Investigating University Instructors’ Experiences And Uses Of Mobile Technology In Teaching And Learning In Saudi Arabia

The use of mobile technology in teaching and learning has become a worldwide phenomenon. Many university instructors in Saudi Arabia have also started using their own mobile technology in their teaching and for communication with students. But there is limited research on Saudi Arabian university faculty’s experiences of using mobile technology in their teaching practices. This mixed-method study adapted the R2D2 (Reading, Reflecting, Displaying, and Doing) model (Bonk & Zhang, 2006, 2008) to investigate faculty’s uses of mobile technology in Saudi Arabian universities, including both instructors’ own teaching and learners’ activities. An online survey, with both Likert-scale items and open-ended questions, was conducted to collect data on university instructors’ (a) general experiences in integrating mobile technology in their teaching practices as well as for learner activities, (b) their attitudes toward mobile learning, (c) the specific learning activities in different categories as per the R2D2 model, in and out of class and for communication with students. A total of 372 instructors participated the survey, 241 of them completed the entire survey. Participants represented the 25 public universities in Saudi Arabia, with a highly diverse profile in terms of age, gender, academic major, geographic location, and years of teaching experiences. In-depth interviews were conducted with six selected participants, representing different age groups, academic majors and teaching experiences to further investigate instructors’ experiences and contributing factors to their uses of mobile technology for teaching and learning in Saudi Arabian universities. The results of this mixed-method research study (Qualitative and quantitative data were collected and used) concluded that the majority of instructors showed their eagerness and willingness to use mobile technology in their teaching practices. Many instructors were already using them in their teaching and for communication with their students. A number of universities already had the appropriate tools and applications that helped students and instructors to use their mobile technology for content delivery, assignment submission, communication, and more. Some university instructors expressed specific concerns regarding the use of mobile technology by their students, together with the needs for training and professional development to better understand the possibilities that mobile technology can bring to the class and to the university environment. The research has practical implications for university administration and policy-makers for better integration of mobile technology and better applications of mobile learning into the different courses and disciplines. The R2D2 four categories (Reading, reflecting, displaying, and doing) cover many learning activities that may be conducted online and through the use of mobile technologies. Although this model focuses on all categories evenly, this research found that university instructors focused on the learning activities from the reading and displaying categories more than the learning activities from the reflecting or doing categories. Instructors nowadays are considered more as facilitators for their learners’ acquisition of knowledge rather than giving and feeding them with the information. And this R2D2 model is a great framework for university instructors to consider, compare, choose and apply different learning activities via mobile devices, when they facilitate and moderate the new ways of teaching. Similarly, this model may be help students where they can take the steps on their own to follow and complete the wide range of mobile learning activities. The adaption of the R2D2 model and its four categories of varied learning activities, together with the key instructional considerations (Bonk & Zhang, 2008) opens new avenues for university instructors to integrate mobile technologies in their courses, for teaching and for students learning activities. The resources and technologies available to instructors differ from one university to another, and from one country to another, so instructors should select the most suitable learning activities from the four R2D2 categories. As Cartner and Hallas (2009) have found that “the (R2D2) model has been easy to use as the cyclical learning process is one that occurs naturally in everyday life” (p. 114). This study sheds light on future research on mobile learning, as well as mobile learning practices for university instructors, higher education administrators and national policy makers

The INTOXICATE study: methodology and preliminary results of a prospective observational study

Background There is currently no practice-based, multicenter database of poisoned patients admitted to intensive care units (ICUs). The INTOXICATE study, endorsed by the ESICM and EAPCCT, aimed to determine the rate of eventful admissions among acutely intoxicated adult ICU patients. Methods Ethical approval was obtained for this multicenter, prospective observational study, and data-sharing agreements were signed with each participating center. An electronic case report form was used to collect data on patient demographics, exposure, clinical characteristics, investigations, treatment, and in-hospital mortality data. The primary outcome, ‘eventful admission’, was a composite outcome defined as the rate of patients who received any of the following treatments in the first 24 h after the ICU admission: oxygen supplementation with a FiO2 > 40%, mechanical ventilation, vasopressors, renal replacement therapy (RRT), cardiopulmonary resuscitation, antidotes, active cooling, fluid resuscitation (> 1.5 L of intravenous fluid of any kind), sedation, or who died in the hospital. Results Seventy-eight ICUs, mainly from Europe, but also from Australia and the Eastern Mediterranean, participated. A total of 2,273 patients were enrolled between November 2020 and June 2023. The median age of the patients was 41 years, 72% were exposed to intoxicating drugs. The observed rate of patients with an eventful ICU admission was 68% (n = 1546/2273 patients). The hospital mortality was 4.5% (n = 103/2273). Conclusions The vast majority of patients survive, and approximately one third of patients do not receive any ICU-specific interventions after admission in an intensive care unit for acute intoxication. High-quality detailed clinical data have been collected from a large cohort of acutely intoxicated ICU patients, providing information on the pattern of severe acute poisoning requiring intensive care admission and the outcomes of these patients. Trial registration: OSF registration ID: osf.io/7e5uy

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Mapping artificial intelligence adoption in hepatology practice and research: challenges and opportunities in MENA region

BackgroundArtificial intelligence (AI) is increasingly relevant to hepatology, yet real-world adoption in the Middle East and North Africa (MENA) is uncertain. We assessed awareness, use, perceived value, barriers, and policy priorities among hepatology clinicians in the region.MethodsA cross-sectional online survey targeted hepatologists and gastroenterologists across 17 MENA countries. The survey assessed clinical and research applications of AI, perceived benefits, clinical and research use, barriers, ethical considerations, and institutional readiness. Descriptive statistics and thematic analysis were performed.ResultsOf 285 invited professionals, 236 completed the survey (response rate: 82.8%). While 73.2% recognized the transformative potential of AI, only 14.4% used AI tools daily, primarily for imaging analysis and disease prediction. AI tools were used in research by 39.8% of respondents, mainly for data analysis, manuscript writing assistance, and predictive modeling. Major barriers included inadequate training (60.6%), limited AI tool access (53%), and insufficient infrastructure (53%). Ethical concerns focused on data privacy, diagnostic accuracy, and over-reliance on automation. Despite these challenges, 70.3% expressed strong interest in AI training., and 43.6% anticipating routine clinical integration within 1–3 years.ConclusionMENA hepatologists are optimistic about AI but report limited routine use and substantial readiness gaps. Priorities include scalable training, interoperable infrastructure and standards, clear governance with human-in-the-loop safeguards, and region-specific validation to enable safe, equitable implementation

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis.

Background: Gait dysfunction or impairment is considered one of the most common and devastating physiological consequences of stroke, and achieving optimal gait is a key goal for stroke victims with gait disability along with their clinical teams. Many researchers have explored post stroke gait, including assessment tools and techniques, key gait parameters and significance on functional recovery, as well as data mining, modeling and analyses methods. Research Question: This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings. Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included. Results and Significance: This scoping review aimed to shed light on tools and technologies employed in post stroke gait assessment toward bridging the existing gap between the research and clinical communities. Conventional qualitative gait analysis, typically used in clinics is mainly based on observational gait and is hence subjective and largely impacted by the observer's experience. Quantitative gait analysis, however, provides measured parameters, with good accuracy and repeatability for the diagnosis and comparative assessment throughout rehabilitation. Rapidly emerging smart wearable technology and AI, including Machine Learning, Support Vector Machine, and Neural Network approaches, are increasingly commanding greater attention in gait research. Although their use in clinical settings are not yet well leveraged, these tools promise a paradigm shift in stroke gait quantification, as they provide means for acquiring, storing and analyzing multifactorial complex gait data, while capturing its non-linear dynamic variability and offering the invaluable benefits of predictive analytics

Designing and Developing A Smart Application for Improving the Communication Between the Deaf, Dumb People and Society

Technology and Science have made Human life addictive to luxury but still there exists poor people who are trying to find innovative ways which make the communication process easier. Regarding to the World Health Organization, about 1 million people are dumb and 300 million are deaf in the world. Whereas; the communication is one of the most important issues for deaf and dumb people. This work aims to propose a smart application named "Jusoor" to improve the communication process and bridge the gap between the deaf, dumb People, and society. The proposed application provides the user with a dictionary that contains many vocabularies with videos explaining the way that the word is indicated, the most important sentences used in public places (markets, parks, restaurants, etc.), Emergency calls that enable recognizing the type assistance needed with the feature of locating the person which makes it easier to reach and provide the assistance, and service of communication with sign language experts. The proposed work was analyzed using the Unified Modeling Language (UML), Firebase, XML and Java programming languages.</jats:p

Trends in bariatric surgery and incidentalomas at a single institution in Saudi Arabia: a retrospective study and literature review

ABSTRACT BACKGROUND: Data are lacking on trends in bariatric surgery and the frequency of incidental findings in Saudi Arabia. OBJECTIVE: Report on trends in bariatric surgery as well as our experience in incidental findings along with a literature review (mainly on gastrointestinal stromal tumor). DESIGN: Retrospective chart and literature review. SETTINGS: Academic tertiary care center. PATIENTS AND METHODS: We conducted a retrospective study at King Khalid University Hospital and analyzed the data collected from 2009 to 2019. We collected data on age, body mass index (BMI), H pylori infection, type of bariatric surgery performed, and type and location of incidental findings. MAIN OUTCOME MEASURES: Incidental findings during or after bariatric surgery (in pathology specimen). SAMPLE SIZE: 3052 bariatric surgeries, 46 patients with incidentalomas. RESULTS: The mean and standard deviation for the age of the 46 patients with incidentalomas was 42.1 (13.9) years and the mean (SD) preoperative BMI was 43.4 (6.4) kg/m 2 . Of 3052 bariatric surgeries performed, the most common type was sleeve gastrectomy (93.9%), followed by gastric bypass surgery (4.58%) and gastric banding (1.47%). The total frequency of incidentalomas was 1.5%; 10.8% of patients had gastrointestinal stromal tumors (GIST), with the stomach being the commonest site for incidental findings. Eighty percent of the patients with GIST were positive for H pylori ( P =.01 vs negative patients). CONCLUSION: The number of incidentalomas and other findings were consistent with other reports. All these findings suggest that bariatric surgeons should take special care before, during, and after a laparoscopic operation in obese patients. LIMITATIONS: Since this is a single-center, retrospective study, we did not collect data on important variables such as gender, socioeconomic status of the patient, and family history of obesity, and we did not perform a preoperative esophagogastroduodenoscopy. CONFLICT OF INTEREST: None. </jats:sec