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Abstract

Objective:

This study aims to investigate the complex relation between adult ADHD symptoms, procrastination, and mediating factors, in light of leading procrastination theories: the Temporal Motivation Theory (TMT), emotion regulation, and a General Architecture for Modeling the Dynamics of Goal-Directed Motivation and Decision-Making – the GOAL architecture.

Method:

The study was preregistered. A survey was conducted with 640 adults recruited online to examine the associations between ADHD symptoms, procrastination, and seven mediating factors. Participants completed measures assessing ADHD symptoms, procrastination tendencies, emotion regulation, motivation, and goal-related behaviors. Structural equation modeling (SEM) was used to test the direct and indirect pathways among the variables.

Results:

A positive association was revealed between ADHD inattention symptoms and procrastination tendencies. The mediating factors that significantly contributed to this relations were sensitivity to delay, perceived low value of the task, and flexible goal adjustment. While ADHD inattention symptoms was associated with all seven variables, three variables directly contributed to increased procrastination behavior, thus explaining the link between inattention symptoms and procrastination.

Conclusions:

The study highlights the relations between procrastination and adult ADHD symptoms and underscores the need to address mediating factors in intervention strategies. Understanding these mechanisms is essential for developing targeted interventions to improve functional outcomes for individuals with ADHD.

Keywords

ADHD procrastination temporal motivation theory emotional regulation

Introduction

ADHD is a common neurodevelopmental condition characterized by persistent patterns of inattentive, hyperactive, and impulsive behavior, which lead to functional impairment (American Psychiatric Association, 2013; Faraone et al., 2015). ADHD can have a negative impact on long-term academic outcomes (as shown in a meta-analysis by Arnold et al., 2020), occupational and social functioning (Holst & Thorell, 2019), health-related quality of life, work productivity, and daily activities (Joseph et al., 2019). It often co-occurs with other conditions (Choi et al., 2022).

Educators and clinicians alike have observed that individuals with ADHD, especially adults, often display a tendency toward procrastination (Langberg et al., 2018; Ramsay, 2020; Safren, 2006; Swartz et al., 2005; Young & Myanthi Amarasinghe, 2010). This association is reflected in a question included in a widely used adult ADHD screening scale by Ustun et al. (2017) “How often do you put things off until the last minute?” The present study examines the factors that account for the link between ADHD and procrastination.

Procrastination, in the sense of a voluntary but irrational delay of an intended course of action (Steel, 2007), has been increasingly acknowledged to contribute to several adverse outcomes in different domains, including academic performance (Kljajic & Gaudreau, 2018), health behavior (F. M. Sirois, 2021), personal finance (Gamst-Klaussen et al., 2019), work (Metin et al., 2018; Nguyen et al., 2013), and general well-being (F. M. Sirois & Pychyl, 2016).

Considerable research attention has been devoted to individual-level variables that may contribute to a tendency toward procrastination, including demographic characteristics such as gender/sex, age, marital status, and education; most scholars concur that procrastinators were more likely to be younger than older, single than married, men than women, and less rather than more highly educated (Balkis & Erdinç, 2017; Beutel et al., 2016; Harriott & Ferrari, 1996; Steel & Ferrari, 2013; Wypych et al., 2018). Furthermore, as already noted, a positive correlation has been demonstrated between procrastination and ADHD. The next section elaborates this association.

ADHD and Procrastination

Thus far, few studies have examined the co-occurrence of ADHD and procrastination, and even fewer have provided theoretical explanations. For example, Ferrari (2000) found no association between procrastination and attention deficits in normal adults. However, subsequent work (Ferrari & Sanders, 2006) indicated that adults with ADHD reported higher procrastination across life domains. Similar results were reported by Miller (2007), who found elevated procrastination among college students with ADHD. Supporting this pattern, Niermann and Scheres (2014) and Ashworth and McCown (2018) observed positive correlations between procrastination and adult ADHD symptoms. Extending these findings, Altgassen et al. (2019) linked this association to everyday prospective memory, while Bolden and Fillauer (2020) focused on executive functions. More recently, Müller et al. (2023) demonstrated significant relationships between ADHD symptoms, procrastination, depression, academic boredom, and smartphone addiction among college students. In another study, Bodalski et al. (2023) showed that ADHD symptoms indirectly influenced general procrastination through serial effects on emotion dysregulation and self-esteem. Finally, Netzer Turgeman and Pollak (2023) identified a positive correlation between adult ADHD and procrastination, partially explained by diminished expectancy and heightened impulsiveness.

The present study builds on the above findings, which cite several different factors as responsible for the correlation between ADHD and procrastination. Accordingly, it assumes a priori that this relation is complex and multifactorial, thus requiring a comprehensive theoretical basis for investigation.

Procrastination Theories

In line with the literature discussed above, this article conceives of procrastination in terms of emotion regulation, temporal motivational theories, and the GOAL architecture.

The first perspective concerns emotion regulation. Beyond motivational explanations, growing research highlights the role of emotion regulation in understanding procrastination and ADHD. Emotion regulation is commonly defined as the processes by which individuals influence which emotions they have, when they have them, and how they experience and express them (Gross, 1998; Gross & Thompson, 2007). Dysregulation occurs when these processes are ineffective or maladaptive. Scholars distinguish between adaptive strategies such as cognitive reappraisal – changing the way one thinks about a situation to alter its emotional impact – and maladaptive strategies such as suppression or avoidance (Gross & John, 2003). In ADHD, difficulties in emotion regulation are highly prevalent and contribute to functional impairments beyond core symptoms (Shaw et al., 2014). Moreover, research suggests that emotion dysregulation may partly account for the strong association between ADHD and procrastination (Bodalski et al., 2023). Hence, the present study incorporated the Emotion Regulation Questionnaire (ERQ) in order to assess whether specific emotion regulation strategies mediate the ADHD–procrastination link.

Within the emotion-regulation perspective, F. Sirois and Pychyl (2013) conceptualize procrastination as a self-regulation failure that results from the overriding desire to feel good, or rather not to feel bad, at a given moment, thus prioritizing short-term mood repair over achieving long-term goals. These authors describe this dynamic as a hedonic shift in the emotions one experiences upon deciding to delay a task, and link the propensity toward procrastination to coping patterns anchored in avoidance and disengagement and reflecting a maladaptive coping style. This perspective rests on studies showing that people procrastinate more when they are sad and that the link between feeling upset and procrastination is moderated by the subjective pleasantness of the distractor. Thus, Pollack and Herres (2020) found, based on self-reports, that procrastination behavior is motivated by negative emotions – even if experienced the previous day. On the flipside, Wohl et al. (2010) demonstrated that procrastination can be reduced through systematic training in emotional regulation skills, which modify aversive emotions.

In the framework of the Temporal Motivation Theory (TMT), procrastination is explained in terms of the motivation to pursue a goal, which is a function of both the value of the goal and the expectancy of achieving it (Steel & König, 2006). In this approach, the mechanism underlying decision-making can be represented by the following equation:

Motivation = \frac{Expectancy \times Value}{1 + Impulsiveness \times Delay}

The greater one’s expectancy for completing the task and the higher the value of the outcome associated with it, the higher one’s motivation, and the less one’s likelihood to procrastinate. One’s motivation is generally reduced by the length of the delay until the outcome is realized and one’s impulsiveness, or sensitivity to delay. Subsequently, Steel et al. (2018) proposed a simplified formulation of temporal motivation theory whereby the motivation for a certain behavior derives from three interconnected sources: the value of the task, the time horizons related to this task, and the expectancy of achieving it.

The validity of TMT was tested using scales and real-life multiple assessments during an introductory psychology course (Steel et al., 2018). In 2011, Steel developed the Motivational Diagnostic Test to this end, which showed that expectancy, value, and impulsivity accounted for 49% of the variance in procrastination. Wypych et al. (2018) probed the connections between impulsivity, emotion regulation, and procrastination using multiple questionnaires, and accounted for the variance in the level of procrastination based on emotion regulation and sensitivity to delay.

A General Architecture for Modeling the Dynamics of Goal-Directed Motivation and Decision-Making aims to integrate various aspects of motivational dynamics during goal pursuit into a single, cohesive model (Ballard et al., 2022). This framework focuses on the task that needs to be accomplished in order to achieve a goal, and predicts motivational changes as one approaches that goal by integrating six theoretical perspectives. The prediction is based on a combination of three gradients that are assumed to influence the motivational value of the goal at any time point: spatial gradient – the distance to the goal, gauged by the amount of work required to complete the task; temporal gradient, that is, the looming deadline; and spatiotemporal gradient – the rate of progress required to reach the goal. This relation is formalized in the following weighted additive equation:

M_{i j} = w_{1} S G_{i j} + w_{2} T G_{i j} + w_{3} S T G_{i j}

where M_ij represents the motivational value of goal i at time j, and w1, w2, and w3 are weight parameters that determine the relative influence of the spatial, temporal, and spatiotemporal gradients on motivation. In essence, Ballard et al. (2022) propose to measure motivation in every given case as goal prioritization.

The Present Study

Building on the reviewed literature, the present study aims to clarify the mechanisms linking ADHD symptoms and procrastination. To this end, we integrate three major theoretical frameworks: (a) the emotion regulation perspective, which defines procrastination as a self-regulation failure motivated by short-term mood repair (Gross & John, 2003; F. Sirois & Pychyl, 2013); (b) Temporal Motivation Theory (TMT), which highlight emphasizes the roles of expectancy, value, and sensitivity to delay in predicting procrastination (Steel et al., 2018; Steel & König, 2006); and (c) the GOAL architecture, which describes motivational dynamics through tenacious and flexible goal pursuit (Ballard et al., 2022). These perspectives collectively inform our hypothesis by highlighting motivational and emotional processes that may mediate the association between ADHD symptoms and procrastination.

Our hypothesis is anchored in a multifactorial weighted approach to procrastination, which we believe to hold promise in probing the relation between this propensity and ADHD. More specifically, we hypothesize that the link between ADHD and procrastination is accounted for by differences in motivational and emotional processes. Simply put, individuals with ADHD may be hypersensitive to certain factors and/or less sensitive to others. We test this hypothesis through self-report measures, which have been shown as good predictors of procrastination behavior (Zuber et al., 2020).

Method

Participants and Procedure

This study was preregistered on OSF (Open Science Framework) prior to data collection. The preregistration, including hypotheses, methods, and analysis plan, can be accessed at https://doi.org/10.17605/OSF.IO/Y9WDX.

The Ethics Committee of the Hebrew University of Jerusalem approved the study (Ethical approval code: 25122022).

Participants were recruited through Prolific and offered a $3 compensation based on the estimated time to complete the survey. Of the 698 participants who responded, more than 95% filled out the survey. Based on an estimation of the fastest possible valid response, we pre-registered an exclusion criterion of duration ≥3 min. The 14 respondents who completed the survey in less than 3 min were excluded from the analysis. An additional 44 respondents were excluded as they provided incorrect answers to two attention-check questions. The analysis was thus based on the responses of 640 participants. The sample size required for the study was determined as N = 625 using the A priori Sample Size Calculator for Structural Equation Models developed by Soper (2023). Our goal was to detect an effect in a structural equation model with a power of 0.80, α = .05, and small-to-moderate correlations (rs = .25) between the 70 manifest and 9 latent variables in the model. Accordingly, our sample size was sufficient for the planed analysis.

The participants’ pre-registered age range was set to 18 to 60; In fact, ages ranged from 18 to 56 (average = 36; SD = 9.64). In addition, 393 identified as male, 234 – as female, and 13 – as other; 217 (34%) were high school graduates, 232 (36%) were pursuing a bachelor’s degree, 92 (14%) held a bachelor’s degree, 82 (13%) held a master’s degree, and 17 (3%) held a PhD, law, or medical degree.

Sixty-eight participants reported having been diagnosed with ADHD, which was significantly correlated with the ADHD screening scale (−0.304**, p < .000) used in the current study, where ADHD was conceptualized within a dimensional approach (Coghill et al., 2012) and treated as a continuous trait.

Measures

Background information regarding age, gender/sex (mistakenly, the question was phrased: “What is your gender?” and the options were male, female, or other, confusing sex with gender), education level, income level, and history of diagnosis and treatment for ADHD was obtained using a Demographic Questionnaire.

The questionnaires were used for measuring the study variables are described in what follows.

ADHD was measured using the Adult ADHD Self-Report Scale (ASRS-V1.1), which is a widely used dimensional instrument for ongoing ADHD symptoms. Of the questionnaire’s 18 items, assessed in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth edition, on a Likert scale ranging from 1 (never) to 5 (very often), 9 address inattention and 9 hyperactivity/impulsivity. This instrument has been found to have an internal consistency of .88 (Kessler et al., 2005) and demonstrated good reliability in the current sample with a Cronbach’s alpha of .80. It also shows a sensitivity of 68.4% and a specificity of 99.6% (Adler et al., 2006; Kessler et al., 2005). For each participant, the ADHD score was taken to be the mean inattention score, computed on 8 items, with the ninth item (“When you have a task that requires a lot of thought, how often do you avoid or delay getting started?”), directly targeting procrastination, excluded. Given that the literature indicates a strong correlation between procrastination and inattention (Bolden & Fillauer, 2020; Netzer Turgeman & Pollak, 2023; Niermann & Scheres, 2014), we decided to focus on this particular factor.

Procrastination was measured using the Irrational Procrastination Scale (IPS), which comprises nine items measuring aspects related to an irrational delay, where higher scores indicate higher levels of procrastination. The scale has yielded good internal consistency, with Cronbach’s α = .91 in previous research (Steel, 2010), and demonstrated similar reliability in the current sample, with a Cronbach’s α of .92. It also showed a strong correlation of .87 with PPS (the Pure Procrastination Scale) at r = .87 (Steel, 2010).

Emotion regulation was measured using the Emotion Regulation Questionnaire (ERQ), a widely used self-report assessment of two common emotion-regulation strategies: reappraisal, which involves modifying emotional experiences by reinterpreting the meaning of situations, and suppression, which refers to inhibiting the outward expression of feelings (Gross & John, 2003). Six questions target reappraisal, and four – emotions, by gauging, respectively, how participants change and restructure their emotions and how they keep themselves from expressing them. The ERQ’s construct validity is evidenced in the significant correlation between the two subscales in the expected direction (Gross & John, 2003). Cronbach’s α reliability values stood at .79 and .86, the respective averages for the suppression and the reappraisal scales (Gross & John, 2003), and in the current sample, the scales demonstrated good reliability with α = .84 and .91, respectively.

Expectancy, value, and sensitivity to delay were all measured using the Motivational Diagnostic Test (MDT). This self-report instrument is anchored in the Temporal Motivational Theory (TMT). It comprises 24 items, measuring the three factors influencing motivation, expectancy, value, and sensitivity to delay, as they are self-perceived. Thus, expectancy is operationalized as self-efficacy (“If I try hard enough, I will succeed”), value as enjoyableness (“I don’t find my work enjoyable”), and sensitivity to delay (delay discounting) as preference of short-term over long-term goals (“I have a hard time postponing pleasurable opportunities as they gradually crop up).” In Steel’s (2011) study, expectancy, value, and sensitivity to delay showed high reliability (α = .83, .84, and .83, respectively) and accounted for 49% of the variance in procrastination. In the current sample, these subscales also demonstrated good reliability, with α = .90, .74, and .76, respectively.

Distance to goal was measured using the short, five-item versions of Tenacious Goal Adjustment (FGA) and Flexible Goal Pursuit (TGP) scales, initially developed by Brandtstädter and Renner (1990). These scales capture the two eponymous aspects of goal-related behavior, respectively. Tenacious goal pursuit (TGP) refers to striving for goals with commitment and determination, whereas flexible goal adjustment (FGA) refers to adjusting and modifying goals when there are obstacles. Both scales showed good internal validity: Although Kelly et al. (2013) reported α = .68 for FGA and α = .73 for TGP, a more recent study reported higher internal consistency (α = .81 and .86, respectively, Kappes & Greve, 2024). In the current sample, the scales demonstrated good reliability as well, with α = .80 for FGA and α = .79 for TGP.

As a screening tool for measuring severe psychological distress, we used K6, short for the Kessler Screening Scale for Psychological Distress (Kessler et al., 2002), which comprises six items, rated on a 5-point Likert scale, and tapping, respectively how often, during the preceding month, the respondent had felt nervous, hopeless, restless or fidgety, depressed, and that everything was an effort or worthless. The scale, whose summary score constitutes a non-diagnostic measure of general psychological distress, has been widely validated in cross-cultural contexts (e.g., Kessler et al., 2010; Pollak et al., 2020; Tomitaka et al., 2019) and found reliable, with Cronbach’s α ranging from .89 to .92 (Kessler et al., 2002). In the current sample, the scale demonstrated good reliability with a Cronbach’s α of .95. The current study used The K6 only for exploratory purposes for raising hypotheses about the link between psychological distress and procrastination.

Results

Statistical analyses of the characteristics and correlations were conducted using SPSS, while the Structural Equation Modeling (SEM) was carried out using MPLUS version 8.1.

Descriptive Statistics

Table 1 displays the descriptive statistics of all metrics gathered for the entire sample; Table 2 showcases the bivariate Pearson correlations among the variables.

Table 1.

Means and Standard Deviations.

Variable	M	SD	Min	Max	Skewness	Kurtosis
Procrastination (IPS)	2.61	0.9	1	4.89	0.23	−0.57
ADHD symptoms (ASRS)
ASRS total	2.3	0.75	1	4.67	0.45	0
ASRS-R total	2.28	0.74	1	4.65	0.49	0.06
ASRS inattention	2.43	0.85	1	5	0.44	−0.06
ASRS hyperactivity	2.17	0.77	1	4.89	0.6	0
Distance to goal (TGP and FGA)
Tenaciousness	3.57	0.83	1	5	−0.55	0.09
Adjustment	3.30	0.87	1	5	−0.33	−0.22
Motivational factors (MDT)
Expectancy	3.81	0.79	1	5	−0.64	0.29
Low value	2.65	0.93	1	5	0.3	−0.56
Sensitivity to delay	2.63	0.85	1	5	0.25	−0.19
Emotion regulation (ERQ)
Reappraisal	4.93	1.21	1	7	−0.81	0.78
Suppression	4.01	1.44	1	7	−0.14	−0.63
Psychological distress (K6)	3.82	1.05	1	5	−0.92	0.08

Note. M and SD are used to represent means and standard deviations, respectively. Values in square brackets indicate the 95% confidence interval for each correlation. ASRS = the Adult ADHD Self-Report Scale-V1.1; ASRS-R = (not including item 4, which overlaps with procrastination); ASRS inattention = the mean of the eight ASRS inattention items (not including Item 4); ERQ = Emotion Regulation Questionnaire; FGA = flexible goal adjustment; IPS = irrational procrastination scale; MDT = motivational diagnostic test; TGP = tenacious goal pursuit.

Table 2.

Correlations With Confidence Intervals.

Variable	1	2	3	4	5	6	7	8	9	10	11	12
1. IPS
2. ASRS	.71** [.67, .74]
3. ASRS_R	.68** [.64, .72]	1.00** [1.00, 1.00]
4. ASRS inattention	.79** [.76, .82]	.93** [.92, .94]	.92** [.90, .93]
5. ASRS hyperactivity	.50** [.44, .56]	.91** [.90, .93]	.93** [.91, .94]	.70** [.66, .74]
6. TGP	−.45** [−.39, −.51]	−.34** [−.27, −.41]	−.33** [−.26, −.40]	−.42** [−.35, −.48]	−.21** [−.13, −.28]
7. FGA	−.37** [−.30, −.44]	−.35** [−.28, −.42]	−.34** [−.27, −.41]	−.39** [−.33, −.46]	−.25** [−.17, −.32]	−.51** [−.45, −.57]
8. Expectancy	−.51** [−.57, −.45]	−.41** [−.47, −.34]	−.39** [−.46, −.33]	−.49** [−.55, −.43]	−.25** [−.32, −.17]	.57** [.62, .52]	.47** [.53,.41]
9. Low value	.70** [.66, .74]	.65** [.61, .70]	.64** [.59, .69]	.70** [.66, .74]	.49** [.43, .55]	−.50** [−.44, −.56]	−.45** [−.38, −.51]	−.54** [−.59, −.48]
10. Sensitivity to delay			.66** [.61, .70]	.67** [.62, .71]	.57** [.51, .62]	−.36** [−.29, −.42]	−.31** [−.24, −.38]	−.27** [−.34, −.20]	.65** [.60, .69]
11. Reappraisal	−.31** [−.38, −.24]	−.26** [−.33, −.18]	−.25** [−.32, −.17]	−.32** [−.39, −.25]	−.15** [−.22, −.07]	.40** [.46,.33]	.51** [.56,.45]	.50** [.44, .55]	−.30** [−.37, −.23]	−.17** [−.24, −.09]
12. Suppression	.20** [.12, .27]	.13** [.05, .21]	.13** [.05, .20]	.16** [.09, .24]	.07 [−.00, .15]	−.14** [−.06, .−21]	−.10* [−.02, −.18]	−.16** [−.24, −.09]	.25** [.18, .32]	.19** [.12, .26]	−.04 [−.12, .04]
13. K6	.46** [.39, .51]	.51** [.45, .56]	.51** [.45, .56]	.50** [.44, .55]	.44** [.37, .50]	−.30** [−.23, −.37]	−.37** [−.30, −.43]	−.42** [−.48, −.36]	.44** [.38, .50]	.32** [.25, .39]	−.30** [−.37, −.23]	.17** [.10, .25]

Note. Values in square brackets indicate the 95% confidence interval for each correlation. ASRS = the Adult ADHD Self-Report Scale-V1.1; ASRS-R = (not including item 4, which overlaps with procrastination); ASRS Inattention = the mean of the eight ASRS inattention items (not including Item 4); ERQ = Emotion Regulation Questionnaire; FGA = flexible goal adjustment; IPS = irrational procrastination scale; MDT = Motivational Diagnostic Test; TGP = tenacious goal pursuit.

p < .05. **p < .01.

Best-Fitted SEM Model Identification

First, we built and validated measurement models for unidimensional and multidimensional variables included in the hypothesized model. Supplemental Table S1 displays the results, including model fit indices, modifications, and chi-square tests for the differences between the nested models.

For ADHD inattention (the independent variable in the hypothesized model), a confirmatory factor model with one factor and two correlated residuals between two items demonstrated good model fit according to common indices (see Supplemental Table S1). For IPS (the dependent variable), a revised model with a single factor and two correlated item residuals showed sufficiently high model fit indices. Measurement models for the mediating variables also achieved satisfactory fit indices after similar revisions in item covariates: a three-factor model for motivation, a two-factor model for ERQ, and a two-factor model for FGA-TGP. After fitting each variable separately, we constructed a comprehensive structural model incorporating all latent factors, their indicators, and covariances between the latent factors. The fit of the four-measurement model was adequate: χ²(1,723) = 3,634.498, CFI = 0.906, TLI = 0.901, RMSEA = 0.043.

Figure 1 displays the full structural model incorporating the hypothesized relations between ADHD inattention, IPS, and the seven mediation constructs, which showed good fit according to the indices: χ²(1,719) = 3,485.256, CFI = 0.919, TLI = 0.914, RMSEA = 0.040 (see Supplemental Table S1). To finalize the model, we used modification indices to add additional covariates between items within the same latent factors. This modified model significantly improved the chi-square indices compared to the original model (Δχ²(4) = 120.444, p < .001) – and was therefore selected as the final version (see Supplemental Table S1).

Figure 1.

Structural model illustrating the hypothesized relationships between ADHD inattention, IPS, and the seven mediation constructs, including added covariates based on modification indices. The model demonstrates good fit to the data.

As can be seen in the model (Figure 1), higher ADHD inattention was significantly associated with all mediators. Specifically, it predicted increased levels of, ERQ suppression, sensitivity to delay and low value, as well with decreased levels of expectancy, ERQ reappraisal, TGP, and FGA. However, higher procrastination was significantly and positively predicted by higher FGA, sensitivity to delay and low value. Other mediators in the model did not significantly predict procrastination.

Table 3 summarizes the results of mediation analysis. Bootstrapped confidence intervals for indirect effects confirm that ADHD inattention predicted procrastination indirectly through mediating variables (total indirect effect = 0.595, SE = 0.092, 95% CI [0.435, 0.803]. Examination of specific indirect effects revealed that higher inattention according to the Adult ADHD Self-Report Scale (ASRS) predicted higher scores for low value and sensitivity to delay, which in turn predicted higher procrastination scores. Moreover, higher ADHD inattention predicted lower FGA, which in turn predicted higher procrastination. The indirect effects of ASRS inattention on procrastination through expectancy, TGP, and ERQ reappraisal and suppression were not significant. Additionally, the direct effect of ADHD on procrastination remained significant (total effect = 1.061, direct effect = 0.465).

Table 3.

Total Direct and Indirect Effects.

Effect	B	SE	95% CI
Total effect	1.061	0.054	[0.964, 1.174]
Direct effect	0.465	0.098	[0.259, 0.650]
Total indirect effect	0.595	0.092	[0.435, 0.803]
ADHD-Inattention-R→Expectancy→Procrastination	0.035	0.032	[−0.027, 0.101]
ADHD-Inattention-R→Low Value→Procrastination	0.418	0.137	[0.158, 0.694]
ADHD-Inattention-R→Sensitivity to Delay→Procrastination	0.156	0.070	[0.030, 0.305]
ADHD-Inattention-R→TGP→Procrastination	0.034	0.023	[−0.010, 0.081]
ADHD-Inattention-R→FGA→Procrastination	−0.071	0.029	[−0.136, −0.020]
ADHD-Inattention-R→ERQ Reappraisal→Procrastination	0.015	0.016	[−0.017, 0.049]
ADHD-Inattention-R→ERQ Suppresion→Procrastination	0.008	0.008	[−0.004, 0.028]

Note. Coefficients are unstandardized. ADHD-Inattention-R = the mean of the eight Adult ADHD Self-Report Scale-V1.1 (ASRS) inattention items (not including Item 4, which overlaps with procrastination); ERQ = Emotion Regulation Questionnaire; FGA = Flexible Goal Adjustment; IPS = Irrational Procrastination Scale; SE = standard error; TGP = tenacious goal pursuit.

Effects presented in bold are statistically significant, as indicated by 95% confidence intervals that do not include zero.

To exploratorily examine whether the model applies equally across gender/sex, a multiple group model comparison was conducted. Comparison of the unconstrained and constrained models using the chi-square difference was only marginally significant (Δχ² (Δdf = 15) = 23.89, p = .07), suggesting the model applies to both groups. A close examination of the indirect paths revealed that the path from ADHD to procrastination through FGA is significant only in the female/women group. Nevertheless, the difference between the parameter estimates was not statistically significant (p = .451). In addition, the path from ADHD to procrastination through TGP was significant in the female/women group, and the difference between the parameter estimates was statistically significant (p = .021). As the sample size was set to test the model as whole, sex/gender differences cannot be ruled out. (See full multi-group SEM results by sex/gender in the Supplemental Materials).

Discussion

The present study has examined the mechanisms underlying the complex relation between ADHD symptoms and procrastination, including several potential mediating factors according to three approaches to procrastination: the emotion-regulation perspective, the Temporal Motivation Theory (TMT), and the General Architecture for Modeling the Dynamics of Goal-Directed Motivation.

Our findings confirmed the positive association between ADHD symptoms and procrastination documented in the literature (e.g., Altgassen et al., 2019; Ferrari & Sanders, 2006; Miller, 2007; Netzer Turgeman & Pollak, 2023; Niermann & Scheres, 2014): Individuals with higher levels of ADHD inattention symptoms reported a greater tendency to procrastinate. Furthermore, the results revealed that the relation between ADHD symptoms and procrastination was indirect and pointed to several possible pathways, thereby underscoring its complexity.

It is revealing that, while in the current study, the symptoms of ADHD inattention were related to all the variables measured, the indirect effects on procrastination were not significant for most of them, as so only a few of them contribute to the prediction of procrastination beyond the influence of the others. Specifically, sensitivity to delay and low value predicted higher procrastination levels, consistent with our multifactorial weighted framework in which contributing factors affect individuals with ADHD differently. On the other hand, although first-order correlations demonstrated negative correlations between flexible goal adjustment and procrastination, in the SEM model, flexibility predicted higher levels of procrastination. These findings may suggest that while people high in flexible goal adjustment tend not to procrastinate, after controlling for other motivational factors, flexibility might reflect a tendency to replace current goals by others, thus ceasing or delaying the pursuit of the original goals.

In a notable study that explored several theories of procrastination by applying structural equation modeling to data from over 600 participants, Wypych et al. (2018) identified the lack of value (termed here low value), delay discounting (termed here sensitivity to delay), and a lack of perseverance (conceptually similar to the opposite of what was termed here tenaciousness) as significant contributors to procrastination – in another study inspired by Steel’s TMT (Netzer Turgeman & Pollak, 2023), lower expectancy and higher sensitivity to delay, but not low value, predicted procrastination beyond other factors. Common to all studies is the central role of sensitivity to delay in predicting procrastination. The differences in the findings regarding other factors may be explained by differences in the variables included in the models, the size of the samples, and the statistical procedures employed. Importantly, the current study’s large number of participants and explanatory variables reinforce the robustness of the results. It stands to reason that incorporating other explanatory variables may reveal new pathways and deemphasize others, highlighting the complexity of this relation. Further investigation is needed to understand how these factors contribute to increased procrastination.

In examining indirect pathways between ADHD and procrastination, we found that individuals with higher levels of ADHD symptoms tended to show greater sensitivity to delays and a lower perceived value of tasks, which, in turn, were associated with increased procrastination tendencies. These findings are consistent with the principles of TMT. Our results also indicate that individuals with higher levels of ADHD symptoms tended to show lower goal adjustment, which in turn predicted higher procrastination. As suggested above, flexible goal adjustment might reflect a complex trait that predicts higher procrastination when other aspects are controlled. Consequently, lower flexibility might reduce the tendency of people with ADHD to procrastinate. The revelation of indirect effects suggests that clinicians aiming to help people with ADHD cope with procrastination may focus on sensitivity to delay and task value as risk factors and maybe also on lack of flexibility as a protective factor. Notably, while ADHD was negatively related to the emotion regulation strategy of reappraisal, and positively to suppression, indicating that individuals with higher ADHD symptoms are less likely to use adaptive reappraisal and more likely to rely on suppression strategies. This pattern aligns with findings showing that adults with ADHD report reduced use of cognitive reappraisal and increased reliance on suppression compared to controls (Hirsch et al., 2022; Shaw et al., 2014). However, in the SEM model, which takes into account many motivational factors, emotion regulation strategies were not related to procrastination, thus not accounting for the link between ADHD and procrastination.

Although this study provides valuable insights into the complex relation between ADHD and procrastination, it has several limitations. First, a cross-sectional design limits the ability to establish causal relations among variables. Longitudinal studies are needed to explore temporal dynamics and potential bidirectional effects over time. Second, reliance on self-report measures introduces biases, including social desirability and response distortion, possibly impacting the accuracy of reported symptoms and behaviors. Future research should integrate a task to enhance assessment validity. Third, the sample, composed of adults recruited online, may limit generalizability to other populations, such as individuals with severe clinical ADHD symptoms. Finally, the study focused on specific mediating variables, overlooking other potential contributors such as executive functioning or environmental influences. Addressing the above limitations in future studies could help tailor interventions to support and improve outcomes for individuals with ADHD in managing procrastination.

Overall, by examining the interplay between ADHD symptoms, emotion regulation, motivation, and goal-related behaviors, our study has shed new light on the mechanisms underlying procrastination among individuals with ADHD. The findings, if replicated, have implications for the development of targeted interventions aimed at addressing procrastination and improving functional outcomes among individuals with high ADHD symptoms. Specifically, interventions for ADHD-related procrastination may focus on increasing the value of the task’s outcome (or decreasing the negative value of the task) and look for strategies to overcome the hypersensitivity to delay (for instance, by setting short-term deadlines and rewards). Future research should continue to investigate these relations using longitudinal designs and experimental methodologies to elucidate causal pathways further and inform intervention strategies.

Supplemental Material

sj-docx-1-jad-10.1177_10870547251408120 – Supplemental material for What Are You Waiting For?! Roles of Motivation, Goal Orientation, and Emotion Regulation in Explaining the Link Between ADHD and Procrastination

Supplemental material, sj-docx-1-jad-10.1177_10870547251408120 for What Are You Waiting For?! Roles of Motivation, Goal Orientation, and Emotion Regulation in Explaining the Link Between ADHD and Procrastination by Ruth Netzer Turgeman and Yehuda Pollak in Journal of Attention Disorders

Footnotes

ORCID iDs

Ruth Netzer Turgeman

Yehuda Pollak

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Ruth Netzer Turgeman is a PhD graduate of the Seymour Fox School of Education, the Hebrew University of Jerusalem, Jerusalem, Israel, and serves as a special educational supervisor at the Ministry of Education, Israel.

Yehuda Pollak is an associate professor at the Seymour Fox School of Education, the Hebrew University of Jerusalem, Jerusalem, Israel.

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What Are You Waiting For?! Roles of Motivation,Goal Orientation,and Emotion Regulation in Explaining the Link Between ADHD and Procrastination

Abstract

Objective:

Method:

Results:

Conclusions:

Keywords

Introduction

ADHD and Procrastination

Procrastination Theories

The Present Study

Method

Participants and Procedure

Measures

Results

Descriptive Statistics

Best-Fitted SEM Model Identification

Discussion

Supplemental Material

sj-docx-1-jad-10.1177_10870547251408120 – Supplemental material for What Are You Waiting For?! Roles of Motivation, Goal Orientation, and Emotion Regulation in Explaining the Link Between ADHD and Procrastination

Footnotes

ORCID iDs

Funding

Declaration of Conflicting Interests

Supplemental Material

Author Biographies

References

Supplementary Material