A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

When More is More: Do Non-Restricted Goals Benefit Employers and the Environment Too?

Prior research on goal self-concordance (GSC) and goal attainment (GA) has studied these dimensions as transversal sections through a person’s life domains. Blending the recent developments in self-determination theory and pro-environmental behavior literature, the current study introduced the concept of non-restricted goals and explored whether work climate (WCQ) and environmental identity (EID) impact GA and, through it, in-role job performance (IRB), organizational citizenship behaviors (OCB) and wellbeing, as well as organizational citizenship behaviors for the environment (OCBE). It also explored GSC along with basic psychological needs’ satisfaction (BPNS) and GA, as explanatory mechanisms. The study relied on data collected at two different moments in time, with a retained sample of 201 employees from different organizations. Results confirmed that WCQ and EID are relevant antecedents for IRB, OCB and wellbeing, as well as OCBE. Except for the direct relationship between EID and OCB/OCBE, most of these impacts were indirect, through BPNS, GSC or GA. The current study did not find a significant relationship between GSC and GA, adding to the line of mixed results regarding their relationship. The findings inform pro-environmental interventions in the workplace, as well as human resource management practices that foster employee wellbeing, work-life balance, and job performance. (AU)

Information technology and addiction science: promises and challenges.

BACKGROUND: Information technology can be used to advance addiction science and clinical practice. MAIN BODY: This special issue, "Information technology (IT) interventions to advance treatment for opioid and other addictions" presents studies that expand our understanding of IT intervention efficacy, patients' perspectives, and how IT can be used to improve substance use health care and research. This editorial introduces the topics addressed in the special issue and focuses on some of the challenges that the field is currently facing, such as attrition and treatment retention, transferability of intervention paradigms, and the challenge to keep pace with rapidly changing technologies. CONCLUSIONS: Increasing treatment reach is particularly crucial in the addiction field. IT empowers researchers and clinicians to reach large portions of the population who might not otherwise access standard treatment modalities, because of geographical limitations, logistical constraints, stigma, or other reasons. The use of information technology may help reduce the substance use treatment gap and contribute to public health efforts to diminish the impact of substance use and other addictive behaviors on population health.

mHealth Research Applied to Regulated and Unregulated Behavioral Health Sciences.

Behavioral scientists are developing new methods and frameworks that leverage mobile health technologies to optimize individual level behavior change. Pervasive sensors and mobile apps allow researchers to passively observe human behaviors "in the wild" 24/7 which supports delivery of personalized interventions in the real-world environment. This is all possible because these technologies contain an incredible array of sensors that allow applications to constantly record user location and can contextualize current environmental conditions through barometers, thermometers, and ambient light sensors and can also capture audio and video of the user and their surroundings through multiple integrated high-definition cameras and microphones. These tools are a game changer in behavioral health research and, not surprisingly, introduce new ethical, regulatory/legal and social implications described in this article.

Psychosocial aspects of diabetes technology.

AIM: To identify key psychosocial research in the domain of diabetes technology. RESULTS: Four trajectories of psychosocial diabetes technology research are identified that characterize research over the past 25 years. Key evidence is reviewed on psychosocial outcomes of technology use as well as psychosocial barriers and facilitating conditions of diabetes technology uptake. Psychosocial interventions that address modifiable barriers and psychosocial factors have proven to be effective in improving glycaemic and self-reported outcomes in diabetes technology users. CONCLUSIONS: Psychosocial diabetes technology research is essential for designing interventions and education programmes targeting the person with diabetes to facilitate optimized outcomes associated with technology uptake. Psychosocial aspects of diabetes technology use and related research will be even more important in the future given the advent of systems for automated insulin delivery and the increasingly widespread digitalization of diabetes care.

The Comparison of Latent Variable Propensity Score Models to Traditional Propensity Score Models under Conditions of Covariate Unreliability.

Propensity score (PS) methods are implemented by researchers to balance the differences between participants in control and treatment groups that exist in observational studies using a set of baseline covariates. Propensity scores are most commonly calculated using baseline covariates in a logistic regression model to predict the binary grouping variable (control versus treatment). Low reliability associated with the covariates can adversely impact the calculation of treatment effects in propensity score models. The incorporation of latent variables when calculating propensity scores has been suggested to offset the negative impact of covariate unreliability. Simulation studies were conducted to compare the performance of latent variable methods with traditional propensity score methods when estimating the treatment effect under conditions of covariate unreliability. The results indicated that using factor scores or composite variables to compute propensity scores resulted in biased estimates and inflated Type I error rates as compared to using latent factors to compute propensity scores in certain conditions. This was largely dependent upon the number of infallible covariates also included in the PS model and the outcome analysis model analyzed. Implications of the findings are discussed.

Sweet dreams or bitter nightmare: a narrative review of 25 years of research on the role of sleep in diabetes and the contributions of behavioural science.

The aim of this review was to provide an overview of developments, clinical implications and gaps in knowledge regarding the relationship between diabetes and sleep over the past 25 years, with special focus on contributions from the behavioural sciences. Multiple prospective observational and experimental studies have shown a link between suboptimal sleep and impaired glucose tolerance, decreased insulin sensitivity and the development of type 2 diabetes. While prevalence rates of suboptimal sleep vary widely according to definition, assessment and sample, suboptimal subjective sleep quality appears to be a common reality for one-third of people with type 1 diabetes and over half of people with type 2 diabetes. Both physiological and psychosocial factors may impair sleep in these groups. In turn, suboptimal sleep can negatively affect glycaemic outcomes directly or indirectly via suboptimal daytime functioning (energy, mood, cognition) and self-care behaviours. Technological devices supporting diabetes self-care may have both negative and positive effects. Diabetes and its treatment also affect the sleep of significant others. Research on the merits of interventions aimed at improving sleep for people with diabetes is in its infancy. Diabetes and sleep appear to be reciprocally related. Discussion of sleep deserves a central place in regular diabetes care. Multi-day, multi-method studies may shed more light on the complex relationship between sleep and diabetes at an individual level. Intervention studies are warranted to examine the potential of sleep interventions in improving outcomes for people with diabetes.

Psychosocial aspects and contributions of behavioural science to medication-taking for adults with type 2 diabetes.

The aim of this narrative review was to determine the contribution of behavioural and psychosocial research to the field of medication-taking for adults with type 2 diabetes over the past 25 years. We review the behavioural and psychosocial literature relevant to adults with type 2 diabetes who are treated with oral antidiabetes agents, glucagon-like peptide-1 receptor agonists and insulin. Delayed uptake of, omission of and non-persistence with medications are significant problems among adults with type 2 diabetes. At each stage of the course of diabetes, during which medication to lower blood glucose is initiated or intensified, ~50% of people take less medication than prescribed. Research aimed at increasing optimal medication-taking behaviour has targeted 'forgetfulness', developing interventions which aid medication-taking, such as reminder devices, with limited success. In parallel, investigation of beliefs about medication has provided insights into the perceived necessity of and concerns about medication and how these inform medication-taking decisions. Guidance is available for health professionals to facilitate shared decision-making, particularly with insulin therapy; however, interventions addressing medication beliefs are limited. Optimal medication-taking behaviour is essential to prevent hyperglycaemia in adults with type 2 diabetes. Evidence from the past 25 years has demonstrated the association between medication beliefs and medication-taking behaviour. Health professionals need to address medication concerns, and establish and demonstrate the utility of diabetes medication with the individual within the clinical consultation. There are interventions that may assist diabetes health professionals in the shared decision-making process, but further development and more robust evaluation of these tools and techniques is required.

Behaviour change in diabetes: behavioural science advancements to support the use of theory.

Behaviour is central to the management of diabetes, both for people living with diabetes and for healthcare professionals delivering evidence-based care. This review outlines the evolution of behavioural science and the application of theoretical models in diabetes care over the past 25 years. There has been a particular advancement in the development of tools and techniques to support researchers, healthcare professionals and policymakers in taking a theory-based approach, and to enhance the development, reporting and replication of successful interventions. Systematic guidance, theoretical frameworks and lists of behavioural techniques provide the tools to specify target behaviours, identify why ideal behaviours are not implemented, systematically develop theory-based interventions, describe intervention content using shared terminology, and evaluate their effects. Several examples from a range of diabetes-related behaviours (clinic attendance, self-monitoring of blood glucose, retinal screening, setting collaborative goals in diabetes) and populations (people with type 1 and type 2 diabetes, healthcare professionals) illustrate the potential for these approaches to be widely translated into diabetes care. The behavioural science approaches outlined in this review give healthcare professionals, researchers and policymakers the tools to deliver care and design interventions with an evidence-based understanding of behaviour. The challenge for the next 25 years is to refine the tools to increase their use and advocate for the role of theoretical models and behavioural science in the commissioning, funding and delivery of diabetes care.

How can big data science transform the psychological sciences?

Big data and related technologies are radically altering our society. In a similar way, these approaches can transform the psychological sciences. The goal of this commentary is to motivate psychologists to embrace big data science for the betterment of the field. Big data sources, algorithmic methods, and a culture that embraces prediction has the potential to advance our science, improve the robustness and replicability of our research, and allow us to focus more centrally on actual behaviors. We highlight these key transformations, acknowledge criticisms of big data approaches, and emphasize specific ways psychologists can contribute to the big data science revolution

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Social Navigation in a Cognitive Architecture Using Dynamic Proxemic Zones.

Robots have begun to populate the everyday environments of human beings. These social robots must perform their tasks without disturbing the people with whom they share their environment. This paper proposes a navigation algorithm for robots that is acceptable to people. Robots will detect the personal areas of humans, to carry out their tasks, generating navigation routes that have less impact on human activities. The main novelty of this work is that the robot will perceive the moods of people to adjust the size of proxemic areas. This work will contribute to making the presence of robots in human-populated environments more acceptable. As a result, we have integrated this approach into a cognitive architecture designed to perform tasks in human-populated environments. The paper provides quantitative experimental results in two scenarios: controlled, including social navigation metrics in comparison with a traditional navigation method, and non-controlled, in robotic competitions where different studies of social robotics are measured.

[Current Status and Perspective of Behavioral Science in Social Medicine].

The term behavioral science was coined in 1946 by a research group at the University of Chicago led by Miller. It is defined as "science that systematically reveals the rules of human behavior". To elucidate human behavior, they proposed combining biological science and social science. In Japan, achievements in behavioral science research have accumulated and have been applied in health education and health policy. In this paper, we describe the current status and future approaches in social medicine through an overview of behavioral science research in Japan with regard to the following five points: 1) representative theories and techniques in health behavior, 2) differences in health awareness, 3) a new approach of behavioral science based on the dual process theory, behavioral economics, and zero-order prevention, 4) diversity in behavioral changes and 5) experimental research in behavioral science.

Importance of HIV/AIDS-Related Behavioral and Social Sciences Research at the NIH and Beyond.

OPPORTUNITY STATEMENT: Key topics discussed in this article were previously presented at the Center for AIDS Research Social and Behavioral Sciences Network's 12th National Scientific Meeting in August 2018. This article highlights the importance of behavioral and social sciences research (BSSR) in addressing the HIV/AIDS pandemic. APPROACH: NIH has made significant investments in HIV/AIDS-related BSSR. These investments support the development of effective, evidence-based sociobehavioral HIV prevention, treatment, and care strategies. DISCUSSION: The implementation and use of evidence-based sociobehavioral approaches in combination with biomedical strategies provide the availability of multiple tools to end the HIV epidemic in the United Sates and the pandemic globally. FUTURE DIRECTIONS: BSSR-related opportunities to mitigate the persistent challenges HIV/AIDS presents include, but are not limited to, further incorporating BSSR into HIV vaccine and cure research; improving interventions that address stigma and the social determinants of health that perpetuate HIV transmission within key populations; and conducting implementation science research that shapes national and international policies impacting HIV prevention, treatment, and care.

The Evolution of Psychology as a Basic Bio-behavioral Science in Healthcare Education.

For over a century, researchers and educators have called for the integration of psychological science into medical school curricula, but such efforts have been impeded by barriers within medicine and psychology. In addressing these barriers, Psychology has re-examined its relationship to Medicine, incorporated psychological practices into health care, and redefined its parameters as a science. In response to interdisciplinary research into the mechanisms of bio-behavioral interaction, Psychology evolved from an ancillary social science to a bio-behavioral science that is fundamental to medicine and health care. However, in recent medical school curriculum innovations, psychological science is being reduced to a set of "clinical skills," and once again viewed as an ancillary social science. These developments warrant concern and consideration of new approaches to integrating psychological science in medical education.

The future of safety science is happening now: The modernization of the benefit-risk paradigm.

The future of safety science is happening now and has the potential to improve patient outcomes through an evolving approach to benefit-risk assessment. Three building blocks for the future of safety science, cognitive and behavioral systems, medical assessment, and data science, individually and collaboratively advance and modernize the benefit-risk paradigm. Incorporating the patient perspective and patient experiences will help identify tools that are useful in real-world practice. Medical assessment teams will bring together the study of toxicity and toxicogenomics, biomarkers, and special populations to personalize the benefit-risk profile. Personalized benefit-risk profiles for patients will help improve outcomes. Data science and related quantitative sciences such as safety statistics, database integration, technology, and epidemiology will provide new approaches and tools for analysis of safety data as well as more rapid access to insights that benefit patients.

Mapping Social Interactions: The Science of Proxemics.

Interpersonal distance and gaze provide a wealth of information during face-to-face social interactions. These "proxemic" behaviors offer a window into everyday social cognition by revealing interactants' affective states (e.g., interpersonal attitudes) and cognitive responses (e.g., social attention). Here we provide a brief overview of the social psychological literature in this domain. We focus on new techniques for experimentally manipulating and measuring proxemics, including the use of immersive virtual environments and digital motion capture. We also discuss ways in which these approaches can be integrated with psychophysiological and neuroimaging techniques. Throughout, we argue that contemporary proxemics research provides psychology and neuroscience with a means to study social cognition and behavior as they naturally emerge and unfold in vivo.