Relevance of Behavioral Research in the Evolving State of Anti-obesity Medications: Is the Glass Half Empty or Half Full?

Obesity continues to be a significant public health challenge. While weight loss medications have been studied and available for several years, the newest generation of highly effective anti-obesity medications (AOMs) will shift how behavioral science professionals approach obesity treatment and research. With the unique skill set of behavioral science professionals, this commentary suggests ways to integrate behavioral science into the rapidly evolving landscape of AOM use to accelerate better obesity care and generate new lines of research. The goal of this commentary is to stimulate discussion and encourage responsive and relevant action to improve population health.

Tucker3-PCovR: The Tucker3 principal covariates regression model.

In behavioral research, it is very common to have manage multiple datasets containing information about the same set of individuals, in such a way that one dataset attempts to explain the others. To address this need, in this paper the Tucker3-PCovR model is proposed. This model is a particular case of PCovR models which focuses on the analysis of a three-way data array and a two-way data matrix where the latter plays the explanatory role. The Tucker3-PCovR model reduces the predictors to a few components and predicts the criterion by using these components and, at the same time, the three-way data is fitted by the Tucker3 model. Both the reduction of the predictors and the prediction of the criterion are done simultaneously. An alternating least squares algorithm is proposed to estimate the Tucker3-PCovR model. A biplot representation is presented to facilitate the interpretation of the results. Some applications are made to empirical datasets from the field of psychology.

Ouvrai opens access to remote virtual reality studies of human behavioural neuroscience.

Modern virtual reality (VR) devices record six-degree-of-freedom kinematic data with high spatial and temporal resolution and display high-resolution stereoscopic three-dimensional graphics. These capabilities make VR a powerful tool for many types of behavioural research, including studies of sensorimotor, perceptual and cognitive functions. Here we introduce Ouvrai, an open-source solution that facilitates the design and execution of remote VR studies, capitalizing on the surge in VR headset ownership. This tool allows researchers to develop sophisticated experiments using cutting-edge web technologies such as WebXR to enable browser-based VR, without compromising on experimental design. Ouvrai's features include easy installation, intuitive JavaScript templates, a component library managing front- and backend processes and a streamlined workflow. It integrates with Firebase, Prolific and Amazon Mechanical Turk and provides data processing utilities for analysis. Unlike other tools, Ouvrai remains free, with researchers managing their web hosting and cloud database via personal Firebase accounts. Ouvrai is not limited to VR studies; researchers can also develop and run desktop or touchscreen studies using the same streamlined workflow. Through three distinct motor learning experiments, we confirm Ouvrai's efficiency and viability for conducting remote VR studies.

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?

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.

A review of applications of the Bayes factor in psychological research.

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The article is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Protocol for Drosophila sleep deprivation using single-chip board.

Sleep behavior is characterized by long-term quiescence and increased arousal threshold, and it is homeostatically regulated. The sleep rebound after deprivation is utilized to verify the abilities to maintain homeostasis. This protocol shows how to build a programmed mechanic oscillation system and detailed procedures to conduct sleep deprivation in Drosophila. This deprivation system is featured by its programming flexibility. The knowledge of electronic circuits and a certain level of programming are both required to fulfill this protocol. For complete details on the use and execution of this protocol, please refer to Jin et al. (2021).

Goal Changes and Healthy Aging.

This article discusses ways in which aging individuals respond to physical, social, and environmental changes and constraints by modifying their goals. We review aging-related trends, which we derive from several theoretical approaches, including goal systems theory, the motivational theory of life-span development and its action-phase model, and the Selection, Optimization, and Compensation model. These theories explain how biological and social role changes in later adulthood prompt individuals to make changes to the content, orientation, and composition of their goals, including disengaging from and adjusting previously central goals. They also help identify individual differences in the capacity to do so effectively. We review several motivation-related interventions that address the challenges in goal adjustment and call for more research on identifying processes of goal changes conducive to healthy aging, more interventions, and modifications of societal and institutional (e.g., workplace, nursing home) operations that support adaptive goal change in older adults.

The measurement, evolution, and neural representation of action grammars of human behavior.

Human behaviors from toolmaking to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Testing this idea will require objective, generalizable methods for measuring the structural complexity of real-world behavior. Here we present a data-driven approach for extracting action grammars from basic ethograms, exemplified with respect to the evolutionarily relevant behavior of stone toolmaking. We analyzed sequences from the experimental replication of ~ 2.5 Mya Oldowan vs. ~ 0.5 Mya Acheulean tools, finding that, while using the same "alphabet" of elementary actions, Acheulean sequences are quantifiably more complex and Oldowan grammars are a subset of Acheulean grammars. We illustrate the utility of our complexity measures by re-analyzing data from an fMRI study of stone toolmaking to identify brain responses to structural complexity. Beyond specific implications regarding the co-evolution of language and technology, this exercise illustrates the general applicability of our method to investigate naturalistic human behavior and cognition.

Introduction.

The theme of this monograph reflects the growing research interest in the contribution of the microbiome-gut-brain axis to mental health. This chapter introduces readers to the study of the microbiome in psychiatric research and emphasises how research into the gut microbiome has had a significant impact on our understanding of mental health. A brief summary of the historical background for microbiome research in mental health is followed by examples of evidence linking gut microorganisms to changes in brain function. As novel technological developments have played a major role in providing the evidence for microbiome modulation of brain function, an overview of modern techniques and technologies is then provided. These have broadened our understanding of the range of microorganisms, in addition to bacteria, which contribute to the changes initiated by the microbiome. In addition, common experimental models are reviewed in light of the important role that animal studies, particularly in germ-free rodents, have played in establishing microbiome-gut-brain interactions. This introduction concludes with a summary of the challenges for future microbiome research, providing a forward-thinking perspective echoed in many of the following chapters.

Using web-based technologies to increase reach, inclusion, and generalizability in behavioral observation research.

Social scientists have long utilized observations of human behavior in research designs. For researchers studying couples, observation of romantic partners has led to important discoveries about how such behavior is associated with physical, mental, and family health. Historically, these methods have been used in in-person laboratory paradigms that place notable limitations on reach and inclusion. This has, in turn, restricted the generalizability of such research to couples who may not attend an in-person laboratory assessment. Transferring the observational laboratory into an online format has the potential to expand the capabilities of these methods to include more diverse couples. This article presents two empirical studies that used online methods to conduct observational behavioral research with sexual and gender minority couples, populations that could be difficult to reach using traditional methods in many places. We demonstrate that we were able to reach, recruit, and enroll diverse couples that more closely resemble the population of same-sex couples in the United States than likely would have been reached in-person. Further, we show that the quality of the observational data collected via the internet allowed for over 94% of collected data to be coded, with acceptable interrater reliabilities and convergent validity. These studies provide a proof-of-concept of online observational methods, accompanied by a tutorial for using such methods. We discuss possible extensions of these online methods, their limitations, and the potential to help further the field of close relationships by reaching more diverse relationships and increasing the generalizability of our research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Age-Related Changes in the Role of Social Motivation: Implications for Healthy Aging.

Prior research has established the importance of social relations and social embeddedness for motivation in healthy aging. Thus, social orientation appears to be essential for understanding healthy aging. This article focuses particularly on age-related changes in goals concerning social orientation, such as increased prioritization of emotional goals, increased prosociality/altruistic motives, generativity, and ego transcendence. We then consider open questions regarding gaps in the links between goals related to social orientation and healthy aging, as well as the implications of theories and research on social goals for leveraging motivation to promote healthy aging. In particular, interventions to promote healthy behavior in late life may be most effective when they match the themes of older adults' strivings to find meaning and purpose in their personal goals.

Ecological Validity and "Ecological Validity".

Egon Brunswik coined the term ecological validity to refer to the correlation between perceptual cues and the states and traits of a stimulus. Martin Orne adapted the term to refer to the generalization of experimental findings to the real world outside the laboratory. Both are legitimate uses of the term because the ecological validity of the cues in an experiment determines the ecological validity of the experiment itself.