The Conceptualisation and Measurement of Pacing Styles


  • The authors would like to thank Flora Beeftink for her contribution to the scale development and data collection, and Rebecca Cosco for her assistance with the qualitative portion of this research.


Pacing style reflects how individuals distribute their effort over time in working toward deadlines. As a new construct introduced in 2002, the notion of pacing style has intuitive appeal, but has been under-researched, in part, due to a measurement need. Therefore, the purpose of this research was to improve the conceptualisation of pacing style and to develop and validate a new scale-based measure. The result was the nine-item Pacing Action Categories of Effort Distribution (PACED), consisting of deadline (complete work in a short time period just before the due date), steady (spread task activities evenly over time), and U-shaped (invest most of the effort at the start and finish of a task, with a break in between) action styles. Across eight independent samples of students, faculty, and organisational employees, we examined the dimensionality, internal consistency, stability (temporal and situational), and validity (construct, convergent, discriminant, predictive) of PACED. Results support the use of PACED as a reliable and valid measure, and we discuss several research avenues that would benefit from incorporating the concept of pacing style.


Time is an inescapable, fundamental, and inherent part of everyday life that has often been unacknowledged in research. Therefore, there have been many calls over the years to place temporality at the center of construct conceptualisation and measurement rather than the periphery (e.g. Ancona, Goodman, Lawrence, & Tushman, 2001; Bluedorn, 2002; Mitchell & James, 2001; Zaheer, Albert, & Zaheer, 1999). In response, temporal research is gaining momentum at the individual (e.g. Jansen & Kristof-Brown, 2005), group (e.g. Gevers, Van Eerde, & Rutte, 2009b), and organisational (e.g. Crossan, Cunha, Vera, & Cunha, 2005) levels.

A key premise underlying multilevel conceptualisations of temporality is that individuals perceive time in different ways (e.g. Bluedorn & Jaussi, 2007; Mohammed, Hamilton, & Lim, 2009). Indeed, temporal characteristics such as time urgency (feeling chronically hurried), polychronicity (preference to engage in more than one task concurrently), and time perspective (past, present, or future temporal bias) have been recognised as fundamental parameters of individual differences (Bluedorn & Denhardt, 1988). However, these constructs do not capture how individuals pace themselves before a deadline, which is of importance given the ubiquity of time limits in everyday life and the work environment.

Deadlines have been identified as an important motivational factor that strongly influences the patterns and intensity of goal directed behavior for both individuals (e.g. Fried & Slowik, 2004; Mitchell, Lee, Lee, & Harman, 2004; Moon & Illingworth, 2005; Smith, Dolis, & Tolli, 2009, Steel & König, 2006; Van Eerde, 2000) and collectives (e.g. Gersick, 1988, 1989; Seers & Woodruff, 1997; Waller, Zellmer-Bruhn, & Giambatista, 2002). Research on the dynamic nature of task behavior has focused on the phenomenon of procrastination to show that deadlines sometimes keep individuals from engaging in task behavior because of anticipated negative consequences (Steel, 2007; Van Eerde, 2000). However, there is more variety in how people work toward deadlines (Blount & Janicik, 2002; Claessens, 2004; Gevers, Claessens, Van Eerde, & Rutte, 2009a; Lim & Murnighan, 1994). For example, while some individuals wait until the deadline is imminent to begin and work until time runs out (deadline action style), others begin tasks soon after they are assigned and finish long before the due date (early action style). Representing additional styles, some individuals tend to spread their effort out evenly over the available time (steady action style), while others adopt a hybrid approach by combining elements of various styles (U-shaped action style, in which more effort is expended at the beginning and end of task execution with a break in between). Whereas the literature on temporal individual differences has tended to ignore pacing behavior before a deadline, the research on dynamic goal directed behavior has de-emphasised individual differences other than procrastination. Planning research (e.g. Claessens, Van Eerde, Rutte, & Roe, 2004; Macan, 1994; Schriber & Gutek, 1987; Tripoli, 1998) has also fallen short in addressing task pacing, as it tends to focus on the extent to which people plan their work, not on when the work is actually done (i.e. early, late, both, or steady). Given the identified gap in the literature, we focus on the conceptualisation and measurement of a construct called pacing style, which describes the distribution of effort over time in working toward deadlines.

According to Bluedorn (2002), “What is a more fundamental process strategy than the choice of the pattern for one's activities?” (p. 48). Indeed, the way individuals pace their time in meeting deadlines is central to their daily experience as it can significantly affect lifestyle decisions and may seriously impact a variety of work-related behavior and outcomes. Pacing style has been shown to influence employees' behavior (e.g. planning), feelings (e.g. control of time, occupational self-efficacy), and outcomes at work (e.g. job performance, working overtime) (Claessens, 2004). The adoption of a specific pacing style may give rise to positive or negative experiences at work (e.g. experiences of task absorption or stress) that may subsequently affect employee health and well-being. Contextually, the match between pacing style and job requirements may have implications for person–job fit and worker well-being. For example, in contrast to a deadline action pacing style, employees with early or steady action styles may not be as comfortable in positions characterised by short and fluctuating due dates such as the newspaper industry. The importance of understanding pacing styles is also evident at the team level when members need to coordinate with each other on interdependent tasks. Different pacing styles in a team create a form of temporal diversity that can be advantageous if properly coordinated or disadvantageous if unproductive conflict (e.g. Mohammed & Nadkarni, 2011) or a dysfunctional temporal pattern (e.g. Gevers, Rutte, & Van Eerde, 2006) ensues. Indeed, pacing style differences may be to blame for numerous problems in teams, but remain unaddressed because individuals rarely verbalise their own style (Mohammed & Harrison, 2007).

Based on a small, but growing body of existing research, pacing style appears to be a meaningful and potentially important construct that warrants further attention (e.g. Gevers et al., 2006; Gevers et al., 2009a; Mohammed & Nadkarni, 2011). However, for its promise to be fully realised, systematic attention must be devoted to conceptualisation and measurement. Existing measures of pacing style are limited to one item (e.g. Gevers et al., 2006; Claessens, 2004), which is psychometrically undesirable (Nunnally & Bernstein, 1994; Spector, 1992; Zuckerman, Hodgins, Zuckerman, & Rosenthal, 1993). Moreover, inconsistency and debate exists regarding the dimensionality and stability of the pacing style concept. Finally, the concept of pacing style has not been fully situated within a nomological network of relevant constructs, so little is known about how pacing styles relate to other individual differences and temporal constructs. Addressing these weaknesses, the purpose of this research is to improve the conceptualisation and measurement of pacing style. The dimensionality, stability, and construct validity of the pacing style construct are systematically examined. Thereafter, we introduce a scale-based measure of pacing style and provide validation evidence over a series of four studies with eight samples in two countries. We conclude with implications for the use of the pacing style scale in temporal research as well as the broader organisation science domain.

The Conceptualisation of Pacing Style

Qualitative Work

Given the relative novelty of pacing style and the suitability of qualitative research for constructs in a nascent stage of development (Edmondson & McManus, 2007), we conducted 25 semi-structured interviews asking participants to describe the way that they usually pace their work in relation to deadlines, the reasons underlying their pacing style, the intentionality of their pacing style, the stability of their style over time and across tasks, and the comparison between their ideal and actual pacing style. The sample included 11 undergraduate students, six graduate students, and eight employees. Eleven males and fourteen females were interviewed, and the average age was 27 (range 19–55). Throughout this section, we discuss the insights gleaned from this qualitative work, which provided inductive grounding for the pacing style construct.

The Concept of Pacing Style

Blount and Janicik (2002) introduced the notion of pacing preferences to refer to the anticipated momentum and flow regarding how events will unfold over time. Specifically, two elements were proposed to comprise a person's pacing preference: (a) the amount of time perceived as available to complete a task, and (b) how an activity is spaced out over that time (Blount & Janicik, 2002). Whereas Blount and Janicik (2002) emphasised preferences, Gevers and colleagues (2006) noted that what is preferred may not match what is done. For example, while some individuals may prefer to start and finish their work way before the due date, they may end up working very close to the deadline. Thus, Gevers and colleagues (2006) coined the term “pacing style” to capture how time is actually allocated in task execution. Of the 25 interviewees described above, 16 indicated that they wanted to pace their work differently from what they actually do, further supporting a distinction between preferences and behavior. Consistent with the conceptualisation of Gevers and colleagues (2006), we define pacing style as behavioral tendencies regarding the distribution of effort over time in working toward deadlines.

The Dimensionality of Pacing Style

Blount and Janicik (2002) referenced a variety of permutations that may capture the pacing of work over time, including linear (individuals work harder as they get closer to the deadline) and curvilinear (work rates are constant, but increase significantly after the midpoint transition) distributions. However, Gevers and colleagues (2006) focused on three modal styles: early action (start task activities immediately to make sure the work is finished long before the deadline), deadline action (complete the bulk of the work in a relatively short period of time just before the deadline), and steady action (engage in a constant work pace and spread out task activities evenly over time). In addition to these three, Claessens (2004) added two more pacing styles, including U-shaped (demonstrate more effort in task execution at the start as well as at the end of the allotted time with a break in between) and inverted U-shaped (complete the bulk of the work half-way through the allotted time).

Of the 25 interviews conducted in the qualitative study described above, the distribution of pacing styles described was as follows: three early action, two steady action, 16 deadline action, and four U-shaped. No participant described an inverted U-shaped style. Consistent with these results, previous research has demonstrated that individuals rarely describe themselves as midterm action workers who exhibit an inverted U-shaped pattern (Claessens, 2004; Gevers et al., 2009a). Therefore, this style was not investigated in the present research.

Other qualitative work showed a strong tendency among Dutch architects toward the U-shaped pacing style (Beeftink, 2008). Eighteen out of 25 architects selected this style when interviewed about their usual action pattern in working up to a deadline. In explaining their reason for selecting the U-shaped pattern, most architects (n = 15) referred to the creative process requiring periods of high task engagement as well as task disengagement or an incubation period. For example, one architect stated, “It works rather well … to free some continuous time [at the start], so you can thoroughly work your way into it, and thus become aware of the complexities and pitfalls. Well, then you let the material sink in for a while” (Beeftink, 2008, p. 41). In summary, the early, deadline, steady, and U-shaped pacing styles seem to capture the patterns of effort distribution that most individuals report in qualitative research, with the U-shaped style having particular importance for creative professionals.

The Stability of Pacing Style

Disagreement concerning the stability of pacing style has surfaced in the extant research. Some authors have conceptualised pacing style as a relatively stable part of a person's personality (e.g. Gevers et al., 2006; Gevers et al., 2009a), while others have viewed the construct as less stable than dispositions, but more stable than transitory states (Mohammed & Harrison, 2007). There are two types of stability that are important to investigate: stability over time (e.g. test–retest reliability) and stability over situations or tasks. Out of 25 respondents interviewed in the first qualitative study described above, 11 (44%) reported that their pacing style did not change over time, and 10 (40%) stated that their style was consistent across tasks. However, other interviewees reported that they used different pacing styles for different types of task (60%). Thus, the temporal and situational stability of pacing style remains a research need which the current paper aims to inform.

Differentiating Pacing Style from Other Constructs

Pacing style captures a unique feature of time-based tendencies that is not measured by other temporal individual differences or variables. The constructs most conceptually similar to pacing style (the deadline action style in particular) are time urgency and procrastination. Time urgent individuals are preoccupied with the passage of time and deadlines (e.g. Landy, Rastegary, Thayer, & Colvin, 1991). There are two aspects that differentiate pacing style from time urgency. First, whereas time urgency involves ardent attention to when work is due, pacing style captures how temporal resources are allocated toward task completion (Mohammed & Nadkarni, 2011). Second, whereas individuals high in urgency view time as their enemy and a constant source of time pressure (Price, 1982), individuals with a deadline action style may be energised and “in their element” as the deadline approaches (Mohammed & Harrison, 2007). In the qualitative study described earlier, several interviewees who described themselves as having a deadline action style reported positive aspects of time pressure. For example, one participant commented, “I work better. It motivates me. I am more efficient overall and get more things done when I am under pressure.”

According to Steel (2007), “To procrastinate is to voluntarily delay an intended course of action despite expecting to be worse off for the delay” (p. 66). As such, procrastination has a predominantly negative connotation, and a large segment of the literature has been devoted to the undesirable and even dangerous consequences resulting from procrastinating (e.g. Holland, 2001; Kasper, 2004; Wesley, 1994). In contrast, the conceptualisation of deadline action style adopts a more neutral tone in that positive or negative outcomes can result, depending on person–job fit, whether unforeseen events arise, and other similar factors. Whereas procrastination is viewed as an irrational and dysfunctional delay because individuals expect negative outcomes to follow (Steel, 2007, 2010), deadline action individuals may, in fact, rationally and intentionally delay starting tasks until close to the deadline because they expect favorable benefits. Thus, although both constructs represent delay, not all delay is procrastination. For procrastinators, deadlines are threats, but for deadline action pacing style individuals, deadlines may represent challenges.1 For example, one deadline action style interviewee in the qualitative study stated, “I realise that my productivity and motivation increases as the task approaches, so that's why I want to leave the majority of the work for the end.” While the vast majority of procrastinators wish to reduce this behavior (Steel, 2007), some deadline action individuals may view switching styles as undesirable. As an example, one interviewee relayed: “I am very happy with it [deadline action style]. It gives me enough pressure to do things, but not too much stress.” Therefore, deadline pacing style is conceptualised as a broader construct that encompasses procrastination (i.e. delay resulting from threat), but also allows for the inclusion of positive benefits of working in close proximity to the deadline (i.e. delay resulting from challenge).

In addition to the conceptual distinctions between procrastination and the deadline action style, it is important to note that the added value of the pacing style construct lies in its more comprehensive and balanced approach to assessing how people work toward deadlines. While the emphasis has been on deadline work and procrastination, there are other styles that individuals adopt in working toward deadlines that have been virtually ignored in the literature (e.g., steady, U-shaped).

The Measurement of Pacing Style

Existing measures of pacing styles have consisted of one-item continuous (Gevers et al., 2006) or categorical (Claessens, 2004) graphical representations of different pacing styles. Participants were asked to select the graph that best captured the way they paced their work when performing tasks. In addition to the pictorial representation, a written description was provided below each graph, and favorable construct validity evidence exists (see Gevers et al., 2006 and Gevers et al., 2009a). Although the graphs are efficient and face-valid (Shamir & Kark, 2004), one-item measures are regarded as less reliable due to random measurement error and lack scope and precision in being able to discriminate between fine degrees of an attribute (e.g. Nunnally & Bernstein, 1994; Spector, 1992; Zuckerman et al., 1993).

Having to choose a single style along a single dimension imposes artificial boundaries and disallows a balanced emphasis on all three types of pacing style. These concerns prompted the current efforts toward the development of an alternative, interval-level measure that treats the three types of pacing style as continuous in nature to better capture the complexity of the construct. The new scale allows respondents to rate their behavioral tendency on each of three styles, offering a more comprehensive assessment than a single item measure (McIver & Carmines, 1981). Although people are likely to have a dominant style, they may in fact use multiple styles, each to a different extent. For example, an individual may be high on the deadline style, moderate on the U-shaped style, and low on the steady style. Such a person would typically allocate effort close to the deadline and may occasionally prepare for deadline work in early preparatory activities, but is unlikely to spread activities across the entire time available.

Over a series of four studies, we used eight samples of students, faculty, and organisational members in two countries to develop a new scale-based pacing style measure (i.e. Pacing Action Categories of Effort Distribution; PACED) and assess its construct validity.

Study 1: Item Generation and Reduction


Based on the pacing styles that respondents identified with the most in previous studies (Beeftink, van Eerde, & Rutte, 2007; Claessens, 2004; Gevers et al., 2006), we selected four styles to pursue further: early action, deadline action, steady action, and U-shaped styles. After several iterations of generating, comparing, and revising items, an initial pool of 24 items (i.e. six items for each of the four styles) was selected that sampled the intended content domain. Example items are: “I begin working on tasks early to avoid having to rush at the end” (early action style); “I do most of the work on tasks in a short time before the deadline” (deadline action style); “I work steadily on tasks, spreading my work out evenly over time (e.g. 3 hours per week until the deadline)” (steady action style); and “The effort I invest in projects is high at the start, low half-way through, and high again at the end” (U-shaped style). The response format was a 5-point Likert scale, which ranged from 1 (strongly disagree) to 5 (strongly agree).

Item reduction occurred in two steps, involving three independent samples from two different countries (see Samples 1–3 in Text Box 1). First, the initial pool of 24 items was administered to samples in the Netherlands (Sample 1) and the United States (Sample 2). In both samples, an exploratory factor analysis (EFA, principal axis factoring) with oblique rotation (Oblimin with Kaizer Normalisation) was conducted. Following Hinkin (1998), items with factor loadings of .40 or greater on the appropriate factor with no major cross loadings were judged as representative of the construct under examination. Based on scree plots and pattern matrices in the EFAs, reliability analyses, and correlations between different dimensions, 16 of the most representative items were selected. The 16-item scale was then administered in a third independent sample (Sample 3) in the United States. Again, EFA and reliability analyses were conducted as a basis for further item reduction.

Text Box 1. Study Samples

Sample 1 consisted of 61 industrial engineering master's students enrolled in a technology university in the Netherlands. The majority of the respondents were Dutch (70.5%) and male (75%). The average age was 23.5 (SD = 1.52). A paper and pencil questionnaire, which included the 24 pacing style items and demographic information, was administered in English during a master's course lecture. Although participation was voluntary, all students agreed to fill out the questionnaire.

Sample 2 consisted of 59 upper-level psychology students attending a large university in the mid-Atlantic region of the United States. The majority of respondents were Caucasian (92.9%), female (61%), and seniors (67.8%). The average age was 21.31 (SD = 1.53). Students completed the 24 pacing style items and demographic information in a paper and pencil format for extra credit.

Sample 3 consisted of 110 undergraduate students at a large university in the mid-Atlantic region of the United States. Respondents were predominantly Caucasian (85%), female (82%), and first- and second-year students (81%). The average age was 19.39 (SD = 1.95). Students completed 16 pacing style items and demographic information online and received course credit in return for their participation.

Sample 4 consisted of 270 undergraduate students from a large university in the mid-Atlantic region of the United States who voluntarily participated and received extra credit for their assistance. Most of the participants were self-identified Caucasians (80.1%), female (67.4%), and first- (53%) or second- (27%) year students. The mean student age was 19.37 (SD = 2.14). Participants completed a web-based survey assessing the PACED items as well as demographics.

Sample 5 comprised 226 undergraduates from a large university in the mid-Atlantic region of the United States. Participants were self-identified Caucasians (93%), female (59.8%), and freshmen (44.2%) and sophomores (35.3%). The mean student age was 19.14 (SD = 1.20). Students completed an online questionnaire for class credit which included PACED and demographics.

Sample 6 included 389 American psychology students who completed an online questionnaire for class credit, including the PACED items and demographics. The majority of the respondents were self-identified Caucasians (84%), female (62.7%), and freshmen (42.6%) or sophomores (30.2%). Ages ranged from 18 to 29 years (M = 19.20; SD = 1.35).

Sample 7 consisted of 128 faculty who volunteered to complete an online questionnaire including PACED items and demographics. The sample contained assistant (43%), associate (30.8%), and full (21.5%) professors. The majority were self-identified Caucasians (90%) and females (52.9%). The average age was 47.46 years (SD = 10.6), and the mean tenure as a faculty member was 13.52 years (SD = 10.98).

Sample 8 included 93 participants from two international organisations operating in the Netherlands, one in the electronics business and the other in business consultancy. Participants were mostly from departments involved in information technology and were predominantly male (85%). Respondents had a mean age of 35.68 years (SD = 8.48) and were employed in diverse occupations (e.g. project managers, consultants, team leaders, engineers, architects, and analysts). Participants voluntarily completed PACED either online or via a paper and pencil survey.


Item Reduction

In Sample 1, the EFA suggested a three-factor solution. The steady action and the U-shaped pacing styles were unambiguously identified as separate factors. The early and deadline action styles were opposites of a single dimension and loaded onto a separate third factor, as is also indicated by the scree plot and a very high correlation between the original two scales (r = −.80). Together, the three factors explained 59 per cent of the total item variance. In Sample 2, a similar three-factor structure emerged, accounting for 48 per cent of the total item variance. Again, early and deadline action styles loaded onto one factor and the original scales correlated strongly (r = −.86). Based on the pattern of cross loadings in the EFAs and alphas from both samples, the number of items was reduced to 16 (four items per style).

Similar to the 24-item scale in Samples 1 and 2, the EFA on the 16-item scale in Sample 3 again suggested a three-factor solution consisting of steady action, U-shaped, and early/deadline dimensions. The three factors explained 54 per cent of the total item variance in the EFA. Although the early and deadline dimensions were not as highly correlated as in Samples 1 and 2, the association was still substantial (r = −.56). Item reduction was again based on the pattern of cross loadings in the EFA, as well as item content (e.g. eliminating similarly worded items). Informed by accumulated evidence across the three samples of a lack of simple structure (high cross loadings) for most of the early items, only deadline action items were selected for the deadline action pacing style dimension. Following item reductions, nine items were retained to measure three pacing style dimensions (deadline, steady, and U-shaped), each with three items. The factor loadings for the final nine items are presented in Table 1. In general, the subscales of the new pacing style scale showed strong psychometric properties, including high factor loadings (with low cross loadings) and adequate internal consistency.

Table 1. Factor Loadings and Reliabilities across All Samples
ItemsSample 1Sample 2Sample 3Sample 4Sample 5Sample 6Sample 7Sample 8
Deadline action pacing style (α)(.83)(.83)(.90)(.88)(.90)(.87)(.88)(.83)
I do not get much done on projects until the due date is close..78.77.871.061.03.961.03.64
I generally do not work until there is time pressure from an approaching deadline..
I do most of the work on tasks in a short time before the deadline..
Steady action pacing style (α)(.74)(.82)(.80)(.79)(.81)(.79)(.79)(.78)
I work steadily on tasks, spreading my work out evenly over time (e.g. 3 hours per week until the deadline)..
I pace myself to work on projects a little bit every day or every week instead of doing several hours of work all at once..
I work in a slow, but steady, manner to complete tasks..
U-shaped action pacing style (α)(.83)(.73)(.77)(.78)(.83)(.75)(.84)(.86)
I put in more effort at the beginning of tasks as well as right before the deadline, but am less active during the middle of the work cycle..
I invest most of my effort toward the beginning and end of projects..
The effort I put into projects is high at the start, low half-way through, and high again at the end..
χ2(24)   39.56*39.32*39.94*42.76*37.71*
SRMR   .
NNFI   .
CFI   .

Descriptives and Intercorrelations

Across the three samples, pacing style items were not subject to range restriction, and skew and kurtosis values suggested that items were normally distributed. Table 2 presents the descriptives and intercorrelations of the nine-item pacing style scale for Samples 1, 2, and 3. Across samples, deadline action and U-shaped styles had higher means than the steady action style among students. The steady action pacing style was negatively related to the deadline action pacing style (r = −.49, p < .01; r = −.44, p < .01; r = −.28, p < .01, respectively) in all three samples, suggesting the tendency of steady workers to start early to avoid working under the pressure of deadlines.

Table 2. Descriptive Statistics and Intercorrelations for the Nine-Item Pacing Style Scale in Samples 1–3
  1. Note: Alphas are on the diagonal; ** p < .01; * p < .05.
Sample 1 (N = 61)     
1. Deadline pacing style2.90.94(.83)  
2. Steady pacing style2.50.78−.49**(.74) 
3. U-shaped pacing style2.95.82−.17.18(.83)
Sample 2 (N = 59)     
1. Deadline pacing style3.381.03(.83)  
2. Steady pacing style2.47.77−.44**(.82) 
3. U-shaped pacing style2.94.83−.24.15(.73)
Sample 3 (N = 110)     
1. Deadline pacing style3.091.04(.90)  
2. Steady pacing style2.99.81−.28**(.80) 
3. U-shaped pacing style3.*(.77)

Study 2: Confirmatory Factor Analyses and Test–Retest Reliability

The item reduction efforts from the three samples in Study 1 resulted in a nine-item scale, which we termed the Pacing Action Categories of Effort Distribution (PACED) scale, representing three pacing style dimensions: deadline action, steady action, and U-shaped. The primary purpose of Study 2 was to confirm the three-factor structure of PACED that emerged from the EFAs with confirmatory factor analyses (CFAs) and to further evaluate its internal consistency reliability and test–retest reliability.


Confirmatory Factor Analyses

CFAs and internal consistency reliability analyses were examined in five independent samples (see Samples 4–8 in Text Box 1). CFAs were performed with Lisrel 8.54 (Jöreskog & Sörbom, 1996). The proposed three-factor structure of PACED was evaluated with multiple indices (Kline, 1998), including the χ2 statistic (including degrees of freedom and significance level), the Root-Mean-Square Error of Approximation (RMSEA; Steiger, 1990), the Comparative Fit Index (CFI; Bentler & Bonett, 1980), the Non-Normed Fit Index (NNFI; Bentler & Bonett, 1980), and the standardised root-mean square residual (SRMR; Hu & Bentler, 1999). Values of CFI approaching .95 and values no higher than .08 for RMSEA and SRMR indicate good model fit (Hu & Bentler, 1999). For the NNFI, the conventional indicator of good fit is close to or above .90 (Hu & Bentler, 1999). After testing the hypothesised three-factor model, we also tested two-factor and one-factor models, collapsing pacing style sub-scales in all combinations. The χ2 provides a statistical basis for comparing the relative fit of these nested models (Bollen, 1989). Finally, internal consistency reliabilities were calculated.

Test–Retest Reliability

Test–retest reliability was assessed with 59 upper-level psychology students from the mid-Atlantic region of the United States, of which most (N = 51) had also participated in Sample 2 three weeks earlier, providing us with the opportunity to examine a three-week test–retest reliability. These respondents completed PACED in a paper and pencil format for extra credit. The majority of respondents were Caucasian (92.9%), female (61%), and seniors (67.8%). The average age was 21.31 (SD = 1.54).


The results from the CFAs and the alphas are presented in Table 1. Across all five samples, the fit indices supported the three-factor structure of the nine-item PACED, meeting the aforementioned cutoff criteria. Across all samples, as indicated by significant differences in the Δχ2-statistic, the collapsed two-factor and single-factor models provided a significantly worse fit to the data than the hypothesised three-factor model. Moreover, the reliability coefficients indicated that each of the three dimensions of PACED possessed adequate internal consistency in all samples (see Table 1).

Table 3 presents the distributions, intercorrelations, and internal consistency reliabilities for the test–retest analysis. As in prior samples, there was a significant negative relationship between the deadline pacing style and the steady pacing style at Time 2 (r = −.49; p < .01) as well as at Time 1 reported earlier (r = −.44; p < .01). Three-week test–retest reliability was strong for the deadline action pacing style (r = .77, p < .01), but weaker for the steady action pacing style (r = .54, p < .01) and the U-shaped pacing style (r = .43, p < .01).

Table 3. Descriptive Statistics and Correlations for the Test–Retest Analysis (N = 51)
  1. Note: For gender: 1 = male, 2 = female; alphas are on the diagonal; * p < .05; ** p < .01.
Time 1         
1. Deadline pacing style3.381.03(.83)      
2. Steady pacing style2.470.77−.44**(.82)     
3. U-shaped pacing style2.940.83−.24.15(.73)    
Time 2         
4. Deadline pacing style3.290.96.77**−.46**−.14(.82)   
5. Steady pacing style2.440.78−.42**.54**.02−.49**(.88)  
6. U-shaped pacing style2.860.91−.29*.40**.43**−.20.14(.85) 
7. Gender1.610.49.05−.14−.02.07−.23−.08 
8. Age21.311.54.14.01−.07.09−.10.13−.35**

Study 3: Convergent and Discriminant Validity

An important step in the validation process involves establishing a construct's nomological net (Hinkin, 1998). Therefore, the primary purpose of Study 3 was to demonstrate convergent and discriminant validity for PACED. We validated PACED against the existing graphical measure of pacing styles and a broad range of individual differences and attitudes.

We expected that the PACED subscales would be positively correlated with their graphical counterparts. In addition, given the motivation of steady workers to avoid deadline work, we expected the steady style subscale to relate positively to the graph representing early action and negatively to the graph representing deadline action. Relatedly, the deadline style subscale was expected to relate negatively to the steady graph.

The pacing style scale was not expected to be related to personal characteristics such as age, gender, or grade point average (GPA) based on previous research using the graphs (e.g. Gevers et al., 2006; Gevers et al., 2009a; Mohammed & Nadkarni, 2011).

An important part of PACED validation is to demonstrate that pacing style comprises content that is non-redundant with other temporal individual differences, including time urgency and time perspective. Whereas pacing style captures how time is allocated in task execution, time urgency involves a preoccupation with how quickly work is done (Landy et al., 1991) and time perspective involves the tendency to concentrate on past, present, or future time frames (Zimbardo & Boyd, 1999). In addition, the one-item pacing style graphical measure used in previous research has not shown significant correlations with time urgency or time perspective (Mohammed & Nadkarni, 2011). Thus, pacing styles were not expected to show significant correlations with time urgency or time perspective.

Polychronicity is another temporal individual difference that refers to the preference to engage in multiple tasks simultaneously (Bluedorn, Kalliath, Strube, & Martin, 1999). When working under the time pressure caused by an impending due date, deadline action style individuals may have to focus exclusively on the task at hand in order to meet the stringent time requirement. Hence, we expect polychronicity to be negatively associated with the deadline action style.

Concerning other potential correlates with respect to convergent validity, we assumed that both the steady action and the U-shaped styles reflect a deliberate and planful work approach, in which the former is motivated to avoid deadline work, while the latter engages in early task orientation and organisation in order to prepare for deadline work. Both styles are, therefore, expected to correlate positively with variables that tap into organisation and planning, such as conscientiousness (Digman, 1990), proactive personality (Bateman & Crant, 1993), rational decision style (systematic evaluation of choices and potential alternatives in decision making; Mohammed & Hamilton, 2009), preference for order (Webster & Kruglanski, 1994), preference for predictability (Webster & Kruglanski, 1994), time management behavior (Claessens, Van Eerde, Rutte, & Roe, 2010; Macan, 1994), perceived control of time (Macan, 1994), and priority focus (extent to which individuals regularly review priorities in their work; Tripoli, 1998). In contrast, the aforementioned constructs were expected to be negatively correlated with the deadline action pacing style.

Choosing to begin work close to the deadline offers no temporal safeguards if guesstimates regarding how much time it will take to complete the task are grossly underestimated or if external events hinder task completion (e.g. technical breakdowns, delays in obtaining needed resources). Therefore, the deadline action style was hypothesised to be positively associated with risk preference (Dulebohn, 2002). In contrast, U-shaped style reduces the risk of underestimating temporal demands by examining the task early, and the steady action style is best positioned to absorb risks associated with unanticipated delays and situational constraints. Consequently, risk preference was expected to be negatively correlated with U-shaped and steady action styles.

It is likely that deadline action style individuals will exhibit a more positive outlook on deadline work, as shown by positive correlations with deadline optimism (generalised expectancies for positive versus negative outcomes when working toward a deadline) and deadline challenge orientation (positive feelings towards and effectiveness in dealing with time pressure situations; Lee & McGrath, 1995). In contrast, a steady action pacing style is expected to relate negatively to deadline optimism and deadline challenge orientation, given the motivation to avoid deadline work. Although they do not avoid deadlines, the cautious approach to deadline work exhibited by starting early suggests that people with a U-shaped style are not as optimistic toward or challenged by the deadline compared to deadline style individuals. Therefore, it is expected that the U-shaped pacing style will be uncorrelated with deadline optimism and deadline challenge.

As discussed above, deadline pacing style is conceptualised as a broader construct than procrastination in that it allows for both positive and negative benefits of working in close proximity to be included. As such, the deadline action pacing style is expected to be positively related, but non-redundant with, procrastination. Although deadline action pacing style and procrastination both represent delay, the nature and origin of the delay may be different. For procrastinators a deadline embodies a threat, but the deadline pacing style incorporates both threat and challenge, representing both rational and irrational delay. Hence, the deadline pacing style and procrastination are expected to be positively related but to also show differential relationships with constructs representing a positive outlook on deadlines, such as deadline optimism and challenge orientation. The U-shaped style resembles the deadline action style in that work is done in bursts of activity and tasks are finished close to the deadline. However, because U-shaped style individuals also adopt a more planned approach by starting early to determine how long a task will take, the U-shaped action pacing style is expected to relate negatively to procrastination. Similarly, the steady action style is hypothesised to be negatively related to procrastination. Table 6 summarises the expected relationships with measured correlates.



Data on the discriminant and convergent validity constructs were obtained from Samples 1, 5, and 6 (see Text Box 1). In addition to PACED and demographics, participants in Sample 1 also responded to a graphical measure of pacing styles. Participants in Sample 5, in addition to PACED and demographics, reported their GPA and completed measures of time perspective, polychronicity, conscientiousness, rational decision style, preference for predictability, preference for order, risk preference, setting goals and priorities, and preference for organisation. Participants in Sample 6 provided data on time urgency, proactive personality, priority focus, deadline optimism, deadline challenge orientation, and procrastination in addition to PACED. Answers were provided on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5), unless otherwise indicated below.


Pacing style: We used PACED as developed in Study 1, in which deadline, steady, and U-shaped action pacing styles were each measured with three items. In addition, pacing style was assessed with a series of graphs utilised in previous research (e.g. Claessens, 2004; Gevers et al., 2009b). For each style, participants were asked to indicate on a 5-point response format how often they used that style when working on a task or project (1 = (almost) never to 5 = (almost) always).

Time urgency was measured with 10 items taken from the “task-related hurry” and “general hurry” subscales of Landy and colleagues' (1991) time urgency measure. An example item is: “I find myself hurrying to get to places even when there is plenty of time.” Internal consistency reliability was .69.

Time perspective was measured with a 12-item scale developed and validated by Shipp, Edwards, and Lambert (2009). Three dimensions of past, present, and future were measured with four items each. One example item representing future temporal focus was, “I think about what the future has in store.” Alpha levels for the three dimensions were .88 for past, .80 for present, and .84 for future temporal focus.

Polychronicity was measured via nine items, six of which were taken from Bluedorn and colleagues (1999) and three of which were taken from Hecht and Allen (2005). A sample item is: “I prefer to do one thing at a time” (reverse coded). Cronbach's alpha of the scale was .81.

Conscientiousness was assessed with a 10-item scale from the International Personality Item Pool (Goldberg, 1990). Respondents were asked to rate themselves on items such as “I am always prepared”, “I like order”, and “I pay attention to detail”. Cronbach's alpha was .82.

Proactive personality was measured with 10 items taken from Bateman and Crant (1993). Some example items are, “No matter what the odds, if I believe in something I will make it happen” and “I am always looking for better ways to do things.” Cronbach's alpha for the scale was .88.

Rational decision style, which is characterised by a thorough search for information and a systematic evaluation of all potential alternatives, was measured with six items from a scale developed and validated by Mohammed and Hamilton (2009). A sample item is: “I prefer to approach decision making deliberately and systematically.” The coefficient α-reliability estimate for the scale was .88.

Preference for predictability was a subscale of the Need for Cognitive Closure Scale (Kruglanski, Webster, & Klem, 1993) as presented by Webster and Kruglanski (1994). The subscale consists of eight items that tap into a person's desire for secure or stable knowledge (e.g. “I don't like to go into a situation without knowing what I can expect from it”). The internal consistency reliability (coefficient alpha) was .81.

Preference for order was another subscale of the Need for Closure measure, which assesses the extent to which individuals desire structure in their environment (e.g. “I think that having clear rules and order at work is essential for success”; Webster & Kruglanski, 1994). The 10-item subscale displayed adequate internal consistency reliability (alpha = .77).

Risk preference: Respondents' perception of their general willingness to take risks was assessed using four items developed by Dulebohn (2002). An example item is: “I am a daring person who generally takes risks.” The coefficient α-reliability estimate for the scale was .82.

Time management behavior was measured using two subscales of the multi-dimensional time management behavior scale developed by Macan, Shahani, Dipboye, and Philips (1990). Setting goals and priorities was assessed via 10 items (e.g. “I break complex, difficult projects down into smaller manageable tasks”). Preference for organisation was measured with eight items (e.g. “At the end of the workday I leave a clear, well-organised workspace”). Participants responded on a 5-point Likert-type scale from seldom true (1) to very often true (5). Cronbach's alpha was .81 for setting goals and priorities, and .80 for preference for organisation.

Priority focus: Six items were taken from Tripoli (1998) to measure the extent to which respondents regularly reviewed their priorities in determining their work activities (e.g. “In my work, most of the time I am very clear about what my priorities are”). Internal consistency reliability of the items was .75.

Deadline optimism: We adapted the Life Orientation Test (Scheier & Carver, 1985) to measure the extent to which respondents expected positive outcomes when working toward a deadline (e.g. “I am generally optimistic about finishing work on time”). Cronbach's alpha was .68.

Deadline challenge orientation: We adopted three items from Lee and McGrath's (1995) scale for deadline challenge and added seven new items to form a scale. Items such as “I use my time more effectively when I work under the pressure of a deadline” and “I rely on deadlines to help me get things done” reflect the extent to which working under the pressure of a deadline is experienced as a positive challenge. The items evidenced high internal consistency reliability (α = .84).

Procrastination was assessed with an eight-item scale designed to measure the behavioral and cognitive avoidance reactions that respondents engage in when confronted with a deadline (Van Eerde, 2003). An example item is: “I have another sweet/cigarette/cup of coffee instead of beginning the task.” Answers were provided on a 5-point scale ranging from (almost) never (1) to (nearly) always (5). Cronbach's alpha for the scale was .89.


Relating the PACED subscales to the pacing style graphs used in earlier research revealed sizable correlations in the expected direction. Specifically, the deadline pacing style subscale showed a strong positive association with the deadline graph (r = .69, p < .001), negative associations with the early (r = −.55, p < .001) and steady (r = −.32, p < .01) style graphs, and a non-significant association with the U-shaped graph (r = .19; p > .05). As expected, the steady style subscale had positive correlations with the steady (r = .47, p < .001) and early (r = .46, p < .001) graphs, but a negative correlation with the deadline style graph (r = −.45, p < .001) and a non-significant correlation with the U-shaped graph (r = .24; p > .05). The U-shaped pacing style subscale was positively related to the U-shaped style graph (r = .75, p < .001), but not significantly related to any of the other graphs.

Tables 4 and 5 present the means, standard deviations, and intercorrelations for Samples 5 and 6, respectively. As predicted, none of the pacing style dimensions were significantly correlated with gender, age, or GPA in either Samples 5 or 6. Also supporting the hypotheses, there were no significant relationships between pacing style dimensions and time urgency or past, present, or future time perspective dimensions. Concerning polychronicity, we did find evidence for the predicted negative relationship with the deadline pacing style (r = −.14, p < .05), and a non-significant relationship with steady (r = .09, p > .05) and U-shaped (r = .06, p > .05) styles.

Table 4. Descriptive Statistics and Correlations of Sample 5 (N = 226)
  1. Note: For gender: 1 = male, 2 = female; alphas are on the diagonal; * p < .05; ** p < .01.
 1. Deadline style3.371.03(.84)                
 2. Steady style2.670.80−.65**(.87)               
 3. U-shaped style2.940.85−.22**.17**(.76)              
 4. Gender1.600.49−.04−.06.11              
 5. Age19.141.20−.02.01−.06−.18**             
 6. GPA3.320.42−.06.05−.07.13−.12            
 7. Past focus3.760.69.09−.09.08.12−.05.02(.88)          
 8. Present focus3.640.57−.01.06.09−.01.02−.04.17*(.80)         
 9. Future focus3.790.61−.**−.01.08.58**.21**(.84)        
10. Polychronicity2.860.61−.14*.−.09.04(.81)       
11. Conscientiousness3.340.57−.37**.27**.13*.−.03(.82)      
12. Rational decision style3.460.52−.21**.24**.15*.02.02−.01.17*.12.31**.06.39**(.88)     
13. Preference for predictability3.000.60−.12.14*−.01−.03−.02.01−.02−.30**−.08−.17*.17*.21**(.81)    
14. Preference for order3.230.55−.22**.27**−.02.06−.01.09.02−.12.06−.12.60**.38**.55**(.77)   
15. Goal setting and prioritising3.230.60−.33**.37**.18**.02−.01.05.13*.22**.29**.04.42**.44**−.02.31**(.81)  
16. Preference for organisation3.410.69−.26**.24**.00.14*.02.08−.05.08.13−.15*.56**.19**.11.47**.27**(.80) 
17. Risk preference3.310.74.06−.14*.11−.03.03−.06.04.29**.10.16*−.06−.21**−.59**−.40**.06−.05(.83)
Table 5. Descriptive Statistics and Correlations between PACED and Convergent and Discriminant Validity Variables of Sample 6 (N = 389)
  1. Note: For gender: 1 = male, 2 = female; alphas are on the diagonal; * p < .05; ** p < .01.
 1. Deadline pacing style3.590.96(.87)             
 2. Steady pacing style2.520.81−.54**(.79)            
 3. U-shaped pacing style2.930.84−.24**.41**(.75)           
 4. Gender1.630.48.02−.03.14**           
 5. Age19.201.35−.03.03.01−.07          
 6. GPA3.220.46−.09−.01−.05.05−.03         
 7. Time urgency3.160.48−.−.02.03(.69)       
 8. Proactive personality3.460.55−.03.11*.20**.07−.05.01.18**(.88)      
 9. Priority focus3.350.59−.22**.19**.16**.03−.04.16**.07.31**(.75)     
10. Deadline optimism3.310.55.10*−.16**−.07−.09−.03.18**−.11*.10*.23**(.68)    
11. Challenge orientation3.320.63.45**−.25**−.03−.05−.**.02.33**(.84)   
12. Procrastination3.190.70.55**−.32**−.12*.09−.01−.10.03.05−.27**−.13*.32**(.89)  
13. Challenge-related stress3.500.78.15**.01.18**.22**−.02.30**.11*.29**.14*−.12*.06.31**(.87) 
14. Task absorption3.000.69−.21**.23**.22**−.08.09.35**.13.30**.20**−.02−.11*−.05.12*(.82)

As expected, conscientiousness and rational decision style were both negatively correlated with deadline (r = −.37, p < .01 and r = −.21, p < .01, respectively), but positively correlated with steady (r = .27, p < .01 and r = .24, p < .01) and U-shaped (r = .13, p < .05 and r = .15, p < .05) styles. Proactive personality was positively associated with the steady action style (r = .11, p < .05) and the U-shaped action style (r = .20, p < .01), but was not significantly correlated with the deadline action style (r = −.03, p > .05). Concerning preference for predictability and preference for order, the steady action style was positively correlated with both (r = .14, p < .05 and r = .27, p < .01, respectively), and the U-shaped style was not significantly correlated with either (r = −.01, p > .05 and r = −.02, p > .05, respectively). The deadline action style was negatively related to preference for order (r = −.22, p < .01), but showed no significant relationship with preference for predictability (r = −.12, p > .05). Risk preference was negatively associated with a steady action style (r = −.14, p < .01) but, interestingly, was not significantly associated with deadline (r = .06, p > .05) or U-shaped (r = .11, p > .05) action styles.

The goal setting and preference for organisation dimensions of time management were negatively related to the deadline action style (r = −.33, p < .01 and r = −.26, p < .01, respectively), but positively related to the steady (r = .37, p < .01 and r = .24, p < .01, respectively) and U-shaped (r = .18, p < .01 for setting goals) styles. Priority focus showed a negative relationship with the deadline (r = −.22, p < .01), but positive relationships with the steady (r = .19, p < .01) and U-shaped (r = .16, p < .01) action styles. Moreover, the deadline action style showed positive relationships with both deadline optimism (r = .10, p < .05) and deadline challenge orientation (r = .44, p < .01), while the steady action pacing style was negatively associated with both constructs (r = −.16, p < .01 and r = −.25, p < .01, respectively). As predicted, the U-shaped style was unrelated to deadline optimism (r = −.07, p > .05) and deadline challenge orientation (r = −.03, p > .05).

Finally, procrastination was positively related to the deadline action style (r = .55, p < .01), but negatively related to the steady (r = −.32, p < .01) and U-shaped (r = −.12, p < .05) styles. Confirmatory factor analyses supported the conceptual differentiation between the deadline action pacing style and procrastination. Specifically, a two-factor model with procrastination and deadline pacing style items each loading onto their respective factors showed superior fit over a one-factor model (Δ χ2 = 387.09; df = 1; p < .001; two-factor model: χ2 = 137.08; df = 42; p < .001; CFI = .96; NNFI = .94; RMSEA = .076; SRMR = .049; one-factor model: χ2 = 524.17; df = 43; p < .001; CFI = .82; NNFI = .77; RMSEA = .17; SRMR = .086). Moreover, it is worth noting that, besides being positively related to procrastination, the deadline action pacing style also related positively to deadline challenge orientation (r = .45, p < .01), thus, indeed, representing both threat and challenge. Interestingly, procrastination showed a weaker positive association with deadline challenge orientation than the deadline pacing style (r = .32 versus r = .45, respectively; Steiger's Z (386) = −2.97, p < .01). In addition, procrastination showed a negative association with deadline optimism (r = −.13, p < .05), whereas the deadline action style showed a positive association (r = .10, p < .05). Thus, although procrastinators report being challenged by the deadline, they do so to a lesser extent than deadline pacing style individuals. In addition, procrastinators evidenced a lack of optimism about their chances for success regarding meeting due dates, whereas deadline pacing style individuals were much more confident. These results support the differentiation between the two constructs.

Table 6 provides an overview of the predictions and results of PACED in relation to the correlates discussed. Overall, the results provide strong evidence of both convergent and discriminant validity of PACED.

Table 6. Convergent and Discriminant Validity Predictions and Results
CorrelateDeadline ActionSteady ActionU-shaped Action
  1. Note:  * p < .05; ** p < .01; ns = non-significant.
Pacing style graphs      
Early graph−.55**+.46**0ns
Deadline graph+.69**−.45**0ns
Steady graph−.32**+.47**0ns
U-shaped graph0ns0ns+.75**
Demographics/Personal characteristics     
Temporal individual differences      
Time urgency0ns0ns0ns
Time perspective      
Past focus0ns0ns0ns
Present focus0ns0ns0ns
Future focus0ns0ns0ns
Individual differences      
Proactive personalityNS+.11*+.20**
Rational decision style−.21**+.24**+.15*
Need for closure      
Preference for predictabilityNS+.15*+ns
Preference for order−.22**+.27**+ns
Risk preference+NS−.14*0ns
Other time-relevant concepts      
Time management behavior      
Setting goals and prioritising−.33**+.37**+.18**
Preference for organisation−.26**+.24**+ns
Priority focus−.22**+.19**+.16**
Deadline optimism+.10*−.16**0ns
Deadline challenge orientation+.45**−.25**0ns

Study 4: Criterion-Related Validity

In addition to convergent and discriminant validity, another important step in building a nomological net is establishing criterion-related validity, or identifying the extent to which a measure is demonstrably related to concrete criteria in the “real” world (Hinkin, 1998). We considered the relationship between PACED and two types of self-reported outcomes: behavioral and psychological.

In terms of behavioral outcomes, we examined the degree to which PACED predicts pacing behavior in a number of “everyday” events associated with strict deadlines. We explored the predictive validity of PACED by examining work tasks in both weak and strong situations. In line with the interactionist approach (Tett & Burnett, 2003), we acknowledge that task conditions may impose constraints on the expression of individual pacing styles. Strong situations (e.g. when strict procedures must be followed or when deadlines are very short) limit the possibilities for freedom of choice (e.g. Mischel, 1977) and tend to negate individual differences in response tendencies. In weaker conditions, though, we expect people to respond in line with their general response tendency regarding pacing style. Associations between the PACED and self-reported pacing behavior are therefore expected to be stronger in weak situations than in strong situations.

In terms of psychological outcomes, we expected that pacing style would be associated with two work experiences that are known to have important implications for employee health and well-being: challenge-related stress and task absorption. Challenge-related stress refers to the stress associated with “job demands or work circumstances that, although potentially stressful, have associated gains for individuals” (Boswell, Olson-Buchanan, & LePine, 2004, p. 166). Despite associated strains, recent research has shown that conditions such as time pressure and high workload can be associated with desirable work outcomes, including enhanced performance, creativity, loyalty, satisfaction, and fewer withdrawal behaviors (Boswell et al., 2004; LePine, Podsakoff, & LePine, 2005; Ohly & Fritz, 2010; Podsakoff, LePine, & LePine, 2007). Moreover, because the challenges associated with these stressors are viewed as opportunities to learn and achieve, they may be responded to by employees with a problem-solving rather than an avoidant approach (Pearsall, Ellis, & Stein, 2009). These findings point to the positive role of challenge stressors on employees' job experiences and give insight into why certain individuals would deliberately choose these working conditions. From the qualitative study described previously, several people with a deadline action pacing style actively solicited this positive type of time pressure because they felt it helped them be more efficient. Likewise, people with a U-shaped pacing style also expose themselves to the stress associated with deadline work, although they seem to attenuate potential strain through some early preparation. Steady action style individuals, in contrast, are typically motivated to avoid high workloads and time pressure, and are, therefore, less likely to experience challenge-related stress. Hence, we expect deadline action and U-shaped action styles to relate positively and the steady action style to relate negatively to challenge-related stress.

In addition to challenge-related stress, pacing styles may also be associated with work-related flow or task absorption. Task absorption refers to the state where one is “fully concentrated and happily engrossed in one's work, whereby time passes quickly and one has difficulties with detaching oneself from work” (Schaufeli & Bakker, 2004, p. 295). Task absorption has been identified as an important dimension of work engagement (Rothbard, 2001; Schaufeli, Bakker, & Salanova, 2006), which has been shown to positively affect employee well-being as well as in-role and extra-role performance (Bakker, Schaufeli, Leiter, & Taris, 2008). Absorption conveys an “intensity of concentration” that allows individuals to fully focus on a particular role or task and “to ignore other factors” (Rothbard, 2001, p. 656).

The ability to be fully focused when working under deadline conditions is likely to depend upon one's pacing style. The deadline action style forces an individual to concentrate on a single task, simply because there is no room for task switching. However, under the intense time pressure of the deadline action style, the looming due date may be distracting, causing a divided focus between the task and time and preventing total engagement with the work content. In addition, intense deadline work is emotionally exhausting (Teuchmann, Totterdell, & Parker, 1999), and, thereby, impairs cognitive functions (Meijman & Mulder, 1998), including the ability to fully concentrate and focus (Demerouti, Taris, & Bakker, 2007; Van der Linden, Keijsers, Eling, & Van Schaijk, 2005). In contrast, the early task engagement and preparation of the U-shaped style may better allow for an exclusive focus on task demands prior to the deadline. Task absorption may also be more likely with steady action style individuals, as their work pattern offers the greatest buffer against deadline stress and therefore lessens the probability of being distracted by the due date. In addition, the steady action style allows for a replenishing of energy reserves between episodes of concentrated work, which is facilitative of task absorption (Demerouti et al., 2007). Hence, task absorption is expected to relate positively to the steady and the U-shaped styles and negatively to the deadline action style.


Predictive validity was measured with Samples 6 (students) and 7 (faculty), which were discussed in Study 2. Besides PACED and variables discussed in previous phases, participants in Sample 6 answered questions on deadline stress and task absorption as well as responding to a set of questions concerning pacing behavior. Likewise, in addition to PACED and previously analyzed variables, faculty members in Sample 7 responded to several questions concerning pacing behavior in work-related tasks with strict deadlines.


Self-reported pacing behavior: Participants responded to a set of situations describing study- and work-related tasks with strict deadlines. In the student sample, the tasks involved writing a two-page paper, studying for a test, and preparing for a team meeting. Each task was framed as a weak as well as a strong situation, resulting in a total of six items. For example: “… you have two weeks to write a two-page paper with no other major assignments due” represented a weak situation, whereas “… you have two weeks to write a two-page paper as well as three other major exams” represented a strong situation. Respondents indicated how they would work on each task described using a categorical response format corresponding to the three pacing styles. For writing the paper, the steady response option was: “I work on the paper a little at a time between the assignment announcement and the due date.” The U-shaped response option was: “I plan what I will write soon after receiving the assignment, but do not complete the paper until close to the deadline.” There were three deadline response options that were collapsed to form a single category: “I start and complete the paper a week before the deadline”, “I start and complete the paper a day before the due date”, and “I miss the paper deadline and hand it in late.” For each response category, we dichotomised responses and calculated the mean across items, resulting in six variables indicating the extent to which respondents reported engaging in deadline, steady, and U-shaped pacing behaviors across the presented deadline situations.

In the faculty sample, the tasks involved preparing taxes, writing conference submissions (e.g. abstracts, papers), and making travel arrangements for academic conferences. Similar to the student pacing behavior measure described above, categorical response formats corresponded to the three pacing styles. However, no distinction was made between weak and strong situations in this sample.

The internal consistency reliability of the pacing behavior measures proved to be problematic in both samples. In the student sample, coefficient alphas based on the Kuder Richardson formula 20 were .63, .53, and .70 for steady, U-shaped, and deadline behaviors across weak and strong situations. In the faculty sample, internal consistencies were .50, .30, and .49 for steady, U-shaped, and deadline behavior, respectively. Given the low internal consistency reliabilities of the pacing behavior measures, these results should be interpreted with caution.

Challenge-related stress comprised six items asking respondents to indicate the extent to which they experienced stress from, for example, “time pressures I experience” and “the amount of time I spend working” (LePine, LePine, & Jackson, 2004). Answers were provided on a 5-point Likert-type scale ranging from produces no stress (1) to produces a great deal of stress (5). The scale displayed high internal consistency reliability (α = .87).

Task absorption was measured with five items from the Rothbard (2001) absorption scale (e.g. “When I am working, I often lose track of time”). Answers were provided on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5). The scale's internal consistency reliability alpha was .82.


Predicting Self-Reported Pacing Behavior across Situations

Table 8 presents the zero-order correlations of the PACED dimensions with the self-reported pacing behaviors. In the student sample, weak and strong situations yielded similar results. As expected, higher scores on deadline pacing style were associated with a higher percentage of deadline behavior (r = .25, p < .001 and r = 24, p < .001) and a lower percentage of steady behavior (r = −.32, p < .01 and r = −.30, p < .01) in weak and strong situations, respectively. Also in both weak and strong situations, students with high scores on the steady pacing style were more likely to report steady pacing behavior (r = .34, p < .001 and r = .37, p < .001, respectively) and less likely to opt for deadline behavior (r = −.29, p < .001 and r = −.35, p < .01, respectively). Surprisingly, students with high scores on the U-shaped pacing style did not report more U-shaped behavior, but instead, reported a higher percentage of steady (r = .13, p < .01 and r = .13, p < .01) and a lower percentage of deadline behavior (r = −.14, p < .01 and r = −.21, p < .01).

In the faculty sample, higher scores on the deadline pacing style were associated with a higher percentage of deadline pacing behavior (r = .37, p < .001) and a lower percentage of steady and U-shaped pacing behavior (r = −.24, p < .01 and r = −.23, p < .01, respectively). Higher scores on the steady action pacing style were not associated with a higher percentage of steady behavior (r = .16, ns), but instead with more U-shaped behavior (r = .23, p < .01) and less deadline behavior (r = −.29, p < .001). No significant effects were found for U-shaped styles in the faculty sample.

These findings lend some support to the predictive validity and situational consistency of the deadline pacing style. In both student and faculty samples, higher scores on deadline style were associated with higher scores on the equivalent behavioral response categories, although effect sizes were small. Steady action style results were more supportive for students as compared to faculty, and neither sample offered substantial evidence for the predictive validity and situational consistency of the U-shaped style. The low internal consistency reliabilities of the self-reported pacing behaviors call for caution in interpreting these results.

Predicting Psychological Outcomes

Zero-order correlations showed that, as expected, deadline and U-shaped pacing styles were both positively associated with challenge-related stress (r = .15, p < .01 and r = .18, p < .01, respectively). The steady pacing style showed no significant relationship with challenge-related stress (r = .01, p > .05). Steady and U-shaped styles were associated with higher levels of task absorption (r = .23, p < .01 and r = .22, p < .01, respectively), whereas the opposite was true for the deadline style (r = −.12, p < .05). Hence, as expected, both deadline and U-shaped pacing style are associated with challenge-related stress. At the same time, early task engagement allows U-shaped workers to experience task absorption as steady workers do.

Furthermore, we performed hierarchical linear regression analyses to test the predictive validity of PACED over and above the pacing style graphs and various time-related constructs (i.e. procrastination, deadline challenge orientation, priority focus, proactive personality, time urgency, and deadline optimism, as described in Study 3). As shown in Table 7, the positive associations of deadline (β = .14, p < .05) and U-shaped (β = .15, p < .01) pacing styles with challenge stress were significant after controlling for the pacing style graphs and various time-related constructs. Controlling for the pacing style graphs resulted in significant positive relationships with absorption for steady and U-shaped pacing styles (β = .18, p < .01; β = .15, p < .01, respectively). After also controlling for other time-related constructs, a significant positive relationship between steady pacing style and task absorption remained (β = .15, p < .05). These results support the predictive validity of PACED over and above the graphical scale and other time-relevant constructs.

Table 7. Predictive Validity of PACED for Challenge-Related Stress and Absorption
  Challenge-related stressAbsorption
  1. Note: Pacing style graph 1 (Early) was taken as the reference category for dummy coding the categorical graphs;
  2. * p < .05; ** p < .01; *** p < .001.
Model 1(Constant)1.11***1.51***
Pacing style graph 2−.08−.02
Pacing style graph 3−.06−.15
Pacing style graph 4−.15−.15
Pacing style graph 5−.18−.33*
Pacing style graph 6−.04−.12
Challenge orientation−.04.18***
Priority focus.19***.12*
Proactive personality.21***.24***
Time urgency.03.07
Deadline optimism−.11*−.11*
  F(11, 386) = 9.582; p = .001; R2 = .22***F(11, 386) = 6.785; p < .001; R2 = .17***
Model 2(Constant)0.7080.968*
Pacing style graph 2−.09−.04
Pacing style graph 3−.06−.17*
Pacing style graph 4−.18−.17
Pacing style graph 5−.22−.26
Pacing style graph 6−.09−.13
Challenge orientation−.08.18**
Priority focus.18***.10
Proactive personality.20***.21***
Time urgency.03.06
Deadline optimism−.11*−.08
PACED_deadline style.14*−.01
PACED_steady style.01.15*
PACED_U-shaped style.15**.07
  F(14, 386) = 8.596; p < .001; R2 = .24***; ΔR2 = .03**F(14, 386) = 6.264; p < .001; R2 = .19**; ΔR2 = .03**
Table 8. Correlations between PACED and Reported Pacing Behavior
 Student sample (N = 380)Faculty sample (N = 124)
Weak situationsStrong situations 
Steady behaviorU-shaped behaviorDeadline behaviorSteady behaviorU-shaped behaviorDeadline behaviorSteady behaviorU-shaped behaviorDeadline behavior
  1. Note:  ** p < .01; *** p < .001.
Steady pacing style.34***.13**−.29***.38***−.09−.35***.16.23**−.30***
U-shaped pacing style.13**.06−.14**.13**.03−.21***−.09−.03.10
Deadline pacing style−.32***−.02.25***−.30***.08.24***−.24**−.23**.37***


Despite intuitive appeal, pacing style has been under-researched. Towards the goal of stimulating future studies, the purpose of the present article was to clarify the conceptualisation of pacing styles and to develop and validate a new scale-based pacing style measure. We developed a nine-item Pacing Action Categories of Effort Distribution (PACED) scale, representing three pacing style dimensions: (a) the deadline action style, which reflects a concentration of effort late in task execution; (b) the steady action pacing style, which reflects a tendency to spread out work evenly over time; and (c) the U-shaped action pacing style, which reflects a tendency to systematically combine both early and late effort distribution. Across eight independent samples from students, faculty, and organisational members in two countries, the dimensionality and reliability of PACED were supported, as demonstrated by a clear factor structure and high internal consistency.

Furthermore, PACED demonstrated expected relationships with variables in the nomological network of pacing style. The PACED subscales were significantly related to their graphical counterparts in the expected direction. The lack of significant relationships with time perspective and time urgency indicate that pacing style contains unique content that is unaddressed by other temporal individual differences. The negative association with polychronicity suggests that the last-minute activity characteristic of the deadline style requires individuals to focus exclusively on the task at hand and does not allow for much task switching. In addition, the pattern of associations between pacing style dimensions and conscientiousness, proactive personality, rational decision style, priority focus, and time management behavior confirm that steady and U-shaped pacing styles are more planful and deliberate in orchestrating their workload compared to the deadline pacing style. However, more than the U-shaped style, the steady style appears to stem from a strong preference for order and predictability as well as a certain level of risk aversion. While U-shaped individuals engage in early efforts to prepare for deadline work, steady workers seem motivated to avoid deadline work altogether.

As expected, the deadline action style was positively related to procrastination, while steady and U-shaped styles were negatively related. However, the findings also confirmed the proposed conceptual differences between the deadline pacing style and procrastination, as demonstrated by confirmatory factor analyses as well as a different pattern of correlates. Although both report feeling challenged by the last-minute rush, deadline action individuals were more optimistic about their effectiveness under deadline pressure compared to self-admitted procrastinators. Therefore, while procrastination generally represents delay resulting from threat, some deadline action style individuals may deliberately wait until the last minute because they are energised by impending due dates and expect beneficial outcomes from working under the pressure of the deadline.

In addition to convergent and discriminant validity, we showed that PACED also predicted psychological work outcomes. As expected, deadline and U-shaped pacing styles were positively associated with challenge-related stress. Task absorption was positively related to steady and U-shaped styles, but negatively related to the deadline action style. In all, the results of the present studies suggest that PACED is a construct valid measure of pacing styles. The nine-item scale with instructions and the response format are listed in the Appendix.

Research Implications

In recent years, there has been increased attention on time-based individual differences (e.g. Conte & Gintoft, 2005; Mohammed & Nadkarni, 2011; Shipp et al., 2009) and the dynamic nature of goal directed behavior (e.g. Fried & Slowik, 2004; Schmidt et al., 2009; Steel & König, 2006). Building on as well as extending these two research streams, the current research focuses on how individuals pace their work leading up to a deadline, which is non-redundant with existing temporal constructs. As pacing styles have not received adequate attention in the extant literature, the creation of a psychometrically sound scale is a first step toward encouraging empirical work in research domains where pacing styles can be expected to have important implications. Below, we describe the relevance of the pacing style construct for both individual-level and team-level research.

McGrath and O'Connor (1996) described deadlines as an important “time-marker” that puts tasks within a certain time frame and motivates people to start working on the task. However, people are known to undervalue distal goals, a phenomenon described as time discounting (Koch & Kleinmann, 2002; Loewenstein & Prelec, 1993). In deriving their Temporal Motivational Theory, Steel and König (2006) suggested several motivational opportunities associated with time discounting. For example, by setting tighter deadlines or by dividing large goals into a series of smaller sub-goals with subsequent deadlines, one can increase the proximity, and thereby, the value of a deadline, which increases motivational force. Moreover, Burgess, Enzle, and Schmaltz (2004) studied the motivational force of deadlines from a self-determination perspective and found that complete or partial self-determination in setting deadlines and sub-deadlines negates the otherwise deleterious effects of imposed deadlines on intrinsic motivation. Participants showed more interest and engagement in their tasks when they actively participated in setting time limits. However, our findings suggest that individuals are not equally deadline driven, and hence, that the motivational force of such goal setting strategies, whether related to what time limits are set or how they are set, may depend upon pacing styles. Increasing the deadline proximity may raise the efficiency and effectiveness of individuals with a U-shaped or deadline pacing style, but may be less effective or even counterproductive for individuals with a steady style. Likewise, differing pacing styles may not be equally motivated to set and adhere to self-imposed deadlines. Hence, future research should examine interactions between temporal goal setting and pacing styles to determine optimal motivational strategies.

Pacing styles may also contribute to research on team processes and team outcomes. Although team research has traditionally focused on “teamwork” and “task work”, scholars increasingly voice the opinion that in order to fully understand team dynamics, we need to consider the “when” as well as the “who” and the “what” (e.g. Mohammed et al., 2009; Rico, Sánchez-Manzanares, Gil, & Gibson, 2008). Because pacing styles relate to the “when” of individual task activity, considering the composition of a team in terms of pacing styles may increase our understanding in areas such as team coordination, conflict, and shared mental models. Individual differences in pacing styles (using the extant graphical measure) have been shown to impede a shared perception of temporal milestones and the pacing of actions among team members (e.g. Gevers et al., 2006), which, in turn, hampers team coordination (Gevers et al., 2009b). As a measurement tool, PACED can contribute to increased insight into the effects of temporal dynamics on team effectiveness outcomes.

Practical Implications

The PACED could be used in time management training programs to educate individuals about the particular strengths and weaknesses of their personal pacing style and how to manage challenges effectively. For example, the steady action style enables accommodation to unforeseen changes in the environment that impact progress toward the deadline, but not all tasks allow for the lengthened time period that this style requires. On the other hand, a deadline pacing style seems well suited for high time pressured situations with short deadlines, but may increase the risk of missing deadlines if unexpected events occur. Finally, the U-shaped pacing style allows for the incubation period helpful in creative tasks, but could result in wasted efforts if early task progress becomes outdated by the time the deadline draws near (Mohammed & Harrison, 2007). Moreover, PACED could be used to select employees whose styles fit the requirements of a job once better insight is established on the match between pacing style and job requirements. Although additional research is required on this matter, it seems plausible that a good match between pacing style and time-related characteristics of a job (e.g. quick turnaround times and tight deadlines) may increase the likelihood of desired outcomes in terms of job performance, job satisfaction, and worker well-being. In addition to personnel selection and training, PACED also has potential uses for team composition and team coordination purposes. Specifically, the nine-item scale could be utilised as an efficient tool to help team members learn about their own as well as each others' pacing styles. Because pacing styles are usually not discussed, implicit assumptions regarding motives (e.g. individuals with a deadline action style are lazy) may lead to unfavorable personal attributions and induce destructive types of conflict in a team (Mohammed & Harrison, 2007). Therefore, PACED can be used to facilitate explicit discussion of pacing styles. Knowledge of the pattern of pacing styles in the team could inform the distribution of task assignments and optimal pacing of team activities as well as foster consensus concerning how team temporal milestones can be met most effectively. Prior research has shown that regulatory action on the part of team members (Gevers et al., 2006; Gevers et al., 2009b) or the team leader (Mohammed & Nadkarni, 2011), based on shared knowledge of temporal individual differences, can help leverage the advantages of temporal diversity while neutralising the disadvantages.

Limitations and Future Research Directions

Despite the promising potential of the new PACED, the current research has limitations to acknowledge. The results of the three exploratory factor analyses in Study 1 were based on relatively small samples, but the consistent results of the five confirmatory factor analyses in the large and diverse samples of Study 2 help to compensate for this weakness.

Moreover, the current research relied exclusively on cross-sectional designs and self-reports, which may have induced common method bias. However, the magnitude of common method variance effects in cross-sectional survey research has recently been disputed (Lance, Dawson, Birkelbach, & Hoffman, 2010; Spector, 2006). In addition, we considered self-report the most appropriate method for assessing pacing styles and their correlates, such as time-relevant attitudinal variables and psychological states. Nevertheless, it would be desirable to collect peer ratings or supervisor ratings of pacing styles in future research and assess their comparability with self-perceptions.

Since we only measured self-reported outcomes, we also acknowledge the need for further research on the predictive validity of PACED, particularly regarding job performance. As the effectiveness of a particular style will depend on a number of contingency factors, we recommend that this research take into account possible interactions between pacing styles, task type, and job context on performance. Preferably, research should also control for procrastination and planning to offer insight into the incremental validity of PACED over and above well-established constructs of goal directed behavior.

Although we included faculty and organisational samples, we used mostly students across studies, which may have contributed to an overrepresentation of the deadline action style. The pattern of pacing style means across the three styles in both the faculty (Deadline: M = 2.80, SD = .95; Steady: M = 2.70, SD = .81; U-shaped: M = 3.10, SD = .89) and organisational (Deadline: M = 2.38, SD = .85; Steady: M = 2.94, SD = .83; U-shaped: M = 2.76, SD = .89) samples tended to be less deadline oriented than the student means reported in Tables 2, 3, 4, and 5. Furthermore, there has been some initial evidence in the literature of cultural differences in deadline avoidant behaviors (Klassen, Ang, Chong, Krawchuk, Huan, Wong, & Yeo, 2010), making cross-cultural differences in pacing style and consequent behaviors an important area for further investigation. Additional research in more diverse contexts should verify the generalisability of findings.

Finally, as the extant literature has demonstrated disagreement concerning the stability of the pacing style construct, one of the purposes of the present research was to begin to inform this empirical research need. However, several methodological weaknesses limited the extent to which clear conclusions could be drawn regarding the temporal and situational stability of the pacing style construct. Concerning temporal stability, three-week test–retest reliability was high for the deadline pacing style, but moderate for the steady and U-shaped styles. These mixed test–retest reliability results mirror the disagreement concerning the stability of pacing style in the literature (Gevers et al., 2009a; Gevers et al., 2006; Mohammed & Harrison, 2007). Nevertheless, the outcomes of the test–retest analysis should be interpreted with caution because of the small sample size and only a three-week time lag. Clearly, future research would benefit from a more elaborate assessment of within-person variations over longer periods of time and across different contexts.

Deadline pacing style had the strongest situational consistency in everyday events (e.g. tax preparation, writing papers, and studying for exams), whereas the U-shaped style had the weakest. However, the low internal consistency reliability of the pacing behavior measures obfuscates conclusions regarding the situational stability of the pacing style construct. The methodological shortcomings of the pacing behavior measures (e.g. a categorical response format, three deadline response options in comparison to a single response option each for steady and U-shaped behaviors) should be improved upon in future research. The relative inconsistency of the U-shaped pacing style over both time and situations may indicate that this style is selected strategically for specific types of task or context. Consistent with this reasoning, a survey-based study of 88 employees found that individuals in more creative professions (e.g. artists, designers, architects) reported using the U-shaped pacing style more than individuals in less creative professions (e.g. executive secretaries, junior account managers; Beeftink, 2008).

We expect individuals to be predisposed to adopt a particular response pattern for how they distribute their effort in working toward deadlines, but task conditions may impose constraints on the expression of individual pacing styles (Mischel, 1977; Tett & Burnett, 2003). As such, pacing style may be best characterised as a somewhat stable behavioral tendency that may be influenced by situational characteristics. However, the temporal and situational stability of pacing style remains a research need that future studies should inform. In addition, longitudinal studies should explore whether there are specific periods of stability and periods of transition in pacing styles (e.g. students moving from the classroom into the job market) as well as the specific mechanisms that account for changes.


As researchers are increasingly being urged to incorporate temporal issues into studies, and practitioners are increasingly time-pressed to deliver goods and services, it will become more germane to address how individuals allocate their effort over time in working toward deadlines. In response, we developed the pacing style construct and derived a new measure, PACED, which offers important advantages over the extant single-item measure. Although currently under-represented as a temporal individual difference, we hope that the introduction of a construct valid measure representing deadline, steady, and U-shaped pacing styles will stimulate empirical research. Further consideration of pacing style as an antecedent to individual, team, and organisational outcomes can help practitioners and researchers in predicting and enhancing employee job fit and well-being.


  1. 1

    The authors would like to thank an anonymous reviewer for helping us to make these points.


When you have to work on a project or task with a time limit, how do you generally distribute your workload from the moment you get the project or task until the deadline? Please indicate the extent to which you agree or disagree with each statement by circling the corresponding number according to the scale below. Describe yourself as you are now, not as you wish to be in the future.

  1. I do most of the work on tasks in a relatively short time before the deadline.
  2. I work steadily on tasks, spreading my work out evenly over time (e.g. 3 hours per week until the deadline).
  3. The effort I put into projects is high at the start, low half-way through, and high again at the end.
  4. I do not get much done on projects until the due date is close.
  5. I invest most of my effort toward the beginning and end of projects.
  6. I pace myself to work on projects a little bit every day or every week instead of doing several hours of work all at once.
  7. I generally do not work until there is time pressure from an approaching deadline.
  8. I work in a slow, but steady, manner to complete tasks.
  9. I put in more effort at the beginning of tasks as well as right before the deadline, but am less active during the middle of the work cycle.