Procrastination in academic and work settings

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Procrastination in academic and work

settings

Csongor Lakatos (10828060)

Master Thesis Business Administration: Leadership and Management University of Amsterdam

Faculty of Economics and Business Amsterdam, Augustus 31, 2015

Supervisor: Dr. W. van Eerde Academic year: 2014-2015

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Statement of Originality

This document is written by Student Csongor Lakatos who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion

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List of Tables and Figures

Table 1: Cronbach’s Alpha ... 26

Table 2 Sub-group means ... 27

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Table 4 Working context – Regression analysis ... 29

Table 5 Working context – Regression analysis with separate subscales ... 30

Table 6 Academic context - Means, standard deviations and correlations ... 31

Table 7 Academic context - Regression analysis ... 32

Table 8 Academic context – Regression analysis with separate subscales ... 33

Table 9 One-way ANOVA with repeated measures results - Procrastination ... 34

Table 10 One-way ANOVA with repeated measures estimated marginal means ... 35

Table 11 One-way ANOVA with repeated measures results - Norms ... 35

Table 12 One-way ANOVA with repeated measures estimated marginal means ... 35

Table 13 Means, standard deviations, and correlations ... 36

Table 14 Regression analysis - Diary study ... 37

Table 15 Regression analysis ... 37

Table 16 Reported procrastination ... 38

Figure 1 Fluctuation in Procrastination - Workers ... 39

Figure 2 Fluctuations in Procrastination - Students ... 39

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Introduction

The phenomenon of procrastination received increasing research attention during the recent decades. However, one can find considerable amount of evidence that it has been affecting mankind since the birth of civilization. Some of the most well-known philosophers and leaders of the ancient times, such as Cicero and Thucydides, wrote about procrastination as a hateful and perilous trait (Steel, 2007). This negative connotation in the literature continues to exist, yet the exact definition remains a subject of debate. What the authors need to be consistent about when conceptualizing procrastination is to include a postponing or delaying of a task or an action, in keeping with the term’s Latin origins of pro, meaning “forward, forth, or in favour of,” and crastinus, meaning “of tomorrow” (Klein, 1971). A rather general definition is given by Schouwenburg & Lay (1995), according to their description, “to procrastinate is to put off acting on one’s intentions”. On the other hand, a more specific explanation is given by Ferrari (1994), who made a distinction between functional and dysfunctional procrastination, defining the latter as the habitual delay of tasks that is ultimately detrimental to task success. The plain dictionary definition is “defer action, especially without good reason” (Oxford English Reference Dictionary, 1996). This explanation suggests that people who procrastinate engage in irrational behaviour, by choosing a course of action despite expecting that it would not maximize their utilities. As it is stated by Steel (2007), the different attempts from researchers to define procrastination can be complementary, and combined in order to create a more specific explanation that is “to procrastinate is to voluntarily delay an intended course of action despite expecting to be worse off for the delay”.

The phenomena of procrastination is pervasive, and concerns many of us. Research suggests that that approximately 95% of college student engage in such behaviour sometimes, and Solomon & Rothblum (1984) claim that at least 50% of the students procrastinate consistently and problematically. By determining the characteristics of the prototypical procrastinator, Steel

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& Ferrari (2012) argued that the ones who are most likely to procrastinate are urban young men, who have stopped or dropped out of school, more likely to remain single or separated rather than be in a committed relationship, and has chosen or put off having kids. These findings provide some interesting implications, like men seem to procrastinate more than women, and that it may decrease as one grows older. However, this doesn’t mean that the rest of the population is not affected, as procrastination has been also found to affect approximately 15-20% of adults chronically (Harriott & Ferrari, 1996).

The importance of the topic stems from the fact that procrastination has been linked to several negative outcomes. The negative aspects include poorer performance and individual well-being, miserableness, and increased amount of stress (Steel, 2007; Tice & Baumeister, 1997). A survey by H&R Block suggests that procrastinating on taxes caused people around $400 loss on average because of rushing and consequent errors (Kasper, 2004). In the same way, it is considered as a major problem in a variety of fields, such as health care, economics, and politics (Steel, 2007). As it is more likely to occur among students, one of the most affected domain is the academic field. Students who engage in procrastination are expected to receive lower course grades, missing deadlines for submitting assignments, and other negative outcomes, such as course withdrawal (Beswick, Rothblum & Mann, 1988). It must be mentioned that some authors claim that procrastination does not necessarily have negative effects. As it was stated before, Ferrari (1992) made a distinction between functional and dysfunctional procrastination, and similarly, Chu & Choi (2005) differentiated active and passive procrastinators. They argued that certain individuals may intend to delay tasks strategically, in order to experience thrill to avoid boredom, and because they believe they can perform better under pressure. However, these studies failed to receive sufficient empirical support, and the fact that one might delay tasks in a planned manner seems to contradict with most definitions of procrastination. Thus, this study aims to focus on delay despite expecting to be worse off.

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Given the prevailing nature and the harmful consequences of procrastination, research has been conducted in order to reveal the possible causes and correlations. Still, these researches on procrastination was not driven by a commonly shared theory (Van Eerde, 2003), instead, many different explanations were given. Probably the most popular one is where procrastination is considered as a trait to postpone or delay tasks or making decisions. Studies suggest that procrastination represents low conscientiousness and self-regulatory failure (Steel, 2007). It was also related to another variety of personality traits, such as self-efficacy, impulsiveness and self-handicapping (Van Eerde, 2003). Another approach is to examine the nature of the task itself. Since postponing a task should mean that one prefers another task instead, it suggests that certain task characteristics might make might make some of them less attractive. These characteristics included task aversiveness, difficulty, and the timing of rewards and punishments (Steel, 2007). Moreover, researchers also identified demographic moderators, such as age, gender, and education, concluding that men procrastinate more than women, and that younger age and lower education also make the occurrence more likely. However, Van Eerde (2003) claims that engaging in procrastination might be a result of several interrelated processes, determined by factors such as personality, motives, task and context as antecedents, and it might be wiser to think of the contextual and process variables that may induce procrastination and moderate the outcomes.

Similarly, Klingsieck (2013) argues that research examined procrastination in a range of diverse life domains, and that there is a need to conduct investigations that are able to compare procrastination’s characteristics across these different areas. According to Steel (2007), there is sufficient evidence that procrastination is a trait with adequate cross-temporal and situational stability. A research that allows comparison across different domains would be able to determine whether procrastination is indeed solely a personality variable, or is it rather a domain specific phenomenon.

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This study aims to fill this research gap by examining the effects of the changes in the perceptions of contextual variables when students leave the academic field and start their lives as employed professionals. Studies suggest that 50% of students procrastinate problematically (Solomon & Rothblum, 1984), which is considerably higher than the 15-20% which is measured among adults (Harriot & Ferrari, 1996). According to these findings, it seems logical to assume that the contextual changes after the transition should affect one’s intention to procrastinate. Thus, the research questions which will be answered in this study are: “Do individuals procrastinate more in the academic than in the working context?” and “Which situational factors causes the difference in procrastination between the two context?”. In order to be able to answer these research questions, the critical contextual variables will be identified and explained in detail. The study will contribute to the existing knowledge by going beyond the traditional single-context settings, and help to determine whether procrastination is a phenomenon with strong cross-situational stability, or is it something that displays itself rather differently in dissimilar domains. The findings might also suggest important practical implications. Procrastination intervention courses have only managed to achieve moderate general effectiveness (Ferrari et al., 1995). As the exact processes and situational variables that may induce procrastination are not sufficiently clear, these interventions might have excluded vital aspects. By gaining deeper understanding of the role of certain contextual factors, the intervention programs to reduce procrastination – especially in the probably most affected academic domain - might be able to become more effective.

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Literature review

In order to be able to identify the critical variables that people might perceive differently in academic and work settings, an extensive review of the existing literature is needed. As the difference among definitions demonstrates, procrastination research has not been driven by a commonly shared theory (Van Eerde, 2003). However, authors tried to provide a systematic characterization of research trends and integrate the results. Van Eerde (2003) did a meta-analysis based on 88 articles, and created a nomological network by systematically linking demographics, cognitive ability, personality variables, motives, affect and performance to procrastination. The research also suggested that there is a strong focus on individual differences, rather than on task and context, even though procrastination is likely to be the result of several different factors related to personality, motives and situational variables. Klingsieck (2013) has tried to systematize the different approaches to understand procrastination by sorting them into four different perspectives: The differential psychology perspective, the motivational and volitional psychology perspective, the clinical psychology perspective, and the situational perspective. The first perspective is the one where procrastination is considered as a personality trait, and the focus is on the relationship between procrastination and other trait variables. As Steel (2007) argues, there has been adequate amount of research to suggest that procrastination is a phenomenon with cross-temporal and cross-situational stability. The correlations showed a strong negative relationship with conscientiousness and a positive relationship with neuroticism (Van Eerde, 2003; Lee, Kelly, & Edwards, 2006; Steel, 2007). It has also been linked to low self-efficacy and low self-esteem (Van Eerde, 2003; Ferrari, 1994), impulsiveness (Schouwenburg & Lay, 1995), lower optimism (Jackson, Weiss, & Lundquist, 2000), and higher level of perfectionism (Flett, Hewitt, & Martin, 1995). It is also related to self-handicapping (Ferrari, 1991; Van Eerde, 2003) as a strategy to avoid the possibility to receive a negative performance feedback, and protect one’s self-esteem.

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Steel (2007) claims that procrastination is theoretically a representative of low conscientiousness and self-regulatory failure. This latter assumption belongs to the motivational and volitional perspective, where procrastination is understood as failure in one’s motivation or volition. Accordingly, researchers tried to link procrastination with motivational variables, and they found negative relationship with intrinsic motivation and internal locus of control (Brownlow & Reasinger, 2000), decreased self-regulation and self-control (Dietz, Hofer & Fries, 2007; Schouwenburg & Groenwoud, 2001), or volitional problems in general (Dewitte & Lens, 2000). It was also related to time management and time orientation (Lay & Schouwenburg, 1993; Ferrari, Díaz-Morales, 2007). Also, this perspective focuses on concrete theories to explain procrastination, such as the Self-Determination Theory (Senécal et al., 2003), Action Control Theory (Blunt & Pychyl, 2005) and Temporal Motivation Theory (Steel & König, 2006).

The clinical psychology perspective is the one that focuses on the clinically relevant degree of procrastination. The clinical type of procrastination is defined by Frings, Höcker, Wolf, and Rist (2011) as the procrastination that lasts more than 6 months, the duration of the delaying behaviour reaches half a day, and at least five of the physical or psychological complains are present. The importance of treating clinical procrastination stems from the fact that it has been linked to a variety of harmful consequences, such as depression and anxiety (Flett, Blankstein, & Martin, 1995). However, conceptualizing procrastination as a disorder may raise ethical issues, as it may lead to the stigmatization of procrastinators (Klinksieck, 2013)

The situational perspective, as its name suggests, examines the contextual factors instead of intra-personal traits and processes. The basic suggestion is that procrastination is activated by certain situational characteristics, such as task difficulty and autonomy (Ackerman & Gross, 2005), task aversiveness and timing of rewards and punishments (Steel, 2007). However, this

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perspective might not be completely independent from personality traits, since individual attributes are likely to influence how the situation is perceived.

As it was mentioned before, Van Eerde (2003) argued that procrastination is likely to be a result of several different factors related to personality, motives, and situational characteristics. And similarly, Klingsieck (2013) claims that a comprehensive explanation is cannot be based solely on one of the perspectives. On the other hand, procrastination is often considered as a personality trait with strong cross-temporal and cross-situational stability and a representative of low conscientiousness and self-regulatory failure (Steel, 2007). As Klingsieck (2013) argues, researches were usually conducted in single-context settings, and there is a need for comparing procrastination’s features across a different domains. In case individuals would report different levels of procrastination in different domains, then a more contextual specific approach would be supported. Klingsieck (2013b) concluded later that procrastination is indeed more typical in certain life domains, yet she did not differentiated between the academic and the work settings. The studies conducted in the field have often used university or college student samples, and found that around 80-95% of students procrastinate occasionally (Ellis & Knaus, 1977), and almost 50% procrastinate problematically (Solomon & Rothblum, 1984). On the other hand, the amount of procrastinators among the general population is expected to be around 15-20% (Harriot & Ferrari, 1996). According to the different approaches to understand procrastination, two explanations could be given. First, as college students are generally youngsters, it can be assumed that trait procrastination may decrease as one grows older. This is supported by the findings of Van Eerde (2003), who claimed that younger people tend to procrastinate more. Likewise, when Steel & Ferrari (2012) attempted to identify the prototypical procrastinator, they concluded that young men are the most likely to procrastinate. The second explanation is that students perceive certain situational features differently in academic settings than in work or other settings. This explanation is supported by the situational perspective, but as it was

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argued before, procrastination is likely to be an outcome of several factors (Van Eerde, 2003). Thus, it is important to identify the critical variables that might be perceived differently by students and could explain why they are more likely to fail in self-regulation.

Miller & Brickman (2004) presented a model of future oriented motivation and self-regulation, based on the theory of future oriented goals and Bandura’s social-cognitive theory (1986). They argue that personally valued future goals provide an incentive value for action. As these goals are likely to be distant, students build proximal goals that incrementally lead to the future objective. However, the perception of instrumentality - the beliefs that performance would lead to rewards (Bandura, 1986) – is playing a vital role in the self-regulatory process when proximal goals are used in order to achieve distant goals. In this context, it means that the tasks that are perceived to be instrumental to reach future objectives are likely to have more incentive value than tasks that lack this relationship. Due to the lack of incentive value, students who perceive academic tasks as irrelevant to achieve their future goals are more likely to engage in procrastination.

The Higher Education Research Institute at UCLA conducted a research in 2012, which was based on the answers of 192,912 participants who entered college or university for the first time in the United States, and it included a measurement of the reasons why students choose to enter higher education. According to their findings, the two most important reasons were “to be able to get a better job” and “to be able to make more money”. Also, both aims were increasing in the recent years, and the desire to get a better job motivated 88% of respondents, while making more money was important for 74,6% of them. The results suggest that the distant goal for most students are related to developing a career. Since the proximal tasks students face in academic settings are likely to be more theoretical than in work settings, it might be logical to assume that they find these tasks less instrumental. Moreover, from a self-determination perspective, Senécal, Julien & Guay (2003) argue that student’s role conflict may also lead to academic

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procrastination, as the level of self-determination toward interpersonal relationships and education can determine whether they decide to study or to spend time with friends. Similarly, students may consider that building social network or social capital during college years is more likely to be instrumental to their future goals, and it would make them more likely to procrastinate academic tasks. Thus, instrumentality is expected to be perceived differently in academic and in work settings.

Hypothesis 1a: Perceptions of instrumentality are negatively related to procrastination across domains.

Hypothesis 1b: In general, the tasks in academic settings are perceived as less instrumental to future goals than the tasks in work settings.

Another model that might help to explain why students procrastinate more is the temporal discounting theory provided by Steel & König (2006). It is an integrated motivational theory containing elements of four related models: hyperbolic discounting, expectancy theory, cumulative prospect theory, and need theory. Its simplest formulation is utility = ( E x V ) / ( Γ x D ). Utility refers to how desirable a task or choice is for an individual, so activities that are higher on expectancy (E) and value (V) supposed to be more desirable. The denominator represents the fundamental term of the model, which is time. The D refers to the delay, meaning that the enjoyable activities that are immediately realizable have larger utility, while Γ refers to the sensitivity to the delay. The viability of the theory stems from the fact that it has the possibility to contain most of the important variables that may affect procrastination on both individual and situational level, as expectancy is can be related to elements such as self-efficacy and task difficulty, value to the need for achievement and task aversiveness, and delay to impulsiveness and temporal distance (Steel, 2007). Temporal discounting refers to the fact that procrastinators appreciate rewards that are realizable now more than those that are only realizable later. Likewise, punishments that are temporally close are likely to receive more

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attention than those that are distant. Again, the work setting and the academic setting can be compared to one another. Since supervisors usually have direct financial or other interest in their employees’ performance, they are likely to act more quickly and firmly than teachers at the universities. Also, while in work settings it’s the employer that pays for the employees’ work, in academic settings, the students are paying for the university. Solely from an economical point of view, the teachers or professors are less interested in punishing underperformance promptly than employers. Moreover, it was argued that students are increasingly pursuing goals such as career development or earning more money. These rewards for studying might be temporally very distant, while engaging in procrastination usually perceived to have immediate benefits. This is the basic assumption of temporal discounting, and usually it is regretted on the long run. Ferrari, Barnes, and Steel (2009) claims that procrastinators report more regret in their educational and academic pursuits than non-procrastinators.

A study conducted by Specter & Ferrari (2000) showed that both avoidant and decisional procrastination are negatively related to future time orientation. Building on these findings, Sirois (2003) tried to prove that the consideration of future consequences (Strathman, Gleicher, Boninger, & Edwards, 1994) plays a mediating role between trait procrastination and health behaviour intentions. As consideration of future consequences is trying to capture the extent to which future concerns of a certain behaviour is considered by the individual, it was argued that it might explain the differences in procrastinators’ attitude to the delayed rewards of forming health behaviour intentions. Even though the mediating role was not confirmed, it was concluded that consideration of future consequences correlated with procrastination. This finding strengthened the suggestion of Baumeister and Scher (1988), who argued that procrastination might involve a trade-off between long-term consequences and short-term benefits. By conducting a meta-analytic investigation on procrastination and time perspective,

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Sirois (2014) claimed that task avoidance has a higher chance to occur when tasks are difficult and the rewards are more distal. Furthermore, in these scenarios individuals might engage in trade-offs by replacing these tasks with more pleasant ones or activities that have immediate rewards. For example Schouwenburg and Groenewoud (2001) examined students’ study motivation under social temptation. They found that students actually do very little work long before the examination period, and they increase their performance as the finals are approaching. Thus, this finding also seems to support the temporal discounting theory (Steel & König, 2006), showing that the closer the consequences are, the more aware students become of their behaviour, and they are less likely to engage in trade-offs between social activities and school tasks. However, the time when students start focusing on their academic activities vary significantly, which can be traced back to individual differences. As it was argued before, the consideration of future consequences correlated with procrastination, and based on the temporal discounting theory, perceptions about the value and expectancy of these future outcomes might influence behaviour. At this point it might be possible to suggest another contextual difference between the academic and the working environment. It was mentioned that students might experience higher degree of temporal discounting, and the punishments they receive might not be as firm like the ones in work context. Moreover, if students and workers may perceive the instrumentality of the tasks in a certain context differently, they are also likely to differ in the perceived “costs” of not engaging in a certain behaviour. It seems reasonable to suggest that the more strict and rapid consequences of not performing at the expected level in the working context would force the working ones to become more aware of their behaviour, and become less likely to engage in those trade-offs that students do more often. In conclusion, it is argued that in general, workers experience lesser amount of temporal discounting, higher probability of getting punished, and greater “costs” for not engaging in work related tasks, which makes them more likely to consider the future consequences of their behaviour compared to students.

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Hypothesis 2a: Consideration of future consequences is negatively related to procrastination across domains.

Hypothesis 2b: In general, consideration of future consequences is higher in work settings than in academic settings.

The third variable refers to the degree of interrelatedness in the two contexts. By using a qualitative approach to explore the possible antecedents of procrastination, Klingsieck, Gurnd, Schmid, and Fries (2013) have found that students did not report procrastination during group tasks that involved interdependence. The explanations given about the behaviour included moral standards, and cooperation ethics. Similarly, Ackermann & Gross (2005) argued that social norms had a major impact on procrastination in their study. This phenomenon might be possible to explain by a research that examined the relationship between procrastination and social emotions (Sirois & Pychyl, 2013). Students had to recall a situation in which they engaged in a trade-off between their academic work and other activities that they considered more pleasant, then rate the extent to which they sensed that they violated the social norms of the group. The findings showed that students who perceived that their behaviour transgressed the social norms reported a feeling of shame and guilt, and more negative and fewer positive expected consequences of delaying. It seems logical that if students are not able to feel the same pleasantness in engaging a different task when working in groups, they become less likely to make the trade-off.

Moreover, the Theory of Planned Behaviour by Ajzen (1985) argues that a certain behaviour can be traced back to three antecedents, perceived behavioural control, attitudes, and subjective social norms. Subjective norms can be divided into two distinct categories, prescriptive and descriptive norms. The first describe what the referent group says about the expected behaviour, while the second refers to how they actually behave. A research by Askew et al. (2014) tested the aforementioned theory of Ajzen as a model of cyberloafing. Cyberloafing refers to internet

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based non-work related activities employees engage in during working hours, such as browsing the web, watching YouTube, or checking Facebook (Lim, 2002). Studies examining this phenomenon might have important implications for procrastination research, as Lavoie and Pychyl (2001) found that more than 50% of the people in their research group procrastinated through cyberloafing on a frequent basis, which suggests that these activities are often involved when procrastinators are making trade-offs between tasks. The results of the investigation supported the Theory of Planned Behaviour as a model of cyberloafing, highlighting the fact that employees’ perceptions of the reference group’s norms have been proven to be a strong predictor of cyberloafing (Blanchard & Henle, 2008), and descriptive norms have higher influence than prescriptive norms (Askew et al.,2014).

On the other hand, the social loafing theory also need to be taken into account, which suggests that people tend to decrease their individual contribution to complete a task when working in groups (Heuzé & Brunel, 2011). The social impact theory explains this effect by suggesting that responsibility among members are more diffused when working in groups, which decreases the motivation of individuals (Latané et al., 1979). It can be argued that when procrastinators are working in groups, the reduced level of responsibility would make them more likely to make the trade-offs between tasks, and engage in cyberloafing instead of the group work for example. However, Heuzé & Brunel (2011) found that higher levels of intergroup competition among athletes blocked the social loafing process, which makes it possible to suggest some differences between the academic and working context.

As it was mentioned, social norms that disapprove of procrastination should force individuals not to engage in trade-offs and delay tasks. In regards of procrastination, prescriptive norms are the extent to which referent others disapprove of delaying tasks, while descriptive norms are the extent to which referent group members themselves procrastinate. Relying solely on numbers, the higher amount of procrastinators among students suggests that descriptive norms,

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the stronger predictor of the two categories, are less likely to exist in the academic context. Moreover, groups at work usually have to fight for scarce resources, as companies do not possess infinite amount of promotions, money, or rewarding tasks, while groups of students are expected to experience less intergroup competition because of the grading system. The mechanism that influences individuals’ behaviour not to engage in social loafing in a competitive context is expected to have a similar effect on procrastination, by blocking or compensating for the feelings of diffused responsibility, and also contribute to the existence of descriptive norms. Thus, social norms are expected to reduce procrastination, and they are more likely to be present in the working context.

Hypothesis 3a: Social norms are negatively related to procrastination across domains.

Hypothesis 3b: In general, individuals experience stronger social norms in work settings than in academic settings.

As Self-Determination Theory argues, human motivation consist of three basic psychological needs in order to experience well-being: autonomy, competence, and relatedness (Guay, Senécal, Gauthier, Fernet, 2003). Competence reflects the individuals’ perceptions of their ability to achieve intended goals, thus it can be considered as a construct closely related to self-efficacy. Relatedness - the need to experience meaningful and significant social interactions - can also influence procrastinators, as social temptations might strive them to engage in trade-offs. However, this temptation is supposed to be present regardless of the context. On the other hand, the third variable autonomy can be expected to differ in the academic and in the working environment.

Perceived autonomy has been conceptualized through motivational processes, therefore, it is suggested that there are a variety of motivations which reflects different levels of autonomy (Deci & Ryan, 1985). The highest degree of autonomy is paired with intrinsic motivation, while different types of extrinsic motivation – such as external regulation, introjected regulation, and

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identified regulation – are reflecting lower levels of autonomy. Identified regulation refers to the behaviour when one engage in a task because it is judged as important by the individual, while introjected regulation means behaviour that is partly internalized by the person. External regulation is when rewards and constraints guide the action, and it represents the lowest level of autonomy. As the literature on procrastination argues, lower levels of autonomy is associated with higher levels of procrastination (Steel, 2007; Lay, 1992). Thus, individuals who experience higher levels of external regulation should be expected to procrastinate more.

On the other hand, the already cited Theory of Planned Behaviour takes a different approach. The article examining cyberloafing from the Theory of Planned Behaviour point of view by Askew et al. (2014) suggests that perceived behavioural control can be conceptualized in two ways in regards to employees’ non-work related online activities during working hours. The first approach is to consider the construct as employees’ ability to successfully reach the desired website, the other is the extent to which employees are confident that they can engage in the activity without “getting caught” by their co-workers or supervisors (Askew et al., 2014). The authors have proven that this second factor is a significant predictor of cyberloafing at work. This notion is supported by the findings of Jia, Jia, & Kurau (2013), arguing that the presence of an Internet Usage Policy reduces cyberloafing, as individuals experience an increased probability and severity of consequences of getting caught. While the dominant self-control view of cyberloafing claims that employees are actually trying to work, but their lack of self-control stimulates them to engage in cyberloafing, the Theory of Planned Behaviour perspective adopted by Askew et al. (2014) suggests that employees are motivated to cyberloaf, but the presence of social norms and high chances of getting caught might convince them not to do so. These implications can also be applied to procrastination. When individuals are closely monitored if they do the tasks they are intended to do instead of the ones that may cause them short-term pleasantness, they might be less likely to procrastinate.

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Thus, it can be concluded that there are controversial views regarding the relationship between autonomy and procrastination. Lay (1992) argues that individuals who feel compelled to engage in a certain task would be more likely to procrastinate, while the Theory of Planned Behaviour approach suggests that individuals’ are more likely to do non-work related tasks when they experience lesser amount of external constraints. To resolve this contradiction, it can be suggested that certain type of restrictions might be helpful to prevent procrastination, while others might be not. Breaugh (1985) separates three different facets of work autonomy - method autonomy, scheduling autonomy, and criteria autonomy - instead of considering it as a global variable. Method autonomy refers to the degree of freedom individuals have in deciding about the procedures they wish to utilize to complete their work. The presence of choice over how to complete a task has been linked to perceiving the task more favourable and higher levels of feeling competent (Cordova & Lepper, 1996). Moreover, granting individuals a high degree of method autonomy does not mean that they cannot be closely monitored during working hours, which helps to resolve the contradiction. On the other hand, scheduling activity refers to the extent individuals feel that they are able to control the sequencing or scheduling their work (Breaugh, 1985). High levels of scheduling autonomy would mean that an individual have complete freedom over deciding when to do a certain task. According to the Theory of Planned Behaviour approach, under this condition procrastinators would be more tempted to engage in dilatory behaviour. Thus, it is suspected that method autonomy would help to reduce procrastination, while scheduling autonomy would foster it.

Regarding contextual differences, it is safe to suggest that students are granted more scheduling autonomy. They have classes, exams, and deadlines for assignments, but they more or less have complete freedom in deciding when to prepare for these. Among students, it is very common to “pull an all-nighter” before the exams, as they used the time that was allowed to them to engage in different tasks until the very last day. On the other hand, workers are likely

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to experience lesser amount of scheduling autonomy, as they generally have fixed working hours at a fixed workplace, where they are expected to make progress with their work related tasks.

The suspected differences between the contexts regarding method autonomy stem from the different purpose of the two environment. The academic context is highly focused on the ability of individuals to understand and apply learned methods, while the working context is more outcome oriented. For example, students might be instructed not to use a calculator during tasks or not to include sources in an assignment that are not closely related to a particular course, while an employee is less likely to be exposed to such constraints. Thus, it is expected that workers experience higher amount of method autonomy than students.

Hypothesis 4a: Perceptions of autonomy are negatively related to procrastination across domains.

Hypothesis 4b: Perceived scheduling autonomy is smaller in work settings than in academic settings.

Hypothesis 4c: Perceived method autonomy is higher in work settings than in academic settings.

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Research method

This study aims to use quantitative techniques in order to decide whether the identified variables are perceived differently in the two settings. The measured participants will be sampled from a narrow age group, in order to reduce the significance of older age. Three groups will be differentiated: students, students who are working besides their academic duties, and young professionals who have graduated recently. In order to increase the reliability of the findings, two studies are conducted, a general survey based quantitative study (Study 1), and a more focused diary study (Study 2).

Study 1

This study used a quantitative, survey based approach. In order to make it as efficient as possible, the questionnaire was internet mediated. Besides procrastination and the situational variables – perceived instrumentality, consideration of future consequences, social norms and autonomy - the questionnaire consists of items related to personality traits, namely conscientiousness and self-efficacy, as these factors are expected to influence the results. Certain scales measuring contextual factors were slightly modified in order to make it obvious for participants which domain the questions are related to. These changes were necessary as the same scales had to be used for each group to make the comparisons between the scores possible. The modifications are explained in detail in the measurement section. Students and workers received the questionnaire with the same scales but tailored to their contexts, yet participants who are studying and working at the same time had to fill out the questions for both domains. As the scales used for the questionnaire are from English studies, the language of the survey is English as well.

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22 Participants

As it was mentioned before, the sample consists three types of respondents: students, part-time working students, and young working professionals. As intention to procrastinate may decrease with age (Steel & Ferrari, 2012), this research aims to reduce the age gap among participants to as narrow as possible. The survey was distributed online, with the goal of reaching as many respondents as possible.

Measurement of variables

All of the variables are measured on a 7 point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Conscientiousness

To measure conscientiousness, the related parts of the International Personality Item Pool scale are used, developed by Goldberg (1992). The 50-item version of the scale measures the Big Five factors of personality, and it contains 10 items for each of the personality traits. The questions related to conscientiousness include “I am always prepared” and “I follow a schedule”. As this scale measures a personality trait, no modifications were required.

Self-efficacy

The original version of the General Self-efficacy Scale that will be used in this study was made by Jerusalem & Schwarzer (1995). 10 items are included, such as “I am confident that I could deal efficiently with unexpected events”. All of the items were left unchanged.

Consideration of future consequences

The original version of the consideration of future consequences scale adopted in this study was 12 item survey developed by Strathman, Gleicher, Boninger & Edwards (1994). It could be divided into two subscales, consideration of immediate consequences and consideration of future consequences (Joireman, Balliet, Sprott, Spangenberg & Schultz, 2008). In order to increase the reliability of this latter subscale, two new items were introduced by Joireman, Shaffer, Balliet, and Strathman (2012). The expanded questionnaire now consists 14 items, with statements measuring the tendency to consider immediate consequences such as “I only act to satisfy my immediate concerns, figuring that I will take care of future problems that may occur at a later date”, and future consequences, like the statement “I think it is important to take

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warning about negative outcomes seriously even if the negative outcome will not occur for many years”. The items for this scale were not modified.

Procrastination

In order to measure procrastination, the General Procrastination Scale (Lay, 1986) was adopted. The questionnaire consists of 20 items which are originally made for student populations. To resolve this issue, minor modifications were made in the questionnaire. First, the questions were divided into two categories, general and contextual specific. Two examples for the general questions are “When it is time to get up in the morning, I most often get right out of bed.” and “When I prepare to go out, I am seldom caught having to do something at the last minute.”. On the other hand, the contextual specific questions were the ones that involved some sort of task, and can be suspected that they would be perceived differently in the two environments. An example for the contextual specific question is “I do not do assignments until just before they are to be handed in”. After the categorization, 14 general items were addressed, and all of the participants received these questions in the same form. For the contextual specific questions, participants were instructed to think about tasks they engage in their own domain, and some words in the items were altered so that they could reflect the environment better. For example, the question “I do not do assignments until just before they are to be handed in.” was modified into “I do not do tasks until just before they are to be handed in.”. For those participants who stated that they are studying and working at the same time, questions regarding both contexts were presented.

Instrumentality

In order to measure individuals’ perceptions about linkage between their performance and the rewards they receive, three questions were used. The three items that are used by Colquitt (2001) to assess instrumentality are “I see a clear linkage between my performance and the rewards I receive.”, “If I perform well for my team, I am usually rewarded.” and “There is a definite relationship between the quality of my work and the rewards I receive.”. However, minor adjustments were made so that the questions could reflect their context. Because the two environments does not necessarily involve teamwork, the question “If I perform well for my team, I am usually rewarded.” was simply turned into “If I perform well at work, I will be rewarded.” and “If I perform well at school, I will be rewarded.”. Making these modifications were necessary so the ones who are completing the questionnaires for both contexts would not get confused which environment an item reflects to.

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Questions regarding social norms are constructed according to the guidance given by Icek Ajzen (2002). The guideline he provided gives clear instructions how to formulate questions to obtain information about subjective norms that affects behaviour in different situations. The three items that are created includes the measurement of prescriptive norms (“Most of my colleagues think that it is acceptable to procrastinate.”) and descriptive norms (“My colleagues often procrastinate.”) as well. The only difference between the items for the two subgroups was that students were asked questions about their classmates, while workers were asked about the behaviour of their colleagues. Consistently, participants who engage in both contexts were asked about their perceptions of their classmates and colleagues as well.

Autonomy

The scales adopted in order to measure the two distinct facets of autonomy are developed by Breaugh (1985). His scale originally consists of three subscales, scheduling autonomy, method autonomy, and criteria autonomy. However, as criteria autonomy refers to individuals’ ability to choose or alter their evaluation criteria, it would not make too much sense in the academic context. Thus, only the two other subscales are measured as they are expected to be related to procrastination. Method autonomy is the degree to which individuals are allowed to choose the procedures they wish to utilize while working, while scheduling autonomy is the extent to which individuals feel they have control over the scheduling and sequencing of their work. The original method autonomy questionnaire consists 3 items, “I am allowed to decide how to go about my job (the methods to use).”, “I am able to choose the way to go about my job (the procedures to utilize).” and “I am free to choose the method(s) to use in carrying out my work.”. The scheduling autonomy subscale also contains three questions, which are “I have control over the scheduling of my work.”, “I have some control over the sequencing of my work.” and “My job is such that I can decide when to do particular work activities.”. However, as these questions are rather focused on the working context, they were altered for the student participants. The modified questions are reflecting the academic context properly, for example “I have some control over the sequencing of my work.” was changed into “I have some control over the sequencing of my academic activities.” and “I am allowed to decide how to go about my job (methods to use).” was turned into “I am allowed to decide how to go about getting my academic tasks done (the methods to use).”.

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Study 2

The second study takes a different approach, using a longitudinal method to measure individual’s perceptions of their day-to-day tasks, instead of a general view. The group of participants complete the same questionnaire throughout a five day period. The main goal is to find a connection between procrastination and individuals’ feeling of satisfaction regarding their performance. This variable is assessed by the question “How did you feel about your performance today?”. The respondents answer the question by choosing a smile emoticon, representing their feelings, with the meaning of “very bad”, “bad”, “neutral”, “good”, and “very good”. The measurement of procrastination consists five questions, with four questions adopted from Steel’s Irrational Procrastination Scale (Steel, 2002), and one question from Lay’s Procrastination Scale for student populations (Lay, 1986). The questions received minor modifications in order to fit in to a diary study. The four modified items from the IPS scale are “Today, I put things off so long that my well-being or efficiency suffered unnecessarily”, “Today, I did things I should before attending to lesser tasks”, “Today, I delayed tasks beyond what is reasonable”, and “Today, I did everything when I believed it needed to be done”. The item adopted from the IPS is “Today, I wasted time on unimportant things”.

The other questions were related to the first study, using a similar branching technique. Respondents can specify if they engage in work or school related tasks, then give their answers based on their contextual perceptions. The first one aims to measure instrumentality, by stating “I receive something I consider worthy in return for my invested time and effort”. The second one tries to tap into a different aspect of social norms, the expectations of significant others by stating “I was expected to complete the tasks by a group I am related to (e.g. friends, family, or colleagues)”. Finally, scheduling autonomy and method autonomy are measured by the items “I had complete freedom to decide when to do the tasks” and “I had complete freedom to decide how to do the tasks”. A five point Likert-scale was used to measure all of the items.

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Results – Study 1

The survey for study 1 was completed by 176 respondents. Out of them, 88 were male, 87 were female, and one didn’t specify. There were 157 participants between the age of 18 and 25, with an average of 23,25. One participant was younger than 18 and 18 participants were older than 25. The goal of the sampling was to reduce the effect of older age on procrastination, so it will be tested whether the age of participants is related to procrastination or not. The sub-groups consists of 84 students, 46 working students and 46 workers. All data was collected online using the Qualtrics application.

First of all, there was a check of frequencies to examine possible errors in the data, yet the tests haven’t revealed any. Due to the branching technique used by the survey, the context specific questions were not completed by each of the sub-groups, so the cases were excluded listwise during the analysis. The items that were expressed so that an agreement with the question or statement means a low level of the construct being measured were recoded. The full list recoded of questions can be found in the Appendix.

After recoding, reliability checks were conducted for each of the variables to examine the consistency of measurements. The Cronbach’s alpha estimates internal consistency among the items, so it can reveal if some questions should not be used for the analysis. The Cronbach’s alpha results are exhibited in Table 1.

Table 1: Cronbach’s Alpha

Variable Cronbach’s Alpha

Conscientiousness 0,822

Self-efficacy

Consideration of future consequences General procrastination

Work procrastination Academic procrastination Work instrumentality Academic instrumentality Work norms (one item excluded) Academic norms (one item excluded) Scheduling autonomy at work Scheduling autonomy at school Method autonomy at work Method autonomy at school

0,840 0,860 0,858 0,835 0,873 0,888 0,901 0,877 0,812 0,865 0,723 0,930 0,895

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The values higher than 0.7 represent strong internal consistency. However, the results were lower than 0.7 in two cases, so these variables were examined more closely. For both Work norms and Academic norms, there was one question that showed inconsistency with the others, “When we are working in groups, my colleagues expect me not to procrastinate” and “When we are working in groups, my classmates expect me not to procrastinate”. With these questions included, the Cronbach’s alphas were 0,627 for Work norms, and 0,434 for Academic norms. After excluding these items, the Cronbach’s alphas were 0,877 and 0,812

Following the reliability check, the scale means were calculated from the items used to describe the variables. Moreover, the means for calculated for every variable in each of the sub-groups. The results are exhibited in Table 2.

Table 2 Sub-group means

Variables Means

Students Working students Workers

Conscientiousness 4,66 4,70 4,79

Self-efficacy 5,43 5,69 5,80

Consideration of future consequences 4,86 4,70 4,94

General procrastination 3,93 3,90 3,53

Work procrastination - 3,85 3,38

Academic procrastination 4,34 4,41 -

Work instrumentality - 5,05 5,06

Academic instrumentality 4,80 5,00 -

Work norms (one item excluded) - 4,34 4,26

Academic norms (one item excluded) 2,72 2,84 -

Scheduling autonomy at work - 5,06 5,48

Scheduling autonomy at school 4,92 4,95 -

Method autonomy at work - 5,11 5,59

Method autonomy at school 4,79 4,75 -

The basic assumption of the study was that people would procrastinate more in the academic context regardless of their personality traits. The differences between the conscientiousness and the self-efficacy of students and workers might explain the gap between their contextual procrastination, but the working students also reported more procrastination in the academic

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context than in the working one, which is a promising result for the analysis. Also, it can be concluded that the largest difference exists between the contextual factors Work norms and Academic norms.

The analysis started with examining the working context. The dependent variable Procrastination was created by merging together the answers workers and working students gave to the general procrastination and the procrastination in the working context scales, uniting the General Procrastination Scale (Lay, 1986) that was divided in order to be able to measure the different contexts. This step seemed necessary as the original questionnaire adopted in the study considered procrastination as a single construct measured by the 20 items. The correlation matrix shows the means, standard deviations, and correlations (Table 3). It can be concluded that Conscientiousness is the strongest predictor of Procrastination, having a negative correlation coefficient of r = -0759 with the significance of p = 0,000. Moreover, Consideration of future consequences and Scheduling autonomy also showed negative correlations, with r = -0,525 and r = -0,291, with the significance of p = 0,000 and p = 0,008. In addition to this, the correlations for Gender and Age were also tested, with Age showing moderate negative connection to Procrastination (r = -0,219; p = 0,048) and positive to Conscientiousness (r = 0,238; p = 0,032).

Table 3 Working context - Means, standard deviations and correlations

Variables M SD 1 2 3 4 5 6 7 8 1. Procrastination 3,67 0,95 (0,882) 2. Conscientiousness 4,75 0,98 -0,759** (0,822) 3. Self-efficacy 5,79 0,63 -0,203 0,196 (0,84) 4. COFC 4,82 0,86 -0,525** 0,572** 0,219* (0,86) 5. Instrumentality 5,04 1,27 -0,105 0,015 0,303** 0,138 (0,888) 6. Norms 4,3 1,45 -0,172 0,058 0,079 0,04 0,051 (0,877) 7. Scheduling aut. 5,28 1,18 -0,291** 0,281** 0,219* 0,346** 0,137 -0,28 (0,865) 8. Method aut. 5,36 1,23 -0,141 -0,031 0,296** 0,207 0,421** -0,071 0,498** (0,93)

Note: COFC = Consideration of future consequences; N=82

To examine the linear relationship between the variables and the procrastination scores provided by the merged subscales, a multiple regression analysis was conducted, and the results can be seen in Table 4.

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Table 4 Working context – Regression analysis

Variables Step 1 Step 2

Gender -0,006 -0,100 Age -0,219* -0,044 Conscientiousness -0,696** Self-efficacy 0,030 COFC -0,095 Instrumentality -0,005 Work norms -0,147 Scheduling autonomy -0,046 Method autonomy -0,130 R2 0,048 0,639 ΔR2 _0,048 _0,591 ΔF 1,993 (2,79) 14,163** (7,72) Overall F 1,993 (2,79) 16,841** (9,72)

Note: Standardized regression coefficients; *p < 0,05; ** p < 0,001; COFC = Consideration of future consequences

In the first step, two predictors entered: gender and age. The model wasn’t significant statistically with a p-value of 0,143. On the other hand, after the introduction of the other variables in the second step, the significance of the model was F (7,72) = 16,841, p = 0,000 and explained 63,9% of variance in procrastination. However, only conscientiousness showed significant correlation with the significance level of p = 0,000 with Beta = -0,696 and t = -7,231. The other variables were not related significantly to the dependent variable.

Yet in this case, the procrastination variable consisted of two sub-scales, general procrastination and procrastination in the working context. Given the assumption that individuals would procrastinate more in certain contexts, it can be suggested that there would also be differences in their general and context related procrastination. Thus, the subscales were tested separately as well. The results are exhibited in Table 5.

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Table 5 Working context – Regression analysis with separate subscales

Variables General procrastination

Procrastination in the working context

Step 1 Step 2 Step 1 Step 2

Gender 0,037 -0,051 -0,092 -0,164 Age -0,306* -0,134 0,047 0,161 Conscientiousness -0,742** -0,331* Self-efficacy 0,052 -0,028 COFC 0,017 -0,296* Instrumentality -0,044 0,081 Work norms -0,071 -0,251* Scheduling autonomy -0,124 0,135 Method autonomy -0,054 -0,242 R2 0,096 0,660 0,011 0,401 ΔR2 _0,096 _0,564 _0,011 _0,39 ΔF 4,172* (2,79) 15,519** (7,72) 0,432 (2,79) 5,345** (7,72) Overall F 4,172* (2,79) 17,065** (9,72) 0,432 (2,79) 6,687** (9,72)

For general procrastination, even the first step of the model where Age and Gender entered was significant F(2,79) = 4,172; p = 0,019 and explained around 9,6% of the variance in general procrastination. After the second step the model was still significant (F(9,72) = 17,065; p = 0,000), and explained 66% of the variance, with Conscientiousness being the only variable with a p value lower than 0,05.

On the other hand, procrastination in the working context correlated significantly with Conscientiousness (r = -0,413; p = 0,000) Consideration of future consequences (r = -0,477; p = 0,000) and Work norms (r = -0,292; p = 0,008). After conducting a second multiple regression analysis with procrastination in the working context as the dependent variable, the step where Age and Gender entered was irrelevant (F(2,79) = 0,432; p = 0,650), while the variable Conscientiousness revealed the significance of p = 0,009 with Beta = -0,331 and t = -2,671, Consideration of future consequences showed p = 0,016 with Beta = -0,296 and t = -2,475, and

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Work norms had the results p = 0,012, Beta = -0,251, and t = -2,574, suggesting that all of them were significantly and negatively related to procrastination in the working context.

Hypothesis 2a stated that Consideration of future consequences has a negative effect on procrastination. The regression results suggest that it is at least partially true, as it was negatively related to procrastination in the working context. However, the strong positive correlation with Conscientiousness (r = 0,572; p = 0,000) proposes that there might be a mediation effect between the variables, which can undermine the assumption that consideration of future consequences can be perceived differently in the two contexts regardless of personality traits. In order to measure this, the SPSS macro of Hayes (2012) was used.

Mediation coefficients. N=84. *p=.00 **p=.00 ***p=.00

The results suggested a significant and negative indirect effect of Conscientiousness on Procrastination in the working context through Consideration of future consequences, a*b = -0,23, BCa95 CL (-0,34; -0,078). The mediator accounted for almost half of the total effect, having a ratio of PM = 0,49.

The analysis continued with the examination of correlations in the academic context (Table 6). Once again, the general procrastination and the procrastination in the academic context scales were merged in order to have Lay’s original procrastination construct as the only dependent variable.

Table 6 Academic context - Means, standard deviations and correlations

Variables M SD 1 2 3 4 5 6 7 8 1. Procrastination 4,07 1,02 (0,908) 2. Conscientiousness 4,67 0,99 -0,752** (0,822) 3. Self-efficacy 5,53 0,62 -0,202* 0,194* (0,84) 4. COFC 4,82 0,76 -0,401** 0,425** 0,068 (0,86) 5. Instrumentality 4,88 1,39 -0,257** 0,169 -0,086 0,225* (0,901) 6. Academic norms 2,77 1,13 -0,121 -0,037 -0,017 -0,027 0,001 (0,812) 7. Scheduling autonomy 4,91 1,07 -0,004 0,094 0,175 0,095 -0,053 -0,104 (0,723) 8. Method autonomy 4,75 1,17 -0,142 0,134 -0,008 0,031 0,183* -0,030 0,394** (0,895)

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The variables that showed significant correlations with procrastination were Conscientiousness (r = -0,752; p = 0,000), Self-efficacy (r = -0,202; p = 0,030), Consideration of future consequences (r = -0,401; p = 0,000), and Instrumentality (r = -0,257; p=0,005). The variables Age and Gender were also tested, yet they did not show significant correlation with any other construct.

A multiple regression analysis was conducted to examine the effect between procrastination and the continuous variables. The results for the hierarchical regression analysis are exhibited in Table 7.

Table 7 Academic context - Regression analysis

Variables Step 1 Step 2

Gender -0,085 -0,072 Age -0,127 0,007 Conscientiousness -0,683** Self-efficacy -0,099 COFC -0,089 Instrumentality -0,096 Academic norms -0,141* Scheduling autonomy -0,101 Method autonomy -0,085 R2 0,024 0,639 ΔR2 _0,024 _0,615 ΔF 1,370 (2,113) 19,942** (7,106) Overall F 1,370 (2,113) 24,674** (9,106)

Like in the working context, Gender and Age entered as the first step of the model, yet the results were not significant (F(2,113) = 1,370; p = 0,258). After controlling for Gender and Age, the second part of the model was significant with F(7,106) = 24,674, and p = 0,000. The two variables with lower p values than 0,05 were Conscientiousness (p = 0,000; Beta = -0,683; t = -10,018) and Academic norms (p = 0,021; Beta = -0,141; t = -2,350).

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The procrastination subscales were tested separately with the multiple regression analysis here as well. The significant correlations between general procrastination and the independent variables in the academic context were Conscientiousness (r = -0,727; p = 0,000), Self-efficacy (r = -0,222; p = 0,017), Consideration of future consequences (r = -0,397; p = 0,000), and Instrumentality (r = -0,259; p = 0,005). The results of the regression analysis can be found in Table 8.

Table 8 Academic context – Regression analysis with separate subscales

Variables General procrastination

Procrastination in the academic context

Step 1 Step 2 Step 1 Step 2

Gender -0,063 -0,050 -0,112 -0,103 Age -0,147 -0,025 0,075 0,063 Conscientiousness -0,642** -0,668** Self-efficacy -0,122 -0,045 COFC -0,096 -0,064 Instrumentality -0,112 -0,056 Academic norms -0,098 -0,202* Scheduling autonomy -0,092 0,102 Method autonomy -0,074 -0,095 R2 0,026 0,585 0,018 0,567 ΔR2 _0,026 _0,559 _0,018 _0,549 ΔF 1,513 (2,113) 16,618** (7,106) 1,056 (2,113) 15,399** (7,106) Overall F 1,513 (2,113) 20,414** (9,106) 1,056 (2,113) 19,158** (9,106)

The multiple regression analysis revealed that Age and Gender were not related (F(2,113) = 1,513; p = 0,225) to general procrastination, and even though the second step was significant with F(7,106)=20,414, and p=0,000, and explained around 58,5% of the variance in general procrastination, the only predictor with a p value lower than 0,05 was again Conscientiousness (p = 0,000; Beta = -0,642; t = -8,910).

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On the other hand, the multiple regression analysis with procrastination in the academic context as the dependent variable showed significant results for Conscientiousness (p = 0,000; Beta = -0,668; t = -9,074) and Academic norms (p = 0,002; Beta = -0,202; t = -3,112). These findings suggest that participants’ general procrastination habits couldn’t be explained by anything else besides Conscientiousness, yet the social norms were significant predictors when it came to the contextual specific, task related procrastination.

The Hypothesises can be tested according to the results of the multiple regression analysis in both context.

Hypothesis 1a - Perceptions of instrumentality are negatively related to procrastination across domains - is rejected, as instrumentality did not show any significant relationship with procrastination.

Hypothesis 2a - Consideration of future consequences is negatively related to procrastination across domains – is partially accepted, as it was related to procrastination in the working context. However, it must be noted that it mediated the effect of Conscientiousness.

Hypothesis 3a - Social norms are negatively related to procrastination across domains – is partially accepted, as it was related to both types of contextual procrastination. However, it was not related to general procrastination.

Hypothesis 4a - Perceptions of autonomy are negatively related to procrastination across domains – is rejected, as scheduling autonomy and method autonomy were not related to procrastination.

Finally, basic assumption of the study was that participants in different contexts would also report different levels of procrastination because of the contextual influences. The working students reported their procrastination habits in both contexts, and their answers suggest that they perceived the two settings differently. In order to test this, a one-way ANOVA with repeated measures was used.

Table 9 One-way ANOVA with repeated measures results - Procrastination

Source Sum of squares DF Mean square F Eta2 _p

Context 6,340 1 6,340 7,248 0,153 0,010

Note: N=41

According to the results, the context had a significant effect on the procrastination of participants, with Wilks’ Lambda = 0.85, F(1,40) = 7,248, p = 0,010, multivariate partial

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squared = 0,153. As the latter value is over 0,14, it can be concluded that the effect size was high. The means, standard deviations and the confidence intervals can be found in Table 10.

Table 10 One-way ANOVA with repeated measures estimated marginal means

Context Mean Std. Error 95% CI

Lower Bound Upper Bound

Academic 4,411 0,180 4,048 4,773

Work 3,854 0,163 3,525 4,184

The same one-way repeated measures analysis was conducted in order to compare the scores of the perceived norms in the two contexts.

Table 11 One-way ANOVA with repeated measures results - Norms

Source Sum of squares DF Mean square F Eta2 _p

Context 48,050 1 48,050 32,761 0,457 0,000

Note: N=40

Working students reported significantly stronger norms in the working context, and the results suggest that it did not happen by chance. Wilks’ Lambda was 0,543, with F(1,39) = 32,761, p = 0,000 and Eta2 =0,457. Thus, it can be argued that the effect of the context on the perceptions of norms was high and significant.

Table 12 One-way ANOVA with repeated measures estimated marginal means

Context Mean Std. Error 95% CI

Lower Bound Upper Bound

Academic 2,838 0,194 2,445 3,230

Work 4,388 0,218 3,946 4,829

Hypothesis 3b - In general, individuals experience stronger social norms in work settings than in academic settings – is accepted.

As a conclusion of the results, it can be claimed that Consideration of future consequences showed significant relationship with one aspect of procrastination, yet it turned out that it only mediated the effect of Conscientiousness. Even though Social norms were unrelated to general procrastination, it showed significant relationship with both type of contextual procrastination. Moreover, the one-way repeated measures analysis revealed that the differences in working

Procrastination in academic and work settings