Ergonomics appraisals in operating rooms.

This document presents the ergonomic assessments carried out by Spanish surgeons on the materials used within an operating room. With the objective of disseminating and raising awareness of the importance of ergonomics, this working group has compiled information from a previously conducted survey on musculoskeletal disorders associated with surgical work from the year 2022, obtaining feedback from 131 surgeons from 17 distinct specialties. A noteworthy 80.2 % of surveyed surgeons reported having experienced forced postures during surgery, and 96.9 % believe that their physical discomfort is a result of the posture adopted during operations. Such postures can result in the development of pathologies and may have a direct impact on work performance and even in extreme cases, it can lead to sick leave or early retirement. By providing their insights on electronic devices, surgical furniture, and instrumentation, surgeons can help identify areas for improvement in the practice of their profession.

Nursing Students' Perceptions on Healthcare-Associated Infection Control and Prevention Teaching and Learning Experience in Portugal.

Healthcare-associated infections (HAI) are one of the major concerns worldwide, posing significant challenges to healthcare professionals' education and training. This study intended to measure nursing students' perceptions regarding their learning experiences on HAI prevention and control. In the first phase of the study, a cross-sectional and descriptive study with a convenience sample composed of undergraduate nursing students from Portugal, Spain, Poland, and Finland was conducted to develop the InovSafeCare questionnaire. In the second phase, we applied the InovSafeCare scale in a sample of nursing students from two Portuguese higher education institutions to explore which factors impact nursing students' adherence to HAI prevention and control measures in clinical settings. In phase one, the InovSafeCare questionnaire was applied to 1326 students internationally, with the instrument presenting adequate psychometric qualities with reliability results in 14 dimensions. During phase two, the findings supported that Portuguese nursing students' adherence to HAI prevention and control measures is influenced not only by the curricular offerings and resources available in academic settings, but also by the standards conveyed by nursing tutors during clinical placements. Our findings support the need for a dedicated curricular focus on HAI prevention and control learning, not only through specific classroom modules, innovative resources, and pedagogical approaches, but also through a complementary and coordinated liaison between teachers and tutors in academic and clinical settings.

Nursing Students' Perceptions on Healthcare-Associated Infection Control and Prevention Teaching and Learning Experience: Development and Validation of a Scale in Four European Countries.

Healthcare-associated infections are one of the major concerns worldwide. This study presents the development and the validation process of the InovSafeCare scale and aimed at identifying and measuring the ecosystem variables related to healthcare-associated infection (HCAI) prevention and control practices in European nurse students. Qualitative and quantitative approaches were used to (1) elaborate an item pool related to the educational environment, the healthcare setting environment, and the attitudes, beliefs, and performance of the nursing students regarding HCAI prevention and control and (2) analyze psychometric properties of the scale using factor analysis. The validated InovSafeCare scale was applied to undergraduate nursing students of five European Higher Education Institutions. The partial least square structural equation modeling (PLS-SEM) method with SMART-PLS3 software was used. The study sample consists of 657 nursing students, who responded a self-report inventory. From the analyzed data were identified 14 factors. The InovSafeCare scale reveals good validity and reliability of the dimensions in different European countries.

Development of a Smart Leg Splint by Using New Sensor Technologies and New Therapy Possibilities.

Nowadays, after suffering a fracture in an upper or lower limb, a plaster cast is placed on the affected limb. It is a very old and efficient technique for recovery from an injury that has not had significant changes since its origin. This project aims to develop a new low-cost smart 3D printed splint concept by using new sensing techniques. Two rapidly evolving Advanced Manufacturing (AM) technologies will be used: 3D scanning and 3D printing, thus combining engineering, medicine and materials evolution. The splint will include new small and lightweight sensors to detect any problem during the treatment process. Previous studies have already incorporated this kind of sensor for medical purposes. However, in this study it is implemented with a new concept: the possibility of applying treatments during the immobilization process and obtaining information from the sensors to modify the treatment. Due to this, rehabilitation treatments like infrared, ultrasounds or electroshock may be applied during the treatment, and the sensors (as it is showed in the study) will be able to detect changes during the rehabilitation process. Data of the pressure, temperature, humidity and colour of the skin will be collected in real time and sent to a mobile device so that they can be consulted remotely by a specialist. Moreover, it would be possible to include these data into the Internet of Things movement. This way, all the collected data might be compared and studied in order to find the best treatment for each kind of injury. It will be necessary to use a biocompatible material, submersible and suitable for contact with skin. These materials make it necessary to control the conditions in which the splint is produced, to assure that the properties are maintained. This development, makes it possible to design a new methodology that will help to provide faster and easier treatment.

Development of a Smart Splint to Monitor Different Parameters during the Treatment Process.

For certain musculoskeletal complex rupture injuries, the only treatment available is the use of immobilization splints. This type of treatment usually causes discomfort and certain setbacks in patients. In addition, other complications are usually generated at the vascular, muscular, or articular level. Currently, there is a really possible alternative that would solve these problems and even allows a faster and better recovery. This is possible thanks to the application of engineering on additive manufacturing techniques and the use of biocompatible materials available in the market. This study proposes the use of these materials and techniques, including sensor integration inside the splints. The main parameters considered to be studied are pressure, humidity, and temperature. These aspects are combined and analyzed to determine any kind of unexpected evolution of the treatment. This way, it will be possible to monitor some signals that would be studied to detect problems that are associated to the very initial stage of the treatment. The goal of this study is to generate a smart splint by using biomaterials and engineering techniques based on the advanced manufacturing and sensor system, for clinical purposes. The results show that the prototype of the smart splint allows to get data when it is placed over the arm of a patient. Two temperatures are read during the treatment: in contact with the skin and between skin and splint. The humidity variations due to sweat inside the splint are also read by a humidity sensor. A pressure sensor detects slight changes of pressure inside the splint. In addition, an infrared sensor has been included as a presence detector.

Nextmed: Automatic Imaging Segmentation, 3D Reconstruction, and 3D Model Visualization Platform Using Augmented and Virtual Reality.

The visualization of medical images with advanced techniques, such as augmented reality and virtual reality, represent a breakthrough for medical professionals. In contrast to more traditional visualization tools lacking 3D capabilities, these systems use the three available dimensions. To visualize medical images in 3D, the anatomical areas of interest must be segmented. Currently, manual segmentation, which is the most commonly used technique, and semi-automatic approaches can be time consuming because a doctor is required, making segmentation for each individual case unfeasible. Using new technologies, such as computer vision and artificial intelligence for segmentation algorithms and augmented and virtual reality for visualization techniques implementation, we designed a complete platform to solve this problem and allow medical professionals to work more frequently with anatomical 3D models obtained from medical imaging. As a result, the Nextmed project, due to the different implemented software applications, permits the importation of digital imaging and communication on medicine (dicom) images on a secure cloud platform and the automatic segmentation of certain anatomical structures with new algorithms that improve upon the current research results. A 3D mesh of the segmented structure is then automatically generated that can be printed in 3D or visualized using both augmented and virtual reality, with the designed software systems. The Nextmed project is unique, as it covers the whole process from uploading dicom images to automatic segmentation, 3D reconstruction, 3D visualization, and manipulation using augmented and virtual reality. There are many researches about application of augmented and virtual reality for medical image 3D visualization; however, they are not automated platforms. Although some other anatomical structures can be studied, we focused on one case: a lung study. Analyzing the application of the platform to more than 1000 dicom images and studying the results with medical specialists, we concluded that the installation of this system in hospitals would provide a considerable improvement as a tool for medical image visualization.

Application of PDF Software with 3D Functionalities in Radiological Models of the Skull Base: Characteristics, Experience and Solutions.

A widely known alternative for reading and exchanging digital files is the PDF file, by Adobe. This type of file has become the most used for the electronic exchange of files. It is platform-independent, suitable for the exchange of medical data in electronic academic publication. PDF can support additional resources such image, media, even, three-dimensional surface mesh models. A three-dimensional model of the base of the skull is generated from computed tomography images to provide an overview of the PDF file format, with emphasis on biomedical images. Three-dimensional representation in PDF files offers many advantages, as these images have more information than two-dimensional images, therefore, we consider this tool (3D PDF) a good alternative for the visualization, interaction and distribution of 3D content.

Advances in the Visualization and the Study of the Pyramidal Tract with Magnetic Resonance Tractography.

Over the last several years, specific radiological techniques have been used for the analysis of the central nervous system pathways. They involve a magnetic resonance sequence called diffusion tensor imaging. In order to process the data provided by this sequence it is necessary to use software that can post-process the image and render three-dimensional images of the central nervous system pathways. Thanks to this sequence it has been possible to isolate over the years many nerve pathways that cross the brain tissue, particularly those which occupy a significant space. This sequence could have a large variety of uses, such as helping with the study of brain anatomy, assisting with surgery planning, or establishing a relationship between the nerve fibers and tumoral lesions. However, there has been an increasing number of cases that report a low reliability related to the tractographic representation of this technique. Our goal with this article is to analyse a specific nerve pathway, the piramidal tract, in order to assess the coherence between the images obtained and the anatomy that is already known from the perspective of the radiological image, and to compare this tract between different patients.

Computer Application of Ultrasound and Nuclear Magnetic Resonance Images for the Anatomical Learning of the Pelvis and the Female Pelvic Floor.

Computer applications have been incorporated as valuable components in teaching, especially thanks to the advancement and innovation of new technologies during the last decades. The implementation of these computer developments in medicine and in the field of medical teaching with different utilities has been a revolution. This is manifested with greater intensity in certain medical specialties and in different areas of medical education, for example in the study of human anatomy, especially in parts of the human body of great complexity such as the pelvis and the pelvic floor of women. New technologies are also important in the use, study and interpretation of radiological tests, including ultrasound and nuclear magnetic resonance. This implies a change in the study and learning techniques of students, resident doctors and specialists in gynecology, radiodiagnosis, urology and many other medical specialties, considering new computer developments as a good alternative or complement to existing teaching methods. For this reason, we consider that computer programs like the one we present in this work can be very useful in the future of education and more specifically in the training of specialists in medicine.

Effects of Mobile Learning in Medical Education: A Counterfactual Evaluation.

The aim of this research is to contribute to the general system education providing new insights and resources. This study performs a quasi-experimental study at University of Salamanca with 30 students to compare results between using an anatomic app for learning and the formal traditional method conducted by a teacher. The findings of the investigation suggest that the performance of learners using mobile apps is statistical better than the students using the traditional method. However, mobile devices should be considered as an additional tool to complement the teachers' explanation and it is necessary to overcome different barriers and challenges to adopt these pedagogical methods at University.