Can a validated website help improve university students' e-health literacy?

Background: The fight against fake news, mainly spread through Internet, is a major public health issue, even among undergraduate students. This study aims to evaluate the effectiveness of a website promoted by the Italian Federation of the Provincial Orders of the Medical Doctors as a first aid communication kit for health topics. Study design: Pre-post study using a web-based survey, conducted in April-May 2019 on Medical students and October-November 2020 on Communication Sciences students at the University of Florence (Italy). Methods. Undergraduate students of both schools were exposed to the use of the "dottoremaeveroche" website. Primary and secondary outcomes measures: the Italian-electronic Health Literacy Scale self-assessment tool was used to examine subjects' electronic Health literacy, and source quality. All responses were rated on a 5-point Likert scale. Changing in perception of abilities were examined using the Wilcoxon test. Results: The 362 participants felt moderately confident in electronic Health Literacy, with an initial Italian-electronic Health Literacy Scale overall mean score of 3.6±0.7 for medical and 3.2±0.8 for communication students. Medical students had a good idea of how to find helpful sources (3.9±0.8) and communication students felt confident in recognizing their quality (3.5±1.0). In contrast, their confidence in using Web information to make health decisions was low (medical: 2.9±1.1; communication: 2.8±1.1). All items improved significantly after "dottoremaeveroche" use (p<.001), with the overall mean score of Italian-electronic Health Literacy Scale increasing to 4.3±0.6 for medical and 4.1±0.8 for communication students. Conclusions: Low electronic health literacy levels can affect public health efforts, as seen during the COVID-19 pandemic. The effectiveness of "dottoremaeveroche" among students showed the usefulness of online educational interventions that, if further implemented, could help combat the spread of infodemic.

Impact assessment of an educational course on vaccinations in a population of medical students.

BACKGROUND: The inadequate knowledge about vaccinations of healthcare workers, including medical doctors, has certainly contributed to the spread of the vaccine hesitancy. Therefore, it is essential to improve the level of knowledge of future doctors. The aim of the study is to evaluate the impact of a course about vaccinations on the knowledge of medical students. METHODS: Medical students were asked to complete an anonymous questionnaire before and after a seminar on vaccination that they willingly attended. The two questionnaires contained the same 10 questions about vaccines. Only the students who had attended the lecture were allowed to fulfil the post-lecture questionnaires through the learning management system (LMS) called "Moodle". A descriptive statistical analysis of the data collected through the comparative evaluation of the answers before and after the seminar was performed. Mann-Whitney test for two independent samples was used to compare medians score before and after the interventions. RESULTS: A total of 100 medical students filled the pre-lecture questionnaire and 81 of them completed the post-lecture questionnaire. Knowledge of the students on the indication of the MMR (Measles-Mumps-Rubella) vaccine strongly improved after the seminar. Moreover, the number of students who would recommend vaccination for pertussis and influenza during pregnancy increased significantly by 37% and 19% respectively after the seminar and those aware of the need for Herpes Zoster vaccination over the age of 65 increased by 22%. DISCUSSION: For future doctors, a thorough knowledge about vaccinations is increasingly required in order to deal with vaccine hesitancy. Extracurricular seminars about vaccines, provided in the second half of the course of study, can have a highly positive impact.

World Wide Web interface for advanced SPECT reconstruction algorithms implemented on a remote massively parallel computer.

Data from Single Photon Emission Computed Tomography (SPECT) studies are blurred by inevitable physical phenomena occurring during data acquisition. These errors may be compensated by means of reconstruction algorithms which take into account accurate physical models of the data acquisition procedure. Unfortunately, this approach involves high memory requirements as well as a high computational burden which cannot be afforded by the computer systems of SPECT acquisition devices. In this work the possibility of accessing High Performance Computing and Networking (HPCN) resources through a World Wide Web interface for the advanced reconstruction of SPECT data in a clinical environment was investigated. An iterative algorithm with an accurate model of the variable system response was ported on the Multiple Instruction Multiple Data (MIMD) parallel architecture of a Cray T3D massively parallel computer. The system was accessible even from low cost PC-based workstations through standard TCP/IP networking. A speedup factor of 148 was predicted by the benchmarks run on the Cray T3D. A complete brain study of 30 (64 x 64) slices was reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s which corresponds to an actual speed-up factor of 135. The technique was extended to a more accurate 3D modeling of the system response for a true 3D reconstruction of SPECT data; the reconstruction time of the same data set with this more accurate model was 5 min. This work demonstrates the possibility of exploiting remote HPCN resources from hospital sites by means of low cost workstations using standard communication protocols and an user-friendly WWW interface without particular problems for routine use.

[A proposal for the use of tridimensional reconstruction in oncology to better assess tumor stage and response to therapy]. / Proposta di utilizzazione della ricostruzione tridimensionale nell'oncologia per la migliore valutazione dello stadio tumorale e della risposta alla terapia.

Besides radiation therapy, diagnostic imaging has always been considered the main medical application of three-dimensional (3D) reconstruction. On the contrary, our study focused mainly on the use of 3D reconstruction for both spatial characterization and morphometric evaluation of the reconstructed objects. We aimed at assisting physicians to solve clinical and therapeutic problems. In particular, in oncology, 3D reconstruction may allow the objective and accurate quantification of the volume of neoplastic lesions. Therefore, we decided to focus our attention on the spatial characterization and morphometric assessment of the examined neoplastic masses. Volumetric measurements based on 3D reconstruction may be of great value to assess volume changes after irradiation and/or chemotherapy of neoplastic lesions. This might also allow to compare, on the basis of such changes, the role of different treatment protocols on similar neoplastic lesions and, possibly, to lead to a new TNM staging system no longer based on 2D measurements but on volumes. To meet these clinical requirements, we developed a software system for accurate volume measurements. We believed 3D reconstruction to be suited to this purpose and therefore we implemented a software incorporating 3D reconstruction capabilities of abnormal anatomical structures from 2D images, the rotation of the volume of interest for better assessment of spatial relationships, and finally morphometric evaluation, for accurate volume measurements. Instead of calculating the volume of a neoplastic lesion by means of a 3D reconstruction algorithm considering voxels as indivisible (voxel-based approach), we implemented a surface rendering algorithm using a cell-based approach, because it allowed voxels to be represented as small volume units, which could be further divided by means of linear interpolation. Thus, great flexibility was possible in the determination of surfaces, together with a good approximation of the volume of the neoplastic lesions. To assess the reliability of the developed software system, we used a real phantom. Its known actual volume was compared with the one measured by our system and the difference, expressed as a percentage of the actual volume itself, was compared with the one obtained by using reconstruction algorithms with a voxel-based approach (1.4% vs 4.4%). The error produced by the latter is three times greater than the one produced by our algorithm. This is a major result for the physician: better approximation of the actual volume of a neoplastic lesion means better evaluation of the number of neoplastic cells in the lesion. This may be useful for the clinical management of the patient. In the paper, the first clinical applications of our algorithm are reported.