Suchergebnisse

Background: Alongside the COVID-19 pandemic, government authorities around the world have had to face a growing infodemic capable of causing serious damages to public health and economy. In this context, the use of infoveillance tools has become a primary necessity. Objective: The aim of this study is to test the reliability of a widely used infoveillance tool which is Google Trends. In particular, the paper focuses on the analysis of relative search volumes (RSVs) quantifying their dependence on the day they are collected. Methods: RSVs of the query coronavirus + covid during February 1—December 4, 2020 (period 1), and February 20—May 18, 2020 (period 2), were collected daily by Google Trends from December 8 to 27, 2020. The survey covered Italian regions and cities, and countries and cities worldwide. The search category was set to all categories. Each dataset was analyzed to observe any dependencies of RSVs from the day they were gathered. To do this, by calling [Formula: see text] the country, region, or city under investigation and j the day its RSV was collected, a Gaussian distribution [Formula: see text] was used to represent the trend of daily variations of [Formula: see text]. When a missing value was revealed (anomaly), the affected country, region or city was excluded from the analysis. When the anomalies exceeded 20% of the sample size, the whole sample was excluded from the statistical analysis. Pearson and Spearman correlations between RSVs and the number of COVID-19 cases were calculated day by day thus to highlight any variations related to the day RSVs were collected. Welch's t-test was used to assess the statistical significance of the differences between the average RSVs of the various countries, regions, or cities of a given dataset. Two RSVs were considered statistical confident when [Formula: see text]. A dataset was deemed unreliable if the confident data exceeded 20% (confidence threshold). The percentage increase [Formula: see text] was used to quantify the difference between two ...

Science is a systematic approach to building and organizing knowledge through testable explanations and predictions. However, since scientists are human beings, they are fallible and subject to various systematic and random biases. The COVID-19 pandemic has definitively unmasked the humanity of scientists, who committed severe communication mistakes or even adhered to conspiracy hypotheses. Indeed, emotionality and rationality (if not epistemic) can foster intellectual dishonesty and compromise the effectiveness of critical thinking. This highlights the importance of the context in which a scientist works, as politeness and respect are essential to maintain lucidity, credibility, and transparency. However, outside of the academic context, many scientists do not behave with the same level of courtesy and carefulness required in scientific publishing. This happens despite communication – which is crucial for scientific investigation, dissemination, and debunking campaigns – being scientifically based on compassion. Specifically, an effective communication plan should be tailored to a specific audience, taking into account their emotional state, cultural and social background, and cognitive and psychological characteristics. The sole purpose must be to help and not to manipulate. Therefore, empathy, kindness, and moderation are essential tools for the success of science, from research to communication and education, and awareness campaigns and training courses should be instituted to promote such a message.