Behavioral Science Research Research Articles

Abstract CN02-01: Is it too late or too little? Prevention through physical activity

Abstract Physical activity is one of the leading ways to prevent cancer with estimates concluding 30% of cancers in the US could be improved through improvements to diet, obesity and exercise behaviors. Despite the cancer and other chronic disease benefits from physical activity, the majority of the US population remains inactive. Efforts to implement cancer prevention through physical activity are met with questions about the specifics of the relation between physical activity and cancer: Everyone? How much? How hard? Evidence is accumulating that physical activity across the lifecourse is important for cancer prevention. In addition to reducing risk of colon cancer by more than 20%, physical activity also reduces risk of colon polyps. Lifetime physical activity levels are consistently related to several cancers. Adolescent physical activity is associated with a reduced risk of colon cancer. This epidemiologic evidence has important policy implications as school physical education classes and class time are being reduced. Research has also suggested that physical activity may have less effect on cancer risk among population subgroups including obese individuals for some cancers. While the physical activity guidelines recommend 30 minutes of moderate activity each day, they also suggest more is better. However, health promotion and behavioral science research has had only modest success at achieving sustained physical activity levels through intervention. We will review data on whether some benefit can be achieved at lower levels or how much greater the risk reduction may be at higher levels. This is particularly important in light of research indicating that sedentary time is, independent of physical activity level, associated with an elevated risk of several cancers. Together, this data has pushed prevention messaging in the direction of “do something” instead of “do more.” While the risks of sedentary behavior are important, such messages may detract from research suggesting that for some cancers, such as prostate, participation in vigorous physical activity may be necessary to see a reduction in risk. The benefits of physical activity for cancer prevention are well known. However, the message may need more refinement in light of emerging evidence on the timing, intensity and duration of activity necessary to reduce risk of specific cancers. Citation Format: Kate Y. Wolin. Is it too late or too little? Prevention through physical activity. [abstract]. In: Proceedings of the Thirteenth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2014 Sep 27-Oct 1; New Orleans, LA. Philadelphia (PA): AACR; Can Prev Res 2015;8(10 Suppl): Abstract nr CN02-01.

The White House Social & Behavioral Sciences Team: Lessons learned from year one

On September 15, 2015, President Obama signed Executive Order 13707 titled “Using Behavioral Science Insights to Better Serve the American People.” The order directs federal agencies to integrate behavioral insights into their policies and programs and formally establishes the Social and Behavioral Sciences Team (SBST). Originally launched in 2014, SBST translates insights from behavioral science research into improvements in federal policies and programs. In its first annual report, SBST detailed results from projects that drew on behavioral insights to promote retirement security, expand college access and affordability, connect workers and small businesses with economic opportunities, improve health outcomes, and increase program integrity and government efficiency. The results of SBST projects offer important lessons for bringing a behavioral perspective to federal policy. The executive order provides a framework for future policy applications.

Blinding prosecutors to defendants’ race: A policy proposal to reduce unconscious bias in the criminal justice system

Racial minorities are disproportionately imprisoned in the United States. This disparity is unlikely to be due solely to differences in criminal behavior. Behavioral science research has documented that prosecutors harbor unconscious racial biases. These unconscious biases play a role whenever prosecutors exercise their broad discretion, such as in choosing what crimes to charge and when negotiating plea bargains. To reduce this risk of unconscious racial bias, we propose a policy change: Prosecutors should be blinded to the race of criminal defendants wherever feasible. This could be accomplished by removing information identifying or suggesting the defendant's race from police dossiers shared with prosecutors and by avoiding mentions of race in conversations between prosecutors and defense attorneys. Race is almost always irrelevant to the merits of a criminal prosecution; it should be omitted from the proceedings whenever possible for the sake of justice.

From ideas to efficacy: The ORBIT model for developing behavioral treatments for chronic diseases.

Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease prevention and outcomes. Findings from basic behavioral and social sciences research hold great promise for addressing behaviorally based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for developing behavioral treatments for preventing and treating chronic diseases. The Obesity-Related Behavioral Intervention Trials (ORBIT) model for behavioral treatment development features a flexible and progressive process, prespecified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization. This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and prespecified milestones for forward or backward movement across phases. The ORBIT model provides a progressive, clinically relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases. (PsycINFO Database Record

Physical Activity Measures in the Healthy Communities Study.

The risk of obesity is reduced when youth engage in recommended levels of physical activity (PA). For that reason, public health organizations in the U.S. have encouraged communities to implement programs and policies designed to increase PA in youth, and many communities have taken on that challenge. However, the long-term effects of those programs and policies on obesity are largely unknown. The Healthy Communities Study is a large-scale observational study of U.S. communities that is examining the characteristics of programs and policies designed to promote healthy behaviors (e.g., increase PA and improve diet) and determining their association with obesity-related outcomes. The purpose of this paper is to describe the methods used to measure PA in children and the personal and community factors that may influence it. The study used both self-reported and objective measures of PA, and measured personal, family, and home influences on PA via three constructs: (1) PA self-schema; (2) parental support; and (3) parental rules regarding PA. Neighborhood and community factors related to PA were assessed using three measures: (1) child perceptions of the neighborhood environment; (2) availability of PA equipment; and (3) attributes of the child's street segment via direct observation. School influences on children's PA were assessed via three constructs: (1) school PA policies; (2) child perceptions of the school PA environment; and (3) school outdoor PA environment. These measures will enable examination of the associations between characteristics of community PA programs and policies and obesity-related outcomes in children and youth.

User-Friendly Taxpaying

Technology is revolutionizing our lives. With the touch of a button or a simple voice command, we can instantly order groceries, get directions, or find the nearest sushi restaurant. Sensibly, the private sector has capitalized on these recent innovations to drive up profits. To sell more laundry detergent, Amazon now enables consumers to order refills by simply pressing the “dash button” mounted above their laundry machines. Starbucks lures more customers by allowing them to pre-order online and have their drink waiting when they arrive at the store. The theory behind this approach is simple: if you want someone to use your product or service, you should make it as quick and easy as possible for them to do so. This Article makes a novel argument to extend this line of reasoning to encourage better compliance with the tax laws. In making this argument, the Article draws upon behavioral science research showing that complexity impacts individuals’ decision making and encourages dishonesty. The Article then offers a number of proposals for how policymakers could simplify individuals’ interactions with the tax system. For example, the IRS could allow taxpayers to easily record their income and deductions online during the year using smart phones or tablets. Those items could be stored in an online personal taxpayer account and, at the end of the year, automatically uploaded to an electronic return. Easing the burden of taxpaying should encourage more taxpayers to report honestly, in addition to reducing their compliance costs. In the same way that designing products or websites to be user-friendly encourages their use, making the tax system more user-friendly should attract more voluntary participation.

The Progression of Programmatic Research in Contextual Behavioral Science: Response to O’Donohue, Snipes, and Soto

The criticisms of the target article are examined and discussed in the context of the larger goals of contextual behavioral science. The central claims of “Overselling” findings from a published dissertation to a peer-reviewed article and a self-help book are examined point-by-point. After clarifying the posited concerns, we find that they are dominantly based on misunderstandings of the assessment data used or improved data analytic methods employed. Criticisms of the larger literature of acceptance and commitment therapy (ACT) are examined, and the larger scientific strategy employed by the contextual behavioral science movement is described with an emphasis on replications in the area of processes of change for ACT (and modification of these processes) in order to improve diabetes as well as other health behaviors.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks. Bill & Melinda Gates Foundation.

Work experiences on MTurk: Job satisfaction, turnover, and information sharing

Amazon's Mechanical Turk (MTurk) is an online marketplace for work, where Requesters post Human Intelligence Tasks (HITs) for Workers to complete for varying compensation. Past research has focused on the quality and generalizability of social and behavioral science research conducted using MTurk as a source of research participants. However, MTurk and other crowdsourcing platforms also exemplify trends toward extremely short-term contract work. We apply principles of industrial–organizational (I–O) psychology to investigate MTurk Worker job satisfaction, information sharing, and turnover. We also report the top best and worst Requester behaviors (e.g., building a relationship, unfair pay) that affect Worker satisfaction. Worker satisfaction was consistently negatively related to turnover as expected, indicating that this traditional variable operates similarly in the MTurk work context. However, few of the traditional predictors of job satisfaction were significant, signifying that new operational definitions or entirely new variables may be needed in order to adequately understand the experiences of crowdsourced workers. Coworker friendships consistently predicted information sharing among Workers. The findings of this study are useful for understanding the experiences of crowdsourced workers from the perspective of I–O psychology, as well as for researchers using MTurk as a recruitment tool.

Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences

Ordinary least squares and stepwise selection are widespread in behavioral science research; however, these methods are well known to encounter overfitting problems such that R2 and regression coefficients may be inflated while standard errors and p values may be deflated, ultimately reducing both the parsimony of the model and the generalizability of conclusions. More optimal methods for selecting predictors and estimating regression coefficients such as regularization methods (e.g., Lasso) have existed for decades, are widely implemented in other disciplines, and are available in mainstream software, yet, these methods are essentially invisible in the behavioral science literature while the use of sub optimal methods continues to proliferate. This paper discusses potential issues with standard statistical models, provides an introduction to regularization with specific details on both Lasso and its related predecessor ridge regression, provides an example analysis and code for running a Lasso analysis in R and SAS, and discusses limitations and related methods.

Social & Behavioral Sciences Research: Is now the time to invest?

Social & Behavioral Sciences Research: Is now the time to invest?

Understanding unmet contraceptive needs among rural Khasi men and women in Meghalaya

There is a global push for increased access to contraception to respond to unmet contraceptive needs. Meghalaya state, with a majority of Indigenous people, has one of the highest unmet contraceptive needs and the lowest contraceptive prevalence rates in India. This qualitative study explores the reasons for the low uptake of contraceptives among Khasi people in a rural district. While policy makers assume that individuals may not be practising family planning because of religion and lack of education, couples actually do use a variety of ‘natural’ or ‘traditional’ contraceptive methods to obtain their desired family composition and size. Health providers focus on the provision of hormonal contraceptives, such as the pill, and on technologies such as IUDs and tubectomies that require regular follow-ups by trained medical staff. Health concerns, distrust of contraceptive technologies, the inadequate local health system and a desire to have more than two children are important factors in the low uptake of available contraceptive technologies. Contraceptive choices in rural areas are shaped by the historically problematic political engagement of Indigenous people with the central state, with policy implementation taking place on the basis of widespread assumptions rather than on evidence from contextually relevant behavioural sciences research.

An Efficient Method for Detecting and Extracting Nomological Networks

The accumulated literature base in the behavioral sciences represents the IS discipline’s greatest source of knowledge, and yet the same literature has grown beyond human comprehension. An experiment is conducted showing the inability of experts to retrieve relevant constructs using full-text search. To address this inability to access the body of theoretical behavioral science research we propose a novel IT artifact built on an information extraction approach to nomological network discovery. Based on the design science paradigm we develop a three-step process for extraction and assembly of nomological networks proceeding through article download, hypothesis extraction, variable extraction, and finally to variable integration. Rule-based vs. machine learning algorithms are evaluated and compared to determine the best approach for the extraction steps. A dataset of all the relevant behavioral studies from two top journals in Information Systems and Psychology is used to evaluate the approach in comparison to expert decisions, leading into a discussion of limitations and possible extensions.

Good Samaritans in Networks: An Experiment on How Networks Influence Egalitarian Sharing and the Evolution of Inequality.

The fact that the more resourceful people are sharing with the poor to mitigate inequality—egalitarian sharing—is well documented in the behavioral science research. How inequality evolves as a result of egalitarian sharing is determined by the structure of “who gives whom”. While most prior experimental research investigates allocation of resources in dyads and groups, the paper extends the research of egalitarian sharing to networks for a more generalized structure of social interaction. An agent-based model is proposed to predict how actors, linked in networks, share their incomes with neighbors. A laboratory experiment with human subjects further shows that income distributions evolve to different states in different network topologies. Inequality is significantly reduced in networks where the very rich and the very poor are connected so that income discrepancy is salient enough to motivate the rich to share their incomes with the poor. The study suggests that social networks make a difference in how egalitarian sharing influences the evolution of inequality.

English

Mixed methods research is recognized as a third model of research in social and behavioral sciences. Its value for educational research just recently began to be discussed in the literature (Ponce, 2014: Scott & Sutton, 2009: Ellis, 2005). A mixed methods research study means the use of quantitative and qualitative methods as components of a research design (Caruth, 2013; Ponce, 2011; Creswell, 2009; Greene, 2007) or a research program (Phillips, 2009). Most of the literature on mixed methods research could be considered generic (Creswell, 2009). This means that the discussion centered on research designs with little or no relation to any particular disciplinary context. According to Creswell (2009), the development of literature in a particular discipline's context, using mixed methods research, will help to strength the mixed research movement. In this article, the authors explain mixed methods research and its possible uses, strengths, and challenges in educational research.

Creating a science of homelessness during the Reagan era.

POLICY POINTS: A retrospective analysis of federally funded homeless research in the 1980s serves as a case study of how politics can influence social and behavioral science research agendas today in the United States. These studies of homeless populations, the first funded by the National Institute of Mental Health, demonstrated that only about a third of the homeless population was mentally ill and that a diverse group of people experienced homelessness. This groundbreaking research program set the mold for a generation of research and policy characterizing homelessness as primarily an individual-level problem rather than a problem with the social safety net. A decade after the nation's Skid Rows were razed, homelessness reemerged in the early 1980s as a health policy issue in the United States. While activists advocated for government-funded programs to address homelessness, officials of the Reagan administration questioned the need for a federal response to the problem. In this climate, the National Institute of Mental Health (NIMH) launched a seminal program to investigate mental illness and substance abuse among homeless individuals. This program serves as a key case study of the social and behavioral sciences' role in the policy response to homelessness and how politics has shaped the federal research agenda. Drawing on interviews with former government officials, researchers, social activists, and others, along with archival material, news reports, scientific literature, and government publications, this article examines the emergence and impact of social and behavioral science research on homelessness. Research sponsored by the NIMH and other federal research bodies during the 1980s produced a rough picture of mental illness and substance abuse prevalence among the US homeless population, and private foundations supported projects that looked at this group's health care needs. The Reagan administration's opposition to funding "social research," together with the lack of private-sector support for such research, meant that few studies examined the relationship between homelessness and structural factors such as housing, employment, and social services. The NIMH's homelessness research program led to improved understanding of substance abuse and mental illness in homeless populations. Its primary research focus on behavioral disorders nevertheless unwittingly reinforced the erroneous notion that homelessness was rooted solely in individual pathology. These distortions, shaped by the Reagan administration's policies and reflecting social and behavioral scientists' long-standing tendencies to emphasize individual and cultural rather than structural aspects of poverty, fragmented homelessness research and policy in enduring ways.

The Need to Restructure the Substance Misuse Behavioral Science Research Enterprise

Two major dynamics characterize the field of substance misuse behavioral science research in recent decades. First, assessments of the outcomes of prevention and treatment services have shown increasing conceptual and methodological sophistication, but, in general, have not kept pace with new developments in biostatistics and multivariate analyses. Second, funding for richer, more informed evaluation efforts to assess the efficacy, cost benefits, and longer term outcomes of these services has declined significantly. These two processes are creating a growing crisis in the field. Researchers, program administrators, and legislative bodies at the state and federal levels have each contributed to this crisis. A significant restructuring of what we do and when (appropriate timing), their underpinnings (theoretical, empirical, stakeholder agendas and goals, etc.) and how we do it, and the ongoing availability and accessibility of relevant human and non-human resources, amongst other considerations, is needed. Although this Op-Ed piece prevents full discussion of these issues, as someone who has been involved in this field for many years, I feel several key issues need to be addressed:

Mobile health applications for asthma

Mobile health applications for asthma

Public Understanding and Knowledge of Rip Currents and Beach Safety in the UK

Rip currents present a severe hazard for water users on beaches and account for the greatest cause of lifeguard rescues worldwide. The physical dynamics of rip currents are well studied, and more recently, the social and behavioural science research surrounding human interaction of rip currents has been expanding, providing a social perspective and feeding into public education strategies. The aim of this study was to assess levels of public understanding of rip currents and beach safety on UK beaches. A questionnaire was undertaken (N = 407) during the summer of 2012 on four beaches. Beach users had a poor knowledge of rip currents (n = 263), but those who have been caught in a rip have a higher level of knowledge. Conversely, beach users had a good understanding of what the beach safety flags indicated (n = 314), and most people complied with this flag system (n = 339). In addition, people previously educated on rip currents had a higher knowledge, and lifeguards proved to be the most effective form of education. The study presents an insight into UK beach users’ knowledge of rip currents and provides more evidence with which to pilot a rip current education scheme within the UK.

Public Understanding and Knowledge of Rip Currents and Beach Safety in the UK

Rip currents present a severe hazard for water users on beaches and account for the greatest cause of lifeguard rescues worldwide. The physical dynamics of rip currents are well studied, and more recently, the social and behavioural science research surrounding human interaction of rip currents has been expanding, providing a social perspective and feeding into public education strategies. The aim of this study was to assess levels of public understanding of rip currents and beach safety on UK beaches. A questionnaire was undertaken (N = 407) during the summer of 2012 on four beaches. Beach users had a poor knowledge of rip currents (n = 263), but those who have been caught in a rip before have a higher level of knowledge. Conversely, beach users had a good understanding of what the beach safety flags indicated (n = 314), and most people complied with this flag system (n = 339). In addition, those previously educated on rip currents had a higher knowledge, and lifeguards proved to be the most effective form of education. The study presents an insight into UK beach users’ knowledge of rip currents and provides more evidence with which to pilot a rip current education scheme within the UK.