Abstract: Behavioral public administration is the analysis of public administration from the micro-perspective of individual behavior and attitudes by drawing upon insights from psychology on behavior of individuals and groups. We discuss how scholars in public administration currently draw on theories and methods from psychology, and related fields, and point to research in public administration that could benefit from further integration. An analysis of public administration topics through a psychological lens can be useful to confirm, nuance or extend classical public administration theories. As such, behavioral public administration complements traditional public administration. Furthermore, it could be a two-way street for psychologists who want to test the external validity of their theories in a political-administrative setting. Finally, we propose four principles to narrow the gap between public administration and psychology.

Abstract: This paper is an attempt to broaden economic discourse by importing insights into human behavior not just from psychology, but also from sociology and anthropology. Whereas the concept of the decision-maker in standard economics is the rational actor and, in early work in behavioral economics, the quasi-rational actor influenced by the context of the moment of decision-making, in some recent work in behavioral economics the decision-maker could be called the enculturated actor. This actor's preferences, perception, and cognition are subject to two deep social influences: (a) the social contexts to which he has become exposed and, especially, accustomed; and (b) the cultural mental models—including categories, identities, narratives, and worldviews—that he uses to process information. The paper traces how these factors shape individual behavior through the endogenous determination of preferences and the lenses through which individuals see the world—their perception and interpretation of situations. The paper offers a tentative taxonomy of the social determinants of behavior and describes the results of controlled and natural experiments that only a broader view of these determinants can plausibly explain. The perspective suggests more realistic models of human behavior for explaining outcomes and designing policies.

Abstract: Regular physical activity is associated with physical, social and mental health benefits, whilst insufficient physical activity is associated with several negative health outcomes (e.g. metabolic problems). Population monitoring of physical activity is important to gain insight into prevalence of compliance to physical activity recommendations, groups at risk and changes in physical activity patterns. This review aims to provide an overview of all existing studies that measure physical activity in youth, in cross-European studies, to describe the variation in population levels of physical activity and to describe and define challenges regarding assessment methods that are used.A systematic search was performed on six databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey), supplemental forward- and backward tracking was done and authors' and experts' literature databases were searched to identify relevant articles. Journal articles or reports that reported levels of physical activity in the general population of youth from cross-European studies were included. Data were reviewed, extracted and assessed by two researchers, with disagreements being resolved by a third researcher. The review protocol of this review is published under registration number CRD42014010684 in the PROSPERO database.The search resulted in 9756 identified records of which 30 articles were included in the current review. This review revealed large differences between countries in prevalence of compliance to physical activity recommendations (i.e. 60 min of daily moderate- to vigorous-intensity physical activity (MVPA)) measured subjectively (5-47%) and accelerometer measured minutes of MVPA (23-200 min). Overall boys and children were more active than girls and adolescents. Different measurement methods (subjective n = 12, objective n = 18) and reported outcome variables (n = 17) were used in the included articles. Different accelerometer intensity thresholds used to define MVPA resulted in substantial differences in MVPA between studies conducted in the same countries when assessed objectively.Reported levels of physical activity and prevalence of compliance to physical activity recommendations in youth showed large variation across European countries. This may reflect true variation in physical activity as well as variation in assessment methods and reported outcome variables. Standardization across Europe, of methods to assess physical activity in youth and reported outcome variables is warranted, preferably moving towards a pan-European surveillance system combining objective and self-report methods.

Abstract: Behavioral economics (BE) in psychology focuses on the application of traditional microeconomics concepts to the study of behavior, particularly the cross-species analysis of consumption broadly defined and choice. Here, we review key concepts such as demand, substitution, and complementarity within a behavioral psychology framework, novel behavioral economics analysis techniques for quantifying demand elasticity and patterns of choice behaviors, and broader implications for organizational decision-making and empirical public policy. Copyright © 2015 John Wiley & Sons, Ltd.

Abstract: When new consumer products are developed and later launched, 50 to 75 percent of them are removed from the market far short of meeting their projected financial targets. In short: they fail. We conclude that this failure is due to institutionalized insufficiencies in the use of the sciences that are best geared to understand and predict consumer behaviour, viz. the behavioural sciences. These are not necessarily the same as the marketing science that is performed by marketing departments. A scientific approach to understanding consumer behaviour appears to be lacking in many corporate research surroundings. This often is in great contrast with their high levels of technological science, paralleled by their respective research budgets. In this paper we present five problem areas that may contribute to this mismatch, contributing to needlessly high numbers of product failures. We have termed these factors: (1) ‘pillars’ (too many different functions addressing different aspects of the consumers and of product development), (2) ‘higher management focus’ (not geared towards understanding consumer behaviour), (3) ‘popular science books’ (out-dated research directives resulting from a hierarchical management model), (4) ‘quality and Quality’ (a definition of ‘quality’ that leads to invalid quality parameters), and (5) ‘psychophobia’ (the latent fear of trusting behavioural science results), respectively.

Abstract: Diverse perspectives in science promote innovation and creativity, and represent the needs of a diverse populace. However, many science fields lack gender diversity. Although fewer women than men pursue careers in physical science, technology, engineering, and mathematics (pSTEM), more women than men pursue careers in behavioral science. The current work measured the relationship between first-year college students’ stereotypes about science professions and course completion in science fields over the next 3 years. pSTEM careers were more associated with self-direction and self-promotion (i.e., agency) than with working with and for the betterment of others (i.e., communion). On the flip side, behavioral science careers were associated with communion to a greater degree than with agency. Women completed a lower proportion of pSTEM courses than did men, but this gender disparity disappeared when women perceived high opportunity for communion in pSTEM. Men pursued behavioral science courses to a lesser degree than did women; this disparity did not exist when men perceived ample opportunity for agency in behavioral science. These results suggest highlighting the communal nature of pSTEM and the agentic nature of behavioral science in pre-college settings may promote greater gender diversity across science fields.

Abstract: Computational thinking is an approach to problem solving that is typically employed by computer programmers. The advantage of this approach is that solutions can be generated through algorithms that can be implemented as computer code. Although computational thinking has historically been a skill that is exclusively taught within computer science, there has been a more recent movement to introduce these skills within other disciplines. Psychology is an excellent example of a discipline that would benefit from computational thinking skills because of the nature of questions that are typically asked within the discipline. However, there has not been a formal curriculum proposed to teach computational thinking within psychology and the behavioural sciences. I will argue that computational thinking is a fundamental skill that can easily be introduced to psychology students throughout their undergraduate education. This would provide students with the skills necessary to become successful researchers, and woul...

Abstract: Executive Order – Using Behavioral Science Insights to Better Serve the American People A growing body of evidence demonstrates that behavioral science insights – research findings from fields such as behavioral economics and psychology about how people make decisions and act on them – can be used to design government policies to better serve the American people. Where Federal policies have been designed to reflect behavioral science insights, they have substantially improved outcomes for the individuals, families, communities, and businesses those policies serve. For example, automatic enrollment and automatic escalation in retirement savings plans have made it easier to save for the future, and have helped Americans accumulate billions of dollars in additional retirement savings. Similarly, streamlining the application process for Federal financial aid has made college more financially accessible for millions of students. To more fully realize the benefits of behavioral insights and deliver better results at a lower cost for the American people, the Federal Government should design its policies and programs to reflect our best understanding of how people engage with, participate in, use, and respond to those policies and programs. By improving the effectiveness and efficiency of Government, behavioral science insights can support a range of national priorities, including helping workers to find better jobs; enabling Americans to lead longer, healthier lives; improving access to educational opportunities and support for success in school; and accelerating the transition to a low-carbon economy. NOW, THEREFORE, by the authority vested in me as President by the Constitution and the laws of the United States, I hereby direct the following: Section 1. Behavioral Science Insights Policy Directive. (a) Executive departments and agencies (agencies) are encouraged to: (i) identify policies, programs, and operations where applying behavioral science insights may yield substantial improvements in public welfare, program outcomes, and program cost effectiveness; (ii) develop strategies for applying behavioral science insights to programs and, where possible, rigorously test and evaluate the impact of these insights; (iii) recruit behavioral science experts to join the Federal Government as necessary to achieve the goals of this directive; and (iv) strengthen agency relationships with the research community to better use empirical findings from the behavioral sciences.

Abstract: Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.

Abstract: The Centre for Behaviour Change at University College London (UCL) is a new venture that has grown out of the work that we have been doing in the Health Psychology Research Group at UCL and seeks to harness the different pockets of behaviour change work in different disciplines across UCL. A lot of our work in health focuses on the adoption of evidence-based guidelines in practice; not just designing and evaluating interventions, but also developing usable tools for people who are tasked with changing behaviours. These tools aim to enable those who do not necessarily have a background in behavioural science to understand the behaviours they are trying to change and design appropriate interventions.

Abstract: For centuries, decision scholars paid little attention to emotions: Decisions were modeled in normative and descriptive frameworks with little regard for affective processes. Recently, however, an "emotions revolution" has taken place, particularly in the neuroscientific study of decision making, putting emotional processes on an equal footing with cognitive ones. Yet disappointingly little theoretical progress has been made. The concepts and processes discussed often remain vague, and conclusions about the implications of emotions for rationality are contradictory and muddled. We discuss three complementary ways to move the neuroscientific study of emotion and decision making from agenda setting to theory building. The first is to use reverse inference as a hypothesis-discovery rather than a hypothesis-testing tool, unless its utility can be systematically quantified (e.g., through meta-analysis). The second is to capitalize on the conceptual inventory advanced by the behavioral science of emotions, testing those concepts and unveiling the underlying processes. The third is to model the interplay between emotions and decisions, harnessing existing cognitive frameworks of decision making and mapping emotions onto the postulated computational processes. To conclude, emotions (like cognitive strategies) are not rational or irrational per se: How (un)reasonable their influence is depends on their fit with the environment.

Abstract: Behavioral economics is an approach to understanding decision making and behavior using principles of behavioral science and economics (Hursh, 1980). An area of investigation in behavioral economics includes evaluating demand for a commodity (such as drug and nondrug reinforcers), given changes in p

Abstract: Thank you very much for reading advances in experimental social psychology advances in experimental social psychology. Maybe you have knowledge that, people have look hundreds times for their favorite novels like this advances in experimental social psychology advances in experimental social psychology, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious virus inside their desktop computer.

Abstract: Emerging scientific and technological opportunities, such as new sensor tools that better characterize neurological, behavioral, and social processes, have the potential to produce a scientific paradigm shift in the behavioral and social sciences. This shift from a fragmented data-poor science to an integrated data-rich science facilitates greater translation from basic to applied research and from applied research to clinical practice. In November 2016, the U.S. National Institutes of Health (NIH) Office of Behavioral and Social Sciences Research (OBSSR) released its strategic plan for fiscal years 2017 through 2021, which seeks to take advantage of these scientific and technological developments ([ 1 ][1]). Here, we outline four key developments that influenced the scientific priorities of the OBSSR strategic plan, each of which offers the potential for accelerating research and translation in the behavioral and social sciences. Advances in neuroscience experimental approaches and technologies provide an ability to observe brain function and activity in real time and with increasing levels of granularity ([ 2 ][2]), but these brain functions and activities do not occur in isolation; they are influenced by an organism’s environment and are expressed as behaviors that, in turn, have the potential to influence the environment. To understand these complex dynamic interactions, the brain must be studied in the context of environmental and social systems. The behavioral and cognitive neurosciences have already invested in this integration, but more progress and expanded attention are needed to further integrate brain functions with higher-level processes (for example, social and cultural neuroscience and neuroeconomics). New transdisciplinary efforts that merge these areas of research hold promise for a more comprehensive research effort that explores the mechanisms of behavior and social phenomena that reside both within and beyond the dura. Advances in measurement science and technology are converging to provide the basis for increasingly accurate measurement that will accelerate new discoveries. The precision and efficiency of self-reported measurement approaches have been improved greatly by the application of (i) modern psychometric theory (for example, item response theory) and (ii) smartphone technologies to obtain prospective, real-time assessments throughout the course of a day (for example, ecological momentary assessment). Digital footprints from routine interactions of people with technology provide new methods of capturing thought and behavior, and the rapid emergence of sensor technologies has provided an efficient and objective means for assessing physiology, behavior, and social and environmental contexts. The application of these scientific and technological advances to the measurement of behavioral and social processes provides a level of granularity and precision that has the potential to transform the behavioral and social sciences into a much more data-rich science ([ 3 ][3]). Advances in technology also hold the potential to transform the means by which behavioral and social science interventions are delivered. These interventions are often resource- and labor-intensive, which results in limited reach, scalability, and duration. The limited duration of these interventions negatively affects the ability to maintain behavioral change. The operationalization of these interventions into code ensures treatment fidelity from research to clinical practice settings and may extend their reach to anyone in any place at any time. Efficient delivery of behavioral and social change strategies via smartphones and other digital technologies provides the potential to extend treatment duration and thus improves behavioral maintenance. Technology-based delivery of behavioral and social interventions also holds promise for improving the precision of these interventions, not only by personalizing or tailoring treatment at initiation but also by adapting the intervention over the course of treatment on the basis of context, timing, and prior responses ([ 4 ][4]). The behavioral and social sciences are benefiting from the expansion of large-scale surveys and longitudinal cohort projects that take advantage of digital technologies to provide extensive databases for studying the role of behavioral and social factors on health ([ 5 ][5]). Long-standing survey projects (for example, the National Health Interview Survey) continue to provide new and important data, and these projects will soon be complemented with two large NIH-supported efforts, the Precision Medicine Initiative Cohort Program (PMI-CP) and the Environmental influences on Child Health Outcomes (ECHO) Program. These efforts will include much larger and more diverse cohorts than previously available, as well as new approaches for obtaining considerable data on cohort participants. These projects also provide a platform from which behavioral and social science researchers can evaluate the effects of population-level interventions and layer additional studies that target specific subpopulations in greater depth. Combined with advances in big data analytics and data integration techniques, an open data-sharing approach for behavioral and social science research will allow those in the field to extend the use of research data. The OBSSR strategic plan addresses these four as well as other emerging opportunities and challenges that have the potential to transform the behavioral and social sciences. Scientific priorities include (i) improvement in the flow of basic to applied science through the research-product pipeline, (ii) advances in measurement and methodological approaches, and (iii) improvements in the dissemination and implementation of social and behavioral interventions. These scientific priorities are supported through the OBSSR foundational processes of communication, coordination, training, and evaluation. Achieving the objectives of this strategic plan and leveraging the emerging opportunities to transform the field of behavioral and social sciences will require a coordinated effort, not only among the NIH institutes and centers but also with our sister government agencies, private research and funding entities, and the larger social, behavioral, and biomedical research communities. These current and emerging opportunities are aligning to transform the behavioral and social sciences and thus to enhance their contribution to the health of the nation. 1. [↵][6]National Institutes of Health (NIH), OBSSR Strategic Plan, Fiscal Years 2017–2021 (2015); . 2. [↵][7]NIH, BRAIN 2025: A scientific vision (2014); . 3. [↵][8]W. T. Riley, A new era of clinical research methods in a data-rich environment, in Oncology Informatics: Using Health Information Technology to Improve Processes and Outcomes in Cancer , B. W. Hesse, D. K. Ahern, E. Beckjord, Eds. (Academic Press, 2016), pp. 343–355. 4. [↵][9]1. I. Nahum-Shani, 2. E. B. Hekler, 3. D. Spruijt-Metz , Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework. Health Psychol. 34, 1209–1219 (2015). [OpenUrl][10] 5. [↵][11]1. B. R. Schatz , National surveys of population health: Big data analytics for mobile health monitors. Big Data 3, 219–229 (2016). [OpenUrl][12] [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #xref-ref-1-1 "View reference 1 in text" [7]: #xref-ref-2-1 "View reference 2 in text" [8]: #xref-ref-3-1 "View reference 3 in text" [9]: #xref-ref-4-1 "View reference 4 in text" [10]: {openurl}?query=rft.jtitle%253DHealth%2BPsychol.%26rft.volume%253D34%26rft.spage%253D1209%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [11]: #xref-ref-5-1 "View reference 5 in text" [12]: {openurl}?query=rft.jtitle%253DBig%2BData%26rft.volume%253D3%26rft.spage%253D219%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx

Abstract: PurposeBehavioral and social science (BSS) competencies are needed to provide quality health care, but psychometrically validated measures to assess these competencies are difficult to find. Moreover, they have not been mapped to existing frameworks, like those from the Liaison Committee on Medical

Abstract: The concept of nudge theory, from the fields of behavioural science, political theory and behavioural economics, has sparked government initiatives yielding significant public value. A nudge is a method for predictably altering behaviour without restricting consumer choice options or significantly changing incentives. Nudges work by leveraging default human behaviour such as the tendency to take the path of least resistance when exercising choice. Government agencies have run many successful trials with simple textual nudges designed to positively influence behaviours such as tax compliance, voter registration and student attrition. This article develops the concept of the digital nudge in social security administration. The digital nudge leverages predictive analytics technology within a digital government framework to support a social investment policy approach. Based on a literature review of nudges within a digital government context, the article identifies examples of innovation within social security administration where nudges are contributing to better social outcomes. At the same time, concerns regarding ethics and privacy are identified as nudges are applied at the individual rather than the population level. The use of data and personal information to drive the nudge process has to be managed in such a way that individual rights are protected. This requirement has to be reconciled with the broader interests of society in achieving affordable outcomes, the parameters of which are determined through the political process.

Abstract: This study aimed to examine motor proficiency in young children, focusing on potential gender differences. For that purpose, the Bruininks-Oseretsky Test of Motor Proficiency–Long Form (BOTMP-LF) w...

Abstract: The essence of social networks is that they can influence people's public opinions and group behaviors form quickly. Negative group behavior influences societal stability significantly, but existing behavior-induction approaches are too simple and inefficient. To automatically and efficiently induct behavior in social networks, this article introduces trust agents and designs their features according to group behavior features. In addition, a dynamics control mechanism can be generated to coordinate participant behaviors in social networks to avoid a specific restricted negative group behavior.

Abstract: Modeling physical activity propagation, such as physical exercise level and intensity, is the key to preventing the conduct that can lead to obesity and to spreading wellness and healthy behavior in a social network. The authors introduce a model for Topic-aware Community-level Physical Activity Propagation (TaCPP) to analyze physical activity propagation and social influence at different granularities. Given a social network, the TaCPP model first integrates the correlations between the content of social communication and social influences and then uses a hierarchical approach to detect a set of communities and their reciprocal influence strength. The authors' experimental evaluation shows not only the effectiveness of their approach but also the correlation of the detected communities with various health outcome measures.

Abstract: Thank you very much for reading animal research and human health advancing human welfare through behavioral science. As you may know, people have search numerous times for their favorite novels like this animal research and human health advancing human welfare through behavioral science, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they juggled with some infectious virus inside their desktop computer.

Abstract: This chapter traces the rise of behavioral policy from the works of behavioral economists in the 1960s to the recent official interest in units designed to improve public policies. It argues that behavioral economics does not pose a threat to mainstream economics; moreover, policy-makers find it helpful in solving practical problems using randomized controlled trials. It also leads to greater innovation within public bureaucracies, better use of social science evidence, and a more citizen-friendly public administration. Behavioral techniques can also empower the citizen and interest groups by helping them nudge policy-makers to be accountable and responsive. A behavioral approach can open up public bureaucracies to citizen influence and create a more responsive public realm that uses social science evidence in a timely and adaptive way.

Abstract: The Teaching Writing series publishes user-friendly writing guides penned by authors with publishing records in their subject matter. Infused with multidisciplinary examples, humor, and a healthy dose of irreverence, Fallon helps emerging researchers successfully navigate the intellectual and emotional challenges of writing quantitative research reports. After reinforcing foundations in methodology, statistics, and writing in the first section of the book, emerging researchers work through a series of questions to construct their research report. The final section contains sample papers generated by undergraduates illustrating three major forms of quantitative research – primary data collection, secondary data analysis, and content analysis. Writing up Quantitative Research in the Social and Behavioral Sciences is appropriate for research methods classes in communication, criminology or criminal justice, economics, education, political science, psychological science, social work, and sociology. Individual students and novice researchers can also read the book as a supplement to any course or research experience that requires writing up quantitative data.

Abstract: We believe cultural group selection is an elegant theoretical framework to study the evolution of complex human behaviours, including large-scale cooperation. However, the empirical evidence on key theoretical issues – such as levels of within- and between-group variation and effects of intergroup competition – is so far patchy, with no clear case where all the relevant assumptions and predictions of cultural group selection are met, to the exclusion of other explanations.