The Association Between Mindfulness and Procrastination: A Meta-Analysis (2024)

 Liam Moloney, John M. Malouff, & Jai Meynadier 

University of New England, Australia 

Please send correspondence regarding this article to John M. Malouff, University of New England School of Psychology, Armidale NSW 2350, Australis. Email: jmalouff@une.edu.au.  

Keywords: association, correlation, meta-analysis, mindfulness, procrastination 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Abstract 

Objectives: Mindfulness is a powerful psychological condition that may be associated with lower levels of procrastination, a phenomenon that can negatively impact an individual’s physical, emotional, and financial wellbeing. This study explored the association between mindfulness and procrastination.  

Method: A meta-analysis synthesised the results from 33 studies that included a total of 11,817 participants. The meta-analysis used a random-effects model to calculate an overall weighted effect size. Lower mindfulness was significantly associated with more procrastination (r = -.38, p < .001, 95% CI [-.44, -.32], k = 33). The association held across nations, groups of researchers, and types of measures. Moderator analyses were used to investigate potential causes of heterogeneity, but none of the potential moderators that were tested had a statistically significant association with the overall effect size. A quality assessment of the studies included in the meta-analysis showed that 28 of the 33 studies measuring mindfulness and procrastination used measures with published evidence of reliability and validity. The findings suggest that mindfulness-based interventions are worth exploring in reducing procrastination.  

 

 

 

 

 

 

 

 

 
 
The Association Between Mindfulness and Procrastination: A Meta-Analysis 

Procrastination can be described as a form of self-regulatory failure and can be defined as the delay of a task for a maladaptively long time (Sirois & Pychyl, 2013; Steel, 2007). Procrastination is a complex and multi-faceted phenomenon, influenced by individual, environmental and psychological factors (Klingsieck, 2013). Anxiety, low emotional regulation, poor attentional control, irrational beliefs, fear of failure and perfectionism are all factors that have been found to be associated with procrastination (Pychyl & Flett, 2012; Steel, 2007). Not only does procrastination have adverse consequences for individuals, but it also imposes costs on the broader economy via reduced productivity, with research finding that most employees procrastinate for a quarter of their working day (Nugyen et al., 2013).   

Estimates suggest that approximately 20 per cent of the adult population struggle with chronic procrastination across a range of domains, including in professional settings, social relationships, and in the management of personal finances (Abassi & Alghamdi, 2015). Procrastination is particularly prevalent in educational settings, with over 50 per cent of university students indicating they would like to reduce their procrastination towards academic tasks such as completing assignments or studying for exams (Rahimi & Hall, 2021). Evidence suggests that procrastination is associated with a range of negative health outcomes, including anxiety, stress and depression (Rozental et al., 2018). Research has also found that procrastination is negatively associated with academic performance and positively associated with course withdrawal rates (Balkis et al., 2013; Gautam et al., 2019; Yockey, 2016). 

Treating Procrastination 

Despite the prevalence of procrastination, there is only limited research on its effective treatment (Glick & Orsillo, 2015). Some researchers attribute this shortage to the competing perspectives on procrastination’s underlying causes, while others contend it may be because procrastination is not classified as a psychological disorder (Rist et al., 2023; Zacks & Hen, 2018). Currently, the treatment of procrastination largely focuses on behaviour modification techniques related to time management, goal setting and self-regulation (Klingsieck, 2013). Evidence also suggests that cognitive behaviour therapy can reduce procrastination, but its efficacy remains unclear due to the small number of studies that have been conducted to date (Rozental et al., 2018). Recently, a small number of randomised controlled trials (RCTs) have found that mindfulness-based interventions can be effective in reducing procrastination (Rad et al., 2023; Schutte and de Bolger, 2020). While these findings represent a promising development, further experimental studies are required to examine whether the effects of mindfulness-based interventions remain stable over time. 

Mindfulness and Mindfulness-Based Interventions 

Mindfulness can be defined as the non-judgemental awareness and acceptance of present moment experiences (Shapiro et al., 2006). Some of the characteristics that underpin mindfulness include: a non-reactive approach towards inner thoughts and experiences; the regulation of attention; an orientation to the present moment; and a capacity to observe and label thoughts, perceptions, feelings and sensations (Baer et al., 2006; Brown et al., 2007). Mindfulness can be conceptualised as a trait that represents an individual’s general mindfulness in daily life, or a state that reflects the degree to which an individual is mindful in a specific moment, such as after meditating (Blanke & Brose, 2016; Sala et al., 2019).  

Evidence from RCTs indicate that mindfulness-based interventions such as mindfulness-based stress reduction programs or mindfulness-based cognitive therapy reduce symptoms associated with anxiety and depression (Fjorback et al., 2011; Polizzi et al., 2018). Mindfulness-based interventions have also been found to improve the management of chronic pain and reduce the symptoms of a number of stress related health conditions (Creswell, 2017). Additionally, meta-analyses indicate that mindfulness-based interventions are associated with a reduction in symptoms associated with post-traumatic stress disorder and may be effective in treating substance use disorders (Hopwood & Schutte, 2017; Cavicchioli et al., 2018). While the precise mechanisms responsible for the health benefits associated with mindfulness remain unknown, neuroimaging findings suggest that mindfulness-based interventions lead to functional changes in areas of the brain which are involved in regulating attention and emotion. For example, research has found that mindfulness-based interventions lead to the activation of brain regions involved in attentional control such as the anterior cruciate cortex (Tang et al., 2015). Research has also shown that areas of the brain involved in the regulation of emotions, including the amygdala and the subgenual anterior cingulate cortex, displayed decreased activation following a mindfulness-based intervention (Creswell & Lindsay 2014; Creswell, 2017). Since poor regulation of attention and emotion are factors that have also been found to be associated with procrastination, these neuroimaging findings suggest that mindfulness-based interventions could be effective in reducing procrastination (Sirois & Pychyl, 2013; Tang, 2015). 

The Association Between Mindfulness and Procrastination 

A number of cross-sectional studies have reported an association between mindfulness and procrastination, with several finding a medium effect size for the association, indicated by Pearson’s r correlation coefficients ranging from r = -.30 to r = -.50 (e.g., Bu et al., 2022; Egan et al., 2023; Gautam et al., 2019; Li et al, 2023; Sirois & Tosti, 2012). Gautam et al. (2019) examined the relationship between mindfulness, procrastination and anxiety among a sample of 801 American college students. The study reported a significant relationship between mindfulness and procrastination (r = -.44, p < .001), as well as a significant association between mindfulness and anxiety (r = -.61, p < .001). Gautam et al. (2019) suggested that the mechanism by which mindfulness could reduce procrastination is through decreasing anxiety. This explanation is consistent with evidence from RCTs, which suggests that increased emotional regulation and attention are the mechanisms through which mindfulness-based interventions could reduce procrastination (Rad et al., 2023; Schutte & de Bolger, 2020). This explanation is also consistent with previous research which found that individuals procrastinate to avoid tasks that cause them anxiety (Klingsieck, 2013; Tice et al., 2001). Additionally, research has found that higher mindfulness is associated with greater attentional control and emotional regulation (Sirois & Pychyl, 2013; Tang, 2015).   Therefore, individuals with higher levels of mindfulness might procrastinate less when completing tasks due to having a greater ability to regulate attention and emotion (Rad et al., 2023).   

Study Aims and Rationale 

The aim of the current meta-analysis was to synthesise the findings of all known studies that have reported an association between mindfulness and procrastination. Although there is accumulating evidence suggesting that mindfulness is negatively associated with procrastination, the strength of the association has not been consistent in previous research, ranging from r = -.04 (Rad et al., 2023) to r = -.83 (Luo et al., 2023). Hence, the purpose of this meta-analysis was to provide a robust estimation of the association between mindfulness and procrastination across all known studies and explore some possible moderators of the effect size. Meta-analysis is an important part of the scientific process as it provides a formal methodology for the synthesis of results across studies that differ in various ways, such as in their geographical location, methodology, and sample characteristics (Gurevitch et al., 2018). Meta-analysis also enables inferences to be drawn from a larger evidence base than from individual studies alone, and thus provides a more accurate estimation of an effect size and the factors that influence this effect size (Gurevitch et al., 2018). My research hypothesis was that there would be a negative association between mindfulness and procrastination across studies, with lower mindfulness being associated with more procrastination.  

Methods 

Search Strategy 

The search strategy and reporting of the meta-analysis was informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (see Appendix A; Page et al., 2021). The protocol for the meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO) in March 2024. The registration number is concealed here to maintain author anonymity. The protocol was updated in PROSPERO on 10 July 2024 to include information on the exploratory moderator analyses, for which there were no hypotheses. To locate all relevant published and unpublished studies reporting an association between mindfulness and procrastination, a second researcher and I independently completed a systematic search of four databases: EBSCOhost, ProQuest, PubMed, and Scopus. The search terms used were mindful* AND procrastin*. There were no restrictions placed on language or publication date. I requested that each database notify me if any relevant research was published after the search was conducted. I examined the reference lists of all included studies to locate further relevant research. I then used Google Scholar’s forward citations function to identify any additional relevant research. Studies located through the systematic search were imported to Covidence (2024), a software program that streamlines the screening phase of the meta-analysis. Studies were initially screened by title and abstract, and then by full text if further information was required to determine their eligibility for inclusion in the meta-analysis. The second researcher and I completed the systematic search and screening process in April 2024. Data collection for the meta-analysis ended on 7 July 2024. 

Eligibility Criteria 

To be eligible for inclusion in the meta-analysis, a study had to report a correlation coefficient value (Pearson’s r) measuring the association between mindfulness and procrastination. A study also had to report a sample size (N) corresponding to the correlation coefficient value. There were no further qualifying criteria. 

Data Extraction and Coding 

In order to calculate an overall weighted effect size for the association between mindfulness and procrastination, I extracted the correlation coefficient and sample size from each study. I also coded the following sample characteristics of each study as part of the data extraction process: a) study author/s and publication year, b) the country in which the study was conducted, c) mean age of participants in each study, d) percentage of participants that were female in each study, e) study design (e.g., cross sectional or longitudinal), f) population sampled (e.g., employees or students), g) the scales used to measure mindfulness and procrastination and whether these scales had evidence of reliability and validity, h) whether the scales were translated, and i) whether English was the main language for the country in which the study was conducted.  

I manually extracted and coded all of the relevant data and entered it into a data file. A second researcher independently checked my data entries. Disagreements were resolved by discussion and consensus. A third researcher then independently checked one third of the studies for the data required to calculate an overall effect size and conduct exploratory moderator analyses. Using the standard that a disagreement of less than five per cent constitutes an agreement, the inter-rater agreement rate was 100 per cent.  

Data Analysis 

I conducted data analyses using version four of Comprehensive Meta-Analysis software (Borenstein, 2022). The meta-analysis used a random-effects model to pool the Pearson’s r correlation coefficient values to calculate an overall weighted effect size. This model assumes that it is likely that the true effect size varies across studies (Borenstein et al., 2010). This assumption was reasonable to make in the context of this meta-analysis as there were differences in sample characteristics across the studies, as well as differences in the scales used to measure the association between mindfulness and procrastination. The weighted effect size was calculated by the software assigning greater weight to studies with lower variance in their effect size estimates, which enables a more precise measure of the overall effect size across studies (Borenstein et al., 2010). To test the robustness of the meta-analytic results, I conducted sensitivity analyses using the one-study removed method. This method involves repeatedly performing the meta-analysis with a different study removed each time to assess whether the overall effect size is substantively influenced by any single study (Borenstein et al, 2021). Cochran’s Q statistic was used to test the null hypothesis that all studies included in the meta-analysis share a common effect size. A statistically significant Q test indicates that there is heterogeneity in the effect size across studies (Borenstein, 2020). The l² statistic was used to examine the proportion of variance in the effect size across studies attributable to true variance rather than sampling error (Borenstein, 2020). 

Publication Bias 

Publication bias can arise if not all completed studies are published. For example, studies that report either large effect sizes or statistically significant results are more likely to be published than studies that do not (Borenstein et al., 2021). Publication bias may result in a meta-analysis overestimating the true effect size (Borenstein et al., 2021). I assessed publication bias through visual inspection of the funnel plot, looking for a larger concentration of studies on one side of the overall effect size to indicate the likely presence of publication bias (Borenstein et al., 2022). I also assessed publication bias using the trim and fill method, which examines for any major asymmetry in the distribution of studies around the overall effect size. If any major asymmetry is found, missing studies are imputed, and the overall effect size is recalculated, correcting for publication bias (Borenstein et al., 2022; Duval & Tweedie, 2000). Additionally, I performed Egger’s test to assess for publication bias. This test examines whether the slope of the regression line, which represents the overall effect size, is significantly different from the intercept, which represents publication bias (Egger et al., 1997).  

Moderator and Subgroup Analyses 

Meta-regressions were performed to evaluate whether the mean age or proportion of female study participants were moderators of the overall effect size. Additionally, a meta-regression was used to assess whether study quality, as measured against a four-point quality assessment framework, moderated the overall effect size. I also conducted a subgroup analysis to test if the overall effect size was moderated by whether English was the main language in the country a study was conducted in. 

Results 

Results of Literature Search 

The systematic search of four databases, reference lists of eligible studies, and Google Scholar’s forward citations function located 185 relevant studies. Of these studies, one was unable to be retrieved, despite my attempts. After duplicates were removed and the screening process was completed, 31 studies were determined to be eligible for inclusion in the meta-analysis. One of these studies included three independent samples (Zhong, 2021), which I treated as three separate studies. In total, the meta-analysis synthesised the results from 31 studies and 33 independent samples. For the purpose of clarity, I will refer to samples as studies from this point forward. Of the 13 studies excluded at the full text screening phase, seven were excluded for not reporting a correlation coefficient value for the association between mindfulness and procrastination. I contacted the corresponding author of each of these studies and requested this information, but I did not receive responses to any of my requests for information. Additionally, I found that three studies, all by the same researcher, reported identical data, including correlation coefficients and sample sizes. To ensure the independence of the samples included in the meta-analysis, I excluded two of these studies (Ahmad et al., 2022; Hussain & Ahmad, 2022), but retained the earlier study (Ahmad, 2019). Two further studies by a separate researcher also reported identical correlation coefficients and sample sizes, so I excluded one of these studies (Gautam, 2017). Additionally, three studies were excluded as they did not measure the association between mindfulness and procrastination.  

Of the 33 studies included in the meta-analysis, 27 were identified through database searches or subsequent database alerts, four through Google Scholar’s forward citations function, and two through searching the reference lists of eligible studies. In four studies (Fan et al., 2024; Flett et al., 2016; Parlade, 2022; Sirois & Tosti, 2012), the same sample was assessed using different outcome measures, resulting in multiple correlation coefficient values being reported for a single sample. In each of these studies, I used the average of the correlation coefficient values reported across the multiple outcome measures to provide an overall correlation coefficient value for the association. Two studies (Jayaraja et al., 2017; Tran et al., 2024) reported two different sample sizes in their study. As the corresponding authors of each study did not respond to my request for further information, the sample size reported in the correlation matrix was used in the Jayaraja et al. (2017) study, and the smaller sample size was used for the Tran et al. (2024) study. Another study (Ergin et al., 2019) reported two different correlation coefficient values for the association between mindfulness and procrastination: one positive and one negative. I contacted the corresponding author of this study and asked which was the correct correlation coefficient value, but the author did not respond. I made the decision to use the negative correlation coefficient value as this value was consistently reported throughout the study.  

Twenty eight of the 33 studies included in the meta-analysis were cross-sectional. Three of the studies were experimental, two of which examined whether mindfulness-based interventions were effective in reducing procrastination (Rad et al., 2023; Schutte & de Bolger, 2020), while the other explored whether mindfulness or procrastination mediated any treatment effects of a stress reduction program (Drozd et al., 2013); the baseline correlation coefficient value between mindfulness and procrastination was used as the effect size in these studies. The remaining two studies were longitudinal (Cheung & Ng, 2019; Luo et al., 2023); the baseline correlation coefficient value between mindfulness and procrastination was used as the effect size for the Cheung and Ng (2019) study, and the post-test between-person correlation coefficient value was used as the effect size in the Luo et al. (2023) study, as this was the only time point the association was measured. The PRISMA flow diagram presented in Figure 1 provides further information about the process involved in determining the final list of eligible studies for the meta-analysis (Page et al., 2021).  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1 

PRISMA Flow Diagram of Study Selection Process for Meta-Analysis 

[contact John Malouff at jmalouff@une.edu.au for Figure 1]

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample Characteristics 

Table 1 provides detailed information for each study included in the meta-analysis. The 33 studies synthesised in the meta-analysis included 11,817 participants. The sample sizes across the studies varied widely, ranging from 30 to 1258. Of the 26 studies which reported mean age, the overall weighted mean age was 20. Of the 32 studies which reported the percentage of female participants, the overall weighted percentage of female participants was 64 per cent. Nine studies were conducted in China, six in the United States, four in Iran, three in Turkey, two in Pakistan, two in Canada, and one each in Australia, Malaysia, Norway, the Republic of Korea, Saudia Arabia, the United Kingdom, and Vietnam. English was the main language for the country in which 10 of the 33 studies were conducted. I translated three studies to English via Google Translate, one from Mandarin (Peng et al., 2024), one from Farsi (Jobaneh et al., 2016), and one from Turkish (Bedel, 2017). Thirty of the 33 studies sampled high school students or university students. Of the remaining three studies, one sampled a population of telecommunications employees (Ahmad, 2019), another a population of manufacturing employees (Zhong, 2021), and one did not specify (Drozd et al., 2013), Additionally, all studies measured the association between procrastination and mindfulness using self-report scales. All of the studies measured trait procrastination. With the exception of the Luo et al. (2023) study, which measured state mindfulness, all of the studies measured trait mindfulness. 

 

 

 

 

 

 

Table 1 

Information About the 33 Studies Included in the Meta-Analysis 

Study and Country	Sample size	% female	Mean age of sample	Name of mindfulness   scale (α)	Name of procrastination scale (α)	Effect size (Pearson’s r)
Ahmad, 2019 (Pakistan)	400	24	NR	MAAS (.87)	TPS (.85)	-.260
Bedel, 2017 (Turkey)	145	76	NR	MAAS (.83)	APS (.89)	-.470
Bu et al., 2021 (China)	512	69	NR	MAAS (.86)	API (.85)	-.421
Cheung and Ng, 2019 (China)	339	70	20	FFMQ (.86)	TPS (.76)	-.410 a
Drozd et al., 2013 (Norway)	259	75	33	MAAS (.90)	MDQ-P (.92)	-.560 a
Egan et al., 2022 (United Kingdom)	206	80	30	FFMQ-S (.78)	GPS (.82)	-.460
Einabad et al., 2019 (Iran)	111	50	21	KIMS (.82)	PASS (.78)	-.110
Eltayeb, 2021 (Saudi Arabia)	206	100	NR	MS (.81)	PS (.82)	-.472
Ergin et al., 2019 (Turkey)	400	38	NR	MAAS (NR)	APS (.89)	-.220
Fan et al., 2024 (China)*	713	51	13	FFMQ (NR)	API (.84)	-.181
Flett et al., 2016 (Canada)*	214	71	20	MAAS (.88)	PASS (.83) b	-.406
Gautam et al., 2019 (United States)	801	69	19	FFMQ (.86)	TPS (.93)	-.437
Jayaraja et al., 2017 (Malaysia)	448	56	21	MAAS (.86)	GPS (.73)	-.290
Jobaneh et al., 2016 (Iran)	331	NR	20	FMI (.97)	PASS (.99)	-.390
Lee, 2019 (Republic of Korea)	444	47	21	MAAS (NR)	GPS (NR)	-.461
Li et al., 2021 (China)	343	73	NR	MAAS (.87)	PASS (.90)	-.504
Lina et al., 2023 (China)	632	85	20	FFMQ (.86)	GPS (.88)	-.483
Luo et al., 2023 (China)	252	100	20	MSMQ (NR)	TPS (.98)	-.830 c
Maga, 2023 (United States)	337	60	21	FFMQ-S (NR)	APS (NR)	-.270
Parlade, 2022 (United States)*	310	67	21	KIMS (NR)	PPS (.92)	-.156
Peng et al., 2024 (China)	514	75	20	MAAS (.86)	IPS (.82)	-.314
Rad et al., 2023 (Iran)	30	43	20	FMI-S (.82)	MMAP (.89)	-.037 a
Rezaei and Zabardast, 2021 (Iran)	350	100	16	FFMQ (NR)	APS (.73)	-.150
Riaz and Saif, 2017 (Pakistan)	385	55	NR	FFMQ (NR)	GPS (NR)	-.424
Schutte et al., 2020 (Australia)	170	76	35	FMI-S (.88)	GPS (.88)	-.270 a
Serrano et al., 2022 (United States)	233	73	25	MAAS (.86)	PPS (.92)	-.740
Sirois and Tosti, 2012 (Canada)*	339	82	22	MAAS (.88) d	GPS (.87)	-.345
Tarman and Sari, 2023 (Turkey)	242	76	22	MAAS (.84)	GPS (.87)	-.240
Tran et al., 2024 (Vietnam)	430	67	20	FFMQ-S (.70)	IPS (.70)	-.099
Wang et al., 2024 (China)	1258	54	16	CAMM (.85)	API (.84)	-.490
Zhong, 2021 (United Staes)	119	47	21	MAAS (.85)	MAEPS (.95)	-.200
Zhong, 2021 (United Staes)	201	52	29	MAAS (.85)	MAEPS (.95)	-.350
Zhong, 2021 (China)	143	48	31	MAAS (.85)	MAEPS (.95)	-.380

 

Note. α = Cronbach’s alpha reported in the study; NR = not reported; API = Aitken’s Procrastination Inventory, CAMM = Child Adolescent Mindfulness Measure, FFMQ = Five Facet Mindfulness Questionnaire, FFMQ-S = Five Facet Mindfulness Questionnaire-Short Form, FMI = Freiburg Mindfulness Inventory, FMI-S = Freiburg Mindfulness Inventory-Short Form, GPS = General Procrastination Scale, IPS = Irrational Procrastination Scale, KIMS = Kentucky Inventory of Mindfulness Skills, MAAS = Mindful Attention Awareness Scale, MAEPS = McGregor and Elliot’s Procrastination Scale, MDQ-P = Melbourne Decision Making Questionnaire-Procrastination Subscale, MS = Mindfulness Scale, MSMQ = Multidimensional State Mindfulness Questionnaire, MMAP = Multifaceted Measure of Academic Procrastination, PASS = Procrastination Academic Scale-Students, PCI = Procrastination Cognitions Inventory, PPS = Pure Procrastination Scale, PS = Procrastination Scale, TPS = Tuckman’s Procrastination Scale. 

a Baseline correlation coefficient value used as the effect size. 

b Also measured procrastination in sample using the Procrastination Cognitions Inventory. 

c Post-test between-person correlation coefficient value used as the effect size. 

d Also measured mindfulness in sample using two subscales from the Kentucky Inventory of Mindfulness Skills.  

* Multiple outcome measures were averaged to provide an overall correlation coefficient value for each sample. 

Quality Assessment 

I used a four-point quality assessment framework to evaluate the quality of each study included in the meta-analysis, awarding one point for adequate reliability and one point for evidence of validity to each of the scales used to measure mindfulness and procrastination, as reported in the study or elsewhere in the research (see Appendix B). Reliability refers to the level of consistency a measure demonstrates when repeated under similar conditions (Boateng et al., 2018). As a convention, a Cronbach’s alpha value of 0.70 or greater indicates a scale has an acceptable level of internal consistency, and this was the benchmark I used to assess whether a scale demonstrated evidence of reliability (Boateng et al., 2018). For a scale to be considered valid, it must accurately measure the underlying construct it is designed to measure (Boateng et al., 2018). A scale’s validity can be demonstrated in numerous ways, including through tests for criterion validity, content validity and construct validity (Boateng et al., 2018; Sullivan, 2011).  

Scales Used to Measure Mindfulness  

Sixteen studies used the Mindful Attention Awareness Scale to measure mindfulness, for which evidence of reliability and validity have been reported (Brown & Ryan, 2003). Nine studies used the Five Facet Mindfulness Questionnaire or its shorter version, for which evidence of reliability and validity have also been reported (Baer et al., 2006, 2012; Bohlmeijer et al., 2011; Christopher et al., 2012). The Freiburg Mindfulness Inventory or its shorter version was used in three studies, and evidence of reliability and validity have been reported for both versions of this scale (Walach et al., 2006). The Kentucky Inventory of Mindfulness Skills or its subscales were used in three studies, for which evidence of reliability and validity have been reported (Baer et al., 2004). The Child Adolescent Mindfulness Measure and the Multidimensional State Mindfulness Questionnaire were each used in one study, and evidence of reliability and validity have been reported for each scale (Blanke & Brose, 2017, 2022; Greco et al., 2011). Additionally, one study used the Mindfulness Scale (Eltayeb, 2021), and while evidence of the scale’s reliability was reported in the study, no evidence of validity could be located. One study measured mindfulness using two different scales (Sirois & Tosti, 2012). 

Scales Used to Measure Procrastination 

Eight studies used the General Procrastination Scale to measure procrastination, for which evidence of reliability and validity have been reported (Diaz-Morales et al., 2006; Lay, 1986). Four studies each used the Tuckman’s Procrastination Scale, the Procrastination Academic Scale-Students and the Academic Procrastination Scale or its shorter version; evidence of reliability and validity have been reported for each of these scales (Alexander & Onwuegbuzie, 2007; McCloskey, 2011; Ozer et al., 2013; Solomon & Rothblum, 1984; Tuckman, 1991; Yockey, 2016). Aitken’s Procrastination Inventory and McGregor and Elliot’s Procrastination Scale were each used to measure procrastination in three studies. While evidence of reliability and validity have been reported for Aitken’s Procrastination Inventory, no evidence of reliability or validity could be located for McGregor and Elliot’s Procrastination Scale (Aitken, 1982; McCown et al., 1987; McGregor & Elliot, 2002). Evidence of reliability and validity have been reported for the Irrational Procrastination Scale and the Pure Procrastination Scale, which were each used in two studies (Steel 2002, 2010). The Multifaceted Measure of Academic Procrastination and the Procrastination Cognitions Inventory were each used in one study, and evidence of reliability and validity have been reported for each scale (Haghbin, 2015; Stainton et al., 2000). Additionally, one study (Eltayeb, 2021) used the Procrastination Scale and one study (Drozd et al., 2013) used the procrastination subscale from the Melbourne Decision Making Questionnaire (Mann et al., 1997). While evidence of each scale’s reliability was reported, no evidence of validity could be located for either scale. One study measured procrastination using two different scales (Flett et al., 2016). 

Meta-Analysis Results 

The random-effects model used to perform the meta-analysis found a significant negative association between mindfulness and procrastination (r = -.38, p < .001, 95% CI [-.44, -.32], k = 33). The forest plot of correlation coefficient values between mindfulness and procrastination for each of the studies included in the meta-analysis is presented in Figure 2. The Q test was also statistically significant, suggesting that there was heterogeneity in the effect size across studies, Q(32) = 466.30, p < .001. The I2 statistic was 0.93, suggesting that 93 per cent of the variance in the effect size across studies could be attributed to true heterogeneity rather than to sampling error (Borenstein, 2022).  

[Contact John Malouff at jmalouff@une.edu.au for for Figure 2]

Sensitivity Analyses 

The one-study removed method was used to examine the sensitivity and robustness of the meta-analytic results. The sensitivity analyses revealed that no individual study had a substantive impact on the overall effect size, since when any study was removed from the analysis, the meta-analytic effect size remained significant (p < .001) and within the 95% confidence interval of the meta-analytic effect size calculated when including all of the studies. Two studies reported particularly high negative correlation coefficient values for the association between mindfulness and procrastination. Luo et al. (2023) was the only study that measured state rather than trait mindfulness and reported a Pearson’s r value of -.83. Removing this study from the meta-analysis did not substantively influence the overall effect size, r = -.36, p < .001. Similarly, removing Serrano et al. (2022) from the meta-analysis, which reported a Pearson’s r value of -.74, did not have a substantive influence on the overall effect size, r = -.37, p < .001. 

Moderator Analyses 

Results from the meta-regression indicated that study quality, as measured against a four-point quality assessment framework, was not a significant moderator of the overall effect size (coefficient = -.003, p = .97). One study was excluded from the meta-regression analysing the moderating effects of the percentage of female participants as this study did not report this information. Percentage of females was not found to be a significant moderator of the overall effect size (coefficient = -.004, p = .20). Seven studies were excluded from the meta-regression analysing the moderating effects of the mean age of study participants as these studies did not report this information. Mean age was also not found to be a significant moderator of the overall effect size (coefficient = -.009, p = .42). Additionally, a subgroup analysis indicated that the overall effect size was not significantly moderated by whether English was the main language for the country in which the study was conducted, Q(1) = 0.04, p = .85. 

Publication Bias 

Visual inspection of the funnel plot indicated that there was no evidence of publication bias. Additionally, Duval and Tweedie’s (2000) trim and fill method did not recommend imputing any studies on the right side of the mean, indicating that it was unlikely the overall effect size was influenced by publication bias. Egger’s test was not significant, p = .75, further suggesting that it was unlikely that publication bias impacted the overall effect size. Figure 3 presents the funnel plot of the standard error of the effect size for the 33 studies included in the meta-analysis. 

Figure 3 

Funnel Plot of the Standard Error of Effect Size for Each Study in the Meta-Analysis 

[Contact John Malouff at jmalouff@une.edu.au for Figure 3}

 

Discussion 

To my knowledge, this is the first meta-analysis to examine the association between mindfulness and procrastination. The meta-analysis synthesised the results from 33 studies and a total 11,817 participants, finding that lower mindfulness was significantly associated with more procrastination, r = -.38, p < .001. According to the guidelines proposed by Cohen (1992), this is a medium effect size. The results from the meta-analysis supported my research hypothesis that lower mindfulness would be associated with more procrastination. While Cochran’s Q test indicated that there was statistically significant heterogeneity in the effect size across studies, neither study quality nor the mean age or percentage of female study participants were found to be significant moderators of the meta-analytic effect size. Additionally, whether or not English was the main language of the country in which a study was conducted did not significantly moderate the overall effect size.  

The robustness of the estimated meta-analytic effect size for the association between mindfulness and procrastination was supported by the generally high quality of studies, the absence of any indication of publication bias, and sensitivity analyses which revealed that no single study had a substantive influence on the meta-analytic effect size. The association held across nations, groups of researchers, and types of measures. For example, negative associations were found between mindfulness and procrastination across all studies included in the meta-analysis, with Pearson’s r correlation coefficient values ranging between r = -.04 to r = -.83. This is notable, as previous research has suggested that the underlying aspects of mindfulness and procrastination may vary across cultures (Christopher et al., 2009; Mann, 2016). Additionally, previous research has suggested that different scales may measure different aspects of mindfulness and procrastination, leading to inconsistencies in the constructs being measured across studies (Grossman, 2019; Svartdal et al., 2016). In contrast, the findings from this meta-analysis suggest that the association between mindfulness and procrastination is relatively consistent across geographic boundaries and measures, with the meta-analysis including the results from research conducted across 13 different countries and multiple measures. The findings from this meta-analysis are also consistent with explanations regarding the potential causes of procrastination. For example, research has found that higher mindfulness is associated with greater attentional control and emotional regulation (Sirois & Pychyl, Tang, 2015). Research has also found that lower attentional and emotional control are associated with procrastination, and therefore individuals lower in mindfulness could be expected to procrastinate more (Steel, 2007). 

Limitations 

There are some limitations to the findings from this meta-analysis. Firstly, 28 of the 33 studies included in the meta-analysis were cross-sectional studies. Of the other five studies, three were experimental, and two were longitudinal. Baseline correlation coefficients were used in the meta-analysis for all but one study (Luo et al., 2023). As such, this meta-analysis is unable to establish any causality for the association between mindfulness and procrastination, as correlation does not imply causation. Secondly, the unrepresentative nature of the population sampled across studies may limit the generalisability of these findings. For example, 30 of the 33 studies sampled student populations, and the weighted mean age across all samples included in the meta-analysis was 20. This is relevant as research suggests that procrastination may decrease with age (Beutel et al., 2016). However, negative associations were still reported in each of the three studies that did not sample student populations, with Pearson’s r values ranging from r = -.26 to r = -.56 (Ahmad, 2019; Drozd et al., 2013; Zhong, 2021). Finally, all of the studies used self-report scales to measure the association between mindfulness and procrastination. While 28 of the 33 studies measured these constructs using scales with evidence of reliability and validity, a degree of caution should be applied when interpreting the results from this meta-analysis due to the limitations associated with using self-report scales, including what Podsakoff et al. (2003) referred to as common method bias. This bias can occur when researchers use the same method to measure an association between two or more variables. Common method bias can lead to a meta-analysis reporting an inflated overall effect size estimate due to the potential of systematic measurement error not being controlled for (Podsakoff et al., 2012). 

 

Directions for Future Research 

To increase the generalisability of these findings, future research could test the association between mindfulness and procrastination in samples that are more representative of the general population, including across different age groups, among workplaces and in other diverse community settings. Given the limitations of self-report scales, future research could also use behavioural and qualitative methods to measure the association between mindfulness and procrastination, as previous research has found inconsistencies between behavioural and self-reported measures of procrastination (Krause & Fruend, 2014). To date, a small number of RCTs have found that mindfulness-based interventions can be effective in treating procrastination (Rad et al., 2023; Schutte & de Bolger, 2020). These preliminary findings suggest sufficient foundation has been laid to warrant further experimental research investigating whether mindfulness-based interventions are effective in reducing procrastination. Longitudinal studies could then examine whether the effects of mindfulness-based interventions remain stable over time. Finally, future research should further explore which aspects of mindfulness are most effective in reducing procrastination. For example, previous research found that the “acting with awareness” and “observing” aspects of mindfulness uniquely predicted procrastination, whereas other aspects of mindfulness such as “non-reactivity” and “describing” did not (Gautam et al., 2019). Understanding which aspects of mindfulness are most effective in reducing procrastination could inform the development of more targeted mindfulness-based interventions to assist in the treatment of procrastination. 

Conclusions 

In summary, this meta-analysis provided a robust estimation of the association between mindfulness and procrastination across all known studies, finding that lower mindfulness was significantly associated with more procrastination. The findings suggest that mindfulness-based interventions could be helpful in reducing procrastination. 

References 

References marked with an asterisk were included in the meta-analysis. 

Abbasi, I. S., & Alghamdi, R. G. (2015). The prevalence, predictors, causes, treatment, and implications of procrastination behaviours in general, academic, and work settings. International Journal of Psychological Studies, 7, 59–66. http://dx.doi.org/10.5539/ijps.v7n1p59 

*Ahmad, Z. (2019). Relationship between procrastination, job performance and mindfulness in male and female employees: A mediating model. European Online Journal of Natural and Social Sciences, 8(3), 535–543. https://european-science.com/eojnss/article/view/5746/pdf 

Ahmad, Z., Hussain, M. M., & Azeem, M. (2022). Nuclear and joint family system as moderator among mindfulness, procrastination and job performance of employees working in organisations. Pakistan Journal of Social Sciences, 42(1), 151–159. https://pjss.bzu.edu.pk/index.php/pjss/article/view/1060 

Aitken, M. E. (1982). A personality profile of the college student procrastinator (Publication No. 8218139) [Doctoral dissertation, University of Pittsburgh]. ProQuest One Academic. https://www.proquest.com/dissertations-theses/personality-profile-college-student/docview/303242158/se-2 

Alexander, E. S., & Onwuegbuzie, A. J. (2007). Academic procrastination and the role of hope as a coping strategy. Personality and Individual Differences, 42(7), 1301–1310. https://doi.org/10.1016/j.paid.2006.10.008   

Baer, R. A., Smith, G. T., & Allen, K. B. (2004). Assessment of mindfulness by self-report: The Kentucky Inventory of Mindfulness Skills. Assessment, 11(3), 191–206. https://doi.org/10.1177/1073191104268029 

Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment, 13(1), 27–45. https://doi.org/10.1177/1073191105283504 

Baer, R. A., Carmody, J., & Hunsinger, M. (2012). Weekly change in mindfulness and perceived stress in a mindfulness-based stress reduction program. Journal of Clinical Psychology, 68(7), 755–765. https://doi.org/10.1002/jclp.21865 

Balkis, M., Duru, E., & Bulus, M. (2013). Analysis of the relation between academic procrastination, academic rational/irrational beliefs, time preferences to study for exams, and academic achievement: A structural model. European Journal of Psychology of Education, 28(3), 825–839. https://doi.org/10.1007/s10212-012-0142-5 

*Bedel, E. F. (2017). The role of mindfulness and metacognitive awareness in predicting academic procrastination in pre-service early childhood teachers. Yuksekogretim ve Bilim Dergisi, 7(3), 504–514. https://doi.org/10.5961/jhes.2017.227 

Beutel, M. E., Klein, E. M., Aufenanger, S., Brahler, E., Dreier, M., Muller, K. W., Quiring, O., Reinecke, L., Schmutzer, G., Stark, B., & Wolfling, K. (2016). Procrastination, distress and life satisfaction across the age range: A German representative community study. PloS One, 11(2), 1–12. https://doi.org/10.1371/journal.pone.0148054 

Blanke, E. S., & Brose, A. (2017). Mindfulness in daily life: A multidimensional approach. Mindfulness, 8(3), 737–750. https://doi.org/10.1007/s12671-016-0651-4 

Blanke, E.S., Brose, A. (2022). Multidimensional State Mindfulness Questionnaire (MSMQ). In O.N. Medvedev, C.U. Krageloh, R.J. Siegert, & N.N. Singh, (Eds.), Handbook of assessment in mindfulness research (pp. 1–13). Springer. https://doi.org/10.1007/978-3-030-77644-2_24-1 

Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quinonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioural research: A primer. Frontiers in Public Health, 6, 1–18. https://doi.org/10.3389/fpubh.2018.00149 

Bohlmeijer, E., Klooster, P. M., Fledderus, M., Veehof, M., & Baer, R. (2011). Psychometric properties of the Five Facet Mindfulness Questionnaire in depressed adults and development of a short form. Assessment, 18(3), 308–320. https://doi.org/10.1177/1073191111408231 

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2010). A basic introduction to fixed-effect and random-effects models for meta-analysis. Research Synthesis Methods, 1(2), 97–111. https://doi.org/10.1002/jrsm.12 

Borenstein, M. (2020). Research note: In a meta-analysis, the I2 index does not tell us how much the effect size varies across studies. Journal of Physiotherapy, 66(2), 135–139. https://doi.org/10.1016/j.jphys.2020.02.011 

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2021). Introduction to Meta-Analysis (Second ed.). Wiley. 

Borenstein, M., Hedges, L. E., Higgins, J. P. T., & Rothstein, H. R. (2022). Comprehensive Meta-Analysis Version 4. In Biostat, Inc. www.Meta-Analysis.com 

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), 822–848. https://doi.org/10.1037/0022-3514.84.4.822 

Brown, K. W., Ryan, R. M., & Creswell, J. D. (2007). Addressing fundamental questions about mindfulness. Psychological Inquiry, 18(4), 272–281. https://doi.org/10.1080/10478400701703344 

*Bu, X., Wu, L., & Wang, H. (2021). Impact of college students’ academic procrastination on subjective well-being. Social Behaviour and Personality, 49(7), 1–13. https://doi.org/10.2224/sbp.9858 

Cavicchioli, M., Movalli, M., & Maffei, C. (2018). The clinical efficacy of mindfulness-based treatments for alcohol and drug use disorders: A meta-analytic review of randomized and nonrandomized controlled trials. European Addiction Research, 24(3), 137–162. https://doi.org/10.1159/000490762 

*Cheung, R. Y. M., & Ng, M. C. Y. (2019). Being in the moment later? Testing the inverse relation between mindfulness and procrastination. Personality and Individual Differences, 141, 123–126. https://doi.org/10.1016/j.paid.2018.12.015 

Christopher, M. S., Charoensuk, S., Gilbert, B. D., Neary, T. J., & Pearce, K. L. (2009). Mindfulness in Thailand and the United States: A case of apples versus oranges? Journal of Clinical Psychology, 65(6), 590–612. https://doi.org/10.1002/jclp.20580 

Christopher, M. S., Neuser, N. J., Michael, P. G., & Baitmangalkar, A. (2012). Exploring the psychometric properties of the Five Facet Mindfulness Questionnaire. Mindfulness, 3(2), 124–131. https://doi.org/10.1007/s12671-011-0086-x 

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155 

Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. www.covidence.org. 

Creswell, J. D., & Lindsay, E. K. (2014). How does mindfulness training affect health? A mindfulness stress buffering account. Current Directions in Psychological Science: A Journal of the American Psychological Society, 23(6), 401–407. https://doi.org/10.1177/0963721414547415 

Creswell J. D. (2017). Mindfulness interventions. Annual Review of Psychology, 68, 491–516. https://doi.org/10.1146/annurev-psych-042716-051139 

Diaz-Morales, J. F., Ferrari, J. R., Díaz, K., & Argumedo, D. (2006). Factorial structure of three procrastination scales with a Spanish adult population. European Journal of Psychological Assessment, 22(2), 132–137. https://doi.org/10.1027/1015-5759.22.2.132 

*Drozd, F., Raeder, S., Kraft, P., & Bjørkli, C. A. (2013). Multilevel growth curve analyses of treatment effects of a web-based intervention for stress reduction: Randomised controlled trial. Journal of Medical Internet Research, 15(4), 1–23. https://doi.org/10.2196/jmir.2570 

Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel‐plot–based method of testing and adjusting for publication bias in meta‐analysis. Biometrics, 56(2), 455–463. https://doi.org/10.1111/j.0006-341x.2000.00455.x 

*Egan, H., O’Hara, M., Cook, A., & Mantzios, M. (2022). Mindfulness, self-compassion, resiliency and wellbeing in higher education: A recipe to increase academic performance. Journal of Further and Higher Education, 46(3), 301–311. https://doi.org/10.1080/0309877X.2021.1912306 

Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629 

*Einabad, Z. S., Roshan, F. J., Roshan, R., & Ghasemzadeh, M. (2019). The relationship among mindfulness, acceptance, and academic procrastination in students. Zahedan Journal of Research in Medical Sciences, 21(4), 1–5. https://doi.org/10.5812/zjrms.68450 

*Eltayeb, F. (2021). Mindfulness and its relation to academic procrastination among university students. Universal Journal of Educational Research, 9(5), 917-927. https://doi.org/10.13189/ujer.2021.090504 

*Ergin, A., Coskun, Y.D. & Mutlu, E. (2019). Are academic procrastination behaviours of engineering students related to their mindfulness levels? International Journal of Educational Researchers, 10(4), 1-19. 

*Fan, Q., Li, Y., Hu, W., Zhang, H., Zhao, F., & Henderson, S. L. (2024). Does mindfulness benefit adolescents’ academic adaptation? The mediating roles of autonomous and controlled motivation. Current Psychology, 43(29), 1-13. https://doi.org/10.1007/s12144-024-06082-6 

Fjorback, L. O., Arendt, M., Ornbol, E., Fink, P., & Walach, H. (2011). Mindfulness-based stress reduction and mindfulness-based cognitive therapy: A systematic review of randomised controlled trials. Acta Psychiatrica Scandinavica, 124(2), 102–119. https://doi.org/10.1111/j.1600-0447.2011.01704.x 

*Flett, A. L., Haghbin, M., & Pychyl, T. A. (2016). Procrastination and depression from a cognitive perspective: An exploration of the associations among procrastinatory automatic thoughts, rumination, and mindfulness. Journal of Rational-Emotive and Cognitive-Behaviour Therapy, 34(3), 169–186. https://doi.org/10.1007/s10942-016-0235-1 

Gautam, A. (2017). Examination of the associations among anxiety, procrastination, and mindfulness (Order No. 10282194). Available from ProQuest One Academic. (1934372569). https://www.proquest.com/dissertations-theses/examination-associations-among-anxiety/docview/1934372569/se-2 

*Gautam, A., Polizzi, C. P., & Mattson, R. E. (2019). Mindfulness, procrastination, and anxiety: Assessing their interrelationships. Psychology of Consciousness, 10(4), 441–453. https://doi.org/10.1037/cns0000209 

Glick, D. M., & Orsillo, S. M. (2015). An investigation of the efficacy of acceptance-based behavioural therapy for academic procrastination. Journal of Experimental Psychology, 144(2), 400–409. https://doi.org/10.1037/xge0000050 

Greco, L. A., Baer, R. A., & Smith, G. T. (2011). Assessing mindfulness in children and adolescents: Development and validation of the Child and Adolescent Mindfulness Measure (CAMM). Psychological Assessment, 23(3), 606–614. https://doi.org/10.1037/a0022819 

Grossman P. (2019). On the porosity of subject and object in ‘mindfulness’ scientific study: Challenges to ‘scientific’ construction, operationalization and measurement of mindfulness. Current Opinion in Psychology, 28, 102–107. https://doi.org/10.1016/j.copsyc.2018.11.008 

Gurevitch, J., Koricheva, J., Nakagawa, S., & Stewart, G. (2018). Meta-analysis and the science of research synthesis. Nature, 555(7695), 175–182. https://doi.org/10.1038/nature25753 

Haghbin, M. (2015). Conceptualization and operationalization of delay: Development and validation of the Multifaceted Measure of Academic Procrastination and the Delay Questionnaire (Doctoral dissertation, Carleton University). https://doi.org/10.22215/etd/2015-11051 

Hopwood, T. L., & Schutte, N. S. (2017). A meta-analytic investigation of the impact of mindfulness-based interventions on post-traumatic stress. Clinical Psychology Review, 57, 12–20. https://doi.org/10.1016/j.cpr.2017.08.002 

Hussain, M. M., & Ahmad, Z. (2021). Moderating effect of marital status among mindfulness, procrastination and job performance of employees. Review of Education, Administration & Law, 4(1), 133–143. https://doi.org/10.47067/real.v4i1.118 

*Jayaraja, A. R., Tan, S. A., & Ramasamy, P. N. (2017). Predicting role of mindfulness and procrastination on psychological well-being among university students in Malaysia. Journal of Psychology Malaysia, 31(2), 29–36.  

*Jobaneh, R. G., Mousavi, S. V., Zanipoor, A., Seddigh, H., & Alsadat, M. (2016). The relationship between mindfulness and emotion regulation with academic procrastination of students. Education Strategies in Medical Sciences, 9, 134–141. 

Klingsieck, K.B. (2013). Procrastination: When good things don’t come to those who wait. European Psychologist, 18(1), 24–34. https://doi.org/10.1027/1016-9040/a000138 

Koenig, H. G. (2023). Person-centred mindfulness: A culturally and spiritually sensitive approach to clinical practice. Journal of Religion and Health, 62(3), 1884–1896. https://doi.org/10.1007/s10943-023-01768-w 

Lay, C. H. (1986). At last, my research article on procrastination. Journal of Research in Personality, 20(4), 474–495. https://doi.org/10.1016/0092-6566(86)90127-3 

*Lee, S. (2019). Influences of mindfulness on career exploration behaviours: Exploration of mediating role of career worry and procrastination. Medico-Legal Update, 19(1), 317–322. https://doi.org/10.5958/0974-1283.2019.00063.X    

*Li, S., Su, J., Zhao, D., Wang, J., & Wang, G. (2023). Future time perspective and academic procrastination among nursing students: The mediating role of mindfulness. Nursing Open, 10(6), 3737–3743. https://doi.org/10.1002/nop2.1630 

*Lina, M., Yang, L., & Qing, G. (2023). The mediating effect of achievement motivation on mindfulness and procrastination behaviour of nursing students: A correlational study. Medicine, 102(12), 1–6. https://doi.org/10.1097/MD.0000000000033327 

*Luo, X., Ma, J., & Hu, Y. (2023). Dynamic and bidirectional relation between mindfulness and procrastination among female college students. Mindfulness, 14(9), 2265–2275. https://doi.org/10.1007/s12671-023-02216-2 

*Maga, J. (2023). Exploring relationships of mindfulness and motivation with academic-related beliefs, behaviours, and outcomes (Publication No. 30531000) [Doctoral dissertation, Indiana University of Pennsylvania]. ProQuest One Academic. https://www.proquest.com/dissertations-theses/exploring-relationships-mindfulness-motivation/docview/2838120266/se-2 

Mann, L., Burnett, P., Radford, M., & Ford, S. (1997). The Melbourne Decision Making Questionnaire: An instrument for measuring patterns for coping with decisional conflict. Journal of Behavioural Decision Making, 10(1), 1–19. https://doi.org/10.1002/(SICI)1099-0771(199703)10:1<1::AID-BDM242>3.0.CO;2-X 

Mann, L. (2016). Procrastination revisited: A commentary. Australian Psychologist, 51(1), 47–51. https://doi.org/10.1111/ap.12208 

McCloskey, J. D. (2011). Finally, my thesis on academic procrastination (Order No. 1506326). Available from ProQuest One Academic. (923044391). https://www.proquest.com/dissertations-theses/finally-my-thesis-on-academic-procrastination/docview/923044391/se-2 

McCown, W., Petzel, T., & Rupert, P. (1987). An experimental study of some hypothesized behaviours and personality variables of college student procrastinators. Personality and Individual Differences, 8(6), 781–786. https://doi.org/10.1016/0191-8869(87)90130-9 

McGregor, H. A., & Elliot, A. J. (2002). Achievement goals as predictors of achievement-relevant processes prior to task engagement. Journal of Educational Psychology, 94(2), 381–395. https://doi.org/10.1037/0022-0663.94.2.381 

Nguyen, B., Steel, P., & Ferrari, J. R. (2013). Procrastination’s impact in the workplace and the workplace’s impact on procrastination. International Journal of Selection and Assessment, 21(4), 388–399. https://doi.org/10.1111/ijsa.12048 

Ozer, B. U., Saçkes, M., & Tuckman, B. W. (2013). Psychometric properties of the Tuckman Procrastination Scale in a Turkish sample. Psychological Reports, 113(3), 874–884. https://doi.org/10.2466/03.20.PR0.113x28z7 

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 74(9), 790–799. https://doi.org/10.1136/bmj.n71 

*Parlade, J. M. (2022). Fear of failure, mindfulness, and procrastination (Master’s thesis, Pittsburgh State University). Electronic Theses & Dissertations. https://digitalcommons.pittstate.edu/etd/454 

*Peng, C., Peng J., Lyu, Z., Dai, L., Wang J., Zhang, J., Liu, Y., & Fan, X. (2024). Relationship between insecure attachment and procrastination in college students: Path analysis of mindfulness and self-control. Sichuan Jingshen Weisheng, 37(2), 150–155. https://doi.org/10.11886/scjsws20230626001 

 

 

Podsakoff, P. M., MacKenzie, S. B., Lee, J.Y., & Podsakoff, N. P. (2003). Common method biases in behavioural research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879 

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452 

Polizzi, C., Gautam, A., & Lynn, S. J. (2018). Trait mindfulness: A multifaceted evaluation. Imagination, Cognition and Personality, 38(2), 106–138. https://doi.org/10.1177/0276236618774321 

Pychyl, T. A., & Flett, G. L. (2012). Procrastination and self-regulatory failure: An introduction to the special issue. Journal of Rational-Emotive and Cognitive-Behaviour Therapy, 30(4), 203–212. https://doi.org/10.1007/s10942-012-0149-5 

*Rad, H. S., Samadi, S., Sirois, F. M., & Goodarzi, H. (2023). Mindfulness intervention for academic procrastination: A randomised control trial. Learning and Individual Differences, 101(102244), 1–7. https://doi.org/10.1016/j.lindif.2022.102244 

Rahimi, S., & Hall, N. C. (2021). Why are you waiting? Procrastination on academic tasks among undergraduate and graduate students. Innovative Higher Education, 46(6), 759–776. https://doi.org/10.1007/s10755-021-09563-9 

*Rezaei, S., & Zebardast, A. (2021). The mediating role of cognitive emotion regulation strategies on mindfulness, anxiety, and academic procrastination in high schoolers. Practice in Clinical Psychology, 9(2), 133–142. https://doi.org/10.32598/jpcp.9.2.731.1 

*Riaz, S., & Saif, A. (2017). Relationship between academic procrastination and stress: Mediating role of mindfulness among university students. Pakistan Journal of Languages and Translation Studies, 2017, 74–86. 

Rist, F., Engberding, M., Hoecker, A., Wolf-Lettmann, J., & Fischbach, E. M. (2023). Diagnostic criteria to differentiate pathological procrastinators from common delayers: A re-analysis. Frontiers in Psychology, 14, 1–23. https://doi.org/10.3389/fpsyg.2023.1147401 

Rozental, A., & Carlbring, P. (2014). Understanding and treating procrastination: A review of a common self-regulatory failure. Psychology, 5(13), 1488–1502 https://doi.org/10.4236/psych.2014. 513160 

Rozental, A., Bennett, S., Forsstrom, D., Ebert, D. D., Shafran, R., Andersson, G., & Carlbring, P. (2018). Targeting procrastination using psychological treatments: A systematic review and meta-analysis. Frontiers in Psychology, 9, 1–15. https://doi.org/10.3389/fpsyg.2018.01588 

Sala, M., Rochefort, C., Lui, P. P., & Baldwin, A. S. (2020). Trait mindfulness and health behaviours: A meta-analysis. Health Psychology Review, 14(3), 345–393. https://doi.org/10.1080/17437199.2019.1650290 

*Schutte, N. S., & del Pozo de Bolger, A. (2020). Greater mindfulness is linked to less procrastination. International Journal of Applied Positive Psychology, 5(1), 1–12. https://doi.org/10.1007/s41042-019-00025-4 

*Serrano, D. M., Williams, P. S., Ezzeddine, L., & Sapon, B. (2022). Association between problematic social media use and academic procrastination: The mediating role of mindfulness. Learning, 8(2), 84–95. https://doi.org/10.1080/23735082.2022.2100920 

Shapiro, S. L., Carlson, L. E., Astin, J. A., & Freedman, B. (2006). Mechanisms of mindfulness. Journal of Clinical Psychology, 62(3), 373–386. https://doi.org/10.1002/jclp.20237 

*Sirois, F. M., & Tosti, N. (2012). Lost in the moment? An investigation of procrastination, mindfulness, and well-being. Journal of Rational-Emotive and Cognitive-Behaviour Therapy, 30(4), 237–248. https://doi.org/10.1007/s10942-012-0151-y 

Sirois, F., & Pychyl, T. (2013). Procrastination and the priority of short-term mood regulation: Consequences for future self. Social and Personality Psychology Compass, 7(2), 115–127. https://doi.org/10.1111/spc3.12011 

Solomon, L. J., & Rothblum, E. D. (1984). Academic procrastination: Frequency and cognitive-behavioural correlates. Journal of Counselling Psychology, 31(4), 503–509. https://doi.org/10.1037/0022-0167.31.4.503 

Stainton, M., Lay, C. H., & Flett, G. L. (2000). Trait procrastinators and behaviour/trait-specific cognitions. Journal of Social Behaviour and Personality, 15(5), 297–312. 

Steel, P. D. G. (2002). The measurement and nature of procrastination (Publication No. 3047664) [Doctoral dissertation, University of Minnesota]. ProQuest One Academic. https://www.proquest.com/dissertations-theses/measurement-nature-procrastination/docview/276586835/se-2 

Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94. https://doi.org/10.1037/0033-2909.133.1.65 

Steel, P. (2010). Arousal, avoidant and decisional procrastinators: Do they exist? Personality and Individual Differences, 48(8), 926–934. https://doi.org/10.1016/j.paid.2010.02.025 

Svartdal, F., Pfuhl, G., Nordby, K., Foschi, G., Klingsieck, K. B., Rozental, A., Carlbring, P., Lindblom-Ylanne, S., & Rębkowska, K. (2016). On the measurement of procrastination: Comparing two scales in six European countries. Frontiers in Psychology, 7(1307), 1–11. https://doi.org/10.3389/fpsyg.2016.01307 

Tang, Y.Y., Holzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16(4), 213–225. https://doi.org/10.1038/nrn3916 

*Tarman, G. Z., & Sari, B. A. (2023). The mediating role of mindfulness on social anxiety and procrastination. International Journal of Mental Health and Addiction, 21(2), 1013–1024. https://doi.org/10.1007/s11469-021-00637-5 

Tice, D. M., & Bratslavsky, E. (2000). Giving in to feel good: The place of emotion regulation in the context of general self-control. Psychological Inquiry, 11(3), 149–159. https://doi.org/10.1207/S15327965PLI1103_03 

Tice, D. M., Bratslavsky, E., & Baumeister, R. F. (2001). Emotional distress regulation takes precedence over impulse control: If you feel bad, do it! Journal of Personality and Social Psychology, 80(1), 53–67. https://doi.org/10.1037/0022-3514.80.1.53 

*Tran, M., Chau, N., Kukreti, S., & Ngo-Hoang, D.L. (2024). A study on the determinants of undergraduates’ procrastination: Social addiction, negative emotion as mediators and mindfulness as moderator. Journal of Rational-Emotive and Cognitive-Behaviour Therapy, 1–21. https://doi.org/10.1007/s10942-024-00554-1 

Tuckman, B. W. (1991). The development and concurrent validity of the Procrastination Scale. Educational and Psychological Measurement, 51(2), 473–480. https://doi.org/10.1177/0013164491512022 

 Vago, D. R., & Silbersweig, D. A. (2012). Self-awareness, self-regulation, and self-transcendence: A framework for understanding the neurobiological mechanisms of mindfulness. Frontiers in Human Neuroscience, 6, 1–30. https://doi.org/10.3389/fnhum.2012.00296 

Walach, H., Buchheld, N., Buttenmuller, V., Kleinknecht, N., & Schmidt, S. (2006). Measuring mindfulness: The Freiburg Mindfulness Inventory. Personality and Individual Differences, 40(8), 1543–1555. https://doi.org/10.1016/j.paid.2005.11.025 

*Wang, S., Shi, J., Sheng, R., Yu, S., & Xu, W. (2022). Hope and academic procrastination in adolescents: A moderated mediation model. The International Journal of Mental Health Promotion, 24(6), 933–944. https://doi.org/10.32604/ijmhp.2022.023083 

Yockey, R. D. (2016). Validation of the short form of the Academic Procrastination Scale. Psychological Reports, 118(1), 171–179. https://doi.org/10.1177/0033294115626825 

Zacks, S., & Hen, M. (2018). Academic interventions for academic procrastination: A review of the literature. Journal of Prevention & Intervention in the Community, 46(2), 117–130. https://doi.org/10.1080/10852352.2016.1198154 

*Zhong, M. (2021). Deep in thought: How do recipients take in negative feedback? (Publication No. 28927089) [Doctoral dissertation, University of Illinois]. ProQuest One Academic. https://www.proquest.com/dissertations-theses/deep-thought-how-do-recipients-take-negative/docview/2610521657/se-2 

 

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