Effects of Email Addiction and Interruptions on Employees
Purpose: The aim of the research is to explore the effect of email interruptions on tasks, and the concept of
email addiction within the workplace.
Design/ methodology/ approach: Data was collected from a large car rental company in the UK. The first
collection method involved observing the effects of simulated email interruptions on seven employees by
measuring the interrupt handling time, the interrupt recovery time, and the additional time required to
complete the task given the number of interruptions. The second part of the study involved a questionnaire
sent to 100 employees to capture addictive characteristics in employees’ email communication behaviour.
Findings: Email interruptions have a negative time impact upon employees and show that both interrupt
handling and recovery time exists. A typical task takes one third longer than undertaking a task with no email
interruptions. The questionnaire data shows clinical characteristics classify 12% of email addicts, and
behavioural characteristics classify 15% of email addicts in the workplace.
Research limitations/implications: Observation was constrained by the timeframes and availability of the
participating organisation. Measuring an employee receiving email interruptions over a greater time period
might achieve a more comprehensive understanding of the impact.
Originality/Value: The small study is the first to determine the impact of email interruptions on work tasks
by observing employees, and a method to determine email addiction. By understanding these factors,
organisations can manage workflow strategies to improve employee efficiency and effectiveness.
Keywords: email addiction; email handing; email recovery time; managing email communications; task
Paper type: Research paper
Computer mediated communication systems can often create as many problems for an organisation as they
solve. The volume and pace of information can become overwhelming, especially since messages are not
necessarily sequential and multiple topic threads are common, resulting in amongst other factors, information
overload (Hiltz, et al., 1985; Kerr & Hiltz, 1982). As defined by Bawden 2001 (in Bawden, 2001): “Information
overload occurs when information received becomes a hindrance rather than a help when the information is
potentially useful”. It is tempting to assume that the major contributing factor in the workplace is ‘too much
information’ (Bawden, 1999), and some believe that too much information is likely to be better than not
enough (Tjaden, 2007). In an increasingly connected global economy, it’s true that we depend on
information, in varied media, to stay current and make decisions. However, the growing pressures to
consume more and more information and to work faster and better than ever before has repercussions. What
is interesting is that information overload is often, at least partially, self induced (Wojcik, 2005). Hallowell
identifies the negative neurological effects of information overload, describing it as Attention Deficit Trait
(ADT), “[ADT is] caused by brain overload (Hallowell, 2005). ADT is now epidemic in organisations. The
core symptoms are distractibility, inner frenzy, and impatience. People with ADT have difficulty staying
organised, setting priorities, and managing time”.
Organisations make concerted efforts to introduce all possible means of improving and maintaining high
work performance levels, on the assumption that deterioration of individual capabilities at work will damage
organisational performance (Mano & Mesch, 2010). Every method of communication has its place but, email
has proved itself to be a strong contender in many situations, especially in business (Bawden, 2001). Email
allows for a number of organisational benefits, including the ability to create timely information and
information permanency, as well as increasing information accuracy and colleague interaction (O’Kane &
Hargie 2007). Email has even been attributed to the success of just-in-time knowledge, and knowledge
integration within everyday work practices (Lichtenstein & Swatman 2003; Fallows 2002). It is the
capability to quickly and easily distribute a message with an attachment such as documents, links, objects,
etc. – to a large dispersed audience, with tracking and audit, which cannot be matched by any other
communication technology to date (Anthes 2006; Brown 2007) and is vital to accessibility, quantity, and
quality of information.
Empirical data shows that although email was originally designed as a communications application it is now
being used for additional functions that it was not designed for, such as task management and personal
archiving (Whittaker & Sidner, 1996; Rennie, 2000). Some individuals experience major problems in reading
and replying to email in a timely manner, and suffer from back logs of unanswered email and finding
information (Whittaker & Sidner, 1996). The challenge in the workplace is that managing email is now a
standard requirement and principal part of worker’s day-to-day tasks (Brown 2007). Email increases the
number of tasks that employees perform and, as a consequence, their level of control over those tasks. As
stated by Zelikovich (2011) not only does email require more attention, subsequently causing larger costs, it
also in some cases implicitly imposes administration costs on employees because of the need to handle so
much more information. Studies now suggest that email may be hindering rather than helping workplace
performance (Mano & Mesch, 2010).
Burgess, Jackson & Edwards recognised that email interruptions could be causing some of these email
problems, where interruptions lead to time inefficiencies and employees become distracted and forced to stop
their planned work (Burgess et al., 2005). Furthermore Stafford suggests that the volume of email has led to
some users to become addicted to email (in Hair et al., 2007). He suggests that the fundamental learning
mechanisms that drive gambling addicts can be associated with email users, suggesting that the variable
interval reinforcement schedule is in play. Thus, rather than reward an action every time it is performed, it is
rewarded only sometimes. Stafford advocates that this is enough to make it difficult for users to resist
checking email. Consequently, problems of email use have become more inherent among users. A
ClearContext survey found that 56% of people spent more than two hours a day in their inbox, and 38% of
respondents received more than 100 emails a day (Anderson, 2008). Hair, Renaud & Ramsay found that 34%
of information workers felt stressed by the volume of emails, 50% checked their email every hour and 35%
checked their email every fifteen minutes (Hair et al., 2007). They identified one in three workers as suffering
from email stress.
This paper builds on Jackson et al.’s research surrounding interrupt recovery time and investigates the
association of email interruptions and work performance, in particular identifying occurrence, handling,
additional time taken to complete a task, interrupt read and response times, and recovery time of email
interruptions (Jackson et al., 2002). It also identifies the characteristics that classify an email addict from both
clinical and behavioural perspectives. The paper starts by looking at the research into the effects on task
interruption and email employee behaviour. It then outlines the methods used to look at both the effects of
email interrupts and the measuring of email addiction. The results and discussion form the next section of the
paper and it finishes with a conclusion and limitations of the research.
2. The known effects of task interruption and email addiction
Back in 2002, Jackson, Dawson and Wilson evaluated the effect of email interruptions within the workplace
(Jackson et al., 2002). Similarly to Solingen et al. they compared email to another medium of interrupt, the
telephone (Solingen et al., 1998). Solingen et al. claim that interruptions have three phases: occurrence,
handling and recovery (Solingen et al., 1998). More concisely an interruption can be defined as “any
distraction that makes a [person] stop their planned activity to respond to the interrupt’s initiator”. In
comparing the two, Jackson et al. found that 70% of emails dealt with were viewed within six seconds,
which was faster than letting the telephone ring three times (Jackson et al., 2002). Czerwinski et al. adopted
diary studies as a method of analysing the effect of interruptions in information workers (Czerwinski, 2004).
Furthermore she found that email took up 23% of the users’ day, and it was found to be the most popular task
and a common cause for task switching.
However, the interesting discovery in Jackson’s work is that instead of delaying the response time which is
more convenient to the user, the user reacted almost instantly within six seconds. In addition, they suggest by
example, that if it takes on average one and a half minutes to read and recover from an email and the
employee is interrupted every five minutes, then an employee could have up to ninety-six interruptions in a
normal eight hour working day. Jackson et al. also identified that the recovery time from an email
interruption is sixty-four seconds; this is also significantly less than published recovery times of a telephone
call, which is 15 minutes (DeMarco & Lister, 1999). This research detailed in this paper proposed a new set of
questions regarding how people manage email interrupts and the effect it has on their work. Jackson et al.
identifies the issue but does not develop discussion on an individual’s perspective of work, email, or consider
the culture that surrounds the urgency of dealing with emails straightaway and invoking multitasking, as
opposed to waiting until one has finished their original task.
What is unclear from the research to date is the effect of email multitasking on employees. Whilst
multitasking is shorthand for the human attempt to do simultaneously as many things as possible and as
quickly as possible (Rosen, 2008), how the human brain deals with memory and thought processes is crucial
in understanding the motions of human behaviour and its interaction with technology. Zull developed
memory as a situation of time, “part of having a good memory is to recall things long after they happened but
there is also value in remembering things for only a short time and forgetting after solving the problem”
(Zull, 2002). It has been argued that we process items intently in working memory for up to forty-five
minutes before becoming fatigued (Sternberg, 2006). In contrast, Russell suggests the short term memory time
span in adults varies between ten and twenty minutes (Russell, 1979). The short term memory temporarily
stores information, but how do we forget information in short term memory. Several theories have been
proposed as to why we forget information, the most well known is the interference theory and decay theory.
According to the interference theory the recall of certain words interferes with the recall of other words.
Conversely, the decay theory asserts that information is forgotten because of the gradual disappearance,
rather than displacement of the memory trace (Sternberg, 2006). On the contrary, it is argued that information
is processed one chunk after another. Parallel processing asserts that the brain seems to handle many
operations and processes information from many sources simultaneously. This theory is supported by the fact
that humans can in fact multitask.
Multitasking is now expected, if not presumed normal, for workplace employees. Before technology was
incorporated in workplace activities, theorists (Meyer, 1997; Kieras, 2000; Lauber, 1995) identified the costs
of multitasking when the brain actively attempts to deal with task switching. In their article Meyer et al.
found that slower responses occurred during task switching in comparison to repeated performance of a
single task (Meyer, 1997). When considering all the data of early experiments into task switching, laboratory
settings are used and found to be most congenial. The everyday or real world approach calls for more
correspondence to engage the ‘whole host of executive mental processes that people presumably have’
(Sternberg, 2006; Kieras, 2000). Whilst studies show email interruptions within the workplace lead to poor
time management and less efficiency in employees (e.g. Burgess et al., 2005), this study is concerned with the
additional time required to complete a workplace task after being interrupted by email. Even though the
principle of email management has been cause for concern since email was created, the effect of email on
human behaviour has only recently been recognised as an urgent call for concern.
The literature indicates there is a problem with email communication in the workplace. Whilst employees are
expected to manage their daily tasks, email interruptions promote a new way of dealing with information.
Firstly in terms of time lost recovering from email interruptions, and secondly in terms of behaviour.
Building on the research into responding to email and interrupt recovery times, this research studies the
effect of five minute email interruptions on employees in the workplace, and tests the seven year old research
findings of Jackson et al. (2003).
Hypothesis 1: Simulated five minute email interruptions will cause an interrupt handling time of around 1.5
minutes and a recovery time of around 64 seconds.
The second part of the research involves determining the behavioural aspects of dealing with email.
In recent years there has been limited research into the correlation between the fundamental learning
mechanisms that drive addicts and email users. In conjunction with Beta Research, AOL conducted an
independent online survey in 2008 of 4,000 e-mail users in the top-20 U.S markets. Almost half, 46%, of
email users claim to be addicted to email (Begun, 2008). This concept is now commonly referred to as
“email addiction” (Anderson, 2008). In this instance addiction can be defined as an (in Maas, 2008): “activity
that takes over one’s life... instead of being an enjoyable addition to their routine, it becomes a way to
manage anxiety, stress, loneliness and depression that one feels or that which interferes with daily
responsibilities”. The increase in self-diagnosed addiction however is in need of professional psychological
diagnostics in order to add clinical justification to the level of addiction that email use causes.
The concept of addiction itself has been criticised both within and outside the mental health disciplines on a
number of grounds: often it is used without an attempt to define it; it has moralistic connotations which are
inappropriate to scientific inquiry; it represents a way of understanding people, behaviour and the mind that
is incompatible with a scientific approach (Goodman, 1990). It is unsurprising therefore that over the last
twenty years there have been much development of The Diagnostic and Statistical Manual of Mental
Disorders (DSM) to serve as a guide for organising the components and definition of addiction (unrestricted
by reference to a particular behaviour) (American Psychiatric Association, 2000).
Whilst the literature lacks psychologists’ forthcomings in the area of addiction and email use, the
repercussions of Internet addiction have been widely raised, and merits for classification as a new psychiatric
disorder in its own right (Young, 1996; Beard & Wolf, 2001; Yellowlees & Marks, 2005). Internet addiction,
first indicated by Young, found that some on-line users were becoming addicted to the Internet in much the
same way that others become addicted to drugs or alcohol (Young, 1996). This clinical study based on similar
questions to that used by DSM-IV (first published by American Psychiatric Association, 1993) for
pathological gambling, used a questionnaire to test Internet addiction. Respondents who answered ‘yes’ to
five or more, from eight adapted questions, were classified as addicted Internet users or as normal Internet
users. Participants in this study either voluntarily participated using an online questionnaire or Young directly
asked questions using telephone interviews (Young, 1996). Young hypothesised that meeting five out of eight
rather than five out of ten criteria, from the original DSM-IV questionnaire, had a more rigorous cut off score
to differentiate normal from addictive usage. Despite differences within the criteria analysis, Young’s results
suggest significant clinical addiction to the Internet, with 396 dependent Internet users and a control group of
100 non-dependent Internet users being identified (Young, 1996).
In a recent article Anderson (2008) interviewed Dr Tom Stafford from the University of Sheffield who
believes, in a much different study to Young (1996) yet yielded similar results, that the fundamental learning
mechanisms that drive gambling addicts can be associated with email users. Interestingly, and unlike any
other literature on the topic, he claims that the ‘variable interval reinforcement schedule’ is in play. Users
sometimes check emails and there is nothing interesting, other times they might get something interesting or
wonderful. Stafford argues that this is enough to make it difficult for users to resist checking email, even
when they’ve only just looked. This opinion based article highlights a comparison between addiction and
emails that would not usually be associated, although it provides little valid evidence to support the
conclusions. Whilst the literature lacks the input of psychologists, independent coaches are coming forth
with criteria to examine email use and levels of email addiction, such as Egan (2008). In addition, McKinney
(2000) an academic coach, argues the basic premise is that our email addictions prevent conscious time
management choices. Egan and McKinney raise very similar issues in behavioural characteristics of email
addicts (Egan, 2008; McKinney, 2000). However, both provide little statistical or quantitative research or
testing in the subject area to provide support for their characterisation and labelling. This does not suggest
their work is a mere fallacy, in contrast it takes the concept in a new direction, making for further research
and assessment into email addiction.
The area of email addiction is growing in the research literature, but little classification has been formed. The
use of Young’s (1996) clinical addiction criteria and, Egan (2008) and McKinney’s (2000) behavioural
addiction criteria, as a method for assessing email addiction, takes the literature a step further in clarifying
email addiction characteristics in the workplace. Comparison of the two criteria described in the preceding
section led to the second hypothesis:
Hypothesis 2: Email addiction will exist in the workplace in line with literature findings of at least 15% of
respondents classified as email addicts. Criteria evaluation of clinical characteristics will occur consistent
with behavioural characteristics, thus responses within Criteria 1 will occur consistent with Criteria 2.
The study collected data from a large international car rental company with corporate-level Head office and
business-level Branch operations in the UK. The company selected for the study was opportunistic, as one of
the authors had experience of working there. There were two elements to this research. The first involved
observing the effects of simulated email interruptions on seven employees by measuring the interrupt
handling time, the interrupt recovery time, and the additional time required to complete the task given the
number of interruptions. The employees were all of managerial status (i.e. branch manager or assistant
manager). The day-to-day tasks of the managers involve communicating to customers and third parties
(following up complaints, recovering monies, setting up new contacts) and communicating to staff and upper
management (training, appraisals, meetings, audits). The seven participants ranged between the ages of 23-
35 and they all had university degrees.
The second part of the study involved a questionnaire to capture addictive characteristics in employees’
email communication behaviour. The questionnaire elicited “self-report” addiction criteria which are
reported elsewhere (Young, 1996; Egan, 2008; McKinney, 2008). The questionnaire was disseminated to 100
employees. All participants frequently used email in the workplace, of which 74 completed the questionnaire
anonymously. It was considered that examining email use can affect a person’s emotional state (Ovisiankina
1928, Mandler, 1964 and 1984) therefore dimensions such as age, gender or race were omitted to avoid
anxiety or hesitation for all parts of the study.
3.1 Email Interrupts Experiment
To determine the impact of email interrupts on the seven employees, they were asked to undertake their
normal job of completing callbacks. A standard daily task completed by all company branches, where all
employees are trained to the same standard. The callback process involves calling and speaking with the
customer and/or garage, retrieve updates and process them onto two computer systems. Each item from the
callback was calculated on a per person basis for consensus in scoring. Each experiment consisted of two
callback tasks. Task 1 was to count and complete as many callbacks in fifteen minutes, documenting results
on the experiment handout. Task 2 was to complete the same number of callbacks as completed in Task 1,
but this time the employee would be interrupted every five minutes by email that required an urgent reply.
All email interrupts were 100 words in length, reflective of the workplace environment, and participants
were made aware that each email was fictional and did not represent the company. Email interruptions were
sent to participants until completion of Task 2. On completion of Task 2 all replies to the fictional emails
Each observation was conducted in a quiet, well-illuminated area of the office that contained two desks with
computers on each. Participants sat out of sight of the observer, but the results of the study need to take into
account the Hawthorne Effect as the behaviour of participants is likely to alter when observed (Swetnam,
3.2 Email Addict Questionnaire
It was considered that examining email use can affect a person’s emotional state thus the reported effects of
email are subject to some bias (Ovsiankina, 1928). The term ‘addiction’ was perceived to be of a personal
nature, therefore to avoid any further anxiety or hesitation, the questionnaire was titled ‘Evaluation of Email
Usage Questionnaire’. For point of clarity, unlike previous research conducted, the questionnaire was not
used to determine the frequency of email usage or any other conceptualisations. The purpose of this study
was only to address the characteristics of email addiction. Each participant was administered with a sixteen
item check box of “yes-no” and “most often-least often” questions that most represented their typical work
and email account behaviour.
Respondents were asked to indicate the extent to which they “...meet or exceed the criteria of an ‘email
addict”. Email addiction was measured using two criteria, clinical characteristics (criteria 1) and behavioural
characteristics (criteria 2). Clinical characteristics (criteria 1) were based on the original study of DSM-IV
for pathological gambling and later developed by Young to assess clinical addiction characteristics of
Internet use (Young, 1996). The Diagnostic Questionnaire (DQ) contained an eight-item classification list.
Key terms of each question were replaced with ‘email’, ‘email use’ or ‘email account’ as necessary. A
nominal scale of ‘Yes’ responses indicated addiction, and ‘No’ responses indicated normal behaviour.
Behavioural characteristics (criteria 2) were based on email addiction symptoms from guidance councillors
and life coaches, Egan and McKinney, whom offer support for email addicted individuals (Egan, 2008;
McKinney, 2000). The questions were chosen systematically by the common themes that were raised from
both authors given first priority and then other symptoms were selected based on relevance in workplace
environments. Items were measured by Likert scales. In order to encourage response rates, hard copies of the
questionnaire were administered in green paper. Green paper has been found on average to aggregate an
increase of 2% when using questionnaires, whilst another reported a 9.1% difference from white to green
paper (Pucel et al., 1971).
4. Results and Discussion
As mentioned in the methodology section the email interrupt study involved seven employees from a large
international car rental company and involved two tasks. Task 1 was to complete as many callbacks in fifteen
minutes, and Task 2 was to complete the same number of callbacks with five minute email interruptions.
Hypothesis 1 assumed that stimulated five minute email interruptions will cause an interrupt handling time of
around 1.5 minutes and a recovery time of around 64 seconds. The evidence from this study supported this
Hypothesis. Jackson et al.’s findings on interrupt recovery time calculated 64 seconds, the results in this
study yield a similar average recovery time of 68 seconds (Jackson et al., 2002). Subsequently where Jackson
et al. reports an interruption handling time of 90 seconds, these results indicate a slighter longer handling
time of 116.5 seconds. On the basis of this study alone, it is difficult to be certain about the factors that
contribute to the existence of the additional recovery time. As discussed earlier, time is lost dealing with an
email interruption, and then further time is lost resuming previous activities. Research by Zull indicates that
the brain needs time to empty the memory space to get back to the task at hand (Zull, 2002). However, the
interference theory suggests the interruption causes a displacement of the memory trace, and in this case the
interrupt recovery time is the brain seeking to find that memory trace again. The results of this research
support the idea an additional recovery time exists, but it was not possible to definitively conclude on the
brains functioning during this time.
The results from this study indicate that five minute email interruptions cause a task to take one third longer
than completing a task without email interruptions. The results show that, similarly to Solingen et al., the
negative aspects are more prominent than that of any positive interrupt effects on employees (Solingen et al.,
1998). During the study, there were signs that the interrupt disturbed concentration where a recovery time
existed, and it caused task delay where additional handling time was present. Due to the number of
participants it is difficult to be certain about the factors that contribute to the additional time, but it can be
concluded that email interruptions cause a negative impact on employees. It is recommended employees
adopt a “think before you check” and “think before you write” attitude in dealing with email to become
aware of the issues surrounding email interruptions.
4.1 Email Addiction
The email addiction questionnaire was administered to a large international car rental company, where a total
of 74 employees responded. The questionnaire was split between two criteria, the first based on Young’s
Diagnostic Questionnaire, and the second compiled from Egan and McKinney life coaches on email
addiction (Young, 1996; Egan, 2008; McKinney, 2008).
The data from the questionnaire was analysed by first determining the general average of addiction
characteristics, followed by frequency distributions to quantify the responses from both criteria. The
questionnaire yielded two relations, either an email addict or not an email addict. The study adopted a similar
evaluation criteria framework to that of Young’s study (Young, 1996). Therefore any five questions
responded to with a ‘Yes’ in Criteria 1, or ‘Most Often’ within Criteria 2, identifies the participant as an
email addict. To distinguish the criteria an email addict is identified by both clinical and behavioural
characteristics in isolation. Therefore, a participant could conceivably have normal subscale scores in the
first criteria while still responding as an addict to a number of items within the other criteria. In addition, the
data was analysed using a Pearson correlation co-efficient to examine any significance between clinical
characteristics (Criteria 1) and behavioural characteristics (Criteria 2).
Hypothesis 2 assumed email addiction will exist in the workplace in line with literature findings of at least
15% of respondents classified as email addicts. In addition, the criteria evaluation of clinical characteristics
will occur consistent with behavioural characteristics, thus responses within Criteria 1 will be consistent with
Criteria 2. The results of this study yield a very different view of the level of email addiction in the
workplace, where the findings in this study indicate, based on clinical characteristics, only 12.2% of users
were email addicts, and 15% of users were classified from the behavioural characteristics. AOL and Beta
Research found evidence in 2007 showing 15% of users and in a similar study in 2008, 48% of users were
email addicts (Begun, 2008). The participants in this survey only partially supported Hypothesis two, which
may have been caused by the rigorous cut off score to differentiate normal from addictive use. An
implication of this would be is if the criteria evaluation was marked lower, therefore four out of eight criteria
indicated email addiction, the results would have doubled in the number of email addicted responses.
Consequently the correlation analysis shows no statistical significant relationship exists between Criteria 1
and Criteria 2. Taken together, these results suggest that whilst a relationship cannot be found to exist in this
study, in future where a wider scale use of the questionnaire is implemented a relationship between the two
criteria may be found. In light of these results, it is necessary to include both criteria in classifying email
addiction. Table 1 shows the characteristics that can aid in classifying email addiction.
Insert - Table 1: Characteristics of an Email Addict
It can be concluded that both clinical and behavioural characteristics are necessary in classifying email
addiction. If employees become aware of their behaviour, ultimately it will reduce habitual inclinations and
bring greater effectiveness to email addiction.
5. Conclusion and Recommendations
The results from this study highlight the many problems that are often associated with email use within
organisations. In particular, this study explored email interruptions and email addiction in the workplace. The
effect of an email interrupt becomes greater the more email is received and in this study five minute email
interruptions caused an average handling time of 116.5 seconds, and recovery time of 68 seconds. Receiving
email on an exponential rate becomes harder to manage and prioritise, so the interruptions lead to negative
effects on employees. This was shown in the study findings where email interruptions caused a task to take a
third longer, because it disturbed the employee’s concentration and employees were generally seen to be less
effective. Additionally, this study showed that the concept of email addiction exists in the workplace, where
clinical characteristics classified at 12% and behavioural characteristics classified at 15% of email addicts.
This research has shown the value in quantifying email addiction characteristics and measuring the level of
addiction within an organisation. The correlation analysis has shown that there is no statistically significant
relationship between clinical and behavioural characteristics. This has led to the need for both characteristics
to be used in classifying email addiction.
Whilst a single study cannot provide a sound basis for the practice of email management, similar studies
have suggested recommendations for employees and employers in the workplace to manage email
interruptions and minimise email addiction. Burgess, Jackson & Edwards found evidence that educating
employees through email training significantly reduced email interruptions and improved the way people
write emails. It is recommended that employees ‘think before they write’ and ask themselves, “Is this email
necessary? If so, is the email easy to read and straight to the point? Does it tell what is expected of the
recipient? Does it state what and when action is required?” (Burgess et al., 2002). It is vital for employers to
convey this and could setup email training as part of their initial introduction or on-going personal
development for all employees.
An understanding of addictive disorders has important connotations for treatment, in that optimal treatment
would require that both positive and negative reinforcement processes be addressed (Goodman, 1990). An
employee with addictive tendencies towards email could show a remarkable improvement by simply being
aware of their problem behaviour or habitual inclination. For example, if an employee is consistently
checking email on an hourly basis (or less) or leaves email open between sessions then they may find an
email schedule useful to control their behaviour and manage their time more efficiently (McCorry, 2005).
The steps to create an email schedule are shown in Table 2. It is important to note these are suggested in light
of the characteristics of email addiction as part of this study, further research is required to test these
techniques and its application.
Insert - Table 2: Steps to adopt an Email Schedule
Although this research has shown both that email interruptions and addiction exists, it is acknowledged that
there are limitations with the research. The study was constrained by the timeframes and availability of the
participating organisation when administering the experiments. Ideally measuring an employee receiving
email interruptions over a greater time period would achieve a more comprehensive understanding of how
the initial impact of the interrupt is sustained, therefore the interrupt recovery time might be longer or shorter
in a one-hour experiment. The most important limitation lies with the questionnaire. Although it was
designed to capture email addiction characteristics within an organisational workplace, the evaluation criteria
have not been used before. The scale used does provide a workable measure of email addiction, but further
research is required to determine its construct validity and clinical utility. However, this research has shown
that email interruptions do cause a negative impact on employees’ time, and email can cause addictive
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