Behavioral Scientist

Most Read Articles of 2020

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We began the year in an optimistic mood by imagining the next decade of behavioral science. As the field celebrated something of a tenth birthday, we asked behavioral scientists to weigh in with their hopes, fears, and questions for the coming decade.

In February, following that predictive flurry, Robert Frank revealed “ The Mother of All Cognitive Illusions .” Lee Anne Fennell provided a new perspective on an old problem, with her insights on how to lump and slice your goals. In early March, with impeccable timing, Dan Heath let us in on how to go “ upstream ” to solve problems before they happen. 

Perhaps unsurprisingly, COVID-19’s fingerprints are on the list, though the lessons it inspired are bigger than just this specific situation or year. 

Erik Angner reminded us of the virtue of epistemic humility —that saying “I don’t know” can actually help you get you closer to the truth. An open letter by behavioral scientists to the U.K. government reminded us how transparent decision-making, good communication, and basing policy on evidence is always a good idea. Syon Bhanot helped us understand those who pushed back on early curve-flattening restrictions. Michael Hallsworth reviewed the barriers to handwashing, and Christina Gravert didn’t let us forget that we were in it for the long haul and that we needed to design our choice architecture with that in mind. 

Last, in a year when rhythms were disrupted, Ashley Whillans showed us how to get “time smart” by understanding the time confetti in our lives.

We hope you’ll take a moment to read or re-read the articles that behavioral scientists like you turned to most.

— The Editorial Board

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Epistemic Humility—Knowing Your Limits in a Pandemic

By Erik Angner

“Ignorance,” wrote Charles Darwin in 1871, “more frequently begets confidence than does knowledge.”

behavioural science research articles

Time Confetti and the Broken Promise of Leisure

By Ashley Whillans

We have more free time than ever before, but it’s so sliced and diced that we feel more time poor than ever. Here’s how to notice and overcome the time confetti in your life.

behavioural science research articles

Why a Group of Behavioral Scientists Penned an Open Letter to the U.K. Government Questioning Its Coronavirus Response

By Ulrike Hahn, Nick Chater, David Lagnado, Magda Osman, and Nichola Raihani

An open letter signed by hundreds of behavioural scientists from across the U.K. calls into question the British government’s decision not to enact social distancing measures.

behavioural science research articles

Imagining the Next Decade of Behavioral Science

By Evan Nesterak

We asked you to share your hopes and fears, predictions and warnings, open questions and big ideas. So, what might the next decade hold?

behavioural science research articles

Why Are People Ignoring Expert Warnings? Psychological Reactance

By Syon Bhanot

While some are heeding the advice of public health experts, not everyone is doing so. From spring breakers to governors, some feel the need to defy orders. This behavioral phenomenon could help explain why.

behavioural science research articles

To Achieve Your Goals, Lump and Slice

By Lee Anne Fennell

Humans are remarkably sensitive to how we bundle and divide tasks and choices. We can use that quirk to help realize our aspirations.

behavioural science research articles

Handwashing Can Stop a Virus—So Why Don’t We Do It?

By Michael Hallsworth

How can behavioral science help us take advantage of one of the most effective measures to prevent the spread of viruses?

behavioural science research articles

The Mother of All Cognitive Illusions

By Robert H. Frank

It’s little wonder that people would believe that higher taxes would make them feel bad. But this is a cognitive error, pure and simple.

behavioural science research articles

To Solve Problems Before They Happen, You Need to Unite the Right People

By Dan Heath

When everyone was telling teenagers to “just say no” to drugs and alcohol, a forward-thinking team in Iceland was figuring out what teenagers could say yes to. The results are nothing short of revolutionary.

behavioural science research articles

Why Triggering Emotions Won’t Lead to Lasting Behavior Change

By Christina Gravert

How can we generate long-term behavior change when compliance isn’t exciting anymore? (Hint: don’t build “Piano Stairs.”)

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Recruiting for the modern military: new research examines why people choose to serve and who makes the ideal soldier

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Nudge theory doesn’t work after all, says new evidence review – but it could still have a future

Magda Osman , Cambridge Judge Business School

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Climate change: efficiency labels really do encourage less energy use – but there’s a better way of using them

David Comerford , University of Stirling

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Will booking an Airbnb help Ukraine? Why people make counterproductive decisions about charity

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Exposure of faked dishonesty study makes me proud to be a behavioural scientist

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Human behaviour: what scientists have learned about it from the pandemic

Stephen Reicher , University of St Andrews

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Reparations for slavery and colonial abuses: how behavioural science can help

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Net zero will mean breaking bad habits, but can we get there in time?

Lorraine Whitmarsh , University of Bath

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How coronavirus has changed us: join an online discussion with three experts in human behaviour

Megan Clement, The Conversation

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We asked 70,000 people how coronavirus affected them – what they told us revealed a lot about inequality in the UK

Daisy Fancourt , UCL and Alexandra Bradbury , UCL

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Greta Thunberg effect: people familiar with young climate activist may be more likely to act

Anandita Sabherwal , London School of Economics and Political Science and Sander van der Linden , University of Cambridge

behavioural science research articles

To get ahead as an introvert, act like an extravert. It’s not as hard as you think

Andrew Spark , Queensland University of Technology and Peter O'Connor , Queensland University of Technology

behavioural science research articles

Even with a vaccine, we need to adjust our mindset to playing the COVID-19 long game

Robert Hoffmann , RMIT University and Swee-Hoon Chuah , University of Tasmania

behavioural science research articles

COVID-19 vaccine: how the ‘mum test’ can help ensure  take-up

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The government should be up front about the trade-offs behind its new social distancing measures

Graham Loomes , Warwick Business School, University of Warwick

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Four potential consequences of wearing face masks we need to be wary of

Olga Perski , UCL and David Simons , Royal Veterinary College

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How to keep up social distancing after lockdown

Benjamin van Rooij , University of Amsterdam and Emmeke B. Kooistra , University of Amsterdam

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Realizing the full potential of behavioral science for climate change mitigation

by Kristian S. Nielsen, Viktoria Cologna, Jan M. Bauer, Sebastian Berger, Cameron Brick, Thomas Dietz, Ulf J. J. Hahnel, Laura Henn, Florian Lange, Paul C. Stern, & Kimberly S. Wolske

Behavioral science has yielded insights about the actions of individuals, particularly acting as consumers, that affect climate change. Behaviors in other spheres of life remain understudied. In this Perspective, we propose a collaborative research agenda that integrates behavioral science insights across multiple disciplines. To this end, we offer six recommendations for optimizing the quality and impact of research on individual climate behavior. They are united by a shift towards more solutions-focused research that is directly useful to citizens, policymakers, and other change agents. Achieving this vision will require overcoming challenges such as limited funding for behavioral and social sciences and structural barriers within and beyond the academic system that impede collaborations across disciplines.

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ScienceDaily

Study tracks shifts in student mental health during college

Dartmouth study followed 200 students all four years, including through the pandemic.

A four-year study by Dartmouth researchers captures the most in-depth data yet on how college students' self-esteem and mental health fluctuates during their four years in academia, identifying key populations and stressors that the researchers say administrators could target to improve student well-being.

The study also provides among the first real-time accounts of how the coronavirus pandemic affected students' behavior and mental health. The stress and uncertainty of COVID-19 resulted in long-lasting behavioral changes that persisted as a "new normal" even as the pandemic diminished, including feeling more stressed, less socially engaged, and sleeping more.

The researchers tracked more than 200 Dartmouth undergraduates in the classes of 2021 and 2022 for all four years of college. Students volunteered to let a specially developed app called StudentLife tap into the sensors that are built into smartphones. The app cataloged their daily physical and social activity, how long they slept, their location and travel, the time they spent on their phone, and how often they listened to music or videos. Students also filled out weekly behavioral surveys, and selected students gave post-study interviews.

The study -- which is the longest mobile-sensing study ever conducted -- is published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies . The researchers will present it at the Association of Computing Machinery's UbiComp/ISWC 2024 conference in Melbourne, Australia, in October. The team made their anonymized data set publicly available -- including self-reports, surveys, and phone-sensing and brain-imaging data -- to help advance research into the mental health of students during their college years.

Andrew Campbell, the paper's senior author and Dartmouth's Albert Bradley 1915 Third Century Professor of Computer Science, said that the study's extensive data reinforces the importance of college and university administrators across the country being more attuned to how and when students' mental well-being changes during the school year.

"For the first time, we've produced granular data about the ebb and flow of student mental health. It's incredibly dynamic -- there's nothing that's steady state through the term, let alone through the year," he said. "These sorts of tools will have a tremendous impact on projecting forward and developing much more data-driven ways to intervene and respond exactly when students need it most."

First-year and female students are especially at risk for high anxiety and low self-esteem, the study finds. Among first-year students, self-esteem dropped to its lowest point in the first weeks of their transition from high school to college but rose steadily every semester until it was about 10% higher by graduation.

"We can see that students came out of high school with a certain level of self-esteem that dropped off to the lowest point of the four years. Some said they started to experience 'imposter syndrome' from being around other high-performing students," Campbell said. "As the years progress, though, we can draw a straight line from low to high as their self-esteem improves. I think we would see a similar trend class over class. To me, that's a very positive thing."

Female students -- who made up 60% of study participants -- experienced on average 5% greater stress levels and 10% lower self-esteem than male students. More significantly, the data show that female students tended to be less active, with male students walking 37% more often.

Sophomores were 40% more socially active compared to their first year, the researchers report. But these students also reported feeling 13% more stressed than during their first year as their workload increased, they felt pressure to socialize, or as first-year social groups dispersed.

One student in a sorority recalled that having pre-arranged activities "kind of adds stress as I feel like I should be having fun because everyone tells me that it is fun." Another student noted that after the first year," students have more access to the whole campus and that is when you start feeling excluded from things."

In a novel finding, the researchers identify an "anticipatory stress spike" of 17% experienced in the last two weeks of summer break. While still lower than mid-academic year stress, the spike was consistent across different summers.

In post-study interviews, some students pointed to returning to campus early for team sports. Others specified reconnecting with family and high school friends during their first summer home, saying they felt "a sense of leaving behind the comfort and familiarity of these long-standing friendships" as the break ended, the researchers report.

"This is a foundational study," said Subigya Nepal, first author of the study and a PhD candidate in Campbell's research group. "It has more real-time granular data than anything we or anyone else has provided before. We don't know yet how it will translate to campuses nationwide, but it can be a template for getting the conversation going."

The depth and accuracy of the study data suggest that mobile-sensing software could eventually give universities the ability to create proactive mental-health policies specific to certain student populations and times of year, Campbell said.

For example, a paper Campbell's research group published in 2022 based on StudentLife data showed that first-generation students experienced lower self-esteem and higher levels of depression than other students throughout their four years of college.

"We will be able to look at campus in much more nuanced ways than waiting for the results of an annual mental health study and then developing policy," Campbell said. "We know that Dartmouth is a small and very tight-knit campus community. But if we applied these same methods to a college with similar attributes, I believe we would find very similar trends."

Weathering the pandemic

When students returned home at the start of the coronavirus pandemic, the researchers found that self-esteem actually increased during the pandemic by 5% overall and by another 6% afterward when life returned closer to what it was before. One student suggested in their interview that getting older came with more confidence. Others indicated that being home led to them spending more time with friends talking on the phone, on social media, or streaming movies together.

The data show that phone usage -- measured by the duration a phone was unlocked -- indeed increased by nearly 33 minutes, or 19%, during the pandemic, while time spent in physical activity dropped by 52 minutes, or 27%. By 2022, phone usage fell from its pandemic peak to just above pre-pandemic levels, while engagement in physical activity had recovered to exceed the pre-pandemic period by three minutes.

Despite reporting higher self-esteem, students' feelings of stress increased by more than 10% during the pandemic. Since the pandemic, stress fell by less than 2% of its pandemic peak, indicating that the experience had a lasting impact on student well-being, the researchers report.

In early 2021, as students returned to campus, the reunion with friends and community was tempered by an overwhelming concern of the still-rampant coronavirus. "There was the first outbreak in winter 2021 and that was terrifying," one student recalls. Another student adds: "You could be put into isolation for a long time even if you did not have COVID. Everyone was afraid to contact-trace anyone else in case they got mad at each other."

Female students were especially concerned about the coronavirus, on average 13% more than male students. "Even though the girls might have been hanging out with each other more, they are more aware of the impact," one female student reported. "I actually had COVID and exposed some friends of mine. All the girls that I told tested as they were worried. They were continually checking up to make sure that they did not have it and take it home to their family."

Students still learning remotely had social levels 16% higher than students on campus, who engaged in activity an average of 10% less often than when they were learning from home. However, on-campus students used their phones 47% more often. When interviewed after the study, these students reported spending extended periods of time video-calling or streaming movies with friends and family.

Social activity and engagement had not yet returned to pre-pandemic levels by the end of the study in June 2022, recovering by a little less than 3% after a nearly 10% drop during the pandemic. Similarly, the pandemic seems to have made students stick closer to home, with their distance traveled cut by nearly half during the pandemic and holding at that level in the time since.

Campbell and several of his fellow researchers are now developing a smartphone app known as MoodCapture that uses artificial intelligence paired with facial-image processing software to reliably detect the onset of depression before the user even knows something is wrong.

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Story Source:

Materials provided by Dartmouth College . Original written by Morgan Kelly. Note: Content may be edited for style and length.

Journal Reference :

  • Subigya Nepal, Wenjun Liu, Arvind Pillai, Weichen Wang, Vlado Vojdanovski, Jeremy F. Huckins, Courtney Rogers, Meghan L. Meyer, Andrew T. Campbell. Capturing the College Experience . Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2024; 8 (1): 1 DOI: 10.1145/3643501

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Behavioural and social science research opportunities

Maria a carrasco.

a United States Agency for International Development (USAID), Office of Population and Reproductive Health; 500 D Street SW, 05.4.1A, Washington, DC, United States of America (USA).

Alexandria K Mickler

b Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, USA.

Kaitlyn Atkins

Joseph g rosen, rafael obregon.

c United Nations Children’s Fund, Asuncion, Paraguay.

Incorporating behavioural insights into health policies, interventions and systems has helped reduce injury-related mortality, improve adherence to medications and reduce tobacco use. 1 Nevertheless, health practitioners and policy-makers sometimes overlook behaviourally informed and focused approaches. For instance, early coronavirus disease 2019 (COVID-19) prevention efforts in the United States of America relied on best-case modelling scenarios, which assumed widespread adoption of preventive behaviours like face-mask use. Despite compulsory face-mask mandates, behavioural adoption was slow; once vaccines were available, officials then focused on vaccine uptake. Adequate vaccine uptake, in turn, depends on incorporating behavioural insights to address vaccine hesitancy. Indeed, vaccine administration, and not vaccines alone, is needed to help curb the COVID-19 pandemic. Voluntary vaccine uptake requires creating an enabling environment based on trust, working with social influencers and respected opinion leaders to model vaccine uptake, and providing appropriate motivation such as vaccine passports that facilitate travel, among other actions. While incorporation of behavioural insights into health policies, interventions and systems is gaining momentum, challenges remain. Here we describe three challenges in behavioural and social science research that hamper the integration of behavioural insights and we highlight opportunities for addressing them.

Methodological challenges

Social and behavioural issues are complex and adaptive, and fully understanding their impact requires the use of similarly dynamic, multidimensional approaches. For example, random assignment is a unique challenge for social behaviour change trials, particularly for national media-based interventions where random assignment to intervention arms is infeasible. This difficulty leads researchers to turn to more complex study designs and statistical approaches to provide unbiased estimates of treatment effects. 2 However, such approaches are resource-intensive, and ensuring their appropriate interpretation down the research pipeline can be challenging.

Behavioural science researchers also face the challenge of measuring key psychosocial, contextual and structural factors that influence health. While progress has been made, existing measures of these factors require constant adaptation and refinement based on context. Furthermore, many health behaviour measures are self-reported and subject to social desirability and recall biases. List experimentation techniques and negatively framed questions in one recent population-based survey, for example, were shown to significantly reduce self-reported compliance with recommended public health measures during the COVID-19 pandemic. 3 Where possible, behavioural studies should integrate additional, more objective indicators (for example biomarkers, attendance records and health clinic registers) and apply techniques to minimize bias in self-reported data, such as self-interviewing and unmatched counting. Similarly, indicators used to assess social behaviour change programme coverage and impact, such as number of media communications received and condom use at last sex, are often unstable, that is, subject to change easily with small environmental adjustments or bias. Recognizing these indicators’ weaknesses can ensure appropriate interpretation of results and the potential development of more stable measures. Elicitation techniques like media recall items, where survey respondents are asked to finish a slogan from a mass media communication, are more nuanced measures for appraising social behaviour change communication intervention coverage. Assessing programme impact is further complicated by the scarcity of modelling studies linking social behaviour change interventions with impact measures such as number of deaths averted. Modelling can provide important information related to the population-level impact of behaviourally informed or focused investments to ensure equitable resource allocation and support advocacy efforts.

Despite these challenges, rigorous behavioural research and evaluations in non-controlled settings are ongoing. Ecological momentary assessments have shown promise for capturing psychosocial, behavioural and intervention outcomes using real-time data capture. 4 Natural experiments have provided causal evidence around the impact of mass media interventions on fertility. 5 Experimental research in mass media and communications has identified intervention effects by comparing outcomes among listener groups who received targeted social and behaviour mass media campaigns, compared to controls who received typical mass media messages. 6 , 7 Donors and peer-reviewed journals should support the use and development of these and other promising new methods for data analysis through funding and publication opportunities, even in cases of null findings.

Limited data availability and use

The integration of behavioural insights into interventions and health policies has been hampered by a lack of data availability and use. Many behavioural science studies are not designed nor used to their maximum potential. Full descriptions of interventions, curriculums or protocols are typically not readily available for replication, thereby reducing opportunities for standardization across programmes and contexts. Similarly, no systematic reporting of costing or cost–effectiveness data exists, preventing cost comparisons and complicating the ability to determine scale-up or replication costs. Limited availability and use of data are also a barrier to determining and analysing opportunities for improved impact in cases where an intervention did not achieve intended results.

While qualitative and quantitative data from behavioural science studies could be used to conduct secondary analyses, these analyses are rare because such data are not openly shared. Oftentimes, systems are not in place to share data with interested stakeholders and researchers in a way that protects the anonymity of research participants. However, making data available is critical for transparency and accountability. Furthermore, widely accessible data can enable local researchers to include indigenous perspectives in addressing local concerns and providing opportunities for knowledge sharing and strengthened data analysis skills, as well as enhancing the presentation and utilization of evidence. In this area, international donors can have an important impact by requiring researchers to make protocols, data collection instruments and de-identified data (that is, that cannot be traced to the study participant) publicly available in a timely manner. Donors can also invest in online data-sharing platforms that outlive project lifecycles. Additionally, international donors and multilateral organizations should encourage research collaboration with local researchers and fund local data analysis and capacity-strengthening activities.

Researchers, policy-makers and practitioners are often unable to cite evidence-based strategies promoting behaviour change and leading to improved health outcomes. Part of the challenge rests with researchers’ tendency to seek simple intervention main effects when the more informative analytical approach would be to identify factors in the pathway between behavioural approaches and health outcomes. In other words, evaluations tend to ask whether interventions achieve desired outcomes, without focusing on explaining why and how these interventions work or not. Additionally, interventions do not affect everyone uniformly; rather, some people are affected under some conditions but not others. Therefore, the contextual factors affecting the intervention’s impact must also be considered. Furthermore, researchers do not typically unpack the contribution of each behavioural strategy employed in multicomponent interventions to measured health outcomes. A recent analysis of behavioural interventions in family planning, for example, aggregated multicomponent interventions into a packages category and estimated their effects on modern contraceptive uptake, since the aggregated studies were not designed to provide individual component effects. 8 To build a strong evidence base and develop strategies for translating behavioural insights across contexts, studies guided by theories of change that examine psychosocial pathways and moderators are key to building the evidence base and strategies for translating behavioural insights across contexts. Funders should prioritize these types of studies.

While the number of high-quality evaluations testing behavioural pathways has grown in the last decade, their dissemination in practitioner and policy-maker circles remains limited. Delegates attending the first International Social and Behaviour Change Communication Summit in Addis Ababa (2016) reached similar conclusions. 9 Furthermore, a stakeholder analysis to inform this field for adolescent sexual and reproductive health programmes highlights that practitioners experience challenges integrating science into practice and that general guidance, tools and strategy standardization are needed. 10 Thus, enhanced research utilization efforts are needed.

The High Impact Practices in Family Planning, an authoritative evidence synthesis, summarize some of the social and behaviour change literature in succinct briefs, using nontechnical language, for decision-makers and implementers. 11 However, the High-Impact Practices Technical Advisory Group has recognized that the current briefs, focused on channels of communication, are too broad to inform family planning investments. Thus, new high impact practices briefs are being developed with evidence syntheses on strategies for advancing intermediate outcomes, such as couples communication, social norms, beliefs and attitudes associated with various family planning outcomes (for example, achieving fertility intentions, full and informed method choice and modern contraceptive uptake). Another example focusing on analysing pathways to change is the work completed under the ACCELERATE project, which identified priority behaviours (or intermediate outcomes) in the pathway leading to ultimate desired health outcomes in maternal and child health. The ThinkBig website, initially developed by ACCELERATE, offers numerous resources for practitioners to integrate behavioural insights into public health programmes. 12 The High Impact Practices and ACCELERATE are examples of strategies to facilitate behavioural insights integration and knowledge utilization, by synthesizing evidence using accessible language that explains complex behavioural pathways. Practitioners and policy-makers should use these and similar tools to integrate behavioural and social science evidence into public health policies and programmes. Donors should prioritize investments to help translate behavioural and social science evidence into practice by integrating research utilization into programme and research design.

Acknowledgements

We thank Rajiv Rimal and Victor Orozco.

Competing interests:

None declared.

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  • Published: 09 October 2020

Use caution when applying behavioural science to policy

  • Hans IJzerman   ORCID: orcid.org/0000-0002-0990-2276 1 , 2   na1 ,
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  • Andrew K. Przybylski   ORCID: orcid.org/0000-0001-5547-2185 4   na1 ,
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Social and behavioural scientists have attempted to speak to the COVID-19 crisis. But is behavioural research on COVID-19 suitable for making policy decisions? We offer a taxonomy that lets our science advance in ‘evidence readiness levels’ to be suitable for policy. We caution practitioners to take extreme care translating our findings to applications.

Researchers in the social and behavioural sciences periodically debate whether their research should be used to address pressing issues in society. To provide a few examples, in the 1940s psychologists discussed using research to address problems related to intergroup relations, problems brought to the fore by the Holocaust and other acts of rampant prejudice. In the 1990s, psychologists debated whether their research should inform legal decision-making. In the 2010s, psychologists argued for advising branches of government as economists often do. And now, in 2020, psychologists and other social and behavioural scientists are arguing that our research should inform the response to the new coronavirus disease (henceforth COVID-19) 1 , 2 .

We are a team mostly consisting of empirical psychologists who conduct research on basic, applied and meta-scientific processes. We believe that scientists should apply their creativity, efforts and talents to serve our society, especially during crises. However, the way that social and behavioural science research is often conducted makes it difficult to know whether our efforts will do more good than harm. We will provide some examples from the field of social-personality psychology, where most of us were trained, to illustrate our concerns. This focus is not meant to imply that our field alone suffers from the issues we will discuss. Instead, a growing meta-science literature suggests that many other social and behavioural disciplines have encountered dynamics similar to those faced by our field.

What are those dynamics? First, study participants, mainly students, are drawn from populations that are in Western (mostly US), educated, industrialized, rich and democratic (WEIRD) societies 3 . Second, even with this narrow slice of population, the effects in published papers are not estimated with precision, sometimes barely ruling out trivially small effects under ostensibly controlled conditions. Third, many studies use a narrow range of stimuli and do not test for stimulus generalisability 4 . Fourth, many studies examine effects on measures, such as self-report scales, that are infrequently validated or linked to behaviour, much less to policy-relevant outcomes 5 . Fifth, independently replicated findings, even under ideal circumstances, are rare. Finally, our studies often fail to account for deeper cultural, historical, political and structural factors that play important moderating roles during the process of translation from basic findings to application. Together, these issues produce empirical insights that are more heterogeneous than might be apparent from a scan of the published literature.

Confident applications of social and behavioural science findings, then, require first and foremost an assessment of the evidence quality and weighing heterogeneity and the trade-offs and opportunity costs that follow. We must identify reliable findings that can be applied, have been investigated in the nations for which the application is intended and are derived from investigations using diverse stimuli. But the assessment of how ‘ready’ the intervention is must be included when persuading decision-makers to apply social and behavioural science evidence, particularly in crisis situations when lives are at stake and resources are limited. Not doing so can have disastrous consequences.

Here we propose one approach for assessing the quality of evidence before application and dissemination. Specifically, we draw inspiration from the US National Aeronautics and Space Administration (NASA)’s ‘technology readiness levels’ (TRL 6 ), a benchmarking system for systematically evaluating the quality of scientific evidence and which has been used by the European Commission to judge how ready scientific applications beyond space flight are for operational environments. TRLs rank a technology’s readiness for application from 1 to 9 (see Fig. 1 ). At TRL1, basic principles have been reliably observed, reported and translated to a formal model. In TRL2, basic principles have been developed and tested in an application area. It is not until TRL4, when a prototype is developed, that tests are run in various environments that are as representative of the eventual application area(s) as possible. Later, at TRL6, the system is tested in a ‘real’ environment (like ground-to-space). At the very highest level (TRL9), the system has been ‘flight-proven’ through successful mission operations. These TRLs provide a useful framework to jumpstart conversations about how to assess the readiness of social and behavioural science evidence for application and dissemination.

figure 1

NASA technology readiness levels. Original image source: https://www.nasa.gov/directorates/heo/scan/engineering/technology/txt_accordion1.html .

Introducing evidence readiness levels

The desire to “directly inform policy and individual and collective behaviour in response to the pandemic” (p. 461) 1 overlooks existing evidence frameworks and the challenges we identify, illustrating that a simple taxonomy is necessary to have at hand during crises. As a very preliminary step to this end we propose a social and behavioural science variant of TRLs, evidence readiness levels (ERLs; Fig. 2 ).

figure 2

Proposed social and behavioural sciences evidence readiness levels.

There are several frameworks for assessing evidence quality across different scientific fields. The one that comes closest to what we envision is the Society for Prevention’s standards for prevention interventions 7 , as they incorporate standards for efficacy dissemination and feedback loops from crisis to theory. However, none of the existing frameworks capture the meta-scientific insights generated in our field in the last decade.

Our ERLs do not map perfectly onto NASA’s TRLs, and we should not expect them to; there are many differences between behavioural and rocket science. In the social and behavioural sciences we think this process should start with defining problem(s) in collaboration with the stakeholders most likely to implement the interventions (ERL1). These concepts can then be further developed in consultation with people in the target settings to gather preliminary information about how settings or context might alter processes (ERL2). From there, researchers can conduct systematic reviews and other meta-syntheses to select evidence that could potentially be applied (ERL3). These systematic reviews require a number of bias-detection techniques. It is well-known that the behavioural sciences suffer from publication bias and other practices that compromise the integrity of research evidence. Some findings may be reliable, but the onus is on us to identify which are and which are not and which generalize or don’t. Yet, these systematic reviews must still be done with an awareness that the currently available statistical techniques do not completely correct for bias and that the resultant findings are at most at ERL3.

Following this, one can gather information about stimulus and measurement validity and equivalence for application in the target setting (ERL4). Next, researchers—in consultation with local experts—should consider the potential benefits and harms associated with applying potential solutions (ERL5) and generate estimates of effects in a pilot sample (ERL6). With preliminary effects in hand, the team can then begin to test for heterogeneity in low-stakes (ERL7) and higher-stakes (ERL8) samples and settings, which would build the confidence necessary to apply the findings in the real target setting or crisis situation (ERL9).

Even at ERL9, evidence evaluation continues; applications of social and behavioural work, particularly in a crisis, should be iterative, so high-quality evidence is fed back to evaluate the effectiveness of the intervention and to develop critical and flexible improvements. Feedback should be grounded in collaboration between basic and applied researchers, as well as with stakeholders, to ensure that the resulting evidence is relevant and actionable. Failure to continually re-evaluate interventions in light of new data could lead to unnecessary harm, where even the best evidence was inadequate to predict the intervention’s real-world effects.

A benchmarking system such as the ERL requires us to think carefully about the nature of our research that can be applied credibly and guides where research investments should be made. For example, we can better recognise that our goal of gathering reliable insights (ERL3) provides a necessary foundation for further collective efforts that scaffold towards scalable and generalizable interventions (ERL7). Engaging community experts, identifying relevant theories, and collecting extensive observations are key to framing challenges and working with interdisciplinary teams to address them (ERL1). Behavioural scientists from different cultures then discuss how interventions may need to differ in nature across context and cultures. The multidisciplinary and multi-stakeholder nature of ERLs requires us to fundamentally rethink how we produce, and communicate confidence in, application-ready findings.

The current crisis provides a chance for social and behavioural scientists to question how we understand and communicate the value of our scientific models in terms of ERLs. It also requires us to communicate those ERLs to policy-makers so that they know whether we are making educated guesses (ERL3 or below) or can be confident about the application of our findings because we have tested and replicated them in representative environments (ERL7). When providing policy advice on the basis of scientific evidence, it is important to understand and be able to explain whether and how recommendations would impact affected individuals under a range of circumstances that are highly relevant to the crisis in question (ERL7).

Even if findings are at ERL3 after assessing evidence quality of primary studies, we have little way of knowing how much positive, or unintended negative, consequences an intervention might have when applied to a new situation. We are concerned to see social and behavioural scientists making confident claims about the utility of scientific findings for solving COVID-19 problems without regard for whether those findings are based on the kind of scientific methods that would move them up the ERL ladder 1 . The absence of recognised benchmarking systems makes this challenging. While it is tempting to instead qualify uncertainty by using non-committal language about the possible utility of existing findings (for example, ‘may’, ‘could’), this approach is fundamentally flawed because public conversations generally ignore these rhetorical caveats 8 . Scientists should actively communicate uncertainty, particularly when speaking to crises. Communicating that their ERL is only at 3 or 4 would empower policy-makers by providing clear understanding of how to weight our advice in terms of their options. Reaching a higher ERL is extremely complicated and will require radical changes in the way we conduct research, not only in response to crises.

How social and behavioural scientists can advance their ERLs

The field of genetics started in a position similar to the position that many behavioural sciences find themselves in now, with small, independently collected samples that produced unreliable findings. Attempts to identify candidate genes for many constructs of interest kept stalling at TRL1/ERL4. In one prominent example, 52 patients provided genetic material for an analysis of the relationship between the 5-HTT gene and major depression 9 , a finding that spurred enormous interest in the biological mechanisms underlying depression. Unfortunately, as with the current situation in psychology, these early results were contradicted by failed replication studies 10 .

Technological advances in genotyping unlocked different approaches for geneticists. Instead of working in isolated teams, geneticists pooled resources via consortium studies and thereby accelerated scientific progress and quality. Their recent studies (with samples that sometimes exceed 1,000,000) dwarf previous candidate gene studies in terms of sample size 11 . To accomplish this, geneticists devoted considerable time to developing research workflows, data harmonization systems and processes that increased the accuracy of their measurements. The new methodologies are not without flaws: for example, there is substantial scope for expanding the representativeness of study cohorts. But the progress that consortium research in genetics has made in a short time is impressive.

In recent years we have observed similar progress in the psychological sciences going from single, small-sample studies to large-scale replications 12 , 13 and novel studies 14 to the building of the prerequisite infrastructure to facilitate team science. One example is the Psychological Science Accelerator (PSA), a large standing network with experts facilitating study selection, data management, ethics and translation 15 . While the PSA is making important progress, problems surrounding measurement validity, sample generalizability and organizational diversity (40% of its leadership is from North America), which affect the network’s ability to accurately interpret findings, still present material challenges to the applicability of their projects. Therefore, the PSA will require substantial improvement and investment before it can generate practical ERL7-level evidence and further develop our proposed framework.

The COVID-19 crisis underscores the critical need to bring the social and behavioural sciences in line with other mature sciences. Diverse consortia of researchers with expertise in philosophy, ethics, statistics and data and code management are needed to produce the kind of research required to better understand people the world over. Realising this mature, inclusive and efficient model necessitates a shift in the knowledge production and evaluation models that guide the social and behavioural sciences.

Be cautious when applying social and behavioural science to policy

On balance, we hold the view that the social and behavioural sciences have the potential to help us better understand our world. However, we are less sanguine about whether many areas of social and behavioural sciences are mature enough to provide such understanding, particularly when considering life-and-death issues like a pandemic. We believe that, rather than appealing to policy-makers to recognise our value, we should focus on earning the credibility that legitimates a seat at the policy table. The ERL taxonomy is a sample roadmap for achieving this level of maturity as a science and for accurately and honestly communicating our current state of evidence. Collaborations among large and diverse teams with local knowledge and multidisciplinary expertise can help us move up the evidence ladder. Equally important, studies in the behavioural sciences must be designed to move up this ladder incrementally. Designing an ERL6 study that is built on a shaky ERL1 foundation will be of little use. Moving up requires investment, thought and, most important of all, epistemic humility. Without a systematic and iterative research framework, we believe that behavioural scientists should carefully consider whether well-intentioned advice may do more harm than good.

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Acknowledgements

The preparation of this work was partly funded by a French National Research Agency “Investissements d’avenir” program grant (ANR-15-IDEX-02) awarded to H.I., a Huo Family Foundation grant to A.K.P., an ERC 647910 (KINSHIP) grant awarded to L.D., and an ERC 851890 (SOAR) grant awarded to N.W. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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These authors contributed equally: Hans IJzerman, Neil A. Lewis Jr., Andrew K. Przybylski.

Authors and Affiliations

LIP/PC2S, Université Grenoble Alpes, Grenoble, France

Hans IJzerman & Patrick S. Forscher

Institut Universitaire de France, Paris, France

Hans IJzerman

Department of Communication, Cornell University, Ithaca, NY, USA

Neil A. Lewis Jr.

Oxford Internet Institute and Department of Experimental Psychology, University of Oxford, Oxford, UK

Andrew K. Przybylski

School of Psychology and Clincal Language Sciences, University of Reading, Reading, UK

Netta Weinstein

Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK

Lisa DeBruine

Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK

Stuart J. Ritchie

Department of Psychology, University of California, Davis, Davis, CA, USA

Simine Vazire

Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia

School of Psychology, Cardiff University, Cardiff, UK

Richard D. Morey

Department of Communication, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

James D. Ivory

Department of Marketing and Management, University of Southern Denmark, Odense, Denmark

Farid Anvari

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Correspondence to Hans IJzerman .

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P.S.F., H.I. and N.A.L. are on the board of directors of the Psychological Science Accelerator network referenced in the manuscript. The remaining authors declare no competing interests.

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IJzerman, H., Lewis, N.A., Przybylski, A.K. et al. Use caution when applying behavioural science to policy. Nat Hum Behav 4 , 1092–1094 (2020). https://doi.org/10.1038/s41562-020-00990-w

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