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Digital health solutions have the potential to complement traditional healthcare approaches and deliver improved health outcomes, but there are system-wide challenges that need to be addressed. These include fragmentation of the digital health landscape, regulatory processes that lack the agility to accommodate the fast pace of digital health advances, and inadequate transparency around data sharing and data governance. All of these challenges have led to mistrust, limited understanding and sharing of best practices, a lack of digital education and awareness, and insufficient patient and public engagement and involvement. In this paper, we argue that for digital health solutions to fulfil their potential, there needs to be a significant increase in early, meaningful, and sustained engagement with the people they intend to benefit. The uptake as well as the impact of digital solutions created in partnership with patients for patients are greater and more relevant to the communities they address. [ABSTRACT FROM AUTHOR]

Text generation tools, often presented as a form of generative artificial intelligence, have the potential to pose a threat to the integrity of the educational system. They can be misused to afford students marks and qualifications that they do not deserve. The emergence of recent tools, such as ChatGPT, appear to have left the educational community unprepared, despite the fact that the computer science community has been working to develop and improve such tools for years. This paper provides an introduction to text generation tools intended for a non-specialist audience, discussing the types of assessments that students can outsource, showing the type of prompts that can be used to generate text, and illustrating one possible watermarking technique that may allow generated text to be detected. A small-scale study into watermarking suggests that this technique is feasible and show technical promise but should not be relied on as a solution to widespread use of artificial intelligence based tools by students. Alternative solutions are needed, including encouraging the educational community to work with artificial intelligence rather than against it. As such, the paper concludes by discussing seven potential areas for further exploration. [ABSTRACT FROM AUTHOR]

Behavioral science has a long history of engaging in efforts to understand and address socially important issues. Poverty and inequities in health and development are among the most important and complex social issues facing the world today. With its Sustainable Development Goals (SDGs), the United Nations (2015) has focused attention and guidance on addressing key global challenges, including to "end poverty" (SDG 1), "ensure good health and well-being for all" (SDG3), and "reduce inequality within and among countries" (SDG 10). In this paper, we provide a framework and illustrative examples of contributions of behavioral science to these issues. We feature illustrative behavioral interventions at the individual, relationship, community, and societal levels. We highlight the diversity of issues, intervention methods, and settings reflected in applications of behavioral science. By joining methods from behavioral science, public health, and other disciplines—and the experiential knowledge of those most affected by inequities—behavioral methods can make significant contributions to collaborative efforts to assure health and well-being for all. [ABSTRACT FROM AUTHOR]

With the increasing complexity of industrial processes, many practical industrial processes have multimodal characteristics to meet production requirements. In addition to stable modes with different operating points, transition modes are also generated when mode switching occurs. To monitor the running state of the process in real-time, it is necessary to carry out online multimodal identification. At present, how to accurately identify the transition modes and unknown modes is still an open problem. In this paper, an online multimodal identification method based on the complex network is proposed, which identifies different modes by the difference of data distribution between samples. To identify transition modes, moving window technology is introduced to extract dynamic characteristics of the historical data. The multimodal data is mapped in a complex network with the mean vectors of windows as nodes and the Jensen–Shannon (JS) divergence between the mean vectors as edges. Then, the community clustering algorithm is applied to cluster the nodes, which can automatically determine the number of clustering and solve the problem of unknown modal numbers in historical data. On this basis, the Kernel Density Estimation method is used to introduce the JS divergence thresholds to realize a new online multimodal identification, including transition modes and unknown modes. The model can be updated by collecting samples of unknown modes from the online multimodal identification results. Finally, the effectiveness of the proposed method is verified by a numerical example and the Tennessee-Eastman process. [ABSTRACT FROM AUTHOR]

Recent police brutality and related violence against Black people, coupled with the COVID-19 pandemic, has further evidenced the disproportionate impact of systemic racism in our institutions and across society. In the United States, the alarming mortality rates for Black people due to police violence and COVID-19 related deaths are clear demonstrations of inequities within a long history of disparate outcomes. In understanding systemic racism, it is essential to consider how it is embedded within society and across socio-ecological levels. The Social-Ecological Model (SEM) is used to examine conditions within the environment that maintain systemic racism, including within our field and discipline. A behavioral-community approach for examining racism aids in determining points of intervention across multiple ecological levels that may contribute to behavior change, including with behaviorists. The science of behavior is well-suited to help examine the contingencies governing behaviors within and across systems, which is pivotal for addressing operant behaviors to influence long-term behavior change. This paper calls on the behavioral community to address systemic racism within our environments and systems of influence to contribute to a more equitable community. Systemic racism, including within the context of anti-Blackness, is examined by considering behavior change strategies that can be supported by behaviorists across socio-ecological levels. Tools for collaborative action are provided to support behaviorists in demonstrating the skills needed across a continuum of behaviors from allyship to anti-racism to actively address systemic racism. [ABSTRACT FROM AUTHOR]

Natural resource conservation concerns have been prevalent around the world, and a range of solutions has been implemented to prevent their depletion. This paper brings together the literature on the commons and on behavioral principles to understand how traditional communities' management of common pool resources can contribute to this discussion. More specifically, it highlights how these communities can offer lessons to governments on how to develop and manage environmental policies to ensure sustainable development. Whereas Ostrom's work focuses on investigating how local communities succeed at managing common pool resources without external interference, behavior analysis can explain how cultural practices are selected. Through this combined framework, we investigate the practices of an extractive reserve (RESEX) in Brazil. A RESEX is an area of land, generally state owned, where access and use rights, including natural resource extraction, are allocated to local groups. The RESEX Mãe Grande de Curuçá is an example of common pool resource management that uses governmental tools to benefit the community. Fisherfolks are able to successfully conserve one of their main sources of livelihood: the fiddler crab. Finally, this paper describes and behavioral interactions regarding the conservation of resources that governments may want to consider. [ABSTRACT FROM AUTHOR]

This paper analyses the use of the main e-tourism platforms by European tourists. A computer-aided Web interview (CAWI) was used to conduct the research in 19 European countries: Germany, Austria, Belgium, Denmark, Spain, Finland, France, Holland, Ireland, Italy, Norway, Poland, Portugal, Russia, Sweden, Switzerland, Luxemburg, Czech Republic, and the United Kingdom. The final sample consisted of 13,243 tourists. Through the methodology of Social Network Analysis (SNA), the study focuses on detecting key network players (social media, OTAs, etc.) in the e-tourism ecosystem. The network analysis reveals the structural characteristics of the network of networks in the European e-tourism ecosystem: number of platforms (473), centrality degree and betweenness, and the specific characteristics of the networks by country. The results show an e-tourism network of platforms following a pattern known as core-periphery. Four platforms show a predominant role: Facebook, TripAdvisor, Google, and Booking. These 'big four' ego-networks are graphically represented to better understand the e-tourism network. The results also show that different networks are formed by country according to the use of e-tourism platforms. This study helps understand in a novel way the behaviour of European tourists when using e-tourism platforms to choose their travel destination. The results obtained are useful for companies and Destination Marketing Organizations (DMOs), understanding how e-tourism platforms are connected in order to design their segmentation and promotion strategy through e-tourism platforms in the European market. [ABSTRACT FROM AUTHOR]

Ethnogenesis is a process of historic construction from interethnic interactions that originate new social categories, in other words, that form groups that distinguish from the rest of society. In Brazil, after the Constitution of 1988, different groups used their ethnogenesis to obtain recognition of their indigenous condition. One of these groups is the Tapuios do Carretão, a community in Brazil's centralwest region inhabited by descendants of indigenous, black, and white people, who speak Portuguese and are recognized by the Brazilian government as an indigenous group. The goal of this paper was to reconstruct an ethnogenesis of the Tapuios indigenous group from a Behavior Analysis perspective, thus improving our comprehension of this group's cultural practices by analyzing the processes that selected them. Behavior-analytical concepts would allow us to further understand changes in cultural practices that occurred due to colonization. Finally, we discuss the importance of laws in planning and changing cultures. For Brazilian indigenous groups, consequences such as the right to land and other benefits had an important role in encouraging members of indigenous communities to seek recognition of their condition. [ABSTRACT FROM AUTHOR]

The need for "sustainability" has encouraged a variety of disciplines to consider ways to reduce the impact of a given community on the environment around it. Approaches can range from changing the behavior of a few people to completely restructuring the communities in which people live. Interventions in the larger system of a community provide potential for larger levels of change. How to do this has yet to be fully evaluated, especially from the perspective of people's behavior interacting within a community environment. The behavior analysis literature provides many individual level interventions, such as contingency management programs and empirically evaluated "kernels" (Embry & Biglan, 2008) across various populations and behaviors. The current paper argues that these provide a starting point for working with other sciences to change the environment, impact the cultural practices of people in the community, and promote sustainability. An overview of the current literature is provided along with various models for application of these interventions to larger communities. [ABSTRACT FROM AUTHOR]

The need for "sustainability" has encouraged a variety of disciplines to consider ways to reduce the impact of a given community on the environment around it. Approaches can range from changing the behavior of a few people to completely restructuring the communities in which people live. Interventions in the larger system of a community provide potential for larger levels of change. How to do this has yet to be fully evaluated, especially from the perspective of people's behavior interacting within a community environment. The behavior analysis literature provides many individual level interventions, such as contingency management programs and empirically evaluated "kernels" (Embry & Biglan, 2008) across various populations and behaviors. The current paper argues that these provide a starting point for working with other sciences to change the environment, impact the cultural practices of people in the community, and promote sustainability. An overview of the current literature is provided along with various models for application of these interventions to larger communities. [ABSTRACT FROM AUTHOR]

A number of primary-intervention studies with typical adults and children in open-community settings have been conducted in the area of applied behavior analysis. For example, communities and researchers have attempted to reach out to certain populations by designing and offering community-based prevention programs. In such attempts, the target individuals have not yet experienced the contingency between the participation and its consequence; that is, it is likely that the recruitment depends on antecedent control of participation. The present paper reviewed studies with group designs in which the individuals were recruited to community-based prevention programs. The selected studies were classified into the following four antecedent control procedures used in the studies: stating contingencies in the invitation; altering the value of consequence through the invitation; manipulating response effort; and others. After specific recruiting strategies used in the studies were examined, the authors concluded that many of the studies consisted of multiple and confounding variables. It is recommended future studies isolate the effects of different independent variables, rather than evaluate treatment packages. [ABSTRACT FROM AUTHOR]