Behavior Modification

Do procrastination-friendly environments make students delay unnecessarily?

Kent Nordby1 • Katrin B. Klingsieck2 •

Frode Svartdal1

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 frode.svartdal@uit.no

1 Department of Psychology, UiT the Arctic University of Norway, 9037 Tromsø, Norway

2 Department of Psychology, Universität Paderborn, Paderborn, Germany

123

Soc Psychol Educ (2017) 20:491–512

DOI 10.1007/s11218-017-9386-x

1 Introduction

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.

2000).

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

2012).

492 K. Nordby et al.

123

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

123

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.

123

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.

1.2 Evaluation

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

123

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.

123

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.

2.1 Method

2.1.1 Participants

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.

2.1.2 Material

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

123

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.

2.2 Results

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).

2.3 Discussion

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.

123

program potentially more procrastination-friendly compared to both medicine and

natural sciences.

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

sciences).

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

123

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.

3.1 Method

3.1.1 Participants

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.

3.1.2 Materials

3.1.2.1 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.

3.1.2.2 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.

123

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.

3.1.2.3 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.

3.1.2.4 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.

3.1.2.5 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.

3.2 Procedure

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

123

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.

123

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

123

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

(SIAP).

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.

3.4.4 Exposure

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.

123

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

Full sample

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

Medicine

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

Natural sciences

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

Humanities

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

123

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.

123

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

123

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.

Appendix

Peer procrastination

• 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.

123

• 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

Peer influence

• 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

med det

• 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

Exposure

• 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

123

• 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

References

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.

10.008.

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-

7967(98)00083-7.

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),

151–161. doi:10.1080/03075079412331382007.

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

Guilford Press.

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.

lindif.2014.04.001.

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),

364–374. doi:10.1016/j.econedurev.2009.08.005.

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.

doi:10.1086/497818.

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.

123

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:10.1891/0889-8391.23.4.283.

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/

j.paid.2004.02.006.

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.

jpubeco.2005.12.001.

Foster, G., & Frijters, P. (2010). Students’ beliefs about peer effects. Economics Letters, 108(3), 260–263.

doi:10.1016/j.econlet.2010.05.020.

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.

doi:10.1007/s10212-012-0143-4.

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

publications.

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.

2.289.

Mann, L. (2016). Procrastination revisited: A commentary. Australian Psychologist, 51, 47–51. doi:10.

1111/ap.12208.

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.

1007/s10447-012-9150-z.

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,

15(5), 135.

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-

53429-3.00004-1.

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.

362.

Do procrastination-friendly environments make students… 511

123

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:10.1037/0022-0663.99.1.12.

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.

31.4.503.

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.

doi:10.1023/A:1026474715384.

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/pr0.1978.42.1.59.

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.

123

Reproduced with permission of copyright owner. Further

reproduction prohibited without permission.