A nudge helps doctors bring up end-of-life issues with their dying cancer patients

Article by Ravi Parikh et al: “When conversations about goals and end-of-life wishes happen early, they can improve patients’ quality of life and decrease their chances of dying on a ventilator or in an intensive care unit. Yet doctors treating cancer focus so much of their attention on treating the disease that these conversations tend to get put off until it’s too late. This leads to costly and often unwanted care for the patient.Related: 

This can be fixed, but it requires addressing two key challenges. The first is that it is often difficult for doctors to know how long patients have left to live. Even among patients in hospice care, doctors get it wrong nearly 70% of the time. Hospitals and private companies have invested millions of dollars to try and identify these outcomes, often using artificial intelligence and machine learning, although most of these algorithms have not been vetted in real-world settings.

In a recent set of studies, our team used data from real-time electronic medical records to develop a machine learning algorithm that identified which cancer patients had a high risk of dying in the next six months. We then tested the algorithm on 25,000 patients who were seen at our health system’s cancer practices and found it performed better than relying only on doctors to identify high-risk patients.

But just because such a tool exists doesn’t mean doctors will use it to prompt more conversations. The second challenge — which is even harder to overcome — is using machine learning to motivate clinicians to have difficult conversations with patients about the end of life.

We wondered if implementing a timely “nudge” that doctors received before seeing their high-risk patients could help them start the conversation.

To test this idea, we used our prediction tool in a clinical trial involving nine cancer practices. Doctors in the nudge group received a weekly report on how many end-of-life conversations they had compared to their peers, along with a list of patients they were scheduled to see the following week who the algorithm deemed at high-risk of dying in the next six months. They could review the list and uncheck any patients they thought were not appropriate for end-of-life conversations. For the patients who remained checked, doctors received a text message on the day of the appointment reminding them to discuss the patient’s goals at the end of life. Doctors in the control group did not receive the email or text message intervention.

As we reported in JAMA Oncology, 15% of doctors who received the nudge text had end-of-life conversations with their patients, compared to just 4% of the control doctors….(More)”.

Behavioral Science and Public Policy

Paper by Cass R. Sunstein: “Behavioral science is playing an increasing role in public policy, and it is raising new questions about fundamental issues – the role of government, freedom of choice, paternalism, and human welfare. In diverse nations, public officials are using behavioral findings to combat serious problems – poverty, air pollution, highway safety, COVID-19, discrimination, employment, climate change, and occupational health. Exploring theory and practice, this Element attempts to provide one-stop shopping for those who are new to the area and for those who are familiar with it. With reference to nudges, taxes, mandates, and bans, it offers concrete examples of behaviorally informed policies. It also engages the fundamental questions, include the proper analysis of human welfare in light of behavioral findings. It offers a plea for respecting freedom of choice – so long as people’s choices are adequately informed and free from behavioral biases….(More)”.

Technology and Democracy: understanding the influence of online technologies on political behaviour and decision-making

Report by the Joint Research Center (EU): “…The report analyses the cognitive challenges posed by four pressure points: attention economy, platform choice architectures, algorithmic content curation and disinformation, and makes policy recommendations to address them.

Specific actions could include banning microtargeting for political ads, transparency rules so that users understand how an algorithm uses their data and to what effect, or requiring online platforms to provide reports to users showing when, how and which of their data is sold.

This report is the second output from the JRC’s Enlightenment 2.0 multi-annual research programme….(More)”.

How Cape Town Used Behavioral Science to Beat Its Water Crisis

Article by Ammaarah Martinus and Faisal Naru: “In March 2018, the metropolitan government of Cape Town, on South Africa’s Western Cape, announced that it had avoided “Day Zero”—the day the dams supplying the city would have reached 13.5 percent capacity, the point at which the water supply to most of the city would be turned off. Earlier in the year, the city had been forecast to hit Day Zero on April 22, 2018.

Fortunately, it didn’t come to this. The city managed to develop a successful water savings campaign which stopped the taps from running dry in Cape Town. Had this not occurred, residents would have had faced severe restrictions on water use and their daily habits would have been upended. For instance, they would have had to visit water collection sites to service their basic needs. 

The city’s bold and comprehensive communication strategy around Day Zero, which focused on changing behaviors and implementing clever nudges, was a big part of the success story. Here’s how it unfolded….(More)

Timeline: Cape Town’s Water Crisis

Behavioral nudges reduce failure to appear for court

Paper by Alissa Fishbane, Aurelie Ouss and Anuj K. Shah: “Each year, millions of Americans fail to appear in court for low-level offenses, and warrants are then issued for their arrest. In two field studies in New York City, we make critical information salient by redesigning the summons form and providing text message reminders. These interventions reduce failures to appear by 13-21% and lead to 30,000 fewer arrest warrants over a 3-year period. In lab experiments, we find that while criminal justice professionals see failures to appear as relatively unintentional, laypeople believe they are more intentional. These lay beliefs reduce support for policies that make court information salient and increase support for punishment. Our findings suggest that criminal justice policies can be made more effective and humane by anticipating human error in unintentional offenses….(More)”

Dispatches from the Behavioral Scientists Fighting Coronavirus in the Global South

Introduction by Neela Saldanha & Sakshi Ghai: “We are in the middle of a global pandemic, one that has infected more than 35 million people worldwide and killed over 1 million. Almost nine months after the World Health Organization declared the novel coronavirus a “public health emergency of international concern,” the primary strategies we have to prevent the spread of an invisible and often deadly virus are behavioral—keeping a distance, wearing masks, washing hands. No wonder behavioral science has been thrust into the spotlight. Behavioral scientists have been advising national and local governments, as well as health institutions around the world about the best ways to help people collectively adhere to new behaviors.

Although the pandemic rages globally, 7 of the 10 worst outbreaks in the world are in countries in the Global South. These countries have very different social, cultural, and economic contexts from those in the Global North. Mitigating the pandemic in these countries is not simply a matter of importing recommendations from the north. As Saugato Dutta pointed out, “advice that can seem grounded in universal human tendencies must be careful not to ignore the context in which it is applied.”

What are the elements of context that we need to attend to? What issues are behavioral scientists in Nairobi or New Delhi grappling with as they tackle the virus? What can we learn from the interventions deployed in Brazil or in the Philippines? And how can these lessons inspire the rest of the world?

We thought the best way to understand these questions was simply to ask behavioral scientists in those countries. And so, in this special collection, we have curated dispatches from behavioral scientists in Africa, Asia, the Middle East, and South America to learn what’s different about tackling coronavirus.

Our goal is to learn from the work they have done, understand the unique challenges they face, and get their view on what behavioral science needs to focus on to benefit the 80 percent of the world population that lives in these countries. We also hope that this collection will spark ideas and seed collaborations among behavioral scientists in the Global South and North alike. The current situation demands it….(More)”.

Can fake news really change behaviour? Evidence from a study of COVID-19 misinformation.

Paper by Ciara Greene and Gillian Murphy: “Previous research has argued that fake news may have grave consequences for health behaviour, but surprisingly, no empirical data have been provided to support this assumption. This issue takes on new urgency in the context of the coronavirus pandemic. In this large preregistered study (N = 3746) we investigated the effect of exposure to fabricated news stories about COVID-19 on related behavioural intentions. We observed small but measurable effects on some related behavioural intentions but not others – for example, participants who read a story about problems with a forthcoming contact-tracing app reported reduced willingness to download the app. We found no effects of providing a general warning about the dangers of online misinformation on response to the fake stories, regardless of the framing of the warning in positive or negative terms. We conclude with a call for more empirical research on the real-world consequences of fake news….(More)”

Quantified Storytelling: A Narrative Analysis of Metrics on Social Media

Book by Alex Georgakopoulou, Stefan Iversen and Carsten Stage: “This book interrogates the role of quantification in stories on social media: how do visible numbers (e.g. of views, shares, likes) and invisible algorithmic measurements shape the stories we post and engage with? The links of quantification with stories have not been explored sufficiently in storytelling research or in social media studies, despite the fact that platforms have been integrating sophisticated metrics into developing facilities for sharing stories, with a massive appeal to ordinary users, influencers and businesses alike.

With case-studies from Instagram, Reddit and Snapchat, the authors show how three types of metrics, namely content metrics, interface metrics and algorithmic metrics, affect the ways in which cancer patients share their experiences, the circulation of specific stories that mobilize counter-publics and the design of stories as facilities on platforms. The analyses document how numbers structure elements in stories, indicate and produce engagement and become resources for the tellers’ self-presentation….(More)”.

Reimagining Help

Guide by Nesta: “Now more than ever, there is a need to help people live well in their homes and communities. The coronavirus pandemic has highlighted the importance of diversifying sources of help beyond the hospital, and of drawing on support from friends, neighbours, local organisations and charities to ensure people can live healthy lives. We must think more flexibly about what ‘help’ means, and how the right help can make a huge difference.

While medical care is fundamental to saving lives, people need more than a ‘fix’ to live well every day. If we are to support people to reach their goals, we must move away from ʻexpertsʼ holding the knowledge and power, and instead draw on people’s own knowledge, relationships, strengths and purpose to determine solutions that work best for them.

We believe there is an opportunity to ‘reimagine help’ by applying insights from the field of behaviour change research to a wide range of organisations and places – community facilities, local charities and businesses, employment and housing support, as well as health and care services, all of which play a role in supporting people to reach their goals in a way that feels right for them….

Nesta, Macmillan Cancer Support, the British Heart Foundation and the UCL Centre for Behaviour Change have worked together to develop a universal model of ‘Good Help’ underpinned by behavioural evidence, which can be understood and accessed by everyone. We analysed and simplified decades of behaviour change research and practice, and worked with a group of 30 practitioners and people with lived experience to iterate and cross-check the behavioural evidence against real life experiences. Dartington Service Design Lab helped to structure and format the evidence in a way that makes it easy for everyone to understand.

Collectively, we have produced a guide which outlines eight characteristics of Good Help, which aims to support practitioners, system leaders (such as service managers, charity directors or commissioners) and any person working in a direct ‘helping’ organisation to:

  • Understand the behaviour change evidence that underpins Good Help
  • Develop new ideas or adapt offers of Good Help, which can be tested out in their own organisations or local communities….(More)”.

Why Coming Up With Effective Interventions To Address COVID-19 Is So Hard

Article by Neil Lewis Jr.: “It has been hard to measure the effects of the novel coronavirus. Not only is COVID-19 far-reaching — it’s touched nearly every corner of the globe at this point — but its toll on society has also been devastating. It is responsible for the deaths of over 905,000 people around the world, and more than 190,000 people in the United States alone. The associated economic fallout has been crippling. In the U.S., more people lost their jobs in the first three months of the pandemic than in the first two years of the Great Recession. Yes, there are some signs the economy might be recovering, but the truth is, we’re just beginning to understand the pandemic’s full impact, and we don’t yet know what the virus has in store for us.

This is all complicated by the fact that we’re still figuring out how best to combat the pandemic. Without a vaccine readily available, it has been challenging to get people to engage in enough of the behaviors that can help slow the virus. Some policy makers have turned to social and behavioral scientists for guidance, which is encouraging because this doesn’t always happen. We’ve seen many universities ignore the warnings of behavioral scientists and reopen their campuses, only to have to quickly shut them back down.

But this has also meant that there are a lot of new studies to wade through. In the field of psychology alone, between Feb. 10 and Aug. 30, 541 papers about COVID-19 were uploaded to the field’s primary preprint server, PsyArXiv. With so much research to wade through, it’s hard to know what to trust — and I say that as someone who makes a living researching what types of interventions motivate people to change their behaviors.

As I tell my students, if you want to use behavioral science research to address real-world problems, you have to look very closely at the details. Often, a simple question like, “What research should policy makers and practitioners use to help combat the pandemic?” is surprisingly difficult to answer.

For starters, there are often key differences between the lab (or the people and situations some social scientists typically study as part of our day-to-day research) and the real world (or the people and situations policy-makers and practitioners have in mind when crafting interventions).

Take, for example, the fact that social scientists tend to study people from richer countries that are generally highly educated, industrialized, democratic and in the Western hemisphere. And some social scientific fields (e.g., psychologyfocus overwhelmingly on whiter, wealthier and more highly educated groups of people within those nations.

This is a major issue in the social sciences and something that researchers have been talking about for decades. But it’s important to mention now, too, as Black and brown people have been disproportionately affected by the coronavirus — they are dying at much higher rates than white people and working more of the lower-paying “essential” jobs that expose them to greater risks. Here you can start to see very real research limitations creep in: The people whose lives have been most adversely affected by the virus have largely been excluded from the studies that are supposed to help them. When samples and the methods used are not representative of the real world, it becomes very difficult to reach accurate and actionable conclusions….(More)”.