Study on Psychological Stress Perceived among Employees in an Italian University during Mandatory and Voluntary Remote Working during and after the COVID-19 Pandemic.

OBJECTIVE OF THE STUDY: This cross-sectional study examined the perceived psychological well-being of administrative/technical employees and researchers/lecturers at the University of L'Aquila (Italy) during the COVID-19 pandemic. The study was carried out in two different periods of 2022: April 2022, when remote working was still mandatory, and December 2022, when the pandemic emergency had ended and, in Italy, remote working had become voluntary for two days a week and exclusively for administrative staff. MATERIALS AND METHODS: Perceived psychological well-being was investigated using the GHQ-12 (Global Health Questionnaire, short-form with 12 items), a self-administered questionnaire created on Google Forms and sent via email to all the employees of the University of L'Aquila. Statistical analysis was conducted using means, standard deviations, and frequency tables for the descriptive analysis of socio-demographic data, while the t-test or Wilcoxon test and the Χ2 test were used to verify the statistical difference and association between categorical variables. RESULTS: Overall, 365 employees, including 118 administrative/technical and 247 research/teaching staff, participated in the survey in April 2022 when remote working was mandatory. Among them, 219 (52.8%) were female and 196 (47.2%) were male. In December 2022, 266 employees engaged in voluntary remote working, including 184 (69.2%) women and 82 (30.8%) men, took part in the study. The most represented age group was 50-59 years old (36.3% of study participants). During mandatory remote working, 83.4% of lecturers reported a perceived level of psychological distress ranging from moderate to severe versus 69.5% of technicians. The percentage of self-reported psychological distress was higher among the technicians forced to work from home (n. 118-42.9%) vs. the technicians working from home on a voluntary basis (n. 157-57.1%), with GHQ score being >14 in 65.5% of enforced remote workers vs. 62.3% of voluntary remote workers. During mandatory remote working, there was a significant difference in the GHQ-12 score between administrative and research staff, particularly related to items such as loss of self-confidence, emotional pressures, and diminished productivity. Moreover, from the comparison between the group of administrative staff engaged in mandatory remote working and those in voluntary remote working for specific GHQ-12 items, a statistically significant difference emerged concerning the perception of not being able to overcome difficulties; the GHQ-12 score was higher in the first group. Significant differences in the overall GHQ-12 score were evident between male and female lecturers, as the latter reported higher levels of perceived stress during mandatory remote working. DISCUSSION: The results confirm that remote working could be associated with a better psychological state of administrative university staff, especially in the case of voluntary remote working. During mandatory remote working, a difference was observed between teaching and administrative staff, with higher stress in the first group and among women. Therefore, our sample appears fragmented in the self-assessment of psychological well-being during remote working, possibly due to profound differences in the organization of work activities between lecturers and administrative employees. Additionally, the increased perception of stress by female lecturers compared to males may reflect gender disparities, as women working from home during the pandemic experienced an increased workload including domestic activities. CONCLUSIONS: Remote working is a type of working that has both advantages and disadvantages. An advantage is undoubtedly a better work-life balance; however, the risks of technostress, workaholism, increased sedentary behaviour, and social isolation are negative aspects. This study provides an indicative overview of the psychological state related to remote working in a university setting during the SARS-CoV-2 pandemic. The study might therefore serve as a starting point for further research on the impact of remote working on self-reported psychological well-being, especially in the university environment.

Application of machine learning approach in emergency department to support clinical decision making for SARS-CoV-2 infected patients.

To support physicians in clinical decision process on patients affected by Coronavirus Disease 2019 (COVID-19) in areas with a low vaccination rate, we devised and evaluated the performances of several machine learning (ML) classifiers fed with readily available clinical and laboratory data. Our observational retrospective study collected data from a cohort of 779 COVID-19 patients presenting to three hospitals of the Lazio-Abruzzo area (Italy). Based on a different selection of clinical and respiratory (ROX index and PaO2/FiO2 ratio) variables, we devised an AI-driven tool to predict safe discharge from ED, disease severity and mortality during hospitalization. To predict safe discharge our best classifier is an RF integrated with ROX index that reached AUC of 0.96. To predict disease severity the best classifier was an RF integrated with ROX index that reached an AUC of 0.91. For mortality prediction the best classifier was an RF integrated with ROX index, that reached an AUC of 0.91. The results obtained thanks to our algorithms are consistent with the scientific literature an accomplish significant performances to forecast safe discharge from ED and severe clinical course of COVID-19.

Fall of viral and bacterial pneumonia hospitalizations following COVID-19 pandemic mitigation strategies: a central Italian Region retrospective study.

Community-Acquired Pneumonia (CAP) represents one of the first causes of hospitalization and death in the elderly all over the world and weighs heavily on public health system. Since the beginning of the COVID-19 (CoronaVirus Disease-19) pandemic, everybody's behavior was forced to change, as the result of a global lockdown strategy and the obligation of using personal protection equipment (PPE). We aimed to evaluate how the mitigation strategies adopted to fight SARS-CoV-2 (Severe Acute Respiratory Coronavirus Syndrome 2) infection have influenced hospitalizations due to CAP in two different Local Health Boards (LHBs) of central Italy. We considered two main periods of observation: before and after the national start of lockdown, in two Abruzzo's LHBs. We analyzed 19,558 hospital discharge records of bacterial and viral CAP. Excluding SARS-CoV2 infection, a significant decrease in CAP hospitalizations was observed. Through the analysis of Diagnosis Related Group (DRG) values, we highlighted a significant saving of founds for the Regional Health Service. The enactment of social distancing measures to contain COVID-19 spread, brought down admissions for bacterial and viral pneumonia. Our study emphasizes that costs for hospitalizations due to CAP could be drastically reduced by mask wearing and social distancing.

rDSA : an intelligent tool for data science assignments.

Tools supporting the teaching and learning of programming may help professors in correcting assignments and students in receiving immediate feedback, thus improving the solution before the final submission. This paper describes the rDSA tool, which was designed, developed, and evaluated to support students in completing assignments concerning (i) the execution of statistical analyses in the R language and (ii) commenting on the results in natural language. The paper focuses on the feedback provided by the tool to students and how it was designed/evaluated/improved over the years. The paper also presents the results of two studies that indicate the advantages of using the tool in terms of engagement and learning outcomes. To conclude, we provide a discussion on the characteristics of the tool, its use in similar courses, and the scope for future work.

A device and an app for the diagnosis and self-management of tinnitus.

Tinnitus is an annoying ringing in the ears, in varying shades and intensities. Tinnitus can affect a person's overall health and social well-being (e.g., sleep problems, trouble concentrating, anxiety, depression and inability to work). The diagnostic procedure of tinnitus usually consists of three steps: an audiological examination, psychoacoustic measurement, and a disability evaluation. All steps are performed by physicians, who use specialised hardware/software and administer questionnaires. This paper presents a system, to be used by patients, for the diagnosis and self-management of tinnitus. The system is made up of an app and a device. The app is responsible for executing - through the device - a part of the required audiological and psychoacoustic examinations, as well as administering questionnaires that evaluate disability. The paper reviews the quality of the automated audiometric reporting and the user experience provided by the app. Descriptive and inferential statistics were used to support the findings. The results show that automated reporting is comparable with that of physicians and that user experience was improved by re-designing and re-developing the acufenometry of the app. As for the user experience, two experts in Human-Computer Interaction evaluated the first version of the app: their agreement was good (Cohen's K = 0.639) and the average rating of the app was 1.43/2. Also patients evaluated the app in its initial version: the satisfactory tasks (audiometry and questionnaires) were rated as 4.31/5 and 4.65/5. The unsatisfactory task (acufenometry) was improved and the average rating increased from 2.86/5 to 3.96/5 (p = 0.0005). Finally, the general usability of the app was increased from the initial value of 73.6/100 to 85.4/100 (p = 0.0003). The strengths of the project are twofold. Firstly, the automated reporting feature, which - to the best of our knowledge - is the first attempt in this area. Secondly, the overall app usability, which was evaluated and improved during its development. In summary, the conclusion drawn from the conducted project is that the system works as expected, and despite some weaknesses, also the replication of the device would not be expensive, and it can be used in different scenarios.

Hospitalization Rates for Respiratory Diseases After L'Aquila Earthquake.

The study aims to investigate the impact of the earthquake on public health, in terms of hospitalizations for respiratory diseases in the Abruzzo region, focusing on the area damaged by the earthquake "Crater". We collected data of hospitalizations of residents in Abruzzo between 2009 and 2015. Hospital Discharge Records (HDRs) with a primary diagnosis of respiratory disease were included and divided into pneumonia, Chronic Obstructive Pulmonary Disease (COPD), and respiratory insufficiency. Absolute frequencies and standardized hospitalization rates were calculated to perform both a short-term and a medium-long term analysis. A linear regression was performed using standardized hospitalization rates and the time. A total of 108.669 respiratory-related records were collected and the most frequent subgroup was respiratory insufficiency. Standardized Hospitalization Rates (SHRs) for respiratory diseases resulted higher in the non-Crater than Crater area, but the short-term analysis showed a significant increase in hospitalizations for pneumonia and respiratory insufficiency in the Crater area. The medium-long term analysis reported a significant difference on the slope decrease of hospitalizations for acute and chronic respiratory diseases in the Crater versus the non-Crater area. The earthquake may have played a triggering role in the increased detection of respiratory diseases. A temporal relationship between the quake and an increase in admissions was found although it is not yet possible to detect a direct cause-effect relationship.

Retrospective Analysis of Injuries and Hospitalizations of Patients Following the 2009 Earthquake of L'Aquila City.

The aim of this study was to investigate the injury patterns and the hospitalizations of patients who were admitted to hospital following the 2009 earthquake in the city of L'Aquila, Central Italy. To the best of our knowledge, this is the first study to analyze the patterns of earthquake-related injuries in Italy. We reviewed the hospital discharge data of 171 patients admitted to hospital within the following 96 h from the mainshock. This is an observational and descriptive study: We controlled for variables such as patient demographics, primary and secondary ICD-9-CM (International Classification of Diseases) diagnosis codes in order to identify the multiple injured patients, main type of injury that resulted in the hospital admission, discharge disposition, and average length of stay (LOS). Seventy-three percent of the 171 patients were admitted to hospital on the first day. Multiple injuries accounted for 52% of all trauma admissions, with a female to male ratio of 63% versus 37%. The most common type of injuries involved bone fractures (46.8%), while lower extremities were the most frequently affected sites (38.75%). The average LOS was 12.11 days. This study allows the evaluation of the impact of earthquake-related injuries in relation both to the health needs of the victims and to the use of the health care resources and assistance.

[Health status and access to health services by the population of L'Aquila (Abruzzo Region, Italy) six years after the earthquake]. / Stato di salute e accesso alle prestazioni sanitarie nella popolazione terremotata del comune di L'Aquila. Un bilancio a sei anni dal sisma.

Natural disasters, such as the earthquake that occurred in the province of L'Aquila in central Italy, in 2009, generally increase the demand for healthcare. A survey was conducted to assess perception of health status an d use of health services in a sample of L'Aquila's resident population, five years after the event, and in a comparison population consisting of a sample of the resident population of Avezzano, a town in the same region, not affected by the earthquake. No differences were found in perception of health status between the two populations. Both groups reported difficulties in accessing specialized healthcare and rehabilitation services.

Cardiovascular and cerebrovascular events pre- and post-earthquake of 6 April 2009: the Abruzzo's experience.

BACKGROUND: On 6 April 2009, an earthquake occurred in Abruzzo, a small region in the middle-east of Italy. Its chief town, L'Aquila, was the epicenter. We carried out an observational analysis to evaluate the potential association between the earthquake and the rate of cardiovascular and cerebrovascular admissions of the residents in the province of L'Aquila. METHODS: We used administrative discharge data, extracting all admissions made from 6 April to 31 July 2008 (pre-earthquake control period) or from 6 April to 31 July 2009 (post-earthquake period), assigned to diagnosis-related groups (DRGs) related to cardiovascular or cerebrovascular diseases. RESULTS: The overall number of hospitalizations for cardio- or cerebrovascular diseases by residents in L'Aquila before and after the earthquake was 10,833. In the whole region, the hospitalization rate was slightly lower in 2009 (-0.9%), whereas only in the local health unit (LHU) of L'Aquila it showed an increase by +13.2% (P < 0.01), essentially due to cardiovascular diseases (+21.9%) in elderly people (+26.9%; P < 0.01). The proportion of the main comorbidities in the admissions for cardiovascular diseases of the residents in L'Aquila significantly increased (P = 0.03), but no significant differences could be observed for each comorbidity separately. CONCLUSIONS: Our study supports previous findings of an association between earthquakes and an increase in cardiovascular diseases in the elderly.

XML technologies for the Omaha System: a data model, a Java tool and several case studies supporting home healthcare.

The eXtensible markup language (XML) is a metalanguage which is useful to represent and exchange data between heterogeneous systems. XML may enable healthcare practitioners to document, monitor, evaluate, and archive medical information and services into distributed computer environments. Therefore, the most recent proposals on electronic health records (EHRs) are usually based on XML documents. Since none of the existing nomenclatures were specifically developed for use in automated clinical information systems, but were adapted to such use, numerous current EHRs are organized as a sequence of events, each represented through codes taken from international classification systems. In nursing, a hierarchically organized problem-solving approach is followed, which hardly couples with the sequential organization of such EHRs. Therefore, the paper presents an XML data model for the Omaha System taxonomy, which is one of the most important international nomenclatures used in the home healthcare nursing context. Such a data model represents the formal definition of EHRs specifically developed for nursing practice. Furthermore, the paper delineates a Java application prototype which is able to manage such documents, shows the possibility to transform such documents into readable web pages, and reports several case studies, one currently managed by the home care service of a Health Center in Central Italy.

A SOA statistical engine for biomedical data.

Currently, large efforts are spent to develop standards and architectures useful to achieve more effective interoperability among medical information systems. Despite such efforts, there are no researches produced so far to directly analyse, with statistical methods, biomedical data represented as eXtensible Markup Language (XML) documents. Thus, the paper proposes an architecture which offers a twofold approach to the statistical analysis of XML data, i.e. via a web service and by extending the query languages used in XML databases. To show how the architecture can be used, a sample system is also reported. Finally, the paper ends by reporting the advantages and drawbacks of the proposed approach in comparison with classic statistical packages.

A comparison between EASI system 12-lead ECGs and standard 12-lead ECGs for improved clinical nursing practice.

AIMS AND OBJECTIVES: This study was carried out to verify the accuracy of 12-Lead ECG, obtained through a continuous ECG monitoring system with five cables positioned in EASI mode, to identify basic ECG alterations. BACKGROUND: This study concerns continuous ECG monitoring systems in Coronary Care Units. Continuous ECG monitoring is an important device for nursing surveillance and is useful in decreasing adverse events. DESIGN AND METHOD: Thirteen patients admitted consecutively to the Coronary Care Unit for Acute Myocardial Infarction underwent daily and simultaneous recording of a12-lead ECG using both procedures: EASI ECG and STANDARD ECG. A sample of 1,164 ECG leads acquired in EASI mode was compared with a sample of as many ECG leads acquired using the standard procedure with a traditional cardiograph. RESULTS AND CONCLUSIONS: In the Coronary Care Unit, Continous ECG monitoring with five cables positioned in EASI mode is a valid alternative to the standard 12-lead ECG for cardiac rhythm abnormalities detection and for acute myocardial ischemia and old myocardial infarction assessment. Therefore, the EASI system might be advantageous for long-term patient monitoring. RELEVANCE TO CLINICAL PRACTICE: The EASI system represents a valid device for the nursing surveillance of patients who need continuous ECG monitoring, improves clinical nursing practice in Coronary Care Units, supports the reduction of adverse events such as cardiac arrest and reduces the hospital costs.

[Information technology for the management of health care data: the EPIweb project]. / L'information technology per la gestione di dati sanitari: il progetto EPIweb.

In the US, the Center for Disease Control and Prevention has produced has increased the permeability of the computer science technologies, in order to achieve a better and more efficient management of health care data. In this context, the present paper proposes a discussion regarding a web-based information system, called EPIweb. This system allows researchers to select the centers for the data entry, collect and elaborate health care data, produce technical reports and discuss results. Such a system aims to be easy-to-use, totally configurable and particularly suitable for the management of multicenter studies. The paper shows the EPIweb features, proposes a sample system run, and concludes with a discussion regarding both the advantages and the possible improvements and extensions.