System-generated alerts are ubiquitous in personal computing and, with the proliferation of mobile devices, daily activity. While these interruptions provide timely information, research shows they come at a high cost in terms of increased stress and decreased productivity. This is due to dual-task interference (DTI), a cognitive limitation in which even simple tasks cannot be simultaneously performed without significant performance loss. Although previous research has examined how DTI impacts the performance of a primary task (the task that was interrupted), no research has examined the effect of DTI on the interrupting task. This is an important gap because in many contexts, failing to heed an alertÑthe interruption itselfÑcan introduce critical vulnerabilities.
Using security messages as our context, we address this gap by using functional magnetic resonance imaging (fMRI) to explore how (1) DTI occurs in the brain in response to interruptive alerts, (2) DTI influences message security disregard, and (3) the effects of DTI can be mitigated by finessing the timing of the interruption. We show that neural activation is substantially reduced under a condition of high DTI, and the degree of reduction in turn significantly predicts security message disregard. Interestingly, we show that when a message immediately follows a primary task, neural activity in the medial temporal lobe is comparable to when attending to the message is the only task.
Further, we apply these findings in an online behavioral experiment in the context of a web-browser warning. We demonstrate a practical way to mitigate the DTI effect by presenting the warning at low-DTI times, and show how mouse cursor tracking and psychometric measures can be used to validate low-DTI times in other contexts.
Our findings suggest that although alerts are pervasive in personal computing, they should be bounded in their presentation. The timing of interruptions strongly influences the occurrence of DTI in the brain, which in turn substantially impacts alert disregard. This paper provides a theoretically grounded, cost-effective approach to reduce the effects of DTI for a wide variety of interruptive messages that are important but do not require immediate attention.
Warning messages are fundamental to users' security interactions. Unfortunately, they are largely ineffective, as shown by prior research. A key contributor to this failure is habituation: decreased response to a repeated warning. Previous research has only inferred the occurrence of habituation to warnings, or measured it indirectly, such as through the proxy of a related behavior. Therefore, there is a gap in our understanding of how habituation to security warnings develops in the brain. Without direct measures of habituation, we are limited in designing warnings that can mitigate its effects. In this study, we use neurophysiological measures to directly observe habituation as it occurs in the brain and behaviorally. We also design a polymorphic warning artifact that repeatedly changes its appearance in order to resist the effects of habituation. In an experiment using functional magnetic resonance imaging (fMRI; n = 25), we found that our polymorphic warning was significantly more resistant to habituation than were conventional warnings in regions of the brain related to attention. In a second experiment (n = 80), we implemented the four most resistant polymorphic warnings in a realistic setting. Using mouse cursor tracking as a surrogate for attention to unobtrusively measure habituation on participants' personal computers, we found that polymorphic warnings reduced habituation compared to conventional warnings. Together, our findings reveal the substantial influence of neurobiology on users' habituation to security warnings and security behavior in general, and we offer our polymorphic warning design as an effective solution to practice > >
Historically, inaccurate credibility assessments have resulted in tremendous costs to businesses and to society. Recent research offers unobtrusive credibility assessment aids as a solution; however, the accuracy of these decision aids is inadequate, and users often resist accepting the aids' recommendations. We follow the principles of signal detection theory to improve the accuracy of recommendations in computer-aided credibility assessment by combining automated and participatory decision support. We also leverage participation in decision-making theory to explain and predict an increased acceptance of assessment aid recommendations when perceptual cues are elicited from users. Based on these two theories, we design and test a hybrid decision aid to perform automated linguistic analysis and to elicit and analyze perceptual cues from an observer. Results from a laboratory experiment indicate that decision aids that use linguistic and perceptual cues offer more accurate recommendations than aids that use only one type of cue. Automatic analysis of linguistic cues improved both the decision aid's recommendations and the users' credibility assessment accuracy. Challenging the generalizability of past findings, the elicitation of perceptual cues did not improve the decision aid's recommendations or the users' assessment accuracy. Elicitation of perceptual cues, however, did improve user acceptance of the decision aid's recommendations. These findings provide guidance for future development of credibility assessment decision aids.
Process satisfaction is one important determinant of work group collaborative system adoption, continuance, and performance. We explicate the computer-mediated communication (CMC) interactivity model (CMCIM) to explain and predict how interactivity enhances communication quality that results in increased process satisfaction in CMC-supported work groups. We operationalize this model in the challenging context of very large groups using extremely lean CMC. We tested it with a rigorous field experiment and analyzed the results with the latest structural equation modeling techniques. Interactivity and communication quality dramatically improved for very large groups using highly lean CMC (audience response systems) over face-to- face groups. Moreover, CMC groups had fewer negative status effects and higher process satisfaction than face-to-face groups. The practical applications of lean CMC rival theoretical applications in importance because lean CMC is relatively inexpensive and requires minimal training and support compared to other media. The results may aid large global work group continuance, satisfaction, and performance in systems, product and strategy development, and other processes in which status effects and communication issues regularly have negative influences on outcomes.