Patient locus of control (LOC) is a strong determinant of health outcomes, yet healthcare systems rarely use patient LOC to devise treatment plans. Our clinical research applies action design research methods to design and evaluate healthcare information systems to improve paths and outcomes of patient care. Socio-technical synergies between the interior (technical) and exterior (socio) designs support effective human-computer interfaces and interactions. Rigorous focus group evaluations of the systems for capturing LOC information and using that information in treatment plans are performed and system refinements are implemented. The practitioner organisation has future plans for full implementation of the designed systems.

Online analytical processing (OLAP) engines display aggregated data to help business analysts compare data, observe trends, and make decisions. Issues of data quality and, in particular, issues with missing data impact the quality of the information. Key decision-makers who rely on these data typically make decisions based on what they assume to be all the available data. The authors investigate three approaches to dealing with missing data: 1) ignore missing data, 2) show missing data explicitly (e.g., as unknown data values), and 3) design mitigation algorithms for missing data (e.g., allocate missing data into known value categories). The authors evaluate the approach with focus groups and controlled experiments. When one tries to inform decision-makers using the approaches in the research, the authors find that they often alter their decisions and adjust their decision confidence: individual differences of tolerance for ambiguity and pre-existing omission bias in the decision context influence their decisions.

On the 10th anniversary of the NeuroIS field, we reflect on accomplishments but, more importantly, on the future of the field. This commentary presents our thoughts on a future NeuroIS research agenda with the potential for high impact societal contributions. Four key areas for future information systems (IS) research are: (1) IS design, (2) IS use, (3) emotion research, and (4) neuro-adaptive systems. We reflect on the challenges of each area and provide specific research questions that serve as important directions for advancing the NeuroIS field. The research agenda supports fellow researchers in planning, conducting, publishing, and reviewing high impact studies that leverage the potential of neuroscience knowledge and tools to further information systems research.

This research essay proposes an elaborated process model for applying the action design research (ADR) approach to immersive industry-based projects. Building on the original ADR concepts, we identify four distinct types of ADR cycles for diagnosis, design, implementation, and evolution of the growing artefact-based solution. Each ADR cycle moves through activities of problem formulation, artefact creation, evaluation, reflection, and learning. Rapid iterations of ADR cycles provide a well-defined process map for managing and performing an emergent ADR project. The proposed model supports multiple entry points based on the current state of the problem environment and the goals of the ADR project. The elaborated ADR process model provides a more flexible yet disciplined inquiry into the initiation, conduct, reflection, and presentation of rigorous and relevant ADR projects.

Local area networks are becoming widely used as the database communication framework for sophisticated information systems. Databases can be distributed among stations on a network to achieve the advantages of performance, reliability, availability, and modularity. Efficient distributed query optimization algorithms are presented here for two types of local area networks: address ring networks and broadcast networks . Optimal algorithms are designed for simple queries . Optimization principles from these algorithms guide the development of effective heuristic algorithms for general queries on both types of networks. Several examples illustrate distributed query processing on local area networks.

The form has become an important abstraction for data management in an office application environment.Structured office forms present data to users in an easily understood and easily manipulated manner.In this paper we classify forms systems in terms of three dimensions: data structuring, user interfaces, and programming interfaces.Current forms systems are analyzed under these dimensions.We have designed a comprehensive forms management system, FORMANAGER, that includes facilities for form specification, form processing, and form control.The system transforms data from a relational database into a hierarchical data structure which defines the form.The design and algorithms for implementation of the system are described, and future extensions to enhance the capabilities of forms systems are proposed.