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Case 1 Assignment1
Link added for Coping with info—- if it’s not open
Module 1 – Case:
THE RESEARCH PROCESS AND ITS COMPONENTS
Assignment Overview
Please read the following research paper (available in Trident’s e-library):
Soucek, R., and Moser, K. (2010)
Coping with information overload in email communication
: Evaluation of a training intervention. Computers in Human Behavior, 26, 1458–1466.
Case Assignment
Based on the above information, write a paper addressing the following issues:
1. What are the key research questions in this study? Summarize the key findings in this paper.
2. Do the study hypotheses rely on a theory or theories? If so, discuss one of these theories and explain how the theory has led to one of the hypotheses.
3. Discuss levels of measurement of the key variables in this study.
4. Discuss the study design.
5. Discuss potential biases in this study, measurement errors, and validity issues.
6. Are causality arguments appropriate in this study?
7. What is your overall evaluation of the quality and effectiveness of this study? Provide criticism on the study design, and suggest possible ways to tackle such issues in future research.
Please organize your paper in a scholarly way. Add section titles when necessary. Explain your logic, and when appropriate, use external sources with proper citations. Conclude your report with a paragraph or so evaluating the entire exercise in terms of what you have learned and your reflections on the topic.
The paper is usually between 5 and 12 pages long.
Assignment Expectations
1. Student understands the key research questions in this paper.
2. Student identifies research elements in a paper, including hypotheses, theory, types of variables, and levels of measurement.
3. Student answers the questions with clarity, depth, and critical thinking.
4. Completeness and coherence: Chain of thought is easy to follow.
5. Student uses relevant evidence and additional papers/resources to support the propositions.
6. Paper is clearly written with appropriate format. Reference list is complete. Citation is properly done.
Note:.
Here IS the LINK for The SOUCEK. R., and Moser, K. (2010)
Coping with information overload in email communication
: Evaluation of a training intervention. Computers in Human Behavior, 26, 1458–1466.
file:///D:/Coping%20with%20information%20overload%20in%20email
I attached the page as well.
Computers in Human Behavior 26 (2010) 1458–1466
Contents lists available at ScienceDirec
t
Computers in Human Behavior
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h
Coping with information overload in email communication: Evaluation of a
training intervention
Roman Soucek *, Klaus Moser
School of Business and Economics, University of Erlangen-Nuremberg, Lange Gasse 20, 90403 Nürnberg, Germany
a r t i c l e i n f o
Article history:
Available online 11 June 2010
Keywords:
Email communication
Information overload
Training intervention
Evaluation study
0747-5632/$ – see front matter � 2010 Elsevier Ltd. A
doi:10.1016/j.chb.2010.04.02
4
* Corresponding author. Tel.: +49 911 5302 245; fa
E-mail address: roman.soucek@wiso.uni-erlangen.
a b s t r a c t
The present paper introduces three facets of information overload in email communication: A lar
ge
amount of incoming information, inefficient workflow, and deficient communication quality. In order
to cope with these facets of information overload, a training intervention was developed and evaluated
.
Data were collected from 90 employees on several evaluation levels within a longitudinal evaluation
design (one pretest double posttest design). The results reveal that the training contributed to an increase
in knowledge and media competencies. We also found evidence for a transfer of training contents to the
workplace. Finally, strain diminished on several dimensions. In particular, problems with media usage
and work impairment decline significantly, an effect that was stronger for those participants who face
a large amount of email at their workplaces.
� 2010 Elsevier Ltd. All rights reserved.
1. Introduction
During the last decades, email communication has found its
way to the workplace and has become an inherent part of today’s
working life (Dabbish & Kraut, 2006). Email communication be-
came popular due to its key advantage; easy and rapid exchange
of information that simplifies communication in large and geo-
graphically distributed organizations (Sproull & Kiesler, 1991). In
fact, Rice and Bair (1984) believed that the use of electronic media
would increase both personal and organizational productivity (see
also Crawford, 1982). However, due to the increasing diffusion of
email communication in organizations, the volume of email re-
ceived has steadily increased to the point where concerns have
been raised as to whether email contributes to employees’ ‘‘infor-
mation overload” (e.g., Dabbish & Kraut, 2006; Edmunds & Morris,
2000; Farhoomand & Drury, 2002). Preliminarily, information
overload can be defined as experiencing a large amount of informa-
tion that exceeds an individuals’ information processing capacity
(Schultze & Vandenbosch, 1998). Though a considerable number
of articles on information overload due to emails can be found in
the popular press (e.g., Musgrove, 2007; Stross, 2008), only more
recent research has both accumulated systematic evidence for in-
creased information overload at the workplace and revealed its im-
pact on strain (e.g., Hair, Renaud, & Ramsay, 2007). For example,
Moser, Preising, Göritz, and Paul (2002) found evidence that infor-
mation overload due to email communication is related to in-
creased psychosomatic complaints and to less job satisfaction.
ll rights reserved.
x: +49 911 5302 243.
de (R. Soucek).
In respect of these problems, the aim of the current paper is the
development and evaluation of a training intervention that en-
hances a more effective use of email communication, and therefore
strives to cope with information overload. In the following we first
specify the contents of such a training intervention. Afterwards we
describe and report the results of an evaluation study that assesses
the effectiveness of the training intervention.
2. Coping with information overload in the context of email
communication: A training intervention
In order to derive the issues that should be addressed by a train-
ing intervention, we first introduce three facets of information
overload in the context of email communication, namely a large
amount of incoming information, inefficient workflow, and defi-
cient communication quality.
2.1. Facets of information overload
2.1.1. Large amount of incoming information
There are several causes of the increase in the amount of email
messages. Besides the steadily growing diffusion of email commu-
nication in general, the ‘‘ease of communication” leads to an
augmentation of sent and received emails. Sending emails to a
multitude of recipients requires only a modicum of effort since
they do not have to be printed out and delivered to a post office.
The consequence of this increased quantity of emails is obvious:
Inboxes become jam-packed and result in a confusing mixture of
relevant and irrelevant emails, which hinders efficient information
processing (Whittaker & Sidner, 1997). In fact, the term
http://dx.doi.org/10.1016/j.chb.2010.04.024
mailto:roman.soucek@wiso.uni-erlangen.de
http://www.sciencedirect.com/science/journal/0747563
2
http://www.elsevier.com/locate/comphumbeh
R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466 1459
‘‘information entropy” describes email users’ experience of incom-
ing messages not being sufficiently organized by topic or content,
nor of being easily recognized as important or as part of the history
of communication on a given topic (Hiltz & Turoff, 1985).
2.1.2. Inefficient workflow
A large amount of incoming messages combined with inappro-
priate working habits may impair information processing capacity
and therefore promote information overload (Whittaker & Sidner,
1997). For example, Lantz (1998) concluded that those employees
reporting problems with emails are not those who received and
sent the most emails, but those who have not developed an effec-
tive structure for filing incoming emails, e.g., in separate folders.
Whittaker and Sidner (1997) used the term ‘‘email overload” to de-
scribe the dysfunctional use of email programs beyond their basic
communication functions. For example, the collection of ‘‘To-do-
emails” in the inbox can contribute to a cluttered and fragmented
inbox, the result being that users lose track of their tasks (Bellotti,
Ducheneaut, Howard, Smith, & Grinter, 2005; see also Dabbish &
Kraut, 2006). Another challenge to efficient workflow is interrup-
tions. New emails steadily reach recipients (Jackson, Dawson, &
Wilson, 2001; Kraut & Attewell, 1997; Whittaker & Sidner, 1997),
resulting in continuous interruptions and in loss of control over
the receiving of information (Hiltz & Turoff, 1985). As a result, deci-
sion-making performance suffers, especially during completion of
complex tasks (Speier, Valicich, & Vessey, 1999).
2.1.3. Deficient communication quality
Up to this point, information overload has been characterized as
the delivery of too many messages to be able to properly deal with
or to respond to (e.g., Farhoomand & Drury, 2002). Beyond this
quantitative issue, email messages are often deficient in their
quality. For example, compared to business letters, email commu-
nication is often considered a spontaneous and less formal commu-
nication medium (Nantz & Drexel, 1995). This notion of email
communication often leads to superficially and ambiguously for-
mulated messages that fail to give the recipients enough informa-
tion to act upon, and therefore fosters misunderstandings (Burgess,
Jackson, & Edwards, 2005; see also Friedman & Currall, 2003). In
addition, social and contextual cues are often missing in email
communication, rendering messages even more difficult to under-
stand (Sproull, 1991). Finally, email messages can contribute to
ambiguity because communication rules are not well developed
(Kiesler, Siegel, & McGuire, 1984). One example of ambiguity due
to unclear communication rules occurs when senders expect recip-
ients to respond to a message within a short time frame (Markus,
1994; Renaud, Ramsay, & Hair, 2006).
2.2. Addressing information overload
Information overload results from a discrepancy between the
amount of information people receive and (the limits of) their
information processing capacity (Schultze & Vandenbosch, 1998).
Accordingly, there exist two general approaches to reducing infor-
mation overload, (1) reducing the amount of incoming information
and (2) enhancing recipients’ information processing capabilities.
Intervention strategies that aim to reduce the amount of incoming
email can address various levels: Technical interventions concern
features of corporate email systems that help to administer email,
e.g., filters that automatically sort out unsolicited emails. Organiza-
tional interventions concern, e.g., the implementation of email pol-
icies that provide guidelines for email use at the workplace like an
adequate use of the carbon copy (cc) function (see Barron & Yech-
iam, 2002). Our paper presents a training intervention that aims to
deal with information overload at the individual level by enhanc-
ing information processing. Relating to the facets of information
overload a training intervention should improve media competen-
cies in order to cope with a large amount of email, improve per-
sonal workflow, and enhance email literacy.
2.2.1. Improving media competencies
The increased amount of incoming emails results in a mixture of
relevant and irrelevant messages, which hinders efficient informa-
tion processing. In order to cope with the given amount of email, a
training intervention must enhance the participants’ knowledge
and readiness to use functions that permit a more efficient han-
dling of incoming emails (see also Ducheneaut & Watts, 2005).
For example, an email client can collect and file incoming emails
according to pre-defined criteria like sender, date, topic, etc. (Dab-
bish & Kraut, 2006). This ‘‘email classification” helps to pre-struc-
ture a recipient’s inbox and therefore supports subsequent
information processing (Whittaker, Bellotti, & Gwizdka, 2007; see
also Dredze, Lau, & Kushmerick, 2006). Another example is to high-
light emails received in carbon copy (‘‘cc emails”) with another col-
or in order to distinguish them from emails that are directly
targeted to the recipient and therefore may be more important.
In sum, the enhancement of media competencies that facilitate
the management of incoming emails should help to reduce email
overload. However, a training intervention should exceed the mere
demonstration of functions provided by email programs, i.e., train-
ing should take into account an appropriate utilization of email
functions at the workplace (see also Whittaker et al., 2007). In par-
ticular, categorizing and filing of emails (Whittaker & Sidner, 1997)
as well as setting up appropriate structures of folders should be ad-
dressed (Lantz, 1998). That way, the training not only presents var-
ious technical means for coping with a high amount of incoming
information but encourages the participants to decide what func-
tions would be useful at their particular workplaces.
2.2.2. Improving personal workflow
Appropriate self-management techniques can help to optimize
information processing, e.g., priority setting and task management
(Whittaker et al., 2007). For example, a training intervention
should recapitulate the principles of task management and address
how these principles can be effectively implemented within email
programs (e.g., definition of special folders, marking emails with
flags, reminders, etc.). Furthermore, interruptions of work tasks
by incoming emails occur when email communication has not
been efficiently integrated into personal workflow and task man-
agement (Whittaker, Bellotti, & Gwizdka, 2006). In order to address
this issue, one strategy can be to perceive email communication as
a daily task that is subject to scheduling and workflow manage-
ment. For example, an employee can schedule his emailing activi-
ties every two hours. In order to avoid interruptions in the
meantime, the email program could be closed or the new email
alert box could be turned off (Jackson, Dawson, & Wilson, 2003).
Note that the aim of a training program should be to advise the
trainees on how to modify or extend their already existing self-
management techniques to email management that fits their
working routines. For example, a recent study suggested that un-
der certain conditions, frequent checking of incoming email can re-
duce email overload (Dabbish & Kraut, 2006).
2.2.3. Enhancing email literacy
In order to cope with superficial and ambiguous communica-
tion, a respective training intervention should address basic princi-
ples of email communication. Participants should learn how to
write effective subject lines and write emails that are more concise
and to the point (Jackson, Burgess, & Edwards, 2006). Further top-
ics are targeting of emails (see also Kimble, Hildreth, & Grimshaw,
1998) and handling of email attachments. Basically, trainees
should learn when to communicate via email. In this context, users
1460 R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466
of email communication should be aware of the strengths and lim-
itations of this particular communication device. Therefore, a train-
ing intervention should foster a discussion about the adequacy of
email communication for a given purpose. For example, emails
are clearly appropriate for routine tasks and for statement of facts
(Lantz, 1998; Lea, 1991), whereas issues that need further interpre-
tation should be conveyed by ‘‘richer” media, e.g., by telephone or
face-to-face communication (Daft & Lengel, 1984; Lee, 1994).
Overall, the reason for including the enhancement of email literacy
into the training intervention is that if employees adequately use
email communication themselves, they can accomplish their work
tasks more efficiently and would get lesser requests upon their
concise written emails.
2.3. Criteria of training effectiveness and research hypotheses
The previous sections introduced three facets of information
overload in the context of email communication and explicated is-
sues that should be addressed by a training intervention, first,
enhancing media competencies in order to cope with a large
amount of incoming email, second, improving personal workflow,
and finally, enhancing email literacy with regard to adequate com-
munication. From the perspective of the training’s effectiveness,
the participants’ knowledge and readiness to use functions and
to follow principles that permit a more efficient email communica-
tion should be enhanced. Hence, participants should improve their
knowledge and apply what they have learned to the workplace.
Hypotheses 1 and 2 summarize these assumptions.
Hypothesis 1. The knowledge of email functions is higher after the
training than before the training.
Hypothesis 2. The application of email functions at the workplace
is higher after the training than before the training.
The training intervention should help to cope with problems
resulting from information overload. With regard to the three fac-
ets of information overload, the training intervention should result
in a reduced level of problems with media usage due to a large
amount of incoming emails and lower levels of work impairment
by means of an improved personal workflow. Furthermore,
enhancing email literacy should result in a decline of superficial
and ambiguous communication. These assumptions are summa-
rized by the Hypotheses 3a–3c.
Hypothesis 3a. Problems with media usage are lower after the
training than before the training.
Hypothesis 3b. Work impairment is lower after the training than
before the training.
Hypothesis 3c. Superficial and ambiguous communication is
lower after the training than before the training.
Moreover, because previous research found that information
overload is related to strain (Moser et al., 2002; see also Mano &
Mesch, 2010), we expect that the training intervention should con-
tribute to a lower level of strain in the context of email communi-
cation. Hypothesis 3d summarizes this as follows.
Hypothesis 3d. Email strain is lower after the training than before
the training.
However, these effects are expected to depend on the intensity
of the respective stressor, i.e., the reduction of strain should be par-
ticularly observed if a considerable amount of information overload
existed beforehand. Therefore, we expect a reduction of problems
associated with email overload especially for those participants
who are facing a large amount of email. This assumption is summa-
rized for the four strain measures by the Hypotheses 4a–4d.
Hypothesis 4a. Participants who are facing a large amount of
incoming email show a stronger decrease in problems with media
usage than participants with a small amount of email.
Hypothesis 4b. Participants who are facing a large amount of
incoming email show a stronger decrease in work impairment than
participants with a small amount of email.
Hypothesis 4c. Participants who are facing a large amount of
incoming email show a stronger decrease in superficial and ambig-
uous communication than participants with a small amount of
email.
Hypothesis 4d. Participants who are facing a large amount of
incoming email show a stronger decrease in email strain than par-
ticipants with a small amount of email.
3. Evaluation study
3.1. Participants
We conducted 16 training sessions in six companies from the
sectors of automation engineering, pharmaceutics, travel, and
accounting. In total, 162 participants voluntarily attended the
training sessions (group sizes varied between 8 and 13 persons).
Data were collected during three points in time, and 56% percent
of the trainees sent back all questionnaires, resulting in a final sam-
ple size of 90 participants. The average age of the participants was
39.92 years (SD = 8.68), and their mean time of employment was
17.74 years (SD = 9.68). Female participants were in the majority
with 60%. The participants had been working with emails for
7.22 years on average (SD = 3.02). A proportion of 47% of the partic-
ipants received more than 20 emails daily. Twenty-six percent of
the participants were executives.
3.2. Procedure
The current training is based upon the principles of cognitive-
behavioral skills training, which have previously been successfully
applied in the context of general stress management interventions
(e.g., van der Klink, Blonk, Schene, & van Dijk, 2001). In particular,
the current training intervention follows the approach of behav-
ioral modeling, i.e., trainees observe a model that demonstrates
certain skills and then reenact the model’s behavior, a technique
that has revealed as an effective method of computer skills training
(Chou, 2001; Davis & Yi, 2004; Simon & Werner, 1996; Yi & Davis,
2003). The training sessions took place in classrooms of the
employees’ organizations. Each participant used a Personal Com-
puter with an installed email program, the same as used at the
workplace. All six companies used the same email program. The
training intervention consisted of three parts: Improving media
competencies, improving personal workflow, and enhancing email
literacy.
The first part of the training started with instructions about
functions of email programs that are useful for coping with a high
amount of email, whereas the second part concentrated on princi-
ples of effective personal workflow. These instructions were
accompanied by a demonstration of the relevant functions, follow-
ing principles of behavior modeling (e.g., Yi & Davis, 2003). In par-
R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466 1461
ticular, behavior modeling consisted in the explanation and dem-
onstration of several email functions and principles of efficient
email communication. The trainer showed the application of these
functions on an overhead screen and participants repeated the
demonstrated behavior. Afterwards, the trainees were encouraged
to explore these functions themselves and to apply their knowl-
edge within an interactive scenario. Within this scenario, the par-
ticipants took the role of an employee of a fictional enterprise and
received emails from their virtual colleagues. These emails repre-
sented several business procedures and encompassed typical prob-
lems of email communication, as identified in earlier research on
information overload (e.g., Burgess et al., 2005; Moser et al.,
2002). For example, the participants received newsletters, spam
mails, and faced poorly formulated and incoherent business
emails. The participants’ task was to apply the previously learned
techniques, e.g., filtering, categorizing, analyzing of emails, and
responding to emails. Participants received feedback on the effects
of their strategies from the scenario itself as well as from the trai-
ner and from other trainees. For example, when participants
decided to use certain automatic filters in order to organize their
incoming emails, the consequences and usefulness of these filters
became obvious in subsequent exercises, namely after having re-
ceived additional emails. Finally, every exercise was ended with
a discussion of the results between the trainees and the trainer.
The third part of the training emphasized writing of emails as well
as the appropriateness of email communication in general. There-
fore, the nature of the exercise changed; for example, poorly for-
mulated emails were displayed on the overhead screen and
discussed by the trainees and the trainer. In addition, the trainer
as well as the trainees provided recommendations for ‘‘best
practice”. Trainees then decided on, which rules they wanted to
use at their workplaces. They received a template form that as-
sisted them to agree on email policies within their workgroups
or between project members. The third part of the training ad-
dressed issues similar to the sender training described by Burgess
et al. (2005).
3.3. Evaluation design
The study consisted of a three-wave survey within a pre–post
design with one follow-up assessment. We began with the collec-
tion of data two weeks before the training. The second question-
naire followed immediately after the training. Finally, we
distributed the third questionnaire three to four weeks after the
training. We gathered data on the following evaluation levels:
Knowledge of email functions, application of email functions at
the workplace, and strain. Knowledge and application of email
functions were assessed at three points in time, whereas strain
was assessed at pretest and posttest 2. Please note that pretest data
and posttest 2 data relate to the workplace, whereas posttest
1
data relate to the training context.
We collected data with paper-and-pencil questionnaires at
posttest 1 and with web-based surveys at pretest and posttest 2.
In order to match pre- and post-training data, participants marked
their questionnaires with a unique anonymous code. The matching
of pre- and post-measures was verified by a profile analysis of
demographic variables that were gathered at all three measuring
points. All statistical analyses of the longitudinal data were con-
ducted with variance analyses for repeated measures.
3.4. Measures
3.
4.1. Knowledge of email functions
Trainees rated their knowledge of 10 basic (e.g., use of folders)
as well as more advanced functions of email programs (e.g., auto-
matic filing of emails). Note that all functions were presented and
discussed during the training sessions. The participants’ knowl-
edge was assessed using the following categories: ‘‘I do not know
this function”, ‘‘I have heard about this function”, and ‘‘I know
how to apply this function”. In order to aggregate the ratings, we
summed up the number of functions that the participants reported
to have already known how to apply, resulting in an index ranging
from 0 to 10 functions.
3.
4.2. Application of email functions
Transfer of training contents means the application of email
functions at the workplace (e.g., ‘‘How often do you utilize rules
for automatic sorting and filing of incoming emails?”). Transfer
was assessed on 7-point rating-scales anchored from ‘‘not at all”
(=1) to ‘‘very frequently” (=7). The scale midpoint was anchored
with ‘‘sometimes” (=4). Finally, we computed the mean of these
items in order to obtain an index for the application of the email
functions presented in the training session.
3.
4.3. Strain
In order to assess the strain of the trainees, we used four scales
that were developed in previous research (Moser et al., 2002;
Preising, 2004): Problems with media usage, work impairment,
superficial and ambiguous communication, and email strain. The
scales were assessed on 7-point rating-scales anchored from ‘‘does
not apply at all” (=1) to ‘‘fully applies” (=7). Problems with media
usage focus on the quantity of received information and on related
problems (5 items). A sample item is: ‘‘Due to the information
flood, I am facing problems when I am working with emails”. The
scale work impairment stressed disruptions of workflow by emails
(5 items). High scores on this scale meant that emails absorbed so
many resources (information processing capacity) that task perfor-
mance suffered (Sample item: ‘‘The accomplishment of my email
correspondence takes so much time, so that other tasks are
neglected.”). Superficial and ambiguous communication concerned
superficiality of work due to deficient email communication (
5
items). A high score on this scale reflected ambiguous and inaccu-
rate communication via email and related problems (Sample item:
‘‘Misunderstandings often occur between me and my colleagues
because they read my emails superficially.”). Finally, email strain
covered general negative emotional reactions related to email
communication (8 items). A sample item is: ‘‘I quickly become an-
noyed when problems with emails occur”. The reliabilities (Cron-
bach’s alpha) of these scales are as follows: Problems with media
usage, a = .80, work impairment, a = .93, superficial and ambiguous
communication, a = .70, and email strain, a = .86. These reliabilities
are comparable to a previous study (problems with media usage,
a = .80, work impairment, a = .82, superficial and ambiguous com-
munication, a = .73, and email strain, a = .89; N = 195; Preising,
2004).
Further evidence for the psychometric quality of these scales
are as follows: First, a previous study found that retest reliabilities
are satisfactory, problems with media usage, r = .82, work impair-
ment, r = .89, superficial and ambiguous communication, r = .75,
and email strain, r = .89 (Preising, 2004; N = 60; four week interval
between test and retest). Second, in another study (Preising, 2004;
N = 195), problems with media usage and email strain were posi-
tively related to psychosomatic complaints (r = .17, p < .10 respec-
tively r = .34, p < .01; one-tailed tests), and both scales were
negatively related to job satisfaction (r = �.16, p < .10 respectively
r = �.18, p < .10; one-tailed tests) as well as work impairment
(r = �.21, p < .05; one-tailed test). Third, though information over-
load should not be simply equated with the amount of email re-
ceived, a certain degree of relationship should be expected. In
fact, in the current study we found significant correlations between
the amount of email and three strain scales before the training
(problems with media usage, Kendall’s tau, s = .16, p = .01; work
Table 1
Strain measures at pretest and posttest 2.
Strain measure Pretest Posttest 2
M SD M SD
Problems with media usage 3.40 1.24 2.44 1.09
Work impairment 3.66 1.58 2.96 1.34
Superficial and ambiguous communication 2.96 1.26 3.08 1.11
1462 R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466
impairment, s = .28, p < .01; superficial and ambiguous communi- cation, s = .06, p = .21; psychological strain, s = .15, p = .02; N be- tween 149 and 151; one-tailed tests). Note that superficial and ambiguous communication was not related to the amount of email received, which seems quite plausible since this scale measures qualitative deficits of email communication that are distinct from the amount of email received.
Email strain 2.43 1.13 2.25 1.0
7
1
2
3
4
5
6
7
pretest posttest 2
pr
ob
le
m
s
w
ith
m
ed
ia
u
sa
ge
small amount
of email
large amount
of email
Fig. 1. Problems with media usage before and after the training.
4. Results
In the following, we report the results of the evaluation study.
In particular, we test our assumptions whether the participants
improved their knowledge of email functions (Hypothesis 1) and
whether they apply what they had learned at the workplace
(Hypothesis 2). Furthermore, we inspect whether the training
intervention results in a decrease of strain (Hypotheses 3a–3d).
We also test the more specific assumption that the decline in strain
is stronger for those participants who face a large amount of email
at their workplaces (Hypotheses 4a–4d).
In order to control for selective dropout, we compared
participants who returned all three questionnaires to those partic-
ipants who did not. No significant differences occurred with regard
to pretest measures of strain, problems with media usage,
T(147) = �0.01, p = 1.00, work impairment, T(149) = �1.90, p = .06,
superficial and ambiguous communication, T(148) = 1.03, p = .31,
and email strain, T(148) = �1.30, p = .20 (two-tailed T-tests).
4.1. Knowledge of email functions
Hypothesis 1 assumes that the participants improve their
knowledge of email functions that support an efficient email com-
munication. The participants rated their knowledge of 10 overall
functions of email programs at three measurement points. Two
weeks before the training sessions, the subjects indicated an aver-
age of 3.76 functions they already knew how to apply (SD = 1.78).
At posttest 1, the participants’ knowledge rose to 8.84 functions
(SD = 1.45) and dropped to 8.01 (SD = 2.33) in posttest 2. An AN-
OVA for repeated measures reveals a significant change between
pretest and posttest 2, F(1, 89) = 201.72, p < .01, indicating an in-
crease of knowledge over time. Thus, hypothesis 1 is confirmed.
4.2. Application of email functions
Hypothesis 2 assumes an increase in the application of email
functions after the training compared to before the training. Con-
cerning the application of email functions, it is possible to analyze
data from three different points in time, though the change be-
tween pretest and posttest 2 deserves more attention because this
difference reflects a change at the workplace and thus the transfer
of training contents. Essentially, the usage of email-functions in-
creased from 2.96 (SD = 0.84) in the pretest to 5.87 (SD = 0.88) in
posttest 1 and dropped to 4.39 (SD = 0.87) in posttest 2. Again,
we computed ANOVAs for repeated measures (pretest and posttest
2). The change over time for training transfer was highly signifi-
cant, F(1, 88) = 163.70, p < .01, confirming hypothesis 2. Overall,
the usage of email functions not only improved after the training
session, but also resulted in a change at the workplace.
4.3. Strain
Table 1 depicts the descriptive statistics of the four strain mea-
sures before and after the training (posttest 2). Overall, the mean
scores declined to a considerable extent for three of the four scales,
namely problems with media usage, work impairment, and email
strain.
The training intervention strived to enhance information pro-
cessing in order to reduce information overload and its negative
consequences, namely problems with media usage, work impair-
ment, superficial and ambiguous communication as well as email
strain (Hypotheses 3a–3d). However, as already noted, we expect
a reduction of strain, more so if a certain amount of information
overload existed beforehand (Hypotheses 4a–4d). In order to test
these assumptions we computed ANOVAs for repeated measures
and considered (measurement) time as the within-subjects factor
and the amount of email as the between-subjects factor. With re-
gard to hypotheses 3a–3d we except main effects of time. Concern-
ing the hypotheses 4a–4d we expect interaction effects of time and
the amount of email. In particular, strain should decline to a higher
extent in case participants receive a large amount of email.
4.3.1. Problems with media usage
Fig. 1 depicts the means of problems with media usage for pre-
test and posttest 2, separated for a small and large amount of
email. Overall, trainees who had a large email load reported gener-
ally more problems with media usage than persons with a small
amount of email, F(1, 85) = 6.68, p = .01 (main effect of the amount
of email). This substantiates the notion that the amount of email
contributes to problems resulting from information overload.
Hypothesis 3a assumed that problems with media usage are lower
after the training than before the training. In fact, the results reveal
that problems with media usage decreased significantly over time,
F(1, 85) = 61.18, p < .01 (main effect of time). Thus, hypothesis 3a is
confirmed. Furthermore, Fig. 1 clearly depicts that the decline in
problems with media usage was more pronounced for those
employees with a large amount of email. In fact, the change in time
of problems with media usage depends on the amount of email,
F(1, 85) = 8.43, p < .01 (interaction effect of time and the amount
of email). With regard to the descriptive measures in Fig. 1 and
the significant interaction effect, hypothesis 4a is confirmed.
1
2
3
4
5
6
7
pretest posttest 2
su
pe
rf
ic
ia
l a
nd
a
m
bi
gu
ou
s
co
m
m
.
small amount
of email
large amount
of email
Fig. 3. Superficial and ambiguous communication before and after the training.
4
5
6
7
il
st
ra
in
small amount
of email
large amount
of email
R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466 1463
4.3.2. Work impairment
Fig. 2 reveals the change in work impairment over time, again
separated for a small and large amount of email. Again, trainees
who experienced a large amount of incoming email reported more
work impairment in general, F(1, 87) = 10.72, p < .01 (main effect of
the amount of email). Hypothesis 3b assumed a decrease of work
impairment over time. This hypothesis can be confirmed, work
impairment was lower after the training than before,
F(1, 87) = 28.94, p < .01 (main effect of time). In addition, the de-
cline in work impairment depended on the amount of email,
F(1, 87) = 7.60, p < .01 (interaction effect of time and the amount
of email). Again, participants reporting a large amount of email
experienced a greater decline in work impairment. Thus, hypothe-
sis 4b is confirmed.
4.3.3. Superficial and ambiguous communication
The means for superficial and ambiguous communication are
depicted in Fig. 3, again separated for time of assessment and
amount of email. Concerning superficial and ambiguous communi-
cation, the main effect for the amount of email is marginally signif-
icant, F(1, 87) = 3.07, p = .08, indicating a trend for higher levels of
superficial and ambiguous communication in case of a large
amount of email (main effect of the amount of email). However,
no decline of superficial and ambiguous communication can be
observed over time, F(1, 87) = 1.65, p = .20 (main effect of time).
Thus, hypothesis 3c is not confirmed. Also, the results do not indi-
cate a different change in time due to the amount of email,
F(1, 87) = 1.28, p = .26 (interaction effect of time and the amount
of email). Hypothesis 4c is not confirmed. Overall, the training
had no effect on superficial and ambiguous communication.
1
2
3
pretest posttest 2
em
a
Fig. 4. Email strain before and after the training.
4.3.4. Email strain
Fig. 4 depicts the change in time for email strain, separated for
participants who experience a small respectively large amount of
email. Overall, participants with a large amount of email reported
a higher extent of email strain, F(1, 84) = 4.69, p = .03 (main effect
of the amount of email). Furthermore, Fig. 4 depicts a decline in
email strain over time that revealed itself as marginally significant,
F(1, 84) = 3.57, p = .06 (main effect of time). Regarding this solely
marginally significant result, hypothesis 3d is not confirmed. Fur-
thermore, the results do not indicate a different change in time
in dependence of the amount of email, F(1, 84) = 1.59, p = .21
(interaction effect of time and the amount of email). Thus, hypoth-
esis 4d is not confirmed.
1
2
3
4
5
6
7
pretest posttest 2
w
or
k
im
pa
ir
m
en
t
small amount
of email
large amount
of email
Fig. 2. Work impairment before and after the training.
5. Discussion
Information overload in the context of email communication
has several facets to explore, the most common being: High
volume of received information that exceeds the recipient’s infor-
mation processing capacity (Schultze & Vandenbosch, 1998), inef-
fective personal workflow (Lantz, 1998; Whittaker et al., 2006),
and deficient communication quality such as ambiguously written
emails (Burgess et al., 2005). We derived three main issues for a
training intervention designed to cope with information overload:
Improvement of media competencies in order to cope with a large
amount of email, improving personal workflow, and enhancing
email literacy. Note that the training goes beyond the mere teach-
ing of specific computer skills. The aim is to promote an appropri-
ate usage of email functions as well as to facilitate an
understanding of the adequacy of email communication in differ-
ent situations. In particular, the third part of the training stresses
the handling of email communication, discussing ‘‘good practice”,
and making trainees aware of ‘‘bad practice”.
Overall, the training intervention we introduced in the current
paper was successful. In fact, we found effects on several evalua-
tion criteria: The participants improved their knowledge of email
functions and transferred the training contents from the training
context to the workplace. Finally, strain declined in three of four
dimensions. In particular, the trainees reported fewer problems
1464 R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466
with media usage and less work impairment. Hence, the training
helps to cope with the amount of email received and reduces train-
ees’ feelings of being overwhelmed and disrupted by incoming
information. Furthermore, the training intervention has a margin-
ally significant effect on email strain, in general. However, the re-
sults reveal no effect concerning superficial and ambiguous
communication, i.e., the trainees still perceive email communica-
tion as more ambiguous compared to alternative communication
media, like face-to-face communication or telephone.
More specifically, the training intervention was particularly
effective with respect to coping with a large amount of email. This
notion could be confirmed with regard to problems with media
usage and work impairment. An important question is why the
training is effective. Whereas our theoretical perspective refers to
the improvement of individual resources, namely information pro-
cessing, an alternative explanation might be that the training sim-
ply helped participants to reduce the number of emails they
normally receive. However, our data do not support this assump-
tion. In fact, the amount of email received did not change over time
(Wilcoxon-Test, Z = �1.51, p = .23). Thus, we assume that the
causes for the alleviation of information overload are due to en-
hanced information processing abilities of participants.
Conceptually, our training intervention is comprehensive from
the vantage point of email research, which has repeatedly been be-
moaned because of its segmentation into a collection of separate
research fields (Ducheneaut & Watts, 2005; see also Rudy, 1996).
Ducheneaut and Watts (2005) use the following metaphors to de-
scribe the different directions of email research: First, there is the
notion of email as a sort of ‘‘file cabinet”, with respective research
being interested in cognitive aspects of receiving, organizing, and
retrieving of information in email systems. Second, there is the
view of email as a production facility, and hence, a part of com-
puter-mediated communication. This approach addresses the
effective design of computer-mediated workflow. Finally, some
researchers analyze email as a communication genre and discuss
its advantages and constraints in comparison with other communi-
cation channels. The current training program adopted all three
directions of email research. It takes into account media competen-
cies (e.g., handling and filing of incoming information), personal
workflow (e.g., making email communication subject to scheduling
respectively task management), and email literacy (e.g., making
appropriate use of email).
5.1. Limitations
5.1.1. Time frame
Any training intervention should be discussed with respect to
the sustainability (vs. relapse) of the training effects in general,
and the transfer to the work environment in particular. Therefore,
we collected data both at the end of the training sessions and three
weeks after the training. We decided to analyze the difference be-
tween pretest and posttest 2 data. There are two reasons why we
consider the data collected immediately after the training as less
relevant. First, the measures of posttest 1 are related to the training
context, whereas pretest and posttest 2 data are related to the
workplace. Thus, the difference between pretest and posttest 2 re-
flects changes at the workplace. Second, we were interested in a
sustained increase of knowledge respective of application of email
functions rather than short-timed effects directly after the training
session. In fact, our data suggest a slight deterioration of the train-
ing effects over time, i.e., between posttest 1 and posttest 2.
Considering strain, the picture is more complex. Whereas sig-
nificant effects were observed for problems with media usage
and work impairment, one reason for the smaller effects on email
strain could be the short time distance between training session
and measurement at posttest 2. That is, a considerable reduction
of email strain may only emerge in the long run. In order to capture
the respective effects, future research should assess email strain
after more time has elapsed, e.g., three months after the training.
Nevertheless, given the multidimensionality of strain, it is quite
unlikely that the email training has strong effects on strain in
general. Note also that the scale ‘‘superficial and ambiguous com-
munication” might be less sensitive to measuring training effects
because change of scores depends on both the behavior of the
trainees and other people (e.g., co-workers, customers).
5.1.2. Measures
Use of self-report measures for the assessment of strain is both
common and appropriate because strain is experienced by the
trainees (see also Cooper, Dewe, & O’Driscoll, 2001). However, con-
cerning the measurement of knowledge and behavior, our results
should be considered with some degree of caution. A test of objec-
tive knowledge (i.e., testing what has been learned) or the use of
observers instead of self-reports are possible supplements in future
studies. For example, Jackson and colleagues monitored and re-
corded employees’ activities with a remote desktop system (Jack-
son et al., 2003).
5.1.3. Evaluation design
Unfortunately, we were not able to convince the organizations
to increase the number of participants of the study and set up a
non-training control group. However, we should briefly comment
on the problems that might result from a study lacking a control
group. Two important issues are trainee maturation and testing ef-
fects (Shadish, Cook, & Campbell, 2002). Considering maturation,
we acknowledge that at least some problems with new technolo-
gies might be due to a simple lack of experience. However, trainees
in our evaluation study had a considerable amount of work expe-
rience in general and with email communication in particular.
Therefore, we estimate that it is very unlikely that some matura-
tion effects parallel with the delivery of the training sessions. In
addition, evidence against the existence of both maturation and
testing effects can be found in a retest study (Preising, 2004),
which did not find any decrease on the same strain scales between
the first and the second measurement point. Furthermore, in the
current study, effects on the strain scales were different depending
on the amount of email that training participants received. Thus, a
general testing effect can be ruled out because it would have lead
to comparably uniform changes in scale scores independent of
scale content.
5.1.4. Composition of trainees
Since trainees participated voluntarily, the training groups were
quite heterogeneous. This is especially important with regard to
the third part of the training intervention: Improving email com-
munication by means of enhancing email literacy respectively
communication rules. As the reduction of superficial and ambigu-
ous communication depends not only on one’s own manner of
communication but also on the recipients, this part of the training
might be less effective because regular ‘‘communication partners”
– who of course should agree with these communication rules –
were not available in the training sessions. In fact, training effects
should be higher when all members of existing working groups
participate in the training session – enabling formal or informal
peer training (see Fulk, 1993) – or when the trainees have the
opportunity to disseminate the rules to their co-workers. Because
the current study was conducted with participants from various
workgroups, the effectiveness of the training regarding superficial
and ambiguous communication can be expected to emerge only
after a considerable time (if at all).
R. Soucek, K. Moser / Computers in Human Behavior 26 (2010) 1458–1466 1465
5.2. Implications and directions for future research
The current evaluation study has both practical implications
and suggests directions for future research. The results reveal that
the training intervention was particularly effective for trainees
who have to cope with a large amount of email. For example, de-
crease in reported problems with media usage and work impair-
ment is stronger for employees who face a large amount of
email. Therefore, the presented training intervention can be even
more recommended to employees who have to cope with a high
volume of emails. A specific target group of the training interven-
tion could be home-based workers who are faced with a high vol-
ume of emails and report higher levels of work distress (Mano &
Mesch, 2010). This type of workers has limited opportunities for
face-to-face communication in order to discuss work-related is-
sues, which need further clarification or interpretation. Rather
home-based workers are bound to media-based communication
like email or telephone, and therefore, should be made aware of
the strengths and weaknesses of these various communication
media and their appropriate usage.
The training intervention paid attention to several facets of
information overload. However, research shows that certain prob-
lems related to email communication (‘‘email defects”) vary be-
tween users (Burgess et al., 2005). For example, employees with
higher job grades are receiving more emails compared to employ-
ees with lower job grades (Burgess et al., 2005). Sales representa-
tives may not have the opportunity to retrieve their emails while
visiting several customers, and therefore are regularly confronted
with an overloaded inbox after returning to their offices. The work
of senior managers involves greater equivocality in communication
contents that can be better resolved by a direct and synchronous
communication medium like face-to-face communication rather
than paperbound or electronic communication (Markus, 1994).
These examples illustrate that different users have to tackle vary-
ing problems in email communication. In a similar vein, Mano
and Mesch (2010) conclude that the assessment of the benefits
and costs of email communication should consider individual char-
acteristics. Overall, detailed knowledge about specific problems
and consequences of email communication should provide fruitful
starting points for the development of specific training interven-
tions and recommendations for various groups of employees.
A more ‘‘conceptual enlargement” of the training intervention
could be as follows. Whereas the current training intervention
focuses on the individual level, recent research has strongly recom-
mended comprehensive stress interventions, i.e., trainings should go
beyond interventions on the individual level and should also pay
attention to organizational-level factors like organizational policies
concerning email communication that provide guidelines for email
use at the workplace (Munz, Kohler, & Greenberg, 2001; Murphy,
1996; van der Klink et al., 2001). Such policies can contribute to
the development of (better) communication rules or a ‘‘common
perspective” in the organization, and therefore, reduce superficial
and ambiguous communication (see Boland & Tenkasi, 1995; Clark
& Brennan, 1991).
Another direction of future research is the relationship of email
communication and job performance. The current paper has a fo-
cus on email communication as a source of strain. From a more
general organizational behavior perspective, the evaluation of
training interventions should not only focus on problems that
could be prevented but also on the effects of email communication
on work performance (see Mano & Mesch, 2010).
6. Conclusions
Overall, the evaluation study showed that individual resources
preventing information overload could be successfully improved
by means of training. In particular, the training intervention en-
hances processing of a given amount of incoming email, and helps
to reduce several facets of strain in the context of email communi-
cation. However, in order to enforce training effects, it is
recommendable to train members of existing workgroups to-
gether. That way, a common understanding and use of email com-
munication can be disseminated within organizational units.
Furthermore, according to comprehensive stress interventions,
trainings should also pay attention to organizational-level factors
like organizational policies concerning email communication
(Munz et al., 2001; Murphy, 1996; van der Klink et al., 2001). Of
course, email-trainings could also be an incentive to develop such
policies if they are currently non-existent.
Acknowledgement
This research was partly supported by grants from the
Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, INQA-Projekt
81-02.
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http://www.washingtonpost.com/wp-dyn/content/article/2007/05/24/AR2007052402258.html
http://www.nytimes.com/2008/04/20/technology/20digi.htm
http://www.nytimes.com/2008/04/20/technology/20digi.htm
- Coping with information overload in email communication: Evaluation of a training intervention
Introduction
Coping with information overload in the context of email communication: A training intervention
Facets of information overload
Large amount of incoming information
Inefficient workflow
Deficient communication quality
Addressing information overload
Improving media competencies
Improving personal workflow
Enhancing email literacy
Criteria of training effectiveness and research hypotheses
Evaluation study
Participants
Procedure
Evaluation design
Measures
Knowledge of email functions
Application of email functions
Strain
Results
Knowledge of email functions
Application of email functions
Strain
Problems with media usage
Work impairment
Superficial and ambiguous communication
Email strain
Discussion
Limitations
Time frame
Measures
Evaluation design
Composition of trainees
Implications and directions for future research
Conclusions
Acknowledgement
References
