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“
Good intro to behavioral design - plus parts 2&3 also helpful for toolbox plus process
I - Intended Behavior N - Non-targeted Audiences C - Compensatory Behaviors A - Additional Behaviors S - Signalling E - Emotional Impact
It’s not just about really liking a product (although you definitely want users to really like your product). With the right design elements, your users might embark on a meaningful bond with your technology, where they feel engaged in an ongoing, two-way relationship with an entity that understands something important about them, yet is recognizably non–human. This is a true emotional attachment that supplies at least some of the benefits of a human-to-human relationship. This type of connection can help your users engage more deeply and for a longer period of time with your product. And that should ultimately help them get closer to their behavior change goals.
The following is from Dr. Bucher’s forthcoming book, Engaged: Designing for Behavior Change. I chose this section because it touches upon a PeopleScience theme: being successful and effective behavioral practitioners while also, and primarily, being good.
This is an excerpt from Amy Bucher’s book Engaged: Designing for Behavior Change. In this chapter, you’ll learn how to structure [users’ meaningful choices on their behavior-change journey] so that it’s easier for people to select good options that ultimately support their goals.
40 participants is an appropriate number for most quantitative studies, but there are cases where you can recruit fewer users.
Key Takeaways When customers want to leave, don’t ask why. Shift their attention to why they committed to your product or service in the first place. Instead citing reasons for leaving back to you, they’ll need to recall all the benefits they could lose if they chose to leave. Don’t underestimate the power of opportunity and impact of the environment on behaviors. Keep in mind that preparation meets opportunity. Do your people have all the tools to commit to change? Do they understand and know what to do each step of the way? If not, they are unlikely to change their behavior. Allow people who will be using the new solution to co-create it. This way, implementing change will be much easier. It’s easier to toss aside talking points someone else has created, but not those you came up with - they seem much more valuable thanks to the IKEA effect.
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.
Ultimately, the greatest threat to controlling the pandemic is the failure of people to get tested as soon as they have symptoms, and to provide their contacts and self-isolate. Providing adequate support for isolation is critical to all of these. And so, by deprioritising the case for support, blaming the public fuels the pandemic. The government’s psychological assumptions have, in fact, squandered the greatest asset we have for dealing with a crisis: a community that is mobilised and unified in mutual aid. When an inquiry is eventually held about the UK’s response to COVID-19, it is essential that we give full attention to the psychological and behavioural dimensions of failure as much as the decisions and policies implemented. Only by exposing the way in which the government came to accept and rely upon the wrong model of human behaviour can we begin to build policies that work.
“I understand how you feel.“
Companies should experiment with interactive social media content types, include relevant calls to action in posts, and avoid posting too frequently.
1699 icons CC 0 · CC by SA
Free, open source health icons Free for use in your next commercial or personal project. Editing is ok. Republishing is ok. No need to give credit.
Of the 293 apps shortlisted as offering a therapeutic treatment for anxiety and/or depression, 162 (55.3%) mentioned an evidence-based framework in their app store descriptions. Of the 293 apps, 88 (30.0%) claimed to use cognitive behavioral therapy techniques, 46 (15.7%) claimed to use mindfulness, 27 (9.2%) claimed to use positive psychology, 10 (3.4%) claimed to use dialectical behavior therapy, 5 (1.7%) claimed to use acceptance and commitment therapy, and 20 (6.8%) claimed to use other techniques. Of the 162 apps that claimed to use a theoretical framework, only 10 (6.2%) had published evidence for their efficacy.
The framework comprises 6 key stages. Each building on the insights of the previous and each with its own objectives, tools and resources: 1. What - are the target behaviours? 2. Who - should we focus our resource on? 3. Why - do/don’t those people manifest the target behaviours? 4. How - can we empower people to change? 5. So What? To what extent were our interventions effective? 6. What Now? How do we apply our learnings at scale?