualization of cardiometabolic diseases, risk factors, healthy eating, physical activity, weight control, medication management, treatment adherence, smoking and alcohol consumption, sleep improvement, stress management, and professional follow-up. The application was deemed valid by experts, achieving a global validity index of 0.99. Regarding usability, it obtained a total score of 78.07, being considered excellent. The application was shown to be a valid, suitable, comprehensive, and relevant technology for the education and health promotion of individuals with cardiometabolic diseases.

The majority of patients with cancer tend to seek health-related information via the Internet. This descriptive and cross-sectional study aims to determine e-health literacy, cyberchondria levels, and affecting factors in patients with cancer. The population of the study consisted of 113 patients who were older than 18 years, with no sensory loss that could hinder their communication, literate in Turkish language, who were conscious, actively used the Internet, and visited a university hospital's oncology and hematology polyclinic. In the multiple regression analysis examining the E-Health Literacy Scale total score according to sociodemographic and other characteristics, it was found that solitary complementary and alternative medicine explained 40.8% of the variance in the E-Health Literacy Scale score (adjusted R2 = 0.408, P < .001). Additionally, it was determined that medication use without a doctor's recommendation and the duration of daily Internet use together explained 22.3% of the variance in the score on the Cyberchondria Scale (adjusted R2 = 0.223, P < .001). Patients with cancer who develop better health literacy skills will be better equipped to navigate healthcare systems and alleviate their health-related worries.

The aim of this study was to develop an electronic patient follow-up system of data collected from patients with a stoma and to measure user satisfaction. Electronic health records are a source of information for the management and interpretation of information and for the development of institutional policies. Prospective, descriptive, and methodological research was planned in three stages. The first stage consisted of literature research, nursing care plans, the management of complications for healthcare personnel, and information packs for patients. In the second stage, lists were prepared of the information required in the electronic patient follow-up system according to the type of stoma in accordance with international recommendations. In the third stage, the software of the electronic patient follow-up system was implemented, and user satisfaction was evaluated. SQUIRE 2.0 Checklist was used. The Stoma Records System is a 10-step Web-based system. The 100 users who agreed to participate in the research comprised 75% nurses and 25% physicians. The Stoma Records System was evaluated by the users with respect to facilitating their work, understanding the information provided, ease of use, understanding the system functions, not creating data loss, ease of navigation within the system, and as a whole. The points given for the responses to the evaluation items had a mean minimum of 4.36 ± 0.785 and a mean maximum of 4.64 ± 0.542. The user evaluation results were positive. Stoma Records System is effective in the management of stoma care and improvement of patient care outcomes. The patient follow-up system ensures that the stoma care process is effectively maintained.

The purpose of this study was to evaluate the effectiveness of virtual reality meditation compared with standard care on sleep quality and delirium incidence in patients admitted to the ICU. We conducted a randomized controlled trial with 96 patients in an 11-bed surgical ICU at a South Korean university hospital. The control group received usual sleep care, whereas the intervention group received an additional 20-minute virtual reality-based mindfulness and relaxation meditation before bedtime. Using the Verran and Snyder-Halpern Sleep Scale, we found significantly improved subjective sleep quality in the intervention group compared with controls during both the first (47.82 vs 39.75, P = .015) and second nights (50.26 vs 43.65, P = .025) of ICU admission. However, objective sleep measurements using Fitbit devices showed no significant differences in total sleep time between groups for either the first (384.59 vs 358.19 minutes, P = .450) or second night (319.94 vs 310.77 minutes, P = .807). Delirium incidence was similar between groups (12.2% vs 12.8%, P = .938). These findings suggest the need for larger-scale studies with robust experimental designs to definitively establish the impact of virtual reality meditation on sleep quality and delirium in ICU patients.

Obesity is health epidemic associated with health conditions specific to women's health. Healthcare providers must identify and develop a follow-up plan for patients with a body mass index of greater than 30 kg/m2 to meet the Merit-Based Incentive Payment System Quality Program rate for body mass index screening and follow-up. Barriers to addressing obesity in this population by healthcare providers include time available for counseling and knowledge about appropriate diagnosis and treatment options. This is a quality improvement project that implements a clinical template within an existing electronic health record platform that includes a treatment order set and prepopulated counseling prompts to improve the rate of which healthcare providers address obesity within the women's health clinic. After 12 weeks, 27 patients started a weight management plan, and the Merit-Based Incentive Payment System rate increased from 59% to 67%. Implementation of order set templates into electronic health record platforms with counseling guidance provides a framework for providers to develop a plan to address obesity to meet their patient's health goals and reduce health disparities related to obesity in women.

This study proposes an evaluation of the efficacy of machine learning algorithms in classifying chronic pain based on Italian nursing notes, contributing to the integration of artificial intelligence tools in healthcare within an Italian linguistic context. The research aimed to validate the nursing diagnosis of chronic pain and explore the potential of artificial intelligence (AI) in enhancing clinical decision-making in Italian healthcare settings. Three machine learning algorithms-XGBoost, gradient boosting, and BERT-were optimized through a grid search approach to identify the most suitable hyperparameters for each model. Therefore, the performance of the algorithms was evaluated and compared using Cohen's κ coefficient. This statistical measure assesses the level of agreement between the predicted classifications and the actual data labels. Results demonstrated XGBoost's superior performance, whereas BERT showed potential in handling complex Italian language structures despite data volume and domain specificity limitations. The study highlights the importance of algorithm selection in clinical applications and the potential of machine learning in healthcare, specifically addressing the challenges of Italian medical language processing. This work contributes to the growing field of artificial intelligence in nursing, offering insights into the challenges and opportunities of implementing machine learning in Italian clinical practice. Future research could explore integrating multimodal data, combining text analysis with physiological signals and imaging data, to create more comprehensive and accurate chronic pain classification models tailored to the Italian healthcare system.

The demands of contemporary everyday contexts have accelerated the deployment and adoption of emerging technologies, such as augmented reality, to enhance the learning experience. Traditionally, AR learning environments have been designed according to established instructional design principles. Now, it has become essential to update this approach by addressing the current demands of modern teaching and learning methods (eg, face-to-face and online learning) alongside technical issues related to augmented reality (eg, virtual scenarios). Additionally, the inclusion of software engineering methodologies can contribute to increased precision in the design process. In this sense, the current research presents a blended learning design model named UXpedite Learning Design, which integrates both instructional design and software engineering design approaches to facilitate the development of AR environments. The model comprises six phases: (i) needs assessment, (ii) ideation, (iii) prototyping, (iv) development, (v) technical testing, and (vi) user evaluation. A case study was conducted to demonstrate the implementation of the proposed model in developing the Virtual-Beat application, a tool designed to teach the interpretation of human vital sign measurements. Our tests indicate that using the Virtual-Beat application leads to slightly better learning outcomes compared with conventional classroom education, as evidenced by a statistically significant difference in examination scores between the experimental group (M = 7.53) and the control group (M = 7.08), t73 = 2.96, P = .004. Additionally, the User Experience Questionnaire completed by participants who used the application yielded positive results, highlighting a favorable overall experience (M = 1.465) and excellent attractiveness (M = 1.667). However, the assessment also identified a need for improvement in user interaction control. In conclusion, the findings suggest that the UXpedite Learning Design model shows promise for creating high-quality learning environments that align with the evolving needs of higher education.

The human-centered design approach has gained prominence in the development of mobile health solutions. However, its application to support foot self-care for persons with diabetes has not been extensively explored. This study aims to develop a mobile application prototype using a human-centered design approach to support foot self-care for persons with type 2 diabetes. The project used mixed methods, including a scoping review, patient interviews, a Delphi panel, and an acceptability and usability study of an educational booklet. This three-phase approach encompassed defining the context of use, specifying user requirements, and developing design solutions. This article specifically details the third phase of the project: the development of the low-fidelity prototype. Functionalities such as daily reminders for foot care, notifications for medical appointments, communication features with healthcare professionals and peers, and repositories of videos and educational content were integrated into the design. These features were tailored to address user needs, emphasizing knowledge enhancement in self-care practices. The human-centered design approach enabled the creation of a comprehensive prototype with essential functionalities and robust educational content, filling gaps in the digital health market and empowering persons to better manage their foot health.

This study aimed to develop a mobile application self-management program for patients with implantable cardioverter-defibrillators and evaluate its effectiveness. A nonequivalent experimental group pre-post quasi-experimental study was conducted. The experimental group (n = 32) received the mobile application and education for 8 weeks. The control group (n = 32) received a booklet and education. Uncertainty, self-care competence, physical quality of life, mental quality of life, and physiological indicators (ejection fraction, systolic blood pressure, diastolic blood pressure, pulse rate) were assessed. Outcomes were analyzed using the independent t test, Mann-Whitney U test, analysis of covariance, and ranked analysis of covariance. Physical and mental quality of life significantly increased in the experimental group compared with the control group. Physiological indicators were unchanged. The mobile application self-management program may be utilized as a nursing intervention to improve quality of life for patients with implantable cardioverter-defibrillators.

As scenario-based simulation teaching gains traction in nursing education, a thorough bibliometric analysis is essential to uncover the breadth and depth of existing research, highlight key trends, and address gaps in multicenter studies.

Maintaining adherence to a long-term lifestyle in heart failure patients is challenging, highlighting the importance of mobile health educational interventions from hospitalization to discharge. This study assessed the effects of mobile health interventions on heart failure patients during the transition from hospital to home through a systematic review and meta-analysis of randomized controlled trials using PubMed, EMBASE, and Scopus. Studies with mobile health interventions starting postdischarge were excluded. The Cochrane Risk of Bias Tool 2 and Grading of Recommendations, Assessment, Development, and Evaluations strategy were used to assess bias. The results indicated that mobile health interventions were not effective in reducing readmissions compared with conventional management after 30 days (relative risk, 1.04; 95% confidence interval, 0.87-1.24). No improvements were found in quality of life or self-care. However, a reduction in mortality was observed (relative risk, 0.64; 95% confidence interval, 0.42-0.9). The study showed that mobile health interventions can reduce mortality in heart failure patients and may reduce late readmissions and improve quality of life over a period longer than 6 months. Longer follow-up studies are necessary.

This study analyzed the gaps in clinical guidelines for the Institute for Clinical Systems Improvement by using the Omaha System. Clinicians use various Non-Opioid approaches for pain management, leading to diverse coding requirements when inputting data into EHRs. Consequently, the lack of standardized coding for Non-Opioid pain management data leads to inconsistencies, hindering effective information transfer and reuse between care settings, impacting continuity of care. By encoding guidelines within the Omaha System, this study aims to create a standardized framework that enhances data integration and promotes seamless communication across healthcare environments. To address this, pain management guidelines for Non-Opioid approaches were mapped using the Omaha System, with a focus on content feasibility, linguistic validity, and term granularity. The analysis revealed three problems, three categories, and 11 targets in the coding of Non-Opioid approaches for pain management. By integrating guidelines encoded within EHRs, the development of improved guidelines is facilitated, enhancing their efficient utilization and thereby improving nursing records and information delivery systems. In conclusion, this approach addresses the need for standardized coding, advancing both guideline development and continuity of care through improved information systems.

Physiologic surveillance systems are intended to notify nurses of patient deterioration but can be rendered ineffective when alarm burden is high. Nurses reported increased alarm burden, loss of confidence that alarms signaled actionable events, and alarm fatigue. Additionally, standard quality assurance tracking indicated a need to evaluate comprehensively the hospital's crucial patient safety system. A systems approach was used to understand changes in the care environment and regain reliable system performance after practice drift. Interventions included decreasing the continuous surveillance pulse rate alarm threshold to 40 beats per minute, restandardizing the peripheral capillary oxygen saturation alarm threshold to 80%, and resetting expectations for alarm response and utilization of alarm escalation pagers. Bedside alarms per patient day decreased by 66.4% (P < .001) for peripheral capillary oxygen saturation low and by 71.2% (P < .001) for pulse rate low. Initial pager notifications per patient day decreased by 84.5% (P < .001) for peripheral capillary oxygen saturation low and by 93% (P < .001) for pulse rate low. Even systems that are stable for long periods are subject to practice drift. This study underscores the importance of clinical process standardization and continuous measurement of system performance with feedback to sustain performance of the patient safety systems nurses rely on.

Nurse staffing decisions are often made without input from high-quality, reliable patient acuity measures, especially in medical-surgical settings. Staffing decisions not aligned with patient care needs can contribute to inadequate patient-to-nurse ratios and nurse burnout, potentially resulting in preventable patient harm and death. We conducted a proof-of-concept study to explore the feasibility of adapting an evidence-based patient acuity tool for use in the EHR. A retrospective cohort of pediatric medical-surgical inpatients was used to map electronic patient data variables. We developed an algorithm to calculate the score for one domain of the tool and validated it by comparing it with a score based on a manual chart review. Through multiple rounds of testing and refinement of the variables and algorithm, we achieved 100% concordance between scores generated by the algorithm and the manual chart review. Our proof-of-concept study demonstrates the feasibility and challenges of adapting an evidence-based patient acuity score for automation in the EHR. Further collaboration with data scientists is warranted to operationalize the tool in the EHR and achieve an automated acuity score that can improve staffing decisions, support nursing practice, and enhance team collaboration.

Electronic health record support nurses' work in many ways; however, nursing documentation within the system has also been associated with burden and noncompliance with organizational and regulatory requirements. An increasing number of studies have analyzed nursing documentation burden and noncompliance, but no scoping review has been conducted that focuses on electronic health record-based strategies for improving nursing documentation. This scoping review aimed to identify electronic health record-based strategies for improving nursing documentation in hospital settings. The Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for Scoping Reviews guidelines were used, and databases MEDLINE, Web of Science, and CINAHL were searched on April 1, 2024. A total of 652 studies were retrieved, of which 25 were included at the full-text level. Six documentation issues emerged across the studies, with 44% identifying documentation compliance as the main issue. Three electronic health record-based strategies, such as organizational change, end-user reminder system, and financial incentives, regulation, and policy, were identified. Six documentation improvement outcomes with findings were identified, with 52% of the studies' outcome demonstrating improved documentation compliance. This review identified electronic health record-based and supplemental strategies that concentrate on improving nursing documentation. More research is needed to identify how these strategies may affect other measures, such as patient care outcomes, accuracy and quality of nursing documentation, and costs associated with nursing time spent on documentation activities.

This study presents a deep learning-based approach for assessing infant pain through facial expression analysis using Convolutional Neural Networks (CNNs). Given infants' inability to verbally articulate pain, reliable assessment methods are crucial in clinical nursing. To address this need, we developed a CNN model utilizing the COPE (Classification of Pain Expression) database. Our model achieved a test accuracy of 90.24%, with an average precision and recall of 87.58%, and an F1 score of 0.8758. Additionally, the model demonstrated high performance with an area under the curve of 0.9818 on the receiver operating characteristic curve. These results underscore the potential utility of CNNs for providing an objective pain assessment in clinical settings. However, the study acknowledges limitations, including a small sample size, the need for external validation, and ethical considerations. Future research should focus on expanding the dataset, conducting external validation, refining model architectures, and addressing ethical considerations to enhance performance and applicability. These efforts will advance infant pain management, ensure ethical integrity, and improve the overall quality of care.