Participation 3.0 in the implementation of the energy transition-Components and effectiveness of an interactive dialogue tool (Vision:En 2040).

The allocation of renewable energy plants, especially wind turbines, is stagnating in Germany. Although the citizens approve of the energy transition, they resist concrete local projects. In recent years, research has shown that interactive map applications support participatory planning through motivation, social interaction, and knowledge transfer. We aim to reduce biases against renewable energy (RE) and support informed decision making while accepting local responsibility. We hypothesized that finding a new gamified participation format, based on behavioral mechanisms, would strengthen the empowerment of people. To this end, we designed a dialogue tool and participation format, 'Vision:En 2040', which combines: (i) a precise target electricity yield, (ii) an interactive map showing results of people's actions, information about environmental impacts, and (iii) game rules which foster cooperation. In facilitated workshops, participants simulate the allocation of wind and photovoltaic power plants in their municipality to achieve a target electricity yield. The developed tool is based on methods of environmental planning and geoinformatics. 'Vision:En 2040' was systematically tested with a technical test and a pre-test. In addition, its impact on participants was assessed through surveys and qualitative content analysis. The evaluation results show that the tool can influence the acceptance of the energy transition in terms of attitude. Through 'Vision:En 2040', participants became aware of the community's responsibility in the energy transition and expanded their knowledge. In addition, decision makers used the workshop results to plan RE sites. Our results indicate that 'Vision:En 2040' is helpful for informal citizen participation in accelerating the energy transition.

Optimally generate policy-based evidence before scaling.

Social scientists have increasingly turned to the experimental method to understand human behaviour. One critical issue that makes solving social problems difficult is scaling up the idea from a small group to a larger group in more diverse situations. The urgency of scaling policies impacts us every day, whether it is protecting the health and safety of a community or enhancing the opportunities of future generations. Yet, a common result is that, when we scale up ideas, most experience a 'voltage drop'-that is, on scaling, the cost-benefit profile depreciates considerably. Here I argue that, to reduce voltage drops, we must optimally generate policy-based evidence. Optimality requires answering two crucial questions: what information should be generated and in what sequence. The economics underlying the science of scaling provides insights into these questions, which are in some cases at odds with conventional approaches. For example, there are important situations in which I advocate flipping the traditional social science research model to an approach that, from the beginning, produces the type of policy-based evidence that the science of scaling demands. To do so, I propose augmenting efficacy trials by including relevant tests of scale in the original discovery process, which forces the scientist to naturally start with a recognition of the big picture: what information do I need to have scaling confidence?

A framework for language technologies in behavioral research and clinical applications: Ethical challenges, implications, and solutions.

Technological advances in the assessment and understanding of speech and language within the domains of automatic speech recognition, natural language processing, and machine learning present a remarkable opportunity for psychologists to learn more about human thought and communication, evaluate a variety of clinical conditions, and predict cognitive and psychological states. These innovations can be leveraged to automate traditionally time-intensive assessment tasks (e.g., educational assessment), provide psychological information and care (e.g., chatbots), and when delivered remotely (e.g., by mobile phone or wearable sensors) promise underserved communities greater access to health care. Indeed, the automatic analysis of speech provides a wealth of information that can be used for patient care in a wide range of settings (e.g., mHealth applications) and for diverse purposes (e.g., behavioral and clinical research, medical tools that are implemented into practice) and patient types (e.g., numerous psychological disorders and in psychiatry and neurology). However, automation of speech analysis is a complex task that requires the integration of several different technologies within a large distributed process with numerous stakeholders. Many organizations have raised awareness about the need for robust systems for ensuring transparency, oversight, and regulation of technologies utilizing artificial intelligence. Since there is limited knowledge about the ethical and legal implications of these applications in psychological science, we provide a balanced view of both the optimism that is widely published on and also the challenges and risks of use, including discrimination and exacerbation of structural inequalities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Expanding the role of justice in secondary research using digital psychological data.

Secondary analysis of digital psychological data (DPD) is an increasingly popular method for behavioral health research. Under current practices, secondary research does not require human subjects research review so long as data are de-identified. We argue that this standard approach to the ethics of secondary research (i.e., de-identification) does not address a range of ethical risks and that greater emphasis should be placed on the ethical principle of justice. We outline the inadequacy of an individually focused research ethic for DPD and describe unaddressed "social risks" generated by secondary research of DPD. These risks exist in the "circumstances of justice": that is, a circumstance where individuals must cooperate to create a public good (e.g., research knowledge), and where it is impractical to individually exempt individuals. This requires researchers to emphasize the just allocation of benefits and burdens against a background of social cooperation. We explore six considerations for researchers who wish to conduct research with DPD without explicit consent: (a) create socially valuable knowledge, (b) fairly share the benefits and burdens of research, (c) be transparent about data use, (d) create mechanisms for withdrawal of data, (e) ensure that stakeholders can provide input into the design and implementation of the research, and (f) responsibly report results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Further evidence for the bidimensionality of the components model of addiction: a reply to Amendola (2023).

In our original research article entitled "Deconstructing the components model of addiction: an illustration through "addictive" use of social media" (Fournier et al., 2023), we showed that the Bergen Social Media Addiction Scale, a six-item psychometric instrument derived from the components model of addiction to assess social media "addiction", did not form a unitary, but a bidimensional construct in which some components (i.e., salience, tolerance) were not associated with psychopathological symptoms, thus conflating central and peripheral features of addiction. Subsequently, in a recent commentary, Amendola (2023) sought to determine whether our findings were driven by the use of data aggregated from multiple independent datasets, i.e., a decision we transparently acknowledged as a limitation in our original research article. Following their re-analysis, Amendola (2023) claimed to have demonstrated that a unidimensional model best fitted the data. However, they only reported results for a partial set of models relevant to this investigation. In the present reply, through a transparent assessment and reporting of all unidimensional and bidimensional models relevant to this investigation, we show that the bidimensionality of the Bergen Social Media Addiction Scale is, in fact, tenable, robust, and consistent across multiple independent datasets. In line with the growing evidence demonstrating that many sets of criteria involved in operationalizing behavioral addictions pathologize involvement in appetitive behaviors, these results highlight the necessity to renew the conceptualization and assessment of behavioral addictions.

Norman Henry Anderson (1925-2022).

This article memorializes Norman Henry Anderson (1925-2022), best known for his information integration theory (IIT). Norman Anderson's work was influential in its time, and his legacy endures. He was the recipient of the 1972 American Association for the Advancement of Science Prize for Behavioral Science Research, and, as a tribute to his work, scholars in the field established a conference that continues to this day: the International Information Integration Theory/Functional Measurement Conference. Highlights of Anderson's career and professional contributions are noted. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Target number influences strategy use by rats (Rattus norvegicus) in the traveling salesperson problem.

The traveling salesman problem (TSP) is an optimization problem in which the goal is to find the shortest possible route that passes through each of a set of points in space. The TSP is of interest not only in the fields of mathematics, computer science, and engineering, but also in cognitive and behavioral research to study problem-solving and spatial navigation. Humans are able to complete even complex TSPs with a high degree of efficiency, and distance minimization in TSP analogs has been observed in a variety of nonhuman species as well. Tasks based on the TSP also have the potential for translational research on cognitive and neurological disorders such as Alzheimer's disease. The current experiment was designed to examine the effects of target number on TSP performance in rats. After pretraining, rats were tested once on each of several target configurations, and their travel routes were recorded. We examined the routes for general efficiency, as well as evidence for strategy use including the nearest neighbor (NN) strategy and crossing avoidance. Our results indicate that latency and route length increase in proportion to the number of targets. Rats also showed a strong tendency to avoid path crossing, and to select NN targets, which strengthened with increasing target numbers. Taken together, our results indicate that travel efficiency decreases linearly in relation to the target number rather than the number of possible routes, which grows factorially with a target number. Additionally, spatial memory and route selection strategy are also affected by an increasing number of targets. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Adolescent health behavior research.

The Adolescent Brain Cognitive Development (ABCD) Study is the largest, long-term study of brain development and child and adolescent health that has ever been conducted in the United States. The ABCD Research Consortium is supported by the National Institutes of Health and includes a central coordinating center, a data analysis and informatics core, and 21 research sites across the country. This special issue of Health Psychology presents some important findings on adolescent health behavior that have recently emerged from the ABCD Study (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Why and How to Account for Sex and Gender in Brain and Behavioral Research.

Long overlooked in neuroscience research, sex and gender are increasingly included as key variables potentially impacting all levels of neurobehavioral analysis. Still, many neuroscientists do not understand the difference between the terms "sex" and "gender," the complexity and nuance of each, or how to best include them as variables in research designs. This TechSights article outlines rationales for considering the influence of sex and gender across taxa, and provides technical guidance for strengthening the rigor and reproducibility of such analyses. This guidance includes the use of appropriate statistical methods for comparing groups as well as controls for key covariates of sex (e.g., total intracranial volume) and gender (e.g., income, caregiver stress, bias). We also recommend approaches for interpreting and communicating sex- and gender-related findings about the brain, which have often been misconstrued by neuroscientists and the lay public alike.

Use behavioral research to improve the feasibility and effectiveness of system-level policy.

Individual-level interventions are inadequate to address complex societal problems. Meaningful solutions require system-level policies that alter the incentives that govern behavior. We argue that individual-level interventions can help improve both the feasibility and effectiveness of system-level interventions, especially when designed as an integrated policy package.

Transient strain differences in an operant delayed non-match to position task.

Working memory refers to the temporary retention of a small amount of information used in the execution of a cognitive task. Working memory impairments are one of the common hallmarks of many neuropsychiatric and neurological disorders including schizophrenia and Alzheimer's disease. Here, we investigated Fischer 344 and Long-Evans rats for strain and sex differences in working memory using the operant-based DNMTP task. Rats were required to press one of two levers presented during a sample phase and followed by a 2-32 second delay, the rats were then required to press the opposite, nonmatch, lever during the choice phase. We found a transient strain difference with Fischer 344 rats performing better than Long-Evans early in training. The Fischer 344 strain showed stable performance across sessions while the performance of Long-Evans increased in the later sessions. Since different background rat strains are used for transgenic rat models, it is critical to be able to compare the behavioral performance across different strains. These findings have implications in behavioral neuroscience research as understanding the typical behavioral endpoints in different background strains will aid our understanding of how different models affect behavioral performance.

Health equity is not possible without addressing disparities.

Health equity is the aspirational assurance of optimal health for all. Synonymous with fair and just opportunities for physical and mental health, equity work reflects intentional efforts to remove access barriers and allocate high-quality, need-based resources. Health equity is not possible without meaningful reductions in disparities-and evaluating progress goes further to describe, assess, and continuously evaluate fairness and social justice within structures, community contexts, and healthcare. The National Institute on Minority Health and Health Disparities (NIMHD) has a longstanding and deep commitment to advancing health equity. This article describes efforts in two specific areas: workforce diversity, equity, and inclusion (DEI) and scientific initiatives. We also summarize five actionable strategies for health equity promotion in health psychology-relevant research and practice, including increasing workforce DEI, inclusive research participation, cultural competence and humility, applying community-engaged research principles, and going beyond "do no harm." Meaningful equity work often requires major shifts in approaches, dedicated resources, and targeted efforts toward social justice. The current emphasis on addressing health disparities and understanding the structural factors underlying them presents unequivocal opportunities for changes in clinical practice and research. NIMHD seeks to support innovative health psychology and behavioral medicine research with the potential to transform health via effective and equitable interventions/treatments, systems changes, and policies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Honoring foundational Black psychologists' contributions to research on Black fathers.

Much of the early psychological research on Black fathers and families employed a deficit lens, pathologizing Black fathers as absent and uninvolved contributors to their children's development. As a response, several Black psychologists articulated the need to move away from deficit-based approaches and employ strengths-based and adaptive frameworks to examine the social experiences of Black fathers and their contributions to child development. This transformative work was not only central to advancing research on Black fathers but also a cornerstone in the broader fathering literature. Though the list of foundational architects of Black fatherhood scholarship spans disciplines, we center this article around the contributions of eight Black psychologists-Drs. Phillip Bowman, Cleopatra Howard Caldwell, Anderson J. Franklin, Nancy Boyd-Franklin, Vivian Gadsden, Harriette Pipes McAdoo, John L. McAdoo, and Melvin Wilson. Their collective works and scientific contributions provided a critical lens and articulated a vision for research on Black fathers. In highlighting their contributions, we focus on six thematic areas: (a) conceptual and theoretical advancements, (b) research methods and designs that centered Black fathers, (c) description and contextualization, (d) children's development and well-being, (e) theory to practice and intervention, and (f) scientific cross-pollination and collaborative ethos. Last, we review and highlight research branches and extensions of these foundational roots. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Towards a three-level neo-Tinbergenian approach to object play: Structure, causes and consequences of a behavioral puzzle.

My main goal in this paper is to propose a reformulation of foundational models in behavioral research, including Tinbergen's (1963) well-known four levels of analysis (namely, ontogenetic, mechanistic, functional, and evolutionary questions) and Mayr's (1961) dichotomy between proximate and ultimate causations. After critically evaluating these influential but problematic models, I present a three-level neo-Tinbergenian approach to behavior that considers the triadic integration of behavioral causes, structure, and consequences along a single temporal continuum. I then argue that object-directed play is a good candidate behavior to apply this new paradigm by presenting significant examples of the combined analysis of at least two of these three levels. Finally, I show how stone handling, a form of culturally-transmitted object play in macaques, is perfectly amenable to this unified three-level explanatory framework. My proposed approach fits recent theoretical and empirical advances in behavioral biology, has a heuristic value, and may provide numerous benefits to a range of behavioral scientists.

Is it ethical to use Mechanical Turk for behavioral research? Relevant data from a representative survey of MTurk participants and wages.

To understand human behavior, social scientists need people and data. In the last decade, Amazon's Mechanical Turk (MTurk) emerged as a flexible, affordable, and reliable source of human participants and was widely adopted by academics. Yet despite MTurk's utility, some have questioned whether researchers should continue using the platform on ethical grounds. The brunt of their concern is that people on MTurk are financially insecure, subject to abuse, and earn inhumane wages. We investigated these issues with two representative probability surveys of the U.S. MTurk population (N = 4094). The surveys revealed: (1) the financial situation of people on MTurk mirrors the general population, (2) most participants do not find MTurk stressful or requesters abusive, and (3) MTurk offers flexibility and benefits that most people value above other options for work. People reported it is possible to earn more than $10 per hour and said they would not trade the flexibility of MTurk for less than $25 per hour. Altogether, our data are important for assessing whether MTurk is an ethical place for research.

Open science in health psychology and behavioral medicine: A statement from the Behavioral Medicine Research Council.

Open Science practices include some combination of registering and publishing study protocols (including hypotheses, primary and secondary outcome variables, and analysis plans) and making available preprints of manuscripts, study materials, de-identified data sets, and analytic codes. This statement from the Behavioral Medicine Research Council (BMRC) provides an overview of these methods, including preregistration; registered reports; preprints; and open research. We focus on rationales for engaging in Open Science and how to address shortcomings and possible objections. Additional resources for researchers are provided. Research on Open Science largely supports positive consequences for the reproducibility and reliability of empirical science. There is no solution that will encompass all Open Science needs in health psychology and behavioral medicine's diverse research products and outlets, but the BMRC supports increased use of Open Science practices where possible. (PsycInfo Database Record (c) 2023 APA, all rights reserved).