Available online at:
https://cc.arcabc.ca/islandora/object/cc%3Apsycjournal

J Camosun Psyc Res. (2020). Vol. 2, pp. 45-50.
Submitted Fall 2019; accepted July 2020.

How to minimize procrastination.
Authors: Danny D. Badke* and Pamir Karpuzcu
Supervising Instructor: Michael Pollock, Psyc 110 (“Experimental Psychology”)
Department of Psychology, Camosun College, 3100 Foul Bay Road, Victoria, BC, Canada V8P 5J2
*Corresponding author email: dannybadke@gmail.com

ABSTRACT
Procrastination is a barrier to achieving personal goals. This project sought to test the
effectiveness of implementation intentions (plan for a time and location connected to an action),
purposeful delay (delaying tasks to increase motivation), and intrinsic reasons (behavior that is
driven by personal internal rewards) on procrastination. Our research consisted of two 2-week
studies on ourselves: a non-experimental study examining the correlations between natural
variations in the variables described above and an experimental study specifically testing the
effect that implementation intentions has upon procrastination. Our correlational results
supported the work of these previous studies by showing the ability to predict the degree of
procrastination based on the amount of implantation intentions and intrinsic reasons that
naturally occurred, with implementation intentions having the highest correlation with
procrastination. However, our experimental results did not support a causal role of
implementation intentions in minimizing procrastination. It is speculated that these results
occurred because of the increased number of times implementation intentions were used and
procrastination was measured and due to influences from external events during trials.
1. Introduction
Procrastination is problematic for
students, who are constantly required to
attain a high level of academic progress, and
also for those in the workplace and home.
This barrier has led to much research on
methods of minimizing procrastination.
Within our own research, we sought to
examine the effectiveness of three possible
solutions to minimizing procrastination,
with our hypotheses derived from the results
of three previous studies.
Our first hypothesis was based on a study
by Owens et al. (2008) which surveyed 152
randomly sampled university students. This
study found that students who form

implementation intentions (plan a time and
location connected to an action) are greater
than 40% more likely to act upon their plan
regardless of participants’ self-rated scale of
high or low procrastination. From these
results, we hypothesized that
implementation intentions would minimize
procrastination.
Our second hypothesis was based on a
study by Pincten et al. (2019) which
surveyed 1605 first-year science and
engineering students from a university in
Flanders, Belgium over a one-year period.
This study found that delaying tasks to
increase motivation (known as purposeful
delay) does not help students meet
deadlines. From these results, we
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Badke, Karpuzcu - J Camosun Psyc Res. (2020). Vol. 2, pp. 45-50.

hypothesized that intentionally delaying
tasks to would not aid in academic success.
Our third hypothesis was based on a
study by Senécal et al. (1995) which
surveyed 498 French-Canadian students
from a junior college in the Montreal area.
This study found that having amotivation
(no a sense of purpose or expectation of
reward) and external regulation (behaviour
controlled by rewards or imposed by others)
self-regulation styles are each positively
associated with procrastination while having
an intrinsic regulation (behavior that is
driven by personal internal rewards) selfregulation style is remarkably negatively
associated with procrastination in everyday
life. From these results, we hypothesized
that procrastination can be minimized by
pursuing intrinsic reasons for completing
tasks.
The present research undertook to
discover which of these three hypotheses
was most strongly supported in a withinsubjects correlational study and then to
further test that hypothesis in a double-blind
experimental study in order to examine if a
causal relationship exists.
2. Methods

2.2.1 Correlational Study Methods
We operationally defined the outcome
variable, procrastination, as time spent on
trivial tasks (postponing, hesitating,
distracting, or wasted time), as opposed to
time spent on needed tasks (work, play,
rest). The daily amount of self-declared
procrastination was measured on a
procrastination scale of 1-10: 1) Less than
10 minutes; 2) 10-19 minutes; 3) 20-29
minutes; 4) 30-39 minutes; 5) 40-49
minutes; 6) 50-59 minutes; 7) 60-69
minutes; 8) 70-79 minutes; 9) 80-89
minutes; and 10) more than 90 minutes.
The degree of each predictor variable was
quantitatively scored in ourselves by the
daily measure of the number of times it
occurred. We operationally defined an
implementation intention as deciding a time
and location in which you will begin a task.
We operationally defined purposeful
delay/active procrastination as intentionally
delaying a task to increase motivation to
complete it (increased pressure by doing a
preferred task first). Finally, we
operationally defined intrinsic reasons as
behavior that is driven by personal internal
rewards, and included for this the use of
personal reward (of play or rest) to motivate
us to begin tasks.

2.1 Participants
The authors were the only participants in
this study. Both were first-year students at
Camosun College (Victoria, B.C., Canada)
pursuing an Associate of Arts Degree in
Psychology before transferring for further
study at the University of Victoria. Both
participants were engaged in full-time study
(without additional part-time employment)
during the duration of this study.
2.2 Materials and Procedure

2.2.2 Experimental Study Methods
We conducted our experimental research
over a two-week period including six
experimental days and six control days. On
experimental days, at the start of the day (or
prior to any study), we set aside a fifteenminute period to create implementation
intentions (a plan for time and location
connected to an action) for each required
task for that day (with a minimum
requirement of two tasks per experimental
day). Implementation intentions related to
required class periods were not to be
observed as part of our experimental
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research for this project. On control days, no
implementation intentions were created.
As a counterbalancing procedure to
reduce the possibility of order effects, we
conducted our experiment through random
assignment. This was done by giving each
participant a set of twelve playing cards (six
red, six black). At the beginning of each day,
participants drew one card from the shuffled
deck. Red cards initiated an experimental
day and black cards initiated a control day.
Results for this study were inputted
daily through an online diary over a
fourteen-day period respectively for both the
correlational study and the experimental
study.
3. Results
3.1 Correlational Study Results
As seen in Table 1, both implementation
intentions and intrinsic reasons were found
to be statistically significant. In our pooled
raw data, we found intrinsic reasons to be
the best predictor of procrastination (r = 0.60, p < 0.001), where greater amounts of
the intrinsic reasons predicted less
procrastination. However, within our pooled
standardized data, implementation intentions
was the better predictor of procrastination (r
= -0.50, p < 0.007; see Figure 1) and the
correlation between intrinsic reasons and

procrastination, although still statistically
significant, was just slightly less (r = -0.45,
p < 0.016). As predicted within our original
hypothesis, purposeful delay did not have
statistical significance in minimizing
procrastination within our pooled
standardized data (r = -0.12, p < 0.567).
3.2 Experimental Study Results
Due to the strong correlation we found
between implementation intentions and
procrastination, we conducted a further
experimental study to test whether a causal
relationship exists between these two
variables. However, as shown in Figure 2
and Table 2, our experimental results found
no statistically significant effect of
implementation intentions upon
procrastination (t = 1.52, p < 0.143).
4. Discussion
Due to the results of our experimental
study, we found no significant support for
our hypothesis that implementation
intentions (having a plan for time and
location connected to an action) minimize
procrastination. Although our correlational
study found the use of implementation
intentions and intrinsic reasons negatively
correlated with procrastination levels, our
experimental study found no support for the

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use of implementation intentions for this
purpose.
One possible explanation for the
discrepancy seen between the lack of
significant results for implementation
intentions in our experimental study and the
significant results reported by previous
experimental studies could be in the number
of times implementation intentions were

used and procrastination was measured. For
example, Owens et al (2008) only measured
one time in each participant the ability to
keep to an appointment when using
implementation intentions. In contrast, our
participants used as many as four
implementation intentions in the same
location (but with different times)
consecutively. For this reason, although the

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implementation intentions may be effective
in beginning a task (to keep an
appointment), they do not appear to
minimize procrastination that may have
occurred between or during multiple
consecutive tasks. This effect could also
have been affected by how our study
measured levels of procrastination for
multiple assignments at the end of the day,
whereas Owens et al, only focused on one
assignment at a time. To test this, future
studies could examine whether
implementation intentions are not effective
when used consecutively in one location
(with different times).
Slight individual discrepancies could be
seen between the experimental results of the
two participants in the current study. While
Subject #1’s results attained statistical
significance (p < 0.028), Subject #2’s results
did not (p < 0.273), and when pooled
together our results were no longer
statistically significant (p < 0.204). Upon
closer inspection of these results, we noted
that Subject #2 had a procrastination score

of 3 (20-29 minutes) on one control day
which caused these results to no longer have
statistical significance. When reviewing why
this was the case, Subject #2 reported that he
had so many assigned tasks for that day that
he had “no time left to procrastinate.” Thus
on that trial it appears that alternative
reasons (pressure, intrinsic, or otherwise)
required him to complete tasks with
minimum procrastination regardless of the
use of implementations. To avoid this
possible source of error, future studies could
better control the influences of external
events during trials.
In conclusion, although our correlational
results supported and inverse relationship of
procrastination with both implementation
intentions and intrinsic reasons, our failure
to obtain statistically significant results in
our experimental study limits our ability to
draw any causal conclusions about the use of
implementation intentions to minimize
procrastination.

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References
Owens, S. G., Bowman, C. G., & Dill, C. A.
(February 01, 2008). Overcoming
Procrastination: The Effect of
Implementation Intentions. Journal of
Applied Social Psychology, 38, 2, 366384.
Pinxten, M., De Laet, T., Van Soom, C.,
Peeters, C., & Langie, G. (2019).
Purposeful delay and academic
achievement: A critical review of the
Active Procrastination Scale. Learning
and Individual Differences, 73, 42–51.
Retrieved from: https://doiorg.libsecure.camosun.bc.ca:2443/10.101
6/j.lindif.2019.04.010
Senécal, C., Koestner, R., & Vallerand, R. J.
(1995). Self-regulation and academic
procrastination. The Journal of Social
Psychology, 135(5), 607-619.
doi:10.1080/00224545.1995.9712234

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