Circuit training during physical education classes to prepare cadets for military academies tests: Analysis of an educational project

Background: The aim of this study was to test the efficacy of an eight-week physical education program based on circuit training to better improve the overall physical and military-specific performance compared to a conventional physical education program in military high school students. Methods: Sixty-four students were enrolled in this study and randomly assigned to an experimental (EG, circuit training) or a control group (CG, traditional physical education program). Immediately before and after the eight-week training period, participants were tested on strength and endurance performance, circuit training tests, and military tests. Moreover, the acquisition of the educational objectives and the pleasantness of the experimental intervention were tested using a qualitative approach. Results: Despite the higher workload in EG than CG during the training period, the effect of the experimental intervention compared to the control was only possibly to likely positive for a few strength and endurance performances and circuit training tests, respectively. A trivial effect was shown in the military tests. On the contrary, the high percentage of motivation (76%), understanding (78%) and collaboration (86%) showed by the students suggests the achievement of acquisition of the educational objectives and a fair pleasantness of the lessons. Conclusions: A lack of clear and marked effect of the experimental intervention could be ascribed to an insufficient exposure time to the training and a high subjective overall workload encountered in military high school students

The Use of Artificial Intelligence (AI) in the Radiology Field: What Is the State of Doctor–Patient Communication in Cancer Diagnosis?

Simple Summary Artificial Intelligence (AI) has been increasingly used in radiology to improve diagnostic procedures over the past decades. The application of AI at the time of cancer diagnosis also creates challenges in the way doctors should communicate the use of AI to patients. The present systematic review deals with the patient's psycho-cognitive perspective on AI and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Evidence from the retrieved studies pointed out that the use of AI in radiology is negatively associated with patient trust in AI and patient-centered communication in cancer disease. Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor-patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Methods: A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were: ("artificial intelligence" or "intelligence machine") and "communication" "radiology" and "oncology diagnosis". The PRISMA guidelines were followed. Results: 517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results. Conclusions: AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients' trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor-patient diagnosis communication

the prevention of chronic diseases through ehealth a practical overview

Disease prevention is an umbrella term embracing individual-based or population-based interventions aimed at preventing the manifestation of diseases (primary prevention), reducing the impact of a disease that has arisen (secondary prevention), or mitigating the impact of an ongoing illness (tertiary prevention). Digital health has the potential to improve prevention of chronic diseases. Its application ranges from effective mHealth weight-loss intervention to prevent or delay the onset of diabetes in overweight adults to the cost-effective intervention on the provision of mental-health care via mobile-based or Internet-based programs to reduce the incidence or the severity of anxiety. The present contribution focuses on the effectiveness of eHealth preventive interventions and on the role of digital health in improving health promotion and disease prevention. We also give a practical overview on how eHealth interventions have been effectively implemented, developed, and delivered for the primary, secondary, and tertiary prevention of chronic diseases