Food Advertisement and Marketing Policies Aimed at Reducing Childhood Obesity: A Review of Existing Regulations in High-Income Countries.

Objectives: To identify and evaluate the difference between voluntary and mandatory food marketing policies and regulations targeting childhood obesity and to study the role of media, the food industry, and private associations in implementing such policies.

Methods: A review of policies and legislation about unhealthy food marketing was conducted by searching and extracting relevant grey literature from the websites of international health agencies, food marketing pledge databases, GINA, and NOURISHING policy databases. Statutory laws and self-regulations of high-income countries were compared with each other and with the WHO recommendations.

The Impact of Violent Media Content and Knowledge of Viable Responses to Cyberviolence on Good Citizenship Behavior Among South Korean Adolescents.

Exposure to cyberviolence among adolescents has become a societal issue in the media-saturated world. In this study, we examine whether or not exposure to violent media content, victimization or perpetration experiences, parental and teacher intervention, susceptibility, knowledge of viable responses when exposed to cyberviolence, and awareness of legal consequences influence the witnessing of cyberviolence among adolescents. Additionally, we investigate the characteristics that lead to good citizenship behavior when adolescents witness cyberviolence.

The effectiveness of visual-based interventions on health literacy in health care: a systematic review and meta-analysis.

Background: Limited Health Literacy (HL) is an obstacle to accessing and receiving optimal health care and negatively impacts patients' quality of life, thus making it an urgent issue in the health care system. Visual-based interventions are a promising strategy to improve HL through the use of visual aids and pictorial materials to explain health-related concepts. However, a comprehensive summary of the literature on the topic is still scarce.

The Impact of COVID-19 and Exposure to Violent Media Content on Cyber Violence Victimization Among Adolescents in South Korea: National Population-Based Study.

Background: Because of the COVID-19 pandemic and consequent stay-at-home mandates, adolescents faced isolation and a decline in mental health. With increased online activity during this period, concerns arose regarding exposure to violent media content and cyber victimization among adolescents. Yet, the precise influence of pandemic-related measures on experiences of cyber violence remains unclear.

Call for emergency action to restore dietary diversity and protect global food systems in times of COVID-19 and beyond: Results from a cross-sectional study in 38 countries.

Background: The COVID-19 pandemic has revealed the fragility of the global food system, sending shockwaves across countries' societies and economy. This has presented formidable challenges to sustaining a healthy and resilient lifestyle. The objective of this study is to examine the food consumption patterns and assess diet diversity indicators, primarily focusing on the food consumption score (FCS), among households in 38 countries both before and during the first wave of the COVID-19 pandemic.

Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study.

Background: Generation Z (born 1995-2010) members are digital residents who use technology and the internet more frequently than any previous generation to learn about their health. They are increasingly moving away from conventional methods of seeking health information as technology advances quickly and becomes more widely available, resulting in a more digitalized health care system. Similar to all groups, Generation Z has specific health care requirements and preferences, and their use of technology influences how they look for health information.

Unlocking the brain secrets of social media through neuroscience.

Neuroscientific buzzwords, such as 'brain hacks', have become commonplace when discussing social media (SM)-platform engineering. Despite societal debates, few studies have used neuroscientific approaches to validate the claims empirically. We call here for a transformative shift engaging scientists and other stakeholders to address this critical knowledge gap.

Generalized Pairwise Comparisons to Assess Treatment Effects: JACC Review Topic of the Week.

A time-to-first-event composite endpoint analysis has well-known shortcomings in evaluating a treatment effect in cardiovascular clinical trials. It does not fully describe the clinical benefit of therapy because the severity of the events, events repeated over time, and clinically relevant nonsurvival outcomes cannot be considered. The generalized pairwise comparisons (GPC) method adds flexibility in defining the primary endpoint by including any number and type of outcomes that best capture the clinical benefit of a therapy as compared with standard of care.

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.

Graphs are a powerful tool for representing and analyzing unstructured, non-Euclidean data ubiquitous in the healthcare domain. Two prominent examples are molecule property prediction and brain connectome analysis. Importantly, recent works have shown that considering relationships between input data samples has a positive regularizing effect on the downstream task in healthcare applications.

Acute Coronary Occlusion in Patients With Non-ST-Segment Elevation Out-of-Hospital Cardiac Arrest.

Background: According to current guidelines, hemodynamic status should guide the decision between immediate and delayed coronary angiography (CAG) in out-of-hospital cardiac arrest (OHCA) patients without ST-segment elevation. A delayed strategy is advised in hemodynamically stable patients, and an immediate approach is recommended in unstable patients.

Objectives: This study sought to assess the frequency, predictors, and clinical impact of acute coronary occlusion in hemodynamically stable and unstable OHCA patients without ST-segment elevation.

Opportunities and challenges of using social media big data to assess mental health consequences of the COVID-19 crisis and future major events.

The present commentary discusses how social media big data could be used in mental health research to assess the impact of major global crises such as the COVID-19 pandemic. We first provide a brief overview of the COVID-19 situation and the challenges associated with the assessment of its global impact on mental health using conventional methods. We then propose social media big data as a possible unconventional data source, provide illustrative examples of previous studies, and discuss the advantages and challenges associated with their use for mental health research.

Toward understanding the communication in sperm whales.

Machine learning has been advancing dramatically over the past decade. Most strides are human-based applications due to the availability of large-scale datasets; however, opportunities are ripe to apply this technology to more deeply understand non-human communication. We detail a scientific roadmap for advancing the understanding of communication of whales that can be built further upon as a template to decipher other forms of animal and non-human communication.

Reducing Changeover Time Between Surgeries Through Lean Thinking: An Action Research Project.

Background: Maximizing the utilization of the operating room suite by safely and efficiently changing over patients is an opportunity to deliver more value to patients and be more efficient in the operating suite. Lean Thinking is a concept that focuses on the waste inadvertently generated during organization and development of an activity, which should maximize customer value while minimizing waste. It has been widely applied to increase process efficiency and foster continuous improvement in healthcare and in the operating room environment.

The Evolution of Public Sentiments During the COVID-19 Pandemic: Case Comparisons of India, Singapore, South Korea, the United Kingdom, and the United States.

Background: Public sentiments are an important indicator of crisis response, with the need to balance exigency without adding to panic or projecting overconfidence. Given the rapid spread of the COVID-19 pandemic, governments have enacted various nationwide measures against the disease with social media platforms providing the previously unparalleled communication space for the global populations.

Objective: This research aims to examine and provide a macro-level narrative of the evolution of public sentiments on social media at national levels, by comparing Twitter data from India, Singapore, South Korea, the United Kingdom, and the United States during the current pandemic.

The perils of misinformation: when health literacy goes awry.

Growing patient empowerment and the deluge of health information and misinformation have highlighted the importance of health literacy. Unfortunately, public information and literacy programmes often fail to counter the effect of misinformation. Successfully countering misinformation presents distinctive challenges beyond patient education, and may require trust built on collaborative patient–clinician relationships.

Obesity-Related Communication in Digital Chinese News From Mainland China, Hong Kong, and Taiwan: Automated Content Analysis.

Background: The fact that the number of individuals with obesity has increased worldwide calls into question media efforts for informing the public. This study attempts to determine the ways in which the mainstream digital news covers the etiology of obesity and diseases associated with the burden of obesity.

Objective: The dual objectives of this study are to obtain an understanding of what the news reports on obesity and to explore meaning in data by extending the preconceived grounded theory.

Dysphagic disorder in a cohort of COVID-19 patients: Evaluation and evolution.

Background: COVID-19 is a multisystem disease complicated by respiratory failure requiring sustanined mechanical ventilation (MV). Prolongued oro-tracheal intubation is associated to an increased risk of dysphagia and bronchial aspiration. Purpose of this study was to investigate swallowing disorders in critically ill COVID-19 patients.

Predicting anticancer hyperfoods with graph convolutional networks.

Background: Recent efforts in the field of nutritional science have allowed the discovery of disease-beating molecules within foods based on the commonality of bioactive food molecules to FDA-approved drugs. The pioneering work in this field used an unsupervised network propagation algorithm to learn the systemic-wide effect on the human interactome of 1962 FDA-approved drugs and a supervised algorithm to predict anticancer therapeutics using the learned representations. Then, a set of bioactive molecules within foods was fed into the model, which predicted molecules with cancer-beating potential.