Visitation Enablers and Barriers: Evaluating the Influences of Practical, Relational, and Experiential Factors on Visitation in Dutch Prisons

This paper aims to advance theory and knowledge about prison visitation by organizing prior studies within a framework of visitation enablers and barriers and examining how practical, relational, and experiential factors explain variation in prison visiting among 773 adult males across eight Dutch prisons. Findings suggest that all three domains play out at once to influence visitation. Whether visitors come to visit seems to depend on their relationship with the incarcerated individual, whereas traveling distance is more predictive of how often they visit. Policies that introduce practical barriers can differentially affect visits from specific relationships. Finally, results indicate that incarcerated individuals make decisions about visits based on their in-prison experiences. Policy and research implications are discussed.

Discussion of Issues Related to Discourse Analysis in Signed and Spoken Language Assessments

The analysis of discourse in language proficiency interviews reveals many similarities and some issues that are specific to the modality and social context of spoken and signed languages. In this chapter, we comment on points of intersection and difference in the preceding two chapters to highlight how the exchange of insights from signed and spoken language research in this area can stimulate further inquiry and advance theory across both fields. This chapter is a joint discussion of key items related to discourse analysis related to signed and spoken language assessment that were discussed in Chapters 10.1 and 10.2.

A Primer on the Conditional Mediation Analysis in PLS-SEM

Conditional mediation (CoMe) analysis integrates mediation and moderation analyses to examine and test hypotheses about how mediated relationships vary as a function of context, boundaries, or individual differences. Although CoMe analysis can be a crucial element of empirical studies that seek to advance theory in information systems, applications of such analysis are scarce, in general, and in partial least squares structural equation modeling (PLS-SEM), in particular. This paper clarifies conceptual fundamentals of and develops guidelines for CoMe analysis within the PLS-SEM context. Furthermore, the paper outlines the illustrative use of CoMe analysis in PLS-SEM and presents detailed step-by-step procedures to do so in the PLS-SEM setting. Overall, this paper provides researchers and practitioners with the required knowledge to properly carry out, report, and interpret CoMe analysis in PLS-SEM.

Quantifying Social Semantics: An Inclusive Definition of Socialness and Ratings for 8,388 English Words

It has been proposed that social experience plays an important role in the grounding of concepts, and socialness has been proffered as a fundamental organisational principle underpinning semantic representation in the human brain. However, the empirical support for these hypotheses is limited by inconsistencies in the way socialness has been defined and measured. To further advance theory, the field must establish a clearer working definition, and research efforts could be facilitated by the availability of an extensive set of socialness ratings for individual concepts. Therefore, in the current work we employed a novel and inclusive definition to test the extent to which socialness is reliably perceived as a broad construct, and we report socialness norms for over 8,000 English words, including nouns, verbs and adjectives. Our inclusive socialness measure shows good reliability and validity, and our analyses suggest that the socialness ratings capture aspects of word meaning which are distinct to those measured by other pertinent semantic constructs, including concreteness and emotional valence. Finally, in a series of regression analyses, we show for the first time that the socialness of a word's meaning explains unique variance in participant performance on lexical tasks. Our dataset of socialness norms has considerable item overlap with those used both in other lexical/semantic norms and in available behavioural mega-studies. They can help target testable predictions about brain and behaviour derived from multiple representation theories and neurobiological accounts of social semantics.

A model to guide the effective use of a business case for IT projects

PurposeThe paper responds to calls in recent research for a model that shows how the business case should be used throughout the project's lifetime to achieve sound governance and thereby project success. The aim of the paper is to advance theory about the effective use of the business case.Design/methodology/approachBesides the processes and information required, the literature identified 43 organizational facilitating factors, structured into 5 categories, which are required for effective use of the business case. To offer a useful model, the authors' approach was to do a factor analysis, based on existing survey data, to reduce the number of facilitators and to validate their categorization.FindingsThe findings of the paper were as follows: (1) the classification of the proposed facilitating factors was validated; (2) the number of facilitators needed to ensure that the business case is used effectively was substantially reduced and (3) a “business case effectiveness model” is proposed to clarify the relationship between the organizational facilitating factors, the business case processes and the information required to effectively use the business case.Originality/valueThis is the first time that a business case effectiveness model has been proposed. Besides consolidating business case theory, it can be used to guide people and organizations on simple, affordable ways to improve their use of the business case to achieve sound governance and hence business/information technology project success.

Towards successful implementation of artificial intelligence in healthcare practice: A research program (Preprint)

BACKGROUND The uptake of artificial intelligence (AI) in healthcare is at an early stage. Recent studies have shown the lack of AI-specific implementation theories, models or frameworks that could provide guidance for how to translate the potential of AI into daily healthcare practices. This protocol provides an outline for the first four years of a research program seeking to address this knowledge-practice gap through collaboration and co-design between researchers, healthcare professionals, patients and industry stakeholders. OBJECTIVE The first part of the program focuses on two specific objectives. First, to build an understanding of implementation of AI in healthcare and to develop a theoretical framework that can facilitate AI implementation in daily healthcare practices. Second, to carry out empirical AI implementation studies guided by the framework for AI implementation, thus generating insights and learning for enhanced knowledge and refinement of the framework. METHODS This research program uses a logic model to structure to the development of a methodological framework for planning and evaluating implementation of AI systems in healthcare and to support capacity building for its use in practice. The logic model is divided into time-separated stages, with a focus on theory driven and co-produced framework development. The activities are based on both knowledge development, utilizing existing theory and literature reviews, and method development by means of co-design and empirical investigations. The activities involve researchers, healthcare professionals and other stakeholders, thus creating a multi-perspective understanding of how the implementation of AI systems should be approached to increase likelihood of successful implementation and application in clinical practice. RESULTS The project is funded by the Swedish Innovation Agency and the Knowledge foundation for a period of 8 years in total starting from July 2021. CONCLUSIONS There is a need to advance theory and empirical evidence on implementation requirements of AI systems in healthcare, and an opportunity to bring together insights from research on the development, introduction and evaluation of AI systems and existing knowledge about implementation research literature. Therefore, we intend in this research program to build an understanding, using both theoretical and empirical approaches, of how implementation of AI systems should be approached to increase the likelihood of successful and widespread application in clinical practice.

Using factorial mediation analysis to better understand the effects of interventions

To improve understanding of how interventions work or why they do not work, there is need for methods of testing hypotheses about the causal mechanisms underlying the individual and combined effects of the components that make up interventions. Factorial mediation analysis, i.e., mediation analysis applied to data from a factorial optimization trial, enables testing such hypotheses. In this commentary, we demonstrate how factorial mediation analysis can contribute detailed information about an intervention’s causal mechanisms. We briefly review the multiphase optimization strategy (MOST) and the factorial experiment. We use an empirical example from a 25 factorial optimization trial to demonstrate how factorial mediation analysis opens possibilities for better understanding the individual and combined effects of intervention components. Factorial mediation analysis has important potential to advance theory about interventions and to inform intervention improvements.

The Value of Mechanistic Experiments to Target the Shared Neural Circuitry of Parenting and Addiction: The Potential for Video Feedback Interventions

Certain neural processes that underlie addiction are also central to parenting, notably stress and reward. Parenting interventions that incorporate the unique context of caregivers with addiction have demonstrated some success: However, real-world implementation of evidence-based interventions can be difficult with this population. Video feedback interventions are an especially promising approach to reach parents who experience barriers to participation, particularly caregivers with addiction. A translational neuroscientific approach to elucidating the mechanisms of change in these interventions will aid the delivery and success of this method and advance theory surrounding parenting in the context of addiction. Along these lines, we provide an example of one video feedback intervention, Filming Interactions to Nurture Development, that will serve as such a mechanistic experiment.

A bridge to progress further afield: The promise of a common framework on attentional capture

Although physical salience looms large in the attentional capture literature, stimuli can also capture attention via salience deriving from non-physical factors. Such psychological salience can stem, for example, from the emotional resonance of stimuli or their relevance to a person’s expertise. We consider how insights from a recently proposed framework for attentional capture can be used to advance theory and drive research on the role of emotion-driven attentional biases in clinical disorders and on how attentional allocation changes with the development of perceptual expertise. In return, we wonder how their common framework can be enriched through considerations of psychological salience.

Entrepreneurs’ Ethnic and Political Identity Alignment as Determinants of Access to Government Support in Africa: A Conceptual Framework

This article contributes to research on the role of government in entrepreneurship by extending the current focus from government policies to policymakers. Specifically, we examine how entrepreneurs’ identity alignment with regime leaders influences their access to government support in Africa. Drawing from ethnocentrism and neopatrimonialism perspectives, we develop a theoretical model that explains how entrepreneurs’ ethnic and political identity alignment influences their access to government support. We also advance theory by discussing the “dark side” of identity-based government support in Africa. In doing so, we shed some light on the rather complex sociopolitical determinants of resource access in Africa.