The Cost of Interrupted Work: More Speed and Stress
Gloria Mark
Department of Informatics
University of California, Irvine
Irvine, CA, U.S.A. 92697
gmark@ics.uci.edu

Daniela Gudith and Ulrich Klocke
Institute of Psychology
Humboldt University
Berlin, Germany
daniela.gudith@gmail.com, klocke@rz.hu-berlin.de

ABSTRACT

We performed an empirical study to investigate whether thecontext of interruptions makes a difference. We found that
context does not make a difference but surprisingly, people
completed interrupted tasks in less time with no differencein quality. Our data suggests that people compensate forinterruptions by working faster, but this comes at a price:
experiencing more stress, higher frustration, time pressureand effort. Individual differences exist in the managementof interruptions: personality measures of openness toexperience and need for personal structure predict
disruption costs of interruptions. We discuss implications
for how system design can support interrupted work.
Author Keywords

Multi-tasking, interruptions, experiment, context
ACM Classification Keywords

H5. Information interfaces and presentation: H.5.2 User
Interfaces: Theory and Methods
INTRODUCTION

The role of interruptions in the workplace has begun toreceive a lot of attention in HCI in the last few years.
Empirical studies have focused on identifying the extent ofinterruptions and how they affect tasks [6], the recovery oftasks after an interruption [3, 9], and timing ofinterruptions, e.g. [1]. Spurred on by these field andlaboratory studies systems have been developed to help
people manage interruptions (e.g. [3]. Yet as more studies
in multi-tasking and interruptions emerge, so do conflicting
ideas on how interruptions might affect work.
INTERRUPTIONS AND CONTEXT

In a field study of managers, Hudson et al. [8] reported thatinterruptions might be beneficial. Other lab and diary study
results have described them as detrimental [1, 3]. Mark et
al. [10] on the other hand discovered that interruption

effects might be more nuanced: in a field study theirinformants reported that interruptions of the same context
as the current task were beneficial, whereas interruptions ofa different context than the current task were disruptive.
We decided to investigate the different perspectives raisedby these studies. Interruptions during the course of theworkday might be of the same context as the current task
at-hand or they might be random, related to other topics. If
indeed interruptions as the same context as the task at-handare beneficial, then this has important implications for
system design. For example, systems might be designed tohelp colleagues gear their interruptions to others so as
match the context of their tasks.
We were interested in measuring the disruption cost ofinterruptions. One type of a disruption cost is the additionaltime to reorient back to an interrupted task after theinterruption is handled. These previous studies introduce
conflicting notions as to whether the interruption context isrelated to a disruption cost. For example, one might beworking on a paper and be interrupted by a completely
different topic, such as a question about a budget. If aninterruption has a different context than the current task athand, this could introduce a disruption cost as it involves a
cognitive shift of context to attend to the interruption, andthen one must reorient back to attend to the interrupted task.
On the other hand, one might be interrupted by a questionthat concerns the same context as the paper one is working
on. This might be beneficial but if the context of theinterruption and primary task are similar, this could lead tointerference with the primary task [5] and in this way may
introduce a disruption cost. A third possibility is that theinterruption context may not matter. Perhaps any
discontinuity in the task creates a disruption cost for work.
Disruption costs of interruptions can also involve otherfactors such as stress. A second question that we asked is
how interrupted work might change the state of a user; isinterrupted work significantly more stressful or viewed as
more effortful than noninterrupted work? Though we might
intuitively believe it does, it remains an open question.
Disruption costs might also be mitigated by personality
factors. We expected that a) the more open one is to newexperiences (and thus better able to handle new tasks), andb) the less need one has for personal structure (and thus is
more flexible), the lower the disruption cost would be. Wereasoned that these measures would indicate if some canadapt quicker than others to a new situation (theinterruption) and then reorient back to the task. Suchindividual differences could be used to design
customization in a system to adapt to workplace
preferences.
The goal of our experiment was to better understand howinterruptions affect work: its patterns, user strategies, anddisruption costs in order to inform system design to help
people manage interrupted work.
EXPERIMENTAL DESIGN AND PROCEDURE

A 3x2 factorial experimental design was used. The withinsubject factor was interruption context with three levels: nointerruption (B, baseline), same-context interruption (S),and different-context interruption (D). The order ofinterruption context was fully counter-balanced. Becauseinterruptions can come through various sources, wechecked whether media might affect the context ofinterruptions. The between-subjects factor was media type:subjects were interrupted with telephone or IM.
Forty-eight subjects participated. 81% of subjects wereGerman university students with a mean age of 26; all had a
German high school degree (roughly equivalent to one year
in a U.S. university). Most majored in psychology (27.1%),
medicine/sciences (16.7%), or mathematics/engineering/IT(10.4%). Fifteen were males and 33 were females. All but
one participant had been using email for at least two years.
Half of the subjects had been using IM for at least one year
or longer; 29.2% had never used IM before. Subjects were
paid 12 Euros for their participation.
Experimental task. We simulated an office environment in
the lab and chose an email task, common in information
work. Subjects read instructions that they were to play arole as a human resource manager at a medium-sized craft
supply company. They had just returned from vacation andwere carefully instructed in all conditions (and were given
incentives) to answer all emails in their inbox as quickly,
correctly and politely as possible. Subjects were given a
simple fact sheet to use in answering the emails, e.g. staff
job levels and education, overtime hours, etc. For eachinterruption type condition, subjects had to answer 12
emails. Based on pilot studies, the emails in the folders
were equally distributed by topics. We confirmed in thepilot study that the email questions in all conditions wereequally demanding. The content of the emails consisted ofquestions from various people, e.g. “Where do I get more
information on internships in your company?” Subjects first
performed one trial email with the experimenter tofamiliarize them with the equipment and the task.
Interruptions. Subjects were told that their “supervisor” (theexperimenter who sat in another room) would contact them
periodically and ask questions. No interruptions were givenin the baseline condition (B). In the S condition participants
were interrupted by the supervisor with questions

concerning the human resource context (e.g. “How many
employees, including you, are in the department today?”).
These questions were of the same context as the primaryemail task, i.e. human resources. In the D condition subjects
were interrupted by the supervisor with questions about adifferent topic not related to the context of humanresources. These interruptions were on random topics, suchas the upcoming company party (e.g. “How many hot dogs
do we need for 240 employees?”). These types of random
interruptions were designed to simulate the types ofinterruptions one might expect in real office work. Pilot
studies confirmed that questions in the S and D conditions
were judged by subjects to be same and different contexts,
respectively, to the human resource scheme.
Subjects were instructed to attend to interruptions
immediately, i.e. to pick up the telephone or attend to the
IM window. Interruption frequency was set to two minutes,
based on observations from [6] and the pilot experiments.
During the experiment, the experimenter adjusted the lengthof time for interruptions to try to make the times as equal as
possible across conditions.
Dependent variables: Our primary variable of interest was
the total time to perform the task. The total time needed tocomplete each block of emails and the time spent oninterruptions were manually recorded. The time to performthe task was computed as [total time to perform task – timespent on interruptions]. If the time to perform the task was
higher with an interruption, then this could indicate thatextra time was needed to perform the task after aninterruption. We expected less politeness and more errors inemail messages that were disrupted. A politeness metric
was computed by assigning points for the use of standard
greeting/closing phrases and polite words (e.g. Dear Mr.;
sincerely yours, please, thank you). Errors were measured
as spelling errors, typos or others (e.g. misspelled names).
Subjective Workload was measured by a modified NASA
Task Load Index (TLX) [7], used by [1]. We added a stressmeasure to the six given rating scales: mental and physicaldemands, performance, and temporal demand, which wechanged to time pressure, effort, and frustration. Subjects
rated these factors on the standard NASA 20-point scale.
Personality measures. ‘Openness to experience’ wasmeasured as part of the NEO Personality Inventory Revisedusing the Openness to Actions subscale of the Germantranslation [11] since these items best fit our topic. Ten
items of the Personal Need for Structure (PNS) subscalefrom the Need for Cognitive Closure/Personal Need for
Structure inventory were used [2], (e.g. “I do not like it at
all to change my plans at the last minute.”).
Procedure. The experiment was conducted at a university
lab and took about 1! hours. Subjects were randomly
assigned to media type and to the interruption order (thetreatments were counterbalanced with six permutations).
Subjects first filled out a questionnaire to obtain personality
measure scores and demographic and computer experienceinformation. Subjects then performed the task for eachinterruption context. After completing each block of emails,
subjects assessed the workload measures in a questionnaire.
RESULTSOur first research question was whether the context of theinterruption matters. We performed repeated measures
analyses with media type as a between-subjects factor.
Means are shown in Table 1. For Time to Perform Task
there was a significant difference between interruption
types (F(2,77.98) =3.36, p<.05). Surprisingly, paired
contrasts showed that subjects took the longest time in thebaseline condition to perform the task (B vs. S:
F(1,46=4.22), p<.05; B vs. D: F(1,46=4.13), p<.05). There
was no significant difference between S and D contexts.

Baseline (nointerruption)Same
context
interruption
Different
context

Time toperformtask*(minutes)

Avg.
numbererrors inemailsPolitenessof emailmessages

1.94
(.91)
1.93
(.88)

Length ofemailmessage*(avg. #
words)
31.49
(8.1)
29.17
(7.02)

22.77(7.60)
20.31(5.94)
20.60(4.93)

1.84
(.92)

30.16
(7.18)

28.90(6.30)

28.98(5.37)
28.69(5.89)

Table 1. Mean measures of task performance (s.d.). *=p<.05.

There was no significant difference of media type, i.e.
whether subjects were interrupted by telephone or IM(F(1,92)=.20, p<.66). There was no significant interactionof media type and interruption type on time to perform task.
We found there was no significant difference in the numberof errors that were made across interruption types(F(2,92)=1.70, p<.19). We compared our politeness metricand found no significant difference across conditions(F(2,92)=.10, p<.91). For both variables, we found nointeraction with media type.
It was possible that the reason that it took longer to do thetask in the uninterrupted condition is because people wrote
more. We examined the length of the email messages acrossconditions. A repeated measures analysis on the average
number of words per email (Table 1) showed that there wasa significant difference among conditions (F(2,92)=3.34,
p<.04). Email messages were longest in the B condition,with no interruptions (B vs. S: F(1,46=5.57), p<.05; B vs.
D: F(1,46=2.20), p<.15). There was no significant
interaction of media type with number of words.

ß

t

p

Openness to experience

-.363

-2.22

.03

Need for personal structure

-.346

-2.13

.04

Table 2. Regression coefficients for personality measures.

As a control, we checked whether the actual time spent oninterruptions was different in the same or different contexts
as longer interruptions could introduce a higher disruption
cost. We found no significant difference in interruption
length (difference=.62 min, sd=2.8), t(47)=1.52, p<.14).
Personality variables. We next examined to what extent themeasures of openness to experience, and need for personal
structure are predictive of the amount of time one needs tocomplete a task that is constantly interrupted. Our primaryvariable of interest was disruption cost and since there wasno difference in time to complete the task between
same/different interruption contexts, we combined the times
for these conditions to form a single dependent measure(time to complete the task - time spent on interruptions). A
stepwise regression analysis using the personality measures
as predictors showed that both ‘openness to actions and‘need for personal structure’ are significant predictors of thetime to complete an interrupted task (F(2,47)=3.41, p<.04),
2
R =.14). There is an inverse relationship: the higher one
scores on ‘openness to experience’ and ‘need for personal
structure’, the quicker it takes to complete an interrupted
task (Table 2).
Mentalworkload*
Baseline (no 10.02
interruption) (3.90)
Same context 10.83
interruption (3.96)
Different
11.50
context(3.55)

Stress**6.92(3.85)
9.46(3.97)
9.13(4.10)

Frustration**
4.73(2.93)
6.63(4.19)
6.48(4.45)

Timepressure**
11.02(4.57)
12.69(4.45)
12.17(4.26)

Effort**9.50(3.38)
11.04(3.78)
11.52(3.31)

Table 3. Mean (s.d.) workload measures across interruption
types. Scale is 1(low)-20 (high), *=p<.05, **p<.01.

Measures of workload. We tested the difference of theNASA mental workload measures (Table 3) acrossinterruption type. A repeated measures analysis showed asignificant difference (F(2,92)=3.82, p<.03). Workload washighest for the D context condition (D vs. B: F(1,46=7.38),
p<.01; D vs. S: F(1,46=2.09), p<.16). We also found thatstress was rated as significantly different across interruption
type (F(2,92)=12.15, p<.001) and was highest for bothinterruption conditions (S vs. B: F(1,46=20.32), p<.001; D
vs. B: F(1,46=14.94), p<.001). Level of frustration was alsosignificantly different across interruption types (F(2,92)5.21, p<.007), and highest in the interruption conditions (Svs. B: F(1,46=7.88), p<.01; D vs. B: F(1,46=7.55), p<.01).
Time pressure was also rated significantly different acrossinterruption types (F(2,92)=4.71, p<.01), with highest timepressure rated in the interruption conditions (S vs. B:
F(1,46=10.65), p<.01; D vs. B: F(1,46=3.65), p<.10). The
amount of effort invested in the task was also significantly
different across interruption types (F(2,79)=8.50, p<.001),
with most effort reported in the interruption conditions (Svs. B: F(1,46=6.92), p<.05; D vs. B: F(1,46=14.60),
p<.001). There was no interaction with media type in any ofthese measures.

DISCUSSION AND CONCLUSIONS

Our results showed that any interruption introduces achange in work pattern and is not related to context per se.
Our results differ from [5] who found similarity ofcognitive processes of interruptions to a task were
disruptive. We looked instead at similarity of the content ofinterruptions and a task. Also, [4] found that interruptions
extremely consistent with the task were facilitating. Ourinterruption context shared the same topic as the main(email) task but unlike [4] the operations and details
differed. Together, our study along with [10], who report
participants’ subjective views, show that interruptions thatshare a context with the main task may be perceived as
being beneficial but the actual disruption cost is the same aswith a different context.
Surprisingly our results show that interrupted work is
performed faster. We offer an interpretation. When people
are constantly interrupted, they develop a mode of working
faster (and writing less) to compensate for the time theyknow they will lose by being interrupted. Yet working
faster with interruptions has its cost: people in theinterrupted conditions experienced a higher workload, morestress, higher frustration, more time pressure, and effort. So
interrupted work may be done faster, but at a price.
Our results suggest that interruptions lead people to change
not only work rhythms but also strategies and mental states.
Another possibility is that interruptions do in fact lengthen
the time to perform a task but that this extra time only
occurs directly after the interruption when reorienting backto the task, and it can be compensated for by a faster andmore stressful working style. More sophisticatedmeasurements of working speed directly after aninterruption must be done to test this. We found that themore open one is to experiences, the quicker one handledinterrupted work and surprisingly, we found the same
relation for those who score high on needing personal
structure. Perhaps those who need personal structure are
better able to manage their time when interrupted.
While laboratory studies are always subject to criticism of
ecological validity, our task design was based on real
fieldwork. We simulated office conditions using an email
task, which is different from many laboratory studies ofattention switching that use abstract tasks. The labenvironment enabled us to isolate variables of interest.
Our results have implications for system design. A certain
amount of interruptions may be tolerable because people
can compensate with a higher working speed. However,technology could be used to keep track of and control
interruptions over a long period of time so as not tooverload people (as our mental workload measuressuggest). After only 20 minutes of interrupted performancepeople reported significantly higher stress, frustration,
workload, effort, and pressure. We cannot say whether

people would cope over time or if these measures would
only increase. Our results confirm experimentally the
anecdotal reports of informants in field studies who
describe high stress when interrupted in real work situations[10]. Our data also contributed to finding individual
differences in interruptions. Our personality measuressuggest the need for customization for systems to fit
people’s preferred interruption tolerance. We hope that ourstudy will spark continued interest in this area.
REFERENCES

1. Adamczyk P. D. & Bailey B. P. If not now, when? The
effects of interruption at different moments within task
execution. Proceedings of CHI’04, (2004), 271-278.
2. Collani, G. Eine deutsche Skala zum Konstrukt
BedürfnisnachkognitiverGeschlossenheit(NFCC)/Persönliches Strukturbedürfnis (PNS). In A.
Glöckner-Rist(Ed.),ZUMA-Informationssystem.
Mannheim: Zentrum für Umfragen, Methoden und
Analysen (2004).
3. Czerwinski, M., Horvitz, E., and Wilhite, S. A diarystudy of task switching and interruptions. Proceedings of
CHI'04, (2004), 175-182.
4. Czerwinski, M., Cutrell, E. and Horvitz, E., Instantmessaging: Effects of relevance and timing. Proc. of
HCI’00, British Computer Society (2000), 71-76.
5. Gillie, T. & Broadbent, D. What makes interruptions
disruptive? A study of length, similarity and complexity.
Psych Research, 50, (1989), 243–250.
6. Gonzáles, V. & Mark, G. Constant, constant, multitasking craziness: managing multiple working spheres.
Proceedings of CHI ‘04, (2004), 113-120.
7. Hart, S. G., & Staveland, L. E. Development of a multidimensional workload rating scale: Results of empiricaland theoretical research. In P. A. Hancock & N. Meshkati(Eds.), Human mental workload, Amsterdam, The
Netherlands: Elsevier, (1988), 139-183.
8. Hudson, J.M., Christensen, J., Kellogg, W.A. andErickson, T. “I’d be overwhelmed, but it’s just one morething to do:” Availability and interruption in research
management. Proc. of CHI 2002, (2002), 97-104.
9. Iqbal, S.T. and E. Horvitz, Disruption and recovery ofcomputing tasks: Field study, analysis, and directions,
Proceedings of CHI 2007, 677-686.
10. Mark, G., Gonzalez, V., and Harris, J. No Task Left
Behind? Examining the Nature of Fragmented Work.
Proceedings of CHI’05, (2005), 113-120.
11. Ostendorf,
F&
Angleitner,
A.
NEOPersönlichkeitsinventar nach Costa und McCrae,
Revidierte Fassung (NEO-PI-R). Manual. Göttingen:
Hogrefe, (2003).