research behavior problems

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 27 January 2022

The future of human behaviour research

• Janet M. Box-Steffensmeier 1 ,
• Jean Burgess 2 , 3 ,
• Maurizio Corbetta 4 , 5 ,
• Kate Crawford 6 , 7 , 8 ,
• Esther Duflo 9 ,
• Laurel Fogarty 10 ,
• Alison Gopnik 11 ,
• Sari Hanafi 12 ,
• Mario Herrero 13 ,
• Ying-yi Hong 14 ,
• Yasuko Kameyama 15 ,
• Tatia M. C. Lee 16 ,
• Gabriel M. Leung 17 , 18 ,
• Daniel S. Nagin 19 ,
• Anna C. Nobre 20 , 21 ,
• Merete Nordentoft 22 , 23 ,
• Aysu Okbay 24 ,
• Andrew Perfors 25 ,
• Laura M. Rival 26 ,
• Cassidy R. Sugimoto 27 ,
• Bertil Tungodden 28 &
• Claudia Wagner 29 , 30 , 31  

Nature Human Behaviour volume  6 ,  pages 15–24 ( 2022 ) Cite this article

60k Accesses

26 Citations

184 Altmetric

Metrics details

Human behaviour is complex and multifaceted, and is studied by a broad range of disciplines across the social and natural sciences. To mark our 5th anniversary, we asked leading scientists in some of the key disciplines that we cover to share their vision of the future of research in their disciplines. Our contributors underscore how important it is to broaden the scope of their disciplines to increase ecological validity and diversity of representation, in order to address pressing societal challenges that range from new technologies, modes of interaction and sociopolitical upheaval to disease, poverty, hunger, inequality and climate change. Taken together, these contributions highlight how achieving progress in each discipline will require incorporating insights and methods from others, breaking down disciplinary silos.

Genuine progress in understanding human behaviour can only be achieved through a multidisciplinary community effort. Five years after the launch of Nature Human Behaviour , twenty-two leading experts in some of the core disciplines within the journal’s scope share their views on pressing open questions and new directions in their disciplines. Their visions provide rich insight into the future of research on human behaviour.

Artificial intelligence

Kate Crawford

Much has changed in artificial intelligence since a small group of mathematicians and scientists gathered at Dartmouth in 1956 to brainstorm how machines could simulate cognition. Many of the domains that those men discussed — such as neural networks and natural language processing — remain core elements of the field today. But what they did not address was the far-reaching social, political, legal and ecological effects of building these systems into everyday life: it was outside their disciplinary view.

Since the mid-2000s, artificial intelligence (AI) has rapidly expanded as a field in academia and as an industry, and now a handful of powerful technology corporations deploy these systems at a planetary scale. There have been extraordinary technical innovations, from real-time language translation to predicting the 3D structures of proteins 1 , 2 . But the biggest challenges remain fundamentally social and political: how AI is widening power asymmetries and wealth inequality, and creating forms of harm that need to be prioritized, remedied and regulated.

The most urgent work facing the field today is to research and remediate the costs and consequences of AI. This requires a deeper sociotechnical approach that can contend with the complex effect of AI on societies and ecologies. Although there has been important work done on algorithmic fairness in recent years 3 , 4 , not enough has been done to address how training data fundamentally skew how AI models interpret the world from the outset. Second, we need to address the human costs of AI, which range from discrimination and misinformation to the widespread reliance on underpaid labourers (such as the crowd-workers who train AI systems for as little as US $2 per hour) 5 . Third, there must be a commitment to reversing the environmental costs of AI, including the exceptionally high energy consumption of the current large computational models, and the carbon footprint of building and operating modern tensor processing hardware 6 . Finally, we need strong regulatory and policy frameworks, expanding on the EU’s draft AI Act of 2021.

By building a more interdisciplinary and inclusive AI field, and developing a more rigorous account of the full impacts of AI, we give engineers and regulators alike the tools that they need to make these systems more sustainable, equitable and just.

Kate Crawford is Research Professor at the Annenberg School, University of Southern California, Los Angeles, CA, USA; Senior Principal Researcher at Microsoft Research New York, New York, NY, USA; and the Inaugural Visiting Chair of AI and Justice at the École Normale Supérieure, Paris, France.

Anthropology

Laura M. Rival

The field of anthropology faces fundamental questions about its capacity to intervene more effectively in political debates. How can we use the knowledge that we already have to heal the imagined whole while keeping people in synchrony with each other and with the world they aspire to create for themselves and others?

The economic systems that sustain modern life have produced pernicious waste cultures. Globalization has accelerated planetary degradation and global warming through the continuous release of toxic waste. Every day, like millions of others, I dutifully clean and prepare my waste for recycling. I know it is no more than a transitory measure geared to grant manufacturers time to adjust and adapt. Reports that most waste will not be recycled, but dumped or burned, upset me deeply. How can anthropology remain a critical project in the face of such orchestrated cynicism, bad faith and indifference? How should anthropologists deploy their skills and bring a sense of shared responsibility to the task of replenishing the collective will?

To help to find answers to these questions, anthropologists need to radically rethink the ways in which we describe the processes and relations that tie communities to their environments. The extinction of experience (loss of direct contact with nature) that humankind currently suffers is massive, but not irreversible. New forms of storytelling have successfully challenged modernist myths, particularly their homophonic promises 7 . But there remain persistent challenges, such as the seductive and rampant power of one-size-fits-all progress, and the actions of elites, who thrive on emulation, and in doing so fuel run-away consumerism.

To combat these challenges, I simply reassert that ‘nature’ is far from having outlasted its historical utility. Anthropologists must join forces and reanimate their common exploration of the immense possibilities contained in human bodies and minds. No matter how overlooked or marginalized, these natural potentials hold the key to what keeps life going.

Laura M. Rival is Professor of Anthropology of Nature, Society and Development, ODID and SAME, University of Oxford, Oxford, UK .

Communication and media studies

Jean Burgess

The communication and media studies field has historically been animated by technological change. In the process, it has needed to navigate fundamental tensions: communication can be understood as both transmission (of information), and as (social) ritual 8 ; relatedly, media can be understood as both technology and as culture 9 .

The most important technological change over the past decade has been the ‘platformization’ 10 of the media environment. Large digital platforms owned by the world’s most powerful technology companies have come to have an outsized and transformative role in the transmission (distribution) of information, and in mediating social practices (whether major events or intimate daily routines). In response, digital methods have transformed the field. For example, advances in computational techniques enabled researchers to study patterns of communication on social media, leading to disciplinary trends such as the quantitative description of ‘hashtag publics’ in the mid-2010s 11 .

Platforms’ uses of data, algorithms and automation for personalization, content moderation and governance constitute a further major shift, giving rise to new methods (such as algorithmic audits) that go well beyond quantitative description 12 . But platform companies have had a patchy — at times hostile — relationship to independent research into their societal role, leading to data lockouts and even public attacks on researchers. It is important in the interests of public oversight and open science that we coordinate responses to such attempts to suppress research 13 , 14 .

As these processes of digital transformation continue, new connections between the humanities and technical disciplines will be necessary, giving rise to a new wave of methodological innovation. This next phase will also require more hybrid (qualitative and quantitative; computational and critical) methods 15 , not only to get around platform lockouts but also to ensure more careful attention is paid to how the new media technologies are used and experienced in everyday life. Here, innovative approaches such as the use of data donations can both aid the ‘platform observability’ 16 that is essential to accountability, and ensure that our research involves the perspectives of diverse audiences.

Jean Burgess is Professor of Digital Media at the School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland Australia; and Associate Director at the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia .

Computational social science

Claudia Wagner

Computational social science has emerged as a discipline that leverages computational methods and new technologies to collect, model and analyse digital behavioural data in natural environments or in large-scale designed experiments, and combine them with other data sources (such as survey data).

While the community made critical progress in enhancing our understanding about empirical phenomena such as the spread of misinformation 17 and the role of algorithms in curating misinformation 18 , it has focused less on questions about the quality and accessibility of data, the validity, reliability and reusability of measurements, the potential consequences of measurements and the connection between data, measurement and theory.

I see the following opportunities to address these issues.

First, we need to establish privacy-preserving, shared data infrastructures that collect and triangulate survey data with scientifically motivated organic or designed observational data from diverse populations 19 . For example, longitudinal online panels in which participants allow researchers to track their web browsing behaviour and link these traces to their survey answers will not only facilitate substantive research on societal questions but also enable methodological research (for example, on the quality of different data sources and measurement models), and contribute to the reproducibility of computational social science research.

Second, best practices and scientific infrastructures are needed for supporting the development, evaluation and re-use of measurements and the critical reflection on potentially harmful consequences of measurements 20 . Social scientists have developed such best practices and infrastructural support for survey measurements to avoid using instruments for which the validity is unclear or even questionable, and to support the re-usability of survey scales. I believe that practices from survey methodology and other domains, such as the medical industry, can inform our thinking here.

Finally, the fusion of algorithmic and human behaviour invites us to rethink the various ways in which data, measurements and social theories can be connected 20 . For example, product recommendations that users receive are based on measurements of users’ interests and needs: however, users and measurements are not only influenced by those recommendations, but also influence them in turn. As a community we need to develop research designs and environments that help us to systematically enhance our understanding of those feedback loops.

Claudia Wagner is Head of Computational Social Science Department at GESIS – Leibniz Institute for the Social Sciences, Köln, Germany; Professor for Applied Computational Social Sciences at RWTH Aachen University, Aachen, Germany; and External Faculty Member of the Complexity Science Hub, Vienna, Austria .

Criminology

Daniel S. Nagin

Disciplinary silos in path-breaking science are disappearing. Criminology has had a longstanding tradition of interdisciplinarity, but mostly in the form of an uneasy truce of research from different disciplines appearing side-by-side in leading journals — a scholarly form of parallel play. In the future, this must change because the big unsolved challenges in criminology will require cooperation among all of the social and behavioural sciences.

These challenges include formally merging the macro-level themes emphasized by sociologists with the micro-, individual-level themes emphasized by psychologists and economists. Initial steps have been made by economists who apply game theory to model crime-relevant social interactions, but much remains to be done in building models that explain the formation and destruction of social trust, collective efficacy and norms, as they relate to legal definitions of criminal behaviour.

A second opportunity concerns the longstanding focus of criminology on crimes involving the physical taking of property and interpersonal physical violence. These crimes are still with us, but — as the daily news regularly reports — the internet has opened up broad new frontiers for crime that allow for thefts of property and identities at a distance, forms of extortion and human trafficking at a massive scale (often involving untraceable transactions using financial vehicles such as bitcoin) and interpersonal violence without physical contact. This is a new and largely unexplored frontier for criminological research that criminologists should dive into in collaboration with computer scientists who already are beginning to troll these virgin scholarly waters.

The final opportunity I will note also involves drawing from computer science, the primary home of what has come to be called machine learning. It is important that new generations of criminologists become proficient with machine learning methods and also collaborate with its creators. Machine learning and related statistical methods have wide applicability in both the traditional domains of criminological research and new frontiers. These include the use of prediction tools in criminal justice decision-making, which can aid in crime detection, and the prevention and measuring of crime both online and offline, but also have important implications for equity and fairness due to their consequential nature.

Daniel S. Nagin is Teresa and H. John Heinz III University Professor of Public Policy and Statistics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA .

Behavioural economics

Bertil Tungodden

Behavioural and experimental economics have transformed the field of economics by integrating irrationality and nonselfish motivation in the study of human behaviour and social interaction. A richer foundation of human behaviour has opened many new exciting research avenues, and I here highlight three that I find particularly promising.

Economists have typically assumed that preferences are fixed and stable, but a growing literature, combining field and laboratory experimental approaches, has provided novel evidence on how the social environment shapes our moral and selfish preferences. It has been shown that prosocial role models make people less selfish 21 , that early-childhood education affects the fairness views of children 22 and that grit can be fostered in the correct classroom environment 23 . Such insights are important for understanding how exposure to different institutions and socialization processes influence the intergenerational transmission of preferences, but much more work is needed to gain systematic and robust evidence on the malleability of the many dimensions that shape human behaviour.

The moral mind is an important determinant of human behaviour, but our understanding of the complexity of moral motivation is still in its infancy. A growing literature, using an impartial spectator design in which study participants make consequential choices for others, has shown that people often disagree on what is morally acceptable. An important example is how people differ in their view of what is a fair inequality, ranging from the libertarian fairness view to the strict egalitarian fairness view 24 , 25 . An exciting question for future research is whether such moral differences reflect a concern for other moral values, such as freedom, or irrational considerations.

A third exciting development in behavioural and experimental economics is the growing set of global studies on the foundations of human behaviour 26 , 27 . It speaks to the major concern in the social sciences that our evidence is unrepresentative and largely based on studies with samples from Western, educated, industrialized, rich and democratic societies 28 . The increased availability of infrastructure for implementing large-scale experimental data collections and methodological advances carry promise that behavioural and experimental economic research will broaden our understanding of the foundations of human behaviour in the coming years.

Bertil Tungodden is Professor and Scientific Director of the Centre of Excellence FAIR at NHH Norwegian School of Economics, Bergen, Norway .

Development economics

Esther Duflo

The past three decades have been a wonderful time for development economics. The number of scholars, the number of publications and the visibility of the work has dramatically increased. Development economists think about education, health, firm growth, mental health, climate, democratic rules and much more. No topic seems off limits!

This progress is intimately connected with the explosion of the use of randomized controlled trials (RCTs) and, more generally, with the embrace of careful causal identification. RCTs have markedly transformed development economics and made it the field that it is today.

The past three decades (until the COVID-19 crisis) have also been very good for improving the circumstances of low-income people around the world: poverty rates have fallen; school enrolment has increased; and maternal and infant mortality has been halved. Although I would not dare imply that the two trends are causally related, one of the reasons for these improvements in the quality of life — even in countries where economic growth has been slow — is the greater focus on pragmatic solutions to the fundamental problems faced by people with few resources. In many countries, development economics researchers (particularly those working with RCTs) have been closely involved with policy-makers, helping them to develop, implement and test these solutions. In turn, this involvement has been a fertile ground for new questions, which have enriched the field.

I imagine future change will, once again, come from an unexpected place. One possible driver of innovation will come from this meeting between the requirements of policy and the intellectual ambition of researchers. This means that the new challenges of our planet must (and will) become the new challenges of development economics. Those challenges are, I believe, quite clear: rethinking social protection to be better prepared to face risks such as the COVID-19 pandemic; mitigating, but unfortunately also adapting to, climate changes; curbing pollution; and addressing gender, racial and ethnic inequality.

To address these critical issues, I believe the field will continue to rely on RCTs, but also start using more creatively (descriptively or in combination with RCTs) the huge amount of data that is increasingly available as governments, even in poor countries, digitize their operations. I cannot wait to be surprised by what comes next.

Esther Duflo is The Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Department of Economics, Massachusetts Institute of Technology, Cambridge MA, USA; and cofounder and codirector of the Abdul Latif Jameel Poverty Action Lab (J-PAL) .

Political science

Janet M. Box-Steffensmeier

Political science remains one of the most pluralistic disciplines and we are on the move towards engaged pluralism. This takes us beyond mere tolerance to true, sincere engagement across methods, methodologies, theories and even disciplinary boundaries. Engaged pluralism means doing the hard work of understanding our own research from the multiple perspectives of others.

More data are being collected on human behaviour than ever before and our advances in methods better address the inherent interdependencies of the data across time, space and context. There are new ways to measure human behaviour via text, image and video. Data creation can even go back in time. All these advancements bode well for the potential to better understand and predict behaviour. This ‘data century’ and ‘golden age of methods’ also hold the promise to bridge, not divide, political science, provided that there is engaged methodological pluralism. Qualitative methods provide unique insights and perspectives when joined with quantitative methods, as does a broader conception of the methodologies underlying and launching our research.

I remain a strong proponent of leveraging dynamics and focusing on heterogeneity in our research questions to advance our disciplines. Doing so brings in an explicit perspective of comparison around similarity and difference. Our questions, hypotheses and theories are often made more compelling when considering the dynamics and heterogeneity that emerges when thinking about time and change.

Striving for a better understanding of gender, race and ethnicity is driving deeper and fuller understandings of central questions in the social sciences. The diversity of the research teams themselves across gender, sex, race, ethnicity, first-generation status, religion, ideology, partisanship and cultures also pushes advancement. One area that we need to better support is career diversity. Supporting careers in government, non-profit organizations and industry, as well as academia, for graduate students will enhance our disciplines and accelerate the production of knowledge that changes the world.

Engaged pluralism remains a foundational key to advancement in political science. Engaged pluralism supports critical diversity, equity and inclusion work, strengthens political scientists’ commitment to democratic principles, and encourages civic engagement more broadly. It is an exciting time to be a social scientist.

Janet M. Box-Steffensmeier is Vernal Riffe Professor of Political Science, Professor of Sociology (courtesy) and Distinguished University Professor at the Department of Political Science, Ohio State University, Columbus OH, USA; and immediate past President of the American Political Science Association .

Cognitive psychology

Andrew Perfors

Cognitive psychology excels at understanding questions whose problem-space is well-defined, with precisely specified theories that transparently map onto thoroughly explored experimental paradigms. That means there is a vast gulf between the current state of the art and the richness and complexity of cognition in the real world. The most exciting open questions are about how to bridge that gap without sacrificing rigour and precision. This requires at least three changes.

First, we must move beyond typical experiments. Stimuli must become less artificial, with a naturalistic structure and distribution. Similarly, tasks must become more ecologically valid: less isolated, with more uncertainty, embedded in natural situations and over different time-scales.

Second, we must move beyond considering individuals in isolation. We live in a rich social world and an environment that is heavily shaped by other humans. How we think, learn and act is deeply affected by how other people think and interact with us; cognitive science needs to engage with this more.

Third, we must move beyond the metaphor of humans as computers. Our cognition is deeply intertwined with our emotions, motivations and senses. These are more than just parameters in our minds; they have a complexity and logic of their own, and interact in nontrivial ways with each other and more typical cognitive domains such as learning, reasoning and acting.

How do we make progress on these steps? We need reliable real-world data that are comparable across people and situations, reflect the cognitive processes involved and are not changed by measurement. Technology may help us with this, but challenges surrounding privacy and data quality are huge. Our models and analytic approaches must also grow in complexity — commensurate with the growth in problem and data complexity — without becoming intractable or losing their explanatory power.

Success in this endeavour calls for a different kind of science that is not centred around individual laboratories or small stand-alone projects. The biggest advances will be achieved on the basis of large, rich, real-world datasets from different populations, created and analysed in collaborative teams that span multiple domains, fields and approaches. This requires incentive structures that reward team-focused, slower science and prioritize the systematic construction of reliable knowledge over splashy findings.

Andrew Perfors is Associate Professor and Deputy Director of the Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia .

Cultural and social psychology

Ying-yi Hong

I am writing this at an exceptional moment in human history. For two years, the world has faced the COVID-19 pandemic and there is no end in sight. Cultural and social psychology are uniquely equipped to understand the COVID-19 pandemic, specifically examining how people, communities and countries are dealing with this extreme global crisis — especially at a time when many parts of the world are already experiencing geopolitical upheaval.

During the pandemic, and across different nations and regions, a diverse set of strategies (and subsequent levels of effectiveness) were used to curb the spread of the disease. In the first year of the pandemic, research revealed that some cultural worldviews — such as collectivism (versus individualism) and tight (versus loose) norms — were positively associated with compliance with COVID-19 preventive measures as well as with fewer infections and deaths 29 , 30 . These worldview differences arguably stem from different perspectives on abiding to social norms and prioritizing the collective welfare over an individual’s autonomy and liberty. Although in the short term it seems that a collectivist or tight worldview has been advantageous, it is unclear whether this will remain the case in the long term. Cultural worldviews are ‘tools’ that individuals use to decipher the meaning of their environment, and are dynamic rather than static 31 . Future research can examine how cultural worldviews and global threats co-evolve.

The pandemic has also amplified the demarcation of national, political and other major social categories. On the one hand, identification with some groups (for example, national identity) was found to increase in-group care and thus a greater willingness to sacrifice personal autonomy to comply with COVID-19 measures 32 . On the other hand, identification with other groups (for example, political parties) widened the ideological divide between groups and drove opposing behaviours towards COVID-19 measures and health outcomes 33 . As we are facing climate change and other pressing global challenges, understanding the role of social identities and how they affect worldviews, cognition and behaviour will be vital. How can we foster more inclusive (versus exclusive) identities that can unite rather than divide people and nations?

Ying-yi Hong is Choh-Ming Li Professor of Management and Associate Dean (Research) at the Department of Management, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China .

Developmental psychology

Alison Gopnik

Developmental psychology is similar to the kind of book or band that, paradoxically, everyone agrees is underrated. On the one hand, children and the people who care for them are often undervalued and overlooked. On the other, since Piaget, developmental research has tackled some of the most profound philosophical questions about every kind of human behaviour. This will only continue into the future.

Psychologists increasingly recognize that the minds of children are not just a waystation or an incomplete version of adult minds. Instead, childhood is a distinct evolutionarily adaptive phase of an organism, with its own characteristic cognitions, emotions and motivations. These characteristics of childhood reflect a different agenda than those of the adult mind — a drive to explore rather than exploit. This drive comes with motivations such as curiosity, emotions such as wonder and surprise and remarkable cognitive learning capacities. A new flood of research on curiosity, for example, shows that children actively seek out the information that will help them to learn the most.

The example of curiosity also reflects the exciting prospects for interdisciplinary developmental science. Machine learning is increasingly using children’s learning as a model, and developmental psychologists are developing more precise models as a result. Curiosity-based AI can illuminate both human and machine intelligence. Collaborations with biology are also exciting: for example, in work on evolutionary ‘life history’ explanations of the effects of adverse experiences on later life, and new research on plasticity and sensitive periods in neuroscience. Finally, children are at the cutting edge of culture, and developmental psychologists increasingly conduct a much wider range of cross-cultural studies.

But perhaps the most important development is that policy-makers are finally starting to realize just how crucial children are to important social issues. Developmental science has shown that providing children with the care that they need can decrease poverty, inequality, disease and violence. But that care has been largely invisible to policy-makers and politicians. Understanding scientifically how caregiving works and how to support it more effectively will be the most important challenge for developmental psychology in the next century.

Alison Gopnik is Professor of Psychology and Affiliate Professor of Philosophy at the Department of Psychology, University of California at Berkeley, Berkeley, CA, USA .

Science of science

Cassidy R. Sugimoto

Why study science? The goal of science is to advance knowledge to improve the human condition. It is, therefore, essential that we understand how science operates to maximize efficiency and social good. The metasciences are fields that are devoted to understanding the scientific enterprise. These fields are distinguished by differing epistemologies embedded in their names: the philosophy, history and sociology of science represent canonical metasciences that use theories and methods from their mother disciplines. The ‘science of science’ uses empirical approaches to understand the mechanisms of science. As mid-twentieth-century science historian Derek de Solla Price observed, science of science allows us to “turn the tools of science on science itself” 34 .

Contemporary questions in the science of science investigate, inter alia, catalysts of discovery and innovation, consequences of increased access to scientific information, role of teams in knowledge creation and the implications of social stratification on the scientific enterprise. Investigation of these issues require triangulation of data and integration across the metasciences, to generate robust theories, model on valid assumptions and interpret results appropriately. Community-owned infrastructure and collective venues for communication are essential to achieve these goals. The construction of large-scale science observatories, for example, would provide an opportunity to capture the rapidly expanding dataverse, collaborate and share data, and provide nimble translations of data into information for policy-makers and the scientific community.

The topical foci of the field are also undergoing rapid transformation. The expansion of datasets enables researchers to analyse a fuller population, rather than a narrow sample that favours particular communities. The field has moved from an elitist focus on ‘success’ and ‘impact’ to a more-inclusive and prosopographical perspective. Conversations have shifted from citations, impact factors and h -indices towards responsible indicators, diversity and broader impacts. Instead of asking ‘how can we predict the next Nobel prize winner?’, we can ask ‘what are the consequences of attrition in the scientific workforce?’. The turn towards contextualized measurements that use more inclusive datasets to understand the entire system of science places the science of science in a ripe position to inform policy and propel us towards a more innovative and equitable future.

Cassidy R. Sugimoto is Professor and Tom and Marie Patton School Chair, School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA .

Sari Hanafi

In the past few years, we have been living through times in which reasonable debate has become impossible. Demagogical times are driven by the vertiginous rise of populism and authoritarianism, which we saw in the triumph of Donald Trump in the USA and numerous other populist or authoritarian leaders in many places around the globe. There are some pressing tasks for sociology that can be, in brief, reduced to three.

First, fostering democracy and the democratization process requires disentangling the constitutive values that compose the liberal political project (personal liberty, equality, moral autonomy and multiculturalism) to address the question of social justice and to accommodate the surge in people’s religiosity in many parts in the globe.

Second, the struggle for the environment is inseparable from our choice of political economy, and from the nature of our desired economic system — and these connections between human beings and nature have never been as intimate as they are now. Past decades saw rapid growth that was based on assumptions of the long-term stability of the fixed costs of raw materials and energy. But this is no longer the case. More recently, financial speculation intensified and profits shrunk, generating distributional conflicts between workers, management, owners and tax authorities. The nature of our economic system is now in acute crisis.

The answer lies in a consciously slow-growing new economy that incorporates the biophysical foundations of economics into its functioning mechanisms. Society and nature cannot continue to be perceived each as differentiated into separate compartments. The spheres of nature, culture, politics, social, economy and religion are indeed traversed by common logics that allow a given society to be encompassed in its totality, exactly as Marcel Mauss 35 did. The logic of power and interests embodied in ‘ Homo economicus ’ prevents us from being able to see the potentiality of human beings to cultivate gift-giving practices as an anthropological foundation innate within social relationships.

Third, there are serious social effects of digitalized forms of labour and the trend of replacing labour with an automaton. Even if digital labour partially reduces the unemployment rate, the lack of social protection for digital labourers would have tremendous effects on future generations.

In brief, it is time to connect sociology to moral and political philosophy to address fundamentally post-COVID-19 challenges.

Sari Hanafi is Professor of Sociology at the American University of Beirut, Beirut, Lebanon; and President of the International Sociological Association .

Environmental studies (climate change)

Yasuko Kameyama

Climate change has been discussed for more than 40 years as a multilateral issue that poses a great threat to humankind and ecosystems. Unfortunately, we are still talking about the same issue today. Why can’t we solve this problem, even though scientists pointed out its importance and urgency so many years ago?

These past years have been spent trying to prove the causal relationship between an increase in greenhouse gas concentrations, global temperature rise and various extreme weather events, as well as developing and disseminating technologies needed to reduce emissions. All of these tasks have been handled by experts in the field. At the same time, the general public invested little time in this movement, probably expecting that the problem would be solved by experts and policy-makers. But that has not been the case. No matter how much scientists have emphasized the crisis of climate change or how many clean energy technologies engineers have developed, society has resisted making the necessary changes. Now, the chances of keeping the temperature rise within 1.5 °C of pre-industrial levels — the goal necessary to minimize the effects of climate change — are diminishing.

We seem to finally be realizing the importance of social scientific knowledge. People need to take scientific information seriously for clean technology to be quickly diffused. Companies are more interested in investing in newer technology and product development when they know that their products will sell. Because environmental problems are caused by human activity, research on human behaviour is indispensable in solving these problems.

Reports by the Intergovernmental Panel on Climate Change (IPCC) have not devoted many pages to the areas of human awareness and behaviour ( https://www.ipcc.ch/ ). The IPCC’s Third Working Group, which deals with mitigation measures, has partially spotlighted research on institutions, as well as on concepts such as fairness. People’s perception of climate change and the relationship between perception and behavioural change differ depending on the country, societal structure and culture. Additional studies in these areas are required and, for that purpose, more studies from regions such as Asia, Africa and South America, which are underrepresented in terms of the number of academic publications, are particularly needed.

Yasuko Kameyama is Director, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan .

Sustainability (food systems)

Mario Herrero

The food system is in dire straits. Food demand is unprecedented, while malnutrition in all its forms (obesity, undernutrition and micronutrient deficiencies) is rampant. Environmental degradation is pervasive and increasing, and if it continues, the comfort zone for humanity and ecosystems to thrive will be seriously compromised. From bruises and shapes to sell-by dates, we tend to find many reasons to exclude perfectly edible food from our plates, whereas in other cases not enough food reaches hungry mouths owing to farming methods, pests and lack of adequate storage. These types of inequalities are common and — together with inherent perverse incentives that maintain the status quo of how we produce, consume and waste increasingly cheap and processed food — they are launching us towards a disaster.

We are banking on a substantial transformation of the food system to solve this conundrum. Modifying food consumption and waste patterns are central to the plan for achieving healthier diets, while increasing the sustainability of our food system. This is also an attractive policy proposition, as it could lead to gains in several sectors. Noncommunicable diseases such as obesity, diabetes and heart disease could decline, while reducing the effects of climate change, deforestation, excessive water withdrawals and biodiversity loss, and their enormous associated — and largely unaccounted — costs.

Modifying our food consumption and waste patterns is very hard, and unfortunately we know very little about how to change them at scale. Yes, many pilots and small examples exist on pricing, procurement, food environments and others, but the evidence is scarce, and the magnitude of the change required demands an unprecedented transdisciplinary research agenda. The problem is at the centre of human agency and behaviour, embodying culture, habits, values, social status, economics and all aspects of agri-food systems. Certainly, one of the big research areas for the next decade if we are to reach the Sustainable Development Goals leaving no one behind.

Mario Herrero is Professor, Cornell Atkinson scholar and Nancy and Peter Meinig Family Investigator in the Life Sciences at the Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA .

Cultural evolution

Laurel Fogarty

Humans are the ultimate ‘cultural animals’. We are innovative, pass our cultures to one another across generations and build vast self-constructed environments that reflect our cultural biases. We achieve things using our cultural capacities that are unimaginable for any other species on earth. And yet we have only begun to understand the dynamics of cultural change, the drivers of cultural complexity or the ways that we adapt culturally to changing environments. Scholars — anthropologists, archaeologists and sociologists — have long studied culture, aiming to describe and understand its staggering diversity. The relatively new field of cultural evolution has different aims, one of the most important of which is to understand the mechanics in the background — what general principles, if any, govern human cultural change?

Although the analogy of culture as an evolutionary process has been made since at least the time of Darwin 36 , 37 , cultural evolution as a robust field of study is much younger. From its beginnings with the pioneering work of Cavalli-Sforza & Feldman 38 , 39 , 40 and Boyd & Richerson 41 , 42 , the field of cultural evolution has been heavily theoretical. It has drawn on models from genetic evolution 40 , 43 , 44 , 45 , ecology 46 , 47 and epidemiology 40 , 48 , extending and adapting them to account for unique and important aspects of cultural transmission. Indeed, in its short life, the field of cultural evolution has largely been dominated by a growing body of theory that ensured that the fledgling field started out on solid foundations. Because it underpins and makes possible novel applications of cultural evolutionary ideas, theoretical cultural evolution’s continued development is not only crucial to the field’s growth but also represents some of its most exciting future work.

One of the most urgent tasks for cultural evolution researchers in the next five years is to develop, alongside its theoretical foundations, robust principles of application 49 , 50 , 51 . In other words, it is vital to develop our understanding of what we can — and, crucially, cannot — infer from different types of cultural data. Where do we draw those boundaries and how can we apply cultural evolutionary theory to cultural datasets in a principled way? The tandem development of robust theory and principled application has the potential to strengthen cultural evolution as a robust, useful and ground-breaking inferential science of human behaviour.

Laurel Fogarty is Senior Scientist at the Department of Human Behaviour, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany .

Over the past decade, research using molecular genetic data has confirmed one of the main conclusions of twin studies: all human behaviour is partly heritable 52 , 53 . Attempts at examining the link between genetics and behaviour have been met with concerns that the findings can be abused to justify discrimination — and there are good historical grounds for these concerns. However, these findings also show that ignoring the contribution of genes to variation in human behaviour could be detrimental to a complete understanding of social phenomena, given the complex ways that genes and environment interact.

Uncovering these complex pathways has become feasible only recently thanks to rapid technological progress reducing the costs of genotyping. Sample sizes in genome-wide association studies (GWAS) have risen from tens of thousands to millions in the past decade, reporting thousands of genetic variants associated with different behaviours 54 , 55 , 56 , 57 . New ways to use GWAS results have emerged, the most important one arguably being a method to aggregate the additive effects of many genetic variants into a ‘polygenic index’ (PGI) (also known as a ‘polygenic score’) that summarizes an individual’s genetic propensity towards a trait or behaviour 58 , 59 . Being aggregate measures, PGIs capture a much larger share of the variance in the trait of interest compared to individual genetic variants 60 . Thus, they have paved the way for follow-up studies with smaller sample sizes but deeper phenotyping compared to the original GWAS, allowing researchers to, for example, analyse the channels through which genes operate 61 , 62 , how they interact with the environment 63 , 64 , and account for confounding bias and boost statistical power by controlling for genetic effects 65 , 66 .

Useful as they are, PGIs and the GWAS that they are based on can suffer from confounding due to environmental factors that correlate with genotypes, such as population stratification, indirect effect from relatives or assortative mating 67 . Now that the availability of genetic data enables large-scale within-family GWAS, the next big thing in behaviour genetic research will be disentangling these sources 68 . While carrying the progress further, it is important that the field prioritizes moving away from its currently predominant Eurocentric bias by extending data collection and analyses to individuals of non-European ancestries, as the exclusion of non-European ancestries from genetic research has the potential to exacerbate health disparities 69 . Researchers should also be careful to communicate their findings clearly and responsibly to the public and guard against their misappropriation by attempts to fuel discriminatory action and discourse 70 .

Aysu Okbay is Assistant Professor at the Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands .

Cognitive neuroscience

Anna C. Nobre

Since the ‘decade of the brain’ in the 1990s, ingenuity in cognitive neuroscience has focused on measuring and analysing brain signals. Adapting tools from statistics, engineering, computer science, physics and other disciplines, we studied activity, states, connectivity, interactions, time courses and dynamics in brain regions and networks. Unexpected findings about the brain yielded important insights about the mind.

Now is a propitious time to upgrade the brain–mind duumvirate to a brain–mind–behaviour triumvirate. Brain and mind are embodied, and their workings are expressed through various effectors. Yet, experimental tasks typically use simple responses to capture complex psychological functions. Often, a button press — with its limited dimensions of latency and accuracy — measures anticipating, focusing, evaluating, choosing, reflecting or remembering. Researchers venturing beyond such simple responses are uncovering how the contents of mind can be studied using various continuous measures, such as pupil diameter, gaze shifts and movement trajectories.

Most tasks also restrict participants’ movements to ensure experimental control. However, we are learning that principles of cognition derived in artificial laboratory contexts can fail to generalize to natural behaviour. Virtual reality should prove a powerful methodology. Participants can behave naturally, and experimenters can control stimulation and obtain quality measures of gaze, hand and body movements. Noninvasive neurophysiology methods are becoming increasingly portable. Exciting immersive brain–mind–behaviour studies are just ahead.

The next necessary step is out of the academic bubble. Today the richest data on human behaviour belong to the information and technology industries. In our routines, we contribute data streams through telephones, keyboards, watches, vehicles and countless smart devices in the internet of things. These expose properties such as processing speed, fluency, attention, dexterity, navigation and social context. We supplement these by broadcasting feelings, attitudes and opinions through social media and other forums. The richness and scale of the resulting big data offer unprecedented opportunities for deriving predictive patterns that are relevant to understanding human cognition (and its disorders). The outcomes can then guide further hypothesis-driven experimentation. Cognitive neuroscience is intrinsically collaborative, combining a broad spectrum of disciplines to study the mind. Its challenge now is to move from a multidisciplinary to a multi-enterprise science.

Anna C. Nobre is Chair in Translational Cognitive Neuroscience at the Department of Experimental Psychology, University of Oxford, UK; and Director of Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK .

Social and affective neuroscience

Tatia M. C. Lee

Social and affective neuroscience is a relatively new, but rapidly developing, field of neuroscience. Social and affective neuroscience research takes a multilevel approach to make sense of socioaffective processes, focusing on macro- (for example, social environments and structures), meso- (for example, social interactions) and micro (for example, socio-affective neural processes and perceptions)-level interactions. Because the products of these interactions are person-specific, the conventional application of group-averaged mechanisms to understand the brain in a socioemotional context has been reconsidered. Researchers turn to ecologically valid stimuli (for example, dynamic and virtual reality instead of static stimuli) and experimental settings (for example, real-time social interaction) 71 to address interindividual differences in social and affective responses. At the neural level, there has been a shift of research focus from local neural activations to large-scale synchronized interactions across neural networks. Network science contributes to the understanding of dynamic changes of neural processes that reflect the interactions and interconnection of neural structures that underpin social and affective processes.

We are living in an ever-changing socioaffective world, full of unexpected challenges. The ageing population and an increasing prevalence of depression are social phenomena on a global scale. Social isolation and loneliness caused by measures to tackle the current pandemic affect physical and psychological well-being of people from all walks of life. These global issues require timely research efforts to generate potential solutions. In this regard, social and affective neuroscience research using computational modelling, longitudinal research designs and multimodal data integration will create knowledge about the basis of adaptive and maladaptive social and affective neurobehavioural processes and responses 72 , 73 , 74 . Such knowledge offers important insights into the precise delineation of brain–symptom relationships, and hence the development of prediction models of cognitive and socioaffective functioning (for example, refs. 75 , 76 ). Therefore, screening tools for identifying potential vulnerabilities can be developed, and timely and precise interventions can be tailored to meet individual situations and needs. The translational application of social and affective neuroscience research to precision medicine (and policy) is experiencing unprecedented demand, and such demand is met with unprecedented clinical and research capabilities.

Tatia M. C. Lee is Chair Professor of Psychology at the State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong Special Administrative Region, China .

Maurizio Corbetta

Focal brain disorders, including stroke, trauma and epilepsy, are the main causes of disability and loss of productivity in the world, and carry a cumulative cost in Europe of about € 500 billion per year 77 . The disease process affects a specific circuit in the brain by turning it off (as in stroke) or pathologically turning it on (as in epilepsy). The cause of the disabling symptoms is typically local circuit damage. However, there is now overwhelming evidence that symptoms reflect not only local pathology but also widespread (network) functional abnormalities. For instance, in stroke, an average lesion — the size of a golf ball — typically alters the activity of on average 25% of all brain connections. Furthermore, normalization of these abnormalities correlates with optimal recovery of function 78 , 79 .

One exciting treatment opportunity is ‘circuit-based’ stimulation: an ensemble of methods (optogenetic, photoacoustic, electrochemical, magnetic and electrical) that have the potential to normalize activity. Presently, this type of therapy is limited by numerous factors, including a lack of knowledge about the circuits, the difficulty of mapping these circuits in single patients and, most importantly, a principled understanding of where and how to stimulate to produce functional recovery.

A possible solution lies in a strategy (developed with G. Deco, M. Massimini and M. Sanchez-Vivez) that starts with an in-depth assessment of behaviour and physiological studies of brain activity to characterize the affected circuits and associated patterns of functional abnormalities. Such a multi-dimensional physiological map of a lesioned brain can be then fed to biologically realistic in silico models 80 . A model of a lesioned brain affords the opportunity to explore, in an exhaustive way, different kinds of stimulation to normalize faulty activity. Once a suitable protocol is found it can be exported first to animal models, and then to humans. Stimulation alone will not be enough. Pairing with behavioural training (rehabilitation) will stabilize learning and normalize connections.

The ability to interface therapy (stimulation, rehabilitation and drugs) with brain signals or other kinds of behavioural sensor offers another exciting opportunity, to open the ‘brain’s black box’. Most current treatments in neuroscience are given with no regard to their effect on the underlying brain signals or behaviour. Giving patients conscious access to their own brain signals may substantially enhance recovery, as the brain is now in the position to use its own powerful connections and learning mechanisms to cure itself.

Maurizio Corbetta is Professor and Chair of Neurology at the Department of Neuroscience and Director of the Padova Neuroscience Center (PNC), University of Padova, Italy; and Principal Investigator at the Venetian Institute of Molecular Medicine (VIMM), Padova, Italy .

Merete Nordentoft

Schizophrenia and related psychotic disorders are among the costliest and most debilitating disorders in terms of personal sufferings for those affected, for relatives and for society 81 . These disorders often require long-term treatment and, for a substantial proportion of the patients, the outcomes are poor. This has motivated efforts to prevent long-lasting illness by early intervention. The time around the onset of psychotic disorders is associated with an increased risk of suicide, of loss of affiliation with the labour market, and social isolation and exclusion. Therefore, prevention and treatment of first-episode psychosis will be a key challenge for the future.

There is now solid evidence proving that early intervention services can improve clinical outcomes 82 . This was first demonstrated in the large Danish OPUS trial, in which OPUS treatment — consisting of assertive outreach, case management and family involvement, provided by multidisciplinary teams over a two-year period — was shown to improve clinical outcomes 83 . Moreover, it was also cost-effective 84 . Although the positive effects on clinical outcomes were not sustainable after five and ten years, there was a long-lasting effect on use of supported housing facilities (indicating improved ability to live independently) 85 . Later trials proved that it is possible to maintain the positive clinical outcomes by extending the services to five years or by offering a stepped care model with continued intensive care for the patients who are most impaired 86 . However, even though both clinical and functional outcomes (such as labour market affiliation) can be improved by evidence-based treatments 82 , a large group of patients with first-episode psychosis still have psychotic symptoms after ten years. Thus, there is still an urgent need for identification of new and better options for treatment.

Most probably, some of the disease processes start long before first onset of a psychotic disorder. Thus, identifying disease mechanisms and possibilities for intervention before onset of psychosis will be extremely valuable. Evidence for effective preventive interventions is very limited, and the most burning question — of how to prevent psychosis — is still open.

The early intervention approach is also promising also for other disorders, including bipolar affective disorder, depression, anxiety, eating disorders, personality disorders, autism and attention-deficient hyperactivity disorder.

Merete Nordentoft is Clinical Professor at the Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; and Principal Investigator, CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark .

Epidemiology

Gabriel M. Leung

In a widely anthologized article from the business field of marketing, Levitt 87 pointed out that often industries failed to grow because they suffered from a limited market view. For example, Kodak went bust because it narrowly defined itself as a film camera company for still photography rather than one that should have been about imaging writ large. If it had had that strategic insight, it would have exploited and invested in digital technologies aggressively and perhaps gone down the rather more successful path of Fujifilm — or even developed into territory now cornered by Netflix.

The raison d’être of epidemiology has been to provide a set of robust scientific methods that underpin public health practice. In turn, the field of public health has expanded to fulfil the much-wider and more-intensive demands of protecting, maintaining and promoting the health of local and global populations, intergenerationally. At its broadest, the mission of public health should be to advance social justice towards a complete state of health.

Therefore, epidemiologists should continue to recruit and embrace relevant methodology sets that could answer public health questions, better and more efficiently. For instance, Davey Smith and Ebrahim 88 described how epidemiology adapted instrumental variable analysis that had been widely deployed in econometrics to fundamentally improve causal inference in observational epidemiology. Conversely, economists have not been shy in adopting the randomized controlled trial design to answer questions of development, and have recognized it with a Nobel prize 89 . COVID-19 has brought mathematical epidemiology or modelling to the fore. The foundations of the field borrowed heavily from population dynamics and ecological theory.

In future, classical epidemiology, which has mostly focused on studying how the exposome associates with the phenome, needs to take into simultaneous account the other layers of the multiomics universe — from the genome to the metabolome to the microbiome 90 . Another area requiring innovative thinking concerns how to harness big data to better understand human behaviour 91 . Finally, we must consider key questions that are amenable to epidemiologic investigation arising from the major global health challenges: climate change, harmful addictions and mental wellness. What new methodological tools do we need to answer these questions?

Epidemiologists must keep trying on new lenses that correct our own siloed myopia.

Gabriel M. Leung is Helen and Francis Zimmern Professor in Population Health at WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong; Chief Scientific Officer at Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park; and Dean of Medicine at the University of Hong Kong, Hong Kong Special Administrative Region, China .

Bahdanau, D., Cho, K. & Bengio, Y. Neural machine translation by jointly learning to align and translate. Preprint at https://arxiv.org/abs/1409.0473 (2014).

Jumper, J. et al. Nature 596 , 583–589 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Dwork, C., Hardt, M., Pitassi, T., Reingold, O. & Zemel, R. Fairness through awareness. In Proc. 3rd Innovations in Theoretical Computer Science Conference , 214–226 (Association for Computing Machinery, 2012).

Chouldechova, A. & Roth, A. Commun. ACM 63 , 82–89 (2020).

Article   Google Scholar  

Hara, K. et al. A data-driven analysis of workers’ earnings on Amazon Mechanical Turk. In Proc. 2018 CHI Conf. on Human Factors in Computing Systems , 1–14 (Association for Computing Machinery, 2018).

Strubell, E., Ganesh, A. & McCallum, A. Energy and policy considerations for deep learning in NLP. Preprint at https://arxiv.org/abs/1906.02243 (2019).

Rival, L. Anthropol. Today 37 , 9–12 (2021).

Carey, J. W. Communication as Culture: Essays on Media and Society (Unwin Hyman, 1985).

Williams, R. Television: Technology and Cultural Form (Fontana, 1974).

Helmond, A. Soc. Media Soc . 1 , https://doi.org/10.1177/2056305115603080 (2015).

Rambukkana, N. (Ed.). Hashtag Publics: The Power and Politics of Discursive Networks (Peter Lang, 2015).

Burrell, J. Big Data Soc. 3 , 1–12 (2016).

Bruns, A. et al. Facebook shuts the gate after the horse has bolted, and hurts real research in the process. Internet Policy Review , https://go.nature.com/3IP2xYr (25 April 2018).

Article 19. EU: Stop platforms from suppressing public interest research. article.19.org , https://go.nature.com/3DTWgXT (13 September 2021).

Burgess, J. et al. Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms. Preprint at https://doi.org/10.31235/osf.io/2cwsu (2021).

Rieder, B. & Hofmann, J. Internet Policy Review 9 , 1–28 (2020).

Vosoughi, S., Roy, D. & Aral, S. Science 359 , 1146–1151 (2018).

Article   CAS   PubMed   Google Scholar  

Hussein, E., Juneja, P. & Mitra, T. Measuring misinformation in video search platforms: an audit study on YouTube. In Proc. of the ACM on Human–Computer Interaction 4 (CSCW1) (eds. Lampe C. et al.) 1–27 (Association for Computing Machinery, 2020).

Lazer, D. M. J. et al. Science 369 , 1060–1062 (2020).

Wagner, C. et al. Nature 595 , 197–204 (2021).

Kosse, F., Deckers, T., Pinger, P., Schildberg-Hörisch, H. & Falk, A. J. Polit. Econ. 128 , 434–467 (2020).

Cappelen, A., List, J., Samek, A. & Tungodden, B. J. Polit. Econ. 128 , 2739–2758 (2020).

Article   PubMed   PubMed Central   Google Scholar  

Alan, S., Boneva, T. & Ertac, S. Q. J. Econ. 134 , 1121–1162 (2019).

Google Scholar  

Almås, I., Cappelen, A. & Tungodden, B. J. Polit. Econ. 128 , 1753–1788 (2020).

Müller, D. & Renes, S. Soc. Choice Welfare 56 , 679–711 (2021).

Falk, A. et al. Q. J. Econ. 133 , 1645–1692 (2018).

Almås, I., Cappelen, A., Sørensen, E. Ø. & Tungodden, B. Global evidence on the selfish rich inequality hypothesis. Proc. Natl Acad. Sci. USA (in the press).

Henrich, J., Root, H. & Henrich, J. The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Propserous (Farrar, Strauss, and Giroux, 2020).

Gelfand, M. J. et al. Lancet Planet. Health 5 , e135–e144 (2021).

Lu, J. G., Jin, P. & English, A. S. Proc. Natl Acad. Sci. USA 118 , e2021793118 (2021).

Hong, Y. Y., Morris, M. W., Chiu, C. Y. & Benet-Martínez, V. Am. Psychol. 55 , 709–720 (2000).

Chan, H.-W. et al. Polit. Psychol. 42 , 767–793 (2021).

Gollwitzer, A. et al. Nat. Hum. Behav. 4 , 1186–1197 (2020).

Article   PubMed   Google Scholar  

de Solla Price, D. Little Science, Big Science (Columbia Univ. Press, 1963).

Mauss, M. 1925. in Sociologie et Anthropologie (Réédition 1978) 143–275 (Presses Universitaires de France).

Darwin, C. The Descent of Man, and Selection in Relation to Sex (Penguin 2004) (reprint of 2nd edn, 1879).

Mesoudi, A. Proc. Natl Acad. Sci. USA 114 , 7853–7860 (2017).

Cavalli-Sforza, L. & Feldman, M. W. Theor. Popul. Biol. 4 , 42–55 (1973).

Cavalli-Sforza, L. L. & Feldman, M. W. Am. J. Hum. Genet. 25 , 618–637 (1973).

CAS   PubMed   PubMed Central   Google Scholar  

Cavalli-Sforza, L. L. & Feldman, M. W. Cultural Transmission and Evolution (Princeton Univ. Press, 1981).

Richerson, P. J. & Boyd, R. J. Social Biological Syst. 1 , 127–154 (1978).

Boyd, R. & Richerson, P. J. Culture and the Evolutionary Process (Chicago Univ. Press, 1985).

Shennan, S. J. Camb. Archaeol. J. 11 , 5–16 (2001).

Strimling, P., Sjöstrand, J., Enquist, M. & Eriksson, K. Theor. Popul. Biol. 76 , 77–83 (2009).

Aoki, K., Lehmann, L. & Feldman, M. W. Theor. Popul. Biol. 79 , 192–202 (2011).

Kandler, A. & Laland, K. N. Theor. Popul. Biol. 76 , 59–67 (2009).

Laland, K. N. & O’Brien, M. J. Biol. Theory 6 , 191–202 (2011).

Richerson, P. J. & Boyd, R. Not By Genes Alone: How Culture Transformed Human Evolution (Univ. Chicago Press, 2005).

Kandler, A. & Powell, A. Phil. Trans. R. Soc. Lond. B 373 , 20170056 (2018).

Kandler, A., Wilder, B. & Fortunato, L. R. Soc. Open Sci. 4 , 170949 (2017).

McElreath, R. et al. Phil. Trans. R. Soc. Lond. B 363 , 3515–3528 (2008).

Turkheimer, E. Curr. Dir. Psychol. Sci. 9 , 160–164 (2000).

Polderman, T. J. C. C. et al. Genet. 47 , 702–709 (2015).

CAS   Google Scholar  

Visscher, P. M. et al. Am. J. Hum. Genet. 101 , 5–22 (2017).

Karlsson Linnér, R. et al. Nat. Genet. 51 , 245–257 (2019).

Article   PubMed   CAS   Google Scholar  

Lee, J. J. et al. Nat. Genet. 50 , 1112–1121 (2018).

Liu, M. et al. Nat. Genet. 51 , 237–244 (2019).

Wray, N. R., Goddard, M. E. & Visscher, P. M. Genome Res. 17 , 1520–1528 (2007).

The International Schizophrenia Consortium. Nature 460 , 748–752 (2009).

Article   CAS   Google Scholar  

Becker, J. et al. Nat. Hum. Behav . (2021).

Belsky, D. W. et al. Psychol. Sci. 27 , 957–972 (2016).

Young, A. I., Benonisdottir, S., Przeworski, M. & Kong, A. Science 365 , 1396–1400 (2019).

Barcellos, S. H., Carvalho, L. S. & Turley, P. Proc. Natl Acad. Sci. USA 115 , E9765–E9772 (2018).

Papageorge, N. W. & Thom, K. J. Eur. Econ. Assoc. 18 , 1351–1399 (2020).

DiPrete, T. A., Burik, C. A. P. & Koellinger, P. D. Proc. Natl Acad. Sci. USA 115 , E4970–E4979 (2018).

Rietveld, C. A. et al. Science 340 , 1467–1471 (2013).

Kong, A., Benonisdottir, S. & Young, A. I. Family analysis with Mendelian imputations. Preprint at https://doi.org/10.1101/2020.07.02.185181 (2020).

Howe, L. J. et al. Within-sibship GWAS improve estimates of direct genetic effects. Preprint at https://doi.org/10.1101/2021.03.05.433935 (2021).

Martin, A. R. et al. Nat. Genet. 51 , 584–591 (2019).

Nuffield Council on Bioethics. Genetics and Human Behaviour: The Ethical Context (Nuffield Council on Bioethics, 2002).

Redcay, E. & Schilbach, L. Nat. Rev. Neurosci. 20 , 495–505 (2019).

Roeckner, A. R., Oliver, K. I., Lebois, L. A. M., van Rooij, S. J. H. & Stevens, J. S. Transl. Psychiatry 11 , 508 (2021).

Sevgi, M., Diaconescu, A. O., Henco, L., Tittgemeyer, M. & Schilbach, L. Biol. Psychiatry 87 , 185–193 (2020).

Wittmann, M. K. et al. Neuron 91 , 482–493 (2016).

Gao, M. et al. Neuroimage 223 , 117290 (2020).

Lee, K. M., Ferreira-Santos, F. & Satpute, A. B. Neurosci. Biobehav. Rev. 131 , 211–228 (2021).

Olesen, J., Gustavsson, A., Svensson, M., Wittchen, H. U. & Jönsson, B. Eur. J. Neurol. 19 , 155–162 (2012).

Corbetta, M., Siegel, J. S. & Shulman, G. L. Cortex 107 , 229–237 (2018).

Griffis, J. C., Metcalf, N. V., Corbetta, M. & Shulman, G. L. Cell Rep. 28 , 2527–2540 (2019).

Deco, G. et al. J. Neurosci. 33 , 11239–11252 (2013).

Patel, V. et al. Lancet 392 , 1553–1598 (2018).

Correll, C. U. et al. JAMA Psychiatry 75 , 555–565 (2018).

Petersen, L. et al. Br. Med. J. 331 , 602 (2005).

Hastrup, L. H. et al. Br. J. Psychiatry 202 , 35–41 (2013).

Secher, R. G. et al. Schizophr. Bull. 41 , 617–626 (2015).

Albert, N. et al. Br. Med. J. 356 , i6681 (2017).

Levitt, T. Harv. Bus. Rev. 38 , 45–56 (1960).

Davey Smith, G. & Ebrahim, S. Int. J. Epidemiol. 32 , 1–22 (2003).

Callaway, E. ‘Randomistas’ who used controlled trials to fight poverty win economics Nobel. Nature, https://www.nature.com/articles/d41586-019-03125-y (14 October 2019).

Topol, E. J. Cell 157 , 241–253 (2014).

Subrahmanian, V. S. & Kumar, S. Science 355 , 489 (2017).

Download references

Author information

Authors and affiliations.

Department of Political Science, Ohio State University, Columbus, OH, USA

School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland, Australia

Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia

Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy

Venetian Institute of Molecular Medicine (VIMM), Padova, Italy

Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, USA

Microsoft Research New York, New York, NY, USA

École Normale Supérieure, Paris, France

Department of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA

Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Department of Psychology, University of California at Berkeley, Berkeley, CA, USA

American University of Beirut, Beirut, Lebanon

Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA

Department of Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Center for Social and Environmental Systems Research, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan

State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, Hong Kong Special Administrative Region, China

Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

Department of Experimental Psychology, University of Oxford, Oxford, UK

Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK

CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia

ODID and SAME, University of Oxford, Oxford, UK

School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA

Centre of Excellence FAIR, NHH Norwegian School of Economics, Bergen, Norway

GESIS – Leibniz Institute for the Social Sciences, Köln, Germany

RWTH Aachen University, Aachen, Germany

Complexity Science Hub Vienna, Vienna, Austria

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to Janet M. Box-Steffensmeier , Jean Burgess , Maurizio Corbetta , Kate Crawford , Esther Duflo , Laurel Fogarty , Alison Gopnik , Sari Hanafi , Mario Herrero , Ying-yi Hong , Yasuko Kameyama , Tatia M. C. Lee , Gabriel M. Leung , Daniel S. Nagin , Anna C. Nobre , Merete Nordentoft , Aysu Okbay , Andrew Perfors , Laura M. Rival , Cassidy R. Sugimoto , Bertil Tungodden or Claudia Wagner .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Box-Steffensmeier, J.M., Burgess, J., Corbetta, M. et al. The future of human behaviour research. Nat Hum Behav 6 , 15–24 (2022). https://doi.org/10.1038/s41562-021-01275-6

Download citation

Published : 27 January 2022

Issue Date : January 2022

DOI : https://doi.org/10.1038/s41562-021-01275-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Corporate social responsibility and individual behaviour.

• Herman Aguinis
• Deborah E. Rupp
• Ante Glavas

Nature Human Behaviour (2024)

Sustainable dietary choices improved by reflection before a nudge in an online experiment

• Sanchayan Banerjee
• Matteo M. Galizzi
• Susana Mourato

Nature Sustainability (2023)

Spatially Small-scale Approach-avoidance Behaviors Allow Learning-free Machine Inference of Object Preferences in Human Minds

• Tsung-Ren Huang
• Tzu-Chun Chen

International Journal of Social Robotics (2023)

Potential of quantum computing to effectively comprehend the complexity of brain

• Shyam R. Sihare

Applied Intelligence (2023)

Nature Human Behaviour turns five

Nature Human Behaviour (2022)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Psychology: Research and Review

• Open access
• Published: 04 June 2018

Behavioral problems of school children: impact of social vulnerability, chronic adversity, and maternal depression

• Ana Karina Braguim Martineli   ORCID: orcid.org/0000-0003-2549-5583 1 ,
• Fernanda Aguiar Pizeta 1 &
• Sonia Regina Loureiro 1  

Psicologia: Reflexão e Crítica volume  31 , Article number:  11 ( 2018 ) Cite this article

29k Accesses

8 Citations

19 Altmetric

Metrics details

This study’s objective was to identify the predictive effect of indicators concerning social vulnerability, chronic adversity, and maternal depression on behavioral problems among school-aged children, according to the perceptions of mothers and teachers, considering the presence or absence of difficulties in the contexts of family and school. A total of 85 pairs of mothers and school children were distributed into three groups according to the behavioral problems identified. A General Questionnaire, the PHQ-9, the Chronic Adversity Scale, and the (Strengths and Difficulties Questionnaire) SDQ were applied to the mothers; the Raven’s Colored Progressive Matrices were applied to the children; and the SDQ was applied to the teachers. Data were analyzed with descriptive, predictive, and comparative statistical procedures ( p  ≤ 0.05). The results reveal the presence of cumulative risks for children with behavioral problems; mothers more frequently identified behavioral problems than teachers; and maternal depression was a predictor for behavioral problems. Such findings are relevant for devising mental health programs.

The behavior of school-aged children is an important indicator of adaptation in this stage of development; however, not all children are successful and may present externalizing or internalizing behavioral problems, expressed within the family and/or school contexts (Achenbach, Ivanova, Rescorla, Turner, & Althoff, 2016 ; Linhares & Martins, 2015 ; Marturano, 2013 ).

Families present structural and internal dynamics that may contribute to either risk or protective outcomes in terms of child development (Macana & Comim, 2015 ; Walsh, 2016 ) so that adaptive difficulties associated with behavioral problems are frequent among children (Pizato, Marturano, & Fontaine, 2014 ). Considering the relevance of the influence exerted by the family context on school children, various studies have addressed the association of cumulative adversity present in the family context and the outcomes of behavioral problems among children (Duncombe, Havighurst, Holland, & Frankling, 2012 ; Leis, Heron, Stuart, & Mendelson, 2014 ; Pizeta, Silva, Cartafina, & Loureiro, 2013 ).

When analyzing the potential risk factors for the development of psychopathologies in 252 children and adolescents who are victims of domestic violence, Hildebrand, Celeri, Morcillo, and Zanolli ( 2015 ) verified that 92.8% of the participants were exposed to at least one risk factor. The authors also noticed that the association of two or more risk factors were present in 53.2% of the sample, namely family conflicts, mental health problems within the family, gender violence between parents, family involvement with drug trafficking and criminal behavior, and the abusive consumption of alcohol by parents or legal guardians, among others.

Therefore, among the events listed as conditions that predispose children to behavioral problems, we highlight indicators of chronic adversity and mental health conditions affecting the parents, especially maternal depression, as risk conditions acknowledged to have a negative impact on children. Additionally, the presence of variables related to social vulnerability is also identified based on conditions or events of life that may interfere in the course of developmental outcomes for children, contributing to the maladaptation of children in typical developmental tasks when experiencing risk conditions.

Considering social vulnerability in the population in general, low socioeconomic status and unemployment among mothers were identified as predictors of behavioral problems among children in situations of poverty, according to a study conducted by Bele, Bodhare, Valsangkar, and Saraf ( 2013 ) of children in India. In the Brazilian context, Correia, Saur, and Loureiro ( 2014 ) conducted a cohort study and identified an association of behavioral problems with low socioeconomic status for boys and low maternal education and larger families for girls. In the same direction, Pizato et al. ( 2014 ) verified association between improved socioeconomic conditions with fewer behavioral problems and more social skills in school-aged children; Saur and Loureiro ( 2015 ) identified associations between behavioral problems among 10-year-old children with low maternal educational level and low socioeconomic status and families with more than four members. It is also considered that the family socioeconomic condition can influence the cognitive performance of children, being this condition strongly related to other environmental aspects such as maternal depression (Piccolo et al., 2012 ).

In regard to the parents’ mental health, maternal depression, especially given its high prevalence and recurrence (World Health Organization [WHO], 2017a , 2017b ), stands out as a form of adversity in different periods of child development, impacting the behavior of school-aged children (Bagner, Pettit, Lewinsohn, & Seeley, 2010 ; Callender, Olson, Choe, & Sameroff, 2012 ; Edwards & Hans, 2015 ; Loosli, Pizeta, & Loureiro, 2016 ). Such a psychopathology, however, is associated with other adverse contextual conditions, favoring cumulative risk in the family context (Kessler, 2012 ). Note that the condition of cumulative risk has been acknowledged in the literature as having a greater impact for outcomes among children compared to the presence of a single risk (Evans, Li, & Whipple, 2013 ). Thus, this justifies the relevance of studying potential associations between maternal depression and behavioral problems, including other variables in the family environment, as proposed in this paper.

Indicators of social vulnerability and clinical characteristics of maternal depression have been identified as relevant factors to understanding risk conditions for child development. Barker, Copeland, Maughan, Jaffee, and Uher ( 2012 ) monitored children from their first year of life up to the age of 7 and verified that, in comparison to children of mothers without depression, children of mothers with depression were more frequently exposed to 10 out of the 11 risk factors assessed in the study, among which, low socioeconomic status, single parent, physical abuse, low maternal education, and drug and alcohol consumption. The frequency of exposure was at a significant level. Indicators concerning the severity of depression and anxiety were examined by Leis et al. ( 2014 ), in a sample of 2891 mother-child pairs, taking into account the perspectives of mothers and teachers. The authors found an association between severe depressive symptoms during pregnancy and more frequent behavioral problems at the age of 10 and 11 years old, according to the reports of teachers. Conners-Burrow et al. ( 2016 ), who took into account the assessment of mothers, determined that early contact with maternal mild depressive symptoms increased the risk of children presenting internalizing and externalizing behavioral problems during school-age years.

Still considering chronic risk and adversity and their influence on child behavior, we highlight the study by Wang, Christ, Mills-Koonce, Garrett-Peters, and Cox ( 2013 ), who found associations between externalizing problems among 4- to 12-year-old children and the use of more rigid control and low maternal educational levels. The study by Bouvette-Turcot et al. ( 2017 ) reports that exposure to more adversity and low family income during childhood was associated with the development of depressive symptoms in adulthood.

When addressing behavioral problems, one issue that arises refers to the source of assessments, considering that children and adolescents may present problems in a specific context but not in another, for instance, family versus school, indicating a need to obtain assessments from multiple informants, especially from parents or legal guardians and teachers (Martoni, Trevisan, Dias, & Seabra, 2016 ; Miller, Martinez, Shumka, & Baker, 2014 ). In this direction, some studies draw attention to the low to moderate level of agreement obtained between informants and to the relevance of such information to implementing clinical practices intended to address specific contexts in which children present problems (De Los Reyes et al., 2015 ; Martel, Markon, & Smith, 2017 ). Despite disagreement among the various informants, different observers provide different perspectives of the same problem (Miller et al., 2014 ). Each observer, though, can provide potentially valuable data in regard to the same patient (De Los Reyes, Thomas, Goodman, & Kundey, 2013 ; Clark, Durbin, Hicks, Iacono, & McGue, 2017 ), taking into consideration different contexts.

With school-aged children in mind, mothers and teachers have a privileged opportunity to observe the behavior of children, since the family and school are the primary contexts of development where competence in specific tasks inherent to this period is acquired (Achenbach et al., 2008 ), as previously mentioned. Some studies addressing the behavior of children according to the assessments of parents and teachers highlight the discrepancy between such assessments. Johnson, Hollis, Marlow, Simms, and Wolke ( 2014 ) used the Strengths and Difficulties Questionnaire (SDQ) to assess 219 children aged 11 years old who were born prematurely. The authors verified that the parents considered their children to present more emotional, attention, and relationship problems compared to the assessments provided by teachers. The informants agreed only in regard to the assessment of problems related to hyperactivity, which indicates the importance of using combined assessments. Kovess et al. ( 2015 ) conducted a study with 9084 children between 6 and 9 years of age, from seven countries (Italy, the Netherlands, Germany, Romania, Bulgaria, Lithuania, and Turkey), in which both teachers and parents were informants. The objective was to identify risks to the mental health of students. They verified that the teachers found the children to present more externalizing problems and fewer internalizing problems when compared to the parents’ assessments.

Even though assessments provided by multiple informants are considered relevant, the literature still lacks data. This study seeks to fill this gap and is intended to produce new data concerning the behavior of school children assessed by mothers and teachers, considering conditions in which children live with maternal depression and other adversities. Therefore, this study is intended to fill the gaps pointed out by De Los Reyes et al. ( 2015 ) concerning the need for further research using the assessments of multiple informants and addressing the specifics of contexts in which behavioral problems manifest, as a way to improve understanding regarding such problems, focusing on maternal depression. According to Goodman et al. ( 2011 ), there is a need for studies focusing on the multiple adversities presented in the family environment, taking into account the influence of maternal mental health when assessing the behavior of children, as indicated by Leis et al. ( 2014 ).

Therefore, the objective was to identify the behavioral profile of school children and associations between the evaluation of mothers and teachers, identifying the level of agreement among the informants. In addition, we aimed to evaluate the predictive effect of indicators concerning social vulnerability, chronic adversity, and maternal depression on behavioral problems presented by school children, according to the perspectives of mothers and teachers, considering the presence or absence of difficulties in both family and school contexts. The hypothesis guiding this study was that social vulnerability, chronic adversity, and maternal depression predict more frequent behavioral problems among school children in both developmental contexts, family and school, assessed by mothers and teachers, respectively.

A cross-sectional, correlational, predictive, comparative design was adopted using data obtained with different techniques from different sources, namely mothers, teachers, and children. The study was approved by the Institutional Review Board (no. 36415514.5.0000.5407) and complied with the ethical recommendations proposed by the Declaration of Helsinki.

Participants

A total of 85 mother-child pairs and 16 teachers from a public school located in the state of São Paulo, Brazil, took part in this study. The participants were assigned to three groups, according to the children’s indicators of behavioral problems assessed by their mothers and teachers, namely G1 = 18 children with behavioral problems according to their mothers and teachers, G2 = 39 children with behavioral problems according to their mothers or teachers, and G3 = 28 children without behavioral problems according to their mothers and teachers.

According to the inclusion criteria, mothers were aged between 25 and 45 years old, 34.5 years old on average (SD = 5.51), and all were literate. The children were aged between 7 and 10 years old, 8.8 years old on average (SD = 1.06) and were homogeneously distributed into three groups. In regard to the children’s sex, 39 were girls and 46 were boys, making a balanced distribution according to sex impossible: G1 presented significantly more boys than girls when compared to the G2 and G3 ( p  = 0.05; p  = 0.02, respectively). In order to assess the weight of this variable for the presence or absence of behavioral problems among children, as assessed by both their mothers and their teachers, an ordinal regression analysis was performed considering the sex of the children, which revealed a model that did not present the minimum criteria regarding slope homogeneity [chi-square (1) = 5.285; p  = 0.022; D (1) = 5.524; p  = 0.019], that is, it is not a model that fits data under analysis.

The inclusion criteria are that the children live with their biological mothers, rather than adoptive mothers, and have attended at least 1 year of primary school. Institutionalized children or those with apparent physical or mental disabilities were excluded. The assessment of children was initiated after consent was obtained from their mothers, and only one child per family was included in the study. In regard to the teachers, only those who had had at least 3 months of contact with the children and taught the children whose mothers explicitly consented to the assessment of their children at school were included. In accordance with the principles of good research practices, the participation of mothers and teachers was voluntary, without incentive payment mechanisms that stimulated the involvement with the research. A lecture was offered to the school on the behavior and learning of school children.

Instruments

Raven’s colored progressive matrices (raven).

The Raven is an instrument standardized by Angelini, Alves, Custódio, Duarte, and Duarte ( 1999 ), to assess the intellectual level of Brazilian children between 5 and 11 years old. It is a psychological test of non-verbal intelligence; the objective of which is to assess one’s analogical reasoning as a general factor, composed of three series: A, AB, and B, each with 12 problems. It presents good psychometric qualities, inferred by construct validity, internal consistency, with item-total correlation between 0.30 and 0.80 for most items, as well as precision, inter-item coefficient of correlation for the total sample equal to 0.92 (Angelini et al., 1999 ). Children presenting potential cognitive deficits, who presented percentiles lower than 25, were excluded from the study (Muniz, Gomes, & Pasian, 2016 ), balancing groups according to the percentiles obtained by the children.

Patient Health Questionnaire-9 (PHQ-9)

The PHQ-9 is a module directly based on the diagnostic criteria for major depression disorder from the DSM-IV, proposed and validated by Spitzer, Kroenke, and Williams ( 1999 ) and by Kroenke, Spitzer, and Williams ( 2001 ). The questionnaire enables both screening for signs and symptoms of current major depression, as well as classifying levels of severity, from mild to moderate or severe; the greater the score, the more indicators of problems the individual presents. It is composed of nine items assessed by an ordinal scale that measures the frequency of signs and symptoms of depression in the last 2 weeks. According to the instrument’s technical instructions, the total score was used so that scores greater than or equal to 10 indicate the presence of depressive symptoms, while scores lower than 10 indicate an absence of such symptoms. The Brazilian version used in this study was translated by Pfizer (Copyright  © 2005 Pfizer Inc., New York, NY), the reliability of which was verified by Osório, Mendes, Crippa, and Loureiro ( 2009 ), presenting satisfactory psychometric indicators.

Strengths and Difficulties Questionnaire (SDQ)

The SDQ was developed by Goodman ( 1997 ) and is intended to assess the behavior of children and adolescents, aged between 4 and 16 years old, by screening their behavioral strengths and difficulties. There is a version for children and adolescents between 11 and 16 years of age, a version for parents, and another for teachers. The SDQ is composed of 25 items subdivided into five subscales: emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and pro-social behavior, with five items each. It provides raw scores and cutoff points for each of the subscales, as well as a total score for difficulty that is obtained by totaling the four behavioral problem scales. Scores are classified as normal, borderline, and abnormal. It was translated to Portuguese and adapted for Brazilian sociocultural characteristics by Fleitlich, Cortázar, and Goodman ( 2000 ), while psychometric data, concerning validity and reliability, were described by Woerner et al. ( 2004 ), presenting good indicators. In this study, based on individual scores and cutoff points established for the Brazilian population, we considered the outcome variable for children classified as normal or borderline, according to the SDQ, to be “without difficulties,” while those who were classified as abnormal to be “with difficulties.” These outcomes were grouped with the assessments performed by the mothers and teachers, according to the distribution in the groups.

Chronic Adversity Scale (CAS)

The CAS was proposed by Marturano ( 1999 ) and is intended to identify recurrent adverse events that may have taken place in a child’s life and happened repeated times or lasted 1 year or longer. It is composed of 18 items addressing issues concerning chronic adversity regarding the child’s or the parents’ health, parents’ temperament, and potential family or marital conflicts. The scale is completed by the mothers based on a list of adverse conditions that may have developed in the lives of children since birth, specifying the duration in years and the child’s period of life at the time. Each item is scored either 0 (absence of recurrence or chronic nature of the event in the child’s life) or 1 (the event was recurrent or has a chronic nature); the sum of all 18 items results in the total score, which is used to identify the existence of chronic events.

General Questionnaire

This questionnaire addresses sociodemographic data and specific information concerning the mothers’ age, marital status, and educational level; the families’ monthly income and socioeconomic status; and the age, sex, and education of the children included in the study. The items from the Brazil Economic Classification Criteria, developed by the Brazilian Association of Survey Companies ( 2015 ), were used to assess socioeconomic conditions. Such information was used to characterize the participants and groups, as well as to identify social vulnerability indicators, including low maternal and paternal education, single-parent families, low socioeconomic status, and low family income, as well as being recipients of governmental financial support.

Data collection procedures

Preferably, data were collected at school in a private room, or in the families’ homes when requested by the mothers, in which case we sought to preserve the respondents’ privacy and convenience. All interviews were held by the first researcher, who is a psychologist and properly trained in the application of instruments.

Initially, 427 families received an invitation letter, which was delivered to the children in their classrooms. The 260 families who responded to the invitation were contacted by phone with the objective to provide clarification about the study’s objectives and schedule an assessment. A total of 154 families accepted the invitation to cooperate with the study, but nine of these were excluded because the grandmothers were the primary caregivers of these families’ children. Of the 145 mothers scheduled for assessment, 43 did not attend the interviews, resulting in 102 families. Seventeen of these did not meet the inclusion criteria: adolescent mothers or mothers older than 45 years of age, children exclusively living with their fathers, and children with characteristics that were not homogeneous with those presented by the groups. Thus, a total of 85 mother-child pairs were included and assessed.

Of the 427 families initially invited to participate in this research, 316 refused to collaborate with the survey and 26 were excluded because they did not meet the inclusion criteria.

The instruments were individually and in-person applied to mothers in a single section according to the following order: General Questionnaire, PHQ-9, CAS, and SDQ, with an average duration of 60 min. The researcher read the instruments and checked the responses while the mothers had a copy of the instruments to accompany the reading. This procedure was adopted to deal with potential difficulties or fatigue that the reading could produce in the mothers, given their level of education or potential depressive symptoms, though the mothers presented a minimum level of literacy that enabled them to understand the questions posed by the instruments.

The children were assessed at school in individual sessions that lasted an average of 15 min. After briefly establishing rapport, the Raven’s Colored Progressive Matrices was applied. The three groups were compared according to the percentiles children obtained in order to balance the groups in regard to this variable. Note that there were no significant statistical differences between them in regard to the children’s cognitive performances (G1: \( \overline{x} \)  = 75.1; σ  = 19.12; G2: \( \overline{x} \)  = 76.0; σ  = 13.44; G3: \( \overline{x} \)  = 66.9; σ  = 14.97).

The 16 teachers collectively completed the SDQ, focusing on the behavior of 85 children who had been previously assessed by their mothers, at the regular time scheduled for a meeting concerning collective teaching work. Each teacher was supposed to assess up to five students per meeting, with an average duration of 50 min and approximately 10 min per child. The teachers filled in the questionnaire, and the researcher remained in the room during the assessment to clarify potential doubts.

Data treatment and analysis

The PHQ-9, Raven, SDQ, and CAS were coded according to the purpose of each instrument. The assessments concerning the behaviors of children performed by the mothers and teachers using the SDQ were used as distinct sources in paired samples, in order to assign the participants to one of the three groups.

Coded data were typed in an Excel® spreadsheet and checked by independent reviewers. The statistical analyses were performed using IBM SPSS Statistics (v. 23; IBM SPSS, Chicago, IL), and a significance level of 0.05 was adopted.

The reliability of the PHQ-9 was verified for this sample using Cronbach’s alpha, which presented good psychometric quality ( α  = 0.87). The reliability of the SDQ ( n  = 85) for the totality of items regarding difficulties was based on the mothers’ ( α  = 0.77) and teachers’ answers ( α  = 0.89), as well as items of the pro-social behavior scale answered by mothers ( α  = 0.71) and teachers.

Normality tests (Kolmogorov-Smirnov, with Lilliefors significance correlation, and Shapiro-Wilk) were performed to guide decision-making regarding the statistical tests used for each set of variables.

The behavioral profile of children, obtained through the assessments of mothers and teachers and represented by the raw scores obtained on the scales addressing problems and pro-social resources and the total scale of difficulties in the SDQ, was analyzed using descriptive and comparative statistics by means of the Wilcoxon test. Indicators of the presence and absence of behavioral problems among children, assessed by the mothers and teachers using the SDQ, were compared using the McNemar test. Inter-observer agreement was also verified using the Kappa coefficient, while the criterion proposed by Landis and Koch ( 1977 ) was adopted.

The sociodemographic data and profiles of social vulnerability and chronic adversity were analyzed using descriptive statistics, while the groups were compared using chi-square and Kruskal-Wallis tests. After the univariate analysis, the predictive effect of cumulative adverse conditions on school children’s behavioral problems was assessed using ordinal regression analysis (Maroco, 2014 ), adopting criteria proposed by Field ( 2013 ) for the inclusion of predictive variables.

The weight of contextual adverse cumulative variables for the children’s behavioral problems was tested using ordinal regression analysis based on the significant variables identified in the comparison between groups. The predictive variables were included in the model (family income, mother’s education, and maternal depression were included as factors, and the score of chronic adversity was included as a covariant), independently tested, and combined with the sex of children, because the distribution of children in the groups according to sex was not homogeneous. Additionally, the contextual variables of cumulative risk were jointly tested in a multivariate model.

The analysis of the social vulnerability indicators (income and maternal education) and maternal depression, in one analysis disregarding the sex of children and then one considering the sex of children, showed that the models did not fit the data. The analysis of the models that included chronic adversity, as a single variable or associated with the sex of children, revealed statistically significant models, with very small effect sizes, in which independent variables did not predict the behavioral outcome among children, thus did not present relevant results. Afterwards, the multivariate model including maternal depression, social vulnerability indicators, and chronic adversity was tested and presented goodness of fit and is the model presented here.

Based on the objectives proposed, the results are presented taking into account the analyses concerning the children’s behavioral profiles according to the assessments of mothers and teachers as distinct sources, comparisons between G1, G2, and G3 regarding profile of social vulnerability, maternal depression, and chronic adversity, as well as the predictive effect of significant variables on the children’s behavioral problems assessed by mothers and professors, as combined sources of information.

The children’s behavioral profiles

Table  1 presents the behavioral profiles of the children assessed, according to the SDQ, by mothers and teachers as two different sources, adopting the presence or absence of behavioral problems verified by the SDQ and total difficulties as the outcome of the development of school children.

Significant statistical differences were found when comparing mothers and teachers in regard to the four specific scales of difficulties and total difficulties. Note that the mothers considered their children to present more emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and total difficulties than the teachers. In regard to pro-social behavior, no statistically significant differences were found in regard to the comparisons between mothers and teachers.

In regard to the level of agreement obtained between assessments (mothers and teachers), note that reasonable agreement levels were found for conduct problems (kappa = 0.29 p  = 0.003) and total behavioral problems (kappa = 0.21; p  = 0.007), in addition to minimum indexes for hyperactivity (kappa = 0.19; p  = 0.035).

Similarly, the same differences were found for continuous scores. The means of the mothers were greater than those presented by the teachers for the total difficulties score (mothers: \( \overline{x} \)  = 17.5; σ  = 6.98; teachers: \( \overline{x} \)  = 9.33; σ  = 7.28; p  <  0.001) and for the four scales concerning symptoms: emotional symptoms (mothers: \( \overline{x} \)  = 3.19; σ  = 2.52; teachers: \( \overline{x} \)  = 2.26; σ  = 1.89; p  <  0.001), conduct problems (mothers: \( \overline{x} \)  = 3.32; σ  = 2.56; teachers: \( \overline{x} \)  = 1.59; σ  = 2.23; p  < 0.001), hyperactivity (mothers: \( \overline{x} \)  = 6.79; σ  = 2.76; teachers: \( \overline{x} \)  = 4.04; σ  = 3.23; p  < 0.001), and peer relationships (mothers: \( \overline{x} \)  = 2.20; σ  = 2.20; teachers: \( \overline{x} \)  = 1.42; σ  = 1.90; p  < 0.001).

The profiles of families in terms of vulnerability and risk variables

Table  2 presents comparisons concerning social vulnerability, maternal depression, and chronic adversities presented in the family context of children according to their distribution in the three groups.

Statistically significant differences were found between G1, G2, and G3 in regard to maternal education, family income, maternal depression, and chronic adversity. The comparison concerning maternal education revealed significant differences between G1 and G3 ( χ 2  = 5.660, p  = 0.017) and between G2 and G3 ( χ 2  = 12.075, p  < 0.001). Significant differences were also found in terms of family income between G1 and G2 ( χ 2  = 4.349, p  < 0.037) and between G1 and G3 ( χ 2  = 5.841, p  = 0.016). No differences were found between groups in terms of paternal education, marital status, socioeconomic status, or receiving governmental financial aid. Considering the variable maternal depression, however, statistically significant differences were found between G1 and G2 ( χ 2  = 13.876, p  < 0.000) and between G1 and G3 ( χ 2  = 22.489, p  < 0.001). G1 was the group in which mothers more frequently presented current symptoms of depression in comparison to the other two groups, while no differences were found between G2 and G3.

Comparisons concerning chronic adversities revealed significant differences between G2 and G3 ( F  = 363.000, p  = 0.016), but no differences were found between G1 and G2 or between G1 and G3.

The predictive effect of adverse cumulative variables on child behavior

Table  3 presents the weight of adverse cumulative contextual variables on child behavior, including data concerning coefficients and significance of the adjusted ordinal model.

Data suggest that the adjusted model is significantly better than the null model [ G 2 (4) = 24,792, p  < 0.001). Additionally, the multivariate model was statistically significant [chi-square (58) = 50,367, p  = 0.752; D (58) = 57,402, p  = 0.497] and showed moderate effect size (R 2 MF = 0.253; R 2 N = 0.288; R 2 CS = 0.139). According to the model, children are more likely to present behavioral problems when their mothers present indicators of depression, according to the assessments of both mothers and teachers ( b  = 1.955, p  = 0.001).

This study was intended to verify associations between indicators of social vulnerability, chronic adversity, and maternal depression, and the weight of such associations, with behavioral problems among school children, as assessed by their mothers and teachers. In this study, mothers and teachers were considered distinct sources of information, and the information they provided on the children’s behaviors was combined considering the presence or absence of difficulties manifested in the two developmental contexts of family and school. The hypothesis guiding this study that social vulnerabilities, chronic adversity, and maternal depression impact behavioral problems among school children was partially confirmed, as data analysis revealed peculiarities regarding such variables, which deserve to be highlighted.

The assessments of the children’s behavior from the perspectives of mothers and teachers in general showed that mothers identified more behavioral problems in children than did the teachers. This finding is in agreement with those reported in the studies conducted by De Los Reyes et al. ( 2015 ) and Martel et al. ( 2017 ), which indicate low to moderate agreement among informants. In this same direction, Clark et al. ( 2017 ) consider that agreement between assessments of parents, teachers, and children is rarely high, however, emphasizing that varied information enriches the understanding of the associations between academic conditions, personality, psychosocial functioning, behavioral aspects, mental health, and social adjustment of school children. According to the mothers’ assessments, a larger number of children experienced difficulties concerning emotional symptoms, while the teachers identified a larger number of children with externalizing problems expressed through conduct problems and hyperactivity. Such results are similar to those reported by Kovess et al. ( 2015 ), who note that externalizing problems are more visible to teachers than internalizing problems.

Analysis of this discrepancy between assessments should take into account that the interaction of mothers and teachers with children occurs in contexts that exhibit different demands, in addition to the fact that observers are guided by different criteria. In the family context, mothers have a more detailed picture of their children’s behavior due to the large range of daily situations, which are not always structured (Leis et al., 2014 ). In the case of the mothers, the parameter is one specific child. In the classroom, in contrast, teachers have more structured situations to assess children and the teachers’ references include comparing the behavior of a set of children with similar demographic parameters. In this sense, when the assessments of mothers and teachers were combined, we accessed a larger set of information concerning the behavior of children, focusing on aspects of contextual comparisons and individual and collective parameters, as proposed by Miller et al. ( 2014 ) and De Los Reyes et al. ( 2015 ).

The literature has recognized the relevance of assessments performed by teachers; however, few studies address behavioral difficulties of children using multiple informants and combined data as a strategy to identify the presence of problems in more than one context of life. The predominance of the mother as the only informant may compromise the results of assessments, especially when a mother presents a psychopathological disorder (Leis et al., 2014 ), such as depression. Such a disorder may influence the individual’s perception of child behavior, and avoiding this influence justifies the use of distinct and combined sources of information. Therefore, we note that one of the contributions of this study, in addition to including multiple informants, is the combined analysis of children’s behavioral outcomes, which enabled verifying problems in two contexts, family and school, to estimate how many children face these sorts of difficulties, information that is relevant for practices in the mental health field.

Another aspect to be analyzed involves social vulnerability, which was assessed considering different social and economic factors, among which are low maternal educational level and income. These are relevant social determinants associated with the presence of behavioral problems among children, according to the assessments by mothers and/or children, indicating aspects to be considered when planning preventive practices. Note that these findings are consistent with those reported by Correia et al. ( 2014 ), who identified association between child behavioral problems and low socioeconomic status and low maternal educational level, indicating a potential profile of cumulative vulnerability favoring behavioral problems among children. Families with low socioeconomic status generally have high rates of divorce, unemployment, and a larger number of members, while parents with a high socioeconomic level have a higher educational level and invest more in their children’s education (Carneiro, Meghir, & Parey, 2013 ; Piccolo et al., 2012 ).

The associations between mental health conditions and vulnerability indicators have been widely recognized by the World Health Organization (WHO, 2017a , 2017b ), which highlights low schooling, lower income, worse material and economic conditions, and less social support, as possible determinants that negatively influence health mental health of adults and children, favoring the accumulation of vulnerability and risk conditions. This developmental scenario focuses on the relevance of the present study, which encompasses diverse and competing contextual variables that influence children’s developmental outcomes in the perception of different informants.

The presence of current depressive symptoms among the mothers was associated with behavioral problems among the children, as indicated by the mothers and/or teachers, characterizing problems in two contexts, family and school. Such an association was also verified by Leis et al. ( 2014 ) and Conners-Burrow et al. ( 2016 ), who noted an increase in behavioral problems among children who had early experience with maternal depression. In this sense, when we considered the behavior of children from the perspectives of mothers and teachers together, we verified that, regardless of the informant, children living with maternal depression more frequently experienced behavioral problems, including in the school context, characterizing the need for specific mental health practices directed to this group, which was identified as the most vulnerable.

The presence of chronic adversities was also verified to identify variables with a potential negative impact on school-aged children. This study reveals that children facing behavioral difficulties, according to the combined assessments of mothers and teachers, lived in family environments that presented more chronic adversities, indicating cumulative and recurrent adversity in these children’s contexts of life. These findings corroborate the study conducted by Hildebrand et al. ( 2015 ), who identified an association of two or more risk factors for more than half of the sample under study.

The identification of differences among groups, especially for children facing problems in the family and school contexts (G1) in regard to social vulnerability, current maternal depression, and chronic adversity, characterizes a group that requires greater attention, as it is exposed to multiple risks. This information highlights the relevance of investigating the presence of cumulative risk in the family context to understand developmental outcomes among children (Evans et al., 2013 ; Goodman et al., 2011 ).

In regard to the identification of the predictive effect of cumulative risk variables and vulnerability, as potential predictors of behavioral problems among children, only maternal depression appears as an explanatory variable for the presence of behavioral problems among children in the context of multiple adverse conditions. These findings are in agreement with Bagner et al. ( 2010 ), who stress that living with maternal depression increases a child’s likelihood of presenting externalizing and internalizing behavioral problems up to the age of 12 years old. Therefore, maternal depression was the only adverse condition with the power to predict the behavioral problem outcome, confirming the relevance of considering such a variable when addressing child behavior, especially considering the high prevalence of depression among women of childbearing age (World Health Organization [WHO], 2017a , 2017b ).

As the positive aspects of this study, we highlight the presence of multiple informants, the methodological care adopted in the systematic assessment of the participants, and the use of validated instruments, in addition to the inclusion of diverse variables to identify, in the same sample, vulnerability indicators that potentially impact the behavior of school children. It is highlighted as the main strength of the study the inclusion of children in the groups considering the presence or absence of behavioral problems in the two main development contexts for the school period, namely, family and school, thus highlighting relevant variables associated with vulnerability and to developmental resources in both contexts, which may favor preventive care and target groups with potential risks.

This study’s limitations include the sample size, lack of a homogeneous distribution between groups in regard to the sex of children, and the identification of depressive symptoms using a screening instrument, which limit the generalization of results. Further studies adopting longitudinal designs, considering the influence of contextual risks over the course of a child’s development, including other sources of information, in addition to the reports of mothers, are needed, as well as observational measures. The relevance of inclusion in new studies of parents’/stepfathers’ evaluations, as well as studies that address the characteristics of the various family configurations in which children are inserted as conditions that can influence the behavior of the school-aged children, is also highlighted. Another relevant point to be considered in new studies is the inclusion of variables that may function as protective factors, which in a cumulative way to vulnerability and risk conditions may favor a more complete and complex analysis of the mechanisms that favor or hinder children’s behavioral problems.

Conclusions

In this study, low maternal educational level, low family income, the presence of more chronic adversity, and living with current maternal depression are factors associated with the outcome of behavioral problems among children in both family and school contexts, showing the importance of including such factors in assessment protocols intended to address the mental health of school-aged children. Note, however, that among these indicators, current maternal depression emerged as the most relevant variable in comparison to the remaining adversities analyzed here. Therefore, this condition requires specific care when implementing mental health actions.

Finally, these results can contribute to and have implications for the planning of mental health programs, confirming the relevance of identifying maternal depressive symptoms and multiple adversities, including social vulnerability indicators as conditions or events that demand attention.

Achenbach, T. M., Becker, A., Döpfner, M., Heiervang, E., Roessner, V., Steinhausen, H.-C., & Rothenberger, A. (2008). Multicultural assessment of child and adolescent psychopathology with ASEBA and SDQ instruments: Research findings, applications, and future directions. Journal of Child Psychology and Psychiatry , 49 (3), 251–275. https://doi.org/10.1111/j.1469-7610.2007.01867.x .

PubMed   Google Scholar  

Achenbach, T. M., Ivanova, M. Y., Rescorla, L. A., Turner, L. V., & Althoff, R. R. (2016). Internalizing/externalizing problems: Review and recommendations for clinical and research applications. Journal of the American Academy of Child & Adolescent Psychiatry , 55 (8), 647–656. https://doi.org/10.1016/j.jaac.2016.05.012 .

Google Scholar  

Angelini, A. L., Alves, I. C., Custódio, E. M., Duarte, W. F., & Duarte, J. L. (1999). Manual das Matrizes Progressivas Coloridas de Raven: escala especial. Manual . São Paulo: Centro Editor de Testes e Pesquisas em Psicologia.

Associação Brasileira de Empresas de Pesquisa. (2015). Critério Padrão de Classificação Econômica Brasil. Recuperado de http://www.abep.org/ .

Bagner, D. M., Pettit, J. W., Lewinsohn, P. M., & Seeley, J. R. (2010). Effect of maternal depression on child behavior: A sensitive period? Journal of the American Academy of Child & Adolescent Psychiatry , 49 (7), 699–707. https://doi.org/10.1016/j.jaac.2010.03.012 .

Barker, E. D., Copeland, W., Maughan, B., Jaffee, S. R., & Uher, R. (2012). The relative impact of maternal depression and associated risk factors on offspring psychopathology. The British Journal of Psychiatry , 200 (2), 124–129. https://doi.org/10.1192/bjp.bp.111.092346 .

PubMed   PubMed Central   Google Scholar  

Bele, S. D., Bodhare, T. N., Valsangkar, S., & Saraf, A. (2013). An epidemiological study of emotional and behavioral disorders among children in an urban slum. Psychology, Health & Medicine , 18 (2), 223–232. https://doi.org/10.1080/13548506.2012.701751 .

Bouvette-Turcot, A.-A., Unternaehrer, E., Gaudreau, H., Lydon, J. E., Steiner, M., & Meaney, M. J. (2017). The joint contribution of maternal history of early adversity and adulthood depression to socioeconomic status and potential relevance for offspring development. Journal of Affective Disorders , 207 , 26–31. https://doi.org/10.1016/j.jad.2016.08.012 .

Callender, K. A., Olson, S. L., Choe, D. E., & Sameroff, A. J. (2012). The effects of parental depressive symptoms, appraisals, and physical punishment on later child externalizing behavior. Journal of Abnormal Child Psychology , 40 (3), 471–483. https://doi.org/10.1007/s10802-011-9572-9 .

Carneiro, P., Meghir, C., & Parey, M. (2013). Maternal education, home environments, and the development of children and adolescents. Journal of the European Economic Association , 1 , 123–160. https://doi.org/10.1111/j.1542-4774.2012.01096.x .

Clark, D. A., Durbin, C. E., Hicks, B. M., Iacono, W. G., & McGue, M. (2017). Personality in the age of industry: Structure, heritability, and correlates of personality in middle childhood from the perspective of parents, teachers, and children. Journal of Research in Personality , 67 , 132–143. https://doi.org/10.1016/j.jrp.2016.06.013 .

Conners-Burrow, N. A., McKelvey, L., Perry, D., Whiteside-Mansell, L., Kraleti, S., Mesman, G., … Kyzer, A. (2016). Low-level symptoms of depression in mothers of young children are associated with behavior problems in middle childhood. Maternal and Child Health Journal , 20 (3), 516–524. https://doi.org/10.1007/s10995-015-1849-0 .

Correia, S. K. B., Saur, A. M., & Loureiro, S. R. (2014). Behavior of school children stratified by birth weight and gestational age. Psicologia: Teoria e Pesquisa , 30 (2), 179–188. https://doi.org/10.1590/S0102-37722014000200007 .

De Los Reyes, A., Augenstein, T. M., Wang, M., Thomas, S. A., Drabick, D. A., Burgers, D. E., & Rabinowitz, J. (2015). The validity of the multi-informant approach to assessing child and adolescent mental health. Psychological Bulletin , 141 (4), 858–900. https://doi.org/10.1037/a0038498 .

Duncombe, M. E., Havighurst, S. S., Holland, K. A., & Frankling, E. J. (2012). The contribution of parenting practices and parent emotion factors in children at risk for disruptive behavior disorders. Child Psychiatry & Human Development , 43 (5), 715–733. https://doi.org/10.1007/s10578-012-0290-5 .

Edwards, R. C., & Hans, S. L. (2015). Infant risk factors associated with internalizing, externalizing, and co-occurring behavior problems in young children. Developmental Psychology , 51 (4), 489. https://doi.org/10.1037/a0038800 .

Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin , 139 (6), 1342–1396. https://doi.org/10.1037/a0031808 .

Field, A. (2013). Discovering statistics using IBM SPSS Statistics. 4th edition. SAGE Publications, London. ISBN 978-1-4462-4971-8.

Fleitlich, B. W., Cortázar, P. G., & Goodman, R. (2000). Questionário de Capacidades e Dificuldades (SDQ). Infanto - Revista de Neuropsiquiatria da Infância e da Adolescência , 8 (1), 44–50.

Goodman, R. (1997). The strengths and difficulties questionnaire: a research note. Journal of Child Psychology and Psychiatry, 38, 581–586. https://doi.org/10.1111/j.1469-7610.1997.tb01545.x .

Goodman, S. H., Rouse, M. H., Connell, A. M., Broth, M. R., Hall, C. M., & Heyward, D. (2011). Maternal depression and child psychopathology: A meta-analytic review. Clinical Child and Family Psychology Review , 14 (1), 1–27. https://doi.org/10.1007/s10567-010-0080-1 .

Hildebrand, N. A., Celeri, E. H. R. V., Morcillo, A. M., & Zanolli, M. D. L. (2015). Domestic violence and risk for mental health in childhood and adolescence. Psicologia: Reflexão e Crítica , 28 (2), 213–221. https://doi.org/10.1590/1678-7153.201528201 .

Johnson, S., Hollis, C., Marlow, N., Simms, V., & Wolke, D. (2014). Screening for childhood mental health disorders using the Strengths and Difficulties Questionnaire: The validity of multi-informant reports. Developmental Medicine & Child Neurology , 56 (5), 453–459. https://doi.org/10.1111/dmcn.12360 .

Kessler, R. C. (2012). The costs of depression. The Psychiatric Clinics of North America , 35 (1), 1–14. https://doi.org/10.1016/j.psc.2011.11.005 .

Kovess, V., Carta, M. G., Pez, O., Bitfoi, A., Koç, C., Goelitz, D., … Otten, R. (2015). The school children mental health in Europe (SCMHE) project: Design and first results. Clinical Practice & Epidemiology in Mental Health , 11 (1), 113–123. https://doi.org/10.2174/1745017901511010113 .

Kroenke, K., Spitser, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine , 16 (9), 606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x .

Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310 .

Leis, J. A., Heron, J., Stuart, E. A., & Mendelson, T. (2014). Associations between maternal mental health and child emotional and behavioral problems: Does prenatal mental health matter? Journal of Abnormal Child Psychology , 42 (1), 161–171. https://doi.org/10.1007/s10802-013-9766-4 .

Linhares, M. B. M., & Martins, C. B. S. (2015). The self-regulation process on child development. Estudos de Psicologia (Campinas) , 32 (2), 281–293. https://doi.org/10.1590/0103-166X2015000200012 .

Loosli, L., Pizeta, F. A., & Loureiro, S. R. (2016). School-age children who live with recurrent maternal depression: Differences between the sexes. Psicologia: Teoria e Pesquisa , 32 (3), 1–10. https://doi.org/10.1590/0102-3772e32322 .

De Los Reyes, A., Thomas, S. A., Goodman, K. L., & Kundey, S. M. (2013). Principles underlying the use of multiple informants’ reports. Annual Review of Clinical Psychology , 9 , 123–149 Recuperado de https://pdfs.semanticscholar.org/4508/6bb381dbf14491e656a95f0d6f57e635adfc.pdf .

Macana, E. C., & Comim, F. (2015). O papel das práticas e estilos parentais no desenvolvimento da primeira infância. In G. A. Pluciennik, M. C. Larazzari, & M. F. Chicaro (Eds.), Fundamentos da família como promotora do desenvolvimento infantil: parentalidade em foco , (pp. 34–47). São Paulo: Fundação Maria Cecília Souto Vidigal Recuperado de http://agendaprimeirainfancia.org.br/arquivos/Fundamentos_Familia.pdf .

Maroco, J. (2014). Análise estatística com o SPSS Statistics . Pêro Pinheiro: Report Number.

Martel, M. M., Markon, K., & Smith, G. T. (2017). Research review: Multi-informant integration in child and adolescent psychopathology diagnosis. Journal of Child Psychology and Psychiatry , 58 (2), 116–128. https://doi.org/10.1111/jcpp.12611 .

Martoni, A. T., Trevisan, B. T., Dias, N. M., & Seabra, A. G. (2016). Funções executivas: relação entre relatos de pais, de professores e desempenho de crianças. Temas em Psicologia , 24 (1), 173–188. https://doi.org/10.9788/TP2016.1-12 .

Marturano, E. M. (1999). Recursos no ambiente familiar e dificuldades de aprendizagem na escola. Psicologia: Teoria e Pesquisa , 15 (2), 135–142 Recuperado de http://dx.doi.org/10.1590/S0102-37721999000200006 .

Marturano, E. M. (2013). A criança, a família, a escola e a transição para o ensino fundamental. In E. C. Konkiewitz (Ed.), Aprendizagem, comportamento e emoções na infância e adolescência: uma visão transdisciplinar , (pp. 47–68). Dourados: UFGD.

Miller, L. D., Martinez, Y. J., Shumka, E., & Baker, H. (2014). Multiple informant agreement of child, parent, and teacher ratings of child anxiety within community samples. The Canadian Journal of Psychiatry , 59 (1), 34–39. https://doi.org/10.1177/070674371405900107 .

Muniz, M., Gomes, C. M. A., & Pasian, S. R. (2016). Factor structure of Raven’s Coloured Progressive Matrices. Psico-USF , 21 (2), 259–272. https://doi.org/10.1590/1413-82712016210204 .

Osório, F. L., Mendes, A. V., Crippa, J. A., & Loureiro, S. R. (2009). Study of the discriminative validity of the PHQ-9 and PHQ-2 in a sample of Brazilian women in the context of primary health care. Perspectives in Psychiatric Care , 45 (3), 216–227. https://doi.org/10.1111/j.1744-6163.2009.00224.x .

Piccolo, L. R., Falceto, O. G., Fernandes, C. L., Levandowski, D. C., Grassi-Oliveira, R., & Salles, J. F. (2012). Psychosocial variables and reading performance of children with low socioeconomic status. Psicologia: Teoria e Pesquisa , 28 (4). https://doi.org/10.1590/S0102-37722012000400004 .

Pizato, E. C. G., Marturano, E. M., & Fontaine, A. M. G. V. (2014). Trajectories of social skills and behavior problems in primary school: Influence of early childhood education. Psicologia: Reflexão e Crítica , 27 (1), 189–197. https://doi.org/10.1590/S0102-79722014000100021 .

Pizeta, F. A., Silva, T. B. F., Cartafina, M. I. B., & Loureiro, S. R. (2013). Maternal depression and risks for children s behavior and mental health: A review. Estudos de Psicologia (Natal) , 18 (3), 429–437. https://doi.org/10.1590/S1413-294X2013000300003 .

Saur, A. M., & Loureiro, S. R. (2015). Mental health of small children for normal gestational age: A cohort study from Southeastern Brazil. Psicologia: Reflexão e Crítica , 28 (1), 204–212. https://doi.org/10.1590/1678-7153.201528122 .

Spitzer, R. L., Kroenke, K., & Williams, J.B.W. (1999). The Patient Health Questionnaire Primary Care Study Group, Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. Journal of American Medicine Association, 282(18), 1737–1744. https://doi.org/10.1001/jama.282.18.1737 .

Walsh, F. (2016). Processos normativos da família: diversidade e complexidade . Porto Alegre: Artmed.

Wang, F., Christ, S. L., Mills-Koonce, W. R., Garrett-Peters, P., & Cox, M. J. (2013). Association between maternal sensitivity and externalizing behavior from preschool to preadolescence. Journal of Applied Developmental Psychology , 34 (2), 89–100. https://doi.org/10.1016/j.appdev.2012.11.003 .

Woerner, W., Fleitlich-Bilyk, B., Martinussen, R., Fletcher, J., Cucchiaro, G., Dalgalarrondo, P., … Tannock, R. (2004). The Strengths and Difficulties Questionnaire overseas: Evaluations and applications of the SDQ beyond Europe. European Child & Adolescent Psychiatry , 13 (2), 47–54. https://doi.org/10.1007/s00787-004-2008-0 .

World Health Organization [WHO]. (2017a). Depression and other common mental disordes: global health estimates. World Health Organization . Recuperado de http://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf;jsessionid=D941E8D6BCD7068FF960F8ACF5312F39?sequence=1 . Accessed Jan 2018

World Health Organization [WHO]. (2017b). Policy options on mental health . Recuperado de http://apps.who.int/iris/bitstream/10665/259406/1/9789241513296-eng.pdf?ua=1 . Accessed Jan 2018

Download references

Acknowledgements

Not applicable in this section

To the development of this research, we counted on the financial support of the National Council for Scientific and Technological Development (CNPq/Brazil) under number 307394/2014-0.

Availability of data and materials

All data necessary to understand the results and analyses presented are found throughout the manuscript, and no additional files were submitted.

Author information

Authors and affiliations.

Universidade de São Paulo (USP), Rua Tenente Catão Roxo, 2650, Ribeirão Preto, SP, CEP: 14051-140, Brazil

Ana Karina Braguim Martineli, Fernanda Aguiar Pizeta & Sonia Regina Loureiro

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to the preparation of this manuscript, approved the submission of their current version, and show their agreement with the publication fee, which will be charged if the manuscript obtains final acceptance. All authors contributed to the conceptualization of the research, to the formal analysis. The first author has a master’s degree and was responsible for data collection.

Corresponding author

Correspondence to Ana Karina Braguim Martineli .

Ethics declarations

Ethics approval and consent to participate.

All the ethical aspects described by the Helsinki Declaration were considered in this manuscript and during the data collection, all the participants signed a consent term, and the study was approved by the Research Ethics Committee of the Faculty of Philosophy, Sciences and Letters of Ribeirão Preto (USP) under number 36415514.5.0000.5407.

Consent for publication

The manuscript was not submitted to another journal, and everyone involved in this research agreed that the work was submitted for publication. If the article is accepted for publication, the copyright will be transferred to Psychology: Reflection and Critical.

Competing interests

The authors declare that they have no competing interests and that this manuscript was not submitted for publication to any other periodical or means of publication.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Martineli, A.K.B., Pizeta, F.A. & Loureiro, S.R. Behavioral problems of school children: impact of social vulnerability, chronic adversity, and maternal depression. Psicol. Refl. Crít. 31 , 11 (2018). https://doi.org/10.1186/s41155-018-0089-9

Download citation

Received : 20 July 2017

Accepted : 02 March 2018

Published : 04 June 2018

DOI : https://doi.org/10.1186/s41155-018-0089-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• School children
• Adversities
• Maternal depression
• Social vulnerability

Advertisement

Ten scientific problems in human behavior understanding

• Regular Paper
• Published: 02 January 2019
• Volume 1 , pages 3–9, ( 2019 )

Cite this article

• Zhiwen Yu 1 ,
• He Du   ORCID: orcid.org/0000-0002-9547-1459 1 ,
• Zhu Wang 1 &
• Bin Guo 1  

3597 Accesses

19 Citations

Explore all metrics

Human behavior understanding is of great importance for a variety of applications, such as personalized recommendations, smart home, urban planning, and anti-terrorism. Although there has been significant progress on the understanding of human behaviors, we still face a number of theoretical and technical challenges that need be further explored. In this article, we first outline the basic research process of human behavior understanding based on existing studies, and illustrate important issues in each step. Afterwards we describe main research challenges from the aspects of human behavior itself, the behavior related data, as well as the modeling and evaluations, respectively. Then we identify and explore ten most important fundamental open problems in this field. The proposed problem list is expected to provoke innovative studies on human behavior understanding, e.g., theory improvement and data collaboration. In this article, we also discuss possible ways that would be helpful for resolving the challenging problems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

A View on the Development and Current Situation of Behavior Analysis in Europe

Putting human behavior predictability in context

On the Need to Understand Human Behavior to Do Analytics of Behavior

https://community.apan.org/wg/afosr/m/alea_stewart/135113/download .

https://sproutsocial.com/insights/new-social-media-demographics/ .

Chen, L., Hoey, J., Nugent, C.D., Cook, D.J., Yu, Z.: Sensor-based activity recognition. IEEE Trans. Syst. Man. Cybern. Part C 42 (6), 790–808 (2012)

Article   Google Scholar  

Barabási, A.-L.: The origin of bursts and heavy tails in human dynamics. Nature 435 (7039), 207–211 (2005)

Song, C., Qu, Z., Blumm, N., Barabási, A.-L.: Limits of predictability in human mobility. Science 327 (5968), 1018–1021 (2010)

Article   MathSciNet   MATH   Google Scholar  

Subrahmanian, V., Kumar, S.: Predicting human behavior: the next frontiers. Science 355 (6324), 489–489 (2017)

Youyou, W., Kosinski, M., Stillwell, D.: Computer-based personality judgments are more accurate than those made by humans. Proc. Natl. Acad. Sci. 112 (4), 1036–1040 (2015)

Kramer, A.D., Guillory, J.E., Hancock, J.T.: Experimental evidence of massive-scale emotional contagion through social networks. Proc. Natl. Acad. Sci. 111 (24), 8788–8790 (2014)

Yu, Z., Du, H., Xiao, D., Wang, Z., Han, Q., Guo, B.: Recognition of human computer operations based on keystroke sensing by smartphone microphone. IEEE Int. Things J. 5 (2), 1156–1168 (2018)

Du, H., Yu, Z., Yi, F., Wang, Z., Han, Q., Guo, B.: Recognition of group mobility level and group structure with mobile devices. IEEE Trans. Mob. Comput. 17 (4), 884–897 (2018)

Mislove, A., Lehmann, S., Ahn, Y.-Y., Onnela, J.-P., Rosenquist, J.N.: Understanding the demographics of twitter users. ICWSM 11 , 5 (2011)

Google Scholar  

Liang, Y., Zhou, X., Yu, Z., Guo, B.: Energy-efficient motion related activity recognition on mobile devices for pervasive healthcare. Mob. Netw. Appl. Spring. Press 19 (3), 303–317 (2014)

Yu, Z., Yi, F., Lv, Q., Guo, B.: Identifying on-site users for social events: mobility, content, and social relationship. IEEE Trans. Mob. Comput. 17 (9), 2055–2068 (2018)

Yu, Z., Wang, H., Guo, B., Gu, T., Mei, T.: Supporting serendipitous social interaction using human mobility prediction. IEEE Trans. Hum. Mach. Syst. 45 (6), 811–818 (2015)

Pan, B., Zheng, Y., Wilkie, D., Shahabi, C.: Crowd sensing of traffic anomalies based on human mobility and social media. In: Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, pp. 344–353 (2013)

Ruths, D., Pfeffer, J.: Social media for large studies of behavior. Science 346 (6213), 1063–1064 (2014)

Wang, L., Yu, Z., Guo, B., Ku, T., Yi, F.: Moving destination prediction using sparse dataset: a mobility gradient descent approach. ACM Trans. Knowl. Discov. Data 11 (3), Article No. 37 (2017)

Zhang, D., Wang, H., Wu, D.: Toward centimeter-scale human activity sensing with WI-FI signals. IEEE Comput. 50 (1), 48–57 (2017)

Wang, Z., Guo, B., Yu, Z., Zhou, X.: Wi-Fi CSI based behavior recognition: from signals, actions to activities. IEEE Commun. Magn. 56 (5), 109–115 (2018)

Morris, M. R., Inkpen, K., Venolia, G.: Remote shopping advice: enhancing in-store shopping with social technologies. In: Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, ACM, pp. 662–673 (2014)

Yi, F., Yu, Z., Chen, H., Du, H., Guo, B.: Cyber-physical-social collaborative sensing: from single space to cross-space. Front. Comput. Sci. 12 (4), 609–622 (2018)

von Ahn, L., Maurer, B., McMillen, C., Abraham, D., Blum, M.: reCAPTCHA: human-based character recognition via web security measures. Science 321 (5895), 1465–1468 (2008)

Download references

Acknowledgements

This work was supported in part by the National Science Fund for Distinguished Young Scholars (No. 61725205), the National Basic Research Program of China (No. 2015CB352400), and the National Natural Science Foundation of China (Nos. 61332005, 61772428).

Author information

Authors and affiliations.

Northwestern Polytechnical University, Xi’an, 710072, People’s Republic of China

Zhiwen Yu, He Du, Fei Yi, Zhu Wang & Bin Guo

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Zhiwen Yu .

Rights and permissions

Reprints and permissions

About this article

Yu, Z., Du, H., Yi, F. et al. Ten scientific problems in human behavior understanding. CCF Trans. Pervasive Comp. Interact. 1 , 3–9 (2019). https://doi.org/10.1007/s42486-018-00003-w

Download citation

Received : 12 September 2018

Accepted : 24 October 2018

Published : 02 January 2019

Issue Date : 01 May 2019

DOI : https://doi.org/10.1007/s42486-018-00003-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Human behavior understanding
• Scientific problems
• Behavior characteristics
• Data analysis
• Modeling and evaluation
• Find a journal
• Publish with us
• Track your research

The Library Is Open

The Wallace building is now open to the public. More information on services available.

• RIT Libraries
• Social/Behavioral Sciences Research Guide

Identifying a Research Problem

This InfoGuide assists students starting their research proposal and literature review.

• Introduction
• Research Process
• Types of Research Methodology
• Data Collection Methods
• Anatomy of a Scholarly Article
• Finding a topic
• Problem Statement
• Research Question
• Research Design
• Search Strategies
• Psychology Database Limiters
• Literature Review Search
• Annotated Bibliography
• Writing a Literature Review
• Writing a Research Proposal

A  research problem  is a specific issue or gap in existing knowledge that you aim to address in your research. You may look for practical problems aimed at contributing to change or theoretical problems aimed at expanding knowledge.

Some research will do both of these things, but usually, the research problem focuses on one or the other. The research problem you choose depends on your broad  topic  of interest and the  type of research  you think will fit best.

This section helps you identify and refine a research problem. When writing your  research proposal  or  introduction , formulate it as a  problem statement  and/or  research questions .

Research Problems Steps

Why is the research problem important?

Having an interesting topic isn’t a strong enough basis for academic research. Without a well-defined research problem, you will likely end up with an unfocused and unmanageable project.

You might end up repeating what other people have already said, trying to say too much, or doing research without a clear purpose and justification. You need a clear problem to research that contributes new and relevant insights.

Whether planning your  thesis , starting a  research paper , or writing a  research proposal , the research problem is the first step towards knowing exactly what you’ll do and why.

Identify a broad problem area As you read about your topic, look for under-explored aspects or areas of concern, conflict, or controversy. Your goal is to find a gap that your research project can fill.

Practical research problems If you are doing practical research, you can identify a problem by reading reports, following up on previous research, or talking to people who work in the relevant field or organization. You might look for:

• Issues with performance or efficiency
• Processes that could be improved
• Areas of concern among practitioners
• Difficulties faced by specific groups of people Examples of practical research problems
• Voter turnout in New England has been decreasing, in contrast to the rest of the country.
• The HR department of a local chain of restaurants has a high staff turnover rate.

A non-profit organization faces a funding gap that means some of its programs will have to be cut

Theoretical research problems If you are doing theoretical research, you can identify a research problem by reading existing research, theory, and debates on your topic to find a gap in what is currently known about it. You might look for:

• A phenomenon or context that has not been closely studied
• A contradiction between two or more perspectives
• A situation or relationship that is not well understood
• A troubling question that has yet to be resolved Examples of theoretical research problems
• The effects of long-term Vitamin D deficiency on cardiovascular health are not well understood.
• The relationship between gender, race, and income inequality has yet to be closely studied in the context of the millennial gig economy
• Historians of Scottish nationalism disagree about the role of the British Empire in developing Scotland’s national identity.

Learn more about the problem Next, you have to find out what is already known about the problem and pinpoint the exact aspect that your research will address. Context and background

• Who does the problem affect?
• Is it a newly-discovered problem, or a well-established one?
• What research has already been done?
• What, if any, solutions have been proposed?
• What are the current debates about the problem? What is missing from these debates?

Specificity and relevance

• What particular place, time, and/or group of people will you focus on?
• What aspects will you not be able to tackle?
• What will the consequences be if the problem is not resolved Example of a specific research problem A local non-profit organization that alleviates food insecurity has always fundraised from its existing support base. It lacks an understanding of how best to target potential new donors. To continue its work, the organization requires research into more effective fundraising strategies.

Once you have narrowed down your research problem, the next step is to formulate a  problem statement , as well as your  research questions  or  hypotheses .

• << Previous: Finding a topic
• Next: Problem Statement >>

Edit this Guide

Log into Dashboard

Use of RIT resources is reserved for current RIT students, faculty and staff for academic and teaching purposes only. Please contact your librarian with any questions.

Help is Available

Email a Librarian

A librarian is available by e-mail at [email protected]

Meet with a Librarian

Call reference desk voicemail.

A librarian is available by phone at (585) 475-2563 or on Skype at llll

Or, call (585) 475-2563 to leave a voicemail with the reference desk during normal business hours .

Chat with a Librarian

Social/behavioral sciences research guide infoguide url.

https://infoguides.rit.edu/researchguide

Use the box below to email yourself a link to this guide

• Research article
• Open access
• Published: 19 May 2020

A qualitative research of adolescents with behavioral problems about their experience in a dialectical behavior therapy skills training group

• Eva Sesma Pardo   ORCID: orcid.org/0000-0003-2150-1616 1 ,
• Aránzazu Fernández Rivas 1 , 2 ,
• Pablo Orgaz Barnier 1 ,
• Marina Beá Mirabent 1 ,
• Iñaki Kerexeta Lizeaga 1 ,
• Aída Díaz Cosgaya 1 ,
• Ana Catalán Alcántara 1 , 2 ,
• Esther Vivanco González 1 ,
• Blaise Aguirre 3 , 4 &
• Miguel Angel González Torres 1 , 2  

BMC Psychiatry volume  20 , Article number:  245 ( 2020 ) Cite this article

8552 Accesses

9 Citations

1 Altmetric

Metrics details

Several quantitative studies support the effectiveness of the Dialectical Behavior Therapy (DBT) psychosocial skills training group component for adolescents with impulse-control disorder and/or emotional dysregulation. However, qualitative research to assess this psychotherapeutic tool in the adolescent population is sparse. This study aims to examine the subjective experience of adolescents with behavioral issues who have completed DBT skills training group, as well as using this experience to extract hypotheses regarding its usefulness which can then be verified at a later time by means of quantitative instruments.

We developed a qualitative study by using focus groups with adolescents ( N  = 20) whose diagnosis includes symptoms such as behavior disorder, impulse-control disorder and/or emotional dysregulation, and good informants, who have completed DBT skills training. Three focus groups were created.

The subjective experience of adolescents who have completed a DBT skills training group is collected in four main categories: experience of illness, motivation for therapy, experience of therapy and results of the therapy.

Conclusions

Adolescents with behavioral problems assess their participation in the DBT skills training group positively, even recommending its usefulness to healthy population. Beyond learning skills, they emphasize the intrapsychic changes (as improvement in reflective activity) that they objectify after the group experience.

Peer Review reports

Adolescence can be seen as a period of coping with a variety of challenges, necessary for normal development [ 1 ]. During adolescence, emotional dysregulation leading to impulsivity and the emergence of behavioral problems is common [ 2 ]. Emotional dysregulation consists of poor control over his or her own affective expression in different situations. It is characterized by little flexibility and spontaneity, lack of control and disruptive behaviors. Following Linehan’s biosocial model, we conceptualize emotion dysregulation in borderline personality disorder (BPD) as consisting of four components: emotion sensitivity, heightened and labile negative affect, a deficit of appropriate regulation strategies, and a surplus of maladaptive regulation strategies. Emotional dysregulation is a dimensional entity, not exclusively related to any specific disorder and may be present both in externalizing and internalizing disorders [ 3 , 4 , 5 ].

Dialectical behavior therapy (DBT) was developed specifically to address Borderline Personality Disorder (BPD). It includes four components: individual therapy, psychosocial skills training, telephone coaching for patients, and a supervision team for the therapists [ 6 , 7 ]. DBT is conceptualized as a transdiagnostic treatment [ 8 ], the aim of which is to help the patient initiate functional behavior, even when they are experiencing very intense emotions [ 9 ]. Skills training appears to be the most effective component of DBT when emotional dysregulation predominates [ 10 ] and also for adolescent patients [ 11 , 12 , 13 ]. It includes five modules (mindfulness, distress tolerance - DT, emotion regulation - ER, interpersonal effectiveness -IE, and walking the middle path) taught throughout sixteen weeks in group format. Mindfulness and DT are the skills most valued by adolescents [ 14 , 15 ].

Several quantitative studies support the effectiveness of DBT for adolescent populations who present multiple problems [ 16 , 17 , 18 , 19 ] including BPD traits, suicidal and/or self-injurious ideation and behavior [ 20 , 21 , 22 , 23 , 24 , 25 ]. Furthermore, preliminary effectiveness of DBT for pre-adolescent children with mood disruptive dysregulation disorder has also been reported in a randomized controlled trial [ 26 ].

The subjective view of young adults treated with DBT regarding the process and outcome of the therapy has been explored using qualitative methodology. Factors such as therapeutic relationship, self-motivation to change, validation and the perception of genuine interest in the support offered by the leaders of the skills group, are described as fundamental components to the improvement experienced [ 27 , 28 , 29 ]. The most valued skills were mindfulness and DT [ 30 ].

Even though DBT for adolescents has provided consistent evidence of efficacy, there are often patients who drop out, others who show insufficient outcomes and some others who find difficulties in adapting to the requirements of participation in skills groups. We think the exploration of the subjective experience of participants with a qualitative methodology could provide potentially interesting insights regarding ways to deal with those problems. Besides that, we believe the qualitative exploration of subjective experience in a group context could not only add to the existing knowledge about emotional dysregulation and interpersonal difficulties shown by those patients but could also give us clues to a better understanding of the healing process itself.

We conducted a study employing qualitative methods with the following objectives: (i) To better understand the subjective experience of adolescents with behavioral problems who have participated in DBT skills training groups, (ii) To assess the perceived usefulness of those skills, and (iii) To ascertain the subjective benefit from participating in a group as a place of learning with peers and authority figures.

Qualitative methodology is essential for health sciences when studying aspects unapproachable by other methodologies. These elements include values, attitudes, expectations, and the impact of suffering and sociocultural factors that influence health and illness. Within those methods of a qualitative nature, we chose focus groups due to the advantages they offer [ 31 ]. The key data generated by focus groups is the narratives of those participating [ 32 , 33 , 34 ]. The research team for our current study was composed of clinicians with experience in the field of psychotherapy and qualitative research [ 35 ].

Selection of the sample

Skills training groups for adolescents have been conducted by the Psychiatry Service of Basurto University Hospital (Bilbao), since January 2010. In parallel, their parents and families were offered similar groups. Adolescents who completed the skills training group (16 weekly sessions) and had shown during the process sufficient capacity to articulate opinions and disposition to share them, were considered as “good informants”. All those who met inclusion criteria (Table  1 ) were contacted by telephone and invited to participate. Their participation was voluntary and they received no incentive.

We contacted 30 patients of which 24 agreed to participate. After parents and adolescents signed informed consent, they were enrolled and allocated to different focus groups. Of the 24 enrolled, four candidates did not attend the focus group providing no reason or explanation. We performed three focus groups with 20 participants. In focus group number 1, 7 participants were cited and 6 attended. In focus group number 2, 7 participants were cited and 6 attended. In focus group 3, 10 participants were cited and 8 of them attended.

The sample consisted of 20 adolescents (mean age 15.40; SD 1.39). Sociodemographic and clinical data are shown in Table  2 . All assessments and diagnoses were performed by a senior Child and Adolescent psychiatrist using DSM-IV-TR [ 36 ] prior to inclusion in the skills training group.

Focus groups and data collection

The research team had previously met before starting the focus groups to prepare a script delineating the scope of inquiry. We agreed upon a set of questions covering topics that in our view merited initial exploration. Two weeks earlier, we piloted these questions with two individuals who had met inclusion criteria in order to establish the utility of the questions as well as to identify unconsidered topics. After determining that the question-set would provide insightful commentary, the questions were put forward to the entire focus group. After completing the first focus group, two researchers independently studied the videotapes and transcripts. Then, all the researchers agreed on adapting the initial questioning path integrating the new ideas expressed in the first group. This process was also repeated after the second group. After completing the third focus group, it was considered that information saturation (no new information added) had been achieved. Groups of ninety minutes duration were performed and were led by two researchers unknown to the participants. A trusting and empathic environment was actively promoted [ 35 ].

Data analysis

The data analysis process is shown in Fig.  1 . The transcript documents were the primary data source. Each of the researchers first performed an in-depth independent reading and then proceeded to the categorization stage. Research team met twice a week to share their findings and reviewed disagreements and discrepancies until a final consensus regarding categorization was reached.

Outline of data analysis process

Analysis of the transcriptions, as required by qualitative methodology (exploratory, inductive and ethnographic), was based on Grounded Theory [ 32 ] .The discourse is codified, broken down into units of meaning, and categorized by a procedure of progressive abstraction from a textual level to a conceptual level by applying the constant comparative method. For the qualitative analysis of the data, we used the MAXQDA software program (version 12) [ 37 ].

Ideas expressed by the participants were grouped into four categories: experience of illness, motivation for therapy, experience of therapy, and results of therapy (Table  2 ).

Experience of illness

• Emotional dysregulation

Adolescents reported the difficulties they had in regulating emotions as a core issue. The blocking of communication or the failure of a mechanism such as emotional restraint, may later lead to the appearance of mood disorders and behavioral dyscontrol.

“And what I did was try to keep it in, keep it in (the distress) and … it worked until I burst” (A; Male, 23).

Behavioral dyscontrol

They describe behavioral dyscontrol, with an aggressive undertone, as a way of regulating emotions.

“she (mother) didn’t do anything wrong, but for the most trivial reasons, like if she would disagree with me, I’d hit her to vent my anger” (A; female, 16).

Identity issues

Adolescents describe identity issues in relation to poor or devalued self-concept, and perceive the identity of sufferer as immutable.

“Well I was a person who … let’s say … lived for her illness … let’s say I thought I was my own illness and I don’t know, I didn’t want to change” (M; female, 19).

Global functional deterioration

They observe how their symptoms have a direct impact on their global functional behavior, describing it as a vital break with a pre-existing global functional deterioration.

“I quit going to class for a year, broke up with the boyfriend I had for a long time, stopped going out with my best friends … it was awful with my family … so yeah, there were repercussions” (A; female, 17).

Environmental feedback

The environment responds to the problems of adolescents in various ways. Sometimes it can act as an aid by offering support and external containment,

“The thing is, in my case, my parents have always been there for me, they’ve been the ones who’ve helped me in everything, I’ve never had any kind of problem with my parents … ” (Y; male, 17).

however, in other cases it can make problems worse, in invalidating environments or where the stigma attached to mental illness is manifestly present.

“They’ve even called me a mental bitch, crazy … all sorts of names” (E; female, 17).

Motivation for therapy

Time factor.

Adolescents state that motivation for therapy varies depending on the moment of the illness course.

“I think it (the therapy) came at just the right time and … maybe what I was referring to was that … this was the beginning of realizing something was wrong with me, I don’t know how to explain it, this helped me realize” (M; female, 19).

Group attendance

It is suggested that group attendance may represent an objective parameter to assess motivation for change and active involvement in therapy.

“I only missed once (one group session) and it was ‘cause I had my tonsils removed, I wanted to change and took it very seriously” (E; female, 17).

Resistance to change

Resistance to change and consequently to receive help at some point during the course of their illness is another characteristic shared by adolescents.

“and well, I didn’t think I wanted to change, nor I felt comfortable or with the strength to change, I didn’t want no help, it’s happened to all of us at some point” (T; female, 21).

Self-motivation for treatment

The importance of self-motivation for change is stressed as an essential factor for the effectiveness of therapy. Without it, the therapy does not work.

“You know, if a person doesn’t want to change, they’ll never change, like, even if someone goes to lots of groups, lots of therapies or even if they travel to 50 different countries to do different therapies, that doesn’t matter, if someone isn’t willing to change, they won’t change” (L; female, 17).

Experience of therapy

Group frame.

Those participating in this study mention certain positive aspects within the group space such as being psychopathologically heterogeneous groups,

“No one else (in the therapy) had my same problem and I think this was good, cause if I’d found people who were as angry as I was at the world … it wouldn’t have done me no good” (A; male, 22).

and the participatory approach as a differentiating characteristic from other therapies.

“(the therapist) for example he made us go up to the blackboard, to explain it, participate … it was like … he made us study the theory, to put it some way, and then would ask us to come up and explain it … , it was different from other groups” (N; female, 18).

The adolescents see some aspects of the group space as therapeutic in themselves. For example, they define the group space as a validating space where there is no room for stigma

“Precisely when I was at my worst I thought I wanted to have someone to talk to who would understand me, so I could share it, that was enough to calm me down” (L; female, 17).

and where interpersonal relationships are encouraged, forming group cohesion.

“And there was a boy (in the group) who was a metalhead, he was great, we would laugh so much … and that would also help me to get better, that good relationship … ” (T; female, 21).

“Well … I don’t know, both of us helped each other to get better and get out of the hell we were in and all” (I; male, 20).

Those participating in this study point out the importance of the images and graphics to help understand the skills,

“I remember the circles, which was rational (mind), irrational or something like that” (A; female, 17).

“I think that one about the emotional, rational (mind) … wise mind, I think that’s what stuck with me the most ‘cause it was an image … you know, it was plain simple” (A; female, 16).

which, in turn, coincides with the importance given to mindfulness, as mindfulness and DT are the most valued skills.

“But that thing about the wise mind and the emotional mind did stick with me” (L; female, 17).

“I will remember this lesson all my life, I use it a lot, it was an exercise which said suffering equals pain plus lack of acceptance, and when you accept that pain, it’s no longer suffering and only the pain remains, this has helped me greatly” (A; female, 18).

However, they do not associate the usefulness of homework with the generalization of the skills learned in the group as the therapists instructed them.

“Yeah, I always (did the homework), ‘cause I felt it was an obligation, I’m not sure if it helped me a lot but I did do it” (L; female, 17).

It is suggested that skills implementation should be done unconsciously, in situations without a high emotional load, where acting with a wise mind is easier.

“Yeah, that’s it, since the beginning what he (the therapist) taught us was what to do in situations like that, so I would always try to put it to the test, I even got the point where I could do it without thinking” (S; female, 15).

“If the anger, let’s say, wasn’t of a very high level, I could do it (apply the skills) without realizing it” (O; female, 15).

Nevertheless, if the situation poses a high emotional load then the implementation of the skills has to be done consciously, with total awareness, since acting with a wise mind is more difficult.

“Well, I remember one time I was in Mathematics class with the teacher I loved so much (sarcasm). I didn’t' want to argue with him in class again so I started to shriek “come on wise mind, wise mind” everyone was freaking out while I kept on “wise mind, wise mind” so I wouldn’t swear at him, ‘cause otherwise I would disrespect him like I always did” (N; female, 15).

Relationship with peers

Adolescents observe that the relationship with peers in the skills groups serves as a measuring tool to assess their own severity.

“Compared to the other girls I was with (in the group), my problems didn’t seem that bad” (S; female, 15).

and point out that the phenomenon of universalization is a relief factor at the beginning of therapy.

“I realized there were more people (in the group) other than me who were ill, and, let’s say that doesn’t make you feel so lonely … ” (M; female, 19).

Relationship with therapists

Regarding the relationship with therapists, emphasis is placed on the need for their presence in order to regulate communication among the peers in the groups,

“I left the (WhatsApp) group chat … in any group of people with problems there has to be a therapist in between. Always” (L; female, 17).

and they value the therapist’s genuine interest to help as a crucial quality that contributes to their improvement.

“they (the therapists) would motivate you a lot, I remember I didn’t do the homework the first time I came here ‘cause I wasn’t motivated at all. Then the second time when I did it, he (the therapist) congratulated me, when I got the stuff done, when I did it well” (N; female, 18).

“they worried about what things served us the most to get better in the future, I don’t know, that was it in general, they were really implicated … ” (A; female, 17).

Results of the therapy

Positive assessment.

Adolescents assessed the skills training group (DBT) positively and recommended its potential usefulness in a healthy population.

“Well, I thought it was all very interesting and that’s something which is supposed to be basic but I think it should be way more in people’s minds, not only in our case; people who have problems, but in everyone else’s” (A; female, 17).

They have a realistic view of the results, being aware of the reversibility of the change, the results become noticeable over time and, likewise, last for a while.

“and eventually, as time went by (in the therapy) I did end up feeling an improvement” (O; female 15).

“yeah, but … even though, I think, to me, considering what I’m seeing lately, the group has served me just for some time ‘cause now I’m beginning to feel bad again” (I; male, 20).

The results are not idealized. Participants describe partial improvement and point out how difficulties in generalizing skills in certain situations still persist, especially those with a high emotional load.

“yeah, mine (the illness) stopped some time ago but I’m still having some bad periods … ” (M; female, 19).

The adolescents state that for the skills to work, motivation for change is essential, where life goals and self-reinforcement come into play.

“So I think all of us have experienced that what really makes us change is that we want to change, cause no one can do nothing for us, we have to take that kind of initiative like, alright, I’m gonna get better … ” (A; female, 16).

Acquiring abilities

The participants state that they acquire behavioral ability in the DBT skills training group to more adaptively cope with crisis situations and use tools to understand their own suffering. This on turn leads them to become aware of the difficulties they present and provide them with an understanding about their illness,

“I think (the therapy) came at the perfect time and … what I meant was that … this was the beginning of realizing something was wrong with me, I don’t know how to explain it … this helped to … stop seeing everything in black and white and lose control” (M; female, 19).

“to also make me realize that one can’t make a big deal out of everything (when asked, How did the therapy help you?)” (A; female, 16).

Intrapsychic changes

In parallel, intrapsychic changes occur, such as improvements in reflective activity. Projection is replaced by reflection, which allows patients to theorize about their illness from the observing self and to give meaning to their previous experience of suffering.

“every time I felt I wasn’t welcomed cause I had done something bad … to stop feeling upset, sometimes I would take two or three pills so I could swallow them … so I could feel as if I was swallowing my pain or something, to find something which would hurt me physically and not psychologically” (N; female, 15).

“cause you end up harming yourself … to forget the psychological pain through physical pain” (M; female, 19).

Adolescents in the skills training groups become aware of their problems and start to reflect upon causative mechanisms. They report difficulties in regulating their emotions as a core issue [ 3 , 5 , 6 ]. Following the group experience and the improvement in reflective function, they realize self-injury behaviors have an anxiolytic purpose [ 4 ].

The function our adolescents give to behavior coincides with the existing published studies. They use behavior to externalize internal difficulties [ 30 ]. This is a fact that supports the consideration of emotional dysregulation as a “transdiagnostic process” present in both internalizing and externalizing disorders [ 6 ].

Regarding their general experience of the skills training groups, participants mention several positive aspects:

They point out two qualities that are therapeutic in themselves: a validating environment and group cohesion. The group is referred to be validating when it is interested in and understanding of the individual’s experience and encourages them to express and communicate their emotions. Group cohesion provides relief, from the beginning of therapy, thanks to the universalization phenomenon and differentiation from peers [ 38 ]. However, we cannot consider these qualities as unique to DBT, because they can happen in other group approaches.

Adolescents also state a direct relationship between therapy effectiveness, self-motivation for change, and an active involvement in treatment [ 31 , 34 ]. Participants highlight how the benefits perceived are only obtained when the person is motivated for therapy, connecting this issue with the importance that DBT gives to the motivational work.

The participants express their preference towards the acceptance skills, mindfulness and DT, a finding consistent with existing literature [ 6 , 17 , 18 , 19 ]. They report that during therapy, mindfulness enables them to realize what is happening to them. ER skills allow them to rethink situations of the past and help to manage difficulties in the present. IE skills help them to have a representation of themselves and the other and be more effective in interpersonal relationships. These skills with the basic ingredients of DBT, validation and dialectics, favor intrapsychic changes such as an improvement in reflective activity.

Participants also express several critical views about the experience:

They do not seem to understand the relevance of homework assignments and how they promote the generalization of skills. It is true that we have not encountered rejection from the adolescents in the study towards completing the homework. This could be a topic to be more thoroughly addressed in groups of adolescents, making them truly aware of the importance of this aspect of the treatment to extend the effect of training across all areas of their lives.

Another relevant criticism concerns their view that improvement may not be complete or permanent, or that it does not come immediately, and relapses are possible. They see skills memorization and application with complete awareness as something difficult during an episode of high emotional dysregulation. Following these thoughts, some degree of maintenance or continuity of the treatment can be considered as a clear need. This could take the form of an extended period of individual DBT sessions, the so called “booster sessions” or graduate groups (involving participants who have already completed a skills training group) [ 12 ]. We opt for using a combination of individual sessions plus graduate groups as an ideal maintenance strategy. In any case the goals are relapse prevention, generalization of skills and promotion of behaviors that induce a positive quality of life.

Participants also mention other interesting proposals.

Taking their narratives into account, skills training is perceived as useful for emotional dysregulation issues. They regard its potential helpfulness also in healthy individuals, a finding shown in a qualitative study on adult population [ 27 ]. Including skills training in the socio-emotional learning curriculum for adolescents would equip them with tools to cope with different life situations, increasing their strength and consequently their resilience [ 38 ]. Likewise, this training may be of great help to encourage treatment adherence in those adolescents who not only suffer from a chronic medical illness [ 39 ] but also have a high resistance to assume and exercise responsibility for the treatment they require.

Therefore, our findings suggest that the flexibility and high structuring of skills training allow this component of DBT to become a vehicle through which we can reach out to adolescents and the multiple areas of their life.

In light of these findings, we see several avenues open to future studies.

Given the difficulties adolescents encounter to keep the gains obtained after the treatment, there is a clear need to evaluate maintenance interventions.

The important programs currently deployed to apply these interventions to healthy adolescents should be thoroughly extended and studied to examine their contributions to normal development and resilience [ 40 ].

Finally, as a logical step continuing from our study, subjective experience of parents and families of adolescent patients, participating in the parents skills training groups, should also be explored. In this instance, we believe a qualitative methodology is very well suited to carry on this study.

Limitations

Our study has two kinds of limitations. One is related to qualitative methodology itself and other specifically related to our study.

Qualitative studies all have an inherent problem of generalizability because the samples do not usually represent the population from where it comes. It is important to note that the goal here is to capture existing subjective experiences without assigning to them frequencies or intensities. These will be later studied through quantitative designs. The focus group format provides some important advantages but also implies limitations as the interaction among patients can favor inhibition of more passive individuals whose opinions fade to the background as a result of those who express more prominently their own opinions. Finally, we must not forget that discou-rse on any aspect of reality is conditioned by the semantic context in which an individual finds himself and in which he has grown up.

Some specific limitations of our study can also be pointed out. There is a lack of information about those subjects who declined to participate after having signed the informed consent. A possibility is that perhaps they had a negative view of the program and felt they would not be able to successfully voice their opinions and could even face rejection. Additionally, the researchers conducting the focus groups had never met the participants before the study, but the adolescents knew they belonged to the staff and this could have influenced the open sharing of their views.

Adolescents with behavioral problems who participated in this study identify the difficulties they have in adaptively managing the emotions that they feel to be a core issue. After completing skills training, they assess the psychotherapeutic tool positively and recommend its usefulness to a healthy population. They report that the motivation for change and the time factor are two aspects closely related to the effectiveness of the therapy. Furthermore, they also note that the most valued skills are mindfulness and DT. With regard to the results of the therapy, in addition to acquiring skills to adaptively manage suffering, they describe intrapsychic changes, such as an improvement in their reflective ability. This allows them to theorize about the difficulties they faced in their past and to better understand themselves in the present.

Availability of data and materials

Transcriptions are kept by the authors. Interested researchers can access them contacting the corresponding author and after complete anonimisation of participants is secured.

Abbreviations

Dialectical Behavior Therapy

Borderline Personality Disorder

Distress Tolerance

Emotion Regulation

Interpersonal Effectiveness

Diagnostic and Statistical Manual of Mental Disorders – IV - revised text

Spanish Association of Child and Adolescent Psychiatry

Looney J, Oldham D (1989) Normal adolescent development. En: Kaplan HI, Sadock BJ (eds): Comprehensive testbook of psychiatry 5° ed. Baltimore, Williams and Wilkins, pp 1710–1715..

Dodge KA. The structure and function of reactive and proactive aggression. In: Pepler DJ, Rubin KH, editors. The development and treatment for childhood aggression. Hillsdale: Erlbaum; 1991.

Google Scholar  

Keenan K. Emotion dysregulation as a risk factor for child psychopathology. Clin Psychol Sci Pract. 2000;7:418–34.

Calkins S, Fox N. Self-regulatory processes in early personality development: a multilevel approach to the study of childhood social withdrawal and agression. Dev Psychopathol. 2002;14:477–98.

PubMed   Google Scholar  

Zalewski M, Lewis KJ, Martin CG. Identifying novel applications of dialectical behavior therapy: considering emotion regulation and parenting. Curr Opin Psychol. 2018;21:122–6.

Linehan M. Cognitive-behavioral treatment of borderline personality disorder. New York: Guildford Press; 1993.

Linehan M. Skills Training Manual for Treating Borderline Personality Disorder. New York: Guildford Press; 1993b.

Ritschel LA, Lim NE, Stewart LM. Transdiagnostic applications of DBT for adolescents and adults. Am J Psychother. 2015;69(2):111–28.

Lynch TR, Chapman AL, Rosenthal MZ, Kuo JR, Linehan MM. Mechanisms of change in dialectical behavior therapy: theoretical and empirical observations. J Clin Psychol. 2006;62(4):459–80.

Vickers J. Assessing a six-month dialectical behaviour therapy skills-only group: results from a study of the effectiveness of a stand-alone treatment for people with borderline personality disorder and other serious mental illnesses. Mental Health Pract. 2016.

Rathus JU, Miller AL. Dialectical behavior therapy adapted for suicidal adolescents. Suicide Life Threat Behav. 2002;32:146–57.

Miller AL, Rathus JH, Linehan MM. Dialectical behavior therapy with suicidal adolescents. New York: The Guilford Press; 2007.

Rathus JU, Miller AL. DBT skills manual for adolescents. New York: The Guildford Press; 2015.

Soler J, Valdepérez A, Feliu-Soler A, Pascual JC, Portella MJ, Martin-Blanco A, Armario A, Álvarez E, Pérez V, Soler J. Effects of the dialectical behavioral therapy-mindfulness module on attention in patients with borderline personality disorder. Behav Res Ther. 2012;50:150–7. https://doi.org/10.1016/j.%20brat.2011.12.002 .

Feliu-Soler A, Pascual JC, Borràs X, Portella MJ, Martín-Blanco A, Armario A, Alvarez E, Perez V, Soler J. Effects of dialectical behaviour therapy- mindfulness training on emotional reactivity in borderline personality disorder: preliminary results. Clin Psychol Psychother. 2014;21:363–70. https://doi.org/10.1002/cpp.1837 .

Groves S, Backer HS, Van den Bosch W, Miller A. Dialectical behaviour therapy with adolescents. Child Adolesc Mental Health. 2012;17(2):65–75.

McPherson A, Cheavens J, Fristad M. Dialectical behavior therapy for adolescentes: theory, treatment adaptations, and empirical outcomes. Clin Child Fam Psychol Rev. 2013;16:59–80.

Nelson-Gray RO, Keane SP, Hurst RM, Mitchell JT, Warburton JB, Chok JT, Cobb AR. A modified DBT skills training program for oppositional defiant adolescents: promising preliminary findings. Behav Res Ther. 2006;44:1811–20. https://doi.org/10.1016/j.brat.2006.01.004 .

Courtney DB, Flament MF. Adapted dialectical behavior therapy for adolescents with self-injurious thoughts and behaviors. J Nerv Ment. 2015;203(7):537–44.

Nixon MK, McLagan L, Landell S, Carter A, Deshaw M. Developing and piloting community-based self-injury treatment groups for adolescents and their parents. Can Child Adolescent Psychiatry Rev. 2004;13:3.

McDonell MG, Tarantino J, Dubose AP, Matestic P, Steinmetz K, Galbreath H, McClellan JM. A pilot evaluation of dialectical Behavioural therapy in adolescente long-term inpatient care. Child Adolesc Mental Health. 2010;15(4):193–6.

Memel B. A quality improvement project to decrease the length of stay on a psychiatric adolescent partial hospital program. J Child Adolescent Psychiatric Nurs. 2012;25:207–18.

Fleischhaker C, Böhme R, Sixt B, Brück C, Schneider C, Schulz E. Dialectical behavioral therapy for adolescents (DBT-A): a clinical trial for patients with suicidal and self-injurious behavior and borderline symptoms with a one-year follow-up. Child Adolesc Psychiatry Ment Health. 2011;5:3. https://doi.org/10.1186/1753-2000-5-3 .

Mehlum L, Tormoen AJ, Ramberg M, Haga E, Diep LM, Laberg S, Larsson BS, Stanley BH, Miller AL, Sund AM, Grohott B. Dialectical behavior therapy for adolescents with repeated suicidal and self-harming behavior: a randomized trial. J Am Acad Child Adolesc Psychiatry. 2014;53:1082–91. https://doi.org/10.1016/j.jaac.2014.07.003 .

Cook NE, Garraiz M. Dialectical behavior therapy for nonsuicidal self-injury and depression among adolescents: preliminary meta-analytic evidence. Child Adolesc Mental Health. 2015;21(2):81–9.

Perepletchikova F, Nathanson D, Axelrod S, Merrill C, Walker A, Grossman M, Rebeta J, Scahill L, Kaufman J, Flye B, Mauer E, Walkup J. Randomized clinical trial of dialectical behavior therapy for pre-adolescent children with disruptive mood dysregulation disorder: feasibility and outcomes. J Am Acad Child Adolesc Psychiatry. 2017;56:832–40.

Chugani CD, Seiler AR, Goldstein TR. Recovery from borderline personality disorder through dialectical behavior therapy. Qual Rep. 2017;22(11):3014–24 Retrieved from http://nsuworks.nova.edu/tqr/vol22/iss11/13 .

Araminta T. Dialectical Behaviour Therapy: A Qualitative Study of Therapist and Client Experience. In: Dissertation Abstracts International: Section B: The Sciences and Engineering, 61. US: Univ Microfilms International; 2000. p. 520.

McCay E, Carter C, Aiello A, Quesnel S, Langley J, Hwang S, Beanlands H, Cooper L, Howes C, Johansson B, MacLaurin B, Hughes J, Karabanow J. Dialectical behavior therapy as catalyst for change in street-involved youth: a mixed methods study. Child Youth Serv Rev. 2015;58:187–99.

McSherry P, O’connor C, Hevey D, Gibbons P. Service user experience of adapted dialectical behaviour therapy in a community adult mental health setting. J Ment Health. 2012;21(6):539–47.

Munarriz M, San Juan J. Investigación cualitativa y psiquiatría. Actas de Psiquiatría. 2001;64(1):7–20.

Kitzinger J. Qualitative research. Introducing focus groups. Br Med J. 1995;311:299–302.

CAS   PubMed   PubMed Central   Google Scholar  

Krueger RA, Casey MA. Focus groups. 3rd edn. Thousand Oaks: Sage; 2000. p. 29. Morgan DL (1998) successful focus groups. Advancing the state of the art. Sage, London.

Morgan DL, Krueger RA. The focus groups kit. London: Sage; 1998.

González Torres MA, Oraa R, Arístegui M, Fernández Rivas A, Guimon J. Stigma and discrimination towards people with schizophrenia and their family members. A qualitative study with focus groups. Soc Psychiatry Psychiatr Epidemiol. 2006. https://doi.org/10.1007/s00127-006-0126-3 .

American Psychiatric Association, APA. DSM-IV-TR. Manual diagnóstico y estadístico de los trastornos mentales. Texto revisado. Barcelona: Masson; 2002.

Corbin J, Strauss A. Basics of qualitative research. Techniques and procedures for developing grounded theory. 4th ed. San Francisco: SAGE Publications; 2015.

Freud S. New Introductory Lectures On Psycho-Analysis. In: The Standard Edition of the Complete Psychological Works of Sigmund Freud, Volume XXII (1932-1936): New Introductory Lectures on Psycho-Analysis and Other Works; 1933. p. 80.

Lois BH, Miller AL. Stopping the nonadherence cycle: the clinical and theoretical basis for dialectical behavior therapy adapted for adolescents with chronic medical illness (DBT-CMI). Cogn Behav Pract. 2017. https://doi.org/10.1016/j.cbpra.2017.01.006 .

Mazza J, Dexter-Mazza ET, Miller AL, Rathus J, Murphy H. DBT Skills in Schools. Skills Trainning for Emotional Problem Solving for Adolescents (DBT STEPS-A). The Guilford Press; 2016.

Download references

Acknowledgements

The authors wish to thanks all of the participants of the study.

This study was partially funded by the Spanish Association of Child and Adolescent Psychiatry (AEPNYA) by awarding the research team the 2015 AEPNYA research prize. The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and affiliations.

Psychiatry Service, Basurto University Hospital, Avda Montevideo, 18 48013, Bilbao, Spain

Eva Sesma Pardo, Aránzazu Fernández Rivas, Pablo Orgaz Barnier, Marina Beá Mirabent, Iñaki Kerexeta Lizeaga, Aída Díaz Cosgaya, Ana Catalán Alcántara, Esther Vivanco González & Miguel Angel González Torres

Department of Neuroscience, University of the Basque Country, Bilbao, Spain

Aránzazu Fernández Rivas, Ana Catalán Alcántara & Miguel Angel González Torres

East Residential. McLean Hospital, Belmont, USA

Blaise Aguirre

Assistant Professor of Psychiatry. Harvard Medical School, Boston, USA

You can also search for this author in PubMed   Google Scholar

Contributions

ESP: design, analysis, manuscript, final approval, corresponding author. AFR: design, analysis, manuscript, final approval. POB: focus group leader, final approval. MBM: focus group leader, final approval. IKL: recruitment, analysis, final approval. ADC: recruitment, analysis, final approval. ACA: recruitment, design, final approval. EVG: recruitment, analysis, final approval. BA: design, manuscript, final approval. MAGT: design, analysis, manuscript, final approval. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Eva Sesma Pardo .

Ethics declarations

Ethics approval and consent to participate.

The present research was carried out in accordance with local regulations and internationally established principles of the Declaration of Helsinki (64th WMA General Assembly, Fortaleza, Brazil, October 2013). Written consent was obtained from all participants. Confidentiality (Spanish data protection law 15/99) and the will of those subjects who did not want to participate in the study has been respected at all times. Likewise, study was assessed and approved by the Research and Ethics Committee of Basurto University Hospital.

Consent for publication

Not applicable.

Competing interests

All authors disclose not having any conflict of interest regarding the study and its publication.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Pardo, E.S., Rivas, A.F., Barnier, P.O. et al. A qualitative research of adolescents with behavioral problems about their experience in a dialectical behavior therapy skills training group. BMC Psychiatry 20 , 245 (2020). https://doi.org/10.1186/s12888-020-02649-2

Download citation

Received : 09 August 2019

Accepted : 04 May 2020

Published : 19 May 2020

DOI : https://doi.org/10.1186/s12888-020-02649-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Adolescents
• Dialectical behavior therapy
• Qualitative research
• Focus groups

BMC Psychiatry

ISSN: 1471-244X

• Submission enquiries: [email protected]
• General enquiries: [email protected]

Disclaimer » Advertising

• HealthyChildren.org

• Previous Article
• Next Article

Introduction

Evidence-based treatments, systemic barriers, recommendations, lead authors, council on early childhood executive committee, 2015–2016, committee on psychosocial aspects of child and family health, 2015–2016, section on developmental and behavioral pediatrics executive committee, 2015–2016, addressing early childhood emotional and behavioral problems.

• Split-Screen
• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• CME Quiz Close Quiz
• Open the PDF for in another window
• Get Permissions
• Cite Icon Cite
• Search Site

COUNCIL ON EARLY CHILDHOOD , COMMITTEE ON PSYCHOSOCIAL ASPECTS OF CHILD AND FAMILY HEALTH , SECTION ON DEVELOPMENTAL AND BEHAVIORAL PEDIATRICS , Dina Lieser , Beth DelConte , Elaine Donoghue , Marian Earls , Danette Glassy , Terri McFadden , Alan Mendelsohn , Seth Scholer , Jennifer Takagishi , Douglas Vanderbilt , Patricia Gail Williams , Michael Yogman , Nerissa Bauer , Thresia B. Gambon , Arthur Lavin , Keith M. Lemmon , Gerri Mattson , Jason Richard Rafferty , EdM , Lawrence Sagin Wissow , Carol Cohen Weitzman , Nerissa S. Bauer , David Omer Childers , Jack M. Levine , Ada Myriam Peralta-Carcelen , Peter Joseph Smith , Nathan J. Blum; Addressing Early Childhood Emotional and Behavioral Problems. Pediatrics December 2016; 138 (6): e20163023. 10.1542/peds.2016-3023

Download citation file:

• Ris (Zotero)
• Reference Manager

Emotional, behavioral, and relationship problems can develop in very young children, especially those living in high-risk families or communities. These early problems interfere with the normative activities of young children and their families and predict long-lasting problems across multiple domains. A growing evidence base demonstrates the efficacy of specific family-focused therapies in reducing the symptoms of emotional, behavioral, and relationship symptoms, with effects lasting years after the therapy has ended. Pediatricians are usually the primary health care providers for children with emotional or behavioral difficulties, and awareness of emerging research about evidence-based treatments will enhance this care. In most communities, access to these interventions is insufficient. Pediatricians can improve the care of young children with emotional, behavioral, and relationship problems by calling for the following: increased access to care; increased research identifying alternative approaches, including primary care delivery of treatments; adequate payment for pediatric providers who serve these young children; and improved education for pediatric providers about the principles of evidence-based interventions.

Emotional, relationship, and behavioral problems affect nearly as many preschoolers as older children, with prevalence rates of 7% to 10%. 1 , – 3 Emotional, behavioral, and relationship problems, including disorders of attachment, disruptive behavior disorders, attention-deficit/hyperactivity disorder (ADHD), anxiety and mood disorders, and disorders of self-regulation of sleep and feeding in children younger than 6 years, interfere with development across multiple domains, including social interactions, parent–child relationships, physical safety, ability to participate in child care, and school readiness. 4 , – 6 Importantly, if untreated, these problems can persist and have long-lasting effects, including measurable abnormalities in brain functioning and persistent emotional and behavioral problems. 7 , – 10 In short, early emotional, behavioral, and relationship problems in preschool-aged children interfere with their current well-being, jeopardize the foundations of emotional and behavioral health, and have the potential for long-term consequences. 11  

Pediatricians and other child health care providers can reduce the risk of childhood emotional and behavioral problems by reducing exposure to toxic stress, promoting protective factors, and systematically screening for risk factors for emerging clinical problems. 12 , 13 Existing policy statements address universal approaches, early identification, and strategies for children at risk. The present policy statement focuses on clinical interventions for children with clinical disorders that warrant targeted treatment. Treatment planning is guided by a comprehensive assessment of the clinical presentation with attention to the child, the parent–child relationships, and community stressors. Beyond assessment, effective treatment of clinical disorders requires the following: (1) access to evidence-based treatments; and (2) primary care providers’ sufficient familiarity with evidence-based treatments to implement first-line approaches, make informed and effective referrals, and collaborate with specialty providers who have expertise in early childhood emotional and behavioral well-being. 14 Currently, most young children with an emotional, relationship, or behavioral problem receive no interventions for their disorder. This policy statement provides a summary of empirically supported approaches, describes readily identifiable barriers to accessing quality evidence-based interventions, and proposes recommendations to enhance the care of young children. This statement has been endorsed by Zero to Three and the American Academy of Child and Adolescent Psychiatry.

Awareness of the relative levels of evidence supporting pharmacologic and nonpharmacologic therapies for emotional, behavioral, and relationship problems can guide clinical decisions in the primary care setting. The evidence base related to psychopharmacologic agents in children younger than 6 years is limited and has only addressed ADHD. 15 Only 2 rigorous trials have examined the safety and efficacy of medications in this age group. Both the trial of methylphenidate and the study of atomoxetine for moderate to severe ADHD demonstrated that the trial medication was more effective than placebo but was less effective for younger children than for older children and produced higher rates of adverse effects in younger children. 16 , 17 Other medications have been less rigorously evaluated in preschool-aged children, although the rates of prescriptions for atypical antipsychotic agents, with their potential for substantial metabolic morbidity, have increased steadily in this age group. 18 , – 20  

Nonpharmacologic treatments have more durable effects than medications, with documented effects lasting for years. 21 , – 23 A first step in reducing the barriers to evidence-based treatments is to ensure that primary care pediatricians are familiar with these approaches, which should be available to young children with emotional, behavioral, or relationship problems. 24  

For infants and toddlers with clinical-level emotional, behavioral, or relationship concerns, dyadic interventions promote attachment security and child emotional regulation and can promote regulation of stress hormones. Examples of these interventions include infant–parent psychotherapy, video feedback to promote positive parenting, and attachment biobehavioral catch-up. These interventions often use real-time infant–parent interactions to support positive interactions, enhance parents’ capacity to reflect on their parenting patterns, and promote sensitivity and an understanding of the infant’s needs. 25  

For preschool-aged children, parent management training models, including parent–child interaction therapy (PCIT), the Incredible Years series, the New Forest Program, Triple P (Positive Parenting Program), and Helping the Noncompliant Child, 26 are effective in decreasing symptoms of ADHD and disruptive behavior disorders. Parents are actively involved in all of these interventions, sometimes without the child and sometimes in parent–child interactions. All share similar behavioral principles, most consistently engaging parents as partners to: (1) reinforce positive behaviors; (2) ignore low-level provocative behaviors; and (3) provide clear, consistent, safe responses to unacceptable behaviors. Table 1 presents some of the characteristics of the best-supported programs for disruptive behavior disorders and ADHD. 25 , 27  

Characteristics of the Best-Supported Programs for Disruptive Behavior Disorders and ADHD

Posttraumatic stress disorder can be treated effectively with cognitive behavioral therapy and child–parent psychotherapy in very young children. In cognitive behavioral therapy for posttraumatic stress disorder, preschool-aged children learn relaxation techniques and are gradually exposed to their frightening memories while using these techniques. Child–parent psychotherapy focuses on supporting parents to create a safe, consistent relationship with the child through helping them understand the child’s emotional experiences and needs. 33 Cognitive behavioral therapy is also effective for other common anxiety disorders, and recent promising studies report effectiveness of modified PCIT for selective mutism and depression. 34 , – 36 Adaptations for use in primary care, including Triple P, the Incredible Years series, and PCIT, similarly show positive outcomes, although further research is warranted. 37 , – 39  

Ensuring that parents have access to appropriate support or clinical care is often an important component of clinical intervention for children. Effective parental treatment (eg, for depression) may reduce child symptoms substantially. 40  

Despite the strong empirical support for these interventions, most young children with emotional, behavioral, and relationship problems do not receive nonpharmacologic treatments. 41 Physical separation, challenges coordinating across systems, stigma, parental beliefs, and provider beliefs about mental health services may interfere with identification of concerns and success of referrals. New models such as co-located care, in which mental health professionals work together with medical care providers in the same space, improve care coordination and referral success, decrease stigma, and reduce symptoms compared with traditional referrals. 42 , – 44 There are insufficient numbers of skilled providers to meet the emotional, behavioral, and relationship needs of children (and young children in particular) who require developmentally specialized interventions. 45 , 46 Therefore, when a primary care pediatrician identifies an emotional, relationship, or behavioral problem in a young child, it is often difficult to identify a professional (eg, social worker, psychologist, child and adolescent psychiatrist, developmental-behavioral pediatrician) with expertise in early childhood to accept the referral and provide evidence-based treatments.

Mental health coverage systems may also reduce access to care. 47 Although mental health parity regulations took effect in 2014, there are still “carved out” mental health programs that prohibit payment to primary care pediatricians for care of a child with an emotional, relationship, or behavioral health diagnosis and may limit access to trained specialists. 48 Even when a trained provider of an evidence-based treatment is identified, communication, coordination of care with primary care pediatricians, and adequate payment can be challenges. 14 , 49 Many health care systems do not pay for, or underpay for, necessary components of early childhood care such as care conferences, school observations, discussions with additional caregivers, same-day services, care coordination, and appointments that do not include face-to-face treatment of the child.

In the context of the focus of the American Academy of Pediatrics on early child and brain development, pediatricians have the opportunity to advocate for legislative and research approaches that will increase access to evidence-based treatments for very young children with emotional, behavioral, and relationship problems.

1a. At the legislative level, pediatricians should advocate for: (1) funding programs that increase dissemination and implementation of evidence-based treatments, especially in areas with limited resources; (2) addressing the early childhood mental health workforce shortage by providing incentives for training in these professions; (3) decreasing third-party payer barriers to accessing mental health services to very young children; and (4) promoting accountable care organization regulations that protect early childhood mental health services.

1b. In collaboration with other child-focused organizations, pediatricians should advocate for prioritization of research that will enhance the evidence base for treatment of very young children with emotional, behavioral, and relationship problems. Comparative effectiveness studies between psychopharmacologic and psychotherapeutic interventions and comparison of mental health service delivery approaches (eg, co-located models, community-based consultation, targeted referrals to specialists) are needed to guide management and policy decisions. In addition, studies that examine moderators of treatment effects, including family, social, and biological factors, are warranted. Studies of interventions adapted to treat young children with mild symptoms in the primary care setting could decrease barriers to care.

At the community and organizational levels, pediatricians should collaborate with local governmental and private agencies to identify local and national clinical services that can serve young children and explore opportunities for innovative service delivery models such as consultation or co-location.

Primary care pediatricians and developmental-behavioral pediatricians, together with early childhood mental health providers, including child and adolescent psychiatrists, and developmental specialists, can create educational materials for trainees and providers to enhance the care young children receive.

Without adequate payment for screening and assessment by primary care providers and management by specialty providers with expertise in early childhood mental health, treatment of very young children with emotional and behavioral problems will likely remain inaccessible for many children. Given existing knowledge regarding the importance of early childhood brain development on lifelong health, adequate payment for early childhood preventive services will benefit not only the patients but society as well and should be supported. Mental health carve-outs should be eliminated because they provide a significant barrier to access to mental health care for children. Additional steps toward equal access to mental health and physical health care include efficient prior authorization processes; adequate panels of early childhood mental health providers; payment to all providers, including primary care providers, for mental health diagnoses; sustainable payment for co-located mental health providers and care coordination; payment for evidence-based approaches focused on parents; and payment for the necessary collection of information from children’s many caregivers and for same-day services. Advocacy for true mental health parity must continue.

To ensure that all providers caring for children are knowledgeable participants and partners in the care of young children with emotional, behavioral, and relationship problems, graduate medical education and continuing medical education should include opportunities for training that ensure that pediatric providers: (1) are competent to identify young children with emotional, behavioral, and relationship problems as well as risk and protective factors; (2) are aware that common early childhood emotional, behavioral, and relationship problems can be treated with evidence-based treatments; (3) recognize the limitations in the data supporting use of medications in very young children, even for ADHD; (4) are prepared to identify and address parental factors that influence early child development; and (5) can collaborate and refer across disciplines and specialties, including developmental-behavioral pediatrics, child and adolescent psychiatry, psychology, and other mental health services.

attention-deficit/hyperactivity disorder

parent–child interaction therapy

This document is copyrighted and is property of the American Academy of Pediatrics and its Board of Directors. All authors have filed conflict of interest statements with the American Academy of Pediatrics. Any conflicts have been resolved through a process approved by the Board of Directors. The American Academy of Pediatrics has neither solicited nor accepted any commercial involvement in the development of the content of this publication.

The guidance in this statement does not indicate an exclusive course of treatment or serve as a standard of medical care. Variations, taking into account individual circumstances, may be appropriate.

All policy statements from the American Academy of Pediatrics automatically expire 5 years after publication unless reaffirmed, revised, or retired at or before that time.

Mary Margaret Gleason, MD, FAAP

Edward Goldson, MD, FAAP

Michael W. Yogman, MD, FAAP

Dina Lieser, MD, FAAP, Chairperson

Beth DelConte, MD, FAAP

Elaine Donoghue, MD, FAAP

Marian Earls, MD, FAAP

Danette Glassy, MD, FAAP

Terri McFadden, MD, FAAP

Alan Mendelsohn, MD, FAAP

Seth Scholer, MD, FAAP

Jennifer Takagishi, MD, FAAP

Douglas Vanderbilt, MD, FAAP

Patricia Gail Williams, MD, FAAP

Lynette M. Fraga, PhD – Child Care Aware

Abbey Alkon, RN, PNP, PhD, MPH – National Association of Pediatric Nurse Practitioners

Barbara U. Hamilton, MA – Maternal and Child Health Bureau

David Willis, MD, FAAP – Maternal and Child Health Bureau

Claire Lerner, LCSW – Zero to Three

Charlotte Zia, MPH, CHES

Michael Yogman, MD, FAAP, Chairperson

Nerissa Bauer, MD, MPH, FAAP

Thresia B. Gambon, MD, FAAP

Arthur Lavin, MD, FAAP

Keith M. Lemmon, MD, FAAP

Gerri Mattson, MD, FAAP

Jason Richard Rafferty, MD, MPH, EdM

Lawrence Sagin Wissow, MD, MPH, FAAP

Sharon Berry, PhD, LP – Society of Pediatric Psychology

Terry Carmichael, MSW – National Association of Social Workers

Edward Christophersen, PhD, FAAP – Society of Pediatric Psychology

Norah Johnson, PhD, RN, CPNP-BC – National Association of Pediatric Nurse Practitioners

Leonard Read Sulik, MD, FAAP – American Academy of Child and Adolescent Psychiatry

George J. Cohen, MD, FAAP

Stephanie Domain, MS, CHES

Nathan J. Blum, MD, FAAP, Chairperson

Michelle M. Macias, MD, FAAP, Immediate Past Chairperson

Nerissa S. Bauer, MD, MPH, FAAP

Carolyn Bridgemohan, MD, FAAP

Peter J. Smith, MD, MA, FAAP

Carol Cohen Weitzman, MD, FAAP

Stephen H. Contompasis, MD, FAAP, Web site Editor

Damon R. Korb, MD, FAAP, Discussion Board Moderator

Michael I. Reiff, MD, FAAP, Newsletter Editor

Robert G. Voigt, MD, FAAP, Program Chairperson

Beth Ellen Davis, MD, MPH, FAAP – Council on Children with Disabilities

Pamela C. High, MD, MS, FAAP – Society for Developmental and Behavioral Pediatrics

Linda Paul, MPH

Advertising Disclaimer »

Citing articles via

Email alerts.

Affiliations

• Editorial Board
• Editorial Policies
• Journal Blogs
• Pediatrics On Call
• Online ISSN 1098-4275
• Print ISSN 0031-4005
• Pediatrics Open Science
• Hospital Pediatrics
• Pediatrics in Review
• AAP Grand Rounds
• Latest News
• Pediatric Care Online
• Red Book Online
• Pediatric Patient Education
• AAP Toolkits
• AAP Pediatric Coding Newsletter

First 1,000 Days Knowledge Center

Institutions/librarians, group practices, licensing/permissions, integrations, advertising.

• Privacy Statement | Accessibility Statement | Terms of Use | Support Center | Contact Us
• © Copyright American Academy of Pediatrics

This Feature Is Available To Subscribers Only

Sign In or Create an Account

Student Behavior Isn’t Getting Any Better, Survey Shows

• Share article

Student behavior problems have continued to rise over the past three to four years, according to a recent survey by the EdWeek Research Center.

Seventy percent of educators—including 1,058 teachers, principals, and district leaders—say students in their schools are misbehaving more now compared with the fall of 2019. And that percentage has held largely steady for a little more than a year, inching up slightly from December 2021, when the EdWeek Research Center last put this question to educators.

Back then, 66 percent of them said their students were misbehaving a little more or a lot more compared with fall of 2019.

The pandemic has also continued to affect students’ motivation and morale. Eighty percent of educators said in a survey fielded by the EdWeek Research Center in January of this year that the pandemic has made students less motivated to do their best in school. A third of educators described the students in their classes, schools, and districts as unmotivated.

Meanwhile, 68 percent of educators said that their students’ morale is lower than compared to before the pandemic.

But even as educators paint a dreary picture of student morale and motivation, students themselves report feeling generally more optimistic. Eighty-six percent of teenagers surveyed in December 2022 by the EdWeek Research Center said they were motivated and 82 percent said they were feeling hopeful about the future—up from 69 percent who said they felt hopeful back 2020.

Sign Up for The Savvy Principal

Edweek top school jobs.

Sign Up & Sign In

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• The Research Problem/Question
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question. In the social and behavioral sciences, studies are most often framed around examining a problem that needs to be understood and resolved in order to improve society and the human condition.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Guba, Egon G., and Yvonna S. Lincoln. “Competing Paradigms in Qualitative Research.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, editors. (Thousand Oaks, CA: Sage, 1994), pp. 105-117; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

Importance of...

The purpose of a problem statement is to:

• Introduce the reader to the importance of the topic being studied . The reader is oriented to the significance of the study.
• Anchors the research questions, hypotheses, or assumptions to follow . It offers a concise statement about the purpose of your paper.
• Place the topic into a particular context that defines the parameters of what is to be investigated.
• Provide the framework for reporting the results and indicates what is probably necessary to conduct the study and explain how the findings will present this information.

In the social sciences, the research problem establishes the means by which you must answer the "So What?" question. This declarative question refers to a research problem surviving the relevancy test [the quality of a measurement procedure that provides repeatability and accuracy]. Note that answering the "So What?" question requires a commitment on your part to not only show that you have reviewed the literature, but that you have thoroughly considered the significance of the research problem and its implications applied to creating new knowledge and understanding or informing practice.

To survive the "So What" question, problem statements should possess the following attributes:

• Clarity and precision [a well-written statement does not make sweeping generalizations and irresponsible pronouncements; it also does include unspecific determinates like "very" or "giant"],
• Demonstrate a researchable topic or issue [i.e., feasibility of conducting the study is based upon access to information that can be effectively acquired, gathered, interpreted, synthesized, and understood],
• Identification of what would be studied, while avoiding the use of value-laden words and terms,
• Identification of an overarching question or small set of questions accompanied by key factors or variables,
• Identification of key concepts and terms,
• Articulation of the study's conceptual boundaries or parameters or limitations,
• Some generalizability in regards to applicability and bringing results into general use,
• Conveyance of the study's importance, benefits, and justification [i.e., regardless of the type of research, it is important to demonstrate that the research is not trivial],
• Does not have unnecessary jargon or overly complex sentence constructions; and,
• Conveyance of more than the mere gathering of descriptive data providing only a snapshot of the issue or phenomenon under investigation.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Brown, Perry J., Allen Dyer, and Ross S. Whaley. "Recreation Research—So What?" Journal of Leisure Research 5 (1973): 16-24; Castellanos, Susie. Critical Writing and Thinking. The Writing Center. Dean of the College. Brown University; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Selwyn, Neil. "‘So What?’…A Question that Every Journal Article Needs to Answer." Learning, Media, and Technology 39 (2014): 1-5; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518.

Structure and Writing Style

I.  Types and Content

There are four general conceptualizations of a research problem in the social sciences:

• Casuist Research Problem -- this type of problem relates to the determination of right and wrong in questions of conduct or conscience by analyzing moral dilemmas through the application of general rules and the careful distinction of special cases.
• Difference Research Problem -- typically asks the question, “Is there a difference between two or more groups or treatments?” This type of problem statement is used when the researcher compares or contrasts two or more phenomena. This a common approach to defining a problem in the clinical social sciences or behavioral sciences.
• Descriptive Research Problem -- typically asks the question, "what is...?" with the underlying purpose to describe the significance of a situation, state, or existence of a specific phenomenon. This problem is often associated with revealing hidden or understudied issues.
• Relational Research Problem -- suggests a relationship of some sort between two or more variables to be investigated. The underlying purpose is to investigate specific qualities or characteristics that may be connected in some way.

A problem statement in the social sciences should contain :

• A lead-in that helps ensure the reader will maintain interest over the study,
• A declaration of originality [e.g., mentioning a knowledge void or a lack of clarity about a topic that will be revealed in the literature review of prior research],
• An indication of the central focus of the study [establishing the boundaries of analysis], and
• An explanation of the study's significance or the benefits to be derived from investigating the research problem.

NOTE :   A statement describing the research problem of your paper should not be viewed as a thesis statement that you may be familiar with from high school. Given the content listed above, a description of the research problem is usually a short paragraph in length.

II.  Sources of Problems for Investigation

The identification of a problem to study can be challenging, not because there's a lack of issues that could be investigated, but due to the challenge of formulating an academically relevant and researchable problem which is unique and does not simply duplicate the work of others. To facilitate how you might select a problem from which to build a research study, consider these sources of inspiration:

Deductions from Theory This relates to deductions made from social philosophy or generalizations embodied in life and in society that the researcher is familiar with. These deductions from human behavior are then placed within an empirical frame of reference through research. From a theory, the researcher can formulate a research problem or hypothesis stating the expected findings in certain empirical situations. The research asks the question: “What relationship between variables will be observed if theory aptly summarizes the state of affairs?” One can then design and carry out a systematic investigation to assess whether empirical data confirm or reject the hypothesis, and hence, the theory.

Interdisciplinary Perspectives Identifying a problem that forms the basis for a research study can come from academic movements and scholarship originating in disciplines outside of your primary area of study. This can be an intellectually stimulating exercise. A review of pertinent literature should include examining research from related disciplines that can reveal new avenues of exploration and analysis. An interdisciplinary approach to selecting a research problem offers an opportunity to construct a more comprehensive understanding of a very complex issue that any single discipline may be able to provide.

Interviewing Practitioners The identification of research problems about particular topics can arise from formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice. Discussions with experts in the field, such as, teachers, social workers, health care providers, lawyers, business leaders, etc., offers the chance to identify practical, “real world” problems that may be understudied or ignored within academic circles. This approach also provides some practical knowledge which may help in the process of designing and conducting your study.

Personal Experience Don't undervalue your everyday experiences or encounters as worthwhile problems for investigation. Think critically about your own experiences and/or frustrations with an issue facing society or related to your community, your neighborhood, your family, or your personal life. This can be derived, for example, from deliberate observations of certain relationships for which there is no clear explanation or witnessing an event that appears harmful to a person or group or that is out of the ordinary.

Relevant Literature The selection of a research problem can be derived from a thorough review of pertinent research associated with your overall area of interest. This may reveal where gaps exist in understanding a topic or where an issue has been understudied. Research may be conducted to: 1) fill such gaps in knowledge; 2) evaluate if the methodologies employed in prior studies can be adapted to solve other problems; or, 3) determine if a similar study could be conducted in a different subject area or applied in a different context or to different study sample [i.e., different setting or different group of people]. Also, authors frequently conclude their studies by noting implications for further research; read the conclusion of pertinent studies because statements about further research can be a valuable source for identifying new problems to investigate. The fact that a researcher has identified a topic worthy of further exploration validates the fact it is worth pursuing.

III.  What Makes a Good Research Statement?

A good problem statement begins by introducing the broad area in which your research is centered, gradually leading the reader to the more specific issues you are investigating. The statement need not be lengthy, but a good research problem should incorporate the following features:

1.  Compelling Topic The problem chosen should be one that motivates you to address it but simple curiosity is not a good enough reason to pursue a research study because this does not indicate significance. The problem that you choose to explore must be important to you, but it must also be viewed as important by your readers and to a the larger academic and/or social community that could be impacted by the results of your study. 2.  Supports Multiple Perspectives The problem must be phrased in a way that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A general rule of thumb in the social sciences is that a good research problem is one that would generate a variety of viewpoints from a composite audience made up of reasonable people. 3.  Researchability This isn't a real word but it represents an important aspect of creating a good research statement. It seems a bit obvious, but you don't want to find yourself in the midst of investigating a complex research project and realize that you don't have enough prior research to draw from for your analysis. There's nothing inherently wrong with original research, but you must choose research problems that can be supported, in some way, by the resources available to you. If you are not sure if something is researchable, don't assume that it isn't if you don't find information right away--seek help from a librarian !

NOTE:   Do not confuse a research problem with a research topic. A topic is something to read and obtain information about, whereas a problem is something to be solved or framed as a question raised for inquiry, consideration, or solution, or explained as a source of perplexity, distress, or vexation. In short, a research topic is something to be understood; a research problem is something that needs to be investigated.

IV.  Asking Analytical Questions about the Research Problem

Research problems in the social and behavioral sciences are often analyzed around critical questions that must be investigated. These questions can be explicitly listed in the introduction [i.e., "This study addresses three research questions about women's psychological recovery from domestic abuse in multi-generational home settings..."], or, the questions are implied in the text as specific areas of study related to the research problem. Explicitly listing your research questions at the end of your introduction can help in designing a clear roadmap of what you plan to address in your study, whereas, implicitly integrating them into the text of the introduction allows you to create a more compelling narrative around the key issues under investigation. Either approach is appropriate.

The number of questions you attempt to address should be based on the complexity of the problem you are investigating and what areas of inquiry you find most critical to study. Practical considerations, such as, the length of the paper you are writing or the availability of resources to analyze the issue can also factor in how many questions to ask. In general, however, there should be no more than four research questions underpinning a single research problem.

Given this, well-developed analytical questions can focus on any of the following:

• Highlights a genuine dilemma, area of ambiguity, or point of confusion about a topic open to interpretation by your readers;
• Yields an answer that is unexpected and not obvious rather than inevitable and self-evident;
• Provokes meaningful thought or discussion;
• Raises the visibility of the key ideas or concepts that may be understudied or hidden;
• Suggests the need for complex analysis or argument rather than a basic description or summary; and,
• Offers a specific path of inquiry that avoids eliciting generalizations about the problem.

NOTE:   Questions of how and why concerning a research problem often require more analysis than questions about who, what, where, and when. You should still ask yourself these latter questions, however. Thinking introspectively about the who, what, where, and when of a research problem can help ensure that you have thoroughly considered all aspects of the problem under investigation and helps define the scope of the study in relation to the problem.

V.  Mistakes to Avoid

Beware of circular reasoning! Do not state the research problem as simply the absence of the thing you are suggesting. For example, if you propose the following, "The problem in this community is that there is no hospital," this only leads to a research problem where:

• The need is for a hospital
• The objective is to create a hospital
• The method is to plan for building a hospital, and
• The evaluation is to measure if there is a hospital or not.

This is an example of a research problem that fails the "So What?" test . In this example, the problem does not reveal the relevance of why you are investigating the fact there is no hospital in the community [e.g., perhaps there's a hospital in the community ten miles away]; it does not elucidate the significance of why one should study the fact there is no hospital in the community [e.g., that hospital in the community ten miles away has no emergency room]; the research problem does not offer an intellectual pathway towards adding new knowledge or clarifying prior knowledge [e.g., the county in which there is no hospital already conducted a study about the need for a hospital, but it was conducted ten years ago]; and, the problem does not offer meaningful outcomes that lead to recommendations that can be generalized for other situations or that could suggest areas for further research [e.g., the challenges of building a new hospital serves as a case study for other communities].

Alvesson, Mats and Jörgen Sandberg. “Generating Research Questions Through Problematization.” Academy of Management Review 36 (April 2011): 247-271 ; Choosing and Refining Topics. Writing@CSU. Colorado State University; D'Souza, Victor S. "Use of Induction and Deduction in Research in Social Sciences: An Illustration." Journal of the Indian Law Institute 24 (1982): 655-661; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); How to Write a Research Question. The Writing Center. George Mason University; Invention: Developing a Thesis Statement. The Reading/Writing Center. Hunter College; Problem Statements PowerPoint Presentation. The Writing Lab and The OWL. Purdue University; Procter, Margaret. Using Thesis Statements. University College Writing Centre. University of Toronto; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518; Trochim, William M.K. Problem Formulation. Research Methods Knowledge Base. 2006; Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Walk, Kerry. Asking an Analytical Question. [Class handout or worksheet]. Princeton University; White, Patrick. Developing Research Questions: A Guide for Social Scientists . New York: Palgrave McMillan, 2009; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

• << Previous: Background Information
• Next: Theoretical Framework >>
• Last Updated: May 7, 2024 9:40 AM
• URL: https://libguides.usc.edu/writingguide

Behavior or Conduct Problems in Children

Children sometimes argue, are aggressive, or act angry or defiant around adults. A behavior disorder may be diagnosed when these disruptive behaviors are uncommon for the child’s age at the time, persist over time, or are severe.  Because disruptive behavior disorders involve acting out and showing unwanted behavior towards others they are sometimes called externalizing disorders .

Oppositional Defiant Disorder

When children act out persistently so that it causes serious problems at home, in school, or with peers, they may be diagnosed with Oppositional Defiant Disorder (ODD). ODD usually starts before 8 years of age, but no later than by about 12 years of age. Children with ODD are more likely to act oppositional or defiant around people they know well, such as family members, a regular care provider, or a teacher. Children with ODD show these behaviors more often than other children their age.

Examples of ODD behaviors include

• Often being angry or losing one’s temper
• Often arguing with adults or refusing to comply with adults’ rules or requests
• Often resentful or spiteful
• Deliberately annoying others or becoming annoyed with others
• Often blaming other people for one’s own mistakes or misbehavior

Learn more about ODD

Conduct Disorder

Conduct Disorder (CD) is diagnosed when children show an ongoing pattern of aggression toward others, and serious violations of rules and social norms at home, in school, and with peers. These rule violations may involve breaking the law and result in arrest. Children with CD are more likely to get injured and may have difficulties getting along with peers.

Examples of CD behaviors include

• Breaking serious rules, such as running away, staying out at night when told not to, or skipping school
• Being aggressive in a way that causes harm, such as  bullying, fighting, or being cruel to animals
• Lying, stealing, or damaging other people’s property on purpose

Learn more about CD

Learn about the guidelines for diagnosing and treating ODD and CD

Treatment for disruptive behavior disorders

Starting treatment early is important. Treatment is most effective if it fits the needs of the specific child and family. The first step to treatment is to talk with a healthcare provider. A comprehensive evaluation by a mental health professional may be needed to get the right diagnosis. Some of the signs of behavior problems, such as not following rules in school, could be related to learning problems which may need additional intervention. For younger children, the treatment with the strongest evidence is behavior therapy training for parents,  where a therapist helps the parent learn effective ways to strengthen the parent-child relationship and respond to the child’s behavior. For school-age children and teens, an often-used effective treatment is a combination of training and therapy that includes the child, the family, and the school.

Get help finding treatment

Here are tools to find a healthcare provider familiar with treatment options:

• Psychologist Locator , a service of the American Psychological Association (APA) Practice Organization.
• Child and Adolescent Psychiatrist Finder , a research tool by the American Academy of Child and Adolescent Psychiatry (AACAP).
• Find a Cognitive Behavioral Therapist , a search tool by the Association for Behavioral and Cognitive Therapies.
• If you need help finding treatment facilities, visit FindTreatment.gov .

Managing Symptoms: Staying Healthy

Being healthy is important for all children and can be especially important for children with behavior or conduct problems. In addition to behavioral therapy and medication, practicing certain healthy lifestyle behaviors may reduce challenging and disruptive behaviors your child might experience. Here are some healthy behaviors that may help:

• Engaging in regular physical activity , including aerobic and vigorous exercise
• Eating a healthful diet centered on fruits, vegetables, whole grains, legumes (for example, beans, peas, and lentils), lean protein sources, and nuts and seeds
• Getting the recommended amount of sleep each night based on age
• Strengthening relationships with family members

Prevention of disruptive behavior disorders

It is not known exactly why some children develop disruptive behavior disorders. Many factors may play a role, including biological and social factors. It is known that children are at greater risk when they are exposed to other types of violence and criminal behavior, when they experience maltreatment or harsh or inconsistent parenting, or when their parents have mental health conditions like substance use disorders , depression , or attention-deficit/hyperactivity disorder (ADHD) . The quality of early childhood care also can impact whether a child develops behavior problems.

Although these factors appear to increase the risk for disruptive behavior disorders, there are ways to decrease the chance that children experience them. Learn about public health approaches to prevent these risks:

• Positive parenting strategies for young children
• Positive parenting tips
• Child maltreatment prevention
• Youth violence prevention
• Bullying prevention
• Mental health in adults
• Finding high quality child care

To receive email updates about this topic, enter your email address:

Exit Notification / Disclaimer Policy

• The Centers for Disease Control and Prevention (CDC) cannot attest to the accuracy of a non-federal website.
• Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website.
• You will be subject to the destination website's privacy policy when you follow the link.
• CDC is not responsible for Section 508 compliance (accessibility) on other federal or private website.

Animal behavior research is getting better at keeping observer bias from sneaking in – but there’s still room to improve

Professor and Associate Head of Psychology, University of Tennessee

Disclosure statement

Todd M. Freeberg does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Tennessee provides funding as a member of The Conversation US.

View all partners

Animal behavior research relies on careful observation of animals. Researchers might spend months in a jungle habitat watching tropical birds mate and raise their young. They might track the rates of physical contact in cattle herds of different densities. Or they could record the sounds whales make as they migrate through the ocean.

Animal behavior research can provide fundamental insights into the natural processes that affect ecosystems around the globe, as well as into our own human minds and behavior.

I study animal behavior – and also the research reported by scientists in my field. One of the challenges of this kind of science is making sure our own assumptions don’t influence what we think we see in animal subjects. Like all people, how scientists see the world is shaped by biases and expectations, which can affect how data is recorded and reported. For instance, scientists who live in a society with strict gender roles for women and men might interpret things they see animals doing as reflecting those same divisions .

The scientific process corrects for such mistakes over time, but scientists have quicker methods at their disposal to minimize potential observer bias. Animal behavior scientists haven’t always used these methods – but that’s changing. A new study confirms that, over the past decade, studies increasingly adhere to the rigorous best practices that can minimize potential biases in animal behavior research.

Biases and self-fulfilling prophecies

A German horse named Clever Hans is widely known in the history of animal behavior as a classic example of unconscious bias leading to a false result.

Around the turn of the 20th century , Clever Hans was purported to be able to do math. For example, in response to his owner’s prompt “3 + 5,” Clever Hans would tap his hoof eight times. His owner would then reward him with his favorite vegetables. Initial observers reported that the horse’s abilities were legitimate and that his owner was not being deceptive.

However, careful analysis by a young scientist named Oskar Pfungst revealed that if the horse could not see his owner, he couldn’t answer correctly. So while Clever Hans was not good at math, he was incredibly good at observing his owner’s subtle and unconscious cues that gave the math answers away.

In the 1960s, researchers asked human study participants to code the learning ability of rats. Participants were told their rats had been artificially selected over many generations to be either “bright” or “dull” learners. Over several weeks, the participants ran their rats through eight different learning experiments.

In seven out of the eight experiments , the human participants ranked the “bright” rats as being better learners than the “dull” rats when, in reality, the researchers had randomly picked rats from their breeding colony. Bias led the human participants to see what they thought they should see.

Eliminating bias

Given the clear potential for human biases to skew scientific results, textbooks on animal behavior research methods from the 1980s onward have implored researchers to verify their work using at least one of two commonsense methods.

One is making sure the researcher observing the behavior does not know if the subject comes from one study group or the other. For example, a researcher would measure a cricket’s behavior without knowing if it came from the experimental or control group.

The other best practice is utilizing a second researcher, who has fresh eyes and no knowledge of the data, to observe the behavior and code the data. For example, while analyzing a video file, I count chickadees taking seeds from a feeder 15 times. Later, a second independent observer counts the same number.

Yet these methods to minimize possible biases are often not employed by researchers in animal behavior, perhaps because these best practices take more time and effort.

In 2012, my colleagues and I reviewed nearly 1,000 articles published in five leading animal behavior journals between 1970 and 2010 to see how many reported these methods to minimize potential bias. Less than 10% did so. By contrast, the journal Infancy, which focuses on human infant behavior, was far more rigorous: Over 80% of its articles reported using methods to avoid bias.

It’s a problem not just confined to my field. A 2015 review of published articles in the life sciences found that blind protocols are uncommon . It also found that studies using blind methods detected smaller differences between the key groups being observed compared to studies that didn’t use blind methods, suggesting potential biases led to more notable results.

In the years after we published our article, it was cited regularly and we wondered if there had been any improvement in the field. So, we recently reviewed 40 articles from each of the same five journals for the year 2020.

We found the rate of papers that reported controlling for bias improved in all five journals , from under 10% in our 2012 article to just over 50% in our new review. These rates of reporting still lag behind the journal Infancy, however, which was 95% in 2020.

All in all, things are looking up, but the animal behavior field can still do better. Practically, with increasingly more portable and affordable audio and video recording technology, it’s getting easier to carry out methods that minimize potential biases. The more the field of animal behavior sticks with these best practices, the stronger the foundation of knowledge and public trust in this science will become.

• Animal behavior
• Research methods
• Research bias

Scheduling Analyst

Assistant Editor - 1 year cadetship

Executive Dean, Faculty of Health

Lecturer/Senior Lecturer, Earth System Science (School of Science)

Sydney Horizon Educators (Identified)

Comprehensive behavioral and physiologic assessment of peripheral and central auditory function in individuals with mild traumatic brain injury

Apr 22, 2024, 2:57 AM

Stahl, A. N., Racca, J. M., Kerley, C. I., Anderson, A., Landman, B., Hood, L. J., Gifford, R. H., & Rex, T. S. (2024). Comprehensive behavioral and physiologic assessment of peripheral and central auditory function in individuals with mild traumatic brain injur y. Hearing Research, 441. https://doi.org/10.1016/J.HEARES.2023.108928

The study investigates auditory issues in individuals with mild traumatic brain injury (mTBI), a group often reporting hearing problems despite normal hearing tests. Researchers used a comprehensive battery of tests assessing both peripheral and central auditory system functions, including pure-tone detection, word and sentence understanding, and various auditory evoked potentials (AEPs), alongside MRI scans. Findings revealed that mTBI patients showed notable changes in several auditory tests, such as reduced otoacoustic emissions, altered middle-ear reflex thresholds, and variations in AEPs indicating auditory processing difficulties. Particularly, those with combined hearing difficulty and noise sensitivity displayed more significant auditory processing deficits and structural brain changes in regions linked to auditory processing, such as the transverse temporal gyrus and planum polare. These results underscore the complexity of auditory issues in mTBI and the need for tailored diagnostic and treatment approaches that account for the nuanced effects of brain injuries on hearing.

Explore Story Topics

• Search Please fill out this field.
• Newsletters
• Sweepstakes
• Raising Kids

How Positive Reinforcement Encourages Good Behavior in Kids

Praise and rewards can be an effective way to change kids' behavior for the better. Here's how to use them.

How Positive Reinforcement Works

• Rewarding Effort
• Behaviors To Reinforce

Linking Rewards To Behavior

• Importance of Consistency
• Avoiding Accidental Reinforcement

When your child misbehaves, rewards might be the last thing on your mind. But positive reinforcement can be one of the most effective behavior modification techniques parents can use. Positive reinforcement can encourage prosocial behaviors in kids, like sharing or following directions. You can also use it to prevent less desirable behaviors, like hitting, spitting, and violating rules.

Positive reinforcement can also motivate your child to do their chores , get along with their siblings, or complete their homework assignments without arguing. Learn more about how to use positive reinforcement with your kids and get examples of positive reinforcement in action.

Positive reinforcement is a type of positive discipline that aims to shape behavior by focusing on the positive while reframing missteps as opportunities for learning. The goal is to catch and reward the good behaviors you want to see from your child.

Essentially, providing a reward for doing well shapes behavior by motivating kids to keep doing well . This strategy works for adults, too. For example, most adults go to work so they can make a living. A paycheck is a positive consequence of going to work. That positive reinforcement motivates them to keep working.

It's important to reward the behavior you want to see more often, rather than simply focusing on your child's misbehavior. When kids get attention and other benefits from behaving how you want them to act, those behaviors are much more likely to become habitual.

Positive Reinforcement vs. Positive Punishment

Positive reinforcement is used to encourage good behavior by adding a positive outcome (like praise or a reward). Positive punishment , on the other hand, is used to discourage misbehavior by taking away something that is desired, such as screen time or other privileges. While positive punishment can be effective, most psychologists say that rewards for desired behavior tend to be more effective than punishments for undesirable behavior.

Examples of Positive Reinforcement

Consistency, limit-setting, encouragement, and kindness are pillars of positive reinforcement. There are many ways to reinforce the behavior you want to encourage from your kids. Positive reinforcement doesn’t have to be complicated or expensive. You can positively reinforce a child’s behavior by:

• Clapping and cheering
• High-fiving
• Hugging or patting on the back
• Giving a thumbs-up
• Offering a special activity, like playing a game or reading a book together
• Offering praise directly to your child or within their earshot

You can also offer positive reinforcement by giving a child extra privileges or tangible rewards. For example, if your child patiently helps their sibling with their homework, you could offer more time for them to play video games.

There are many different types of reward systems you can use to aid positive reinforcement. Younger children often do well with sticker charts and older children often respond well to token economy systems, where they can earn "tokens" that can be exchanged for bigger rewards. When you offer your child a choice of what reward they would like to earn for consistently showing good behavior, they get a greater sense of agency and motivation.

Using Positive Reinforcement To Reward Effort

It's important to reward your child's efforts and improvement, rather than focusing only on perfect results. If you see them try, let them know you notice.

Let's say, for example, that you want your child to learn to put away their school things when they get home. If you see that they hang up their coat but forget to put their lunchbox on the counter, you can still praise the partial success. Similarly, if they start walking to the bathroom when you tell them it's time to brush their teeth but they get distracted on the way, you can praise their original intention and then redirect them.

Offer praise when the good behavior starts rather than waiting until a longer task is complete, especially if you suspect their good intentions may get derailed. For example, if a child who struggles with homework begins working on their math problems, compliment them for getting started. This early praise will give your child a sense of success and encourage them to stick with it.

Examples of Behaviors To Positively Reinforce

Use positive reinforcement to encourage any behaviors that you want your child to repeat. Examples of behaviors to reinforce include:

• Being a good friend
• Being a good sport
• Completing chores
• Complying with a request
• Compromising or being flexible
• Handling a disagreement or disappointment without a tantrum
• Helping you without complaint
• Playing nicely with a sibling
• Putting in a lot of effort on a difficult task
• Showing compassion
• Staying at the dinner table without fidgeting or getting up
• Talking about their feelings
• Using manners
• Waiting patiently

If you offer rewards along with praise, connect them to the behavior you seek to reinforce. You want your child to see that exhibiting positive behavior makes good things happen.

Here are some examples of good behavior and a positive consequence that might go with it:

• If your child helps you prepare a meal, you can let them decide on a component of it, like the salad dressing or a dessert to serve.
• If your child is a good sport about losing a game, you can let them choose the next game .
• If your child shares their toy with their sibling, you can allow them to stay up a bit later to continue playing or give them a small new plaything the next day.

This connection between the reinforcement and the behavior will make the positive consequence more memorable and effective.

Importance of Consistent Positive Reinforcement

When your child is learning a new behavior or working on a specific skill, it's important to offer positive reinforcement consistently. After all, how often would you go to work if you only got paid occasionally? You might give up if your efforts don't seem worthwhile. 

The same can be said for your child. If you only catch them being good once in a while or you only give them positive reinforcement randomly, their behavior is unlikely to change. 

This doesn’t mean you need to reward your child every time they carry a dish to the sink. However, the more often their good behavior is noticed, the better—especially for younger kids .

This is where a reward system comes in handy. You can easily provide immediate reinforcement in the form of a sticker or token. Stickers and tokens can later be exchanged for bigger rewards, such as a new book or an ice cream cone.

Over time, you can space out your reinforcement. Once your child has mastered a skill, surprise reinforcement from time to time can be effective maintenance. Say, "Wow, I'm so impressed you've been getting ready for school on time lately. I think we'll go to the playground tonight to celebrate." 

Avoid Accidental Positive Reinforcement

Sometimes, parents accidentally reinforce negative behavior. One common way this happens is with attention. Attention can be very reinforcing, even if it’s negative attention like yelling . Ignoring can be one of the best ways to respond to obnoxious attention-seeking behavior. Another way parents unintentionally reinforce negative behavior is by giving in.

For example:

• A child who is purposely annoying their parent receives reinforcement for the annoying attention-seeking behavior every time their parent says, “stop that!” or “don’t do that.” (The child learns that they can get their parent's attention through annoying behavior.)
• A child begs and pleads to go outside after their parent already said no receives reinforcement for the whining when the parent gives in and lets them go outside (The child learned that whining helps them get what they want, encouraging them to whine again in the future.)
• A child who aggressively takes a toy from their sibling receives reinforcement for the behavior when the parent allows the behavior to go unchecked (The child learns that they can take things and get to keep them.)

Instead, make sure that negative behavior doesn't get reinforced. When your child misbehaves, follow through with a negative consequence , such as a loss of privileges or logical consequences.

While eliminating reinforcement of negative behaviors, be sure to focus on the good behaviors that you want to reinforce. Once you get the hang of noticing all the praise-worthy things your child is doing, you'll likely find that positive reinforcement works much better than punishments—and makes for a much happier household. 

Behavior Modification . StatPearls . 2024.

How to shape and manage your young child's behavior . American Academy of Pediatrics . 2018.

Reinforcement and Punishment . University of Central Florida . n.d.

Steps for Using Consequences . Centers for Disease Control and Prevention . 2017.

Positive Reinforcement Through Rewards . American Academy of Pediatrics . 2023.

Related Articles

Health Science Center

What Can we help you find?

Popular Searches

• Academic Calendar
• Study Abroad
• Majors & Minors
• Request Info

UT Tyler Health Science Center

Build a healthier tomorrow.

Home to the region’s only academic medical center, The University of Texas at Tyler Health Science Center is one of the five campuses of UT Tyler. Two of UT Tyler’s four health-related schools have a presence on this campus: the School of Health Professions and the School of Medicine.

Campus History

Our Beginnings

Joining the University of Texas System

A Name Change

New Programs

Campus Programs and Facilities

The UT Tyler Health Science Center facility offers an array of crucial medical and healthcare education resources, fostering an environment dedicated to excellence in education. From cutting-edge simulation labs to dedicated research spaces, every aspect of the UT Tyler Health Science Center is designed to enhance the educational experience. This dynamic campus is not just a hub for learning; it’s a catalyst for progress in healthcare education and a testament to UT Tyler's commitment to shaping the future of healthcare in the East Texas region.

Office of Health Affairs

School of Health Professions

School of Medicine

Center for Biomedical Research

Simulation in Medicine and Immersive Learning Experience Center

Watson W. Wise Medical Research Library

Public Health Laboratory of East Texas

UT Health North Campus Tyler (UTHET)

HOPE Cancer Center

A Regional Leader in Health Research

UT Tyler pioneers solutions to improve health. Several research centers, including the Center for Mycobacterial Treatment and Discovery and the Center for Biomedical Research, are housed on this campus. The centers build on our history of innovative treatments for lung disease and focus on the health concerns of rural populations through projects funded by agencies like the National Institutes of Health and the Centers for Disease Control and Prevention. Students benefit from hands-on research opportunities and instruction informed by the latest developments in the field. 

Dr. Maolin Lu

Assistant Professor of Cellular and Molecular Biology

Meet Professor Lu

Community Outreach and Engagement

Ut health east texas.

In its regional network of hospitals, clinics and other facilities, UT Health East Texas delivers world-class care to thousands of patients each year while conducting clinical trials and training the next generation of professionals through UT Tyler’s unique programs. The UT Tyler Health Science Center is home to UT Health North Campus Tyler .

Public Health Programs

Faculty, staff and students at the UT Tyler Health Science Center campus connect their expertise with local community needs to assist traditionally underserved populations through an array of health and outreach programs, including behavioral health telemedicine services for rural populations, cancer screenings, parental education, lifestyle changes and more.

Regional Health Resources

To strengthen regional healthcare, we train community health workers, promote healthcare careers in underrepresented communities and support community health education and development efforts.

Connect With Us

The university of texas at tyler health science center.

Phone:   903.877.7777

We’re pioneering the future of healthcare in East Texas. Find out how you can join us.

11937 U.S. Hwy. 271 Tyler, TX 75708-3154