Aim The aim of this study was to systematically review and evaluate the types and effectiveness of digital health interventions used for diabetes management in the Eastern Mediterranean Region (EMRO). Methods This systematic review, conducted according to PRISMA guidelines, searched PubMed, Web of Science, and Scopus up to May 2025 to identify studies on digital interventions for diabetes management in EMRO countries. Methodological quality of the included studies was evaluated using the EPHPP tool, and findings were categorized by intervention type, outcome measures, and intervention effectiveness. Results A total of 46 studies were included, mainly from Iran and Saudi Arabia. Phone calls and SMS were the most common digital tools. Digital interventions significantly improved HbA1c, fasting blood sugar, and several behavioral outcomes such as physical activity, medication adherence, and self-efficacy, while effects on psychological outcomes were mixed. Conclusion Digital health interventions, especially phone calls and SMS, effectively improve glycemic control and self-care behaviors, though their impact on psychological outcomes remains inconsistent.

Introduction Breast cancer is one of the leading causes of mortality among women worldwide. Telemedicine presents a promising pathway to improve cancer care delivery; however, structured approaches to systematically eliciting and integrating stakeholder requirements remain scarce. This study aimed to conduct a comprehensive needs assessment using requirements engineering principles to inform the design of a telemedicine-based follow-up system for breast cancer patients.Methods An exploratory sequential mixed-methods design was employed, encompassing five stages: requirements elicitation, data collection, data analysis, requirements validation, and use-case development. Data were collected from 41 stakeholders-including healthcare professionals, administrative staff, patients, and caregivers-using semi-structured interviews and focus group discussions. Quantitative data were analyzed descriptively, while qualitative data underwent thematic analysis.Results The analysis identified three key domains of requirements-organizational, system, and stakeholder. Organizational requirements underscored the importance of leadership support, sustainable funding, and comprehensive training. System requirements emphasized security, scalability, interoperability, and user-centered design. Stakeholder needs highlighted privacy protection, accessibility, and effective communication channels.Conclusion Applying a structured, stakeholder-driven requirements engineering approach enabled the identification of organizational, technical, and user needs essential for designing a telemedicine follow-up system for breast cancer. The developed framework provides a replicable model for implementing secure, scalable, and user-centered telemedicine solutions not only in oncology but also across other healthcare domains.

Background Antimicrobial resistance (AMR) is a growing global threat. Antimicrobial stewardship programs (ASPs) represent a key strategy to combat AMR and to minimize the adverse effects associated with antibiotic use. Implementing ASPs in hospital settings faces significant challenges and barriers, particularly in low- and middle-income countries (LMICs). This study aims to identify the barriers to the implementation of ASPs in Iranian hospitals. Methods This qualitative study was conducted in 2023–2024, involving 41 stakeholders in antibiotic prescription within five public hospitals in Iran. The participants included physicians, administrators, pharmacologists, pharmacists, the secretary of the stewardship committee, microbiologists, laboratory managers, ICU nurses, nurse managers, quality improvement managers, infection control officers, and information technology managers. Participants were recruited using a convenience sampling method. Data were collected through semi-structured interviews and analyzed using conventional content analysis techniques. Results The barriers to implementing ASPs were categorized into three main categories, nine subcategories as follows: (1) Deficiencies in intelligent surveillance and monitoring of antibiotics prescribing (including inadequate health information technology for ongoing collection, collation and analysis of antibiotic prescribing pattern, and poor audit, and feedback mechanisms in HIS); (2) Deficiencies in health system governance, policies, and regulatory frameworks (including weak policy framework and clinical guidelines, limited policy learning and contextual adaptation and legal and regulatory gaps affecting clinical practice); and (3) Deficiencies in hospital-wide management and support structure (including poor organizational governance and structural capacity, ineffective interprofessional collaboration, weak leadership commitment and low stakeholder engagement, and inadequate professional competencies and limited technical skills). Conclusion The study underscores the multifaceted and heterogeneous nature of barriers to the implementation of ASPs in a LMIC. Enhancing information technology infrastructure, optimizing antibiotic prescribing practices, engaging physicians, strengthening financial and human resource capacity, and fostering supportive management attitudes were identified as potential effective strategies for facilitating successful ASP implementation in hospital settings in a LMIC.

Medication errors from illegible or incomplete handwritten prescriptions can compromise patient safety and increase costs. While E-prescribing aims to reduce errors through improved prescription quality and legibility, these systems can potentially introduce different types of medication errors due to various technical, environmental, and human factors. This qualitative study analyzed the factors contributing to E-prescribing errors at Iranian Social Security Organization outpatient centers. Qualitative content analysis was performed on data from interviews with 10 physicians, pharmacists and pharmacy technicians. The participants had at least 6 months of experience using the E-prescribing. The interview data were coded until saturation and analyzed via the methods of Graneheim and Lundman. This qualitative study identified four main categories of error sources: system, human, organizational, and medication-related factors. In the system domain, technical challenges such as problematic autocomplete features for drug names emerged as significant contributors to selection errors. Human factors, particularly prescriber fatigue and reduced physician-patient interaction time, were found to compromise prescribing accuracy. At the organizational level, insufficient training programs and inadequate staffing levels hindered effective system utilization. Medication factors, including look-alike drug names and complex dosing regimens, further increased error risks. The findings revealed that E-prescribing errors stem from multiple interacting factors, affecting both clinician and non-clinician prescribers similarly. While system design improvements and enhanced user training are crucial, addressing the broader sociotechnical context is essential for error reduction. A balanced approach incorporating standardized protocols, integrated decision support systems, and continuous professional development is recommended to enhance system usability and patient safety.

Background: Social media has become a significant platform for sharing medical knowledge and promoting public health awareness. Cardiovascular diseases (CVDs) are among the leading causes of mortality worldwide, accounting for nearly one-third of global deaths. Analyzing the content of health organizations’ social media platforms, such as Instagram pages related to cardiovascular diseases, offers valuable insights into their role in public health promotion and nursing practiceObjectives: This study aimed to analyze the content of leading health organizations' Instagram pages focused on cardiovascular diseases.Methods: A content analysis was conducted on the Instagram pages of two leading health organizations, the American Heart Association and the British Heart Foundation. All posts related to cardiovascular diseases from January to June 2022 were systematically analyzed. Data collection and analysis were performed concurrently, following the Graneheim and Lundman method for qualitative content analysis. To ensure the trustworthiness of the data, Guba and Lincoln’s (1994) four criteria were applied.Results: A total of 278 posts from the two selected pages were meticulously analyzed, leading to the identification of three primary categories: “Cultural Influence on Cardiovascular Health,” “Guiding the Health Journey,” and “Empowerment Amidst Cardiovascular Disease.” These categories were further subdivided into six subcategories: increasing social sensitivity, enhancing social responsibility, promoting lifestyle modifications, improving psychological skills, managing diseases, and sharing peer experiences.Conclusions: In today's digital landscape, awareness of credible health information on social media is essential for nurses to provide optimal care, remain informed, and engage effectively with patients and communities. Given the rising utilization of these platforms, regular content analyses are recommended due to their substantial influence on public health.

BackgroundPatient-centered, measurable, and transparent care is essential for improving healthcare outcomes, particularly for patients undergoing percutaneous coronary intervention (PCI) procedures. Electronic follow-up questionnaires offer the potential for efficient and accurate data collection, enhancing the monitoring of patient experiences and outcomes. This study aimed to design and evaluate an electronic follow-up questionnaire tailored for post-PCI patients, focusing on real-time symptom monitoring and data collection.MethodsThis developmental study was conducted in 2020 in three phases. In the first phase, a follow-up questionnaire was developed through a needs assessment and expert consultations. Each item's content validity ratio (CVR) and content validity index (CVI) were evaluated to ensure content validity. The finalized questionnaire elements were then reviewed and refined by a panel of ten cardiologists using the Delphi technique. In the second phase, an electronic platform was designed to host the follow-up questionnaire. The tool's effectiveness for post-PCI follow-up was evaluated in the third phase.ResultsCardiologists confirmed all items in the Delphi technique's first round, validating the follow-up questionnaire's content. A total of 41 patients undergoing PCI were enrolled in the study. The most frequently reported symptoms included issues at the catheter insertion site, chest discomfort, digestive complications, and shortness of breath. Of these patients, 21 (51.2%) utilized the electronic follow-up tool. The primary reasons for non-participation were busy schedules, forgetfulness, and perceived recovery. Among the participants, 16 (76.2%) expressed high or very high satisfaction with the tool.ConclusionThe findings suggest that this electronic follow-up questionnaire has the potential to effectively collect clinical data, support academic research, and improve the quality of post-PCI care. However, addressing barriers to patient participation and involving patients in the tool's iterative development will be critical for enhancing its adoption and impact.

This study aimed to develop a minimum dataset and an electronic registry system for hemodialysis patients to evaluate hemodialysis patients’ treatment procedures and outcomes, conduct related research, and design therapeutic interventions. This developmental research was performed in multiple phases, including content determination using the Delphi technique; database designing using MySQL; building a user interface using PHP; usability evaluation using the think-aloud method by 10 evaluators through a scenario consisting of 7 tasks; and finally, the system was piloted by entering the 160 patients’ paper records into the system. Following the CVR and CVI content validity assessment, 108 of the 118 extracted data elements (DEs) were validated. Then, using the Delphi technique, nephrologists chose 57 DEs and divided them into 4 information categories, including the patient’s clinical history, hemodialysis episodes, laboratory findings, and the outcomes of hemodialysis. The three tabs that made up the user interface were the homepage, information recording, reports, and definitions. The problems with appearance and performance were discovered using the think-aloud method, and they were then resolved. Finally, users had the opportunity to identify issues, improve the system’s capabilities, and express their satisfaction throughout the system’s three-month test period. The E-hemodialysis registry was created based on knowledge gained from industrialized nations, opinions and suggestions from medical specialists, and the facilities that were accessible. Information from this system can be utilized as a starting point for evaluating the hemodialysis patients’ status, identifying problems, and making sensible decisions for the best possible planning and management of end-stage renal disease.

Introduction: A growing area is the use of ChatGPT in simulation-based learning, a widely recognized methodology in medical education. This study aimed to evaluate ChatGPT’s ability to generate realistic simulation scenarios to assist faculty as a significant challenge in medical education. Method: This study employs a qualitative research design and thematic analysis to interpret expert opinions. The study was conducted in two phases. Scenario generation via ChatGPT and expert review for validation. We used ChatGPT (GPT-4) to create clinical scenarios on cardiovascular topics, including cardiogenic shock, postoperative cardiac tamponade after heart surgery, and heart failure. A panel of five experts, four nurses with expertise in emergency medicine and critical care and an anesthesia specialist, evaluated the scenarios. The experts' feedback, strengths and weaknesses, and proposed revisions from the expert discussions were analyzed via thematic analysis. Key themes and proposed revisions were identified, recorded, and compiled by the research team. Results: The clinical scenarios were produced by ChatGPT in less than 5 seconds per case. The thematic analysis identified six recurring themes in the experts' discussions: clinical accuracy, the clarity of learning objectives, the logical flow of patient cases, realism and feasibility, alignment with nursing competencies, and level of difficulty. All the experts agreed that the scenarios were realistic and followed clinical guidelines. However, they also identified several errors and areas that needed improvement. The experts identified and documented specific errors, incorrect recommendations, missing information, and inconsistencies with standard nursing practices. Conclusion: It seems that, ChatGPT can be a valuable tool for developing clinical scenarios, but expert review and refinement are necessary to ensure the accuracy and alignment of the generated scenarios with clinical and educational standards.

BACKGROUND:Online appointment scheduling systems have been designed and implemented to address barriers and problems related to in-person appointment scheduling; however, these systems also face challenges and issues that require continuous evaluation and resolution. This research aimed to investigate the experiences, perceptions and satisfaction of stakeholders with an electronic appointment system and identify its problems. METHODS:This was a qualitative study conducted at a specialty Clinic in Iran during 2022-2023. A systematic purposive sampling method was used to select the participants. The participants included 10 administrative and executive users working at the Specialty Clinic, 8 physicians working at the clinic and 18 patients and visitors to the clinic. Data was collected through semi-structured face-to-face interviews. The interviews were analyzed using qualitative content analysis. RESULTS:The findings derived from the semi-structured interview data revealed that the problems with the appointment system fell into two main themes: "Problems Related to Planning and Management of the Electronic Appointment System" and "Non-managerial Problems of the Electronic Appointment System". The problems related to planning and management were divided into three categories: national-level system management, university-level system management and clinic-level system management. The non-managerial problems were classified into two groups: functional problems and non-functional problems. CONCLUSIONS:The results of this study showed that the electronic appointment system, despite facilitating appointment processes, can be influenced by various factors and lead to stakeholder dissatisfaction. Planning, management and policymaking have a significant impact on the appointment process of healthcare centers and attention to the problems arising from it is of particular importance. Moreover, if the functional and non-functional requirements of appointment systems are unclear, the system will face many challenges.

Information technology (IT) solutions can facilitate evidence-based decision-making for antibiotic use by delivering timely information directly to clinicians at the point of care. This study aimed to evaluate the effects of IT interventions in optimizing antibiotic prescribing for urinary tract infections (UTIs). A comprehensive search was performed in Medline (through PubMed), Web of Science, and Scopus databases from inception to June 2024. The study included randomized controlled trials (RCTs) and cluster randomized controlled trials (CRCTs) that investigated the effects of IT interventions on optimizing antibiotic prescribing for UTI patients. Participants were patients with UTI. IT interventions were used for improving antibiotic prescribing. Two researchers independently extracted data from studies on study characteristics, intervention details, and intended outcomes. Ten eligible studies (5 RCTs and 5 CRCTs) were included. Clinical decision support systems (CDSS) were the most common intervention type (50

Background Among the numerous factors contributing to health care providers’ engagement with mobile apps, including user characteristics (eg, dexterity, anatomy, and attitude) and mobile features (eg, screen and button size), usability and quality of apps have been introduced as the most influential factors. Objective This study aims to investigate the usability and quality of the Head Computed Tomography Scan Appropriateness Criteria (HAC) mobile app for physicians’ computed tomography scan ordering. Methods Our study design was primarily based on methodological triangulation by using mixed methods research involving quantitative and qualitative think-aloud usability testing, quantitative analysis of the Mobile Apps Rating Scale (MARS) for quality assessment, and debriefing across 3 phases. In total, 16 medical interns participated in quality assessment and testing usability characteristics, including efficiency, effectiveness, learnability, errors, and satisfaction with the HAC app. Results The efficiency and effectiveness of the HAC app were deemed satisfactory, with ratings of 97.8% and 96.9%, respectively. MARS assessment scale indicated the overall favorable quality score of the HAC app (82 out of 100). Scoring 4 MARS subscales, Information (73.37 out of 100) and Engagement (73.48 out of 100) had the lowest scores, while Aesthetics had the highest score (87.86 out of 100). Analysis of the items in each MARS subscale revealed that in the Engagement subscale, the lowest score of the HAC app was “customization” (63.6 out of 100). In the Functionality subscale, the HAC app’s lowest value was “performance” (67.4 out of 100). Qualitative think-aloud usability testing of the HAC app found notable usability issues grouped into 8 main categories: lack of finger-friendly touch targets, poor search capabilities, input problems, inefficient data presentation and information control, unclear control and confirmation, lack of predictive capabilities, poor assistance and support, and unclear navigation logic. Conclusions Evaluating the quality and usability of mobile apps using a mixed methods approach provides valuable information about their functionality and disadvantages. It is highly recommended to embrace a more holistic and mixed methods strategy when evaluating mobile apps, because results from a single method imperfectly reflect trustworthy and reliable information regarding the usability and quality of apps.

Introduction: As a key custodian of public health, the Vice-Chancellor for Treatment Affairs in medical sciences universities plays a pivotal role in delivering healthcare services to the citizens through electronic service desk. In this study, we conducted an evaluation and ranking of the e-service desks managed by the Vice-Chancellor of Treatment Affairs at Iranian medical sciences universities.Material and Methods: A cross-sectional study conducted in Iran between 2022 and 2023 assessed e-service desks in medical sciences universities. The study included 51 desks categorized by their electronic service methods. Subsequently, e-services were evaluated and scored based on components, which are provided by the national administrative organization for employment. The evaluation components encompassed a) use of an e-service desk to provide services; b) provision of an information package; c) availability of a flowchart outlining the service; d) clarity of the service recipient; and e) electronic collection of user opinions. The total points and the average of each desk were calculated to rank them.Results: The assessed e-service desks were categorized into three groups based on the method of providing electronic services: service provider, service recipient, and not categorized. After evaluating each e-service desk, the highest and lowest points of e-service desks were 708 and 2. The result indicated that only 31 e-service desks achieved an average score of 50% or above.Conclusion: It could be concluded that electronic government (e-government) has been partially implemented in the field of treatment throughout a developing country. However, the absence of a unified model to serve as a guideline for designing e-service desks has resulted in an undesirable diversity in the services offered and their delivery methods. It is recommended that medical sciences universities adopt and adhere to a unified model when designing e-service desks for the provision of healthcare services electronically.

Abstract Background: Stroke is the second leading cause of death worldwide and a major contributor to disability among survivors. This descriptive app-development study aims to investigate the design and evaluate the usability of a self-care app specifically designed for stroke survivors. Methods: The app was developed using the iterative-incremental model. It is a hybrid web-android-based app that follows a client-server model, incorporating both static and dynamic content. The usability evaluation consisted of two components: an expert-based evaluation conducted with five experts using the Cognitive Walkthrough (CW) methodology, and a user-based evaluation involving 30 users who assessed the app's usability using the System Usability Scale (SUS). Results: The app, known as SSM (Stroke Self-Management), was developed with three distinct sides: admin side, user side, and therapist side. During the evaluation process, a total of 39 usability problems were identified across various aspects, including efficiency, effectiveness, user satisfaction, error, learnability, and memorability. Notably, the number of usability problems related to efficiency and user satisfaction outweighed those of other variables. Similarly, usability problems associated with effectiveness and error were significantly more pronounced. On the other hand, the least number of usability problems (n = 1) was identified in terms of learnability. From the users' perspective, the developed app received an average score of 75.25, which can be considered acceptable in terms of usability. Conclusions: Most of the identified usability issues in this server-based app for stroke survivors were related to efficiency and user satisfaction. Therefore, it is recommended that future studies focus on evaluating the app for usability problems before the release phase and address high-intensity issues, such as effectiveness and errors.

Children's burns are a major public health concern due to their long-term physical, psychological, and social impacts, as well as their high financial burden. This study aimed to evaluate the effectiveness of a smartphone-based educational program on outcomes of children with severe burns. This study was designed as a double-blinded, randomized controlled trial (RCT) to test the effectiveness of a developed mobile application. A total of 93 participants were included in the final analysis. The participants were randomly assigned to either the intervention or control groups. Participants in both groups received usual self-care training at discharge, but those in the intervention group used an Android-based application for 2 months. The primary goal of the burn application was scar recovery, and the secondary goals were to increase child caregivers' satisfaction rate and decrease unplanned hospital readmissions. Data collection was conducted using valid and reliable questionnaires. Data were analysed using SPSS software. The study showed that the mobile application significantly affected the frequency of patient visits to the burn clinic and the satisfaction of caregivers of children with burns with the treatment process (p-value <0.05). Also, there was a significant relationship between the duration of application use and wound healing status ((p-value <0.001). These findings suggest that smartphone-based educational programs can be valuable for optimizing care for children with severe burns. Further research is warranted to explore the long-term impact of this intervention and its potential application in different healthcare settings.

Among the numerous factors contributing to health care providers' engagement with mobile apps, including user characteristics (eg, dexterity, anatomy, and attitude) and mobile features (eg, screen and button size), usability and quality of apps have been introduced as the most influential factors.

Background: Mobile phone applications (apps) show promise for enhancing asthma self-management, but their effectiveness varies. This study examined the effect of a smartphone asthma app on asthma control and quality of life. Methods: Using block randomization, 60 patients with asthma were allocated to an intervention group (n = 30) or control group (n = 30) for this single-blind randomized controlled trial. At baseline, both groups completed the Asthma Control Test (ACT) and Asthma Quality of Life Questionnaire-Marks (AQLQ-M). The intervention group used a smartphone-based asthma self-management app plus their regular treatment, while the control group received only usual care. Follow-up ACT and AQLQ-M assessments occurred at 3 and 6 months. SPSS version 26 was used for analysis, including descriptive statistics, non-parametric tests (Wilcoxon and Mann-Whitney U), and analysis of variance with repeated measurements. Results: Both groups showed improved asthma control and quality of life at 3 and 6 months compared to baseline. However, after 6 months the intervention group had significantly greater improvement than controls (p < 0.05). Repeated measures ANOVA revealed divergent changes in ACT and AQLQ-M scores over time, with the intervention group demonstrating greater enhancement of asthma control and quality of life (p < 0.001). Conclusion: This study demonstrated that use of a smartphone-based asthma self-management app improved asthma control and quality of life after 6 months compared to usual care alone. These findings indicate that guideline-based asthma apps can positively impact outcomes.

BACKGROUND:Acute respiratory infections are a common presentation in clinical practice and medical interns must learn proper diagnosis and antibiotic prescribing. Traditional lecture-based teaching may not provide sufficient opportunities for students to apply their knowledge in realistic scenarios, whereas computer case-based simulations offer an alternative approach that allows active learning and decision-making in simulated patient cases. This study investigated the effectiveness of computer case-based reasoning simulation versus traditional lectures for medical interns teaching of diagnosis and antibiotic prescribing for acute respiratory infections. METHODS:This comparative quasi-experimental study was conducted from 2020 to 2022 in the Department of Infectious Diseases at Shahid Beheshti Hospital, affiliated to Kashan University of Medical Sciences. The samples were selected using a convenience method and assigned to the intervention and control groups using a permuted block randomization approach. Over a period of ten months (Each month, an average of eight medical interns), a total of 40 medical interns received traditional lecture-based teaching, while another 40 medical interns were taught using a Computer Case-based Reasoning simulation. The medical interns' knowledge in both groups was assessed using pre- and post-tests. The collected data from the pre- and post-tests were then analyzed statistically using paired t-tests, independent t-tests, and ANCOVA. RESULTS:The posttest scores of the medical interns in both groups were significantly higher than the pretest scores (P < 0.001). No statistically significant differences were observed between the two teaching methods regarding mean knowledge gains in diagnoses and antibiotic prescribing practices. (P > 0.21). The results of the ANCOVA, after controlling for pre-test scores, showed no statistically significant difference between the two teaching methods in their effect on medical interns' diagnostic and antibiotic prescribing performance (P > 0.33). CONCLUSION:The study found that both computer case-based reasoning simulation and traditional lectures were effective in improving medical interns' knowledge of diagnosis and antibiotic prescribing practices for acute respiratory infections. However, no statistically significant differences were observed between the two teaching methods. Thus, computer- based simulation could replace face-to-face teaching when this method is impractical or computerized methods are more cost-effective.

The pharmacy surveillance information system (PSIS) is intended to manage the dispensing practice of under-controlled drugs and substances. We designed and developed a PSIS for the first time in a developing country. This study aimed to evaluate the usability of this system using a heuristic evaluation method before the pilot implementation in outpatient pharmacies. The study was conducted in 2022 during the development of a pharmacy surveillance information system. Five evaluators examined the system using Nielson’s heuristic evaluation method. The detected usability problems were categorized into 10 Nielson’s usability principles, and their severity was calculated. In total, 91 unique usability problems were identified. The most detected usability problems were minor (60

Objectives: Patients with psychiatric disorders are particularly vulnerable to drug-drug interactions (DDIs), which can lead to significant fluctuations in blood concentrations of medications. This study aimed to assess the prevalence of potential DDIs (pDDIs) in prescriptions made by physicians using a straightforward software tool. Methods: This cross-sectional study was conducted in two phases. The first phase focused on creating a comprehensive database of drug-drug interactions related to psychiatric medications. The second phase involved identifying potential DDIs using SQL Server and Python (version 3.8). Results: A total of 3,107 patients prescriptions were analyzed, comprising 1,752 men (56.4%) and 1,355 women (43.6%). The average age of participants was 38.95 years (SD = 15.244), with an average length of hospital stay of 12.01 days (SD = 8,756). The majority of patients were diagnosed with mood disorders (n=1,461; 47.0%). In total, 89,801 prescriptions were evaluated, revealing a prevalence of pDDIs at 34.46% (n=30,953). Notably, male patients exhibited a higher risk for developing pDDIs. The most frequently encountered pDDIs were associated with mental retardation (55.93%) and mental and behavioral disorders (49.03%). The combinations of Clonazepam with Risperidone (11.93%), Lorazepam with Risperidone (6.87%), and Haloperidol with Lorazepam (6.58%) were identified as the most common pDDIs. In terms of risk classification, the majority fell into class C (n=24,914; 80.49%), followed by class I) (n=6,033; 19.49%) and class E (n = 6; 0.02%). Conclusion: The findings of this study highlight the urgent need for greater awareness of potential drug-drug interactions among healthcare providers treating psychiatric patients. Implementing computerized prescription screening tools could significantly aid in identifying pDDIs and mitigating the risk of adverse events.

Background The use of mobile tools in nursing care is indispensable. Given the importance of nurses’ acceptance of these tools in delivering effective care, this issue requires greater attention. Objective This study aims to design the Mobile Health Tool Acceptance Scale for Nurses based on the Expectation-Confirmation Theory and to evaluate it psychometrically. Methods Using a Waltz-based approach grounded in existing tools and the constructs of the Expectation-Confirmation Theory, the initial version of the scale was designed and evaluated for face and content validity. Construct validity was examined through exploratory factor analysis, concurrent validity, and known-group comparison. Reliability was assessed using measures of internal consistency and stability. Results The initial version of the scale consisted of 33 items. During the qualitative and quantitative content validity stage, 1 item was added and 1 item was removed. Exploratory factor analysis, retaining 33 items, identified 5 factors that explained 70.53% of the variance. A significant positive correlation was found between the scores of the designed tool and nurses’ attitudes toward using mobile-based apps in nursing care (r=0.655, P<.001). The intraclass correlation coefficient, Cronbach α, and ω coefficient were 0.938, 0.953, and 0.907, respectively. Conclusions The 33-item scale developed is a valid and reliable instrument for measuring nurses’ acceptance of mobile health tools.