I need help with an assignment. You are to summarize the attached article. It is to be 1-2 pages single spaced APA format.
Do procrastination-friendly environments make students delay unnecessarily?
Kent Nordby1 • Katrin B. Klingsieck2 •
Received: 7 March 2017 /Accepted: 5 June 2017 / Published online: 14 July 2017
� Springer Science+Business Media B.V. 2017
Abstract Research on procrastination emphasizes trait explanations for unwanted delay, yet environmental factors are most probably significant contributors to the
problem. In this paper, we review literature related to the influence of environmental
factors on academic procrastination and investigate how such factors may be
assessed in facilitating academic procrastination in students. Study 1 asked students
to evaluate three different fields of study—natural sciences, medicine, and
humanities—on environmental variables assumed to be relevant for academic
procrastination (e.g., structured course progression, freedom in the study situation).
Distinct differences between the academic fields were observed. In Study 2, par-
ticipants from these three fields of study rated their own academic procrastination as
well as peer procrastination and peer influence. Dispositional (trait) procrastination
was also measured. The results demonstrated that environmental factors have a
negligible impact on low-procrastinating students, whereas procrastination-friendly
environments seem to facilitate and augment academic procrastination in students at
medium-level dispositional procrastination, i.e., the majority of students. We con-
clude that social and environmental factors should receive increased attention in
measures taken to reduce and prevent academic procrastination.
Keywords Academic procrastination � Peer effects � Procrastination environment � Procrastination antecedents � Self-control
& Frode Svartdal firstname.lastname@example.org
1 Department of Psychology, UiT the Arctic University of Norway, 9037 Tromsø, Norway
2 Department of Psychology, Universität Paderborn, Paderborn, Germany
Soc Psychol Educ (2017) 20:491–512
The goal of the present study is to explore the role of environmental factors in
academic procrastination by focusing on culture differences between different
academic disciplines, peer procrastination, and peer influence. Academic procras-
tination—the intentional delay of initiation or completion of important and timely
academic activities (Ziesat et al. 1978)—is common among students. The core
characteristic of procrastination is the intention-action-gap (Steel 2007): Procras-
tinators demonstrate no lack of good intentions, but too often intentions are not
implemented as planned (Dewitte and Lens 2000). As much as 50% of students
procrastinate to the extent that it becomes problematic (Solomon and Rothblum
1984; Steel 2007). Academic procrastination typically manifests itself as delay in
starting or finishing academic tasks such as studying for exams, writing term papers,
and keeping up with weekly assignments. Such delays result in suboptimal
performance in meeting deadlines (Ellis and Knaus 1977; Pychyl et al. 2000; Steel
2007), and are accompanied by discomfort and stress (Sirois 2014), depression and
anxiety (Flett et al. 1995; Stöber and Joormann 2001), worry (Antony et al. 1998;
Ferrari et al. 1995), and shame and guilt (Fee and Tangney 2000; Pychyl et al.
Most research on procrastination has focused on the dispositional accounts of the
problem. Indeed, procrastination is referred to as the ‘‘quintessential self-regulatory
failure’’ (Steel 2007), and the notion of a ‘‘procrastinator’’ identifies procrastination
as essentially a personal problem. In support of this view, a large body of research
has investigated the relation between personality dimensions and procrastination,
demonstrating the close connection between procrastination and impulsiveness, low
conscientiousness, and lack of self-control (Gustavson et al. 2014; Ozer and Benet-
Martinez 2006; Rozental and Carlbring 2014; Steel 2007). Such findings accentuate
the stereotypical picture of the procrastinating student as a person who is easily
distracted by tempting activities such as socializing with friends or surfing the
Internet, demonstrating little concern for academic work. Additionally, students
with high levels of evaluation anxiety, maladaptive perfectionism, low self-efficacy,
and fear of failure have been found to have problems with writing term papers,
studying for exams, and keeping up with weekly readings due to procrastination
(Alexander and Onwuegbuzie 2007). Research has further demonstrated that low
extrinsic motivation and external locus of control contribute to academic
procrastination (Brownlow and Reasinger 2000), whereas high intrinsic motivation
reduces it (Lee 2005; Steel 2007). Negative metacognitive beliefs about procras-
tination (e.g., thoughts about the uncontrollability of procrastination) tend to
increase unnecessary delay (Fernie et al. 2009), as do positive beliefs such as
‘‘procrastination helps creative thinking’’ or ‘‘I work better under pressure’’ (Cao
492 K. Nordby et al.
1.1 Environmental factors in procrastination
As discussed, research over the past four decades has amply demonstrated that
individual factors significantly contribute to the procrastination problem. In
contrast, environmental (exogenous) factors have received considerably less
attention. This is surprising, given the fact that being a student is an inherently
social endeavor, and that a multitude of social and environmental factors beyond the
students’ control may create and sustain unnecessary delay. In the following
paragraphs, we review research concerning exogenous factors that foster procras-
tination. Due to the relative scarcity of this research, we have also included some
relevant findings from outside the field of procrastination.
1.1.1 Teacher/instructor effects
Several studies have documented how teachers and instructors can affect learning
and achievement (Corkin et al. 2014; Sacerdote 2011), and how effective teachers
can make students feel better about school and learning as well as enhance student
achievement (Darling-Hammond 2000). A few studies have investigated how
teachers directly affect student procrastination. For example, Corkin et al. (2014)
found that procrastination was inversely related to instructor organization, possibly
because instructors who are organized ‘‘make it easier for students to organize,
structure, and plan their own work’’ (Corkin et al. 2014, p. 299). Similar results were
reported in a qualitative study where students indicated unorganized and lax
teachers to be a reason for their procrastination (Grunschel et al. 2013), whereas
instructors with high expectations have been found to increase students’ class
enjoyment and interest and reduce student procrastination (Corkin et al. 2014).
Similarly, teachers who expect less, are more flexible in their grading, and are
willing to negotiate deadlines with students have been found to promote
procrastination (Schraw et al. 2007). Patrzek et al. (2012) interviewed 12
experienced university counselors who work with students struggling with
procrastination. Although these counselors highlighted the importance of disposi-
tional aspects and task characteristics as important causes of procrastination, they
also emphasized the negative effect of poor teaching skills and coaching in lecturers
and overwhelming amounts of work put on students by the universities. Concerning
deadlines, several studies have shown that instructors who set deadlines help
students reduce their procrastination and increase their performance, compared to
students with self-imposed deadlines (Grunschel et al. 2013; Lamwers and
Jazwinski 1989; Wesp 1986). Accordingly, several authors recommend setting
strict deadlines for students to reduce procrastination (Ariely and Wertenbroch
2002; Steel 2007; Tuckman and Schouwenburg 2004).
1.1.2 Task characteristics
Task characteristics are important for evoking and maintaining procrastination. As
many study-related tasks are imposed on students by others, they represent an
important environmental context for student procrastination. Task aversiveness, i.e.,
Do procrastination-friendly environments make students… 493
the degree to which a task is unpleasant, boring, and/or uninteresting, is a strong
predictor of procrastination (Steel 2007). Blunt and Pychyl (2000) found different
aspects of task aversiveness to be important at different stages of personal projects.
During the initial startup stages of a project, task aversiveness is related to aspects of
personal meaning such as project enjoyment, pleasure, fun, and communion,
whereas later on the feeling of control, initiating work, and feeling of uncertainty
play a greater role in the perception of aversiveness. Several studies have found task
difficulty to be important. On the one hand, the more difficult the task, the more
students tend to procrastinate (Scher and Ferrari 2000; Senécal et al. 1997). On the
other hand, if the task is too easy, it can promote procrastination by appearing
boring or uninteresting. Thus, a balance between making a task sufficiently
challenging but also achievable seems to be optimal (Steel 2007; van Eerde 2000).
Ackerman and Gross (2005) found that students procrastinated less on assignments
perceived as interesting, required a variety of skills to complete, were accompanied
with clear instructions, and were carried out in a milieu with social norms and
rewards for starting promptly.
1.1.3 Social environment and peers
Another possibly important factor in procrastination is the role of the social
environment and peers (Klingsieck et al. 2013). Klingsieck et al. (2013) noted that
‘‘…it seems especially surprising that previous research has virtually neglected social aspects of procrastination.’’ This conclusion may be particularly relevant for
students since they interact with other students on a daily basis, both in academic
settings and in their free time, creating arenas for modeling and other forms of social
influence. Based on interviews with students, Klingsieck et al. (2013) found a three-
category divide in social antecedents for procrastination: (1) group tasks versus
individual tasks, (2) significant others’ attitudes toward procrastination, and (3)
procrastinating role models. Students reported procrastinating less when collabo-
rating with others. They also reported that family and friends served as role models
for procrastination tendencies (e.g., ‘‘because my sisters are very similar with regard
to procrastination’’) and that the influence of significant others depended on both the
attitude to procrastination and the model.
These categories are also in line with social psychological research. For example,
according to the social facilitation hypothesis, the mere presence of others can speed
up or slow down performance, depending on individual skill (Falk and Ichino 2006;
Zajonc and Sales 1966). Also, other students may serve as good or bad models
(Bandura 1977) depending on behavior and consequences relating to procrastination
(Stinebrickner and Stinebrickner 2006). Third, according to social comparison
theory (Festinger 1964), people evaluate themselves by comparing with others. To
avoid feeling less capable or intelligent than their peers, students might feel
obligated to work harder to keep up. Finally, research indicates that procrastinators
may have good reason to believe they are being judged negatively by others. Thus,
Ferrari and Patel (2004) found that across academic and everyday activities,
procrastinators punish other procrastinators by allocating procrastinating peers
494 K. Nordby et al.
fewer resources, giving them lower ratings, and attributing more internal negative
dispositions to them.
Outside the field of procrastination research, peer effects have been investigated
by examining student academic performance related to that of their close peers. The
assumption is that pairing students with academically stronger peers will have a
positive performance impact on the weaker peers. Coleman and Department of
Health USA (1966) found the expected presence of peer effects in elementary and
secondary school, concluding that ‘‘…a pupil’s achievement is strongly related to the educational backgrounds and aspirations of the other students in the school.’’
However, results from studies in higher education have rendered mixed results
(Carrell et al. 2009; Sacerdote 2011). For example, Zimmerman (2003), using
random assignment of housing for students, found only small positive effects for
students in the middle 70% of the distribution, but no peer effects at all for the top
and bottom 15%. Similarly, Foster (2006), Lyle (2007) and Stinebrickner and
Stinebrickner (2006) found no or weak evidence for contextual peer effects on
academic grades. In contrast, Hoxby and Weingarth (2005) demonstrated strong
peer effects for the top and bottom 15% students in their sample, and smaller effects
in the middle of the distribution, concluding that ‘‘higher achieving people are better
peers all else equal.’’ Carrell et al. (2009), studying a sample from the United States
Air Force Academy, found that the SAT score of peers influenced weaker peers’
outcomes on some topics (i.e., math and science), but not on others (i.e., physical
education and language).
Research on peer effects also indicates an impact on students’ procrastination
behavior. For example, Foster and Frijters (2010) found that students believed that
high-quality peers could positively influence their outcomes and that their effort
levels depended on the effort level of their peers. Similarly, Stinebrickner and
Stinebrickner (2006) found that first-year grade outcomes and drop-out decisions
depended partly on the effort students put into studying, the quality of their study
time, and students’ beliefs about the importance of education and that their peers
could influence these effects. In addition, working with peers has been shown to
have motivational effects on students (Eisenkopf 2009), possibly playing an
important role in student procrastination.
Reviewing the literature leaves the impression that environmental and social factors
may be important in facilitating or hindering procrastination, but it is difficult to
formulate clear-cut conclusions about their effects. One reason for this is that social
and environmental factors affect people in complex ways, often interacting with
dispositional factors. For example, students prone to procrastinate may ‘‘thrive’’ in a
procrastination-friendly environment (e.g., peers are procrastinating, teachers are
lax), causing them to feel very little pressure to get things done, whereas students
low in procrastination might react to the same environment in an opposite way,
attempting to distinguish themselves from their less diligent peers. Second,
environments are diverse. Within any single student group, some students
procrastinate, whereas others do not, putting any one student in contact with a
Do procrastination-friendly environments make students… 495
variety of different influences, possibly making a given environment both
procrastination-friendly and unfriendly at the same time. This diversity also
presents possibilities for individual students to self-select into peer groups within a
larger study environment, making it difficult to distinguish peer-effects from
selection effects. Third, factors inhibiting versus promoting procrastination in a
given context may be additive or interactive, implying that a given factor may be
unimportant or important depending on other factors. Accordingly, an examination
of the effects of environmental factors on procrastination should be prepared for
complexity, taking into account also that their effects most probably will be
modulated by the dispositional tendency to procrastinate in a given student.
Importantly, existing research has not examined the role of study content and
academic climate related to procrastination. Characteristics of different academic
disciplines might differentially affect how students behave and think in relation to
delay. For example, study environments may differ as to whether they are
competitive and outcome-focused, or whether they emphasize specific knowledge
and skills rather than understanding and reflection. Schachter et al. (1991, p. 362)
found that lecturers in different study topics differed in their lecture styles as to
whether skills and knowledge can be described accurately or not:
The academic disciplines differ markedly in the extent to which, let us say, a
speaker is required to choose among options in an undergraduate introductory
lecture. In the pure sciences, we maintain, there are relatively few options.
Consider a statement such as E = mc2. There are no options; it cannot be c3 or
c4; it is mc2 and that is it. In contrast, consider the statement, ‘‘What
Shakespeare probably meant in that passage from Lear was …’’ or ‘‘The reason Jackson Pollack put the patch of red in the corner of the canvas was
…’’ The options seem limitless.
Such differences may be accompanied by structural and cultural differences in
the study curriculum, for example in the degree of freedom of the study situation,
the way exams are arranged, the types of knowledge and competence tested, and
more (e.g., Becher 1994). We are not aware of studies documenting the existence of
such procrastination-relevant differences as perceived by students, but we find it
likely that structural and cultural differences between academic disciplines are
associated with overall differences in student procrastination. As noted, it is also
likely that structural and cultural differences between academic disciplines may act
differently, depending on individual procrastination level.
1.3 The present studies
The goal of the present study was to explore the role of environmental factors in
academic procrastination by focusing on culture differences between different
academic disciplines, peer procrastination, and peer influence. Study 1 examined
structural and cultural differences between three academic disciplines, natural
sciences, medicine, and humanities as perceived by students. Based on the literature
reviewed, we identified six dimensions believed to be particularly relevant for
academic procrastination (Becher 1994; Schachter et al. 1991): Rote learning and
496 K. Nordby et al.
memorizing, tangible knowledge, reflection and afterthought, structured course
progression, high demands and grade pressure, and freedom in the study situation.
In evaluating these dimensions, we expected students to rate the humanities high on
the dimensions such as reflection and afterthought and freedom in the study
situation, and low on dimensions such as rote learning and memorizing and tangible
knowledge. Natural sciences, and to some extent medicine, should be evaluated in
an opposite way. If correct, such differences between the three selected academic
disciplines represent procrastination-relevant dimensions that present differential
opportunities for students to procrastinate.
Study 2 examined academic procrastination among students from these three
academic disciplines. Assuming that structural and cultural differences between the
disciplines are related to procrastination, overall differences in academic procras-
tination should be observed, with more procrastination in procrastination-friendly
environments. More importantly, study environments should affect students
differently, depending on dispositional tendency to procrastinate. Thus, a student
low in procrastination should be relatively little influenced by a procrastination-
friendly environment, whereas students higher in dispositional procrastination
should be negatively affected. Finally, to examine possible peer effects, we also
assessed the extent to which peers were perceived to procrastinate and the extent to
which a given student was influenced by peers.
2 Study 1
Study 1 asked students to evaluate three different academic disciplines on six
dimensions assumed to facilitate versus hinder procrastination. We chose the
academic disciplines natural sciences, medicine, and humanities, as we believe
these to demonstrate distinctly different characteristics on the six dimensions
specified. For example, medicine and natural sciences are characterized by a
pragmatic and factual approach to learning, whereas humanities can be character-
ized by a more reflective and contemplative approach. It is also likely that these
differences are reflected in the structure of study progression.
Participants were 49 students (mean age = 24.3 years, SD = 3.70) at a Norwegian
university. Most (43) were from natural sciences, medicine, and humanities.
The questionnaire described six dimensions describing natural sciences, medicine,
and humanities. The six dimensions were rote learning and memorizing, tangible
knowledge, reflection and afterthought, structured course progression, high
demands and grade pressure, and freedom in the study situation. Each dimension
Do procrastination-friendly environments make students… 497
was rated on a 5-point Likert-scale (1–5), higher scores indicated the dimension to
be more characteristic of the academic field. The academic fields were rated in
sequence, natural science first, then medicine, and finally humanities.
Comparing the mean dimension evaluations between the study programs indicated a
significant interaction effect, F(10, 480) = 35.67, p \ .00, partial eta squared = .43. As is seen from Table 1, natural sciences and medicine were evaluated as
higher on the dimensions rote learning and memorizing, tangible knowledge, and
structured course progression, whereas evaluations of humanities were higher on
the dimensions reflection and afterthought and freedom in the study situation. Note
also that medicine was evaluated very high on high demands/grade pressure,
reflecting the fact that this study program has very high grade admission demands.
The mean of all dimensions (all except dimensions 3 and 6 reversed) can be seen as
a measure of ‘‘procrastination-friendliness.’’ Comparing the study fields on these
means rendered a significant difference, F(2, 96) = 113.46, p\ .00, natural science and medicine being evaluated low in the scale (2.47 and 2.09, respectively) and
humanities as markedly higher (3.51).
The present results demonstrate distinct differences between the three study fields,
indicating that students in these fields have different beliefs, expectations, and
attitudes that are likely to facilitate versus hinder procrastination. Whether such
structural and climate differences affect procrastination in students enrolled in the
programs is not known from the present data, but we find it likely. For example,
against the backdrop of research concerning situational aspects of procrastination,
freedom in the study situation, the need for reflection and afterthoughts, and lack of
structured course progression are all factors that are likely to facilitate procrasti-
nation, at least in people prone to delay unnecessarily in the first place. Hence, as is
apparent from Table 1, the profile describing the humanities makes that study
Table 1 Culture differences in study programs
Dimensions Natural Sciences Medicine Humanities
M SD M SD M SD
1. Rote learning/memorizing 3.65 1.03 4.53 .71 3.02 1.05
2. Tangible knowledge 4.06 .94 4.20 .89 2.78 1.01
3. Reflection/afterthoughts 3.14 1.17 3.51 1.14 4.41 .84
4. Structured course progression 4.04 .84 4.47 .68 2.92 1.12
5. High demands/grade pressure 3.74 1.00 4.22 1.20 2.82 .88
6. Freedom in the study situation 3.16 1.20 2.45 1.14 4.18 .81
498 K. Nordby et al.
program potentially more procrastination-friendly compared to both medicine and
3 Study 2
The aim of Study 2 was to examine the relation between procrastination-relevant
environmental factors and academic procrastination. Procrastination-relevant envi-
ronmental factors are conditions that facilitate (or hinder) individual procrastination,
such as the organization of the study situation, unstructured (or structured)
coursework, study content, procrastinating (or non-procrastinating) peers, as well as
other variables. As indicated in Study 1, several of these factors seem to be
distinctly different between the academic disciplines natural sciences, medicine, and
humanities. Hence, we recruited participants from these three disciplines for Study
2. To examine procrastination, we administered the Irrational Procrastination Scale
(IPS; Steel 2010) as well as a scale measuring specific instances of academic
procrastination. The first scale addresses dispositional procrastination, whereas the
latter focuses on socially-induced episodes of doing something else that planned
academic work, e.g., ‘‘When I am with other students to do schoolwork, we often
end up doing other things instead.’’ We also administered items to assess peer
procrastination, peer influence, and exposure to the student environment.
Given these measures, the study attempted to assess the influence of environ-
mental and social factors on academic procrastination. Here it is of great interest to
examine if and how there are differences between academic disciplines related to
procrastination-relevant factors, and if such differences are modulated by disposi-
tional tendency to procrastinate. No or small differences in academic procrastination
were expected between academic disciplines for well-regulated students scoring low
in dispositional procrastination. However, for students demonstrating medium or
high procrastination as defined by the dispositional IPS measure, study programs
with characteristics that facilitate procrastination (i.e., humanities in the present
study), should be associated with significantly more academic procrastination
compared to programs low on these dimensions (i.e., medicine and natural
Furthermore, as peers may facilitate or reduce procrastination in a given student
through their procrastination habits, peer procrastination may be an important factor
in understanding academic procrastination. We obtained a measure of peer
procrastination by asking the participants to evaluate procrastination in fellow
students, e.g., ‘‘My fellow students rarely delay schoolwork.’’ In the present context,
peer procrastination should at least in part be a function of the different study
disciplines, with overall more peer procrastination in humanities compared to
natural sciences and medicine. However, this overall tendency may be modulated by
a given student’s own dispositional tendency to procrastinate. For example, students
prone to procrastination may prefer to interact with other students also prone to
procrastination, or they may simply have been excluded from groups consisting of
low-procrastinating students. We also find it likely that students will evaluate their
peers in a somewhat egocentric manner, evaluating others differently depending on
Do procrastination-friendly environments make students… 499
their own procrastination level (i.e., a false consensus effect). Hence, students low
in dispositional procrastination should report less procrastination among peers
compared to students high in dispositional procrastination. If correct, such selective
or biased perception of peers may modulate own academic procrastination in
positive or negative directions, the most detrimental scenario being that students
already prone to procrastination may be negatively influenced by procrastinating
peers. Finally, we also included items to assess exposure to the study environment.
Exposure might be a moderating factor for environmental factors. Clearly, students
working extensively at home are less exposed to environmental factors affecting
procrastination. Hence their effect should be reduced.
A total of 215 students (137 females) from a Norwegian university participated.
Mean age was 22.0 years (SD = 4.69). Participants were recruited from three
different fields of study: natural sciences (n = 51, mean age = 22.3), medicine
(n = 113, mean age = 21.1), and social sciences/humanities (51, mean
age = 23.8), during the middle of the fall and spring semesters. In medicine and
natural sciences, the majority of the sample consisted of students in their first year at
the university (81.4 and 70.6% respectively), while in social sciences/humanities
35.3% of students were in their first year of university and the rest studied two or
more semesters. Participants from medicine consisted of a mix of students studying
to become either medical doctors or dentists; participants from natural sciences
consisted of students studying computer programming and engineering as an open
course or part of a bachelor program. Participants from humanities consisted of a
mix of students studying either religion, pedagogics or English language as an open
course or part of a bachelor program.
18.104.22.168 Irrational procrastination scale The IPS (Steel 2010) consists of nine
items (e.g., ‘‘I put things off so long that my well-being or efficiency unnecessarily
suffers’’), three of which are reversely coded (e.g., ‘‘I do everything when I believe
it needs to be done’’). Items are rated on a five-point Likert-scale (1–5), with higher
scores indicating more procrastination. The IPS has good internal consistency with a
Cronbach’s alpha of .93, and a test–retest reliability coefficient of .68 (Steel 2010).
The Norwegian version was translated and validated by Svartdal (2015), with good
internal consistency (Cronbach’s a = .85–.91). In the present study, a = .92.
22.214.171.124 Socially-induced academic procrastination (SIAP) This is a measure of
academic procrastination behavior focusing on self-control in the face of tempting
social activities, given an intention to do academic work. Three items addressed this
construct, e.g., ‘‘When I am at the university to work, I often get distracted by
500 K. Nordby et al.
activities with my fellow students.’’ See Appendix for full list of items. Items are
rated on a five-point Likert-scale (1–5), a higher score indicating higher social
impulsiveness. Item-test correlations ranged from .73 to .81. For these items,
Cronbach’s alpha was .68.1 Evaluation of this and the following constructs was also
performed by confirmatory factor analysis (CFA; Brown 2015; Kline 2016), testing
each measure assuming unidimensional latent constructs. Measurement model fit
was excellent, RMSEA = .000, CFI = 1.000, SRMR = .000.
126.96.36.199 Peer procrastination This construct consisted of four items related to peer
culture to procrastinate (or not to procrastinate), e.g., ‘‘There is a culture among my
fellow students to delay exams-reading and starting writing assignments,’’ and ‘‘My
fellow students rarely delay schoolwork.’’ All items are presented in ‘‘Appendix’’.
Items are rated on a five-point Likert-scale (1–5), higher score implying higher
procrastination. Two items were reversed, giving an overall index with increasing
values implying increasing procrastination among peers. Item-test correlations
ranged from .65 to .74, and Cronbach’s alpha for the selected items was .68. For
peer procrastination, the measurement model fit was good, RMSEA = .043,
CFI = .994, SRMR = .023.
188.8.131.52 Peer influence For this measure, six items related to comparison to others
were included, e.g., ‘‘I work harder when I know I am behind my fellow students’’
and ‘‘When I am late with my schoolwork, I find it reassuring that other students are
also behind in their work.’’ Items are rated on a five-point Likert-scale (1–5), higher
score implying a higher degree of peer influence. In contrast to the peer
procrastination measure, these items do not assess level of procrastination but
instead the regulation of own behavior when comparing to other students. Item-test
correlations ranged from .58 to .75. Cronbach’s alpha for these items was .65, and
measurement model fit to the expected unidimensional construct was acceptable,
RMSEA = .074, CFI = .961, SRMR = .047.
184.108.40.206 Exposure Three items measured the extent to which the student spent time
at the university, as well as social integration, e.g., ‘‘I spend a lot of time at the
university’’ and ‘‘I often hang out with fellow students.’’ Item-test correlations
ranged from .75 to .84. Cronbach’s alpha for these items was .69 and measurement
model fit to the expected unidimensional construct was excellent, RMSEA = .000,
CFI = 1.000, SRMR = .000.
Students were recruited using convenience sampling from courses described in the
methods section. The students present at the lectures were asked to fill out a web-
based questionnaire (www.qualtrics.com) between lectures, while students who
1 The relatively low alphas reported here are probably due to low number of items (e.g., Streiner 2003) as
well as relatively heterogeneous subsamples. Hence, we supplement alphas with estimates of
measurement fits using CFA.
Do procrastination-friendly environments make students… 501
were not attending lectures were asked to follow a link to the questionnaire posted
on the course forum. All were informed that participation was voluntary and
responses were given anonymously. The main project of which the current study is
part received ethical approval from the Regional Ethical Board in Tromsø, Norway
(REK Nord 2014/2313).
3.3 Statistical analysis
Descriptive and correlational analyses were performed to examine the relations
between socially-induced academic procrastination (SIAP), peer procrastination,
peer influence, dispositional procrastination (IPS), as well as exposure. In the next
step, we performed an ANOVA (GLM) with study programs (natural sciences,
medicine, and humanities) and levels of dispositional procrastination (low, medium,
and high) as between-group predictor variables, and SIAP, peer procrastination,
peer influence, and exposure as dependent variables. In this way, profiles could be
compared between study programs and over three procrastination levels. Predicted
differences were tested by contrast analyses. In the third step, these variables were
entered in a regression analysis with SIAP as a dependent variable and the other
variables as predictors, both across academic disciplines and within each discipline.
In these analyses, Statistica (www.statsoft.com) was used.
3.4 Results and discussion
Means, standard deviations, and correlations between the indices are shown in
Table 2. As expected, the correlation between socially-induced academic procras-
tination (SIAP) and IPS was relatively high, r = .48, but the shared variance
between these variables, 22.5%, indicates that most of the variance in SIAP is
independent of IPS. For the three study programs, the IPS – SIAP correlations were
r = .65 (natural science), .37 (medicine), and .46 (humanities). SIAP correlated
relatively equally with the peer influence and peer procrastination measures, r = .40
and .37. The mean IPS score for the natural sciences was 3.02 (SD = .88), for
medicine 2.80 (SD = .72), and for humanities 3.22 (SD = .75), F(2, 212) = 6.91,
p = .001, medicine demonstrating somewhat lower scores compared to the natural
sciences and humanities.2
3.4.1 Socially-induced procrastination (SIAP)
An overall ANOVA demonstrated a significant effect of study environment on
SIAP, F(2, 212) = 9.87, p\ .00, natural sciences demonstrating the lowest SIAP (2.60) and humanities the highest (3.24). SIAP was examined over the three study
fields and over different levels of dispositional procrastination. We expected that
procrastination-friendly academic disciplines affect students differentially, depend-
ing on dispositional procrastination. Thus, at low dispositional procrastination level,
differences in study environment should make little difference for SIAP scores.
2 In an aggregated sample of 1015 Norwegian students, the mean IPS score was 3.20 (Svartdal 2015).
502 K. Nordby et al.
However, at higher procrastination levels, procrastination-friendly study environ-
ments (humanities in the present context) should negatively affect SIAP scores
compared to procrastination-unfriendly environments (natural sciences, medicine).
To test this expectation, we compared mean SIAP scores over IPS level (low B 2.5;
medium[ 2.5\ 3.5; high C 3.5) in the three different fields of study. The first expectation is illustrated in Fig. 1, leftmost panel. Here, low-procrastinating
students (low IPS) demonstrated low SIAP scores regardless of field of study, with
no difference between the humanities versus natural sciences and medicine, F(1,
206) = .47, p = .49. The corresponding contrast at medium IPS level demonstrated
Table 2 Correlations, means, and standard deviations for the measures
Measure M SD 1 2 3 4
1. Peer procrastination 2.66 .63 1.00
2. Peer influence 3.38 .73 .06 1.00
3. Exposure 3.23 .82 -.28* .16* 1.00
4. Socially-induced acad. procrastination (SIAP) 2.85 .78 .40* .37* -.06 1.00
5. Irrational procrastination scale (IPS) 2.94 .79 .37* .33* -.34* .48*
* p\ .01
Fig. 1 Mean scores for socially-induced procrastination (SIAP), peer procrastination, peer influence, and exposure over different levels of procrastination (IPS low, medium, and high) in the three different study programs
Do procrastination-friendly environments make students… 503
a significant difference in SIAP scores, F(1, 206) = 17.96, p\ .00, humanities demonstrating higher scores compared to medicine/natural sciences as predicted.
Also at high IPS level, students from the humanities demonstrated high SIAP scores
compared to medicine and the natural sciences, but not significantly different, F(1,
206) = 1.65, p = .20. Importantly, as medium IPS level is typical procrastination
for students (Svartdal 2015; Svartdal et al. 2016), this result indicates that the study
environment is of importance for the majority of students. For low or non-
procrastinators or high procrastinators (high IPS level), study environment does not
appear to make much of a difference for socially-induced academic procrastination
3.4.2 Peer procrastination
An overall ANOVA of peer procrastination over the three study fields indicated a
significant effect, F(2, 212) = 29.66, p\ .00, reflecting that medicine and natural sciences demonstrated lower means (2.44 and 2.26, respectively) compared to
humanities (3.16). As is apparent from Fig. 1, no difference between the study
programs appeared at low IPS level, F(1, 206) = .40, p = .53. However, as
predicted, contrast analyses indicated that the humanities scored significantly higher
compared to natural sciences and medicine at higher IPS levels, F(1, 206) = 27.12,
p \ .00 (medium IPS) and F(1, 206) = 15.92, p\ .00 (high IPS). Overall peer procrastination scores increased over IPS levels, from 2.44 to 2.95, F(2,
206) = 9.60, p \ .00, and as is apparent from Fig. 1, most of that increase was due to elevated scores in humanities.
3.4.3 Peer influence
The peer influence scores were remarkably stable and high over procrastination
levels in medicine, probably due to a strong pressure and culture within that field of
study to adhere to common medical and ethical values. Overall, medicine
demonstrated a higher level of reported peer influence (3.57 vs. 3.14 in natural
sciences and 3.20 in the humanities), F(2, 212) = 8.63, p\ .00, and peer influence increased over procrastination levels, from 2.70 in low procrastinating students to
3.59 in high procrastinators, F(2, 206) = 24.12, p\ .00. Both effects are seen in Fig. 1. As is also evident from that figure, differences in peer influence between the
three fields of study largely disappeared at the higher IPS levels.
Finally, exposure (our estimate of time spent among fellow students) indicated a
significant reduction over increasing IPS levels, F(2, 206) = 9.29, p\ .00, from 3.32 at low IPS level to 2.75 at high IPS level. This indicates that the high
procrastinator tends to withdraw from interaction with fellow peers rather than
spending more time with them. Note that high level of SIAP among students at
medicine and natural sciences at high IPS level (Fig. 1) was accompanied by a
lower exposure scores. Also note that peer procrastination remained low in these
504 K. Nordby et al.
groups, indicating that peer procrastination bears little relation to heightened SIAP
scores for these students.
3.4.5 Relations among variables
Assuming that peer procrastination, peer influence, IPS, and exposure are possible
predictors of SIAP, we performed a multiple regression analysis to assess this
model. The results indicated that all variables except exposure significantly
predicted SIAP. The results are displayed in Table 3. The overall model was
significant, F(4, 210) = 27.96, p\ .00. Running this model separately for each field of study indicated that these
predictor variables were differentially related to SIAP. Specifically, for the
humanities, peer influence was the only significant predictor in the regression
analysis, for natural science the only significant predictor was IPS (dispositional
procrastination), whereas for medicine peer procrastination, peer influence, and IPS
(dispositional procrastination) all predicted SIAP. These results are shown in
Table 3. The model was significant for each study field, F(4, 46) = 8.78, p\ .00 (natural sciences), F(4, 108) = 10.29, p\ .00 (medicine), and F(4, 46) = 8.34, p\ .00 (humanities).
Table 3 Multiple linear regression results, socially-induced academic procrastination (SIAP), full sample and subsamples
Predictor variables B SE B b P 95% CI B
Peer procrastination .36 .08 .29 .00 .21, .51
Peer influence .24 .07 .23 .00 .11, .37
Exposure .09 .06 .10 .13 -.03, .21
Irrational procrastination scale (IPS) .33 .07 .33 .00 .19, .46
Peer procrastination .36 .12 .26 .00 .13, .59
Peer influence .31 .11 .25 .01 .10, .52
Exposure .13 .09 .13 .14 -.04, .30
Irrational procrastination scale (IPS) .24 .09 .25 .01 .06, .42
Peer procrastination .06 .17 .04 .73 -.28, .40
Peer influence -.02 .12 -.03 .86 -.26, .22
Exposure .08 .10 .11 .43 -.12, .28
Irrational procrastination scale (IPS) .59 .12 .69 .00 .34, .84
Peer procrastination .26 .17 .20 .14 -.08, .59
Peer influence .35 .17 .32 .04 .01, .69
Exposure .14 .14 .14 .31 -.14, .43
Irrational procrastination scale (IPS) .29 .16 .26 .08 -.04, .62
Do procrastination-friendly environments make students… 505
4 General discussion
The present study explored the role of environmental factors in academic
procrastination. Previous research has found teachers and instructors, as well as
task characteristics, to be important exogenous factors in academic delay. We
contribute to this knowledge by examining the role of different academic disciplines
on procrastination behavior. Study 1 examined three academic disciplines—natural
sciences, medicine, and humanities—on six dimensions believed to be important for
academic procrastination. Study 2 extended this line of reasoning by examining
academic procrastination in samples from these disciplines.
The main results can be summarized as follows: Academic procrastination
(SIAP) and peer procrastination (evaluations of other students’ procrastination
habits) were higher in humanities compared to natural sciences and medicine.
Importantly, these differences were modulated by dispositional tendency to
procrastinate. Specifically, students low in dispositional procrastination (as defined
by low scores on the IPS) appeared to be little affected by differences in study
program; they demonstrated little socially-induced academic procrastination and
reported peers to procrastinate little. In contrast, students at higher dispositional
procrastination levels reported higher degrees of SIAP, but highly dependent on
study program. Thus, for students at medium to high levels of dispositional
procrastination, humanities indicated significantly higher degree of SIAP compared
to students in medicine and natural sciences, in addition to reporting higher degree
of peer procrastination. As students at this dispositional level of procrastination
constitute the majority of the student population, these results suggest that social
and environmental factors potentially are important for a large number of students.
To our knowledge, these findings are the first to demonstrate that students at the
same level of dispositional procrastination (medium IPS) are differentially
influenced by environmental factors related to academic procrastination behavior.
Students at the humanities demonstrated here a higher level of SIAP, as well as
evaluating their peers as procrastinating more than students in both medicine and
natural sciences. It might be argued that these results may be explained in terms of
selection, students at the humanities preferring study directions that permit a higher
degree of procrastination. Support for this hypothesis is the fact that the student
groups differed in mean dispositional procrastination scores, students from
humanities scoring somewhat higher compared to the other two groups. However,
note in Fig. 1 that students are compared at similar procrastination levels, and that
SIAP levels are very similar among the groups at low and high procrastination
levels; the student groups differ in terms of SIAP only at medium level of
dispositional procrastination. We interpret this as quite a strong hint that students at
medium procrastination level differ either because of procrastinating peers (as
indicated by correlated peer procrastination scores in these students) and/or study
program differences. In the present study, it is not possible to separate these sources,
but it is reasonable to believe that they are intimately interwoven, self-regulation
probably being a basic causal mechanism with environmental factors being a
facilitator for less self-regulated students. Several of the dimensions evaluated by
506 K. Nordby et al.
our independent sample (Table 1) are known to facilitate procrastination (Steel
2007) and, as shown in the table, humanities were evaluated as scoring significantly
higher on these facilitating factors compared to medicine and natural sciences.
It should be noted that procrastination is a term with negative connotations,
maybe more so in some contexts compared to others. For example, it is possible that
there is a cultural difference between natural science and medicine on the one hand,
and humanities on the other, implying that delay is differentially perceived as
unwanted and detrimental versus productive and positive. Consequently, this might
imply that our measure of SIAP may wrongly classify behavioral episodes among
students in the humanities as ‘‘procrastination’’ rather than as ‘‘discussion’’ or
‘‘reflection.’’ If correct, this hypothesis would imply a lower correlation between
SIAP and dispositional procrastination in the humanities subgroup compared to
medicine and natural sciences. However, this correlation was high in the humanities
subgroup (r = .46), lower in medicine (r = .37) and highest in natural sciences
(r = .65). Also note that SIAP scores among low and high procrastinators were very
similar between student groups, further suggesting that these students demonstrate a
relatively similar understanding of the SIAP items. Hence, although we recognize
the need for cross-cultural validation of procrastination scales (e.g., Mann 2016;
Svartdal et al. 2016), we believe that SIAP as reported in the present study in fact
reflects unwanted academic delay.
Our results also indicate that determinants of socially-induced academic
procrastination may differ between the student groups. Thus, whereas SIAP in the
natural sciences subgroup was related to dispositional procrastination (IPS), with
little relation to peer procrastination or peer influence, the picture was more
complex in medicine and humanities. In both the latter cases, both peer
procrastination and peer influence explained significant parts of the variance
associated with SIAP. This indicates that differences among study regimes affect the
way students interact and hence how academic procrastination is best explained.
Thus, in the natural sciences subgroup, a dispositional explanation of SIAP seems
appropriate, whereas in the medicine and humanities subgroups environmental and
situational explanations must complement a dispositional explanation.
As for peer influence, no differences between the study programs were observed
for students with middle and high levels of dispositional procrastination; at low
levels of dispositional procrastination, however, medicine students reported to be
significantly more influenced by their peers. This difference is reasonable, given the
high demands and grade pressure in medicine studies, as well as strong pressure to
adhere to common medical and ethical values. Overall, peer influence could have
beneficial or detrimental effects, depending on peer procrastination level. The
present results indicate, however, that both peer influence and peer procrastination
are positively related to SIAP, the most negative scenario being a student reporting
high peer influence among high procrastinating peers. The correlation between IPS
and peer procrastination (r = .36; see Table 2) may indicate a bias in perception of
others, alternatively that students select peers with procrastination habits similar to
themselves, thus creating micro-environments that facilitate procrastination. Of
note, this correlation differed among the study programs, with strongest correlation
(r = .41) in the humanities.
Do procrastination-friendly environments make students… 507
Our survey to assess procrastination-relevant dimensions among study programs
indicates that the three programs differ in significant ways on important dimensions.
At least two of these dimensions, structured course progression and freedom in the
study situation, are definitely procrastination-friendly factors, and they differed in
this case markedly between the study programs. Importantly, similar differences
were observed in respondents who were students at the programs themselves,
indicating that students at different study programs have different expectations,
beliefs, and attitudes that may represent strong facilitators for academic procras-
tination. Future research should explore these factors in more detail, along with
different avenues of prevention and intervention measures to counteract their
detrimental effects. For example, if freedom in the study situation is highly valued
in some study programs, what measures can be taken to prevent this factor from
creating unwanted academic procrastination?
4.1 Limitations and future studies
First, the present study focused on one form of academic procrastination behavior,
i.e. being distracted from planned academic work by peers, and included only a
limited sample of environmental factors possibly contributing to such academic
procrastination behavior. Future studies should include additional and more diverse
measures to enable more precise conclusions about the exact nature of social and
environmental features related to academic procrastination. Second, it should be
noted that in Norway, like in many other countries, medicine is regarded as high
prestige study with high grade requirements to enter. Although previous research
has found only small differences in grades and intelligence between high and low
procrastinators (Steel 2007), it is likely that medical students represent a group of
students who differ from natural sciences and humanities students in their self-
regulation abilities. This again speaks for the inclusion of other study programs.
Third, the relatively low sample size of the present study indicates that conclusions
should be interpreted with some caution. Finally, as pointed out by many authors
examining peer effects (e.g., Eisenkopf 2009), it is difficult to examine how students
self-select into smaller peer groups within each field of study. Such micro-
environments might have an unexpected and opposite effect of what could be
expected in an overall environment, speaking for a closer examination of the role of
subgroups within larger student groups.
• There is a culture among my fellow students to delay exams-reading and starting writing assignments/Det er en kultur blant mine medstudenter for å utsette
eksamenslesing og oppgaveskriving
508 K. Nordby et al.
• My fellow students rarely delay schoolwork/Mine medstudenter utsetter sjelden skolearbeid
• Many of my fellow students are relaxed about their schoolwork/Mange av mine medstudenter er avslappet til skolearbeid
• There is a culture among my fellow students to get started early and finish early with schoolwork/Det er en kultur blant mine medstudenter for å komme tidlig i
gang og bli ferdig med skolearbeid
• When I am late with my schoolwork, I find it reassuring that other students are also behind on their work/Når jeg er sent ute med skolearbeid, opplever jeg det
betryggende at andre studenter også henger etter
• When other students around me delay working on their schoolwork, it gets easier for me to delay as well/Når jeg opplever at andre studenter rundt meg
utsetter skolearbeid, blir det lettere for meg å utsette
• I work more on my schoolwork when I know my fellow students are working as well/Jeg jobber mer med skolearbeid når jeg vet andre medstudenter også jobber
• I envy those students who get started early on their exams-reading and written assignments/Jeg misunner de studenter som kommer tidlig i gang med
eksamenslesing eller oppgaveskriving
• I work harder when I know I am behind my fellow students on schoolwork/Jeg jobber mer når jeg vet at jeg ligger etter mine medstudenter
• I try to work as much as my fellow students with schoolwork/Jeg prøver å jobbe omtrent like mye som mine medstudenter med skolearbeid
• I spend a lot of time on the university/Jeg tilbringer mye tid på universitetet • I work a lot with schoolwork together with my fellow students/Jeg jobber mye
med skolearbeid sammen med mine medstudenter
• I am often social with my fellow students/Jeg er ofte sosial med mine medstudenter
Socially-induced academic procrastination (SIAP)
• When I am at the university to work, I often get distracted by activities with my fellow students/Når jeg er på universitetet for å jobbe, blir jeg ofte distrahert av
aktiviteter med mine medstudenter
Do procrastination-friendly environments make students… 509
• If I have to choose between schoolwork and being together with friends, I usually choose to be with friends/Hvis jeg må velge mellom skolearbeid og være
sammen med venner, velger jeg som oftest å være med sammen med venner
• When I am with other students to do schoolwork, we often end up doing other things instead/Når jeg er sammen med andre studenter for å jobbe med
skolearbeidet, ender det ofte opp med at vi gjøre andre ting i stedet
Ackerman, D. S., & Gross, B. L. (2005). My instructor made me do it: Task characteristics of
procrastination. Journal of Marketing Education, 27(1), 5–13. doi:10.1177/0273475304273842.
Alexander, E. S., & Onwuegbuzie, A. J. (2007). Academic procrastination and the role of hope as a
coping strategy. Personality and Individual Differences, 42(7), 1301–1310. doi:10.1016/j.paid.2006.
Antony, M. M., Purdon, C. L., Huta, V., & Swinson, R. P. (1998). Dimensions of perfectionism across the
anxiety disorders. Behaviour Research and Therapy, 36(12), 1143–1154. doi:10.1016/S0005-
Ariely, D., & Wertenbroch, K. (2002). Procrastination, deadlines, and performance: Self-control by
precommitment. Psychological Science, 13(3), 219–224. doi:10.1111/1467-9280.00441.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review,
84(2), 191. doi:10.1037/0033-2.
Becher, T. (1994). The significance of disciplinary differences. Studies in Higher Education, 19(2),
Blunt, A. K., & Pychyl, T. A. (2000). Task aversiveness and procrastination: A multi- dimensional
approach to task aversiveness across stages of personal projects. Personality and Individual
Differences, 28(1), 153–167. doi:10.1016/S0191-8869(99)00091-4.
Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York City: The
Brownlow, S., & Reasinger, R. D. (2000). Putting off until tomorrow what is better done today: Academic
procrastination as a function of motivation toward college work. Journal of Social Behavior and
Personality, 15(5), 15.
Cao, L. (2012). Differences in procrastination and motivation between undergraduate and graduate
students. Journal of the Scholarship of Teaching and Learning, 12(2), 39–64.
Carrell, S. E., Fullerton, R. L., & West, J. E. (2009). Does your cohort matter? Measuring peer effects in
college achievement. Journal of Labor Economics, 27(3), 439–464. doi:10.1086/600143.
Coleman, J. S., & Department of Health USA. (1966). Equality of educational opportunity (Vol. 2).
Washington, DC: US Department of Health, Education, and Welfare, Office of Education.
Corkin, D. M., Yu, S. L., Wolters, C. A., & Wiesner, M. (2014). The role of the college classroom climate
on academic procrastination. Learning and Individual Differences, 32, 294–303. doi:10.1016/j.
Darling-Hammond, L. (2000). Teacher quality and student achievement: A review of state policy
evidence. Education Policy Analysis Archives. doi:10.14507/epaa.v8n1.2000.
Dewitte, S., & Lens, W. (2000). Procrastinators lack a broad action perspective. European Journal of
Personality, 14(2), 121–140.
Eisenkopf, G. (2009). Peer effects, motivation, and learning. Economics of Education Review, 29(3),
Ellis, A., & Knaus, W. (1977). Overcoming procrastination. New York: Signet.
Falk, A., & Ichino, A. (2006). Clean evidence on peer effects. Journal of Labor Economics, 24(1), 39–57.
Fee, R. L., & Tangney, J. P. (2000). Procrastination: A means of avoiding shame or guilt? Journal of
Social Behavior and Personality, 15(5), 167.
510 K. Nordby et al.
Fernie, B. A., Spada, M. M., Nikčević, A. V., Georgiou, G. A., & Moneta, G. B. (2009). Metacognitive
beliefs about procrastination: Development and concurrent validity of a self-report questionnaire.
Journal of Cognitive Psychotherapy, 23(4), 283–293. doi:10.1891/0889-83220.127.116.113.
Ferrari, J. R., Johnson, J. L., & McCown, W. G. (1995). Procrastination Research. In J. R. Ferrari, J.
L. Johnson, & W. G. McCown (Eds.), Procrastination and task avoidance: Theory, research, and
treamtent (pp. 41–46). New York: Plenum Press.
Ferrari, J. R., & Patel, T. (2004). Social comparisons by procrastinators: Rating peers with similar or
dissimilar delay tendencies. Personality and Individual Differences, 37(7), 1493–1501. doi:10.1016/
Festinger, L. (1964). Conflict, decision, and dissonance (Vol. 3). Stanford: Stanford University Press.
Flett, G. L., Blankstein, K. R., & Martin, T. R. (1995). Procrastination, negative self-evaluation, and stress
in depression and anxiety. In J. R. Ferrari, J. L. Johnson, & W. G. McCown (Eds.), Procrastination
and task avoidance: Theory, research, and treatment (pp. 41–46). New York: Plenum Press.
Foster, G. (2006). It’s not your peers, and it’s not your friends: Some progress toward understanding the
educational peer effect mechanism. Journal of Public Economics, 90(8), 1455–1475. doi:10.1016/j.
Foster, G., & Frijters, P. (2010). Students’ beliefs about peer effects. Economics Letters, 108(3), 260–263.
Grunschel, C., Patrzek, J., & Fries, S. (2013). Exploring reasons and consequences of academic
procrastination: An interview study. European Journal of Psychology of Education, 28(3), 841–861.
Gustavson, D. E., Miyake, A., Hewitt, J. K., & Friedman, N. P. (2014). Genetic relations among
procrastination, impulsivity, and goal-management ability implications for the evolutionary origin
of procrastination. Psychological Science, 25(6), 1178–1188. doi:10.1177/0956797614526260.
Hoxby, C. M., & Weingarth, G. (2005). Taking race out of the equation: School reassignment and the
structure of peer effects (No. 7867). Working paper.
Kline, R. B. (2016). Principles and practice of structural equation modeling. New York City: Guilford
Klingsieck, K. B., Grund, A., Schmid, S., & Fries, S. (2013). Why students procrastinate: A qualitative
approach. Journal of College Student Development, 54(4), 397–412. doi:10.1353/csd.2013.0060.
Lamwers, L. L., & Jazwinski, C. H. (1989). A comparison of three strategies to reduce student
procrastination in PSI. Teaching of Psychology, 16(1), 8–12. doi:10.1207/s15328023top1601_2.
Lee, E. (2005). The relationship of motivation and flow experience to academic procrastination in university
students. The Journal of Genetic Psychology, 166(1), 5–15. doi:10.3200/GNTP.166.1.5-15.
Lyle, D. S. (2007). Estimating and interpreting peer and role model effects from randomly assigned social
groups at West Point. The Review of Economics and Statistics, 89(2), 289–299. doi:10.1162/rest.89.
Mann, L. (2016). Procrastination revisited: A commentary. Australian Psychologist, 51, 47–51. doi:10.
Ozer, D. J., & Benet-Martinez, V. (2006). Personality and the prediction of consequential outcomes.
Annual Review of Psychology, 57, 401–421. doi:10.1146/annurev.psych.57.102904.190127.
Patrzek, J., Grunschel, C., & Fries, S. (2012). Academic procrastination: The perspective of university
counsellors. International Journal for the Advancement of Counselling, 34(3), 185–201. doi:10.
Pychyl, T. A., Lee, J. M., Thibodeau, R., & Blunt, A. (2000a). Five days of emotion: An experience
sampling study of undergraduate student procrastination. Journal of Social Behavior and
Personality, 15(5), 239.
Pychyl, T. A., Morin, R. W., & Salmon, B. R. (2000b). Procrastination and the planning fallacy: An
examination of the study habits of university students. Journal of Social Behavior and Personality,
Rozental, A., & Carlbring, P. (2014). Understanding and treating procrastination: A review of a common
self-regulatory failure. Psychology, 5(13), 1488. doi:10.4236/psych.2014.513160.
Sacerdote, B. (2011). Peer effects in education: How might they work, how big are they and how much do
we know thus far? Handbook of the Economics of Education, 3, 249–277. doi:10.1016/b978-0-444-
Schachter, S., Christenfeld, N., Ravina, B., & Bilous, F. (1991). Speech disfluency and the structure of
knowledge. Journal of Personality and Social Psychology, 60(3), 362. doi:10.1037/0022-3514.60.3.
Do procrastination-friendly environments make students… 511
Scher, S. J., & Ferrari, J. R. (2000). The recall of completed and noncompleted tasks through daily logs to
measure procrastination. Journal of Social Behavior and Personality, 15(5), 255.
Schraw, G., Wadkins, T., & Olafson, L. (2007). Doing the things we do: A grounded theory of academic
procrastination. Journal of Educational Psychology, 99(1), 12. doi:10.1037/0022-0618.104.22.168.
Senécal, C., Lavoie, K., & Koestner, R. (1997). Trait and situational factors in procrastination: An
interactional model. Journal of Social Behavior and Personality, 12(4), 889.
Sirois, F. M. (2014). Procrastination and stress: Exploring the role of self-compassion. Self and Identity,
13(2), 128–145. doi:10.1080/15298868.2013.763404.
Solomon, L. J., & Rothblum, E. D. (1984). Academic procrastination: Frequency and cognitive-
behavioral correlates. Journal of Counseling Psychology, 31(4), 503–509. doi:10.1037/0022-0167.
Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential
self-regulatory failure. Psychological Bulletin, 133(1), 65. doi:10.1037/0033-2909.133.1.65.
Steel, P. (2010). Arousal, avoidant, and decisional procrastinators: Do they exist? Personality and
Individual Differences, 48(8), 926–934. doi:10.1016/j.paid.2010.02.025.
Stinebrickner, R., & Stinebrickner, T. R. (2006). What can be learned about peer effects using college
roommates? Evidence from new survey data and students from disadvantaged backgrounds. Journal
of Public Economics, 90(8), 1435–1454. doi:10.1016/j.jpubeco.2006.03.002.
Stöber, J., & Joormann, J. (2001). Worry, procrastination, and perfectionism: Differentiating amount of
worry, pathological worry, anxiety, and depression. Cognitive Therapy and Research, 25(1), 49–60.
Streiner, D. L. (2003). Starting at the beginning: An introduction to coefficient alpha and internal
consistency. Journal of Personality Assessment, 80(1), 99–103. doi:10.1207/s15327752jpa8001_18.
Svartdal, F. (2015). Measuring procrastination: Psychometric properties of the Norwegian versions of the
irrational procrastination scale (IPS) and the pure procrastination scale (PPS). Scandinavian Journal
of Educational Research. doi:10.1080/00313831.2015.1066439.
Svartdal, F., Pfuhl, G., Nordby, K., Foschi, G., Klingsieck, K. B., Rozental, A., et al. (2016). On the
measurement of procrastination: Comparing two scales in six European countries. Frontiers in
Psychology, 7, 1307. doi:10.3389/fpsyg.2016.01307.
Tuckman, B., & Schouwenburg, H. C. (2004). Behavioral interventions for reducing procrastination
among university students. In H. C. Schouwenburg, C. H. Lay, T. A. Pychyl, & J. R. Ferrari (Eds.),
Counseling the procrastinator in academic settings (pp. 91–103). Washington, DC: American
Psychological Association. doi:10.1037/10808-007.
van Eerde, W. (2000). Procrastination: Self regulation in initiating aversive goals. Applied Psychology,
49(3), 372–389. doi:10.1111/1464-0597.00021.
Wesp, R. (1986). Reducing procrastination through required course involvement. Teaching of
Psychology, 13(3), 128–130. doi:10.1207/s15328023top1303_6.
Zajonc, R. B., & Sales, S. M. (1966). Social facilitation of dominant and subordinate responses. Journal
of Experimental Social Psychology, 2(2), 160–168. doi:10.1016/0022-1031(66)90077-1.
Ziesat, H. A., Rosenthal, T. L., & White, G. M. (1978). Behavioral self-control in treating procrastination
of studying. Psychological Reports, 42(1), 59–69. doi:10.2466/pr0.1922.214.171.124.
Zimmerman, D. J. (2003). Peer effects in academic outcomes: Evidence from a natural experiment.
Review of Economics and Statistics, 85(1), 9–23. doi:10.1162/003465303762687677.
Kent Nordby licensed psychologist, PhD student, Department of Psychology, UiT the Arctic University of Norway. Interests: Procrastination, self-regulation.
Katrin B. Klingsieck PhD, professor, Department of Psychology, Paderborn University, Germany. Interests: self-regulation and self-regulated learning (e.g., procrastination, academic writing competence),
professional competence of teachers and teacher education, didactics in higher education.
Frode Svartdal PhD, professor, Department of Psychology, UiT the Arctic University of Norway. Interests: Cognition, learning, verbal control, self-regulation, procrastination, social competence training,
psychometrics, research methods.
512 K. Nordby et al.
Reproduced with permission of copyright owner. Further
reproduction prohibited without permission.