Objective: In this work, we aimed to develop a practical, structured approach to identify narratives in public online conversations on social media platforms where concerns or confusion exist or where narratives are gaining traction, thus providing actionable data to help the WHO prioritize its response efforts to address the COVID-19 infodemic. Methods: We developed a taxonomy to filter global public conversations in English and French related to COVID-19 on social media into 5 categories with 35 subcategories. The taxonomy and its implementation were validated for retrieval precision and recall, and they were reviewed and adapted as language about the pandemic in online conversations changed over time. The aggregated data for each subcategory were analyzed on a weekly basis by volume, velocity, and presence of questions to detect signals of information voids with potential for confusion or where mis- or disinformation may thrive. A human analyst reviewed and identified potential information voids and sources of confusion, and quantitative data were used to provide insights on emerging narratives, influencers, and public reactions to COVID-19–related topics. Results: A COVID-19 public health social listening taxonomy was developed, validated, and applied to filter relevant content for more focused analysis. A weekly analysis of public online conversations since March 23, 2020, enabled quantification of shifting interests in public health–related topics concerning the pandemic, and the analysis demonstrated recurring voids of verified health information. This approach therefore focuses on the detection of infodemic signals to generate actionable insights to rapidly inform decision-making for a more targeted and adaptive response, including risk communication.
chatbot conversational “game“
In 2005, he asked participants to read samples of text including graduate school applications, sociology dissertation abstracts and translations of a work of Descartes. Some participants read the original versions, written in a verbose, jargon-filled style, while others were given edited versions, with unnecessarily complex words switched for simpler alternatives. Finally, the psychologist asked the participants to rate the intelligence of the authors. Those who read the simplified versions rated the author as +10% more intelligent than those who read the more complex, original text.
“I understand how you feel.“
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Amy Jo Kim interviews Casey Means, cofounder of Levels
Our project tracks behavioural science evidence and advice about COVID-19 vaccine uptake. The handbook is for journalists, doctors, nurses, policy makers, researchers, teachers, students, parents – in short, it’s for everyone who wants to know more: about the COVID-19 vaccines, how to talk to others about them, how to challenge misinformation about the vaccines. The handbook is self-contained but additionally provides access to a Wiki of more detailed information, found here: https://sks.to/c19vax.
Effective communication is always important in public health, but it’s never been more important to understand the perceptions of Americans and modify your language accordingly. These recommendations are based on the “Changing the COVID Conversation” poll, conducted by Frank Luntz in partnership with the de Beaumont Foundation, Nov. 21-22, 2020.
Five principles for an effective COVID-19 lexicon 1. Messaging never merely provides factual information – communication unavoidably conveys many assumptions (the subtext, indirect meanings, inferences, and implications). 2. Messaging should be lexically and grammatically precise and thus easy to enact and adhere to. 3. Messaging should be ‘irony-resistant’. 4. ‘Branding’ or sloganeering should not come at the expense of clarity and precision. 5. Messaging should be underpinned by evidence about what is effective.
They found that the indulgent label resulted in the highest consumption. It was chosen 25% more than the basic label, 35% more than with h healthy positive label, and 41% more than the health restrictive label. Veggie consumption increased significantly as well—16% more than the basic label, 23% more than the healthy positive label, and 33% more than the healthy restrictive label.
Again: you don’t convince people. People convince themselves. Studies done as far back as the 1940’s by Kurt Lewin showed that lectures about why people should change their behavior were effective a measly 3% of the time. But when people self-generated reasons for the same activity, behavior change occurred 37% of the time. People reject ideas they are given and act on ideas they feel they came up with themselves.
Ratzan and colleagues identified three general areas of capacity building for health communication during the pandemic: the need for communicators to be proactive and to take preventive actions at times; the importance of planning ahead while also acknowledging the unpredictability of the situation; and the call to focus on people. The checklist for health communicators is made up of five objectives: set shared goals, establish coordinated response, devise a communication strategy, implement the communication plan, and be ready to adapt.
When people see food that is symmetrical, they tend to believe it is more natural – and when they think a food is more natural, they perceive it to be healthier.
To become a better catalyst for change, Berger suggests to: Find the gaps. Rather than push or persuade someone, highlight a gap between their attitudes and their actions, and then get them to persuade themselves. For example: If someone is reluctant to wear a mask at work, ask them if they would wear one if their child or elderly parent were in the office. Ask why that same care or concern isn't present with their colleagues? Provide a “menu” of choices. Rather than unilaterally force a single solution on others, give people the freedom and autonomy to choose from a few options. This is one way to reduce people’s gut resistance, and again, help them persuade themselves. Cut through perceived risks. If people feel like a new idea is controversial or risky, explain your personal experience as to why you think it is more relatable and less extreme than they think.
Accurate classification of smoking status has long been regarded as an essential prerequisite for advancing tobacco-related epidemiologic, treatment, and policy research. However, the descriptors we commonly use to classify people who smoke may inadvertently perpetuate harmful, stigmatizing beliefs and negative stereotypes. In recognizing the power of words to either perpetuate or reduce stigma, Dr. Nora Volkow—Director of the National Institute on Drug Abuse—recently highlighted the role of stigma in addiction,1 and the movement encouraging the use of person-first language and eliminating the use of slang and idioms when describing addiction and the people whom it affects.2,3 In this commentary, we make an appeal for researchers and clinicians to use personfirst language (e.g., “people who smoke”) rather than commonly used labels (e.g., “smokers”) in written (e.g., in scholarly reports) and verbal communication (e.g., clinical case presentations ) to promote greater respect and convey dignity for people who smoke. We assert that the use of precise and bias-free language to describe people who smoke has the potential to reduce smoking-related stigma and may enhance the precision of scientific communication.
Language data There is little information available on the languages crisis-affected people speak and understand. Humanitarians often develop communication strategies without reliable data on literacy, languages spoken, or preferred means of communication. The result too often is that crisis-affected people struggle to communicate with humanitarian organizations in a language they understand. Women, children, older people, and people with disabilities are often at the greatest disadvantage because they are less likely to understand international languages and lingua francas. TWB’s Language Data Initiative addresses those issues and provides important resources for humanitarians. It supports humanitarian organizations to develop language-informed programs and communication strategies. Click on a country on the map below to see language data, resources, and maps that we have available for that country. This map will update as new data is published in the future.
Forward-thinking public health professionals are reaching across sectors to build healthier communities. Recognizing that effective collaboration advances everyone’s mission, Public Health Reaching Across Sectors (PHRASES) supports an “all-hands-on-deck” approach with tools to build communication skills and strategies designed for success.
The Patient Activation Measure is a valid, highly reliable, unidimensional, probabilistic Guttman‐like scale that reflects a developmental model of activation. Activation appears to involve four stages: (1) believing the patient role is important, (2) having the confidence and knowledge necessary to take action, (3) actually taking action to maintain and improve one's health, and (4) staying the course even under stress. The measure has good psychometric properties indicating that it can be used at the individual patient level to tailor intervention and assess changes. (https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1475-6773.2004.00269.x)
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