Task Interruption: Resumption Lag and the Role of Cues

Task Interruption: Resumption Lag and the Role of Cues Erik M. Altmann ( ema@msu.edu ) J. Gregory Trafton ( trafton@itd.nrl.navy.mil ) Department of Psychology Michigan State University East Lansing, MI 48824 Naval Research Laboratory, Code 5513 4555 Overlook Avenue S. W. Washington, DC 20375 Abstract again, when an interruption is over and we can return to what we were doing before. There is surprisingly little research focused on this measure, and what there is is distributed across a variety of domains and paints no clear picture of whether interruptions are disruptive or not. For example, in a study of interruption of administrative and clerical workers, disruptive effects of interruption were difficult to detect (Zijlstra, Roe, Leonora, & Krediet, 1999), and interruption in a simple question-answering task can actually improve performance, measured in terms of overall accuracy and time-on-task (Speier, Vessey, & Valacich, 2003). In the mainstream cognitive psychology literature, research on “task switching” (Monsell, 2003) would seem to be relevant, as studies in this domain typically focus on the “switch cost” associated with shifting from one task to another. However, this literature is perhaps not so aptly named; the “tasks” used in task-switching studies take a few hundred milliseconds to complete, with switch cost a small and not particularly relevant fraction of that (Altmann, in press). We are interested in higher-level tasks with greater ecological validity, where switch cost is measured not in tens of milliseconds, but in seconds or longer. In operational terms, the dependent measure in the current study is the resumption lag, illustrated in Figure 1. The resumption lag is the time interval separating the end of the secondary task and the first subsequent action taken by the human operator in the primary task. We report first a comparison of this resumption lag to an estimate of the time interval that usually separates actions in the primary task, to give a sense of the absolute magnitude of the disruptive effect; to preview, the mean inter-action interval, in the highly interactive primary task we are using, is roughly 2 s, and the resumption lag is roughly 4 s, indicating a substantial disruption both in absolute and relative terms. We then report on two factors that have the potential to reduce the resumption lag. Both focus on the interruption lag, also illustrated in Figure 1. The interruption lag is a brief transitional interval immediately preceding an interruption, during which the operator knows of the pending interruption but is not yet engaged by it. An example is the time between the phone starting to ring and the act of actually taking the call; during this interval, there is a brief opportunity to complete a thought, for example, or negotiate quickly with a conversation partner (physically present) how and when to resume after the call is over. Many real-world interruptions, even more urgent ones, afford a brief interruption lag; even when a fire alarm sounds, one is still likely to take time to save changes to an electronic document, for example, before evacuating. The consequences of interrupting someone in the middle of a complex task are of considerable practical and theoretical interest. We examine one behavioral measure of the disruption caused by task interruption, namely the resumption lag, or the time needed to “collect one’s thoughts” and restart a task after an interruption is over. The resumption lag (in our task environment) was double the interval between uninterrupted actions (3.8 s vs. 1.9 s), indicating a substantial disruptive effect. To probe the nature of the disruption, we examined the role of external cues associated with the interrupted task, finding that cues available immediately before an interruption facilitate performance immediately afterwards (reducing the resumption lag). This c u e - availability effect suggests that people deploy preparatory perceptual and memory processes, apparently spontaneously, to mitigate the disruptive effects of task interruption. Introduction For better or worse, interruptions are part of everyday life. For better, interruptions are an essential part of efficient communication, among people and between people and machines. For worse, interruptions can be annoying, and can seem disruptive. For example, the annoyance of unwanted telephone solicitations drove the recent overwhelming popularity of “do not call” registries in the United States. Similarly, consider the “software assistant” included in Microsoft products in the late 1990s. If Word, for example, detected what it thought was a letter being drafted, it would freeze the keyboard and demand to know if the user needed “help” — a feature that in more recent editions of the software is no longer enabled by default. There are many parameters to how an interruption is structured — including interruption duration, for example, or whether the interrupted person has control over interruption timing (McFarlane & Latorella, 2002) — and there is also a range of different behavioral measures on which the assess the impact of an interruption. In one classic result, Zeigarnik (1927/1938) found that interrupted tasks were actually remembered better, in terms of recalled detail, than tasks that were allowed to run to completion. In more applied work, however, interruptions have been found to have detrimental effects on situational awareness in dynamic task environments like aviation (Latorella, 1996), where losing one’s place in a checklist during takeoff, for example, can have catastrophic results (NTSB, 1988). The current study examines the disruptive effects of interruption in terms of the time needed to resume the primary (interrupted) task after the secondary (interrupting) task is complete. In less formal terms, we examine the time needed to collect one’s thoughts, or pick up the thread