ArticlePDF Available

Abstract and Figures

Procrastination refers to the delay or postponement of a task or decision and is often conceptualised as a failure of self-regulation. Recent research has suggested that procrastination could be delineated into two domains: intentional and unintentional. In this two-study paper, we aimed to develop a measure of unintentional procrastination (named the Unintentional Procrastination Scale or the ‘UPS’) and test whether this would be a stronger marker of psychopathology than intentional and general procrastination. In Study 1, a community sample of 139 participants completed a questionnaire that consisted of several items pertaining to unintentional procrastination that had been derived from theory, previous research, and clinical experience. Responses were subjected to a principle components analysis and assessment of internal consistency. In Study 2, a community sample of 155 participants completed the newly developed scale, along with measures of general and intentional procrastination, metacognitions about procrastination, and negative affect. Data from the UPS were subjected to confirmatory factor analysis and revised accordingly. The UPS was then validated using correlation and regression analyses. The six-item UPS possesses construct and divergent validity and good internal consistency. The UPS appears to be a stronger marker of psychopathology than the pre-existing measures of procrastination used in this study. Results from the regression models suggest that both negative affect and metacognitions about procrastination differentiate between general, intentional, and unintentional procrastination. The UPS is brief, has good psychometric properties, and has strong associations with negative affect, suggesting it has value as a research and clinical tool.
This content is subject to copyright. Terms and conditions apply.
The Unintentional Procrastination Scale
Bruce A. Fernie
1,2
Zinnia Bharucha
1
Ana V. Nikc
ˇevic
´
3
Marcantonio M. Spada
4
Published online: 11 August 2016
ÓThe Author(s) 2016. This article is published with open access at Springerlink.com
Abstract Procrastination refers to the delay or postponement of a task or decision
and is often conceptualised as a failure of self-regulation. Recent research has
suggested that procrastination could be delineated into two domains: intentional and
unintentional. In this two-study paper, we aimed to develop a measure of unin-
tentional procrastination (named the Unintentional Procrastination Scale or the
‘UPS’) and test whether this would be a stronger marker of psychopathology than
intentional and general procrastination. In Study 1, a community sample of 139
participants completed a questionnaire that consisted of several items pertaining to
unintentional procrastination that had been derived from theory, previous research,
and clinical experience. Responses were subjected to a principle components
analysis and assessment of internal consistency. In Study 2, a community sample of
155 participants completed the newly developed scale, along with measures of
general and intentional procrastination, metacognitions about procrastination, and
negative affect. Data from the UPS were subjected to confirmatory factor analysis
and revised accordingly. The UPS was then validated using correlation and
regression analyses. The six-item UPS possesses construct and divergent validity
and good internal consistency. The UPS appears to be a stronger marker of psy-
chopathology than the pre-existing measures of procrastination used in this study.
Results from the regression models suggest that both negative affect and
metacognitions about procrastination differentiate between general, intentional, and
&Bruce A. Fernie
bruce.fernie@kcl.ac.uk
1
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s
College London, Henry Wellcome Building, De Crespigny Park, London SE5 8AF, UK
2
HIV Liaison Service, South London and Maudsley NHS Foundation Trust, London, UK
3
Kingston University, Kingston upon Thames, UK
4
London South Bank University, London, UK
123
J Rat-Emo Cognitive-Behav Ther (2017) 35:136–149
DOI 10.1007/s10942-016-0247-x
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
unintentional procrastination. The UPS is brief, has good psychometric properties,
and has strong associations with negative affect, suggesting it has value as a
research and clinical tool.
Keywords Procrastination Metacognition Unintentional procrastination
Depression Anxiety
Introduction
Procrastination is a term familiar to many. It refers to the postponement or
avoidance of starting, engaging in, and completing a task or a decision-making
process. It is not a behaviour limited to students, despite high estimates of its
prevalence in this population (up to 70 % according to Ellis and Knaus 1977). For
example, the prevalence of procrastination has been found to be as high as 20 % in
an adult sample (Harriott and Ferrari 1996). Within psychology, procrastination has
been conceptualised as a failure of self-regulation (Baumeister and Heatherton
1996; Baumeister et al. 1994) associated with poor academic and work performance
and mental ill health (Sto
¨ber and Joormann 2001).
The measurement of procrastination is vital to aid research that aims to
understand this common and injurious behaviour. A range of self-report scales have
been developed to measure this construct in general (e.g., the General Procrasti-
nation Scale or ‘GPS’: Lay 1986), in specific aspects (e.g., the Decisional
Procrastination Scale or ‘DPS’: Mann 1982), and in specific populations (e.g., for
students with the Tuckman Procrastination Scale or ‘TPS’: Tuckman 1991). More
recently, the construct of intentional procrastination has been delineated and
measured using the active procrastination scale (APS: Choi and Moran 2009). This
separation of sub-types of procrastination is similar to that proposed by Ferrari
(1993) who distinguished between functional and dysfunctional procrastinators,
where the latter are characterised by their tendency to chronically delay starting or
completing tasks.
The APS was developed to advance earlier work by Chu and Choi (2005) that
proposed that there are two types of procrastinator: passive and active. A passive
procrastinator was described as similar to more ‘traditional’ conceptualizations of
the behaviour: i.e., the term refers to individuals who typically leave tasks to the last
minute despite their good intentions, impairing performance. On the other hand,
active procrastinators choose to delay task initiation or completion; they intend to
procrastinate as a means of optimising performance. Indeed, Choi and Moran (2009)
reported evidence that active procrastination was distinct from traditional procras-
tination, finding different relationships between measures of the former and latter
with other study variables, such as participants’ self-reported performance and
ability to structure their time (in a sample of Canadian university students).
However, we argue that the items comprising the measure of passive procrastination
used in their study did not clearly distinguish between intentional and unintentional
procrastination, offering further justification of the need to develop a scale that
entirely focuses on the latter. Indeed, a brief and informal content analysis of many
The Unintentional Procrastination Scale 137
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
of the extant procrastination scales appeared to offer support for the contention that
several of their items fail to clearly distinguish between intentional and uninten-
tional procrastination (e.g., the DPS, GPS, and TPS).
Intentional or active procrastination thus alludes to the idea that procrastination is
to some extent a voluntary strategy, possibly aimed at self-regulation (Fernie and
Spada 2008). If this were the case, active procrastination should correlate with
positive beliefs about the benefits of engaging in procrastination, such as
‘Procrastination helps me cope’’ and ‘‘Procrastination allows to creativity occur
more naturally’’ (Fernie and Spada 2008; Fernie et al. 2009). Research has also
shown that individuals hold negative beliefs about procrastination, such as ‘‘When I
procrastinate, I find it difficult to concentrate on other tasks’’ and ‘‘My
procrastination is uncontrollable’’ (Fernie and Spada 2008; Fernie et al. 2009),
concurrently with positive beliefs. This suggests that although procrastination may
be voluntarily initiated for some, it later becomes, or is perceived as becoming,
involuntary. These beliefs further support the conceptualisation of two domains of
procrastination: intentional, or active, and unintentional.
Distinguishing unintentional from intentional procrastination may help to explain
the strong relationship between worry, metacognitions pertaining to worry, and
general procrastination (e.g., Spada et al. 2006; Sto
¨ber and Joormann 2001). Indeed,
mindfulness, which can be defined as an awareness of the present (Brown and Ryan
2003) and thus, in some sense, representative of a meta-level of cognition, has been
shown to mediate the relationship between procrastination and stress (Sirois and
Tosti 2012). In addition, it is possible that procrastination may be appear to be
uncontrollable because an individual’s cognitive resources are engaged in worry,
leaving less mental assets available for task initiation or completion. If an individual
is engaged in what they perceive as unintentional procrastination, they may attempt
to regulate their predicament with further procrastination, leading to its
perseveration.
Despite the myriad of pre-existing measures of procrastination, there is arguably
a need for a brief, domain-specific measure of unintentional procrastination
appropriate not just to students, but also to the general population. We hypothesized
that unintentional procrastination is likely to be a stronger marker of psychopathol-
ogy than general procrastination because it encapsulates perceived involuntary and
not voluntary control of this behaviour, thus a measure of unintentional procras-
tination might not only be beneficial for research, but also for use in clinical
settings. The current paper reports two studies that trace the development of the
Unintentional Procrastination Scale. The first study incorporates a principle
components analysis and an assessment of internal consistency to construct the
scale. The second details a confirmatory factor analysis using data from a second
sample as well as assessment of the construct and divergent validity of the newly
constructed scale, specifically considering the likelihood of shared proportion of
variance explained by general and unintentional procrastination. We also explored
the relationships between negative affect with intentional, unintentional, and general
procrastination.
138 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Study 1: Construction of the Unintentional Procrastination Scale
Method
Participants
A convenience sample of 139 (111 female; mean age =29.5 years [SD =11.5;
range 18–72 years]) participants was recruited for this study and completed a
battery of online questionnaires. Eligibility criteria were minimal to attract a sample
that represented a broad range of individuals. Participants were required: (1) to be at
least 18 years of age, (2) to possess adequate English language skills, and (3) to
consent to participate.
The sample was international, with participants reporting nationalities from six
continents, although the distribution of participants’ nationalities was skewed, with
46.8 % (65) reporting to be British. The ethnicity of the sample was also skewed,
with 67.6 % (94) of participants reporting to be white. Because an international
sample was anticipated, it was thought likely that for many of the participants
English would not be their first language. Indeed, 38.8 % (54) of the sample
reported a first language other than English. As a result, participants were asked to
rate their confidence in their ability to speak, read, and write in English. 96.4 %
(133) of the sample rated their confidence in all three of these domains as either
‘confident’ or ‘very confident’.
From earlier research that has developed questionnaires, a frequently identified
limitation is a failure to control for participants’ previous (or current) exposure to
psychological therapies and how this may impact on responses to items in
questionnaires (e.g. Fernie et al. 2014). Thirty-four participants reported that they
had undergone psychotherapy previously that is not on going. Of these, 58.8 % (20)
stated that CBT had been a component in their therapy, 70.6 % (24) had seven or
more sessions, and 14.7 % (five) reported that at least part of their therapy aimed to
address problematic procrastination. 6.5 % (nine) participants reported that they
were currently in psychotherapy, with 22.2 % (two) of these stating that they were
being treated with CBT, 44.4 % (four) declaring that they had completed more than
seven sessions, and 66.7 % (six) revealing that problematic procrastination was
being addressed in their therapy.
In an attempt to control for variations in mental health wellbeing, self-report
mood measures were taken and participants were also asked if they have a
psychiatric diagnosis from a mental health clinician. 9.4 % (13) of participants
reported that they had, with the majority reporting diagnoses of depression and
anxiety disorders.
Materials
Seven items pertaining to unintentional procrastination were derived from a review
of transcriptions of an earlier procrastination study (Fernie and Spada 2008), as well
The Unintentional Procrastination Scale 139
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
as the authors’ clinical experience and from deductions based on theory to form the
raw version of the Unintentional Procrastination Scale (UPS).
Items were framed as statements to which participants could respond to on a
four-point Likert-type scale to indicate their level of agreement (‘‘1. Do not agree’’,
‘2. Agree slightly’’, ‘‘3. Agree moderately’’, and ‘‘4. Agree strongly’’). The items
were preceded by a pre-amble that read as follows:
Please read each statement and select a number 1, 2, 3 or 4 that indicates how
much you agree or disagree with the statement. There are no right or wrong
answers. Do not spend too much time on any statement.
Procedure
Participants were recruited via social media and through a London university’s
fortnightly research volunteer email circular. An additional recruitment strategy
involved emailing a hyperlink to the online questionnaires to individuals on the
authors’ email contact lists and asking recipients to forward this on to others on their
contact lists, in attempt to create a viral-like spread.
Potential participants were directed to the study website containing the
questionnaires. The first two pages of this provided information regarding the
purpose of the study, how responses were anonymous, and that consent would be
assumed once participants click on the ‘submit’ button that followed the battery of
questionnaires. The pages following this information contained a series of questions
to ascertain participants’ demographic details, their exposure to psychotherapy, and
their current mental wellbeing (i.e. do they have a psychiatric diagnosis?).
Participants were not required to record their names.
Results
Principle Components Analysis
The seven original items of the UPS were subject to a principle components
analysis (PCA). Both initial eigenvalues (only a single component had a value over
one) and a Scree plot indicated a one-factor solution. This single factor accounted
for 60.7 % of the variance and all seven items loaded strongly (see Table 1). The
internal consistency of the newly developed scale was .89 and further analysis
indicated that this would not be improved if any of the items were removed.
We re-ran the PCA excluding the participants that reported having current or
previous CBT to control for exposure to procrastination-related cognitions. This led
to the loading of item #2 to fall below .4 to .39. However, because a subsequent
analysis with the ‘no current or previous exposure to CBT’ sample suggested that
the internal consistency would not be improved by removing any of the items, we
retained the original seven-item UPS for the second study where the factor would be
subjected to a confirmatory factor analysis (CFA) using a new dataset.
140 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Study 2: Validation of UPS
Introduction
In order to validate the UPS and provide evidence to support the delineation of
procrastination into intentional and unintentional domains, we tested several
hypotheses. Firstly, we hypothesized that UPS scores would be significantly
correlated with those from a pre-existing measure of procrastination, establishing
concurrent validity, and that this relationship would remain significant when
controlling for negative affect, suggesting divergent validity. Secondly, we posited
that as a test of divergent validity, because we have argued that unintentional
procrastination is a stronger marker of psychopathology than both general and
intentional procrastination, data from the UPS would be a stronger predictor of
negative affect than measures of general and intentional procrastination. Thirdly, we
predicted that the UPS would be more strongly associated with negative beliefs
about procrastination than measures of general and intentional procrastination.
Finally, we hypothesized that intentional procrastination would be a stronger
predictor of positive beliefs about procrastination than UPS scores and a measure of
general procrastination.
Method
Participants and Procedure
A convenience sample of a 155 participants (118 female; mean age =32.5 years
[SD =11.4; range 18–68 years]) completed a battery of online questionnaires.
Eligibility criteria and the procedure matched that used in Study 1.
Again, the participants were international and the distribution of participants’
nationalities was skewed, with 46.2 % (72) reporting as British. The majority of the
sample self-reported their ethnicity as white (71.6 % [110]) and 61.9 % (96) stating
that English as their first language. At least 90.3 % (139) of participants rated their
confidence in speaking, reading, or writing in English as either ‘confident’ or ‘very
confident’.
In terms of exposure to psychological therapy, 1.9 % (3) of participants were
currently in therapy and 24.5 % (38) had undergone it in the past. Overall, 7.4 %
(12) of participants reported that they were, or had undergone, CBT. Only 8.4 %
(13) of participants stated that they had a mental health diagnosis, reporting
depressive, anxiety, or eating disorders.
Materials
Emotional Measures The Patient Health Questionnaire 9 (PHQ-9; Kroenke et al.
2001) was used to assess depressive symptoms. The PHQ-9 is a nine-item scale that
possesses good psychometric properties, with higher scores indicating the presence
of greater levels of symptoms (Kroenke et al. 2001). The Generalized Anxiety
The Unintentional Procrastination Scale 141
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Disorder 7 (GAD-7; Spitzer et al. 2006) was administered to measure anxiety
symptoms. The GAD-7 also possesses good psychometric properties and higher
scores again indicate the presence of more anxiety symptoms (Spitzer et al. 2006).
Procrastination Measures In addition to the newly developed UPS, the General
Procrastination Scale (GPS: Lay 1986) was used to assess traditional procrastina-
tion. The GPS is a 17-item questionnaire that taps largely into, arguably, both
intentional and unintentional procrastination. The Active Procrastination Scale was
also used and consists of a total of 16-items equally distributed over four factors,
namely ‘preference for pressure’, ‘intentional decision to procrastinate’, ‘ability to
meet deadlines’, and ‘outcome satisfaction’ (Choi and Moran 2009). This current
study focuses on the ‘intentional decision to procrastinate’ (IDP) factor that consists
of items such as ‘‘I intentionally put off work to maximize my motivation’’ and ‘‘To
use my time more efficiently, I deliberately postpone some tasks’’.
Finally, we used the Metacognitive beliefs about Procrastination scale (MaP) to
assess higher-order thinking about procrastination (Fernie et al. 2009). The MaP
consists of 16-items equally distributed over two subscales: positive metacognitions
about procrastination (PMP) and negative metacognitions about procrastination
(NMP). An example item of the PMP is ‘‘When I procrastinate, I am unconsciously
mulling over difficult decisions’’ and for NMP is ‘‘My procrastination is
uncontrollable’’. NMP has been shown to significantly correlate with both general
and decisional procrastination and PMP to only the latter (Fernie et al. 2009). The
factors have been shown to possess good internal consistency (Fernie et al. 2009).
Table 1 Factor Loadings for the UPS items from Initial PCA, Second PCA, and Second CFA
PCA loading
(total sample;
n=139)
PCA loading (no
CBT exposure;
n=105)
2nd CFA loadings
(total sample;
n=131)
1. I rarely begin tasks as soon as I am given
them, even if I intend to.
.643 .627 1.000
2. I find it difficult to make a decision the
moment I am faced with it.
.411 .392 N/A
3. Often I mean to be doing something, but it
seems that sometimes I just don’t get
round to it.
.760 .749 1.179
4. I often seem to start things and don’t seem
to finish them off.
.605 .590 1.269
5. I intend to get things done, but sometimes
this just does not happen.
.634 .616 1.449
6. Often I will set myself a date by which I
intend to get something done or make a
decision, but miss the deadline.
.577 .577 1.429
7. I really want to get things finished in time,
but I rarely do.
.620 .607 1.553
142 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Results
Confirmatory Factor Analysis
Responses to the seven-items from the UPS were used to confirm its single factor
structure. The Lavaan package (Rosseel 2012) was installed into R Studio (R-Studio
2015) and was used to conduct a confirmatory factor analysis (CFA). We defined
unintentional procrastination as the single latent variable and the seven-items of the
UPS as congeneric indicators of the latent variable. Using maximum likelihood
estimation, we assumed multivariate normality of item scores and defined them as
continuous indicators within the model. We utilised four indices to evaluate the fit
of the model: a Chi square measure of fit, the Root Mean Square Error of
Approximation (RMSEA), the Comparative Fit Index (CFI), and the Tucker-Lewis
Index (TFI: also known as the Non-Normed Fit Index).
This initial CFA revealed mixed results regarding the fitting of the data to the
specified model. Two absolute fit indices suggested that the data weakly fitted the
specified model: the Chi square test was significant (v
2
=29.13, df =14, p[.01)
and the RMSEA was 0.09. However, relative fit indices produced an opposite
picture. The CFA generated a CFI of 0.97 and TLI of 0.95 suggesting that
the data better fit the specified model than the baseline model. Parameter estimates
were reviewed and modification indices were calculated. Together, these suggested
that a re-specified model, resulting from the removal of a single item (#2), might
lead to an improvement of fit. The re-specified model was a better fit of the data,
with a non-significant Chi square test (v
2
=10.72, df =9, p=.30), an RMSEA of
0.038, CFI of 0.99, and a TFI of 0.99. See Table 1for the factor loadings for the re-
specified model (note that Lavaan automatically assigns a loading of 1.000 to the
first item).
Construct Validity
Table 2shows the means, standard deviations, and ranges for all experimental
variables. A series of Kolmogorov–Smirnov tests of normality were conducted on
the data that suggested PHQ-9, GAD-7, PMP, NMP, and UPS were significantly
different than normal, while the GPS and IDP were not. As a result a series of non-
parametric, Spearman’s Rho correlation analyses were conducted on the data (see
Table 2). These revealed that the UPS was positively associated with GPS (very
strong), PMP (moderate), NMP (moderate), IDP (weak), PHQ-9 (strong), and GAD-
7 (strong).
In order to further test the construct validity of the UPS, we assessed its
relationship with GPS while controlling for IDP and negative affect. The
relationship between UPS and GPS remained significant (b=0.79, p\.001
[LL =1.96, UL =2.09]). In this model, which accounted for 67 % of the variance
in the pre-existing measure of procrastination, IDP, GAD-7, and PHQ-9 became
non-significant predictors of GPS.
The Unintentional Procrastination Scale 143
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Unintentional Procrastination as a Marker of Psychopathology
We conducted two further regression analyses, the first with GAD-7 as the
dependent variable and the second with PHQ-9, to test the hypothesis that
unintentional procrastination would be a stronger marker of psychopathology than
measures of intentional and general procrastination. The same sets of predictor
variables were entered into both models: UPS, IDP, and GPS. In both models, only
UPS remained a significant predictor: both with PHQ-9 as the dependent variable
(b=0.52, p\.001 [LL =0.31, UL =0.94]) and GAD-7 (b=0.48, p=.001
[LL =0.23, UL =0.83]). Thus, despite the shared pattern of correlations between
the measures of negative affect and the IDP, GPS, and UPS, these analyses provided
some evidence of divergent validity existing between all three measures.
Metacognitions and Intentional and Unintentional Procrastination
We predicted that unintentional procrastination would be more strongly associated
with negative metacognitions about procrastination than measures of intentional and
general procrastination. We tested this by conducting a regression analysis with
NMP as the dependent variable and UPS, IDP, and GPS as independent variables. In
this model, UPS once more was the only significant predictor of NMP (b=0.52,
p=.001 [LL =0.33, UL =1.17]).
To test our hypothesis that intentional procrastination would be a stronger
predictor of positive metacognitions about procrastination than both general and
unintentional procrastination, we calculated another regression analysis with PMP
as the dependent variable and UPS, IDP, and GPS as independent variables. In line
with our hypothesis, only IDP was a significant predictor of PMP (b=0.27,
p\.001 [LL =0.09, UL =0.40]).
Table 2 Means, SDs, and ranges for all experimental variables and correlation matrix
Means SD Range 1 2 3 4 5 6 7
1. UPS 13.67 4.91 6 to 24 .78
**
.31
**
.35
**
.25
**
.53
**
.47
**
2. GPS -0.04 14.31 -28 to 37 .26
**
.23
**
.22
*
.47
**
.49
**
3. PMP 14.99 4.57 8 to 32 -.07 .34
**
.28
**
.25
**
4. NMP 18.83 6.97 8 to 32 .02 .45
**
.50
**
5. IDP 15.97 5.11 4 to 28 .25
**
.19
*
6. PHQ-9 14.96 5.9 9 to 35 .73
**
7. GAD-
7
12.36 5.45 7 to 28
UPS Unintentional Procrastination Scale, GPS General Procrastination Scale, PMP Positive Metacog-
nitions about Procrastination, NMP Negative Metacognitions about Procrastination, IDP Intentional
Decision to Procrastinate, PHQ-9Patient Health Questionnaire, GAD-7General Anxiety Disorder-7,
n=118 to 131; * p\.05; ** p\.01
144 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Finally, to see if participants’ exposure to psychotherapy impacted on their scores
on the measures of procrastination used in this study, a series of Mann–Whitney U
or independent ttests were used (dependent on the distribution of data) to compare
these two groups. None of these tests resulted in significant results: i.e., GPS
[t(116) =1.73, p=.08; n
exposure
=32, n
no-exposure
=86], IDP [t(107) =0.42,
p=.68; n
exposure
=30, n
no-exposure
=79], PMP [U =1072, p=.39; n
exposure
=
30, n
no-exposure
=80], and NMP [U =1191, p=.95; n
exposure
=30,
n
no-exposure
=80].
Assumptions of Regression Analyses
A total of five regression analyses were conducted for this study and the suitability of
the data for all the models for this kind of analyses was assessed. Firstly, there was no
evidence of multicollinearity in the dataset for all models: (1) no correlations greater
than r=.9 were identified between the predictor variables used in the regression
analyses (the strongest correlation was found between GPS and UPS at r=.78); (2)
the Tolerance Index (TI) values were all above .20 (e.g., for all of the models, the
predictors’ TIs ranged between .27 and .93); (3) the Variance Inflation Factors (VIFs)
for all predictor variables were substantially less than 10 (e.g., again, for all of the
models, the predictors’ VIFs ranged between 1.08 and 3.78); and (4) eigenvalues,
condition indexes, and variance proportions were calculated for all models. Models
that used both GPS and UPS as predictors revealed that both of these variables
explained large variance proportions ([50 %) at the smallest eigenvalues, however
none of these were associated with condition indexes greater than 15. This provided
further evidence that, despite the strong correlation between GPS and UPS, as well as
their shared patterns of correlations between GAD-7 and PHQ-9, multicollinearity
was not problematic for any of the models. Secondly, the Durbin-Watson test
suggested that the assumption of independent errors is tenable. Thirdly, histograms
and normality plots suggested that the residuals were normally distributed and plots
of the regression-standardized residuals against the regression standardized predicted
values suggested that the assumptions of linearity and homoscedasticity were met.
Discussion
The central aim of this study was to develop a brief measure of unintentional
procrastination in the form of the UPS. This study resulted in a six-item measure of
unintentional procrastination that appeared to possess construct and divergent
validity and good internal consistency. The final six-item version of the UPS was a
good fit of Study 2 data. The UPS remained a strong predictor of general
procrastination even when controlling for negative affect.
Our second set of hypotheses regarded unintentional procrastination being a
stronger marker of psychopathology than both general and intentional procrastina-
tion. Despite the strong correlation between the GPS and the UPS (acknowledging
that general and unintentional procrastination are overlapping concepts), our tests of
multicollinearity and our regression models supported this hypothesis, as UPS
The Unintentional Procrastination Scale 145
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
scores were independent predictors of both anxiety and depression in models that
contained measures of general and intentional procrastination.
Our final set of hypotheses concerned the role of metacognitions about procras-
tination in the delineation between intentional and unintentional procrastination. Our
results suggested that positive metacognitions about procrastination are more strongly
associated with intentional procrastination, while negative metacognitions are more
relevant to unintentional procrastination. It is possible to speculate a metacognitive
model of procrastination to suggest how these relationships may operate. Firstly, an
individual with positive beliefs about procrastination might respond to being given a
task with intentional procrastination. Examples of these metacognitions might include
‘Procrastination allows creativity to occur more naturally’’ and ‘‘Procrastination stops
me from being bored’’ (Fernie et al. 2009), therefore relating to not only to optimising
performance, but also to minimising feelings of discomfort. Secondly, intentional
procrastination, in problematic or dysfunctional procrastinators (Ferrari 1993), could
activate negative beliefs about procrastination, leading to negative affect. Uninten-
tional procrastination might be responded to with cognitive processes that are
‘resource-heavy’ (such as worry, rumination, and distraction) in a maladaptive at-
tempt to control this behaviour. Such responses might be activated because an
individual holds certain other positive metacognitions pertaining to these processes.
For example, an individual might respond with worry because they believe it helps
them to organize their thoughts (Cartwright-Hatton and Wells 1997) or with
rumination because of metacognitions such as ‘‘Ruminating about the past helps me to
work out how things could have been done better’’ (Papageorgiou and Wells 2001).
Responses such as these could result in a depletion of mental resources that inhibit an
individual from achieving their optimal performance, reinforcing negative self-
efficacy beliefs and maintaining the postponement of starting or completion of a task
or the making of a decision (see Fig. 1), resulting in what Ferrari (1993) referred to as
dysfunctional procrastination.
This study is subject to several limitations that will have to be addressed by
future research. First, social desirability, self-report biases, context effects, and poor
recall may have contributed to errors in the self-report measurements. Future studies
could involve Ecological Momentary Assessment to test whether UPS scores predict
real-time procrastination, further establishing construct validity. Second, a cross-
sectional design was adopted and this does not allow causal inferences. Third, this
study utilized self-report measures to assess subjective experience and meta-
Fig. 1 Speculative metacognitive model of procrastination
146 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
awareness and, as such, like much cognitive research, there is always doubt whether
we are measuring the constructs we intend. Fourth, there were issues with the
sample characteristics: it was moderate in size and this impacted on the power of the
statistical analyses; the majority of participants were female; and participants
predominately ethnically identified themselves as ‘white’ and in terms of
nationality, British. This impacts on our ability to generalize these findings to
other ethnicities and nationalities, though a significant proportion of participants
self-reported as non-white and non-British. Fifth, the lack of homogenous sample
nationality risked leading to increased error measurements due to the self-report
measures all being written in English; however, participants’ ratings of their
language abilities suggested that very few were not confident in English. Finally, the
strong correlation between GPS and UPS data raises concerns that they are
measuring similar constructs. However, we assumed that general procrastination
would encapsulate both intentional and unintentional aspects (e.g., the GPS was
significantly correlated with both IDP and UPS). Furthermore, our collinearity
diagnostics that we employed for our regression models provided evidence that the
GPS and the UPS measure similar but distinct constructs.
Despite these limitations, we believe that the UPS is promising research tool. It is
brief and easy to administer; its use is not limited to specific samples (e.g., students)
and it strongly correlates with pre-existing measures of procrastination. Perhaps the
most important contribution this scale makes is by providing further evidence for
the delineation of procrastination into intentional and unintentional domains, and by
suggesting that the latter is stronger marker of psychopathology than the former.
Unintentional Procrastination Scale
Please read each statement and select a number 1, 2, 3 or 4 that indicates how much
you agree or disagree with the statement. There are no right or wrong answers. Do
not spend too much time on any statement.
Do not
agree
Agree
slightly
Agree
moderately
Agree
very
much
1. I rarely begin tasks as soon as I am given them, even if I
intend to.
12 3 4
2. Often I mean to be doing something, but it seems that
sometimes I just don’t get round to it.
12 3 4
3. I often seem to start things and don’t seem to finish them
off.
12 3 4
4. I intend to get things done, but sometimes this just does
not happen.
12 3 4
5. Often I will set myself a date by which I intend to get
something done or make a decision, but miss the
deadline.
12 3 4
6. I really want to get things finished in time, but I rarely
do.
12 3 4
The Unintentional Procrastination Scale 147
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Acknowledgments Author BAF receives salary support from the National Institute for Health Research
(NIHR) Mental Health Biomedical Research Centre and Dementia Research Unit at South London and
Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the
author and not necessarily those of the NHS, the NIHR or the Department of Health.
Compliance with Ethical Standards
Conflict of interest All authors declare that they have no conflicts of interest.
Humans and Animal Rights This study involved human participants. All procedures performed in this
study were conducted in accordance with the ethical standards of the institutional research committee and
with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed Consent Informed consent was obtained from all individual participants included in the study.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, dis-
tribution, and reproduction in any medium, provided you give appropriate credit to the original
author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were
made.
References
Baumeister, R. F., & Heatherton, T. F. (1996). Self-regulation failure: An overview. Psychological
Inquiry, 7(1), 1–15.
Baumeister, R. F., Heatherton, T. F., & Tice, D. M. (1994). Losing control: How and why people fail at
self-regulation. Cambridge: Academic Press.
Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in
psychological well-being. Journal of Personality and Social Psychology, 84(4), 822.
Cartwright-Hatton, S., & Wells, A. (1997). Beliefs about worry and intrusions: The meta-cognitions
questionnaire and its correlates. Journal of Anxiety Disorders, 11(3), 279–296. doi:10.1016/S0887-
6185(97)00011-X.
Choi, J. N., & Moran, S. V. (2009). Why not procrastinate? Development and validation of a new active
procrastination scale. Journal of Social Psychology, 149(2), 195–211. doi:10.3200/SOCP.149.2.195-
212.
Chu, A. H., & Choi, J. N. (2005). Rethinking procrastination: Positive effects of ‘‘active’’ procrastination
behavior on attitudes and performance. Journal of Social Psychology, 145(3), 245–264. doi:10.3200/
SOCP.145.3.245-264.
Ellis, A., & Knaus, W. J. (1977). Overcoming procrastination: Or how to think and act rationally in spite
of life’s inevitable hassles. New York: Institute for Rational Living.
Fernie, B. A., Maher-Edwards, L., Murphy, G., Nikcevic, A. V., & Spada, M. M. (2014). The
Metacognitions about symptoms control scale: Development and concurrent validity. Clinical
Psychology & Psychotherapy. doi:10.1002/cpp.1906.
Fernie, B. A., & Spada, M. M. (2008). Metacognitions about procrastination: A preliminary investigation.
Behavioural and Cognitive Psychotherapy, 36(03), 359–364.
Fernie, B. A., Spada, M. M., Nikc
ˇevic
´, 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. (1993). Procrastination and impulsiveness: Two sides of a coin? In W. McCown, M.
B. Shure, & J. Johnson (Eds.), The impulsive client: Theory, research, and treatment (pp. 265–276).
Washington, DC: American Psychological Association.
Harriott, J., & Ferrari, J. R. (1996). Prevalence of procrastination among samples of adults. Psychological
Reports, 78(2), 611–616.
148 B. A. Fernie et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity
measure. Journal of General Internal Medicine, 16(9), 606–613.
Lay, C. H. (1986). At last, my research article on procrastination. Journal of Research in Personality,
20(4), 474–495.
Mann, L. (1982). Decision-making questionnaire. Unpublished scale. Flinders University of South
Australia.
Papageorgiou, C., & Wells, A. (2001). Positive beliefs about depressive rumination: Development and
preliminary validation of a self-report scale. Behavior Therapy, 32(1), 13–26. doi:10.1016/S0005-
7894(01)80041-1.
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical
Software, 48(2), 1–36.
RStudio Team. (2015). RStudio: Integrated development for R. RStudio, Inc., Boston, MA. http://www.
rstudio.com/.
Sirois, F. M., & Tosti, N. (2012). Lost in the moment? An investigation of procrastination, mindfulness,
and well-being. Journal of Rational-Emotive & Cognitive-Behavior Therapy, 30(4), 237–248.
Spada, M. M., Hiou, K., & Nikcevic, A. V. (2006). Metacognitions, emotions, and procrastination.
Journal of Cognitive Psychotherapy, 20(3), 319–326. doi:10.1891/jcop.20.3.319.
Spitzer, R. L., Kroenke, K., Williams, J. W., & Lo
¨we, B. (2006). A brief measure for assessing
generalized anxiety disorder: The gad-7. Archives of Internal Medicine, 166(10), 1092–1097.
doi:10.1001/archinte.166.10.1092.
Sto
¨ber, 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.
Tuckman, B. W. (1991). The development and concurrent validity of the procrastination scale.
Educational and Psychological Measurement, 51(2), 473–480.
The Unintentional Procrastination Scale 149
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center
GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers
and authorised users (“Users”), for small-scale personal, non-commercial use provided that all
copyright, trade and service marks and other proprietary notices are maintained. By accessing,
sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of
use (“Terms”). For these purposes, Springer Nature considers academic use (by researchers and
students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and
conditions, a relevant site licence or a personal subscription. These Terms will prevail over any
conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription (to
the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of
the Creative Commons license used will apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may
also use these personal data internally within ResearchGate and Springer Nature and as agreed share
it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not otherwise
disclose your personal data outside the ResearchGate or the Springer Nature group of companies
unless we have your permission as detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial
use, it is important to note that Users may not:
use such content for the purpose of providing other users with access on a regular or large scale
basis or as a means to circumvent access control;
use such content where to do so would be considered a criminal or statutory offence in any
jurisdiction, or gives rise to civil liability, or is otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association
unless explicitly agreed to by Springer Nature in writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a
systematic database of Springer Nature journal content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a
product or service that creates revenue, royalties, rent or income from our content or its inclusion as
part of a paid for service or for other commercial gain. Springer Nature journal content cannot be
used for inter-library loans and librarians may not upload Springer Nature journal content on a large
scale into their, or any other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not
obligated to publish any information or content on this website and may remove it or features or
functionality at our sole discretion, at any time with or without notice. Springer Nature may revoke
this licence to you at any time and remove access to any copies of the Springer Nature journal content
which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or
guarantees to Users, either express or implied with respect to the Springer nature journal content and
all parties disclaim and waive any implied warranties or warranties imposed by law, including
merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published
by Springer Nature that may be licensed from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a
regular basis or in any other manner not expressly permitted by these Terms, please contact Springer
Nature at
onlineservice@springernature.com

Supplementary resource (1)

... On the other hand, passive procrastination is characterized by a more subconscious and unintentional delay in completing tasks. Passive procrastinators do not intend to procrastinate; they often end up doing so due to an inability to make quick, effective decisions [21]. Affectively, an approaching deadline ultimately causes passive procrastinators to feel pressured, therefore creating pessimistic thoughts regarding their ability to achieve good results [22]. ...
... The Unintentional Procrastination Scale (UPS) was developed by Fernie et al. (2017) [21], and it was adopted to assess passive procrastination behavior among nurses. The UPS consists of six items that were measured using a 4-point Likert scale ranging from don't agree (1) to very much agree (4), with a single-factor structure. ...
... The Unintentional Procrastination Scale (UPS) was developed by Fernie et al. (2017) [21], and it was adopted to assess passive procrastination behavior among nurses. The UPS consists of six items that were measured using a 4-point Likert scale ranging from don't agree (1) to very much agree (4), with a single-factor structure. ...
Article
Full-text available
Background Controlling smartphone addiction and procrastination among nurses is crucial for enhancing the productivity of both nursing and the healthcare system. Critical care nurses are highly vulnerable to smartphone addiction and procrastination behaviors than other groups. They may purposefully delay their tasks, a practice known as active procrastination, or inadvertently delay them, a practice known as passive procrastination. Aim This study was designed to assess the prevalence of smartphone addiction and procrastination behavior among nurses, examine the effect of smartphone addiction on the active and passive procrastination behaviors, and explore the correlation between active and passive procrastination behaviors among nurses. Method This is a descriptive correlational exploratory study that was conducted at 23 critical care units of one large educational hospital in Egypt. Data were collected from 360 nurses who were conveniently selected using three tools: the Smartphone Addiction Inventory, the New Active Procrastination Scale, and the Unintentional Procrastination Scale. Correlation and regression analyses were conducted to test the hypothetical relationship among the study variables. Results This study revealed that 55.0%, 80.0%, and 45.3% of nurses had a moderate perceived level of smartphone addiction, active procrastination behavior, and passive procrastination behavior, respectively. There is a significant positive correlation between smartphone addiction and both nurses’ active and passive procrastination behaviors. Smartphone addiction accounts for 25% of the variance in nurses’ active procrastination behavior and 18% of the variance in their passive procrastination. Furthermore, there is a moderately significant negative correlation between nurses’ active procrastination behavior and their passive procrastination behavior. Conclusion Nurses are exhibiting moderate levels of smartphone addiction and procrastination, which is a significant threat to the healthcare industry and nursing productivity. This requires technological, educational, and organizational interventions that foster active procrastination and combat passive procrastination behaviors among nurses. Implications Continuous training programs are required to enhance time management skills among nurses and increase the awareness of nurse managers with the symptoms of smartphone addiction among nurses. Nurse leaders should early detect and address the addictive use of smartphones among nurses, identify potential procrastinators, and provide counseling to eradicate these behaviors in the workplace.
... La procrastinación irracional supone costes de tiempo y dinero importantes, se han estimado pérdidas millonarias (7,(12)(13) . Asimismo, también tiene importantes efectos en el área de salud (14)(15) en el bienestar subjetivo (16-17) y el rendimiento académico (18) , entre otros. ...
Article
Full-text available
Various studies have reported positive relationships between Irrational Procrastination (IP) and impulsivity, a trait that could be considered susceptible to immediate reinforcement. The theory of susceptibility to reinforcement and punishment proposed by Gray has been reviewed, and subcategories have been suggested, such as susceptibility to immediate and delayed reinforcement, as well as susceptibility to immediate and anticipated punishment, variables that have only been studied in relation to IP on a single occasion. OBJECTIVE. To study the relationship between IP and Susceptibility to Immediate and Delayed Reinforcement, and susceptibility to Anticipated Punishment. METHODOLOGY: The Irrational Procrastination Scale (IPS), the Susceptibility to Anticipated Punishment Scale (SAPS), and the Susceptibility to Immediate and Delayed Reinforcement Scale (SIDR) were administered to a sample of 960 university students. RESULTS. The regression model highlighted that the three factors of the two scales were significant and predicted irrational procrastination, explaining 23% of the variance. CONCLUSION. Those factors that clearly allude to susceptibility to delayed reinforcement or anticipated punishment are negatively related to procrastination. On the other hand, when the susceptibility to reinforcement or punishment is short term, the relationship is positive.
... Lla procrastinación es una conducta que conduce a la toma de decisiones erróneas en la vida cotidiana, generando conflictos emocionales que acarrean problemas en las áreas académicas, sociales y personales (Zanabria-Contreras, 2020;Domínguez-Lara, 2017;Fernie et al., 2016). ...
Article
Full-text available
La procrastinación se entiende como el conjunto de comportamientos que involucran la postergación deliberada de la ejecución de una acción planificada, incluso cuando esto pueda generar dificultades tanto en el presente como en el futuro, impactando en múltiples facetas de la vida del individuo. En cuanto a los objetivos y el método del presente estudio, este contó con dos fases, para la primera orientada a la validación del instrumento “Escala de Procrastinación Irracional” (IPS) en población colombiana, seguido de una fase de carácter descriptivo y la generación de una baremación de los puntajes de la escala para facilitar la interpretación de los datos para futuras investigaciones. El instrumento IPS mostró adecuadas propiedades psicométricas: AFC: CMIN/gl2=2.1; CFI=0.94; TLI=0.92; RMR=0.05; RSMEA= 0.08; GFI= 0.82 Confiabilidad: α=0.86, por lo que se considera un instrumento válido para su aplicación en universitarios colombianos. Se identificó además que un 31.3%, mostró niveles moderados y un 38% niveles altos de procrastinación, por otra parte, se observa que las actividades relacionadas con el uso de aparatos electrónicos y de servicios de internet, así como también las de ocio y descanso se asocian con la presencia de procrastinación, por último, se describen los baremos para los puntajes obtenidos.
... The Unintentional Procrastination Scale [91] UPS Passive, it is related to unintentional procrastination and highlights the negative aspects of procrastination. ...
Article
Full-text available
The relationship between academic performance and procrastination has been well documented over the last twenty years. The current research aggregates existing research on this topic. Most of the studies either find no result or a small negative result. However, recent studies suggest that procrastination can have a positive influence on academic performance if the procrastination is active instead of passive. To analyse the effect of active procrastination on academic performance, a meta-analysis was conducted. The analysis includes 96 articles with 176 coefficients including a combined average of 55,477 participants related to the correlation between academic performance and procrastination. The analysis uncovered a modest negative correlation between academic performance and procrastination overall. Importantly, the type of procrastination exerted a substantial impact on the strength of this correlation: active procrastination demonstrated a small positive effect size, whereas passive procrastination registered a small negative effect size. Additionally, participant-specific characteristics and indicators further modulated the magnitude of the correlation. The implications of this research extend to underscoring a potential beneficial aspect of procrastination, specifically elucidating how certain types of procrastination can positively influence academic performance.
Article
Aim This study aims to assess the relationship between workplace ostracism and the procrastination behavior of nurses, as well as examine the effect of organizational silence on this relationship. Background Controlling workplace ostracism and eradicating time wasters, especially procrastination behavior among nurses, are key strategies that add value to organizational effectiveness. In addition, remaining silent about significant issues facing nurses is a devastating approach to the success of both healthcare organizations and the nursing profession. Method A cross-sectional descriptive correlational exploratory research design was used to conduct the study. Data were collected from 352 nurses recruited from three large university hospitals in Alexandria, Egypt. Four instruments, namely, the Workplace Ostracism Questionnaire, the Organizational Silence Scale, the Active Procrastination Scale, and the Unintentional Procrastination Scale, were used. Structural equation modeling was used to test the hypothesized relationships among the variables. Results The findings demonstrated a significant positive and moderate association between workplace ostracism and both active and passive procrastination behaviors among nurses. Moreover, there was a strong positive and significant correlation between organizational silence and workplace ostracism. The results of mediation revealed that the indirect effect of workplace ostracism on both active and passive procrastination behavior through organizational silence was statistically significant, suggesting that organizational silence partially mediated this relationship. Conclusion The study highlighted the ongoing challenges posed by toxic workplace issues, such as organizational ostracism and silence, as significant factors contributing to nurses' procrastination behaviors. Not only do these factors directly impact nurses' productivity, but they also interact to exacerbate negative outcomes in nursing care. Addressing these toxic dynamics is critical to improving nurse performance and ensuring quality care in healthcare settings. Implications for nursing and health policy This study offers new insights for navigating toxicity and upgrading nursing productivity in healthcare organizations through fostering a more inclusive and communicative work environment. Promoting team cohesion and ensuring that all staff members feel valued and included can reduce feelings of isolation that may lead to procrastination. Also, creating safe spaces for nurses to voice concerns without fear of reprisal could significantly diminish passive procrastination, which ultimately enhances overall patient care quality and organizational efficiency.
Article
Bu araştırma, üniversite öğrencilerinin tükenmişlik düzeyleri, sosyal destek algıları ve psikolojik iyi oluş durumları ile istemsiz erteleme eğilimleri arasındaki ilişkileri ve ilişki yönünü belirlemek amacıyla gerçekleştirilmiştir. Bu amaç doğrultusunda ilgili literatürde yer alan ölçekler kullanılmıştır. Ayrıca bu çalışmada tanımlayıcı-ilişki arayıcı türde bir araştırma tipi tercih edilmiştir. Çalışma Erzincan Binali Yıldırım Üniversitesi sağlık hizmetleri meslek yüksekokulunda eğitim gören 1376 öğrenciden 328 kişiye ulaşılarak gerçekleştirilmiştir. Araştırmada örnekleme hatalarını azaltmak ve daha yüksek temsil yeteneğine sahip örneklemler oluşturmak için orantılı tabakalı örnekleme yöntemi kullanılmıştır. Araştırma verileri doğrultusunda öğrencilerin, tükenmişlik düzeyleri ile istemsiz erteleme eğilimleri arasında orta düzeyde pozitif bir ilişki, algıladıkları sosyal destek algıları ile istemsiz erteleme eğilimleri arasında negatif yönlü zayıf bir ilişki, psikolojik iyi oluşları ile istemsiz erteleme eğilimleri arasında negatif yönlü orta düzeyde bir ilişki tespit edilmiştir. Değişkenler arası yapılan regresyon analizi sonucuna göre de öğrencilerin tükenmişlik düzeyinin, algılanan sosyal desteğin ve psikolojik iyi oluşunun istemsiz erteleme eğilimi üzerinde anlamlı bir etkisinin olduğu sonucuna da ulaşılmıştır. Sonuç olarak, araştırma eğitim psikolojisi alanında öğrencilerin akademik başarısını etkileyen önemli bir faktör olan istemsiz erteleme davranışının altında yatan nedenleri daha iyi anlamamıza katkı sağlayarak, öğrencilerin motivasyonunu artırmaya yönelik programların geliştirilmesi için önemli bir araç sağlayacağı düşünülmektedir.
Book
The monograph constitutes a theoretical and empirical study of the phenomenon of procrastination, providing a comprehensive overview of its manifestations within the domains of organization and management. The book presents a systematic and comprehensive review of theoretical positions and results of empirical research on general procrastination and procrastination at work. It also includes the process of empirical verification of the structure of procrastination at work, tools for its diagnosis, subjective and organizational sources, and explanatory mechanisms in the Polish organizational context. The monograph's contemporary understanding of procrastination behavior offers managers insight into comprehending the nature and mechanisms underlying the manifestation or intensification of this prevalent phenomenon in the professional environment. It has the potential to raise the awareness of management practitioners to the emergence of procrastination behavior within the organizational structure. This knowledge can be instrumental in identifying risk factors and protective factors against employee procrastination behavior, as well as in developing individual and organizational intervention strategies. Consequently, organizations can cultivate employee engagement, creativity, and productivity while concomitantly mitigating employee procrastination. This can assist companies in optimizing their effectiveness in achieving their objectives and managing human resources, particularly in the domains of recruitment, selection, career development, and competence development. The monograph proposes an interdisciplinary perspective on the phenomenon of procrastination in professional contexts, integrating psychological and organizational perspectives to analyze the phenomenon. It takes into account subject and contextual conditions, as well as mechanisms that explain employees' procrastination behavior.
Article
Full-text available
Örgütlerde çalışan bireylerin sahip oldukları kontrol odağı türleri sosyal öğrenmeye yönelik kurdukları ilişkilerin şekillenmesinde etkili olmaktadır. Söz konusu sosyal öğrenme ilişkisinin bireyler üzerindeki en önemli etkilerinden bir tanesi de işyerinde erteleme (prokrastinasyon) davranışıdır. Bu araştırmanın temel amacı, çalışanların kontrol odağı türleri ve sosyo-demografik özellikleri ile işyerinde erteleme (prokrastinasyon) davranışları arasında anlamlı bir farklılığın olup olmadığının tespit edilmesidir. Bu amaçla Mersin ilinde faaliyet gösteren iki gıda üretim tesisinde görev yapan 236 çalışandan veri toplanmıştır. Anketler sonucu toplanan veriler SPSS programında faktör analizi başta olmak üzere çeşitli analizlere tabii tutulmuştur. Elde edilen araştırma bulgularına göre bireylerin sahip olduğu kontrol odağı türü ile işyerinde erteleme (prokrastinasyon) davranışı arasında ilişki tespit edilmiştir. Dışsal kontrol odağına sahip olan bireylerin işyerinde erteleme (prokrastinasyon) davranışı sergileme noktasında daha eğilimli oldukları gözlemlenmiştir. Bununla birlikte yaş, cinsiyet, medeni durum, eğitim durumu, mesleki tecrübe gibi sosyo-demografik özellikler açısından da anlamlı farklılıklar belirlenmiştir.
Article
Full-text available
Researchers and practitioners have long regarded procrastination as a self-handicapping and dysfunctional behavior. In the present study, the authors proposed that not all procrastination behaviors either are harmful or lead to negative consequences. Specifically, the authors differentiated two types of procrastinators: passive procrastinators versus active procrastinators. Passive procrastinators are procrastinators in the traditional sense. They are paralyzed by their indecision to act and fail to complete tasks on time. In contrast, active procrastinators are a "positive" type of procrastinator. They prefer to work under pressure, and they make deliberate decisions to procrastinate. The present results showed that although active procrastinators procrastinate to the same degree as passive procrastinators, they are more similar to nonprocrastinators than to passive procrastinators in terms of purposive use of time, control of time, self-efficacy belief, coping styles, and outcomes including academic performance. The present findings offer a more sophisticated understanding of procrastination behavior and indicate a need to reevaluate its implications for outcomes of individuals.
Article
Full-text available
Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software pack-ages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the develop-ment of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
Article
Full-text available
In this study, we extend previous work documenting links between procrastination, stress, and physical health by examining the potential role of mindfulness in explaining the high stress and poor health reported by procrastina-tors. A sample of 339 students (81% female) completed an on-line survey that included measures of trait procrastination, mindfulness, perceived stress, and per-ceived health. Univariate analyses revealed that procrastination was associated with low mindfulness, high stress, and poor perceived health. Structural equation mod-elling was used to test the role of mindfulness in explaining the links between procrastination and stress, and between procrastination and perceived health. The overall measurement model indicated a good fit to the data. Tests of the nested mediation models revealed that the effects of procrastination on stress and health were mediated by mindfulness, and bootstrapping analyses confirmed the signifi-cance of these effects. Our findings are consistent with previous research and theory on the salutatory effects of mindfulness for health and well-being and indicate that for procrastinators, low mindfulness may be a risk factor for poor emotional and physical well-being. This paper is based in part on data collected for Natalia Tosti's (2010) honours thesis.
Article
Full-text available
Explored the prevalence of avoidant, arousal, and decisional types of procrastination among 64 members of a public gathering, 54 professionals, 59 bank employees, and 34 university managers. At 4 public meetings, Ss (mean age 47.6 yrs) completed measures of demography and decisional, avoidant, and arousal procrastination. Results show that about 20% of the adult community population claimed to be chronic procrastinators, with the highest rates of all 3 procrastination types reported by members of the general public compared to other groups. Ss who were separated, divorced, or widowed reported higher rates of procrastination (independent of number of children) than Ss who were currently married or never married. Ss with high school education or less reported higher rates of decisional procrastination than Ss with college or postcollege educations. Occupational groups differed on decisional procrastination. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Objective: While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. Measurements: The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. Results: As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. Conclusion: In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
Article
Objective This paper presents the development and preliminary validation of a self-report instrument designed to measure metacognitions pertaining to symptoms control in the form of the following: (1) symptoms focusing and (2) symptoms conceptual thinking. Methods A total of 124 patients (95 female and 29 male) presenting with chronic fatigue syndrome (CFS) contributed data to the study to test the structure and psychometric properties of the Metacognitions about Symptoms Control Scale (MaSCS). Results A principal components factor analysis indicated that a two-factor solution best fitted the data. The factors were labelled positive and negative metacognitions about symptoms control. Further analyses revealed that both factors had good internal consistency. Correlation analyses established preliminary concurrent validity, indicating that both positive and negative metacognitions about symptoms control were significantly associated with levels of fatigue in CFS. Regression analysis revealed that positive and negative metacognitions about symptoms control significantly predicted fatigue severity when controlling for anxiety and depression. Conclusions The newly developed instrument may help future research that examines the role of metacognitions in CFS, as well as aiding clinical assessment and case formulation. Copyright © 2014 John Wiley & Sons, Ltd. Key practitioner message: The MaSCS is a useful first instrument to assess metacognitions in CFS. The MaSCS may help to deepen our understanding of symptoms control (symptoms focusing and conceptual thinking about symptoms) in the experience of CFS symptoms. Assessing and conceptualizing symptoms control through the MaSCS may aid treatment of CFS.
Article
The purpose of this study was to develop a self-report measure of procrastination tendencies and to investigate its relationship to a behavioral measure of procrastination and to a self-report measure of general self-efficacy. In a pilot study, the 72-item scale in a 4-point Likert-type response format was developed and administered to 50 college juniors and seniors. A factor analysis of the results yielded two factors which formed the basis for reducing the scale to 35 items with a resulting reliability of .90. The relationship between scores on the 35-item instrument and performance on a self-regulated performance task called the Voluntary Homework System (VHS) yielded a correlation of -.54, and a coefficient of -.47 was observed between the 35-item scale and the General Self-Efficacy Test (GSE; both correlations of p < .001). The correlation between GSE and VHS scores was .29 (p < .05). In a subsequent study of 183 college students, a factor analysis of scores on the 35-item scale yielded a single-factor structure and a condensed scale of 16 items with a reliability of .86. This shortened version of the procrastination scale was recommended for use as a means of detecting students who may tend to procrastinate in the completion of college requirements.
Article
The major patterns of self-regulatory failure are reviewed. Underregulation occurs because of deficient standards, inadequate monitoring, or inadequate strength. Misregulation occurs because of false assumptions or misdirected efforts, especially an unwarranted emphasis on emotion. The evidence supports a strength (limited resource) model of self-regulation and suggests that people often acquiesce in losing control. Loss of control of attention, failure of transcendence, and various lapse-activated causes all contribute to regulatory failure.
Article
Procrastination can have deleterious effects on well-being. Despite this, little is known about cognitive-attentional processes involved in procrastination. In this study, 12 individuals self-reporting problematic procrastination were assessed using a semi-structured interview to investigate: (1) whether they held positive and/or negative metacognitive beliefs about procrastination; (2) what was their main goal in procrastinating, and how they knew if they had achieved their goal; (3) how they directed their focus of attention when procrastinating; and (4) what they perceived the advantages and disadvantages of these attentional strategies to be. Results indicated that participants endorsed both positive and negative metacognitive beliefs about procrastination, and that the goal of procrastination was to regulate cognition and negative affect. Participants reported that they either did not know how to determine if they had achieved their goal or that an improvement in mood would signal the goal was achieved. Participants also reported that the principal object of their attentional focus when procrastinating was their emotional state. All participants were able to identify disadvantages to their attentional strategies, whilst nine participants described perceived advantages. The implications of the findings are discussed.
Article
The present study explored the relationships between metacognitions, negative emotions, and procrastination. A convenience sample of 179 participants completed the following questionnaires: General Procrastination Scale, Decisional Procrastination Scale, Meta-cognitions Questionnaire 30, Penn State Worry Questionnaire and Hospital Anxiety and Depression Scale. A cross-sectional design was adopted and data analysis consisted of correlation and multiple regression analyses. One dimension of metacognitions was found to be positively and significantly correlated with behavioral procrastination. Four dimensions of metacognitions were found to be positively and significantly correlated with decisional procrastination. Positive and significant relationships were also observed between anxiety, depression and behavioral procrastination; and between anxiety, depression, worry, and decisional procrastination. Multiple regression analyses indicated that depression and beliefs about cognitive confidence independently predicted behavioral procrastination, and that depression and positive beliefs about worry independently predicted decisional procrastination. These preliminary results would seem to suggest that metacognitive theory may be relevant to understanding procrastination.