Education
Following the literature review, a total of 37 papers were found that use models with scales. This is the background for proposing the theoretical model: “Procrastination of University Students” (PUS). The PUS model is multidimensional and reflexive, as the latent variable (procrastination construct in university students) causes the observed variables (procrastination dimensions) [ 102 ]. The first proposal of the theoretical model is composed of 6 dimensions linked to procrastination in higher education students; namely: (1) Psychological; (2) Physiological; (3) Socio-demographic; (4) Academic; (5) Cultural; and (6) Environmental. The theoretical model considers the dimensions that are mostly incorporated by the studies in the academic literature, as well as the aspects or elements considered by each study. Table 2 shows detailed information on the dimensions, considered aspects, and authors.
Proposal for a Theoretical Model of Procrastination in University Students.
Dimensions | Considered Aspects | Previous Scales |
---|---|---|
Psychological | Motivation, personality dimensions, dishonest behavior, perfectionism, self-esteem, psychological well-being, emotional intelligence, perfectionist traits, time management, time distribution, mental symptoms, psychological processes, dissatisfaction with performing tasks, self-regulation, expectation to succeed, indecision, avoidance, activation, self-regulation, sources of motivation, behavior, postponement of the task, commitment, attraction to the task, fear of failure, boredom, uncertainty about the task. | [ , , , , , , , , , , , , , , , , , , , , , , ] |
Physiological | Biological variables, anxiety, stress, self-regulation of learning, vigor, absorption, health hazards. | [ , , , , , , , ] |
Socio-demographic | Gender, age, personal variables, socio-demographic profile, socio-economic level, demographic variables. | [ , , , , , , , , , , , ] |
Academic | Dropping out, control variables, distance learning, academic performance, academic year, level of education, academic performance, GPA, study habits, academic satisfaction, study patterns, exam performance, academic delay, academic self-efficacy, teacher model, assessment, academic behavior. | [ , , , , , , , , , , , , , , , , , ] |
Cultural | Personal variables, planning failure. | [ ] |
Environmental | Risk factors, protective factors, difficulty in performing tasks, lack of time, time, dedication, peer influence. | [ , , , , ] |
The six proposed dimensions cover all the relevant aspects reviewed in the literature; therefore, they can be used for content validation. The results show that the “Psychological” dimension includes factors such as motivation, personality dimensions, emotional intelligence, time management, and so on. The “Physiological” dimension is composed of biological variables: anxiety, self-regulation of learning, and vigor, among others. The “Socio-demographic” dimension is made up of aspects, such as gender, age, socio-economic and demographic variables. The “Academic” dimension includes control variables, distance learning, academic performance, level of education, dropping out, academic performance, GPA, study habits, and academic satisfaction, among others. The “Cultural” dimension mainly contains personal individual elements. Lastly, the “Environmental” dimension involves aspects such as risk factors, difficulties in performing tasks, lack of time, levels of dedication, and peer influence.
The literature review yielded six dimensions that theoretically link a number of elements with procrastination in university students. These dimensions were assessed through a semi-structured online questionnaire on a sample of 320 respondents studying in Chilean universities. Respondents were asked to write down the factors or dimensions that best represent procrastination in academic tasks and relate them to a number of items on the topic.
As background information, respondents were asked several questions about how they deal with tasks on a daily basis from the point of view of procrastination. Table 3 shows the results when the respondents were asked to choose an item with which they most identify. From a total of 309 responses, 60.95% of respondents identified most with “I do my tasks in order of priority”; 19.37% with “I do my tasks whenever I have time”; 16.51% with “I do my tasks depending on the backlog”; 1.9% with “I do not do any task”; and 1.27% with “I only do the tasks I manage to get done”.
Respondents’ Results on How they Deal with Tasks.
Items | Responses |
---|---|
I do my tasks in order of priority | 188 |
I do my tasks whenever I have time | 59 |
I do my tasks depending on the backlog | 52 |
I do not do any task | 6 |
I only do the tasks I manage to get done | 4 |
In order to validate the content of the first proposal of the Theoretical Model “Procrastination of University Students”, the following question was asked: “What are the dimensions that best represent procrastination in academic tasks?” A total of 320 responses were collected, covering nine dimensions, from which four are repeated in the literature review and five enhanced their importance thanks to the questionnaire. The dimensions are Psychological, Social, Academic, Physiological, Time Management, Leisure, Resources, Environmental, and Labor. Table 4 shows the importance given by respondents to each dimension and its component elements.
Percentage of importance for each dimension and its associated factors.
Dimension | Preference Percentage | Associated Factors |
---|---|---|
Psychological | 22.91% | Lack of motivation, attitude, insecurity in personal skills, psychological factors, stress, boredom, exciting factors, and addictions |
Social | 19.34% | Family aspects, socialization, socio-cultural level, personal problems, lack of support, home activities, and love relationships |
Academic | 13.15% | Educational model, teacher performance, study habits, administrative-academic management of the university, academic training, interest in the task, academic overload, vocation, and university environment |
Physiological | 12.28% | Physiological needs, physical or mental exhaustion, depression, health status, age, pregnancy, Attention Deficit Disorder (ADD) |
Time Management | 9.58% | Lack of time, definition of priorities, task planning, doing everything at the last minute and task overload |
Leisure | 9.28% | Recreational activities, technological devices, social media, browsing the Internet, and leisure time |
Resources | 5.31% | Transportation, economic resources, academic resources, and technological resources |
Environment | 5.10% | Conflicting environment, accessibility, environmental conditions, inappropriate study space and distracting elements |
Labor | 3.05% | Workload, working and studying at the same time, work problems, and working hours. |
The dimension that best represents procrastination in academic tasks according to the respondents was the Psychological one, with 22.91% of preferences, and the “lack of motivation” factor was the most chosen one (22.24%). This was followed by the Social dimension, with 19.34% of preferences, with the factor “family aspects” as the most relevant with 28.83%. In third place was the Academic dimension with 13.15%, where the “educational model” was the most representative factor with 21.85% of preferences. The Physiological dimension reported 12.28% of preferences, where “physiological needs” was the most relevant factor (26.6%). Time Management ranked fifth among the dimensions, with 9.58%, and “lack of time” as the dominant factor with 40.91%. The Leisure dimension emerged as a new dimension with 9.28% of preferences, with “recreational activities” as the most chosen factor (30.03%). Resources and Environmental dimensions showed similar percentages, with 5.31% and 5.10%, respectively, where “economic resources” dominated the former (84.43%), and “conflictive environment” the latter (41.03%). The Labor dimension least represented procrastination according to the respondents, with “workload” as the dominant factor with 70% of preferences.
Owlia and Aspinwall [ 103 ] established that validity comprises two aspects: quantitative validity and qualitative validity. Qualitative validity identifies the dimensions linked to procrastination in the literature and reviews their validity through a questionnaire. Qualitative validity determines whether the measures capture the key factors of an unobservable construct, which is also in line with content validity. The latter is relevant for full validation and the subsequent scaling of the PUS model. Future research studies are expected to collect information through individual interviews, focus groups, and expert opinions, seeking to achieve category saturation [ 104 ]. The proposal, therefore, is to use qualitative tools as they allow for analyzing phenomena in greater depth than quantitative tools [ 105 ]. The proposal includes the following: fifteen in-depth interviews to be conducted to find out students’ perceptions of the procrastination construct and the dimensions that they consider relevant in evaluation; four focus groups to study and analyze students’ perceptions in interaction; and four experts in university procrastination can also participate, who should be asked to evaluate the proposed scale for procrastination in university students. This information will be used to validate the results obtained from the semi-structured online questionnaires applied to the students.
This research studies the factors that influence procrastination among university students in Latin America on this topic because none of the previous studies have covered the factors affecting this concept. The aim was to collect information in relation to the actions that have an impact on the backlog of academic tasks. After data collection, the dimensions that directly affect the student’s procrastination were considered through a repetitive search, and the content validity was given by the questionnaire. The analysis seems to conclude that the factors that mainly influence university students to postpone the fulfillment of an obligation or the development of action have to do with the psychological, social, and academic dimensions and the factors that integrate them.
These results are in line with other international studies that deem these dimensions relevant. Even so, they also highlight areas such as resources and labor, which for a certain percentage of students are distracting elements that prevent the fulfillment of their academic tasks. This is not a novelty, since due to the configuration of higher education systems in Latin America (and in Chile), many students must work in order to pay for their university studies, making both roles compatible. Academic procrastination is not a subject of the establishment of a repertoire of activities but is rather a self-regulatory model that includes aspects such as autonomous learning goals.
The aim of the research was to propose a theoretical model of procrastination in university students, which was achieved by means of quantitative instruments. However, the model still needs to corroborate its full validation through qualitative methods in order to carry out the corresponding factorial analysis, which will make the model reliable and accurately prove that procrastination in university students is explained by the aforementioned dimensions. This is not a trivial task, as a scale measuring procrastination in university students can finally be developed.
This research received no external funding.
Conceptualization, L.A.-C.; Methodology, M.B.; Validation, V.Y.J.; Formal analysis, N.B.; Investigation, P.G. and Y.R.; Writing—review & editing, F.G.-C. and W.S. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and ethics committee review and approval was waived, as the survey was made available on an online platform for potential respondents to answer voluntarily. The survey was developed following institutional protocols and regulations for this type of research.
Informed consent was obtained from all subjects involved in the study.
The authors declare no conflict of interest.
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Procrastination is consistently viewed as problematic to academic success and students’ general well-being. There are prevailing questions regarding the underlying and maintaining mechanisms of procrastination which are yet to be learnt. The aim of the present study was to combine different ways to explain procrastination and explore how students’ time and effort management skills, psychological flexibility and academic self-efficacy are connected to procrastination as they have been commonly addressed separately in previous studies. The data were collected from 135 students who participated in a voluntary time management and well-being course in autumn 2019. The results showed that students’ ability to organize their time and effort has the strongest association with procrastination out of the variables included in the study. Psychological flexibility also has a strong individual role in explaining procrastination along with time and effort management skills. Surprisingly, academic self-efficacy did not have a direct association with procrastination. Interestingly, our findings further suggest that time and effort management and psychological flexibility are closely related and appear to go hand in hand and, thus, both need to be considered when the aim is to reduce procrastination. The implications of the findings are further discussed.
Why are you waiting procrastination on academic tasks among undergraduate and graduate students, predictors of procrastination in first-year university students: role of achievement goals and learning strategies, explore related subjects.
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Academic procrastination is very common among university students: almost all occasionally procrastinate in one or another domain of their studies, and approximately every second student regularly procrastinates (Rothblum et al., 1986 ; Steel, 2007 ). Considerable attention has been given to procrastination in university setting (Klassen et al., 2008 ). The student population is especially prone to procrastination, with an estimated prevalence of 50–95% (Steel, 2007 ). Procrastination may be defined as ‘the voluntary delay of an intended and necessary and/or [personally] important activity, despite expecting potential negative consequences that outweigh the positive consequences of the delay’ (Klingsieck, 2013 , 26). Typical for procrastination is that it is irrational and not imposed by external matters and it is often accompanied by subjective discomfort and negative consequences (Klingsieck, 2013 ). Procrastination is often associated with several negative factors, such as lower academic performance (Steel et al., 2001 ), increased stress (Sirois et al., 2003 ) and poorer mental health (Stead et al., 2010 ). Therefore, it is necessary to understand the causes and the factors that maintain procrastination in order to be able to reduce it. The challenge is that research in the area of procrastination often lacks a coherent, theoretical explanation of the behaviour (Glick et al., 2014 ) which has made it difficult to understand the phenomenon and to follow the research (e.g., Klingsieck, 2013 ; Schraw et al., 2007 ; Steel, 2007 ). Therefore, there are prevailing questions regarding the underlying and maintaining mechanisms of procrastination which are yet to be learnt (Katz et al., 2014 ; Visser et al., 2018 ).
The core characteristic of procrastination is the intention-action gap suggesting that the procrastinators often have good intentions, but the challenge lies in the implementation of these intentions (Dewitte and Lens, 2000 ). Thus, procrastination has traditionally been understood as a self-regulation or time management problem (Wolters et al., 2017 ). There is a strong body of evidence suggesting that lower levels of self-regulating behaviours are related to higher levels of procrastination, and thus self-regulation is one of the keys to understanding procrastination (Ferrari, 2001 ). However, Visser et al. ( 2018 ) suggest that procrastination is complex behaviour that involves both cognitive and emotional elements as well as evaluations of one’s own competence. Recent research suggests that instead of being purely a self-regulation or time management problem, procrastination is also strongly influenced by psychological factors, such as the low confidence in one’s own abilities to perform (Steel, 2007 ) and inability to cope with negative emotions that arise in challenging situations referring to the centrality of psychological flexibility in understanding procrastination (Dionne, 2016 ; Gagnon et al., 2016 ). In this article, we aim to bring together these central constructs that have usually been addressed separately in previous studies in order to understand the phenomenon of procrastination and its underlying mechanisms better.
There are several theoretical perspectives that have been used when exploring procrastination: the differential psychology perspective; the motivational and volitional psychology perspective; the clinical psychology perspective; and the situational perspective (Klingsieck, 2013 ). In the context of higher education, the motivational-volitional psychology and situational perspectives may be regarded as the most relevant because they provide tangible tools and theories for educational developers to try to influence students’ procrastination tendencies whereas the other perspectives focus more on aspects that are not so easily influenced, such as personality traits, depression or personality disorders. The motivational-volitional perspective is focused on the relationship between different motivational and volitional variables such as motivation, self-regulation, time management and learning strategies which are central in successful studying in higher education (Lindblom-Ylänne et al., 2015 ; Klingsieck, 2013 ). The situational perspective, on the other hand, focuses on procrastination evoked by situational features, such as the perceived difficulty of the task (Klingsieck, 2013 ). This situational perspective can be further extended to include the person’s reactions to the challenges posed by the situation.
From the motivational-volitional perspective, academic procrastination has been found to be related to lower levels of self-regulation and academic self-efficacy and is associated with higher levels of stress and anxiety (e.g., Ferrari et al., 2005 ; Howell et al., 2006 ; Schraw et al., 2007 ; Wolters, 2003 ). Klassen et al. ( 2008 ) state that among all the variables that have been investigated in relation to academic procrastination, self-regulation, self-efficacy, and self-esteem have received the most attention (see e.g., Cassady and Johnson, 2002 ; Chun Chu and Choi, 2005 ; Ferrari, 2001 ; Howell et al., 2006 ; Steel, 2007 ; Wolters, 2003 ). Procrastination has traditionally been considered to be a form of self-regulation failure, as a weakness of will and low ability to organise own studying (e.g., Ferrari, 2001 ; Senecal et al., 1995 ; Steel, 2007 ) and, thus, one common theory is that procrastination results from a person’s inability to manage time (Burka and Yuen, 1982 ; Glick and Orsillo, 2015 ).
Research focusing on exploring university students’ study progress has consistently shown that time and effort management skills are among the most crucial factors (e.g., Ariely and Wertenbroch, 2002 ; Entwistle, 2009 ; Haarala-Muhonen et al., 2011 ; Häfner et al., 2015 ; Pintrich, 2004 ). In the higher education context, time and effort management skills refer to students’ ability to set goals for themselves and to study according to their goals, to manage their time usage and to prioritise the tasks to be conducted (Entwistle et al., 2001 ). It has further been suggested that time and effort management skills provide a foundation for cognitive engagement and student achievement as they refer to how much the students are willing to invest in their learning (Appleton et al., 2008; Fredricks et al., 2004). Previous studies indicate that many higher education students struggle with time and effort management skills (Parpala et al., 2010 ) and that these skills remain constant throughout the studies and are hard to change (Parpala et al., 2017a ). Many students study without study schedules and thus fail to pass the courses because they run out of preparation time, such as for exams (Asikainen et al., 2013 ). Thus, many interventions to reduce procrastination have focused on improving time management skills (e.g., Ariely and Wertenbroch, 2002 ; Häfner et al., 2015 ; Levrini and Prevatt, 2012 ).
There are also critical voices claiming that time and effort management skills, or lack thereof, are not enough to explain the phenomena and that research focusing on the role of time and effort management skills in procrastination does not take the persons’ internal experiences enough into account (Glick and Orsillo, 2015 ). It has been suggested that when exploring factors that maintain and cause procrastination, we have to widen the perspective to include a broader theory of regulation of inner experiences, namely, psychological flexibility (Hayes, 2004 ; Hayes et al., 2012 ). Recent studies concerning procrastination have brought up the importance of psychological flexibility in decreasing procrastination and suggest that procrastination may also result from person’s psychological inflexibility (Eisenbeck et al., 2019 ; Gagnon et al., 2016 ; Glick et al., 2014 ; Scent and Boes, 2014 ).
Psychological flexibility refers to one’s ability to be consciously present, confronting and accepting the negative experiences, emotions and thoughts one might have, and being able to take action about achieving one’s own goals despite unpleasant feelings and thoughts, and further, being able to react to negative feelings and thoughts from a new perspective (Chawla and Ostafin, 2007 ; Hayes et al., 2006 ). Thus, it is a central factor influencing the way students react in a stressful and challenging situation. Procrastinators often fail to regulate their actions in situations that are challenging and involve high levels of stress and cognitive workload and avoiding the unpleasant feelings generated by the situation (Ferrari, 2001 ). This experiential avoidance, or an unwillingness to encounter unpleasant experiences, such as anxiety, is a key component of psychological inflexibility (Sutcliff et al., 2019 ). Tasks that are considered to be difficult and challenging and do not provide instant rewards tend to be delayed and avoided (Blunt and Pychyl, 2000 ; Sirois and Pychyl, 2013 ; Steel, 2007 ). Escaping from stressful and aversive situations might relieve stress and are thus rewarding. As an example, students are always faced with a trade-off when choosing between procrastinating or studying (Kirby et al., 2005 ; Olsen et al., 2018 ) . One alternative is to complete the challenging academic tasks on time which leads to delayed rewards in the form of achieving academic and career goals (see e.g., Sutcliff et al., 2019 ). These goals often strongly align with students' values. However, students always have an alternative to choose an immediate, positive reinforcers in the form of avoidance or escape from negative internal experiences elicited by challenging tasks, such as engaging in social or leisure activities that are not related to the task at hand. Consequently, a number of recent studies have suggested that procrastination is strongly characterised by avoidant tendencies and aversive experiences and is thus mainly involved with the person’s ability to deal with negative emotions, in addition to their time and effort management skills (Sirois, 2014 ; Ticeand Bratslavsky, 2000 ; Hailikari et al., submitted).
Psychological flexibility is thought to be constructed of six core psychological processes, which are cognitive defusion, self-as-context, being present, acceptance, values and committed actions (Hayes et al., 2012 ). These processes include the ability to observe and recognise ones’ own thoughts and seeing them just as thoughts rather than truths; keeping a flexible perspective-taking attitude on one’s thinking and feeling; the ability to remain in the present moment and be mindful of thoughts, feelings, and sensations without judging them; confronting negative thoughts and emotions without attempting to change them; clarifying one’s hopes, values and goals in life and finally, doing and taking actions which are consistent with one’s hopes, values and goals (Flaxman et al., 2013 ; Hayes et al., 2012 ). Each of these processes is a psychological skill that can be enhanced in different life domains.
Previous research has clearly shown a link between high levels of procrastination and psychological inflexibility. Eisenbeck et al. ( 2019 ) found that procrastination and psychological distress were associated with psychological inflexibility and further, psychological inflexibility mediated the relationship between general psychological distress and procrastination. The role of psychological flexibility’s sub-processes in procrastination among university students has also been studied, and it was found that committed actions were moderately negatively correlated with procrastination suggesting that committed action could be a promising variable in the study of procrastination (Gagnon et al. 2016 ). Another study showed that procrastination was negatively and moderately related to lower levels of acceptance, adding support to the negative link between psychological flexibility and procrastination (Glick et al., 2014 ). The significance of psychological flexibility in the university context has been studied less, but recent research in this context showed that psychological flexibility has a strong relationship with student engagement and study progression (Asikainen, 2018 ; Asikainen et al., 2018 ).
A recent study by Jeffords et al. ( 2018 ), showed that psychological flexibility is closely related to self-efficacy. Self-efficacy has often been studied previously, focusing on procrastination with results showing an inverse relationship with procrastination (Howell and Watson, 2007; Steel, 2007 ; Wolters, 2003 ). Academic Self-efficacy beliefs describe students’ beliefs in their own capabilities to learn new things and to complete given tasks successfully (Bandura, 1997 ). According to the study by Jeffords et al. ( 2018 ) students who reported greater psychological flexibility felt more efficacious in their ability to complete their studies, whereas students who reported greater inflexibility also reported feeling less efficacious. Similar findings have been reported in relation to students’ time and effort management skills. Bembenutty ( 2009 ) showed that college students who have greater academic self-efficacy also tend to show increased management of their time and study environment (see also Burlison et al., 2009 ; Park and Sperling, 2012 ). Academic Self-efficacy beliefs have been proposed as a possible explanation for procrastination in the academic context, indicating that low academic self-efficacy beliefs are associated with an increased tendency to procrastinate (Judge and Bono, 2001 ). If one’s academic self-efficacy beliefs are low, the motivation to initiate work or to commit to required action should also be low, resulting in avoidance behaviour and consequently procrastination (Grunschel et al. 2013 ). On the other hand, students who believe that they can and will do well are more likely to be motivated to self-regulate, persist and engage in studying (Pintrich and Schunk, 2002 ; Zimmerman, 2000 ). Academic Self-efficacy beliefs have been found to be among the strongest predictive factors of performance in various domains (e.g., Lane and Lane, 2001 ; Pajares, 1996 ). Thus, when exploring the maintaining factors of procrastination, it is important to include academic self-efficacy.
Taken together, previous research suggests that time and effort management skills, psychological flexibility and self-efficacy are all closely related to procrastination. Although the studies in this area support a tentative connection between these factors, it is far from conclusive. To our knowledge, no previous study has brought together these central constructs in explaining procrastination. They have been explored separately as they represent different research traditions. The aim of the present study is to include all these variables and explore their interrelations and how they together predict procrastination among students that experiences challenges with their study skills. There is a need to understand the underlying mechanisms of procrastination and which constructs are especially important if the aim is to reduce procrastination among higher education students. This research focuses on answering the following research question: How are university students’ time and effort management skills, psychological flexibility and self-efficacy associated with (a) each other and (b) to their reported level of procrastination.
2.1 participants.
The data were collected from students studying arts and humanities at a Finnish university. Prolonged study times are a great challenge at the Faculty of Arts and Humanities (Kurri, 2006 ). Recent research also suggests that students procrastinate more in the field of arts and humanities compared to other academic fields (Nordby et al., 2017 ). The data came from the students who participated in a voluntary time management and well-being course, and who were willing/eager to improve their study skills. This course was advertised for students who have challenges with their time-management and well-being. A total of 149 students voluntarily participated in the study and answered the questionnaire in autumn 2019. Students responded to the questionnaires at the beginning of the course as a part of their pre-assignment. Of these students, 14 were excluded because their answers had many missing values concerning the measured dimensions (> 50%). Thus, a total of 135 students provided the data. In the questionnaire, the students were asked to evaluate their own time and effort management skills, academic self-efficacy, tendency to procrastinate and psychological flexibility. Of these students, 22 were male students and 110 female students. Two students identified as ‘other gender’, and one did not answer this question. Approximately a quarter of the students in the Faculty of Arts are male and, thus, the sample distribution is similar to the population. The average age of the participants was 28.1 years (SD = 7.62).
We used two scales, focusing on time and effort management skills and academic self-efficacy, from the HowULearn questionnaire (Parpala and Lindblom-Ylänen, 2012 ). HowULearn -questionnaire and its scales are widely used and validated in Finnish and international contexts (e.g., Cheung et al., 2020; Parpala et al., 2010 ; Postareff et al., 2018; Ruohoniemi et al., 2017 ; Rytkönen et al., 2012). The HowULearn questionnaire has also been translated in the context of Danish higher education (Herrmann et al., 2017 ). Time and effort management skills are measured with four items on a Likert-scale from 1 to 5 (e.g. 'I am generally systematic and organised in my studies’). Concerning students’ academic self-efficacy, we used a scale from HowULearn questionnaire which has been constructed based on (Pintrich and Garcia ( 1991 ) Motivated Strategies for Learning Questionnaire (MSLQ). Five items, using a Likert scale from 1 to 5, were modified to suit the academic self-efficacy. As it is applied here, academic self-efficacy refers to students’ appraisal of their ability to master academic tasks including their judgements about their ability to accomplish a task as well as their confidence in their skill to perform that task. Based on these items, an academic self-efficacy scale for constructed (5 items, e.g., ‘I believe I will do well in my studies as long as I make an effort’). Psychological flexibility was measured according to the work-related acceptance and action questionnaire (WAAQ) (Bond et al., 2013) which was recently developed to fit the higher education context in Finland (7 items, e.g., ‘My worries do not prevent me from succeeding in my studies’ (Asikainen, 2018 ). The items used a 7-point Likert scale (1 = totally disagree, 7 = totally agree). Procrastination was measured with a short version of the Pure procrastination scale (PPS) (Svartdahl and Steel, 2017 ) using a 5-point Likert scale (5 items, e.g.,’ In preparation for some deadlines, I often waste time by doing other things’). This short version of the original pure procrastination scale has been proven to be a robust instrument to measure academic procrastination (Svartdahl et al., 2017; see also Klein et al., 2019 ).
Missing value analysis was conducted on the items measuring the scales. There were only four separate missing values concerning different items and, thus, these were replaced with means. The relationships between the scales were analysed with Pearson’s correlation analysis. In addition, linear regression analysis was conducted on the scales measuring academic self-efficacy, time and effort management (= organised studying) and psychological flexibility explaining procrastination. In addition, the students were then divided into three score groups (low/medium/high) based on their scores measuring time and effort management and psychological flexibility where the middle group was formed using the mean + − a half standard deviation. The groups were combined and thus, six score groups were conducted. The differences in these groups in procrastination was analysed with One-way ANOVA and Tukey’s test.
According to the Cronbach alpha analysis, the scales measuring psychological flexibility, procrastination and academic self-efficacy had very good reliability (α = 0.83–0.90). The reliability for the scale measuring time and effort management can be regarded as acceptable (see Table 1 ). Adding more items to measure the same dimension, would most probably have increased the alpha on Organised studying (Taber 2018). However, as the scale has been used in many previous studies with good reliability (Herrmann et al., 2017 ; Parpala et al., 2010 ; Ruohoniemi et al., 2017 ) its use can be considered to be acceptable.
The correlational analysis showed that there was a clear relationship between procrastination, psychological flexibility, academic self-efficacy and time and effort management skills. Procrastination was statistically significantly and negatively correlated with time and effort management skills (r = − 0.584, p < 0.001), academic self-efficacy ( p = − 0.358, p < 0.001) and psychological flexibility (r = − 0.461, p < 0.001). In addition, academic self-efficacy was positively related to psychological flexibility ( p = 0.322, p < 0,001) and time and effort management skills ( p = 0.357, p < 0.001). In addition, time and effort management skills and psychological flexibility correlated positively with each other (r = 0.332, p < 0.001). The correlations can be seen in Table 2 .
A linear regression model was conducted with psychological flexibility, time and effort management and academic self-efficacy as predictors of procrastination. As presented in Table 3 , time and effort management skills, psychological flexibility and academic self-efficacy explained a significant level of variance in procrastination (Adjusted R Square = 0.382). Both time and effort management (t = − 5.63, p < 0.001) and psychological flexibility (t = − 3.06, p = 0.003) explained the variance in procrastination statistically significantly meaning that students who reported greater use of time and effort management strategies and higher psychological flexibility reported less tendency to procrastinate. Academic self-efficacy failed to emerge as an individual predictor of procrastination t = − 1.04, p = 0.301). The results of the regression analysis can be seen in Table 3 .
The One-way ANOVA of the score groups showed that there were differences in experiences of procrastination according to the score groups. According to the Tukey’s test, the group with a high score on time and effort management as well as psychological flexibility scored statistically significantly lower on procrastination than the other score groups (see Table 4 ). In addition, the group with a low score in time and effort management as well as on psychological flexibility scored higher in procrastination than the group scoring average on time and effort management and high on psychological flexibility as well as the group scoring high on time and effort management and average on psychological flexibility. The group scoring average on time and effort management and low on psychological flexibility also scored statistically significantly higher on procrastination than the group scoring high on time and effort management and average on psychological flexibility.
Procrastination is consistently viewed as problematic to academic success and students’ general well-being (Steel, 2007 ). Students’ time management skills as well as ability to manage their own actions despite the negative feelings have been identified as central factors associated with procrastination along with students’ academic self-efficacy beliefs. To this point, however, only a few studies have included all these measures and compared their impact on procrastination. Thus, an aim with the present study was to explore how students’ time and effort management skills, psychological flexibility and academic self-efficacy are interrelated and associated with procrastination as they have been commonly addressed separately in previous studies.
Designed to address this limitation, our findings support three noteworthy findings regarding academic procrastination among students who experience problems in their time management skills. Firstly, our findings show that students’ ability to organise their time and effort had the strongest association with procrastination out of the variables included in the study. Secondly, our findings indicate that psychological flexibility has a strong individual role in explaining procrastination along with time and effort management skills, although to a slightly smaller degree. And thirdly, our findings suggest that these two constructs appear to be closely related and clearly go hand in hand and, thus, both need to be considered. In the remainder of this section, we review the findings that support these points, identify implications for research and practice, and discuss some limitations to these conclusions.
Time management has been repeatedly identified in previous studies as a major factor contributing to procrastination (Ferrari, 2001 ; Senécal et al., 1995 ; Steel, 2007 ; Wolters, 2003 ). Our findings add to this work by showing that in our study time and effort management skills were strongly related to self-reported level of procrastination and explained the largest variance of procrastination in the regression. This finding implies that students’ time and effort management skills can be used to understand their self-reported levels of academic procrastination. However, it appears that time and effort management skills alone are not enough to explain the phenomenon of procrastination as we assumed. In our study, psychological flexibility also had a strong individual role in explaining large variation of procrastination. This is in line with the recent research suggesting that psychological flexibility is also a central construct explaining procrastination (Dionne, 2016 ; Gagnon et al. 2016 ). These two factors were also strongly correlated with each other as well as with academic self-efficacy beliefs which suggests that they share common variance. Their central role was further explained by regression analysis which showed that together they explained almost 40% of the variance in procrastination. Interestingly, in the present study academic self-efficacy beliefs did not have a direct association with procrastination. This finding is in contrast with previous studies showing that lower self-efficacy beliefs are associated with an increased tendency to procrastinate (Judge and Bono, 2001 ; Wolters, 2003 ). However, some studies have similarly reported a non-significant association between self-efficacy and procrastination. For example, Klassen et al. ( 2010 ) showed with Canadian and Singaporean students that although procrastination negatively and significantly correlated with academic self-efficacy, in the regression model there was no association between academic self-efficacy and procrastination. Only self-efficacy for self-regulation and self-esteem had a significant relationship with procrastination (Klassen et al., 2010 ). This finding is very similar to our result. The most likely explanation for the result is that time and effort management skills and psychological flexibility have a more direct and stronger relationship with procrastination than academic self-efficacy even though it is closely related to all these constructs. It might be that if one is committed to value-based actions which are at the core of psychological flexibility, the negative thoughts one might have about oneself may not be hindering one’s goal-based actions (Hayes et al., 2006 ). This is an interesting finding, and it would be useful to study it in more detail in subsequent studies.
As a third noteworthy finding, our findings provide insight into the relations between time and effort management and psychological flexibility as factors contributing to procrastination. Psychological flexibility and time and effort management skills appear to go hand in hand. When the students were divided to three groups based on their scores on psychological flexibility and time and effort management, the largest groups were the ones in which both time and effort managements skills and psychological flexibility were either low or high. The groups where one of these measures would be high and the other would be low were the smallest in implicating their close relationship. Therefore, it seems that if a person rates his/her time and effort management skills highly, he/she rates his/her psychological flexibility high as well. Also, significant correlations between these measures support this notion. A significant positive correlation between time and effort management and psychological flexibility has also been found in previous study (Asikainen et al., 2019 ). Interestingly, the group that rated both time and effort management and psychological flexibility highly rated their tendency to procrastinate as markedly low compared to other groups. The opposite phenomenon was true for the group that rated their time and effort management skills and psychological flexibility low. This group rated their tendency to procrastinate very highly. Interestingly, if the rating on one of these measures, especially on time and effort management studying was lower, the tendency to procrastinate increased drastically. Although this conclusion fits with common-sense expectations regarding these constructs and their relationship, our findings are the first to establish this relationship empirically.
One implication of this finding is that future efforts to remediate students’ procrastination should account for both these factors. Only when accounting for both time and effort management and psychological flexibility can students’ procrastination be understood. Instead of taking procrastination merely as a self-regulation problem, it is also strongly influenced by a person’s inability to cope with negative emotions that arise in challenging situations (Eisenbeck et al., 2019 ; Gagnon et al., 2016 ; Glick et al., 2014 ). It may be suggested that time and effort management support psychological flexibility. Some studies on time allocation suggest that psychological flexibility process includes allocating one’s time to important and value-based actions in everyday life (Kashdan and Rottenberg, 2010 ). Thus, when time is allocated to support value-based action well-being also increases (Sheldon et al., 2010 ). Thinking about your own values and setting goals can also be considered to be a central part of both time and effort management (Entwistle and McCune, 2004 ) and psychological flexibility (Hayes et al., 2006 ). Thus, we could suggest that when practising psychological flexibility, time management is a part of the process in which one needs to plan how to allocate time to support one’s own personal values. Fostering students’ psychological flexibility as well as time and effort managements skills, could be a promising tool to decrease procrastination. As procrastinators often fail to regulate their actions in challenging or stressful situations (Ferrari, 2001 ), it might be that psychological flexibility could be a central construct. More attention should be paid to encouraging students to pursue value-based committed actions, despite the negative thoughts and feelings one might have. Thus, students’ capacity to cope with their negative thoughts and emotions should be enhanced during their studying (Asikainen, 2018 ).
There are also some limitations that should be addressed. The participants consisted of a selected sample of students which most probably influenced the results. The students took part in a time management and well-being course which was directed especially at those students who had experienced problems with their studies. Thus, the sample of the students in this study was selected and most probably consisted mostly of students who were eager and motivated to improve their time management skills and studying. That might also explain why the time and effort management skills were the strongest explanatory variable of procrastination in the present study. Thus, these results of the study are not generalisable to general student population and the selected sample most probably influenced the results. More research is still needed with a bigger and more representative population. Studies should also explore the role of time and effort management skills in procrastination with a more representative student population. The number of participants was rather low which gave limited opportunities for analysis. For example, the number of students in different score groups was rather low, and in some cases too low for the analysis. Therefore, the results should be interpreted with care. Still, we wanted to include the One Way Anova analysis in our study as it clearly showed that psychological flexibility and time and effort management skills are aligned with each other and students with high scores in both of these dimensions report much less procrastination than other students. Furthermore, one major limitation of the study is that the data are based solely on self-reports. This means that we have measured students’ experiences of these variables. However, we used validated questionnaires which have been shown to be reliable in measuring these constructs and thus, we argue that these results also bring valuable insights to research in procrastination which should be further explored. Future research should also include other measures such as accumulation of credits to see how these measures relate to students’ study progression. In addition, our data are also cross-sectional in nature and thus represents only one particular timeframe. Thus, it is not possible to draw any conclusions regarding the predictive value of the variables. In future research we should also include longitudinal data to explore more closely the relationship between these measures. Despite of the numerous limitations in our study, we argue that this paper provides a novel exploration of these predictors of procrastination together which has not been provided in previous studies.
One promising way to support students’ psychological flexibility and learning processes could be to combine study skills courses, such as time and effort management intervention courses with acceptance and commitment therapy (ACT)-based intervention courses, in which students could practise tolerating stress and negative thoughts as well as developing their time and effort management. Recent studies (Asikainen et al., 2019 ) have shown that this kind of ACT-interventions including reflection of one’s own study processes and practising new ways to study, in this way practising new ways to study, can enhance students’ psychological flexibility and time and effort management and in this way, foster students’ well-being and study skills. ACT-based intervention has shown to have multiple positive effects on students’ well-being and studying (Asikainen et al., 2019 ; Levin et al. 2017 ; Räsänen et al. 2016 ). In addition, ACT-based training can help students to manage psychological inflexibility and encourage persistence behaviour, which in turn is likely to have a positive impact on students’ self-efficacy and further, to their academic performance (Jeffords et al. 2018 ). Earlier studies have found that ACT-based interventions targeted at students who suffer from procrastination can decrease experiences of procrastination (Scent and Boes, 2014 ; Wang et al., 2015 ). One study has suggested that different core processes of psychological flexibility have different effects on procrastination. That is, although all the components correlate with procrastination, acceptance and committed actions significantly predict experiences of procrastination (Gagnon et al., 2016 ). Thus, it seems that being more open and accepting of one’s emotional experiences or thoughts and being willing to engage in difficult activities to persist in the direction of important values is important in reducing procrastination.
As time and effort management in our study was the predominant factor associated with procrastination, we suggest that time management should be promoted for higher education students. It has been shown that many students have trouble with time management (Parpala et al., 2010 ). Many studies have shown that different time management strategies are beneficial for different students. These include things like setting goals and planning how to achieve these (Häfner et al., 2015 ), setting deadlines (Ariely and Wertenbroch, 2002 ) and monitoring time use (Asikainen et al., 2019 ). These skills should be enhanced during university study because it has been shown that time and effort management skills remain rather constant without a conscious effort to influence them (Lindblom-Ylänne et al., 2017 ).
To conclude, our study brings novel insights into the underlying mechanisms of procrastination. Our study showed that both psychological flexibility and time management are important factors influencing procrastination, and furthermore, they appear to be closely related factors and together influence procrastination behavior. Thus, both these factors should be considered when the focus is on reducing procrastination. Students who tend to procrastinate might benefit from trainings that focus on training both time management skills and psychological flexibility and not focusing on only either one. This might produce the best results.
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The idea for the article was by TH. All authors contributed to the study conception and design. Material preparation and data collection were performed by TH and the analysis were performed by HA. The first draft of the manuscript was written by TH and NK was responsible for writing the parts regarding psychological flexibility and discussion. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Hailikari, T., Katajavuori, N. & Asikainen, H. Understanding procrastination: A case of a study skills course. Soc Psychol Educ 24 , 589–606 (2021). https://doi.org/10.1007/s11218-021-09621-2
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Procrastination is a prevalent form of self-regulatory failure familiar to most people. Although many consider procrastination innocuous as long as the deadline is met, it is associated with negative consequences in various life domains. Thus, it is important to understand why people procrastinate, what factors contribute to procrastination and what can be done to reduce procrastination. Most research on these topics has been conducted with adults, and the few developmental studies have been conducted independently from adult procrastination research. In this Review, we seek to bring these disparate lines of research into closer alignment and point out their mutual implications. Specifically, we discuss how studying procrastination developmentally highlights a need to reconsider a highly restrictive definition of procrastination dominant in adult research. We also suggest future directions for both adult and developmental research, including measurement, theoretical development and interventions.
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The authors thank Nicolas Chevalier and his lab group, Logan Fiorella, Daniel Gustavson, Flaviu Hodis, Michael Kane and Katrin Klingsieck for providing useful feedback on an earlier version of this article. The authors also thank Sofia Garibay and Adrien Ward for creating initial sketches for Fig. 1 .
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Department of Psychology, Brock University, St Catharines, Ontario, Canada
Caitlin E. V. Mahy
Department of Psychology and Center for Mind & Brain, University of California Davis, Davis, CA, USA
Yuko Munakata
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
Akira Miyake
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All authors were involved in conceptualization of this review, and the writing and editing of the manuscript involved a highly collaborative process between developmental psychologists (C.E.V.M. & Y.M.) and a cognitive psychologist studying procrastination in adults (A.M.). C.E.V.M. and A.M. wrote an initial draft of the Introduction. C.E.V.M. and Y.M. wrote the initial draft of the ‘Procrastination in children’ section. A.M. wrote the initial drafts of ‘Procrastination in adults’ and ‘Summary and future directions’ sections. A.M. and Y.M. wrote the initial draft of ‘Mutual implications’ section. All authors edited the draft of the manuscript and approved the final version of the manuscript.
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Mahy, C.E.V., Munakata, Y. & Miyake, A. Mutual implications of procrastination research in adults and children for theory and intervention. Nat Rev Psychol 3 , 589–605 (2024). https://doi.org/10.1038/s44159-024-00341-w
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What research has been conducted on procrastination evidence from a systematical bibliometric analysis.
Procrastination is generally perceived as a common behavioral tendency, and there are a growing number of literatures to discuss this complex phenomenon. To elucidate the overall perspective and keep abreast of emerging trends in procrastination research, this article presents a bibliometric analysis that investigates the panorama of overviews and intellectual structures of related research on procrastination. Using the Web of Science Database, we collected 1,635 articles published between 1990 and 2020 with a topic search on “procrastination” and created diverse research maps using CiteSpace and VOS viewer. Bibliometric analysis in our research consists of category distribution, keyword co-occurrence networks, main cluster analysis, betweenness centrality analysis, burst detection analysis, and structure variation analysis. We find that most research has focused on students' samples and has discussed the definition, classification, antecedents, consequences and interventions to procrastination, whereas procrastination in diverse contexts and groups remains to be investigated. Regarding the antecedents and consequences, research has mainly been about the relationship between procrastination and personality differences, such as the five-factor model, temperament, character, emotional intelligence, and impulsivity, but functions of external factors such as task characteristics and environmental conditions to procrastination have drawn scant attention. To identify the nature and characteristics of this behavior, randomized controlled trials are usually adopted in designing empirical research. However, the predominant use of self-reported data collection and for a certain point in time rather than longitudinal designs has limited the validation of some conclusions. Notably, there have been novel findings through burst detection analysis and structure variation analysis. Certain research themes have gained extraordinary attention in a short time period, have evolved progressively during the time span from 1990 to 2020, and involve the antecedents of procrastination in a temporal context, theoretical perspectives, research methods, and typical images of procrastinators. And emerging research themes that have been investigated include bedtime procrastination, failure of social media self-control, and clinical interventions. To our knowledge, this is almost the first time to conduct systematically bibliometric analysis on the topic of procrastination and findings can provide an in-depth view of the patterns and trends in procrastination research.
Procrastination is commonly conceptualized as an irrational tendency to delay required tasks or assignments despite the negative effects of this postponement on the individuals and organizations ( Lay, 1986 ; Steel, 2007 ; Klingsieck, 2013 ). Poets have even written figuratively about procrastination, with such phrases as “ Procrastination is the Thief of Time ,” and “ Procrastination is the Art of Keeping Up with Yesterday ” ( Ferrari et al., 1995 ). Literal meanings are retained today in terms of time management. The conceptualizations of procrastination imply inaction, or postponing, delaying, or putting off a decision, in keeping with the Latin origins of the term “pro-,” meaning “forward, forth, or in favor of,” and “-crastinus,” meaning “tomorrow” ( Klein, 1971 ). Time delay is just the behavioral reflection, while personality traits, cognitive and motivational process, as well as contextual conditions are in-depth inducements to procrastination. Procrastination can be viewed as purposive and irrational delay so as to miss the deadlines ( Akerlof, 1991 ; Schraw et al., 2007 ).
Procrastination is believed to be a self-regulation failure that is associated with a variety of personal and situational determinants ( Hen and Goroshit, 2018 ). Specifically, research suggests that task characteristics (e.g., unclear instructions, the timing of rewards and punishment, as well as task aversiveness), personality facets (e.g., the five-factor model, motivation, and cognition), and environmental factors (e.g., temptation, incentives, and accountability) are the main determinants of procrastination ( Harris and Sutton, 1983 ; Johnson and Bloom, 1995 ; Green et al., 2000 ; Wypych et al., 2018 ). Procrastination can be an impediment to success, and may influence the individual's mood, and increase the person's anxiety, depression, and low self-esteem ( Ferrari, 1991 ; Duru and Balkis, 2017 ). Furthermore, a person with procrastination is prone to poor performance, with lower exam scores, slower job promotions, and poorer health ( Sirois, 2004 ; Legood et al., 2018 ; Bolden and Fillauer, 2020 ). Importantly, if policymakers postpone conducting their decision-making until after the proper timing, that procrastination can cause a significant and negative impact on the whole society, such as the cases with the COVID-19 pandemic management in some countries ( Miraj, 2020 ).
In practice, procrastination is stable and complex across situations, ranging from students' academic procrastination, to staffs' work procrastination, to individuals' bedtime procrastination, to administrative behavior procrastination when government organizations face multiple tasks in national governance, and even to delayed leadership decision-making in crisis situations in global governance ( Nevill, 2009 ; Hubner, 2012 ; Broadbent and Poon, 2015 ; Legood et al., 2018 ). As for science research, procrastination has attracted more and more attention and been studied extensively. Personally, possible explanations for emerging research focuses mainly consist of two aspects. On one hand, procrastination with high prevalence and obvious consequences highlights the importance to explore the complex phenomenon deeply, especially the meteoric rise in availability of information and communications technologies (ICTs) amplifies chronic procrastination, such as problematic social media use, smartphone addictions as well as mobile checking habit intrusion ( Ferrari et al., 2007 ; Przepiorka et al., 2021 ; Aalbers et al., 2022 ). On the other hand, more and more basic and milestone research emerges in large numbers, which set the foundation for latecomer' further exploration toward procrastination. In particular, it can't be ignored the efforts of those productive authors in different periods to drive the knowledge development of procrastination.
Procrastination research has experienced tremendous expansion and diversification, but systematic and overview discussion is lacking. Several meta-analyses about procrastination have emerged, but they emphasize more on specific topics ( Steel, 2007 ; Sirois et al., 2017 ; Malouff and Schutte, 2019 ). Furthermore, the number of newly published articles is increasing, so it becomes difficult to fully track the relevant domain literature. In order to grasp knowledge development about the fast-moving and complex research field, bibliometric analysis is necessary to construct diagram-based science mapping, so as to provide a comprehensive and intuitive reference for subsequent researchers. Thus, this article emphasizes on the following major research question: what is the intellectual base and structure of procrastination research? How does the emerging direction of procrastination develop? In our research, bibliometric analysis included the annual distribution of literature, distribution of categories, keyword co-occurrence networks, main research clusters, high citation betweenness centrality, and the strongest citation bursts, as well as the recent publications with transformative potential, in order to look back on the early development of procrastination research and look forward to the future transformation of that research. For both scholars and members of the public, this study can comprehensively enhance their understanding of procrastination and can provide overall perspectives for future research.
Bibliometric analysis is a quantitative method to investigate intellectual structures of topical field. On the basis of co-citation assumption that if two articles are usually cited together, then there are high associations between those articles, bibliometric analysis can reflect the scientific communicational structures holistically ( Garfield, 1979 ; Chen et al., 2012 ). Bibliometric techniques, such as CiteSpace, VOSviewer, HistCite, can generate the science maps based on plenty of literature concerning certain domain. Through the process of charting, mining, analyzing, sorting, and displaying knowledge, science mapping can extract pivotal information from huge complex literature, present knowledge base and intellectual structure of a given field visually, then researchers even general individual can quickly grasp one subject's core structure, development process, frontier field and the whole knowledge framework ( Chen, 2017 ; Widziewicz-Rzonca and Tytla, 2020 ). Bibliometric analysis is commonly regarded as a complementary method to traditional structured literature reviews such as narrative analysis and meta-analysis ( Fang et al., 2018 ; Jiang et al., 2019 ). Traditional literature analysis tends to labor intensive with subjective preferences, and faces difficulties in analyzing larger body of literature, whereas bibliometric analysis provides a more objective approach for investigating considerable literature's intellectual structure through statistical analysis and interactive visual exploration.
In order to master the characteristics of procrastination research, the study adopted the bibliometric software of CiteSpace and VOSviewer to analyze the literature on procrastination during the time period 1990–2020. The software tool VOSviewer is designed for creating maps of authors, journals, and keyword co-occurrences based on network data ( van Eck and Waltman, 2010 ), whereas CiteSpace is applied to conduct co-citation analysis, including centrality betweenness analysis, burst detection, and the emerging trends of research ( Chen, 2006 , 2017 ). In our study, we adopted the CiteSpace (5.7.R1) and VOSviewer (1.6.15) software together. Specifically, co-citation analysis mainly depends on CiteSpace software, and co-occurrence analysis is conducted through VOS viewer ( Markscheffel and Schroeter, 2021 ).
Though there is one similar bibliometrics analysis toward this topic ( Tao et al., 2021 ), related research just focuses on academic procrastination, and mainly conducts co-occurrence analysis using VOSviewer, so as to there is a lack of analysis to core co-citation structures including high betweenness centrality articles, citation burst research and structure variation analysis. To offer insight into the intellectual structure of procrastination research, we further employ CiteSpace — a java application including bibliometric analysis, data mining algorithms and visualization methods developed by Chen — to visualize and elucidate vital trends and pivotal points about knowledge development.
To conduct our bibliometric analysis of procrastination research, we collected bibliographic records from the Web of Science Core Collection as of December 31, 2020. Web of Science is currently the most relevant scientific platform regarding systematic review needs, allowing for a “Topic” query, including searching a topic in the documents' “title”, “abstract”, “author keywords” and “keywords plus” of the documents being reviewed ( Yi et al., 2020 ). A topic search strategy is broad enough to be used in science mapping ( Olmeda-Gomez et al., 2019 ). Given the aim of the study, records were downloaded if they had the term “procrastination” in the “Topic” field. After restricting the type of publication to “Article” for the years 1900–2020, we had searched 2105 papers about procrastination research.
Figure 1 shows the yearly distribution of 2105 literature during 1900–2020, and it can be classified into three phases. In phase I (1900–1989), the annual number of publications never exceeded 10. In phase II (1990–2010), the annual quantity gradually increased from 11 papers in 1991 to 48 in 2010. The annual number of publications had begun to grow in this period, but remained below 50 papers yearly. In phase III (2011–2020), however, the procrastination research experienced a dramatic growth, with 255 literature in the year 2020. Although procrastination research appeared as early as 1900s, it had a stable total volume until the 1990s, when it developed sustained growth, and that growth became extraordinary during the 2010s. Therefore, this research emphasized centered on 1,635 literature that were published during the time span 1990–2020.
Figure 1 . Distribution of publications on the topic of procrastination, 1900-2020.
Category distribution.
Procrastination research has been attracting increasing attention from scholars, and it has been successfully integrated into various scientific fields. With the help of CiteSpace software, we present in Figure 2 the timelines of the various disciplines that are involved in procrastination research, and the cumulative numbers of literature that have been published.
Figure 2 . Distribution of categories involved in procrastination research.
As Figure 2 shows, the size of node on the horizontal lines represents the quantity of literature published. Node colors denote the range of years of occurrence, and purple outlining is an indication of those articles with prominent betweenness centrality, and red nodes present references with high citation burst ( Chen, 2017 ). Besides, the uppermost line shows the timeline of different disciplines, and the numbers on the longitudinal lines describe the distinct categories of procrastination research, of which are arranged vertically in the descending order of cluster's size. Clusters are numbered from 0, i.e Cluster #0 is the largest cluster and Cluster #1 is the second largest one. Specifically, the earlier research about procrastination occurs in the Psychology and Social Science disciplines. Subsequently, research has expanded into Computer Science and Information Systems, Economics, the Neurosciences, the Environmental Sciences, Ethics, Surgery, and general Medicine. As the connections arc in the Figure 2 presents, those categories #0 Psychology and Social Sciences, #1 Computer Science, and #2 Economics interact actively, but the interdisciplinary research about the remaining categories, such as #9 Medicine, #5 Ethics, and #4 Environmental Science, is not active.
Our analysis of the category distribution reveals two aspects of the characteristics about procrastination research. One, related research mostly has its roots in the Psychology and Social Science disciplines, and interdisciplinary research needs to be improved. And Two, the foundational literature dates back to the 1990s, and transformational exploration is currently needed in order to further develop the research on procrastination.
Analysis of co-occurring keywords is often used to obtain the content of research fields. Using the VOS viewer, we obtained a total of 5,203 keywords and created a co-occurrence network. As mentioned above, the size of a node represents the number of times that a specific keyword occurs. Several keywords turn up frequently, such as Procrastination, Performance, Academic Procrastination, Motivation, Personality, Self-regulation, Self-control, and Behavior. To create a readable map, the “minimum number of occurrences” is set to 20, and the final network includes 90 high-frequency keywords and five clusters with 2,650 links, as is shown in Figure 3 .
Figure 3 . Keywords co-occurrence network for procrastination research.
Among the five clusters depicted in Figure 3 , the blue cluster is mainly related to the definition of procrastination, with keywords such as Procrastination, Delay, Deadlines, Choice, Self-Control, and Implementation Intentions. Procrastination is a complex phenomenon, and previous research has elaborated on the core traits about procrastination from various dimensions. Mainstream views hold that procrastination can be defined as the intentional delay of work because of a self-regulation failure, time-management inefficiency, short-term benefits, a gap between intention and action ( Tice and Baumeister, 1997 ; Steel, 2007 ; Pychyl and Flett, 2012 ; Klingsieck, 2013 ), or missing a deadline and causing negative outcomes ( Johnson and Bloom, 1995 ; Howell and Watson, 2007 ; Sirois, 2021 ).
The cluster in red in Figure 3 involves procrastination performance in relation to different life-domains, including Academic Achievement, Life Satisfaction, Online Learning, and Technology Uses. Previous research has elaborated on procrastination as being negatively correlated with performance. However, intrinsic motivation, self-regulated learning, and time-management have been shown to relieve the procrastination behavior ( Wolters, 2003 ; Howell and Watson, 2007 ; Baker et al., 2019 ).
The green cluster highlights traits associated with procrastination. Related research in that cluster mostly discusses the correlation between the five-factor model (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and procrastination ( Schouwenburg and Lay, 1995 ). In addition, personality traits including indecisiveness, indecision, and perfectionism have been elaborated upon ( Klingsieck, 2013 ; Tibbett and Ferrari, 2019 ). Furthermore, to measure the trait of procrastination itself, various scales have been developed, such as the General Procrastination Scale, Decisional Procrastination Questionnaire, Procrastination at Work Scale, Irrational Procrastination Scale, Adult Inventory of Procrastination Scale and so on ( Lay, 1986 ; Ferrari et al., 1995 ; Steel, 2010 ; Metin et al., 2016 ). The validity and reliability of those scales have also been investigated fully.
The cluster presented in yellow depicts studies that focuses on academic procrastination, and especially those that discuss the antecedents of the prevalent behavior, such as Anxiety, Perfectionism, Self-efficacy, Depression, and Stress ( Schraw et al., 2007 ; Goroshit, 2018 ). Owing to their accessibility for use as a research sample, a large body of procrastination research has chosen students in an academic setting as the research objects. Researchers have found that academic procrastination is an impediment to academic performance, especially for very young students. Notably, too, female students may perform lower levels of academic procrastination than males do.
The last cluster, presented in purple, relates to chronic procrastination's involvement in health and addiction, for either adults or adolescents. Discussion about chronic procrastination is growing, and interventions can be effective in relieving this behavior.
From the analysis of co-occurrence keywords, we can infer that procrastination research has been developing steadily. The fundamental discussion has become more adequate and persuasive in regard to the definition, the individual differences, and the antecedents of procrastination, and a discussion of how to relieve the behavior has begun.
Comparing to keyword co-occurrence network analyses, cluster analysis can help us grasp the primary themes in procrastination research. Clusters are based on the assumption that if two references are often cited together, they may be associated in some way ( Chen et al., 2012 ; Pan et al., 2019 ). Eventually, related references shape diverse co-citation networks. Clustering is a procedure to classify co-cited references into groups, with references in the same clusters being tightly connected with each other but loosely associated with other clusters ( Chen et al., 2010 ).
Based on the references of the top 50 articles with the most citations every year (if the number was less than 50 in a certain year, then all of the articles were combined), the final network contained 982 references and we were able to develop the final cluster landscape. Two procedures are used to label each cluster: (1) retrieval of keywords from the citing articles using the log likelihood ratio, and (2) retrieval of terms contained in the cited articles with latent semantic indexing ( Olmeda-Gomez et al., 2019 ). In our research, we adopted the log-likelihood ratio (LLR) method to label the clusters automatically. Given the related structural and time-based values, articles in the co-citation network are assigned to each cluster. Eventually, the network was divided into 23 co-citation clusters.
In addition, two critical parameters, silhouette and modularity, are used to measure whether clusters are available and whether they are well-constructed. Silhouette indicates the homogeneity of clusters, whereas modularity measures whether the network is reasonably divided into independent clusters. The silhouette value ranges from −1 to 1, and the modularity score ranges from 0 to 1. When values of the two metrics are high, the co-citation network is well-constructed ( Chen et al., 2010 ; Widziewicz-Rzonca and Tytla, 2020 ). As is shown in Figure 4 , the mean silhouette score of 0.9223 suggested that the homogeneity of these clusters was acceptable, and the modularity score of 0.7822 indicated that the network was reasonably divided.
Figure 4 . Landscape view of co-citation network of procrastination research.
In our research, we summed the largest nine clusters. As is shown in Table 1 , the silhouette value for all clusters was higher than 0.8, suggesting the references in each cluster were highly homogeneous. The labels of these clusters were controlled trial, avoidant procrastination, conscientiousness procrastination, smoking cessation, explaining lack, academic achievement, procrastinatory media use, career indecision, and goal orientation.
Table 1 . Summary of the nine largest clusters in procrastination research.
In Table 1 , the year in the far-right column indicated the average year when the reference was cited. Ranking the clusters by the mean cited year, we can follow the development of research themes. During the 1990s, research themes focused on discussions about the antecedents of procrastination. For example, Lay (1988) discussed that the self-regulation model cannot explain procrastination fully, and errors in estimations of the time taken to complete a task may be attributed to procrastination. Procrastinators were thought to tend to lack conscientiousness and goal orientation as well as to be motivated by neurotic avoidance ( Ferrari et al., 1995 ; Elliot and Harackiewicz, 1996 ). Besides, procrastination was prevalent throughout our lifespan, and empirical research on procrastination conducted through controlled trials had considered various settings or scenarios, such as academic procrastination, smoking cessation, career indecision, and in the most recent years, media use ( Klassen et al., 2008 ; Germeijs and Verschueren, 2011 ; Du et al., 2019 ). Because procrastination was negatively associated with performance, life satisfaction, health and well-being, research on procrastination avoidance and intervention, including strengths-based training and cognitive behavioral therapy had attracted the most attention from scholars ( van Eerde, 2003 ; Balkis and Duru, 2016 ; Visser et al., 2017 ).
Co-citation analysis and clustering analysis form the cornerstone for bibliometric investigation ( Olmeda-Gomez et al., 2019 ), especially for the microscopic intellectual structures of the science, such as betweenness centrality, burst detection, and structural variation analysis ( Pan et al., 2019 ). Based on the cited references network during the period of 1990–2020, we generated a landscape visualization of intellectual structures about procrastination research. The section consists of three parts: (1) Betweenness Centrality Analysis captures the bridge nodes, which represents the landmark and pivotal literature of a scientific field ( Freeman, 1978 ). (2) Burst Detection Analysis is used to detect the emergent and sharp increases of interest in a research field ( Kleinberg, 2003 ), which is a useful method for easily tracing the development of research focus and research fronts. (3) Structural Variation Analysis (SVA) is an optional measurement to identify whether newly published articles have the potential to transform the citation network in the latest years. Newly published articles initially have fewer citations and may be overlooked. To overcome the limitation, structural variation analysis often employs zero-inflated negative binomial (ZINB) and negative binomial (NB) models to detect these transformative and potential literature ( Chen, 2013 ).
Literature with high betweenness centrality tends to represent groundbreaking and landmark research. On the basis of our co-citation network on procrastination research for the period 1990–2020, we chose the top 10 articles to explore (see Supplementary Material for details). Related research mainly focuses on three areas.
Procrastination is described as the postponement of completion of a task or the failure to meet deadlines, even though the individual would meet adverse outcomes and feel uncomfortable as a result ( Johnson and Bloom, 1995 ). Extracting from authoritative procrastination scales, Diaz-Morales et al. (2006) proposed a four-factor model of procrastination: dilatory behaviors, indecision, lack of punctuality, and lack of planning. Procrastination is commonly considered to be a pattern of self-regulation failure or self-defeating behavior ( Tice and Baumeister, 1997 ; Sirois and Pychyl, 2013 ).
The most popular classification is the trinity of procrastination: decisional, arousal, and avoidant procrastination ( Ferrari, 1992 ). Using the General Behavioral Procrastination Scale and Adult Inventory of Procrastination Scale, Ferrari et al. (2007) measured the difference between arousal and avoidant procrastination, and they elaborated that those two patterns of procrastination showed similarity and commonality across cultural values and norms. However, by conducting a meta-analytic review and factor analyses, Steel (2010) found that evidence for supporting the tripartite model of procrastination may not be sufficient. Research has reached a consensus about the basic definition of procrastination, but how to classify procrastination needs further discussion.
Procrastination is related to time management in its influence on one's behavior. Non-procrastinators or active procrastinators have better time control and purposive use of time ( Corkin et al., 2011 ). However, time management is an obstacle to procrastinators. From the temporal disjunction between present and future selves, Sirois and Pychyl (2013) pointed out that procrastinators tended to give priority to short-term mood repair in the present, even though their future self would pay for the inaction. Similarly, in a longitudinal study Tice and Baumeister (1997) pointed out that maladjustment about benefits-costs in participants' timeframe shaped their procrastination. When a deadline is far off, procrastination can bring short-term benefits, such as less stress suffering and better health, whereas early benefits are often outweighed by possible long-term costs, including poor performance, low self-esteem, and anxiety. These viewpoints confirm that procrastination is a form of self-regulation failure, and that it involves the regulation of mood and emotion, as well as benefit-cost tradeoffs.
Procrastination shows significant stability among persons across time and situations. Predictors of procrastination include personality traits, task characteristics, external environments, and demographics ( Steel, 2007 ). However, typically, empirical research has mostly focused on the relationship between the five-factor model and procrastination behavior. Johnson and Bloom (1995) systematically discussed five factors of personality to variance in academic procrastination. Research also had found that facets of conscientiousness and neuroticism were factors that explained most procrastination. In alignment with these findings above, Schouwenburg and Lay (1995) elaborated that procrastination was largely related to a lack of conscientiousness, which was associated with six facets: competence, order, dutifulness, achievement-striving, self-discipline, and deliberation. Meanwhile, impulsiveness (a facet of neuroticism) has some association with procrastination, owing to genetic influences ( Gustavson et al., 2014 ). These discussions have established a basis for research about personality traits and procrastination ( Flett et al., 2012 ; Kim et al., 2017 ).
To relieve procrastination, time management (TM) strategies and clinical methods are applied in practice. Glick and Orsillo (2015) compared the effectiveness of those interventions and found that acceptance-based behavior therapies (ABBTs) were more effective for chronic procrastinators. Regarding academic procrastination, Balkis (2013) discussed the role of rational beliefs in mediating procrastination, life satisfaction, and performance. However, there is no “Gold Standard” intervention for procrastination. How to manage this complex behavior needs further investigation.
A citation burst indicates that one reference has gained extraordinary attention from the scientific community in a short period of time, and thus it can help us to detect and identify emergent research in a specialty ( Kleinberg, 2003 ). A citation burst contains two dimensions: the burst strength and the burst status duration. Articles with high strength values can be considered to be especially relevant to the research theme ( Widziewicz-Rzonca and Tytla, 2020 ). Burst status duration is labeled by the red segment lines in Figure 5 , which presents active citations' beginning year and ending year during the period 1990-2020. As can be seen in Figure 5 , we ranked the top 20 references (see Supplementary Material for details) with the strongest citation bursts, from the oldest to the most recent.
Figure 5 . Top 20 references with the strongest citation bursts.
To systematically investigate the active areas of procrastination research in different time periods, we divided the study's overall timespan into three time periods. During the period 1990 through 1999, there were six references with high citation bursts, with two of them by Ferrari and a third by Ferrari, Johnson, and McCown. Subsequently, in 2000 through 2009, there were eight reference bursts, and the meta-analysis and theoretical review by Steel (2007) had the highest citation burst among those 20 references. From the period 2010 through 2020, six references showed high citation bursts.
How one defines procrastination is important to interventions. During the early period of procrastination research, scholars paid significant attention to define procrastination and discuss its antecedents. Time delay in completing tasks constitutes the vital dimension that distinguishes procrastination behavior, and that distinction has set the foundation for future exploration of the behavior. Lay (1988) found that errors in estimations of time led to procrastination, then identified two types of procrastinators: pessimistic procrastinators and optimistic ones, according to whether one is optimistic or pessimistic about judgments of time. In addition, the timeframe or constraint scenario influences one's behavioral choices. Procrastinators tend to weigh short-term benefits over long-term costs ( Tice and Baumeister, 1997 ).
However, time delay is just a behavioral representation, and personality traits may be in-depth inducements to procrastination behavior ( Ferrari, 1991 ; Ferrari et al., 1995 ). Schouwenburg and Lay (1995) empirically studied and elaborated upon the relationship between the five-factor model and procrastination facing a sample of students, and their findings showed consistency with research by Ferrari (1991) which demonstrated that the trait facets of lacking conscientiousness and of neurotic avoidance were associated with procrastination. In addition, Ferrari (1992) evaluated two popular scales to measure procrastination: the General Procrastination (GP) scale and the Adult Inventory for Procrastination (AIP) scale. Regarding the measurement of procrastination, a variety of scales have been constructed to further enhance the development of procrastination research.
During period II, procrastination research with high citation bursts focused largely on two dimensions: behavioral antecedences and empirical methods. On one hand, discussions about cognitive and motivational antecedents spring up. A series of studies find that cognitive and motivational beliefs, including goal orientation, perceived self-efficacy, self-handicapping, and self-regulated learning strategies, are strongly related to procrastination ( Wolters, 2003 ; Howell and Watson, 2007 ; Klassen et al., 2008 ). Specifically, Howell and Watson (2007) examined the achievement goal framework with two variables, achievement goal orientation and learning strategies usage, in which four types of goal orientation can be derived by the performance vs. mastery dimension and the approach vs. avoidance dimension. Their research found that procrastination was attributed to a mastery-avoidance orientation, whereas it was adversely related to a mastery-approach orientation. Moreover, Chu and Choi (2005) identified two types of procrastinators, active procrastinators versus passive procrastinators, in terms of the individual's time usage and perception, self-efficacy beliefs, motivational orientation, stress-coping strategies, and final outcomes. This classification of procrastinators has aroused a hot discussion about procrastination research ( Zohar et al., 2019 ; Perdomo and Feliciano-Garcia, 2020 ). Cognitive and motivational antecedents are complementary to personality traits, and the antecedents and traits together reveal the complex phenomenon.
In addition, there are various research methods being applied in the research, such as meta-analyses and grounded theory. Having the strongest citation burst in period II, research that was based on a meta-analysis of procrastination by Steel (2007) elaborated on temporal motivation theory (TMT). Temporal motivational theory provides an innovative foothold for understanding self-regulation failure, using four critical indicators: expectancy, value, sensitivity to delay, and delay itself. Similarly, van Eerde (2003) conducted a meta-analysis to examine the relationship between procrastination and personality traits, and proposed that procrastination was negatively related to conscientiousness and self-efficacy, but was also actively associated with self-handicapping. Procrastinators commonly set deadlines, but research has found that external deadlines may be more effective than self-imposed ones ( Ariely and Wertenbroch, 2002 ). Furthermore, Schraw et al. (2007) constructed a paradigm model through grounded theory to analyze the phenomenon of academic procrastination, looking at context and situational conditions, antecedents, phenomena, coping strategies, and consequences. These diverse research methods are enhancing our comprehensive and systematical understanding of procrastination.
After nearly two decades of progressive developments, procrastination research has entered a steady track with diverse current bursts, on topics such as type distinction, theoretical perspective, temporal context, and the typical image of procrastinators. Steel (2010) revisited the trinity of procrastination — arousal procrastinators, avoidant procrastinators, and decisional procrastinators — and using the Pure Procrastination Scale (PPS) and the Irrational Procrastination Scale (IPS), he found that there was no distinct difference among the three types. Regarding research settings, a body of literature has focused on academic procrastination in-depth, and that literature has experienced a significant citation burst ( Kim and Seo, 2015 ; Steel and Klingsieck, 2016 ). For example, academic procrastination is associated more highly with performance for secondary school students than for other age groups.
Notably, theoretical discussions and empirical research have been advancing synchronously. Klingsieck (2013) investigated systematic characteristics of procrastination research and concluded that theoretical perspectives to explain the phenomenon, whereas Steel and Ferrari (2013) portrayed the “typical procrastinator” using the variables of sex, age, marital status, education, community location, and nationality. Looking beyond the use of time control or time perception to define procrastination, Sirois and Pychyl (2013) compared the current self and the future self, then proposed that procrastination results from short-term mood repair and emotion regulation with the consequences being borne by the future self. In line with the part of introduction, in the last 10 years, research on procrastination has flourished and knowledge about this complex phenomenon has been emerging and expanding.
Structure variation analysis (SVA) can predict the literature that will have potential transformative power in the future. Proposed by Chen (2012) , structure variation analysis includes three primary metrics — the modularity change rate, cluster linkage, and centrality divergence — to monitor and discern the potential of newly published articles in specific domains. The modularity change rate measures the changes in and interconnectivity of the overall structure when newly published articles are introduced into the intellectual network. Cluster linkage focuses on these differences in linkages before and after a new between-cluster link is added by an article, whereas centrality divergence measures the structural variations in the divergence of betweenness centrality that a newly published article causes ( Chen, 2012 ; Hou et al., 2020 ). The values of these metrics are higher, and the newly published articles are expected to have more potential to transform the intellectual base ( Hou et al., 2020 ). Specifically, cluster linkage is a direct measure of intellectual potential and structural change ( Chen, 2012 ). Therefore, we adopted cluster linkage as an indicator by which to recognize and predict the valuable ideas in newly published procrastination research. These top 20 articles with high transformative potential that were published during the period 2016-2020 were listed (see Supplementary Material for details). Research contents primarily consist of four dimensions.
Although procrastination research has drawn mostly on samples of students, innovative research contents and methods have been emerging that enhance our understanding of academic procrastination. In the past five years, different language versions of scales have been measured and validated ( Garzon Umerenkova and Gil-Flores, 2017a , b ; Svartdal, 2017 ; Guilera et al., 2018 ), and novel research areas and contents have arisen, such as how gender difference influences academic procrastination, what are the effective means of intervention, and what are the associations among academic procrastination, person-environment fit, and academic achievement ( Balkis and Duru, 2016 ; Garzon Umerenkova and Gil-Flores, 2017a , b ; Goroshit, 2018 ). Interestingly, research has found that females perform academic procrastination less often and gain better academic achievements than males do ( Balkis and Duru, 2017 ; Perdomo and Feliciano-Garcia, 2020 ).
In addition, academic procrastination is viewed as a fluid process. Considering the behavior holistically, three different aspects of task engagement have been discussed: initiation, completion, and pursuit. Vangsness and Young (2020) proposed the metaphors of “turtles” (steady workers), “task ninjas” (precrastinators), and “time wasters” (procrastinators) to elaborate vividly on task completion strategies when working toward deadlines. Individual differences and task characteristics can influence one's choices of a task-completion strategy. To understand the fluid and multifaceted phenomenon of procrastination, longitudinal research has been appearing. Wessel et al. (2019) observed behavioral delay longitudinally through tracking an undergraduate assignment over two weeks to reveal how passive and active procrastination each affected assignment completion.
In addition to the relationship between procrastination and the five-factor model, other personality traits, such as temperament, character, emotional intelligence, impulsivity, and motivation, have been investigated in connection with procrastination. Because the five-factor model is not effective for distinguishing the earlier developing temperamental tendencies and the later developing character traits, Zohar et al. (2019) discussed how temperament and character influence procrastination in terms of active and passive procrastinators, and revealed that a dependable temperament profile and well-developed character predicted active procrastination.
Procrastination is commonly defined as a self-regulation failure that includes emotion and behavior. Emotional intelligence (EI) is an indicator with which to monitor one's feelings, thinking, and actions, and hot discussions about its relationship with procrastination have sprung up recently. Sheybani et al. (2017) elaborated on how the relationship between emotional intelligence and the five-factor model influence decisional procrastination on the basis of a students' sample. As a complement to the research above, Wypych et al. (2018) explored the roles of impulsivity, motivation, and emotion regulation in procrastination through path analysis. Motivation and impulsivity reflecting a lack of value, along with delay discounting and lack of perseverance, are predicators of procrastination, whereas emotion regulation, especially for suppression of procrastination, has only appeared to be significant in student and other low-age groups. How personality traits influence procrastination remains controversial, and further research is expected.
Newly published research is paying more attention to procrastination in different sample groups across the entire life span. Not being limited to student samples, discussions about procrastination in groups such as teachers, educated adults, and workers have been emerging. With regard to different life domains, the self-oriented domains including health and leisure time, tend to procrastinate, whereas parenting is low in procrastination among highly educated adults. Although the achievement-oriented life domains of career, education, and finances are found with moderate frequency in conjunction with procrastination, these three domains together with health affect life the most ( Hen and Goroshit, 2018 ). Similarly, Tibbett and Ferrari (2019) investigated the main regret domains facing cross-cultural samples, so as to determine which factors increased the likelihood of identifying oneself as a procrastinator. Their research found that forms of earning potential, such as education, finances, and career, led participants to more easily label themselves as procrastinators. Procrastination can lead to regret, and this research adopted reverse thinking to discuss the antecedents of procrastination.
In addition to academic procrastination, research about the behavior in diverse-context settings has begun to draw scholars' attention. Nauts et al. (2019) used a qualitative study to investigate why people delay their bedtime, and the study identified three forms of bedtime procrastination: deliberate procrastination, mindless procrastination, and strategic delay. Then, those researchers proposed coached interventions involving time management, priority-setting skills, and reminders according to the characteristics of the bedtime procrastination. Interestingly, novel forms of procrastination have been arising in the attention-shortage situations of the age of the internet, such as social media self-control failure (SMSCF). Du et al. (2019) found that habitual checking, ubiquity, and notifications were determinants for self-control failures due to social media use, and that finding provided insight into how to better use ICTs in a media-pervasive environment. Moreover, even beyond those life-related-context settings, procrastination in the workplace has been further explored. Hen (2018) emphasized the factor of professional role ambiguity underlying procrastination. Classification of procrastination context is important for the effectiveness of intervention and provides us with a better understanding of this multifaceted behavior.
Overcoming procrastination is a necessary topic for discussion. Procrastination is prevalent and stable across situations, and it is commonly averse to one's performance and general well-being. Various types of interventions are used, such as time management, self-management, and cognitive behavioral therapy. To examine the effectiveness of those interventions, scholars have used longitudinal studies or field experimental designs to investigate these methods of intervention for procrastination. Rozental et al. (2017) examined the efficacy of internet-based cognitive behavior therapy (ICBT) to relieve procrastination, from the perspective of clinical trials. Through a one-year follow-up in a randomized controlled trial, researchers found that ICBT could be beneficial to relieve severe, chronic procrastination. Taking the temporal context into consideration, Visser et al. (2017) discussed a strengths-based approach — one element of the cognitive behavioral approach — that showed greater usefulness for students at an early stage of their studies than it did at later ages. Overall, research on the effectiveness of intervention for procrastination is relatively scarce.
Discussion on procrastination research.
This article provides a systematic bibliometric analysis of procrastination research over the past 30 years. The study identifies the category distribution, co-occurrence keywords, main research clusters, and intellectual structures, with the help of CiteSpace and VOS viewer. As is shown in Figure 6 , the primary focuses for research themes have been on the definition and classification of procrastination, the relationships between procrastination and personality traits, the influences brought by procrastination, and how to better intervene in this complex phenomenon.
Figure 6 . Bibliometric analysis and science map of the literature on procrastination.
Those contents have built the bases for procrastination research, but determining how those bases are constructed is important to the development of future research. Therefore, this article primarily discusses three aspects of intellectual structure of procrastination research: betweenness centrality, burst detection, and structural variation analysis. From the betweenness centrality analysis, three research themes are identifiable and can be generally summarized as: definition and classification of procrastination, procrastination behavior in a temporal context, and causes and interventions for procrastination.
However, procrastination research themes have evolved significantly across the time period from 1990–2020. Through burst detection analysis, we are able to infer that research has paid extraordinary attention to diverse themes at different times. In the initial stage, research is mainly about the antecedents of procrastination from the perspectives of time-management, self-regulation failure, and the five-factor model, which pays more attention to the behavior itself, such as delays in time. Subsequently, further discussions have focused on how cognitive and motivational facets such as goal orientation, perceived self-efficacy, self-handicapping, as well as self-regulated learning strategies influence procrastination. In the most recent 10 years, research has paid significant attention to expanding diverse themes, such as theoretical perspectives, typical images of procrastinators, and procrastination behavior in diverse temporal contexts. Research about procrastination has been gaining more and more attention from scholars and practitioners.
To explore newly published articles and their transformative potential, we conduct structural variation analysis. Beyond traditional research involving academic procrastination, emerging research themes consist of diverse research settings across life-domains, such as bedtime procrastination, social media self-control failure, procrastination in the workplace, and procrastination comparisons between self-oriented and achievement-oriented domains. Furthermore, novel interventions from the perspective of clinical and cognitive orientations to procrastination have been emerging in response to further investigation of procrastination's antecedents, such as internet-based cognitive behavior therapy (ICBT) and the strengths-based approach.
In summary, research on procrastination has gained increasing attention during 1990 to 2020. Specifically in Figure 7 , research themes have involved in the definition, classification, antecedents, consequences, interventions, and diverse forms of procrastination across different life-domains and contexts. Furthermore, empirical research has been conducted to understand this complex and multifaceted behavior, including how best to design controlled trial experiments, how to collect and analyze the data, and so on.
Figure 7 . Brief conclusions on procrastination research.
From the perspective of knowledge development, related research about procrastination has experienced tremendous expansion in the last 30 years. There are three notable features to describe the evolutionary process.
First, research focuses are moving from broader topics to more specific issues. Prior research mostly explored the definition and antecedents of procrastination, as well as the relationship between personality traits and procrastination. Besides, earlier procrastination research almost drew on students' setting. Based on previous research above, innovative research starts to shed light on procrastination in situation-specific domains, such as work procrastination, bedtime procrastination, as well as the interaction between problematic new media use and procrastination ( Hen, 2018 ; Nauts et al., 2019 ; Przepiorka et al., 2021 ). With the evolvement of research aimed at distinct contexts, more details and core contents about procrastination have been elaborated. For example, procrastination in workplace may have association with professional role ambiguity, abusive supervision, workplace ostracism and task characteristics ( Hen, 2018 ; He et al., 2021 ; Levin and Lipshits-Braziler, 2021 ). In particular, owing to the use of information and communication technology (ICTs), there currently are ample temptations to distract our attention, and those distractions can exacerbate the severity of procrastination ( Du et al., 2019 ; Hong et al., 2021 ). Therefore, how to identify those different forms of procrastination, and then to reduce their adverse outcomes, will be important to discuss.
Second, antecedents and consequences of procrastination are further explored over time. On one hand, how procrastination occurs arises hot discussions from diverse dimensions including time management, personality traits, contextual characteristics, motivational and cognitive factors successively. Interestingly, investigations about neural evidences under procrastination have been emerging, such as the underlying mechanism of hippocampal-striatal and amygdala-insula to procrastination ( Zhang et al., 2021 ). Those antecedents can be divided into internal factors and external factors. Internal factors including character traits and cognitive maladjustments have been elucidated fully, but scant discussion has occurred about how external factors, such as task characteristics, peers' situations, and environmental conditions, influence procrastination ( Harris and Sutton, 1983 ; He et al., 2021 ). On the other hand, high prevalence of procrastination necessitates the importance to identify the negative consequences including direct and indirect. Prior research paid more attention to direct consequences, such as low performance, poor productivity, stress and illness, but the indirect consequences that can be brought about by procrastination remain to be unclear. For example, “second-hand” procrastination vividly describes the “spillover effect” of procrastination, which is exemplified by another employee often working harder in order to compensate for the lost productivity of a procrastinating coworker ( Pychyl and Flett, 2012 ). Although such phenomena are common, adverse outcomes are less well investigated. Combining the contexts and groups involved, targeted discussions about the external antecedents and indirect consequences of procrastination are expected.
Third, empirical research toward procrastination emphasizes more on validity. When it comes to previous research, longitudinal studies are often of small numbers. However, procrastination is dynamic, so when most studies focus on procrastination of students' sample during just one semester or several weeks, can limit the overall viewpoints about procrastination and the effectiveness of conclusions. With the development of research, more and more longitudinal explorations are springing up to discuss long-term effects of procrastination through behavioral observation studies and so on. Besides, how to design the research and collect data evolves gradually. Self-reported was the dominant method to collect data in prior research, and measurements of procrastination usually depended on different scales. However, self-reported data are often distorted by personal processes and may not reflect the actual situation, even to overestimate the level of procrastination ( Kim and Seo, 2015 ; Goroshit, 2018 ). Hence, innovative studies start to conduct field experimental designs to get observed information through randomized controlled trials. For the following research, how to combine self-reported data and observed data organically should be investigated and refined.
This bibliometric analysis to procrastination is expected to provide overall perspective for future research. However, certain limitations merit mentioning here. Owing to the limited number of pages allowed, it is difficult to clarify the related articles in detail, so discussion tends to be heuristic. Furthermore, the data for this research comes from the Web of Science database, and applying the same strategy to a different database might have yielded different results. In the future, we will conduct a systematic analysis using diverse databases to detect pivotal articles on procrastination research.
The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author/s.
BY proposed the research question and conducted the research design. XZ analyzed the data and wrote primary manuscript. On the base of that work mentioned above, two authors discussed and adjusted the final manuscript together.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.809044/full#supplementary-material
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Keywords: procrastination, co-citation analysis, intellectual structure, CiteSpace, bibliometric analysis
Citation: Yan B and Zhang X (2022) What Research Has Been Conducted on Procrastination? Evidence From a Systematical Bibliometric Analysis. Front. Psychol. 13:809044. doi: 10.3389/fpsyg.2022.809044
Received: 04 November 2021; Accepted: 10 January 2022; Published: 02 February 2022.
Reviewed by:
Copyright © 2022 Yan and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Xiaomin Zhang, zhangxiaomin2014@mail.sjtu.edu.cn
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Solving Procrastination
Here, you will find a comprehensive collection of research about procrastination. It comes in two parts:
The sources that were used to write the articles come from many fields, such as psychology, behavioral economics, and neuroscience. They include many types of papers, such as theoretical articles, review articles, meta-analyses, experimental studies, clinical studies, and computational studies. Most of these are publications in peer-reviewed journals, but some represent other types of academic sources, including book chapters, doctoral dissertations, and entries in scientific encyclopedias, all written by scientific experts.
There are hundreds of procrastination papers listed in this bibliography. A selection of key ones are bolded ; these are recommended items to start with if you want to read the scientific literature about procrastination.
The following are the key articles on the website that summarize and synthesize existing procrastination research:
Below, you will find all the procrastination research that these articles are based on, which is cited throughout the articles using hyperlinks. Note that the articles also cite additional sources that are not listed here, primarily about topics that are relevant for understanding and dealing with procrastination, but that are not directly about procrastination itself (e.g., the stages that people go through as they work to change their behavior).
Chen, G., & Lyu, C. (2024). The relationship between smartphone addiction and procrastination among students: A systematic review and meta-analysis. Personality and Individual Differences , 224 , Article 112652. https://doi.org/10.1016/j.paid.2024.112652
Araya-Castillo, L., Burgos, M., González, P., Rivera, Y., Barrientos, N., Yáñez Jara, V., … & Sáez, W. (2023). Procrastination in university students: A proposal of a theoretical model. Behavioral Sciences , 13 (2), Article 128. https://doi.org/10.3390/bs13020128
Arnold, I. J. (2023). The link between procrastination and graduation rates: Evidence from the ALEKS learning platform. Education Economics , 31 (3), 275-287. https://doi.org/10.1080/09645292.2022.2063796
Bai, H., Li, X., Wang, X., Tong, W., Li, Y., & Hu, W. (2023). Active procrastination incubates more creative thinking: The sequential mediating effect of personal mastery and creative self-concept. Creativity Research Journal . Advance online publication. https://doi.org/10.1080/10400419.2023.2171721
Bodalski, E. A., Flory, K., Canu, W. H., Willcutt, E. G., & Hartung, C. M. (2023). ADHD symptoms and procrastination in college students: The roles of emotion dysregulation and self-esteem. Journal of Psychopathology and Behavioral Assessment , 45 (1), 48-57. https://doi.org/10.1007/s10862-022-09996-2
Campbell, R. L., & Bridges, A. J. (2023). Bedtime procrastination mediates the relation between anxiety and sleep problems. Journal of Clinical Psychology , 79 (3), 803-817. https://doi.org/10.1002/jclp.23440
Cruz, R. N. C., & Miranda, J. O. (2023). Examining procrastination using the DSM-5 personality trait model: Disinhibition as a core personality trait. Current Psychology . Advance online publication. https://doi.org/10.1007/s12144-023-04815-7
Fuke, T. S. S., Kamber, E., Alunni, M., & Mahy, C. E. V. (2023). The emergence of procrastination in early childhood: Relations with executive control and future-oriented cognition. Developmental Psychology , 59 (3), 579. https://doi.org/10.1037/dev0001502
Gökalp, Z. Ş., Saritepeci, M., & Durak, H. Y. (2023). The relationship between self-control and procrastination among adolescent: The mediating role of multi screen addiction. Current Psychology , 42 (15), 13192-13203. https://doi.org/10.1007/s12144-021-02472-2
Johansson, F., Rozental, A., Edlund, K., Côté, P., Sundberg, T., Onell, C., … & Skillgate, E. (2023). Associations between procrastination and subsequent health outcomes among university students in Sweden. JAMA Network Open , 6 (1), Article e2249346. https://doi.org/10.1001/jamanetworkopen.2022.49346
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Is procrastination good or bad? Some people judge procrastination and call it “lazyness”. Others insist that procrastinating helps them to do their best under pressing deadlines.
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📌 interesting procrastination essay topics to write about, 👍 good procrastination research topics, ❓ research questions about procrastination.
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Procrastination and stress: a conceptual review of why context matters.
2. procrastination, stress, and emotion regulation, 3. stressful contexts and vulnerability for procrastination, 3.1. coping depletion vulnerability, 3.2. phenotypic expression vulnerability, 4. covid-19 stress and vulnerability for procrastination, 4.1. health threats, 4.2. social isolation and loneliness, 4.3. remote working, 4.4. financial insecurity, 5. applications of a stress context vulnerability model of procrastination, 6. implications and future directions, 7. conclusions, institutional review board statement, data availability statement, conflicts of interest.
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Sirois, F.M. Procrastination and Stress: A Conceptual Review of Why Context Matters. Int. J. Environ. Res. Public Health 2023 , 20 , 5031. https://doi.org/10.3390/ijerph20065031
Sirois FM. Procrastination and Stress: A Conceptual Review of Why Context Matters. International Journal of Environmental Research and Public Health . 2023; 20(6):5031. https://doi.org/10.3390/ijerph20065031
Sirois, Fuschia M. 2023. "Procrastination and Stress: A Conceptual Review of Why Context Matters" International Journal of Environmental Research and Public Health 20, no. 6: 5031. https://doi.org/10.3390/ijerph20065031
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COMMENTS
Introduction. Procrastination is commonly conceptualized as an irrational tendency to delay required tasks or assignments despite the negative effects of this postponement on the individuals and organizations (Lay, 1986; Steel, 2007; Klingsieck, 2013).Poets have even written figuratively about procrastination, with such phrases as "Procrastination is the Thief of Time," and ...
Procrastination is moderately and positively associated with perceived stress in samples of adolescents , university students [6,9,12,16,22], community-dwelling adults [5,8,23], and individuals with hypertension and cardiovascular disease . This research is primarily cross-sectional, making it difficult to confirm the direction of influence.
The potential role of study self-efficacy was not examined in the Kim and Seo paper, but other research (e.g., Balkis, Citation 2011) has demonstrated study self-efficacy as a moderator variable. The results of the present paper indicate that study self-efficacy should receive increased attention as a moderator or mediator variable in studies ...
Procrastination would stem from present costs (if the task is done now) being perceived in a much more vivid manner than distant costs (if the task is done later) 1. Thus, in this model, the ...
Academic procrastination is a common and detrimental behavior among students that negatively impacts academic performance and well-being. This comprehensive review examines the various factors ...
Procrastination is generally perceived as a common behavioral tendency, and there are a growing number of literatures to discuss this complex phenomenon. To elucidate the overall perspective and keep abreast of emerging trends in procrastination research, this article presents a bibliometric analysi …
This research aims to systematize the scientific production on educational interventions aimed at reducing academic procrastination in the classroom. To this end, a systematic review of the literature (PRISMA-P) of the interventions carried out in the last decade (n = 32) was conducted.
Furthermore, severe procrastination was associated with greater self-reported negative effects on all of the life-domains that were examined, most notably for work/studies, but also for physical activity/diet and rest/sleep, which resemble previous research on the impact of procrastination on both academic achievement and health (e.g ...
searching a topic in the documents' "title ", "abstract", "author. ... 2105 papers about procrastination research. Figure 1 shows the yearly distribution of 2105 literature.
The relationship between different emotions with situational (e.g., academic) and dispositional (chronic) procrastination was examined extensively in the literature since the early days of procrastination research. A review of empirical studies over the past 40 years might shed light on the role of emotions in procrastination in different contexts with different populations. The current paper ...
The research presented in this paper examined the relationships between academic procrastination and learning-specific emotions, and how these variables predict one another over time among undergraduate (n = 354) and graduate students (n = 816). Beyond findings showing expected valences of relations between procrastination and positive emotions (enjoyment, hope, and pride) and negative ...
Harriott and Ferrari (1996) reported 20 % of adults engage in procrastination. In academic settings, previous studies reported 23-52% of undergraduate students suffer from procrastination (Balkis & Duru 2009; Özer, Demir, & Ferrari, 2009). Apart from the prevalence of procrastination, the frequency of procrastination experienced can influence ...
Introduction. Procrastination involves unnecessary and unwanted delay, be it decisional, implemental, or lack of timeliness (Lay, 1986; McCown et al., 1989; Mann et al., 1997; Steel, 2010).Furthermore, Steel (2007) emphasized that a core characteristic of procrastination is the realization by the actor that one will be worse off because of the delay. . Hence, procrastination can be seen as ...
1.1. Procrastination. Procrastination is a relatively old phenomenon, as psychologist William James already recognized the emotional cost generated in people who suffered from it more than 120 years ago [].Lay [] pointed out that procrastination considers importance to the individual whose action is being postponed, while Milgram, Mey-Tal, and Levison [] discussed whether the performance of a ...
ABSTRACT. Academic procrastination is a prevalent phenomenon with a. range of negative outcomes. Many studies focused on causes. and correlates of academic procrastination; however, the study. of ...
Procrastination is consistently viewed as problematic to academic success and students' general well-being. There are prevailing questions regarding the underlying and maintaining mechanisms of procrastination which are yet to be learnt. The aim of the present study was to combine different ways to explain procrastination and explore how students' time and effort management skills ...
Procrastination is often viewed as innocuous as long as deadlines are met but it is associated with negative life outcomes. In this Review, Mahy et al. bring together procrastination research in ...
Among the five clusters depicted in Figure 3, the blue cluster is mainly related to the definition of procrastination, with keywords such as Procrastination, Delay, Deadlines, Choice, Self-Control, and Implementation Intentions.Procrastination is a complex phenomenon, and previous research has elaborated on the core traits about procrastination from various dimensions.
International Journal of Sociology and Anthropology Research Vol.5, No.1, pp.17-22, January 2019 ___Published by European Centre for Research Training and Development UK (www.eajournals.org) 17 Print ISSN: 2059-1209, Online ISSN: 2059-1217 THE IMPACT OF PROCRASTINATION ON STUDENTS ACADEMIC PERFORMANCE IN SECONDARY SCHOOLS
List of all the procrastination research that was used to write the articles on the website. The sources that were used to write the articles come from many fields, such as psychology, behavioral economics, and neuroscience. They include many types of papers, such as theoretical articles, review articles, meta-analyses, experimental studies ...
So, in conclusion, procrastination reduces th e. quality of academic work while increasing st ress (Schraw et al., 2007). The majority of these research projects are ab out the individual factors ...
Procrastination as a Means of Improving Creativity. The work's author is Adam Grant, a professor of management and psychology at the Wharton School of the University of Pennsylvania. The point of the essay is to talk about the benefits of procrastination. Procrastination: Qualitative and Quantitative Research Methods.
Research over the past two decades has continued to highlight the robust associations between procrastination and stress across multiple populations and contexts. Despite this burgeoning evidence base and theory linking procrastination to higher levels of stress, as well as the reverse, the role of context in this potentially dynamic association has received relatively little attention. In ...
This page provides a comprehensive list of engineering thesis topics designed to assist students in selecting relevant and engaging subjects for their academic research. With 600 diverse topics organized into 20 categories—ranging from aeronautical and chemical engineering to robotics and environmental engineering—this list offers a broad spectrum of ideas to inspire your thesis.
S. Arumsari, 2014) . Sometimes students have planned to start working on a task at the time that. procrastination is the failure of a person to do a task in the form of procrastinating starting ...
This page provides a comprehensive list of economics thesis topics designed to assist students in selecting relevant and impactful subjects for their academic research. Featuring 600 topics across 20 diverse categories, this list covers the full spectrum of economics, from agricultural economics and behavioral economics to international trade and public economics.