Characteristics of successful technological interventions in mental resilience training.

In the last two decades, several effective virtual reality-based interventions for anxiety disorders have been developed. Virtual reality interventions can also be used to build resilience to psychopathology for populations at risk of exposure to traumatic experiences and developing mental disorders as a result, such as for people working in vulnerable professions. Despite the interest among mental health professionals and researchers in applying new technology-supported interventions for pre-trauma mental resilience training, there is a lack of recommendations about what constitutes potentially effective technology-supported resilience training. This article analyses the role of technology in the field of stress-resilience training. It presents lessons learned from technology developers currently working in the area, and it identifies some key clinical requirements for the supported resilience interventions. Two processes made up this research: 1) developers of technology-assisted resilience programs were interviewed regarding human-computer interaction and system development; 2) discussions with clinicians were prompted using technology-centered concept storyboards to elicit feedback, and to refine, validate and extend the initial concepts. A qualitative analysis of the interviews produced a set of development guidelines that engineers should follow and a list of intervention requirements that the technology should fulfill. These recommendations can help bridge the gap between engineers and clinicians when generating novel resilience interventions for people in vulnerable professions.

Usability of an adaptive computer assistant that improves self-care and health literacy of older adults.

OBJECTIVES: We developed an adaptive computer assistant for the supervision of diabetics' self-care, to support limiting illness and need for acute treatment, and improve health literacy. This assistant monitors self-care activities logged in the patient's electronic diary. Accordingly, it provides context-aware feedback. The objective was to evaluate whether older adults in general can make use of the computer assistant and to compare an adaptive computer assistant with a fixed one, concerning its usability and contribution to health literacy. METHODS: We conducted a laboratory experiment in the Georgia Tech Aware Home wherein 28 older adults participated in a usability evaluation of the computer assistant, while engaged in scenarios reflecting normal and health-critical situations. We evaluated the assistant on effectiveness, efficiency, satisfaction, and educational value. Finally, we studied the moderating effects of the subjects' personal characteristics. RESULTS: Logging self-care tasks and receiving feedback from the computer assistant enhanced the subjects' knowledge of diabetes. The adaptive assistant was more effective in dealing with normal and health-critical situations, and, generally, it led to more time efficiency. Subjects' personal characteristics had substantial effects on the effectiveness and efficiency of the two computer assistants. CONCLUSIONS: Older adults were able to use the adaptive computer assistant. In addition, it had a positive effect on the development of health literacy. The assistant has the potential to support older diabetics' self care while maintaining quality of life.

Cognitive task load in a naval ship control centre: from identification to prediction.

Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support.

Cognitive task analysis: harmonizing tasks to human capacities.

This paper presents the development of a cognitive task analysis that assesses the task load of jobs and provides indicators for the redesign of jobs. General principles of human task performance were selected and, subsequently, integrated into current task modelling techniques. The resulting cognitive task analysis centres around four aspects of task load: the number of actions in a period, the ratio between knowledge- and rule-based actions, lengthy uninterrupted actions, and momentary overloading. The method consists of three stages: (1) construction of a hierarchical task model, (2) a time-line analysis and task load assessment, and (3), if necessary, adjustment of the task model. An application of the cognitive task analysis in railway traffic control showed its benefits over the 'old' task load analysis of the Netherlands Railways. It provided a provisional standard for traffic control jobs, conveyed two load risks -- momentary overloading and underloading -- and resulted in proposals to satisfy the standard and to diminish the two load risk.