Interruption science

From Wikipedia, the free encyclopedia

Interruption science is the interdisciplinary scientific study concerned with how interruptions affect human performance, and the development of interventions to ameliorate the disruption caused by interruptions. Interruption science is a branch of human factors psychology and emerged from human–computer interaction and cognitive psychology.

Being ubiquitous in life and an intuitive concept, there are few formal definitions of interruption. A commonly agreed upon definition proposed by Boehm-Davis and Remington specifies an interruption is "the suspension of one stream of work prior to completion, with the intent of returning to and completing the original stream of work".[1] Interruptions are considered to be on the spectrum of multitasking and in this context referred to as sequential multitasking.[2] The distinguishing feature of an interruption (see Task switching (psychology), concurrent multitasking) is the presence of primary task which must be returned to upon completing a secondary interrupting task.[2] For instance, talking on the phone while driving is generally considered an instance of concurrent multitasking; stopping a data entry task to check emails is generally considered an instance of an interruption.

Interruptions, in almost all instances, are disruptive to performance and induce errors.[3] Therefore, interruption science typically examines the effects of interruptions in high-risk workplace environments such as aviation,[4] medicine,[5] and vehicle operation[6] in which human error can have serious, potentially disastrous consequences. Interruptions are also explored in less safety-critical workplaces, such as offices, where interruptions can induce stress,[7] anxiety,[8] and poorer performance.[9]


The first formal investigation into interruptions was conducted by Zeigarnik and Ovsiankina as part of the Vygotsky Circle in the 1920s. Their seminary research demonstrated the Zeigarnik effect: people remember uncompleted or interrupted tasks better than completed tasks. In the 1940s, Fitts and Jones reported that interruptions were a cause of pilot errors and flying accidents, and made recommendations on reducing these disruptive effects.[10]

Theoretical models[edit]

Knowledge workers[edit]

Office workers face a number of interruptions due to information technologies such as e-mail, text messages, and phone calls. One line of research in interruption science examines the disruptive effects of these technologies and how to improve the usability and design of such devices. According to Gloria Mark, "the average knowledge worker switches tasks every three minutes, and, once distracted, a worker can take nearly a half-hour to resume the original task".[11] Mark conducted a study on office workers, which revealed that "each employee spent only 11 minutes on any given project before being interrupted".[12] Kelemen et al. showed that a team of programmers is interrupted through a technical Skype support chat up to 150 times a day, but these interruptions can be reduced by introducing a dispatcher role and a knowledge base.[13]


One of the major challenges associated with increased reliance on information technologies is they will send users notifications, without considering current task demands. Answering notifications impedes task performance and the ability to resume to the original task at hand.[14] In addition, even just knowing that one has received a notification can negatively impact sustained attention.[15]

Several solutions have been proposed to this problem. One study suggested entirely disable email notifications. The down side was it may induce a pressure to constant need to check their email accounts.[14]: 27  In fact, entirely removing notifications may lead people to spend more time checking their email.[14]: 29  The absence of e-mail notifications is often seen as counterproductive because of the required "catch-up" time periods after a long time between email checking.[14]: 30  Alternatively, there are several attempts to design software applications that deliver notifications when there is an identified break from work,[16] or categorize notifications based on their relative importance (e.g. Oasis).

Research has also investigated the effects of relevant interruptions, and found notifications relevant to the current task are less disruptive than if it were unrelated.[17]: 99  Overall task performance is most impacted when an instant message is received during fast and stimulus-driven tasks such as typing, pressing buttons, or examining search results.[18]: 263, 265, 268 

Bounded deferral is a restricted notification method that entails users waiting a prescribed amount of time before they access a notification to reduce the amount of interruption and decline in productivity. This technique was used in the aim to provide calmer and less disruptive work spaces.[19]: 1  If users are busy, alerts and notifications are put aside and delivered only when users are in a position to receive notifications without harming their work. The bounded deferral method has proven to be useful and has the potential to become even more effective on a wider scale, as it has showed how an effective notification system can operate.


For a surgeon, interruption during an operation could have serious consequences. Yet in some cases, a surgeon may need to be interrupted to make him or her aware of new issues arising with the patient.

In nursing, a study has been conducted of the impact of interruptions on nurses in a trauma center.[20] Another study has been done on the interruption rates of nurses and doctors.[21]

Interruption caused by smartphone use in health-care settings can be deadly. Hence, it may be worthwhile for health care organizations to craft effective cellphone usage policies to maximize technological benefits and minimize unnecessary distraction associated with smartphone use.[22]

See also[edit]


  1. ^ Boehm-Davis, Deborah A.; Remington, Roger (September 2009). "Reducing the disruptive effects of interruption: A cognitive framework for analysing the costs and benefits of intervention strategies". Accident Analysis & Prevention. 41 (5): 1124–1129. doi:10.1016/j.aap.2009.06.029. PMID 19664456.
  2. ^ a b Taatgen, Dario D. Salvucci, Niels A. (2011). The multitasking mind. New York: Oxford University Press. ISBN 978-0199733569.
  3. ^ Trafton, Gregory J.; Monk, Christopher A. (1 March 2007). "Task Interruptions". Reviews of Human Factors and Ergonomics. 3 (1): 111–126. doi:10.1518/155723408X299852.
  4. ^ Latorella, K. A. (1 October 1998). "Effects of Modality on Interrupted Flight Deck Performance: Implications for Data Link". Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 42 (1): 87–91. doi:10.1177/154193129804200120. S2CID 220255262.
  5. ^ Sanderson, Penelope M.; Grundgeiger, Tobias (July 2015). "How do interruptions affect clinician performance in healthcare? Negotiating fidelity, control, and potential generalizability in the search for answers" (PDF). International Journal of Human-Computer Studies. 79: 85–96. doi:10.1016/j.ijhcs.2014.11.003.
  6. ^ Kim, Seungjun; Chun, Jaemin; Dey, Anind K. (2015). Sensors Know When to Interrupt You in the Car. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15. pp. 487–496. doi:10.1145/2702123.2702409. ISBN 9781450331456. S2CID 15340675.
  7. ^ Gloria Mark; Daniela Gudith; Ulrich Klocke (2008). "The cost of interrupted work: more speed and stress". CHI '08 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. pp. 107–110.
  8. ^ Bailey, Brian P.; Konstan, Joseph A. (July 2006). "On the need for attention-aware systems: Measuring effects of interruption on task performance, error rate, and affective state". Computers in Human Behavior. 22 (4): 685–708. doi:10.1016/j.chb.2005.12.009.
  9. ^ Cades, D. M.; Werner, N. E.; Boehm-Davis, D. A.; Arshad, Z. (1 September 2010). "What makes Real-World Interruptions Disruptive? Evidence from an Office Setting". Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 54 (4): 448–452. doi:10.1177/154193121005400437. S2CID 110014660.
  10. ^ Gillie, Tony; Broadbent, Donald (April 1989). "What makes interruptions disruptive? A study of length, similarity, and complexity". Psychological Research. 50 (4): 243–250. doi:10.1007/BF00309260. S2CID 14878182.
  11. ^ Alboher, Marci (22 June 2008). "Fighting a War Against Distraction". New York Times.
  12. ^ Thompson, Clive (16 October 2005). "Meet the Life Hackers". New York Times.
  13. ^ Kelemen, Zádor Dániel; Tódor, Balázs; Hodosi, Sándor; Somfai, Ákos (2016-11-01). "Refactoring technical support to reduce interrupts of developers". Journal of Software: Evolution and Process. 28 (11): 960–968. arXiv:1510.04929. doi:10.1002/smr.1822. ISSN 2047-7481. S2CID 16409217.
  14. ^ a b c d Iqbal, Shamsi T.; Horvitz (2010). Notifications and Awareness: A Field Study of Alert Usage and Preferences. Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work. pp. 27–30. doi:10.1145/1718918.1718926. ISBN 9781605587950. S2CID 843427.
  15. ^ Stothart, C; Mitchum, A; Yehnert, C (29 June 2015). "The Attentional Cost of Receiving a Cell Phone Notification". Journal of Experimental Psychology: Human Perception and Performance. 41 (4): 893–7. doi:10.1037/xhp0000100. PMID 26121498.
  16. ^ Cutrell, Edward. "Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance" (PDF). Microsoft Research. Retrieved 15 October 2012.
  17. ^ Iqbal, Shamsi T; Bailey (2008). "Effects of Intelligent Notification Management on Users and Their Tasks". Proceedings of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems, CHI'08: 93–102. CiteSeerX doi:10.1145/1357054.1357070. ISBN 9781605580111. S2CID 9847368. Retrieved 17 October 2012.
  18. ^ Cutrell, Edward; Czerwinski, Horvitz (2001). "Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance" (PDF). INTERACT 2001 Conference Proceedings: 263–269. Retrieved 17 October 2012.
  19. ^ Horvitz, Eric. "Balancing Awareness and Interruption: Investigation of Notification Deferral Policies" (PDF). Microsoft Research. Retrieved 17 October 2012.
  20. ^ Brixey J. J., Robinson D. J., Tang Z., Johnson T. R., Zhang J. & Turley J. P. (2005) "Interruptions in Workflow for RNs in a Level-One Trauma Center", in: AMIA 2005 Annual Symposium Proceedings, Bethesda, MD: American Medical Informatics Association, 86-90
  21. ^ Paxton, F.; Heaney, D. J.; Howie, J. G.; Porter, A. M. (1996). "A study of interruption rates for practice nurses and GPs". Nursing Standard. 10 (43): 33–36. doi:10.7748/ns.10.43.33.s53. PMID 8826300.
  22. ^ Gill, P.S.; Kamath, A.; Gill, T.S. (2012). "Distraction: an assessment of smartphone usage in health care work settings". Risk Management and Healthcare Policy. 5: 105–114. doi:10.2147/RMHP.S34813. PMC 3437811. PMID 22969308.

Further reading[edit]