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Abstract

Life regrets over inactions were found to have a long-term negative effect on people’s lives. Procrastination can be considered as a type of inaction; however, life regret regarding procrastination has been only briefly studied. The present study examined the factorial structure of the life-domain regret regarding procrastination scale (LDR-P) in two cultures (the US and Israel). In addition, the associations of regret regarding procrastination with general and behavioral procrastination measures and its mean scores were compared between the two cultures. Findings indicated a four-factor structure (career & community, interpersonal relationships, personal development, self-enhancement) based on the presence of procrastination in different life-domains. Further findings revealed strong associations between regret regarding procrastination and the two other procrastination measures mainly for the US sample. Finally, a comparison of factors means between the US and Israeli samples indicated that Americans more than Israelis experience regret over procrastination in education, career planning, finance and community life-domains. These results suggest both that life-domain regret regarding procrastination is a multi-dimensional construct that can be measured in different cultures and detect some cross-cultural differences. It should be further studied to better understand if and how it affects peoples’ lives, and how it can be addressed.
Life-domain regret regarding procrastination (LDR-P): Scale validation
in the United States and Israel
Marina Goroshit
1
&Meirav Hen
1
&Joseph R. Ferrari
2
#Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
Life regrets over inactions were found to have a long-term negative effect on peoples lives. Procrastination can be considered as a type
of inaction; however, life regret regarding procrastination has been only briefly studied. The present study examined the factorial
structure of the life-domain regret regarding procrastination scale (LDR-P) in two cultures (the US and Israel). In addition, the
associations of regret regarding procrastination with general and behavioral procrastination measures and its mean scores were
compared between the two cultures. Findings indicated a four-factor structure (career & community,interpersonal relationships,
personal development,self-enhancement) based on the presence of procrastination in different life-domains. Further findings revealed
strong associations between regret regarding procrastination and the two other procrastination measures mainly for the US sample.
Finally, a comparison of factors means between the US and Israeli samples indicated that Americans more than Israelis experience
regret over procrastination in education, career planning, finance and community life-domains. These results suggest both that life-
domain regret regarding procrastination is a multi-dimensional construct that can be measured in different cultures and detect some
cross-cultural differences. It should be further studied to better understand if and how it affects peopleslives, and how it can be
addressed.
Keywords Life-domains .Regret .Procrastination .Culture .Validation
Most people are familiar with the painful feelings of regret
resulting from the negative consequences of a bad action or a
poor decision. A chronic tendency to experience regret is consis-
tently correlated with lower subjective happiness and with higher
depression and can interfere with learning and future decision-
making (Reb and Connolly 2009), Roese and Summerville
(2005) showed that peoples biggest life-domain regrets were a
reflection of where in life they observed their largest opportuni-
ties for change, growth, and renewal. Other studies indicated that
regrets of inaction seem to last longer than regrets of action, in
part, because they reflect a greater perceived opportunity
(Morrison and Roese 2011). Interestingly, although procrastina-
tion can be considered one of the most studied types of inaction,
regret regarding procrastination in general and in different life-
domains has been only briefly studied (Ferrari et al. 2009;
Kuhnle et al. 2011; Pittman et al. 2008).Ferrarietal.(2009)
suggested that missing an opportunity to decide or act because
of engaging in procrastination might result in feelings of regret.
They studied life-domain regret in chronic procrastinators and
found that chronic procrastinators experience more regret than
non-procrastinators in 6 of 12 life-domains. Pittman et al. (2008)
discussed the option that anticipated regret mediates the relation-
ship between missed opportunity and further procrastination, and
Kuhnle et al. (2011) suggested that students would procrastinate
less as a way to avoid feelings of regret. These findings highlight
the need to further examine regret regarding procrastination in
order to better understand the dynamics underlying this phenom-
enon and how to address it.
Regret
Regret is often defined as an unpleasant, counterfactual, self-
focused emotion that results from having made an unfavorable
choice (Roese and Summerville 2005). In counterfactual
thinking, the actual is compared to the imagined possible,
*Marina Goroshit
marina@telhai.ac.il
1
Department of Psychology, Tel-Hai Academic College,
1220800 Upper Galilee, Israel
2
Department of Psychology, DePaul University, Chicago, IL, USA
Current Psychology
https://doi.org/10.1007/s12144-018-9801-2
resulting in negative feelings arising from the post-decisional
thought of the decision maker that estimates that his position
would have been better had he chosen differently (Halpern
and Leung 2015). As a negative emotional experience, regret
is believed to be subject to regulatory mechanisms that serve
to limit its sting but also to direct behavior toward fixing what
evoked the regret (Epstude and Roese 2008).
The vast majority of research on regret has focused on
the effects of anticipated and perceived regret regarding
consumer decision making (Gilbert et al. 2004), the dis-
tinction between regret pertaining to action and inaction
and the missed opportunity and correction effects of regret
(Beike et al. 2009). Further studies have indicated that the
tendency to regret is linked to lower levels of life satisfac-
tion and happiness and to higher levels of depression, guilt,
and disappointment (Berndsen et al. 2004;Schwartzetal.
2002; Zeelenberg et al. 2000).
Regrets concerning education and work in particular had a
negative impact on life satisfaction, and self-related regrets
were associated with depressive symptoms (Jokisaari 2004).
The ability to resolve and come to terms with life regrets has
been shown to contribute to better well-being for adults across
all ages (Dijkstra and Barelds 2008; Torges et al. 2008). In a
meta-analysis, Roese and Summerville (2005)proposedthat
opportunity breeds regret and found that Americanssix big-
gest regrets fall into the following life-domains: education,
career, romance, parenting,self-improvement,andleisure.
Further findings showed that when an older sample of
Americans was studied (non-college students), the most in-
tense life regrets were in romance and family, followed by
career, education, finance and parenting (Morrison and
Roese 2011).
Still in the framework of regret regulation theory, Beike
et al. (2009) argued that the intensity and prevalence of life-
domain regret was not affected by future opportunities for
corrective actions (Roese and Summerville 2005) but rather
by missed opportunities. People regret outcomes that could
have been changed in the past but can no longer be changed
and for which people experience low psychological closure
(Beike et al. 2009). These authors found that people experi-
enced most regret in the following life-domains: health, fi-
nance, self-improvement, family and education,followedby
lower levels of regret in parenting, romance, spirituality, com-
munity, friends, career and leisure. Finally, Morrison et al.
(2012) proposed that for non-college students, the regret in
social-based life-domains is more intense because they are
judged which constitute threats to belonging.
Most people believe that feelings of regret would be stron-
ger for actions than for inactions. However, studies showed
that young, middle-aged, and older adults from the United
States as well as from several other cultures tend to recall more
regrets of inaction than regrets of action when asked to recall
regrets accumulated throughout life (Gilovich et al. 2003;
Schwartz et al. 2002). Gilovich and Medvec (1995)suggested
that regrets of inaction and action might have different
temporal patterns, as people may regret their inactions more
so in the long term or regret their actions more so in the short
term. Gilovich et al. (1995) argued that regrets of inaction are
more psychologically Bopen^and imaginatively boundless,
whereas regrets of action are psychologically fixed by their
factual status and have only one alternative (not doing it).
Thus, regrets of inaction seem to last longer than regrets of
action, in part, because they reflect a greater perceived oppor-
tunity; however, intensity levels of both action and inaction
regrets seems to be similar and fade very slowly over time
(Beike and Crone 2008; Feldman et al. 1999;Roeseand
Summerville 2005).
Procrastination and Regret
Interestingly, although procrastination can be considered as
one of the most studied types of inaction, due to the tendency
to delay decisions and actions, the relationship between regret
and procrastination has been only briefly studied (Ferrari et al.
2009;Kuhnleetal.2011; Pittman et al. 2008). Procrastination
is often defined as the "voluntarily delay of an intended course
of action despite expecting to be worse off for the delay^
(Steel 2007, p. 66). It is considered as a personality character-
istic or a behavioral tendency that affects an individualslife
across settings and situations (Ferrari 2010). The recent liter-
ature on procrastination shows that as many as 2025% of
normal, healthy adult men and women in the United States
and in other countries around the globe are classified as chron-
ic procrastinators (Argiropoulou and Ferrari 2015; Ferrari
et al. 2007). In academic settings, the prevalence of procrasti-
nation is reported to be much higher (Steel and Klingsieck
2016). Further studies show that people procrastinate in the
workplace and when seeking a job (Nguyen et al. 2013;
Senecaletal.2003), in conducting health related behaviors
(Sirois 2015), in preparing for retirement (ODonoghue and
Rabin 2001),and in bedtime and sleep behaviors (Kroese et al.
2014). Recently, Klingsieck (2013) examined procrastina-
tion in six different life-domains, including academic and
work,everyday routines and obligations,health, leisure,
family and partnership, and social contacts.Herfindings
indicated that procrastination can be considered domain
specific and more typical for the academic and work,ev-
eryday routines and obligations, and health domains than
for the leisure, family and partnership,andsocial contacts
domains (Klingsieck 2013).
Curr Psychol
Overall, procrastination has been found to be associated
with some negative affective experiences, such as depressed
mood, anxiety, shame, guilt and low levels of well-being
(Beutel et al. 2016; Fee and Tangney 2000). Many other psy-
chological states, including social anxiety, forgetfulness, dis-
organization, non-competitiveness, dysfunctional impulsivity,
behavioral rigidity, and lack of energy, and lower states of self-
confidence and self-esteem were also found to be positively
associated with procrastination (Ferrari and Landreth 2014;
Ferrari et al. 2005;Riceetal.2012). Interestingly, although
most definitions of procrastination entail the presence of dis-
comfort, or the expectation of being worse off for the delay
(Ferrari 2010;Steel2010), feelings of regret have not been
specifically studied in relation to procrastination.
Pittman et al. (2008) discussed the option that anticipated
regret would mediate the relationship between missed
opportunity and further procrastination. Ferrari et al. (2009)
suggested that chronic procrastination might often result in
people failing to act either because they cannot make up their
mind (indecision) or because they wait to take action until it is
too late and that this failure might result in feelings of regret.
Using the life-domain regret (LDR) inventory (Roese and
Summerville 2005),Ferrarietal.(2009) measured life-
domain regret and procrastination in 2887 adults from across
the United States. Based on previous research that found pro-
crastination to be related to a variety of negative outcomes
(Steel 2007), these authors expected that chronic procrastina-
tors will report higher levels of life-domain regret, in compar-
ison to non-procrastinators. Their findings indicated that
chronic procrastinators reported significantly regret more,
rather non-procrastinators in the domains of education pur-
suits, parenting, family and friend interactions, health and
wellness, and financial planning. No significant differences
in the feelings of regret were found between chronic procras-
tinators and non-procrastinators in romance, career planning,
spiritual and self-improvements. Interestingly, these authors
also noticed that arousal procrastinators reported significantly
more regret than avoidant procrastinators in some life-do-
mains. Overall, these findings are preliminary, but strongly,
suggest thatthe association between regret and procrastination
should be further explored in general and in different life-
domains specifically.
The Current Study
Following the above literature, that indicates the long-term
negative consequences of regrets of inaction, the prevalence
of procrastination as a type of inaction in most life-domains
and the absence of studies on the relationship between these
two constructs, the main objective of this study was to
evaluate a newly developed measure of regret regarding pro-
crastination in different life-domains. Following Ferrari et al.
(2009), we used Roese and Summervilles(2005)Life-
Domain Regret (LDR) measure that included twelve catego-
ries. Each category represents a life-domain (family, friends,
leisure, health, finances, career, education, self-growth,
spirituality, community, parenting, and romance) in which
participants report whether they experience regret or not.
Each life-domain is followed by example (e.g., Career: jobs,
employment, earning a living (BIf only I were a dentist^)or
Health: exercise, diet, avoiding of treating stress (BIf I only
could stick to my diet^). Roese and Summerville (2005)used
each one of the twelve categories to represent a life-domain in
which a person may experience regret. Further, Ferrari et al.
(2009) converted this measure into a Likert-scale question-
naire asking participants to indicate to what extent they expe-
rience regret regarding each one of twelve life-domains (from
1=a little regret to 5 = a lot of regret). In addition, they used a
measure of general procrastination and examined the associa-
tions between these two variables.
In the present study, to specifically measure
procrastination-related regrets in different life-domains, we
modified the items of Ferrari et al. (2009) questionnaire. For
example, instead of asking about regret concerning an
Beducational degree and studying^, we asked about
Bprocrastinating in attaining an educational degree and
studying^or instead of regret about Bfinancial decisions/
investments^, we asked about Bprocrastinating in making fi-
nancial decisions/investments^. Unlike Ferrari et al. (2009)
that measured separately life-domain regret and procrastina-
tion, we directly asked respondents to reflect on their regret
regarding procrastinating in each life-domain. This direct
manner of asking people about their delays characterizes most
frequently used procrastination scales (Steel 2010).
Further, we validated our scale using general procrasti-
nation and decisional procrastination scales. Finally, in or-
der to allow the cross-cultural generalizability of findings,
usage of scales, and the overall detection of cross-cultural
differences in regret regarding procrastination, we validat-
ed this scale cross-culturally (Boer and Fischer 2013;
McCabe et al. 2008).
To conclude, our main goal was to adjust and evaluate an
instrument for a measurement of regret regarding procrastina-
tion in different life-domains, and it led to the following re-
search questions:
(1) What is the factorial structure of the life-domain regret
regarding procrastination (LDR-P) scale as documented
by exploratory factor analysis (EFA)?
(2) Is the factorial structure found in EFA valid for the US
and Israeli samples?
Curr Psychol
(3) Are English and Hebrew versions of the LDR-P scale
equivalent as documented by measurement invariance
across the US and Israeli samples?
(4) Is the LDR-P scale a valid and reliable measurement tool
as documented by discriminant and convergent validity
and reliability testing?
Methods
Participants and Procedure
The US sample consisted of 2300 adults with ages that ranged
from 25 to 67 (M=42.50, SD = 12.06). Sixty-one percent of
the sample was female; approximately 46% were single, 39%
were married, and 12% were divorced or separated.
Approximately 79% of the sample was Caucasian, and the
rest were Asian (3%), African-American (3%), Indian (3%)
or Hispanic (3%). Sixty-seven percent of the sample stated
that they were employed, 22% were students, 5% were retired
and 6% were unemployed.
Recruitment of participants was conducted through an on-
line questionnaire disseminated by DePaul University, USA.
The participation in data collection was voluntary and anony-
mous, and no incentives were offered for taking part in the
research.
The Israeli sample consisted of 897 Jewish adults with ages
that ranged from 25 to 70 (M=39.25,SD = 12.97). Sixty-one
percent of the sample was female; approximately 77% stated
that they were married, 62% were employed, 12% were stu-
dents, and 25% were employed and enrolled in school.
Recruitment of participants was conducted by an Israeli
online data collection company, which employs a panel of
over 100,000 participants representing the total Israeli
Jewish population (www.ipanel.co.il). The questionnaires
were translated by the first and the second authors using a
back-translation method and then transformed into their on-
line form using Qualtrics software (www.qualtrics.com). The
recipients who received the link to the survey were first
directed to a page containing an informed consent letter;
they were required to provide their informed consent before
proceeding to the survey itself.
Measures
To measure life-domain regret regarding procrastination
(LDR-P) we adapted the life-domain regret (LDR) inventory
(Ferrari et al. 2009; Roese and Summerville 2005). This in-
strument measures how much regret a participant has (from
1=a little regret to 5 = a lot of regret) in different life areas:
family, friends, leisure, health, finances, career, education,
self, spirituality, community, parenting, and romance. For the
purposes of our research, we rephrased each item to measure a
procrastination-specific regret. For example, instead of having
regret concerning an Beducational degree and studying^,we
asked about Bprocrastinating on an educational degree and
studying^or instead of regret about Bfinancial decisions/
investments^, we asked about Bprocrastinating on making fi-
nancial decisions/investments^.
To test discriminant and convergent validity, we used the
following measures:
1) The Adult Inventory of Procrastination (AIP;McCown
et al. 1989), which is a 15-item, 5-point Likert scale (from
1=false for me to 5 = true for me) that included items
such as BI do not get things done on time^and BIam
not good at meeting deadlines^. Previous studies reported
that the AIP was a valid and reliable measure of behav-
ioral procrastination with a Cronbachs alpha reliability of
.79.83 and a test-retest reliability score of .71 (Ferrari
1994; Ferrari et al. 1995). For the current study, we used
a composite score of AIP items with internal reliability
values of .91 for the US sample and .81 for the Israeli
sample.
2) The Decisional Procrastination Scale (DP,Mann1982)
consisted of five items on a 5-point Likert scale (1 = false
for me;5=true for me). Previous studies reported a
Cronbachs alpha ranging from .71 to .80 and a one-
month testretest reliability of .69 (Effert and Ferrari
1989; Ferrari 1994). For the current study, we used a
composite score of the DP items with internal reliability
values of .90 for the US sample and .88 for the Israeli
sample.
Data Analysis
The statistical analysis involved several steps. First, we calcu-
lated descriptive statistics of LDR-P items and presented ef-
fect sizes between the means of the items for our two samples.
Second, to explore a factorial structure of LDR-P, we per-
formed exploratory factor analysis (EFA). Third, we per-
formed a series of validation tests of LDR-P:
(1) To validate the structure found in the EFA, we performed
confirmatory factor analysis (CFA) of the LDR-P for
each sample separately and then performed a multiple
group confirmatory factor analysis (MGCFA) for both
samples simultaneously.
(2) To explore differences and similarities in the LDR-P
structure between the two samples, we tested measure-
ment invariance.
(3) We conducted reliability tests using composite reliability
and factor determinacy coefficients of internal
consistency.
Curr Psychol
(4) We tested discriminant validity by exploring the inter-
correlation between LDR-P factors, and we tested con-
vergent validity using an examination of correlations be-
tween LDR-P factors and two types of procrastination
(behavioral, as measured by AIP, and decisional, as mea-
sured by DP).
Results
Descriptive Statistics
Descriptive statistics of LDR-P items are shown in Table 1.
For the overall sample, it seems that health,career,community
and education life-domains had the highest means, while
parenting and spirituality life-domains had the lowest means.
Exploring the means of each sample separately shows that in
the US sample, participants had the most regret in health,
career,community and education life-domains, with means
of 3 or above, while parenting,spirituality and leisure life-
domains had the lowest means. In contrast, in the Israeli sam-
ple, only the health life-domain had a mean above 3, while the
spirituality life-domain had the lowest mean.
To give a sense to these differences and show the size
of effects between the two samples, we also computed
Cohensdvalues (Cohen 1988). As seen from Table 1,
for10of12items(exceptparenting and leisure), the US
participants scored higher than Israeli participants did.
The majority of effects in terms of effect size (s) were
small. For items 1 (career)and2(community), these
effects were medium.
Exploratory Factor Analysis
The US and Israeli samples were randomly split into two
datasets of approximately equal sample size: a Btraining
sample^(N= 1624, 72% participants from the US and 28%
participants from Israel) and two Bvalidation samples^(N=
1146 for the US sample and N= 447 for the Israeli sample).
Exploratory factor analysis (EFA) with robust maximum like-
lihood (RML) estimation using an exploratory SEM (ESEM)
procedure was performed on the training sample using
MPLUS 7.4 (Muthén and Muthén 2015). The advantage of
ESEM is that items can cross-load freely (like in EFA), but
model fit (SEM) is also assessed (Mathieu et al. 2013). This
approach also allows the exploration of the structure underly-
ing a given construct and provides the best solution in terms of
model fit. In our study, we compared factorial structures with
one, two, three and four latent variables. Oblique Geomin
rotation was chosen since the extracted factors were expected
to correlate (see Table 2).
Conventional fit indices and thresholds were used to exam-
ine the goodness of fit of the model being analyzed: χ
2
/df
[1;4], the root mean square error of approximation
(RMSEA) [0.05; 0.08], RMSEA 90% CI with its lower limit
close to 0 and the upper limit below 0.08, probability level
value of the tests of close fit (PClose) >0.50, standardized root
mean square residual (SRMR) [0.05;0.08], comparative fit
index (CFI) and Tucker-Lewis Fit Index (TLI) [0.90;0.95]
(Hu and Bentler 1999). In addition, we looked at Akaike
Information Criterion (AIC) and at Bayesian Information
Criterion (BIC) and searched for a model with the lowest
values (Raftery 1995).
We extracted models with one, two, three and four factor
solutions and compared them using a chi-square difference
Table 1 Means, standard deviations and Cohens d effect size values for the LDR-P inventory data
Item Overall sample(N= 3197) US (N= 2300) Israel (N=897) Cohensd
M SD M SD M SD
1 Career: jobs, employment, earning a living 3.16 1.27 3.34 1.30 2.70 1.18 0.52
2 Community: volunteer work, political activism 3.01 1.25 3.22 1.32 2.47 1.06 0.63
3 Education: school, studying, getting good grades 3.00 1.38 3.09 1.44 2.78 1.23 0.23
4 Parenting: interactions with offspring 2.27 1.17 2.20 1.18 2.44 1.13 0.21
5 Family: interactions with parents and siblings 2.70 1.23 2.73 1.28 2.61 1.11 0.10
6 Finance: decisions about money 2.93 1.34 3.00 1.41 2.75 1.17 0.19
7 Friends: interactions with close others 2.94 1.22 3.01 1.27 2.76 1.08 0.21
8 Health: exercise, diet, avoiding or treating illness 3.36 1.27 3.43 1.32 3.19 1.15 0.20
9 Leisure: sports, recreation, hobbies 2.73 1.25 2.63 1.30 2.97 1.12 0.28
10 Romance: love, sex, dating, marriage 2.93 1.37 3.01 1.42 2.74 1.23 0.20
11 Spirituality: religion, philosophy, the meaning of life 2.36 1.28 2.44 1.38 2.15 1.02 0.24
12 Self: improving oneself in terms of abilities, attitudes, behaviors 2.77 1.28 2.81 1.34 2.68 1.11 0.11
Curr Psychol
test using the Satorra-Bentler scaled chi-square, which is an
appropriate test for models with robust maximum-likelihood
estimation (Bryant and Satorra 2012). These comparisons re-
vealed that a model with four factors had the best fitting model
factors (χ
2
= 438.22, df = 54, p< .001, RMSEA = 0.03, CFI =
0.99, TLI = 0.96). Therefore, this four-factor model was sub-
sequently tested by confirmatory factor analysis (CFA) and
then by multiple-group confirmatory factor analysis
(MGCFA) using the second half of the US and Israeli dataset
(validation samples), separately.
The factor structure of the four-factor model is presented in
Tabl e 3. To determine the appropriateness of the four-factor
model, we examined the standardized factor loadings using a
cut-off 0.3 for item inclusion (Costello and Osborne 2009).
As seen in Table 3, we received four distinguishable factors: all
the items met the cut-off criterion, and there were no cross load-
ings. The first factor (career & community) consisted of items
regarding regret about career (item 1) and education (item 3),
which have the highest factor loadings, indicating that these two
items represent Factor 1 the most, and community (item 2) and
finance (item 6). The second factor (interpersonal relationships)
included items regarding regret about family (item 5, the highest
factor loading), parenting (item 4) and friends (item 7). The third
factor (personal development) involved items regarding regret
Table 2 Model fit indices of ESEM results from the training sample (N= 1624)
Model χ
2
df χ
2
/df p RMSEA (90% CI) PClose CFI TLI SRMR AIC BIC
1 factor 438.22 54 8.12 <.001 0.07 (0.06; 0.07) 0.00 0.88 0.85 0.05 53,944.70 54,137.64
2 factors 310.19 43 7.21 <.001 0.06 (0.05; 0.07) 0.00 0.91 0.87 0.04 53,780.46 54,032.36
3 factors 200.71 33 6.08 <.001 0.06 (0.05; 0.07) 0.06 0.95 0.89 0.03 53,638.63 53,944.12
4 factors 68.46 24 2.85 <.001 0.03 (0.02; 0.04) 1.00 0.99 0.96 0.02 53,535.05 53,888.77
Model comparison Δχ
2
Δdf p ΔCFI
2-factor vs. 1-factor 117.09 11 <.001 0.03
3-factor vs. 2-factor 92.63 10 <.001 0.04
4-factor vs. 3-factor 160.68 9 <.001 0.04
Table 3 Standardized factor loadings and standard estimates of the four-factor model (N =1624)
Factor
Factor 1:
Career &
community
Factor 2:
Interpersonal
relationships
Factor 3:
Personal
development
Factor 4: Self-
enhancement
Item M
(SD)
Loading SE Loading SE Loading SE Loading SE
1 Career: jobs, employment, earning a living 3.17 (1.33) 0.67 0.05 0.01 0.04 0.01 0.05 0.03 0.03
2 Community: volunteer work, political activism 3.12 (1.33) 0.34 0.06 0.14 0.08 0.09 0.08 0.14 0.08
3 Education: school, studying, getting good grades 3.01 (1.41) 0.61 0.08 0.06 0.07 0.01 0.05 0.02 0.06
4 Parenting: interactions with offspring 2.66 (1.61) 0.10 0.07 0.52 0.09 0.04 0.06 0.01 0.03
5 Family: interactions with parents and siblings 2.73 (1.28) 0.02 0.02 0.75 0.08 0.03 0.04 0.01 0.02
6 Finance: decisions about money 3.01 (1.38) 0.34 0.06 0.19 0.07 0.09 0.08 0.01 0.02
7 Friends: interactions with close others 3.01 (1.25) 0.07 0.07 0.41 0.09 0.22 0.09 0.02 0.05
8 Health: exercise, diet, avoiding or treating illness 3.40 (1.30) 0.09 0.14 0.03 0.06 0.65 0.14 0.01 0.02
9 Leisure: sports, recreation, hobbies 2.81 (1.31) 0.12 0.12 0.04 0.06 0.82 0.07 0.01 0.01
10 Romance: love, sex, dating, marriage 2.98 (1.42) 0.10 0.08 0.18 0.09 0.32 0.08 0.07 0.05
11 Spirituality: religion, philosophy, the meaning of life 2.38 (1.39) 0.02 0.03 0.01 0.05 0.01 0.02 0.93 0.32
12 Self: improving oneself in terms of abilities, attitudes, behaviors 2.80 (1.31) 0.19 0.09 0.01 0.07 0.18 0.13 0.36 0.21
Correlations between factors
Factor 1 Factor 2 Factor 3 Factor 4
Factor 2 .49
***
Factor 3 .53
***
.60
***
Factor 4 .32
***
.47
***
.45
***
Factor loadings in bold in bold identify the factor to which the item was assigned *p<.05, **p<.01, ***p<.001
Curr Psychol
about leisure (item 9, the highest factor loading), health (item 8)
and romance (item 9). The last factor (self-enhancement)includ-
ed two items: spirituality (item 11, the highest factor loading) and
self (item 12). The inter-correlations between the LDR-P factors
were moderate and ranged between .32 and .60, providing addi-
tional support for the multi-dimensional structure of LDR-P.
Validation of LDR-P
Construct Validity
To validate the factor structure found in EFA, we ran a confirma-
tory factor analysis (CFA) for each sample and then a multiple-
group confirmatory factor analysis (MGCFA), where each group
was a sample from our country of interest (the US or Israel). For
this purpose, we used a second portion of each split sample (a
validation sample).
The results of the CFA analysis produced the following re-
sults. For the US sample, χ
2
(48) = 163.85, χ
2
/df = 3.41,
RMSEA = 0.05 [90% CI: 0.04; 0.06], PClose = 0.52, SRMR =
0.05, CFI = 0.92, and TLI = 0.90. For the Israeli sample,
χ
2
(48) = 106.11, χ
2
/df = 2.21, RMSEA = 0.05 [90% CI: 0.04;
0.06], PClose = 0.61, SRMR = 0.06, CFI = 0.94, and TLI =
0.92. In addition, the results of the CFA provided acceptable
standardized item loadings (i.e., λij 0.30, p < .001) (see
Tab le 4). Overall, these results clearly provide support for the
four-factor solution model found in the EFA.
Tab le 4shows that there were some differences between
the US and Israeli samples, although the general pattern was
the same. The main difference can be seen in Factor 1 (career
& community): for the US sample, items with the highest
factor loadings were 1 (career)and3(education), while in
the Israeli sample, the item with the highest factor loading
was 6 (finance). Of course, these differences are descriptive
only, and formal tests are needed to determine whether they
are statistically significant. These tests were performed
following the steps suggested by Van de Schoot et al. (2012)
and are described in the next section.
Measurement Invariance of LDR-P across the Samples
Testing measurement invariance is crucial in cross-cultural
research addressing latent constructs. If we want to ensure that
comparisons of models involving latent variables are valid
across groups or time, we must establish some level of invari-
ance (Milfont and Fischer 2015; Van de Schoot et al. 2012).
To assess measurement invariance, we tested three levels of
invariance: configural, metric, and scalar (Steenkamp and
Baumgartner 1998; Vandenberg and Lance 2000).
Configural invariance is a test of weak factorial invariance in
which the same pattern of factor loadings hold across groups
(Vandenberg 2002). Configural invariance must be met for
subsequent tests (i.e., metric, scalar invariance) to be mean-
ingful. Metric invariance postulates that all factor loadings are
equal across groups (Cheung and Rensvold 2002). If metric
invariance is satisfied, factor covariance or unstandardized
regression coefficients can be compared across groups
(Steenkamp and Baumgartner 1998); the presence of metric
variance indicates that the construct has the same meaning
across the groups. Scalar invariance assumes that all item in-
tercepts are the same across groups. To meaningfully compare
groups and avoid biases that might be present even when
satisfying metric invariance, scalar invariance is needed
(Steenkamp and Baumgartner 1998). If scalar invariance is
met, then latent means can be meaningfully compared across
groups.
If metric or scalar invariance is not achieved, one can try to
establish partial measurement invariance, which requires at
least two loadings and intercepts that are equal across the
groups. In this case, latent factor means can still be compared
Table 4 Results of the
confirmatory factor analysis from
US and Israeli validation samples
(standardized factor loadings are
presented)
Item US (N = 1146) IL (N = 447)
Loading SE Intercept Loading SE Intercept
Factor 1: Career & community 1 0.58 0.04 3.35 0.47 0.06 2.77
3 0.61 0.04 3.05 0.52 0.05 2.94
6 0.45 0.03 2.93 0.65 0.04 2.94
2 0.48 0.04 3.15 0.42 0.06 2.72
Factor 2: Interpersonal relationships 5 0.6 0.04 2.68 0.66 0.05 2.78
4 0.59 0.04 2.19 0.4 0.05 3.36
7 0.68 0.03 2.94 0.72 0.04 2.84
Factor 3: Personal development 9 0.67 0.03 2.65 0.8 0.04 3.09
8 0.61 0.03 3.39 0.72 0.05 3.33
10 0.55 0.03 2.97 0.53 0.06 2.94
Factor 4: Self-enhancement 11 0.65 0.03 2.52 0.6 0.06 2.44
12 0.78 0.03 2.8 0.74 0.05 2.78
Curr Psychol
across the groups, but not the sum scores (Byrne et al. 1989;
Steinmetz 2013).
Model fit for configural, metric, and scalar invariance
models is shown in Table 5. The configural model with the
unconstrained factor loadings and intercepts had acceptable fit
indices. For the subsequent model, metric invariance held, as
indicated by nonsignificant chi-square difference tests and a
ΔCFI smaller than .01 (Cheung and Rensvold 2002).
However, scalar invariance did not hold, as shown by both
significant chi-square difference tests and a ΔCFI larger than
.01. Releasing intercepts of items 1 (career)and2
(community)inFactor 1 (career & community), item 4
(parenting)inFactor 2 (interpersonal relationships) and item
9(leisure)inFactor 3 (personal development) led us to a
model that did not differ significantly from the full metric
invariance model, meaning that partial scalar invariance was
achieved.
Reliability of LDR-P
To assess the reliability of the LDR-P factors, we calculated a
composite reliability (CR), which is usually calculated in con-
junction with structural equation modeling (Peterson and Kim
2013) and, in contradiction to Cronbachs alpha, does not
assume that all indicators have equal factor loadings (Hair
et al. 2006). The CR values found for the US sample are as
follows: .61 for Factor 1 (career & community), .66 for
Factor 2 (interpersonal relationships), .64 for Factor 3 (per-
sonal development), .and 68 for Factor 4 (self-enhancement).
The CR values for the Israeli sample are as follows: .60 for
Factor 1, .63 for Factor 2, .73 for Factor 3 and .62 for Factor
4. Therefore, for all the factors, the recommended threshold of
.60 (Bagozzi and Yi 1998) was achieved.
In addition, we calculated factor determinacy, which is a
measure of the quality of factor scores and which is expressed
as a correlation between the estimated factor score and the
factor itself. The factor determinacy scores were above the
desired threshold of .80 (Muthén and Muthén 2012). For the
US sample, factor determinacy scores were as follows: .85 for
Factor 1 (career & community), .86 for Factor 2 (interper-
sonal relationships) and for Factor 3 (personal development),
and .87 for Factor 4 (self-enhancement). For the Israeli sam-
ple, factor determinacy scores were as follows: .91 for Factor
1, .89 for Factor 2, .90 for Factor 3,and.87forFactor 4.
Discriminant and Convergent Validity
Discriminant validity was tested using the inter-correlations
between LDR-P factors, while convergent validity was tested
using the correlations between LDR-P factors and behavioral
procrastination (AIP) and decisional procrastination (DP).
These correlations are presented in Table 6. Discriminant va-
lidity requires that the dimensions of a construct reflect dis-
tinct components and, thus, should not be associated too
strongly. Although there is no standard rule, a correlation less
than .85 indicates that discriminant validity likely exists be-
tween the scales (Lee et al. 2014; Spreitzer 1995). Convergent
validity requires indicator loadings to be .6 or more (Bagozzi
and Yi 1998).
Results showed that for the US sample, the inter-
correlations between LDR-P factors ranged from .56 to .67,
while for the Israeli sample, they were between .71 and .89.
Correlations between LDR-P factors, AIP, and DP in the US
sample ranged between .37 and .73, while in the Israeli sam-
ple, they ranged between .06 and .26. Based on the guidelines
for discriminant and convergent validity as stated above, we
can conclude that the results are in favor for discriminant
validity and partially for convergent validity in the US sample,
but they raise some questions about these types of validity of
the measures in the Israeli sample.
The existence of metric and partial scalar invariances
allowed us to compare statistically correlations between the
LDR-P factors themselves, LDR-P factors and two other types
of procrastination and latent means of LDR-P factors between
the two samples. This was done by comparison of models
where correlation coefficients or latent means were
constrained to be equal between the two samples to the un-
constrained model where all the coefficients or latent means
Table 5 Measurement invariance tests and fit indices of the assessed models
Model (type of invariance) χ
2
df χ
2
/df p RMSEA (90% CI) Pclose CFI TLI AIC BIC SRMR
Configural 269.96 96 2.81 <.001 0.05 (0.04; 0.06) 0.63 0.93 0.91 52,285.79 52,734.26 0.05
Full metric 286.23 104 2.75 <.001 0.05 (0.04; 0.06) 0.71 0.93 0.91 52,288.08 52,693.83 0.05
Full scalar 487.92 112 4.36 <.001 0.07 (0.06; 0.07) 0.00 0.85 0.83 52,519.31 52,882.35 0.07
Partial scalar (1,2,4,9 free) 295.87 108 2.74 <.001 0.05 (0.04; 0.06) 0.73 0.93 0.91 52,289.54 52,673.94 0.05
Model comparison Δχ
2
Δdf p ΔCFI
Full metric vs. Configural 12.29 8 0.14 0.03
Full scalar vs. Full metric 201.68 8 <.001 0.04
Partial scalar vs. Full metric 7.26 4 0.12 0.04
Curr Psychol
were estimated freely. Since these models are nested within
each other, we used a Chi-square difference test to evaluate the
model fit of the constrained versus unconstrained model (Fan
and Sivo 2009) with Sattora-Bentler correction, because we
estimated our models with robust maximum likelihood
(RML) estimation (Satorra and Bentler 1994). Comparisons
of correlations revealed that all the inter-correlations between
the LDR-P factors were significantly stronger for the Israeli
sample (except the correlation between Factor 3 and Factor
4), while all the correlations between the LDR-P factors and
two other types of procrastination were significantly stronger
for the US sample (see Table 7). Comparisons of latent means
showed that the latent means of Factor 1 was significantly
higher for the US sample (difference of .54 points).
Discussion
Life regrets over inactions was found to have a long-term
negative effect on peoples lives (Beike et al. 2009;
Morrison et al. 2012; Morrison and Roese 2011).
Procrastination can be considered a prevalent unique type of
inaction, characterized by the presence of discomfort.
However life regrets in relation to procrastination was only
Table 6 Pearson correlations
between LDR-P factors and other
variables
US Israel
12 3456
1 Factor 1: Career & community .89
***
.74
***
.91
***
.26
***
.22
**
4 Factor 2: Interpersonal relationships .67
***
.76
***
.71
***
.19
**
.18
**
3 Factor 3: Personal development .65
***
.67
***
.62
***
.17
**
.13
*
4 Factor 4: Self-enhancement .66
***
.56
***
.67
***
.06 .24
***
5 AIP .73
***
0.42
***
.43
***
.37
***
.45
***
6DP .73
***
0.48
***
.44
***
.45
***
.63
***
*
p<.05;
**
p<.01;
***
p<.001
Table 7 Correlations between factors and latent means comparisons between the US and Israeli samples
Model Difference between correlation
coefficients (IL-US)
Model comparison using
Satorra-Bentler Scaled χ
2
1 Unconstrained χ
2
= 286.23, df = 104
2F1<>F2 equal .22 χ
2
= 297.16, df = 105 Δχ
2
=10.93,Δdf = 1, p < .001
3F1<>F3 equal .09 χ
2
= 289.36, df = 105 Δχ
2
=3.13, Δdf=1,p<.01
4F1<>F4 equal .25 χ
2
= 299.37, df = 105 Δχ
2
=13.14,Δdf = 1, p< .001
5F2<>F3 equal .09 χ
2
= 289.36, df = 105 Δχ
2
=3.13, Δdf = 1, p<.01
6F2<>F4 equal .15 χ
2
= 290.78, df = 105 Δχ
2
=4.55, Δdf = 1, p< .001
7F3<>F4 equal .05 χ
2
= 287.76, df = 105 Δχ
2
=1.53, Δdf = 1, p=.13
8F1<>AIP equal .47 χ
2
= 298.08, df = 105 Δχ
2
=11.85,Δdf=1,p<.001
9F2<>AIP equal .24 χ
2
= 290.80, df = 105 Δχ
2
=4.57, Δdf = 1, p < .001
10 F3 <>AIP equal .26 χ
2
= 291.38, df = 105 Δχ
2
=5.15, Δdf = 1, p < .001
11 F4 <>AIP equal .31 χ
2
= 292.10, df = 105 Δχ
2
=5.87, Δdf = 1, p < .001
12 F1 <>DP equal .51 χ
2
= 298.90, df = 105 Δχ
2
=12.67,Δdf = 1, p < .001
13 F2 <>DP equal .30 χ
2
= 292.33, df = 105 Δχ
2
=6.10, Δdf = 1, p < .001
14 F3 <>DP equal .31 χ
2
= 292.34, df = 105 Δχ
2
=6.11, Δdf=1, p<.001
15 F4 <>DP equal .21 χ
2
= 297.15, df = 105 Δχ
2
=10.92,Δdf = 1, p < .001
Difference between latent means (IL-US)
1 Unconstrained χ
2
= 295.86, df = 108
2 F1 equal 0.54 χ
2
= 350.56, df = 109 Δχ
2
=54.7, Δdf = 1, p < .001
3 F2 equal 0.02 χ
2
= 296.47, df = 109 Δχ
2
=0.61, Δdf = 1, p=.44
4 F3 equal 0.06` χ
2
= 297.07, df = 109 Δχ
2
=1.21, Δdf = 1, p=.27
5 F4 equal 0.03 χ
2
= 296.64, df = 109 Δχ
2
=0.78, Δdf = 1, p=.38
Curr Psychol
briefly studied (Ferrari et al. 2009; Kuhnle et al. 2011;Pittman
et al. 2008). Following the above literature and the absence of
a scale that specifically measures life-domain regrets regard-
ing procrastination, the main aim of this study was to adjust
the LDR scale (Roese and Summerville 2005) to measure
LDR regarding procrastination (LDR-P). In addition, we val-
idated this measure using a cross-cultural sample, in order to
allow the cross-cultural generalizability of findings, usage of
scales, and the overall detection of cross-cultural differences
in regret regarding procrastination (Boer and Fischer 2013;
McCabe et al. 2008). Finally, we examined the relationships
between the LDR-P scale factors and two other procrastina-
tion scales.
Our descriptive findings indicated that LDR-P scale re-
vealed the highest means in health,career,community and
education life-domains and the lowest means in parenting
and spirituality life-domains. When compared to other mean
scores in the life-domain regret literature (Beike et al. 2009;
Morrison and Roese 2011), similarities were found in some of
the most regretted life-domains (health,education and
career). However, several other life-domains differed.
Finance,self,romance and family life-domains were highly
regretted in the reviewed studies but were not in our study.
Further, in our sample, parenting and spirituality life-domains
were the least regretted, while in the reviewed studies, leisure,
friends and self life-domains were the least regretted. These
results may suggest that life-domain regret regarding procras-
tination is similar to life-domain regret regarding other inac-
tions (Gilovich et al. 2003), but only to some degree. This may
suggest that procrastination is a type of inaction, but it is
mostly a delay of the action and therefore is regretted in a
somewhat different manner. A comparison of our results to
the literature on life-domain procrastination (Klingsieck 2013)
reveals that people regret procrastination the most in those
life-domains where they tended to procrastinate the most
academics and work. Our results also partially aligned with
the results of Ferrari et al. (2009) who examined life-domain
regret in chronic procrastinators. In both studies, procrastina-
tion was most regretted in health and education life-domains
and the least in spirituality.
The results of the exploratory factor analysis revealed that
LDR-P is a multi-dimensional construct characterized by four
factors: Factor 1 (career and community)-career,education,
community,andfinance,Factor 2 (interpersonal relation-
ships) - family, parenting, and friends,Factor 3 (personal
development) -leisure,health,andromance,andFactor 4 -
spirituality and self (self-enhancement).
Based on previous literature, we expected that the factorial
structure of LDR-P would reflect both the life-domain regret
and the life-domain procrastination patterns mentioned in the
literature. We examined the missed opportunity principle
(Beike et al. 2009), and the inaction effect (Morrison and
Roese 2011) from the literature on regret and the life-domain
procrastination presence effect from the literature on procras-
tination (Ferrari et al. 2009;Klingsieck2013). The results of
the factor analysis indicated that the procrastination presence
effect could better explain our factorial structure as described
by Klingsieck (2013), suggesting Factor 1 (career &
community) as grouping the life-domains where people pro-
crastinate more often, and Factor 2 (interpersonal
relationships) as where people procrastinate less often.
Factors 3 (personal development)and4(self-enhancement)
involve those domains where people mildly procrastinate
(Klingsieck 2013). Our findings can also be explained by
Ferrari et al. (2009) findings regarding regret in avoidant pro-
crastinators. In their study, avoidant procrastinators mostly
regretted education, community, romance and career (similar
to Factor 1 in our study), and they least regretted family,
parenting, friends and self (similar to Factor 2 in our study).
Further, to validate the factorial structure of LDR-P, we
performed a confirmatory factor analysis in both the US and
Israeli samples and found that the four-factor structure held in
both cultures (configural invariance). We also found that peo-
ple from both cultures understood the LDR-P items in the
same manner, meaning that regression models and correla-
tions of its factors can be compared between these two cul-
tures (metric invariance). Finally, we found that people par-
tially rated the LDR-P items in the same manner, meaning that
latent means of those items can be meaningfully compared
between the two cultures (partial scalar invariance).
Comparisons of correlations between the two cultural
groups revealed some minor differences. We found that most
of the inter-correlations between the LDR-P factors were sig-
nificantly stronger for the Israeli sample, suggesting that
Israelis report more similarly regret regarding procrastination
across all life-domains in comparison to Americans. Further,
the correlations between the LDR-P factors and the two other
types of procrastination (general and decisional) were signif-
icantly stronger for the US sample, suggesting that the general
tendencies to procrastinate are associated to regret regarding
procrastination in all life-domains stronger in the US sample.
In addition, the comparisons of latent means showed that the
latent mean of Factor 1 (career & community) was signifi-
cantly higher for the US sample. These initial findings should
be interpreted with caution, but it may suggest that life-
domain regret regarding procrastination, similar to other hu-
man cognitive-emotional states, is influenced by cultural
norms and can be detected by the LDR-P scale. Other studies
that examined cross-cultural differences between these two
cultures assumed Israel as an collective-oriented culture that
is often characterized by low uncertainty avoidance, low fu-
ture orientation and strong intergroup relations, whereas the
US as an individualistic culture where independence, freedom
of choice, and pursuing individual goals are highly valued.
These studies revealed some differences in social attitudes,
work values and behavior (Baum et al. 1993;Berkowitz
Curr Psychol
et al. 2004; Elizur et al. 1991; Hojat et al. 2003; Leyser et al.
1994), between the two cultures, however no study that com-
pared feelings such as regret was found. Gilovich et al. (2003)
that compared regret over actions and inactions across
individualistic versus collective cultures did not find cultural
differences. On the other hand, Chen et al. (2006) found that
American in comparison to Chinese students had a greater
tendency to generate additive counterfactuals (inactions) in
the domains of schoolwork and family. They speculated that
this difference might reflect cultural differences in goal regu-
lation and self-improvement. Following these studies, our
findings may add to the notion that cross-cultural difference
is not imbedded in the overall mechanism of counterfactual
thoughts but rather can be detected in examining specific life-
domains. However, in order to better understand the actual
cultural meanings of these findings, further studies are needed.
Strengths, Limitations and Future Research
This study should be weighed in consideration of its strengths
and shortcomings that might suggest future lines of research.
First, it is the first study to provide an in-depth investigation
on the construct validity of the life-domain regret regarding
the concept of procrastination. Second, it is based on relatively
large samples, which provided the analyses with a good power
and allowed us to test the measurement invariance of the
LDR-P. Third, it shows promising results and provides initial
implications for a cross-cultural comparability of the LDR-P
construct. Fourth, unlike the majority of procrastination stud-
ies, our samples consisted of adult, non-student participants,
allowing for a wider range of life and regret experiences
(Morrison and Roese 2011).
Despite the strengths, a few limitations should be noted and
could be addressed in future studies. First, we employed a
closed questionnaire that asked people to refer only to twelve
life-domains, while other studies in the life-domain regret lit-
erature usually collect data by asking people to describe their
regrets (Dijkstra and Barelds 2008; Wrosch and Heckhausen
2002). Second, the data were self-reported and, as such, are
prone to various known biases (e.g., social desirability, mem-
ory recall biases). However, in the case of procrastination
research, the study by Krause and Freund (2014)showedthat
self-reported measures of procrastination were even more re-
liable than behavioral ones. Third, the data were collected
online and it is arguable that the use of traditional paper-and
pencil methods of data collection may have led to a different
set of results. However, previous research has demonstrated
that online responses are generally as valid and reliable as
those that are collected offline (Hiskey and Troop 2002).
Fourth, the LDR-P measure has been validated using samples
from two Western cultures, and westill know nothing about its
applicability for other cultures (e.g., Eastern). Finally, the clear
majority of our sample was Caucasian (for the US sample) or
Jewish (for the Israeli sample), which might constrain the
generalizability of our results to other ethnic groups.
Considering these limitations, future research on life-
domain regret as it regards procrastination should explore this
concept using closed and open-ended questionnaires and
should be replicated within different contexts and cultures. A
follow-up study might continue examining further psycho-
metric characteristics of the LDR-P, including convergent
and discriminant validity by using additional measures of pro-
crastination and other psychological variables. Finally, it is
also advisable that future studies using other designs (e.g.,
longitudinal) with more representative samples (e.g., proba-
bility samples) should be conducted.
Conclusions
This initial study suggests that LDR-P is a multidimensional,
valid construct that can be measured within groups and can be
compared cross-culturally. To strengthen and better under-
stand the factorial structure we found, this construct needs to
be further explored, and examined in relation to other con-
structs. A better understanding of this human experience can
benefit both the life-domain regret literature and, more impor-
tant, the literature regarding procrastination in different life-
domains, which is very limited. This understanding can con-
tribute to addressing and preventing procrastination and the
regret over procrastination in different life-domains. The val-
idation of our factorial structure in two very different cultures
widens our ability to measure and examine this construct
across different cultural groups and to make comparisons be-
tween them.
Compliance with Ethical Standards
Conflict of Interest All authors declare that they have no conflict of
interest in pursuing this publication.
Ethical Approval This article does not contain any studies with animals
performed by any of the authors. Informed consent was obtained from all
individual participants included in the study. All procedures performed in
studies involving human participants were in accordance with the ethical
standards of the institutional and/or national research committee and with
the 1964 Helsinki declaration and its later amendments or comparable
ethical standards.
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... After the research was carried out it was found that procrastination correlates directly with the other variables, more significantly with rumination, concluding, then, that students with higher levels of anxiety and depression participate in more negative repetitive thinking, which may contribute to procrastinating behavior as a result of a concern for depressing or painful thoughts about the past. Goroshit, Hen and Ferrari (2018) found in their research that there are strong associations between repentance regarding procrastination and that the Repentance of vital dominance about to procrastination is multidimensional and that is why cultural differences can be found. Wang et al. (2019) determined the predictive role of sensation seeking in smartphone addiction in adolescents was examined and also investigated whether the fear of getting lost (FoMO) and procrastination sequentially mediated the relationship between sensation seeking and smartphone addiction in adolescents, in a sample of 794 adolescents, finding that the partial procrastination partially and sequentially the relationship between the search for feelings and addiction to smartphones in teenagers. ...
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... 66). While Steel's definition is an accurate description for chronic procrastinators, Ferrari, who is another leading researcher in the study of procrastination (Ferrari, 2001;Ferrari & Diaz-Morales, 2014;Goroshit et al., 2020;Tibbett and Ferrari, 2019), explains that many people consider their procrastination as something that is helpful, believing they work best under pressure (Ferrari, 2001). Klingsieck (2013) names this "arousal procrastination" due to a perceived increase in motivation to act at the last minute. ...
... As procrastination-related negative consequences may occur in different domains and situations, the first step in developing such a scale is determining relevant domains/situations. Prior research (e.g., Gröpel and Kuhl, 2006;Ferrari et al., 2009;Klingsieck, 2013;Goroshit et al., 2020) has identified procrastination in several life domains, such as work (including academic work), everyday routines and obligations, health, leisure, family, and partnership, social and financial. Reviews and meta-analyses (e.g., van Eerde, 2003;Steel, 2007) have demonstrated procrastination tendencies ("trait procrastination") to be relatively stable across domains and situations, but it is important to recognize that situational and personality variables may be important in facilitating or hindering actual instances of procrastinatory behavior from occurring (e.g., Wäschle et al., 2014;Steel and Klingsieck, 2016;Svartdal et al., 2020). ...
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... After the research was carried out it was found that procrastination correlates directly with the other variables, more significantly with rumination, concluding, then, that students with higher levels of anxiety and depression participate in more negative repetitive thinking, which may contribute to procrastinating behavior as a result of a concern for depressing or painful thoughts about the past. Goroshit, Hen and Ferrari (2018) found in their research that there are strong associations between repentance regarding procrastination and that the Repentance of vital dominance about to procrastination is multidimensional and that is why cultural differences can be found. Wang et al. (2019) determined the predictive role of sensation seeking in smartphone addiction in adolescents was examined and also investigated whether the fear of getting lost (FoMO) and procrastination sequentially mediated the relationship between sensation seeking and smartphone addiction in adolescents, in a sample of 794 adolescents, finding that the partial procrastination partially and sequentially the relationship between the search for feelings and addiction to smartphones in teenagers. ...
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Addressing the lack of population-based data the purpose of this representative study was to assess procrastination and its associations with distress and life satisfaction across the life span. A representative German community sample (1,350 women; 1,177 men) between the ages of 14 and 95 years was examined by the short form of the General Procrastination Scale (GPS-K; 1) and standardized scales of perceived stress, depression, anxiety, fatigue and life satisfaction. As hypothesized, procrastination was highest in the youngest cohort (14-29 years). Only in the youngest and most procrastinating cohort (aged 14 to 29 years), men procrastinated more than women. As we had further hypothesized, procrastination was consistently associated with higher stress, more depression, anxiety, fatigue and reduced satisfaction across life domains, especially regarding work and income. Associations were also found with lack of a partnership and unemployment. Findings are discussed with regard to potential developmental and cohort effects. While procrastination appears to be a pervasive indicator for maladjustment, longitudinal analyses in high-risk samples (e.g. late adolescence, unemployment) are needed to identify means and mechanisms of procrastinating.
Chapter
As indicated in Chapter 1, there is reason to believe that procrastination is an important subject for empirical research. Tasks that are not completed promptly may reduce both individual performance and organizational effectiveness (Ferrari, 1993a; 1994). Furthermore, they may be a source of stress to those individuals who are expected to complete the tasks (McKean, 1990). Articles and books on procrastination have appeared recently in the popular press (e.g., Burka & Yuen, 1983; Cornyn-Selby, 1986; Ellis & Knaus, 1977; Gagliard, 1984; Knaus, 1973). Useful theory and research have begun to be conducted. However, before theory construction and substantial research are performed, precise measurement of the construct is needed. Our purpose in this Chapter is to address the psychometric properties of several self-report measures of procrastination.
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This article explores the viability of conducting longitudinal survey research using, the Internet in samples exposed to trauma. A questionnaire battery assessing psychological adjustment following adverse life experiences was posted online. Participants who signed up to take part in the longitudinal aspect of the study were contacted 3 and 6 months after initial participation to complete the second and third waves of the research. Issues of data screening and sample attrition rates are considered and the demoaraphic profiles and questionnaire scores of those who did and did not take part in the study during successive time points are compared. The results demonstrate that it is possible to conduct repeated measures survey research online and that the similarity in characteristics between those who do and do not take part during successive time points mirrors that found in traditional pencil-and-paper trauma surveys.
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We consider a setting where a decision maker’s uncertainty is represented by a set of probability measures, rather than a single measure. Measure-by-measure updating of such a set of measures upon acquiring new information is well known to suffer from problems. To deal with these problems, we propose using weighted sets of probabilities: a representation where each measure is associated with a weight, which denotes its significance. We describe a natural approach to updating in such a situation and a natural approach to determining the weights. We then show how this representation can be used in decision making, by modifying a standard approach to decision making—minimizing expected regret—to obtain minimax weighted expected regret (MWER). We provide an axiomatization that characterizes preferences induced by MWER both in the static and dynamic case.