P>0.05 Is Good: The NORD-h Protocol for Several Hypothesis Analysis Based on Known Risks, Costs, and Benefits.

Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.

Google trends in infodemiology: Methodological steps to avoid irreproducible results and invalid conclusions.

Background: Google Trends is a widely used tool for infodemiological surveys. However, irregularities in the random sampling and aggregation algorithms compromise the reliability of the relative search volume (RSV) and the regional online interest (ROI).

Objective: The study aims to unmask methodological criticalities commonly ignored in carrying out infodemiological surveys via Google Trends.

For a proper use of frequentist inferential statistics in public health.

As widely noted in the literature and by international bodies such as the American Statistical Association, severe misinterpretations of -values, confidence intervals, and statistical significance are sadly common in public health. This scenario poses serious risks concerning terminal decisions such as the approval or rejection of therapies. Cognitive distortions about statistics likely stem from poor teaching in schools and universities, overly simplified interpretations, and - as we suggest - the reckless use of calculation software with predefined standardized procedures.

Correction: Multiple Confidence Intervals and Surprisal Intervals to Avoid Significance Fallacy.

[This corrects the article DOI: 10.7759/cureus.51964.

Multiple Confidence Intervals and Surprisal Intervals to Avoid Significance Fallacy.

Overconfidence in statistical results in medicine is fueled by improper practices and historical biases afflicting the concept of statistical significance. In particular, the dichotomization of significance (i.e.

A Framework to Avoid Significance Fallacy.

This manuscript presents a concise approach to tackle the widespread misuse of statistical significance in scientific research, focusing on public health. It offers practical guidance for conducting accurate statistical evaluations and promoting easily understandable results based on actual evidence. When conducting a statistical study to inform decision-making, it is recommended to follow a step-by-step sequence while considering various factors.

There is a need for more precise models to assess the determinants of health crises like COVID-19.

The COVID-19 pandemic has had a significant impact on global mortality. While the causal relationship between SARS-CoV-2 and the anomalous increase in deaths is established, more precise and complex models are needed to determine the exact weight of epidemiological factors involved. Indeed, COVID-19 behavior is influenced by a wide range of variables, including demographic characteristics, population habits and behavior, healthcare performance, and environmental and seasonal risk factors.

World Health Organization is losing online credibility towards health-sensitive topics: Infodemiological analysis of Facebook users' reactions.

The scientific infodemic constitutes one of the greatest threats to public health and safety today. The credibility of the main dissemination agencies is an essential tool for adhering to measures to preserve public health. The study is a longitudinal retrospective conducted on a web platform to investigate netizens' infodemic attitude towards World Health Organization.

Common Statistical Errors in Scientific Investigations: A Simple Guide to Avoid Unfounded Decisions.

During my experience as an author, peer reviewer, and editor during COVID-19, I have encountered - and committed - various errors related to the interpretation and use of statistical measures and tests. Primarily concerning health sciences such as epidemiology, infodemiology, and public health, the evidence used to inform a conclusion carries an extremely high weight as it translates into decisions made to preserve the population's well-being. Therefore, the aforementioned evidence must be reliable.

Are We Sure We Fully Understand What an Infodemic Is? A Global Perspective on Infodemiological Problems.

Infodemic is defined as an information epidemic that can lead to engaging in dangerous behavior. Although the most striking manifestations of the latter occurred on social media, some studies show that dismisinformation is significantly influenced by numerous additional factors, both web-based and offline. These include social context, age, education, personal knowledge and beliefs, mood, psychological defense mechanisms, media resonance, and how news and information are presented to the public.

Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.

Background: Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature.

Objective: This paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends.

The Impact of COVID-19 on Mortality in Italy: Retrospective Analysis of Epidemiological Trends.

Background: Despite the available evidence on its severity, COVID-19 has often been compared with seasonal flu by some conspirators and even scientists. Various public discussions arose about the noncausal correlation between COVID-19 and the observed deaths during the pandemic period in Italy.

Objective: This paper aimed to search for endogenous reasons for the mortality increase recorded in Italy during 2020 to test this controversial hypothesis.

A new infodemiological approach through Google Trends: longitudinal analysis of COVID-19 scientific and infodemic names in Italy.

The scientific community has classified COVID-19 as the worst pandemic in human history. The damage caused by the new disease was direct (e.g.

Influence of Mass Media on Italian Web Users During the COVID-19 Pandemic: Infodemiological Analysis.

Background: Concurrently with the COVID-19 pandemic, the world has been facing a growing infodemic, which has caused severe damage to economic and health systems and has often compromised the effectiveness of infection containment regulations. Although this infodemic has spread mainly through social media, there are numerous occasions on which mass media outlets have shared dangerous information, giving resonance to statements without a scientific basis. For these reasons, infoveillance and infodemiology methods are increasingly exploited to monitor information traffic on the web and make epidemiological predictions.

The Impact of Cheering on Sports Performance: Comparison of Serie A Statistics Before and During COVID-19.

Background:  The role of cheering in home advantage in sports performance is unclear. As anti-coronavirus disease 2019 (COVID-19) restrictive measures have prevented crowds from entering stadiums, analysis of the past two football seasons can reveal important details.

Objective:  This paper aims to compare the last two football seasons in Italy with the previous six, highlighting changes due to the absence of cheering.

The Impact of COVID-19 on Conspiracy Hypotheses and Risk Perception in Italy: Infodemiological Survey Study Using Google Trends.

Background: COVID-19 has caused the worst international crisis since World War II. Italy was one of the countries most affected by both the pandemic and the related infodemic. The success of anti-COVID-19 strategies and future public health policies in Italy cannot separate itself from the containment of fake news and the divulgation of correct information.

Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research.

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. The aim of this study is to test the reliability of a widely used infoveillance tool which is Google Trends.

Raiders of the Lost Correlation: A Guide on Using Pearson and Spearman Coefficients to Detect Hidden Correlations in Medical Sciences.

Pearson and Spearman correlations are important tools for all scientific fields and are widely used in medical sciences, especially during the current COVID-19 pandemic emergency. This technical report has shown that conventional criteria for evaluating the adoption of these coefficients can conceal substantial scientific information regarding correlations that occur above or below a certain threshold. In particular, the Pearson coefficient can reveal hidden correlations even when data are not normally distributed.

Relationships between Demographic, Geographic, and Environmental Statistics and the Spread of Novel Coronavirus Disease (COVID-19) in Italy.

Background: Since January 2020, the coronavirus disease 2019 (COVID-19) pandemic has raged around the world, causing nearly a million deaths and hundreds of severe economic crises. In this scenario, Italy has been one of the most affected countries.

Objective: This study investigated significant correlations between COVID-19 cases and demographic, geographical, and environmental statistics of each Italian region from February 26 to August 12, 2020.

The Impact of COVID-19 on Italian Web Users: A Quantitative Analysis of Regional Hygiene Interest and Emotional Response.

Background: Between the end of February and the beginning of June 2020, Italy was certainly one of the worst affected countries in the world by the coronavirus disease 2019 (COVID-19) pandemic. During this period, Web interest in the novel coronavirus underwent a drastic surge.

Objective: The aim of this study was to quantitatively analyze the impact of COVID-19 on Web searches related to hygiene-preventive measures and emotional-psychological aspects as well as to estimate the effectiveness and limits of online information during an epidemic.