Trust plays an essential role in all human relationships. However, measuring trust remains a challenge for researchers exploring psychophysiological signals. Therefore, this article aims to systematically map the approaches used in studies assessing trust with psychophysiological signals. In particular, we examine the numbers and frequency of combined psychophysiological signals, the primary outcomes of previous studies, and the types and most commonly used data analysis techniques for analyzing psychophysiological data to infer a trust state. For this purpose, we employ a systematic mapping review method, through which we analyze 51 carefully selected articles (studies focused on trust using psychophysiology). Two significant findings are as follows: (1) Psychophysiological signals from EEG(electroencephalogram) and ECG(electrocardiogram) for monitoring peripheral and central nervous systems are the most frequently used to measure trust, while audio and EOG(electro-oculography) psychophysiological signals are the least commonly used. Moreover, the maximum number of psychophysiological signals ever combined so far is three (2). Most of which are peripheral nervous system monitoring psychophysiological signals that are low in spatial resolution. (3) Regarding outcomes: there is only one tool proposed for assessing trust in an interpersonal context, excluding trust in a technology context. Moreover, there are no stable and accurate ensemble models that have been developed to assess trust; all prior attempts led to unstable but fairly accurate models or did not satisfy the conditions for combining several algorithms (ensemble). In conclusion, the extent to which trust can be assessed using psychophysiological measures during user interactions (real-time) remains unknown, as there several issues, such as the lack of a stable and accurate ensemble trust classifier model, among others, that require urgent research attention. Although this topic is relatively new, much work has been done. However, more remains to be done to provide clarity on this topic.

System architecture plays a crucial role in the establishment of Digital Government infrastructure. Over recent decades, various architectures have been introduced by scholars for the establishment of Digital Government infrastructure. However, there is no uniform agreement on Digital Government architecture concepts required for Digital Government infrastructure. To more thoroughly examine the Digital Government architecture introduced in this article, we collected 103 papers published between 2003 and 2020 retrieved from five leading literature databases. To conduct our research, we followed best practice scholarly accepted guidelines for researchers. Per the guidelines, we formulated research questions and employed an approach based on specific inclusion and exclusion criteria to meet our research goals. Our study found evidence that there is a lack of knowledge in terms of the state-of-the-art in Digital Government infrastructure and its challenges concerning existing Digital Government architectures. We identified a set of primary Digital Government architecture characteristics and building blocks on which the Digital Government infrastructures are built. These components are meant to improve the design of future Digital Government systems and applications. Furthermore, our research revealed a need for designing a reference architecture to provide government organizations with the best practice knowledge of already existing Digital Government architectures.

Human–computer interaction (HCI) practice has emerged as a research domain in the HCI field and is growing. The need to transfer HCI practices to the industry began significantly with the works of Nielsen on usability engineering. To date, methods and techniques for designing, evaluating, and implementing interactive systems for human use have continued to emerge. It is, therefore, justified to conduct a systematic mapping study to determine the landscape of HCI practice research. A Systematic Mapping Study method was used to map 142 studies according to research type, topic, and contribution. These were then analyzed to determine an overview of HCI practice research. The objective was to analyze studies on HCI practice and present prominent issues that characterize the HCI practice research landscape. Second, to identify pressing challenges regarding HCI practices in software/systems development companies. The results show that HCI practice research has steadily increased since 2012. The majority of the studies explored focused on evaluation research that largely contributed to the evaluation methods or processes. Most of the studies were on design tools and techniques, design methods and contexts, design work and organizational culture, and collaboration and team communication. Interviews, case studies, and survey methods have been prominently used as research methods. HCI techniques are mostly used during the initial phase of development and during evaluation. HCI practice challenges in companies are mostly process-related and on performance of usability and user experience activities. The major challenge seems to be to find a way to collect and incorporate user feedback in a timely manner, especially in agile processes. There are areas identified in this study as needing more research.

Trust in technology is a topic of growing importance in Human–Computer Interaction due to the growing impact of systems on daily lives. However, limited attention has been paid to how one’s national culture shapes their propensity to trust. This study addresses an existing gap in trust in technology research by advancing towards a more accurate tool for quantitatively measuring propensity to trust across different contexts. We specifically evaluate the psychometric properties of the human–computer trust scale (HCTS) in Brazil, Singapore, Malaysia, Estonia, and Mongolia. To accomplish this, we used the Measurement Invariance of Composite Models (MICOM), a procedure that examines the equivalency of the instrument’s psychometric properties across different groups. Our results highlight the importance of rigorous validation processes when applying psychometric instruments in cross-cultural contexts, offering insights into the differences between the countries investigated and the procedure’s potential to investigate trust across different groups.

This perspective essay proposes Democracy Labs as new processes for developing democratic innovations that help tackle complex socio-ecological challenges within an increasingly unequal and polarised society, against the backdrop of democratic backsliding. Next to the current socio-ecological crisis, rapid technological innovations present both opportunities and challenges for democracy and call for democratic innovations. These innovations (e.g., mini-publics, collaborative governance and e-participation) offer alternative mechanisms for democratic participation and new forms of active citizenship, as well as new feedback mechanisms between citizens and traditional institutions of representative democracy. This essay thus introduces Democracy Labs, as citizen-centred processes for co-creating democratic innovations to inspire future transdisciplinary research and practice for a more inclusive and sustainable democracy. The approach is illustrated with examples from a Democracy Lab in Lisbon, reflecting on requirements for recruiting participants, the relevance of combining sensitising, reflection and ideation stages, and the importance of careful communication and facilitation processes guiding participants through co-creation activities.