Gabriele Panerai

Bio: Gabriele Panerai is an academic researcher from University of Florence. The author has contributed to research in topics: The Internet & Locus of control. The author has an hindex of 1, co-authored 2 publications receiving 1 citations.

What Went Wrong? Predictors of Contact Tracing Adoption in Italy during COVID-19 Pandemic

Abstract: Together with vaccines, contact tracing systems (CTS) have proved to be one of the best strategies to deal with the current COVID-19 pandemic. However, the adoption of such systems has been quite limited in EU countries, and Italy was no exception. The present research aimed to investigate the factors drawn from the most relevant psychological models in the literature, most associated with the adoption of CTS. The data analysis of the 501 surveyed answers (329 from CTS adopters) showed that knowing important others who have downloaded the CTS, CTS attitudes, CTS perceived efficacy, COVID-19 risk perception, and trust in the government and its actions influenced the adoption of the Italian CTS (52% of explained variance). These factors defined a new specific model that can be used to more effectively promote CTS adoption and thus increase the protective potential of these technologies, whose effectiveness is inevitably linked to adoption.

Development and Validation of the Social Media Capital Scale (SMC): A Brand New Measure for Online Social Capital

Abstract: We conducted a series of studies in order to develop a tool to assess social media capital, that is, more specifically, individual confidence in the use of social media sites and in their application to maintain and increase social capital. In our first study, we created the social media capital (SMC) scale by adapting parts of two already existing instruments and administered it to 6935 people to test its psychometric properties and dimensionality. After having validated the SMC in its final 7-item form, we proceeded to assess its external validity in two subsequent studies, by testing it against measures for Internet self-efficacy (study 2; n = 3100 ) and motives to use the Internet and social media addiction (study 3; n = 244 ). Overall, the SMC displayed satisfactory psychometric properties and appears to be a sound measure of social media capital.

Development and validation of the Internet Locus of Control Scale (I-LOC):

Abstract: No psychological tools have yet been developed to assess the locus of control that people experience when in the Internet environment. In a first study, we developed the Internet Locus of Control (...

Management of Smart and Sustainable Cities in the Post-COVID-19 Era: Lessons and Implications

Abstract: Nowadays, the concept of smart sustainable governance is wrapped around basic principles such as: (i) transparency, (ii) accountability, (iii) stakeholders’ involvement, and iv) citizens’ participation. It is through these principles that are influenced by information and communication technologies (ICT), Internet of Things (IoT), and artificial intelligence, that the practices employed by citizens and their interaction with electronic government (e-government) are diversified. Previously, the misleading concepts of the smart city implied only the objective of the local level or public officials to utilize technology. However, the recent European experience and research studies have led to a more comprehensive notion that refers to the search for intelligent solutions which allow modern sustainable cities to enhance the quality of services provided to citizens and to improve the management of urban mobility. The smart city is based on the usage of connected sensors, data management, and analytics platforms to improve the quality and functioning of built-environment systems. The aim of this paper is to understand the effects of the pandemic on smart cities and to accentuate major exercises that can be learned for post-COVID sustainable urban management and patterns. The lessons and implications outlined in this paper can be used to enforce social distancing community measures in an effective and timely way, and to optimize the use of resources in smart and sustainable cities in critical situations. The paper offers a conceptual overview and serves as a stepping-stone to extensive research and the deployment of sustainable smart city platforms and intelligent transportation systems (a sub-area of smart city applications) after the COVID-19 pandemic using a case study from Russia. Overall, our results demonstrate that the COVID-19 crisis encompasses an excellent opportunity for urban planners and policy makers to take transformative actions towards creating cities that are more intelligent and sustainable.

Through the Second Wave: Analysis of the Psychological and Perceptive Changes in the Italian Population during the COVID-19 Pandemic

Abstract: More than a year has passed since “patient 0” was found and COVID-19 is now an established reality that a lot of people have had to accept and coexist with. In Italy, the pandemic hit in “waves”, but the studies assessing the longitudinal impact of the pandemic in the general population are not many. In this paper, we compared data collected during the first wave with data gathered during the second one, so that we can provide insights about the Italian population’s psychological adaptation to the pandemic also by comparing them with pre-pandemic normative scores. From our results, it seemed that people were seeking a compromise: indeed, despite the still-relevant risk perception, people apparently “learned” how to deal with the pandemic as indicated by an increase in self-efficacy and a more internal locus of control.

An IoT-Based COVID-19 Prevention and Control System for Enclosed Spaces

Abstract: To date, the protracted pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had widespread ramifications for the economy, politics, public health, etc. Based on the current situation, definitively stopping the spread of the virus is infeasible in many countries. This does not mean that populations should ignore the pandemic; instead, normal life needs to be balanced with disease prevention and control. This paper highlights the use of Internet of Things (IoT) for the prevention and control of coronavirus disease (COVID-19) in enclosed spaces. The proposed booking algorithm is able to control the gathering of crowds in specific regions. K-nearest neighbors (KNN) is utilized for the implementation of a navigation system with a congestion control strategy and global path planning capabilities. Furthermore, a risk assessment model is designed based on a “Sliding Window-Timer” algorithm, providing an infection risk assessment for individuals in potential contact with patients.

COVID-19 Mobile Health Apps: An Overview of Mobile Applications in Indonesia

Abstract: Background Mobile health applications (mHealth apps) have been widely used for various purposes for mitigating the COVID-19 pandemic, such as self-assessment, contact tracing, disseminating information, minimizing exposure, and reducing face-to-face health consultation. The objective of this study is to systematically review COVID-19 related mHealth apps and highlight gaps to inform the development of future mHealth initiatives in Indonesia. Methods A systematic search strategy using a PRISMA flowchart was used to identify mHealth apps available in Google Play and Apple Play stores. We searched mHealth apps using certain specific terms related to COVID-19 outbreaks. The inclusion criteria were apps-based smartphone users related to COVID-19 using local language, free of cost, available in the Google Play and Apple Play Stores, and supported by the Indonesian government. We excluded games, apps on infectious diseases unrelated to COVID-19 specifically, and apps with non-Bahasa Indonesia (Indonesian language). The selected mHealth apps were assessed based on two measures: (1) the WHO guidelines on digital health intervention and (2) the four dimensions of the mHealth technology fit framework. In addition, user feedback from experienced and non-experienced users was conducted to evaluate four dimensions of the apps. Results A total of 339 mHealth apps were generated from the initial search, remaining seven selected apps that met inclusion criteria. The results highlighted that mHealth apps reviewed had still not been widely used by the general public. The applications were purposed to disseminate information, conduct a self-risk assessment, provide an online community forum, and telemedicine or teleconsultation regarding COVID-19. Data services, including data storage, aggregation, and data exchange, are available in most apps. The rarest function found was contact tracing and assisting health management and health workers, such as the availability of testing facilities, reporting test results, and prescribing medication. The main issues reported were the lack of data security and data privacy protection, integration and infrastructures, usability, and usefulness. Conclusion Our study highlighted the necessity to improve mHealth apps' functions related to assisting health workers and the function of digital contact tracing. An effort to increase public awareness regarding the use of mHealth is also necessary to streamline the function of this innovation. Policymakers must consider usefulness, usability, integration, and infrastructure issues to improve their mHealth function.

Italian Version of the Internet Self-Efficacy Scale: Internal and External Validation

Abstract: Online activities are a fundamental part of daily life in this digital era and Internet self-efficacy (ISE) became a central construct for the psychologists of virtual environments. The Internet Self-Efficacy Scale developed by Kim and Glassman (2013) is a recent, valid, and reliable 17-item test to assess the ISE. The aim of this research, composed by two studies, was to translate and validate the Italian version of the ISS. In study 1, we evaluated the factorial validity and internal consistency of the Italian version of the ISS on 3724 individuals. In study 2, we tested the ISS external validity relying on the Bergen Social Media Addiction Scale (BSMAS) and the Internet Addiction Scale (IAS) based on the answers of 244 participants. The findings supported the reliability and validity of the translated ISS and its use for assessing ISE on the Italian population. Implications for researchers and interventions are also discussed.