Is it all about trust? Elderly people’s propensity to digital technology in healthcare: a case study from Italy

Digital technologies for healthcare have found great development and diffusion in the pandemic period, especially as a solution to reach patients with chronic conditions, mostly elderly and residing in remote areas. However, in order to be effective, trust in these technologies is a central component of the interaction. Using data from a survey on the propensity to use digital technologies of elderly people residing in remote areas in four regions of Italy, the present study tests through of latent class model for polytomous outcome what is the probability that they trust health technology tools. The results show that the majority of the sample has trust in digital technologies, even if they do not use them directly. The factors influencing these probabilities turn out to be age and education level. This evidence may be considered useful in forming new digital health policies, especially in view of the factors that influence distrust of digital tools in healthcare

Excess economic burden of multimorbidity: a population-based study in Italy.

t In Italy the increasing incidence of chronic disease and multimorbidity are major challenges for health systems. When a patient suffers from more than one chronic condition, the conditions can interact causing a significant increase in patients’ care needs. Using healthcare administrative databases of Tuscany region to identify cohorts of chronic prevalent patients and their total direct healthcare expenses, in this paper we aim to study the economic burden of multiple chronic conditions and calculate the excess cost when comorbidities occur in order to assess how combinations of chronic conditions in adults affect total direct health expenditure

Inference for big data assisted by small area methods: an application to OBEC (on-line based enterprise characteristics)

Nowadays, the availability of a huge amount of data produced by a wide range of new technologies, so-called big data, is increasing. However, data obtain- able from big data sources are often the result of a non-probability sampling process and adjusting for the selection bias is an important practical problem. In this paper, we propose a novel method of reducing the selection bias associated with the big data source in the context of Small Area Estimation (SAE). Our approach is based on data integration and the combination of a big data sample and a probability sam- ple. An application on OBEC (on-line based enterprise characteristics) combining Istat sampling survey and web scraping data has been proposed

Intraoperative use of tranexamic acid to reduce transfusion rate in patients undergoing radical retropubic prostatectomy: double blind, randomised, placebo controlled trial

Objectives To determine the efficacy of intraoperative treatment with low dose tranexamic acid in reducing the rate of perioperative transfusions in patients undergoing radical retropubic prostatectomy

Membrane targeted Azobenzene drives optical modulation of bacterial membrane potential

Recent studies have shown that bacterial membrane potential is dynamic and plays signaling roles. Yet, little is still known about the mechanisms of membrane potential dynamics regulation—owing to a scarcity of appropriate research tools. Optical modulation of bacterial membrane potential could fill this gap and provide a new approach for studying and controlling bacterial physiology and electrical signaling. Here, the authors show that a membrane-targeted azobenzene (Ziapin2) can be used to photo-modulate the membrane potential in cells of the Gram-positive bacterium Bacillus subtilis. It is found that upon exposure to blue–green light (λ = 470 nm), isomerization of Ziapin2 in the bacteria membrane induces hyperpolarization of the potential. To investigate the origin of this phenomenon, ion-channel-deletion strains and ion channel blockers are examined. The authors found that in presence of the chloride channel blocker idanyloxyacetic acid-94 (IAA-94) or in absence of KtrAB potassium transporter, the hyperpolarization response is attenuated. These results reveal that the Ziapin2 isomerization can induce ion channel opening in the bacterial membrane and suggest that Ziapin2 can be used for studying and controlling bacterial electrical signaling. This new optical tool could contribute to better understand various microbial phenomena, such as biofilm electric signaling and antimicrobial resistance

Measuring Latent Variables is space and/or time: A Gender Statistics exercise

This paper concerns a Multivariate Latent Markov Model recently introduced in the literature for estimating latent traits in social sciences. Based on its ability of simultaneously dealing with longitudinal and spacial data, the model is proposed when the latent response variable is expected to have a time and space dynamic of its own, as an innovative alternative to popular methodologies such as the construction of composite indicators and structural equation modeling. The potentials of the proposed model and the added value with respect to the traditional weighted composition methodology, are illustrated via an empirical Gender Statistics exercise, focused on gender gap as the latent status to be measured and based on supranational official statistics for 30 European countries in the period 2010-2015

Measuring Latent Variables in Space and/or Time: A Gender Statistics exercise

This paper concerns a Multivariate Latent Markov Model recently introduced in the literature for estimating latent traits in social sciences. Based on its ability of simultaneously dealing with longitudinal and spacial data, the model is proposed when the latent response variable is expected to have a time and space dynamic of its own, as an innovative alternative to popular methodologies such as the construction of composite indicators and structural equation modeling. The potentials of the proposed model and the added value with respect to the traditional weighted composition methodology, are illustrated via an empirical Gender Statistics exercise, focused on gender gap as the latent status to be measured and based on supranational o cial statistics for 30 European countries in the period 2010–2015