Technology Adoption and Innovation in Public Services.The Case of E-Government in Italy

Using data on 1,176 Italian municipalities in 2005, this paper discusses a number of factors associated with the development of a particular type of innovative activities, namely e-government services supplied by local public administrations (PAs). We find that municipalities which got involved into e-government are larger, carry out more in-house ICT activities and are more likely to have intra-net infrastructures, relative to PAs that do not offer front office digitalised services. They are also generally located in regions with relatively large shares of firms using or producing ICT, where many other municipalities offer digitalised services, and where concentration of inhabitants in metropolitan areas is not very high. The range and quality of e-government services supplied by local PAs tend to increase with their stock of ICT competencies, with their efforts to train workers, and with their ability to organise efficient interfaces with end-users. Moreover, there is a correlation between the range and quality of e-government services offered and the broadband infrastructure development of the geographic area in which local PAs are located. In more general terms, we show that the combination of internal competencies and context specific factors is different when explaining the decision to start e-government activities vs. the intensity of such activities. Regional factors, relating to both demand and supply of services, appear to affect only the decision to enter e-government activities. Competencies needed to expand and improve the quality of services are much more numerous and complex than the ones associated with the mere decision to start e-government activities.Innovation system, Dynamic capabilities, Technology adoption, Electronic government, Innovation in services, Two-part model.

UNIMIB @ DIACR-Ita: Aligning Distributional Embeddings with a Compass for Semantic Change Detection in the Italian Language

In this paper, we present our results related to the EVALITA 2020 challenge, DIACR-Ita, for semantic change detection for the Italian language. Our approach is based on measuring the semantic distance across time-specific word vectors generated with Compass-aligned Distributional Embeddings (CADE). We first generate temporal embeddings with CADE, a strategy to align word embeddings that are specific for each time period; the quality of this alignment is the main asset of our proposal. We then measure the semantic shift of each word, combining two different semantic shift measures. Eventually, we classify a word meaning as changed or not changed by defining a threshold over the semantic distance across time

The interplay between excess weight and hyper-glycemia on NCDs in Italy: results from a cross-sectional study

purpose to evaluate the prevalence of chronic comorbidities according to BMI classes and assess the interplay between excess body weight and blood glucose abnormalities in increasing the risk of major chronic diseases. methods the study is based on data from the health search/IQVIA Health LPD longitudinal patient database, an Italian general practice registry, with data obtained from electronic clinical records of 800 general practitioners throughout Italy. data relative to the year 2018 were analyzed. the study population was classified according to BMI (normal weight, overweight, and obesity classes 1, 2 and 3) and glucose metabolism status (normoglycemia-NGT; impaired fasting glucose-IFG; diabetes mellitus-DM). comorbidities were identified through ICD-9 CM codes. results data relative to 991,917 adults were analyzed. the prevalence of overweight was 39.4%, while the prevalence of obesity was 11.1% (class 1: 7.9%, class 2: 2.3%, class 3: 0.9%). In the whole population, the prevalence of DM and IFG was 8.9% and 4.2%, respectively. both overweight and obesity were associated with an increasing prevalence of glucose metabolism alterations and a large array of different chronic conditions, including cardio-cerebrovascular diseases, heart failure, chronic kidney disease, osteoarticular diseases, depression, sleep apnea, and neoplasms of the gastrointestinal tract. within each BMI class, the presence of IFG, and to a greater extent DM, identified subgroups of individuals with a marked increase in the risk of concomitant chronic conditions. conclusion addressing the double burden of excess weight and hyperglycemia represents an important challenge and a healthcare priority

Outpatient healthcare costs associated with overweight and obesity in Italy

To evaluate outpatient healthcare expenditure associated with different levels of BMI and glucose metabolism alterations

Psychotropic drug purchases during the COVID-19 pandemic in Italy and their relationship with mobility restrictions

Recent literature on the mental health consequences of social distancing measures has found a substantial increase in self-reported sleep disorders, anxiety and depressive symptoms during lockdown periods. We investigate this issue with data on monthly purchases of psychotropic drugs from the universe of Italian pharmacies during the first wave of the COVID-19 pandemic and find that purchases of mental health-related drugs have increased with respect to 2019. However, the excess volumes do not match the massive increase in anxiety and depressive disorders found in survey-based studies. We also study the interplay between mobility, measured with anonymized mobile phone data, and mental health and report no significant effect of mobility restrictions on antidepressants and anxiolytics purchases during 2020. We provide three potential mechanisms that could drive the discrepancy between self-reported mental health surveys and psychotropic drugs prescription registries: (1) stockpiling practices in the early phases of the pandemic; (2) the adoption of compensatory behavior and (3) unexpressed and unmet needs due to both demand- and supply-side shortages in healthcare services

New neuroanatomy learning paradigms for the next generation of trainees: A novel literature-based 3D methodology

Background: An appreciation for complex three-dimensional relationships in neuroanatomy forms a fundamental tenet of neurosurgical education. The value of experience in the cadaver lab is indisputable; however, it is expensive and often inaccessible. The wide availability of 3D technologies has opened new possibilities, although scientific inaccuracy has hitherto limited their use. Objective: In the present study, we aim to describe a novel, literature-based process of scientific 3D modeling for the creation of neuroanatomical models adapted for mobile technology. Methods: A systematic literature review regarding current resources in neuroanatomy education was performed according to PRISMA guidelines. The composition of the team and the workflow behind the 3D Head Atlas app are also described. Results: A total of 101 manuscripts were reviewed, and 24 included. Cadaveric dissections improve the learning process, although high costs limit their availability. Digital advancements have partially overcome the limitations of dissection, and have been associated with improved knowledge retention. Nevertheless, 3D models are often inaccurate, poorly adapted to mobile hardware, and expensive. Recent technological advances provide a new way to widely disseminate complex 3D models, with a revolutionary impact on learning. The approach behind the 3D Head Atlas app, based on the synergistic work of scientific and development teams, facilitates the creation of interactive 3D scientific material with high accuracy and wide accessibility. Conclusion: The study of neuroanatomy is intimately related to the evolution of digital technology. Traditional methods (i.e. cadaveric dissections) have undisputed value but high costs. High-fidelity 3D scenarios and mobile devices may revolutionize learning if based on a sound evidence-based approach

Comparison of anatomical-based vs. nTMS-based risk stratification model for predicting postoperative motor outcome and extent of resection in brain tumor surgery

The authors acknowledge the support of the Cluster of Excellence Matters of Activity. Image Space Material funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germanýs Excellence Strategy – EXC 2025. Dr. Rosenstock is participant in the BIH Charité Digital Clinician Scientist Program funded by the Charité – Universitätsmedizin Berlin, and the Berlin Institute of Health at Charité (BIH). Dr. Belotti received fundings from the Italian Society of Neurosurgery - “Premio Melitta Grasso Tomasello” and the Beretta Foundation for Cancer Study - “European Scholarship on Oncology”.Background: Two statistical models have been established to evaluate characteristics associated with postoperative motor outcome in patients with glioma associated to the motor cortex (M1) or the corticospinal tract (CST). One model is based on a clinicoradiological prognostic sum score (PrS) while the other one relies on navigated transcranial magnetic stimulation (nTMS) and diffusion-tensor-imaging (DTI) tractography. The objective was to compare the models regarding their prognostic value for postoperative motor outcome and extent of resection (EOR) with the aim of developing a combined, improved model. Methods: We retrospectively analyzed a consecutive prospective cohort of patients who underwent resection for motor associated glioma between 2008 and 2020, and received a preoperative nTMS motor mapping with nTMS-based diffusion tensor imaging tractography. The primary outcomes were the EOR and the motor outcome (on the day of discharge and 3 months postoperatively according to the British Medical Research Council (BMRC) grading). For the nTMS model, the infiltration of M1, tumor-tract distance (TTD), resting motor threshold (RMT) and fractional anisotropy (FA) were assesed. For the PrS score (ranging from 1 to 8, lower scores indicating a higher risk), we assessed tumor margins, volume, presence of cysts, contrast agent enhancement, MRI index (grading white matter infiltration), preoperative seizures or sensorimotor deficits. Results: Two hundred and three patients with a median age of 50 years (range: 20–81 years) were analyzed of whom 145 patients (71.4%) received a GTR. The rate of transient new motor deficits was 24.1% and of permanent new motor deficits 18.8%. The nTMS model demonstrated a good discrimination ability for the short-term motor outcome at day 7 of discharge (AUC = 0.79, 95 %CI: 0.72–0.86) and the long-term motor outcome after 3 months (AUC = 0.79, 95 %CI: 0.71–0.87). The PrS score was not capable to predict the postoperative motor outcome in this cohort but was moderately associated with the EOR (AUC = 0.64; CI 0.55–0.72). An improved, combined model was calculated to predict the EOR more accurately (AUC = 0.74, 95 %CI: 0.65–0.83). Conclusion: The nTMS model was superior to the clinicoradiological PrS model for potentially predicting the motor outcome. A combined, improved model was calculated to estimate the EOR. Thus, patient counseling and surgical planning in patients with motor-associated tumors should be performed using functional nTMS data combined with tractography.Peer Reviewe