Ubiquitous monitoring and behavioural change: a semiotic perspective

We are soon approaching the pervasive-era ofcomputing, where computers are embedded intoobjects and the environment in order to provide newservices to users. Significant levels of data arerequired in order for these services to function asintended, and it is this collection of data which werefer to as ubiquitous monitoring. Existing monitoringtechniques have often been known to cause undesirableeffects, and it is anticipated that ubiquitousmonitoring, with its increased coverage, will lead toincreases in their occurrence and impact. To date, theeffects of ubiquitous monitoring on human behaviourhave not been sufficiently investigated, furtherincreasing the risk of undesirable effects. We propose apreliminary model consisting of a series of factorsbelieved to influence human behavior and augmentedby the Theory of Planned Behaviour. This model mayallow us to understand, predict, and therefore preventany undesirable effects caused by ubiquitousmonitoring.

Deciding the price of fame

Previous studies of ignorance-driven decision-making have either analyzed when ignorance should prove advantageous on theoretical grounds, or else they have examined whether human behavior is consistent with an ignorance driven inference strategy (e.g., the recognition heuristic). The current study merges these research goals by examining whether – under conditions where ignorance driven inference might be expected – the type of advantages theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgments, participants reliably use recognition as a basis for their judgments. Their wealth judgments under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all the names (the “less-is-more effect”). these data are robust against a number of variations on the size of the pool from which participants have to choose and the nature of the wealth judgment.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

A complex system perspective on the emergence and spread of infectious diseases: integrating economic and ecological aspects

The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.

Motivational, emotional, and behavioral correlates of fear of missing out

Social media utilities have made it easier than ever to know about the range of online or offline social activities one could be engaging. On the upside, these social resources provide a multitude of opportunities for interaction; on the downside, they often broadcast more options than can be pursued, given practical restrictions and limited time. This dual nature of social media has driven popular interest in the concept of Fear of Missing Out – popularly referred to as FoMO. Defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent, FoMO is characterized by the desire to stay continually connected with what others are doing. The present research presents three studies conducted to advance an empirically based understanding of the fear of missing out phenomenon. The first study collected a diverse international sample of participants in order to create a robust individual differences measure of FoMO, the Fear of Missing Out scale (FoMOs); this study is the first to operationalize the construct. Study 2 recruited a nationally representative cohort to investigate how demographic, motivational and well-being factors relate to FoMO. Study 3 examined the behavioral and emotional correlates of fear of missing out in a sample of young adults. Implications of the FoMOs measure and for the future study of FoMO are discussed.

Self-concept clarity, social support, and Compulsive Internet Use: a study of the USA and the UAE

Compulsive Internet Use (CIU) has been mostly studied among adolescents, yet some studies reveal that this can be a problem for the adult population, too. The lack of agreement on diagnostic tools and cut-off points results in markedly different prevalence figures. Building on Charlton’s (2002) distinction between core CIU and positive engagement dimensions, the first objective was to confirm that prevalence figures including the core dimensions of CIU were lower than those including the engagement dimensions as well. Second, building on Davis’s (2001) diathesis-stress model, we tested the role that self-concept clarity (SCC) and social support play in predicting core CIU in US subjects (NUS = 268). Finally, we expected that, because self-concept clarity is mostly linked to well-being in Western countries, the association between this variable and core CIU would be weak in the Eastern culture sample (NUAE = 270). Our findings confirmed that prevalence figures were 20–40% lower when including the core dimensions only, and that SCC is a key predictor of CIU at low levels of social support in the US. We also confirmed that this is not the case in the UAE. Future research opportunities to advance this study were discussed.

Evolutionary explanations in the social and behavioral sciences : introduction and overview

Despite a growing acceptance of the value of evolutionary approaches to understanding the natural world there has been relatively little attention paid to evolutionary ideas in sociology, socio-cultural anthropology, and — of particular relevance for this special issue — criminology and forensic/correctional psychology. The aim of this paper is to provide an introductory overview of evolutionary approaches to human behavior with a focus on illuminating the role they can play in enriching our understanding of criminal and antisocial behavior. We begin with an overview of the main approaches to applying evolutionary theory to human behavior and we suggest that a pluralistic perspective is most likely to advance conceptual and empirical work in the field. We then turn to a brief discussion of some common, but misguided criticisms of this approach. Some of the more substantive conceptual and methodological issues that evolutionary approaches need to address are then explored. Finally, we engage with the broader issues that relate to the role of evolutionary explanations in the social and behavioral sciences.