Design, Implementation, and Analysis of an Assessment and Accreditation Model to Evaluate a Digital Competence Framework for Health Professionals: Mixed Methods Study.

Background: Although digital health is essential for improving health care, its adoption remains slow due to the lack of literacy in this area. Therefore, it is crucial for health professionals to acquire digital skills and for a digital competence assessment and accreditation model to be implemented to make advances in this field.

Objective: This study had two objectives: (1) to create a specific map of digital competences for health professionals and (2) to define and test a digital competence assessment and accreditation model for health professionals.

m-RESIST, a Mobile Therapeutic Intervention for Treatment-Resistant Schizophrenia: Feasibility, Acceptability, and Usability Study.

Background: In the European Union, around 5 million people are affected by psychotic disorders, and approximately 30%-50% of people with schizophrenia have treatment-resistant schizophrenia (TRS). Mobile health (mHealth) interventions may be effective in preventing relapses, increasing treatment adherence, and managing some of the symptoms of schizophrenia. People with schizophrenia seem willing and able to use smartphones to monitor their symptoms and engage in therapeutic interventions.

Measuring the Digital Skills of Catalan Health Care Professionals as a Key Step Toward a Strategic Training Plan: Digital Competence Test Validation Study.

Background: Despite Catalonia being an advanced region in terms of digital health adoption, the "Forum for Professional Dialogue" identified the need to improve information and communication technology (ICT) competences as one of the present and future challenges for health care professionals (HPs).

Objective: We aimed to validate the digital competence test developed ad hoc for this study and to measure the digital competence level of Catalan HPs to establish their current level as the baseline for designing a strategic training plan.

Methods: An exploratory observational study was conducted based on a voluntary survey where sociodemographic, professional and digital tool knowledge, digital tool use, and training needs data were collected and based on the score obtained from a digital competence test developed ad hoc.

Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records.

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysiological and genetic characteristics affecting its progression, associated complications and response to therapies. The advances in deep learning (DL) techniques and the availability of a large amount of healthcare data allow us to investigate T2DM characteristics and evolution with a completely new approach, studying common disease trajectories rather than cross sectional values. We used an Kernelized-AutoEncoder algorithm to map 5 years of data of 11,028 subjects diagnosed with T2DM in a latent space that embedded similarities and differences between patients in terms of the evolution of the disease.

A Method to Compare the Delivery of Psychiatric Care for People with Treatment-Resistant Schizophrenia.

Introduction: Community services are gaining ground when it comes to attention to patients with psychiatric diseases. Regarding patients with treatment-resistant schizophrenia (TRS), the use of information and communication technology (ICT) could help to shift the focus from hospital-centered attention to community services. This study compares the differences in mental health services provided for patients with TRS in Budapest (Hungary), Tel-Aviv (Israel) and Catalonia (Spain) by means of a method for the quick appraisal of gaps among the three places, for a potential implementation of the same ICT tool in these regions.

Real-Time Constant Monitoring of Fall Risk Index by Means of Fully-Wireless Insoles.

Constant monitoring of gait in real life conditions is considered the best way to assess Fall Risk Index (FRI) since most falls happen out of the ideal conditions in which clinicians are currently analyzing the patient's behavior. This paper presents the WIISEL platform and results obtained through the use of the first full-wireless insole devices that can measure almost all gait related data directly on the feet (not in the upper part of the body as most existing wearable solutions). The platform consists of a complete tool-chain: insoles, smartphone & app, server & analysis tool, FRI estimation and user access.

A Multi-Stage Human Factors and Comfort Assessment of Instrumented Insoles Designed for Use in a Connected Health Infrastructure.

Wearable electronics are gaining widespread use as enabling technologies, monitoring human physical activity and behavior as part of connected health infrastructures. Attention to human factors and comfort of these devices can greatly positively influence user experience, with a subsequently higher likelihood of user acceptance and lower levels of device rejection. Here, we employ a human factors and comfort assessment methodology grounded in the principles of human-centered design to influence and enhance the design of an instrumented insole.

Manganese(I) templates for the construction of benzannulated triphosphamacrocycles.

Nine-membered 1,4,7-triphosphamacrocycles with unsaturated benzo-backbones have been prepared using the [(CO)3Mn](+) unit as a template. Two synthetic methods have been employed for the macrocyclisation both of which involve the attack of a coordinated phosphide at an activated, electrophilic ortho-fluorophenyl substituent on a neighbouring pnictide donor. Addition of base to the precursor complex fac-[(CO)3Mn(dfppb)(PhPH2)](+), 1, where dfppb = 1,2-bis[di(2-fluorophenyl)phosphino]benzene, results in the direct formation of the macrocyclic compound fac-[Mn(CO)3(tribenzo-9aneP3-Ph,Ph(F)2)](+), 3.

A wireless sensor insole for collecting gait data.

This paper presents the status of the EU project WIISEL - Wireless Insole for Independent and Safe Elderly Living, with the focus on sensors and wireless communications. Pressure and inertial sensors are embedded into insoles and a smartphone collects data utilizing Bluetooth Low Energy.