Validation of a TAM Extension in Agriculture: Exploring the Determinants of Acceptance of an e-Learning Platform

Supporting education and training initiatives has been identified as an effective way to address Sustainable Development Challenges. In this sense, e-learning stands out as one of the most viable alternatives considering its advantages in terms of resources, time management, and geographical location. Understanding the reasons that move users to adopt these technologies is critical for achieving the desired social objectives. The Technology Acceptance Model (TAM) provides valuable guidelines to identify the variables shaping users’ acceptance of innovations. The present study aims to validate a TAM extension designed for FARMER 4.0, an e-learning application in the agricultural sector. Findings suggest that content quality (CQ) is the primary determinant of farmers’ and agricultural entrepreneurs’ perception of the tool’s usefulness (PU). Furthermore, experience (EXP) and self-efficacy (SE) shape potential users’ perceptions about ease of use (PEOU). This study offers helpful insight into the design and development of e-learning applications in the farming sector and provides empirical evidence of TAM’s validity to assess technology acceptance

Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications

In recent years information and communication technologies (ICT) have played a significant role in all aspects of modern society and have impacted socioeconomic development in sectors such as education, administration, business, medical care and agriculture. The benefits of such technologies in agriculture can be appreciated only if farmers use them. In order to predict and evaluate the adoption of these new technological tools, the technology acceptance model (TAM) can be a valid aid. This paper identifies the most commonly used external variables in e-learning, agriculture and virtual reality applications for further validation in an e-learning tool designed for EU farmers and agricultural entrepreneurs. Starting from a literature review of the technology acceptance model, the analysis based on Quality Function Deployment (QFD) shows that computer self-efficacy, individual innovativeness, computer anxiety, perceived enjoyment, social norm, content and system quality, experience and facilitating conditions are the most common determinants addressing technology acceptance. Furthermore, findings evidenced that the external variables have a different impact on the two main beliefs of the TAM Model, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). This study is expected to bring theoretical support for academics when determining the variables to be included in TAM extensions

Incidence and Determinants of Symptomatic and Asymptomatic SARS-CoV-2 Breakthrough Infections After Booster Dose in a Large European Multicentric Cohort of Health Workers-ORCHESTRA Project

Background: SARS-CoV-2 breakthrough infections (BI) after vaccine booster dose are a relevant public health issue. Methods: Multicentric longitudinal cohort study within the ORCHESTRA project, involving 63,516 health workers (HW) from 14 European settings. The study investigated the cumulative incidence of SARS-CoV-2 BI after booster dose and its correlation with age, sex, job title, previous infection, and time since third dose. Results: 13,093 (20.6%) BI were observed. The cumulative incidence of BI was higher in women and in HW aged < 50 years, but nearly halved after 60 years. Nurses experienced the highest BI incidence, and administrative staff experienced the lowest. The BI incidence was higher in immunosuppressed HW (28.6%) vs others (24.9%). When controlling for gender, age, job title and infection before booster, heterologous vaccination reduced BI incidence with respect to the BNT162b2 mRNA vaccine [Odds Ratio (OR) 0.69, 95% CI 0.63-0.76]. Previous infection protected against asymptomatic infection [Relative Risk Ratio (RRR) of recent infection vs no infection 0.53, 95% CI 0.23-1.20] and even more against symptomatic infections [RRR 0.11, 95% CI 0.05-0.25]. Symptomatic infections increased from 70.5% in HW receiving the booster dose since < 64 days to 86.2% when time elapsed was > 130 days. Conclusions: The risk of BI after booster is significantly reduced by previous infection, heterologous vaccination, and older ages. Immunosuppression is relevant for increased BI incidence. Time elapsed from booster affects BI severity, confirming the public health usefulness of booster. Further research should focus on BI trend after 4th dose and its relationship with time variables across the epidemics.BackgroundSARS-CoV-2 breakthrough infections (BI) after vaccine booster dose are a relevant public health issue.MethodsMulticentric longitudinal cohort study within the ORCHESTRA project, involving 63,516 health workers (HW) from 14 European settings. The study investigated the cumulative incidence of SARS-CoV-2 BI after booster dose and its correlation with age, sex, job title, previous infection, and time since third dose.Results13,093 (20.6%) BI were observed. The cumulative incidence of BI was higher in women and in HW aged < 50 years, but nearly halved after 60 years. Nurses experienced the highest BI incidence, and administrative staff experienced the lowest. The BI incidence was higher in immunosuppressed HW (28.6%) vs others (24.9%). When controlling for gender, age, job title and infection before booster, heterologous vaccination reduced BI incidence with respect to the BNT162b2 mRNA vaccine [Odds Ratio (OR) 0.69, 95% CI 0.63-0.76]. Previous infection protected against asymptomatic infection [Relative Risk Ratio (RRR) of recent infection vs no infection 0.53, 95% CI 0.23-1.20] and even more against symptomatic infections [RRR 0.11, 95% CI 0.05-0.25]. Symptomatic infections increased from 70.5% in HW receiving the booster dose since < 64 days to 86.2% when time elapsed was > 130 days.ConclusionsThe risk of BI after booster is significantly reduced by previous infection, heterologous vaccination, and older ages. Immunosuppression is relevant for increased BI incidence. Time elapsed from booster affects BI severity, confirming the public health usefulness of booster. Further research should focus on BI trend after 4th dose and its relationship with time variables across the epidemics

Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort

Short summaryWe investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months.BackgroundPersistence of vaccine immunization is key for COVID-19 prevention.MethodsWe investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements.ResultsWe observed a progressively decreasing difference in serologic levels from <30 days to 210–240 days. Age was associated with an increased difference in serologic levels. There was a greater difference between the two serologic measurements in infected HCW than in HCW who had never been infected; before the first measurement, infected HCW had a relative risk (RR) of 0.81 for one standard deviation in the difference [95% confidence interval (CI) 0.78–0.85]. The RRs for a 30-day increase in time between first dose and first serology, and between the two serologies, were 1.08 (95% CI 1.07–1.10) and 1.04 (95% CI 1.03–1.05), respectively. The first measurement was a strong predictor of subsequent antibody decrease (RR 1.60; 95% CI 1.56–1.64). Compared with Comirnaty, Spikevax (RR 0.83, 95% CI 0.75–0.92) and mixed vaccines (RR 0.61, 95% CI 0.51–0.74) were smaller decrease in serological level (RR 0.46; 95% CI 0.40–0.54).ConclusionsAge, COVID-19 infection, number of doses, time between first dose and first serology, time between serologies, and type of vaccine were associated with differences between the two serologic measurements within a 13-month period

Corrigendum: Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: an individual-level analysis within 13 months in the ORCHESTRA cohort

: [This corrects the article DOI: 10.3389/fimmu.2022.1079884.]

SARS-CoV-2 Breakthrough Infections: Incidence and Risk Factors in a Large European Multicentric Cohort of Health Workers

The research aimed to investigate the incidence of SARS-CoV-2 breakthrough infections and their determinants in a large European cohort of more than 60,000 health workers