Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

On the Road to Better Value: State Roles in Promoting Accountable Care Organizations

Outlines how accountable care organizations can deliver value through incentives to manage utilization, improve quality, and curb cost growth. Profiles states supporting the model with data, new payment methods, accountability measures, and other efforts

A Static Verification Framework for Secure Peer-to-Peer Applications

In this paper we present a static verification framework to support the design and verification of secure peer-to-peer applications. The framework supports the specification, modeling, and analysis of security aspects together with the general characteristics of the system, during early stages of the development life-cycle. The approach avoids security issues to be taken into consideration as a separate layer that is added to the system as an afterthought by the use of security protocols. The main functionality supported by the framework are concerned with the modeling of the system together with its security aspects by using an extension of UML, modeling of abuse cases to represent scenarios of attackers and assist with the identification of properties to be verified, specification of properties to be verified in a graphical template language, verification of the models against the properties, and visualization of the results of the verification process

A Study of Concurrency Bugs and Advanced Development Support for Actor-based Programs

The actor model is an attractive foundation for developing concurrent applications because actors are isolated concurrent entities that communicate through asynchronous messages and do not share state. Thereby, they avoid concurrency bugs such as data races, but are not immune to concurrency bugs in general. This study taxonomizes concurrency bugs in actor-based programs reported in literature. Furthermore, it analyzes the bugs to identify the patterns causing them as well as their observable behavior. Based on this taxonomy, we further analyze the literature and find that current approaches to static analysis and testing focus on communication deadlocks and message protocol violations. However, they do not provide solutions to identify livelocks and behavioral deadlocks. The insights obtained in this study can be used to improve debugging support for actor-based programs with new debugging techniques to identify the root cause of complex concurrency bugs.Comment: - Submitted for review - Removed section 6 "Research Roadmap for Debuggers", its content was summarized in the Future Work section - Added references for section 1, section 3, section 4.3 and section 5.1 - Updated citation

The Performativity of Literature Reviewing: Constituting the Corporate Social Responsibility Literature through Re-Presentation and Intervention

Although numerous books and articles provide toolkit approaches to explain how to conduct literature reviews, these prescriptions regard literature reviewing as the production of representations of academic fields. Such representationalism is rarely questioned. Building on insights from social studies of science, we conceptualize literature reviewing as a performative endeavor that co-constitutes the literature it is supposed to “neutrally” describe, through a dual movement of re-presenting—constructing an account different from the literature, and intervening—adding to and potentially shaping this literature. We discuss four problems inherent to this movement of performativity—description, explicitness, provocation, and simulacrum—and then explore them through a systematic review of 48 reviews of the literature on Corporate Social Responsibility (CSR) for the period 1975-2019. We provide evidence for the performative role of literature reviewing in the CSR field through both re-presenting and intervening. We find that reviews performed the CSR literature and, accordingly, the field’s boundaries, categories, priorities in a self-sustaining manner. By reflexively subjecting our own systematic review to the four performative problems we discuss, we also derive implications of performative analysis for the practice of literature reviewing

Cognitions and emotions - testing the tenets of Fairness Theory

In this study, we test the tenets put forth by Fairness Theory (Folger & Cropanzano, 2001). Fairness Theory argues that perceptions of unfairness are formulated through a cognitive process that evaluates an event in terms of the presence or absence of injury or harm, the commission or omission of discretionary conduct on the part of the entity responsible for the injury or harm, and whether or not an ethical or moral standard was violated by such conduct (termed “Would,” “Could,” and “Should,” respectively). In this paper, we examine the role each of these elements plays in the assessment of fairness. Across two laboratory studies we show that a combination of harm and moral infraction shows the strongest effects on both first- and third-party justice perceptions, anger, and subsequent behaviors, whereas perceived discretion (“Could”) has little effect. Results are interpreted in light of recent research in moral psychology

A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System

Self-adaptation is a promising approach to manage the complexity of modern software systems. A self-adaptive system is able to adapt autonomously to internal dynamics and changing conditions in the environment to achieve particular quality goals. Our particular interest is in decentralized self-adaptive systems, in which central control of adaptation is not an option. One important challenge in self-adaptive systems, in particular those with decentralized control of adaptation, is to provide guarantees about the intended runtime qualities. In this paper, we present a case study in which we use model checking to verify behavioral properties of a decentralized self-adaptive system. Concretely, we contribute with a formalized architecture model of a decentralized traffic monitoring system and prove a number of self-adaptation properties for flexibility and robustness. To model the main processes in the system we use timed automata, and for the specification of the required properties we use timed computation tree logic. We use the Uppaal tool to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

Further evidence for the involvement of EFL1 in a Shwachman-Diamond-like syndrome and expansion of the phenotypic features.

Recent evidence has implicated EFL1 in a phenotype overlapping Shwachman-Diamond syndrome (SDS), with the functional interplay between EFL1 and the previously known causative gene SBDS accounting for the similarity in clinical features. Relatively little is known about the phenotypes associated with pathogenic variants in the EFL1 gene, but the initial indication was that phenotypes may be more severe, when compared with SDS. We report a pediatric patient who presented with a metaphyseal dysplasia and was found to have biallelic variants in EFL1 on reanalysis of trio whole-exome sequencing data. The variant had not been initially reported because of the research laboratory's focus on de novo variants. Subsequent phenotyping revealed variability in her manifestations. Although her metaphyseal abnormalities were more severe than in the original reported cohort with EFL1 variants, the bone marrow abnormalities were generally mild, and there was equivocal evidence for pancreatic insufficiency. Despite the limited number of reported patients, variants in EFL1 appear to cause a broader spectrum of symptoms that overlap with those seen in SDS. Our report adds to the evidence of EFL1 being associated with an SDS-like phenotype and provides information adding to our understanding of the phenotypic variability of this disorder. Our report also highlights the value of exome data reanalysis when a diagnosis is not initially apparent

Hybrid Choice Models: Progress and Challenges

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.