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Abstract

Academic procrastination, the tendency to delay academic tasks without reasonable justification, has significant implications for students’ academic performance and overall well-being. To measure this construct, numerous scales have been developed, among which the Academic Procrastination Scale (APS) has shown promise in assessing academic procrastination across various cultural contexts. However, it is essential to validate the APS in different settings and populations to ensure its reliability and validity. This study aims to comprehensively examine the psychometric properties of the APS in an Iranian sample of university students. Through two distinct yet interrelated studies involving exploratory and confirmatory factor analyses, item response theory analysis, and tests of convergent validity, we seek to establish the validity and applicability of the APS in the Iranian cultural context. The Item Response Theory analysis revealed that the items on the Academic Procrastination Scale exhibited adequate levels of difficulty, discrimination, and item information, thereby supporting the scale’s reliability and validity. Furthermore, evidence of convergent validity was established through significant correlations between the scores of the Academic Procrastination Scale and the Tuckman Procrastination Scale.

Plain language summary

Checking if the academic delay survey works for Iranian college students

Putting off school work can be a real problem for students, sometimes causing poor grades and stress. To understand why students procrastinate, scientists have made special surveys. One of these, the Academic Procrastination Scale (APS), has been useful in many countries. Yet, to be certain it works for students everywhere, we need to test it in different places, like Iran. Our research did just that. We looked closely at the APS by asking Iranian university students to fill it out. We examined every part of the survey through two studies. One study was like an exploration, checking if the questions covered different aspects of procrastination. Another confirmed what we found, ensuring that our results were trustworthy. We also used a method called ‘Item Response Theory’ to see if the survey’s questions were good at picking up on different levels of procrastination, making sure none were too easy or too hard, and that they measured what we wanted to measure. And it all checked out—the survey did its job well. To top it off, we checked if the APS results matched another well-known procrastination survey, the Tuckman Procrastination Scale. They did! This link-up means that the APS can be trusted to measure procrastination in Iranian students in a way that matches what we already know from other research. Why is this important? When we know a survey works, we use it to find students who need help managing their time and avoiding the last-minute rush. This isn’t just about grades; it’s about helping students feel less stressed and more in control. With reliable surveys, we can make a real difference.

Keywords

validation academic procrastination scale adaptation psychometric properties

Introduction

Academic procrastination refers to the tendency to delay academic tasks and activities without any reasonable justification, and is characterized by a pattern of behavior that involves frequent postponement in initiating and accomplishing such tasks (McCloskey, 2011). Academic procrastination had considerable impacts on different contexts of students’ lives and based on research it is significantly had a positive association with anxiety and depression (Brader & Luke, 2013; Tice & Baumeister, 2018; Ulgener et al., 2020), It occurs in all ages and educational levels (McCloskey & Scielzo, 2015), and it has been shown that it is more prevalent among students than other groups (Balkis & Duru, 2009; Closson & Boutilier, 2017; Steel, 2007). The detrimental effects of academic procrastination have led to the development of various scales to assess this construct. Among these scales, the Academic Procrastination Scale (APS), introduced by McCloskey (2011), has gained prominence due to its one-dimensional structure and precise focus on academic behaviors. The APS has been extensively used and validated in different cultural contexts, providing valuable insights into the prevalence and impact of academic procrastination worldwide. However, it is essential to ensure the cross-cultural validity of the APS by examining its psychometric properties in diverse settings and populations. Cultural differences can influence the way individuals perceive and respond to scale items, potentially affecting the scale’s reliability and validity in specific cultural contexts (Chakraborty & Chechi, 2019). Therefore, this study aims to validate the APS in an Iranian sample of university students.

The study of academic procrastination began in the 1980s, as researchers recognized its prevalence and negative consequences among students (Solomon & Rothblum, 1984). Since then, several studies have explored cultural variations in procrastination (Brando-Garrido et al., 2020; Mann et al., 1998; McCloskey, 2011; Kim et al., 2017; Steel, 2007). For instance, Mann et al. (1998) found that Japanese, Taiwanese, and Hong Kong students scored higher on academic procrastination compared to students from the U.S., Australia, and New Zealand. However, meta-analyses have indicated no significant variations in procrastination outcomes between the U.S. and Canada (Steel, 2007). Such cross-cultural variations highlight the need for further transcultural evidence on academic procrastination (Soares et al., 2022). In the Iranian context, research on procrastination has primarily focused on its relationship with variables such as anxiety and perfectionism (Hosseinzadeh Firouzabad et al., 2018; Sepehrian Azar, 2011; Sevari, 2011; Tamadoni et al., 2010). However, research on procrastination remains relatively rare in Iran, and more psychometrically sound tools are required to accurately measure this construct (Abdi Zarrin et al., 2019).

The Academic Procrastination Scale (APS) has emerged as a superior measure of academic procrastination due to its precise definition and exclusive focus on academic behaviors (McCloskey, 2011). Numerous studies have employed the APS in surveys, establishing significant associations between academic procrastination and academic achievement, self-efficacy, achievement motivation, and stress (Akmal et al., 2017; Batool, 2020; Itani, 2019; Muliani et al., 2020). To alleviate participant burden and save time, Yockey (2016) proposed a shortened version of the APS, known as the APS-S (Coelho et al., 2020). The APS-S has undergone validation in various countries, including Brazil (Soares et al., 2022), India (Chakraborty & Chechi, 2019), and Spain (Brando-Garrido et al., 2020). These findings suggest that the APS and its shortened version provide reliable and valid measures of academic procrastination across diverse cultural contexts.

Iranian culture is characterized by its unique values, beliefs, and social norms, which can influence individuals’ approaches to academic tasks and activities (Abdi Zarrin & Gracia, 2020). Consequently, it is crucial to validate the APS in an Iranian context to accurately measure academic procrastination within this specific population. The findings of this study will have significant implications for both researchers and practitioners working in the field of academic procrastination in Iran. By validating the APS in this cultural context, we provide researchers with a robust and reliable tool to measure academic procrastination accurately. The results will enhance our understanding of academic procrastination among Iranian students and contribute to the broader literature on procrastination in a cross-cultural perspective. Furthermore, educators and practitioners can benefit from the validated APS to identify and address procrastination-related challenges in educational settings. Developing targeted interventions and strategies to mitigate academic procrastination can lead to improved academic performance and overall well-being among Iranian students. Based on the argument presented, the main objective of this study is to comprehensively validate the APS in an Iranian sample of university students. To achieve this objective, we will conduct two distinct yet interrelated studies and employ a comprehensive methodology, including exploratory and confirmatory factor analyses, item response theory analysis, and tests of convergent validity. The first study will employ an exploratory factor analysis (EFA) to explore the underlying factor structure of the APS within the Iranian cultural context. Cultural factors can influence individuals’ perceptions and behaviors, and an EFA will ensure that the scale accurately reflects academic procrastination as perceived by Iranian students. The second study will involve confirmatory factor analysis (CFA) and item response theory (IRT) analysis to confirm and refine the factor structure of the APS in the Iranian context. CFA will rigorously assess how well the proposed one-dimensional structure aligns with the data collected from Iranian students. Additionally, IRT analysis will provide valuable insights into the psychometric properties of individual items, contributing to a more precise assessment of academic procrastination at an individual level. To establish convergent validity, we will compare the scores from the APS-S with those from the Tuchman Procrastination Scale, another widely used measure of academic procrastination. By doing so, we can assess whether the APS-S correlates with a similar construct, thereby confirming its validity and relevance in the Iranian context.

The article is organized as follows: In the following sections, we will describe the methodological approach, including the participants, measures, and data collection procedures. Subsequently, we will present the results of both the exploratory and confirmatory factor analyses, followed by the item response theory analysis. The section on convergent validity will then be presented. Finally, we will discuss the implications of our findings, provide limitations of the study, and offer suggestions for future research in this area. The paper will conclude with a summary of the study’s key contributions and its relevance to the broader field of academic procrastination research.

Method

This research is classified as an instrumental study based on Montero and Leon’s (2005) categorization. The study included a total of 813 college students, with an average age of 23.4 years (SD = 5.3). Among the participants, 68% were male, and 82% attended public universities.

Data collection was primarily conducted through social media platforms, where the survey link was disseminated. Social media proved to be the most effective means of gathering data for the study. All participants were fully informed about the study’s objectives, and their voluntary participation was sought. Prior to participation, students were made aware of the study’s purpose and provided their consent to take part. As the study was conducted anonymously, written consent was not required. Participants demonstrated their consent by voluntarily opting to participate in the research.

For the purpose of validating McCloskey’s Academic Procrastination Scale (APS) in the Iranian context, the back-translation procedure was employed following the guidelines of the International Test Commission. This procedure ensures the accuracy and equivalence of the translated version of the scale in the target language. In the first step of the back-translation procedure, the APS was translated from English to Persian by a qualified translator fluent in both languages. Subsequently, a bilingual researcher proficient in both English and Persian performed the back-translation, translating the Persian version back into English. This step aimed to verify the conceptual equivalence between the original APS and the translated version. In the next stage, a third individual, also bilingual, compared the two translations to ensure consistency and accuracy. This comparison focused more on maintaining the conceptual similarity rather than literal translation. Any discrepancies or ambiguities were addressed in this step to refine the Persian version further.

To validate the semantic equivalence of the translated version, seven students familiar with both English and Persian languages were involved in the process. They carefully examined the translated items and provided feedback on the clarity and appropriateness of the translated text. As a result of this semantic validation, it was confirmed that the translated items retained the intended meaning and did not require significant changes. During the translation process, it was identified that five items from the APS (item numbers 2, 4, 7, 17, and 23) were also part of the APS-S, a shortened version of the original scale proposed by Yockey (2016). As a result, these five items were considered separately in this study to maintain consistency with the APS-S. In conclusion, the back-translation procedure was meticulously conducted to ensure the accuracy and equivalence of the Persian version of McCloskey’s Academic Procrastination Scale for use in the Iranian context. The validation process involved multiple steps of translation, back-translation, and semantic validation, resulting in a translated version that retained the original scale’s intended meaning and maintained its conceptual equivalence. By following the International Test Commission guidelines, this study establishes the validity of the APS for measuring academic procrastination among Iranian university students.

Instrument

In addition to utilizing the Academic Procrastination Scale (APS) developed by McCloskey (2011), our study also employed two other measures of procrastination: the APS-S (Yockey, 2016) and the Tuckman Procrastination Scale (TPS; Tuckman, 1991).

The APS is a comprehensive tool designed to assess procrastination specifically related to academic tasks, such as term papers, exams, and projects. It consists of 25 statements that capture the degree of agreement or disagreement of the respondents. Participants rate each statement on a 5-point Likert scale, with options ranging from 1 (completely disagree) to 5 (completely agree). The APS offers a comprehensive evaluation of academic procrastination behaviors in the context of educational settings.

The APS-S, a shortened version of the APS, was also employed in our study. Developed by Yockey (2016), the APS-S retains a single-factor structure and comprises only five items. This concise version allows for a more time-efficient assessment of academic procrastination while maintaining the effectiveness of the original APS. Participants rate their agreement with each item on the same 5-point Likert scale as the full APS.

The third measure utilized in our study was the Tuckman Procrastination Scale (TPS), developed by Tuckman (1991). Unlike the APS, which focuses on academic procrastination, the TPS assesses the tendency to delay or postpone tasks in general, encompassing various aspects of individuals’ self-regulation abilities. It consists of 16 items that participants rate based on how well they describe themselves, using a 4-point scale (1 = that’s me for sure; 4 = that’s not me for sure). The TPS provides valuable insights into participants’ tendencies to delay tasks across different domains of their lives.

Analytical Approach

In this study, we employed three analytical approaches to answer our research questions: exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and the Item Response Theory (IRT) graded response model.

Prior to conducting the analysis, we rigorously performed data screening procedures to ensure the reliability and validity of our results. These procedures included checking for linearity, assessing multivariate normality, handling missing data, and detecting outliers.

To ensure the generalizability of our findings, we randomly divided the entire sample of participants into two parts. The first part of the sample was used for exploratory factor analysis (EFA), which allowed us to explore the underlying structure of the data and identify potential factors or dimensions related to academic procrastination. By using the principal axis factoring method with Promax rotation, we aimed to identify the distinct underlying factors related to academic procrastination as measured by the Academic Procrastination Scale (APS). This approach not only helps us determine the number of factors that explain the variance in the APS items but also provides insights into how these factors are interrelated. The use of Promax rotation enhances the interpretability of the factor structure, making it easier to understand and interpret the results, and facilitates a more comprehensive analysis of academic procrastination behaviors among the participants.

We also considered four criteria to decide how many factors to retain: Parallel analysis, the shape of the scree plot (Cattell, 1966), which shows the amount of variance explained by each factor; the eigenvalues, which measure the significance of each factor; and the meaningfulness and clarity of the factors after rotation (Kim & Mueller, 1978). According to the results of the parallel analysis, the eigenvalue from the actual data for Factor 1 (6.28) was substantially higher than the corresponding eigenvalue from the random data sets (1.52). Based on the parallel analysis, we decided to retain one factor in our factor analysis of the APS. The retained factor explains a significant amount of variance in the data and is statistically significant. The scree plot, another criterion we considered, also supported the retention of one factor, as there was a clear break after the first factor in the plot.

Furthermore, we assessed the scale’s reliability using two different indicators: McDonald’s Omega (ω) and Composite Reliability (CR). Both indicators reflect the degree to which the scale items measure a common latent construct. According to Kline (2013), ω should be higher than .70 for a reliable scale. Similarly, Fornell and Larcker (1981) and Gouveia and Soares (2015) suggested that CR should also exceed .70 for a satisfactory reliability level. Overall, the high values of McDonald’s Omega (ω) and Composite Reliability (CR) indicate that the APS is a reliable measure for capturing academic procrastination tendencies, and it can be confidently used in future research and practical applications related to academic procrastination among college students in Iran.

Following the EFA, the second part of the sample served as a separate dataset to conduct confirmatory factor analysis (CFA). CFA allowed us to test and validate the factor structure that emerged from the EFA. By using this two-step approach, we ensured the robustness and reliability of the factor structure identified during the exploratory phase. To confirm the validity of the APS factor model, we conducted a confirmatory factor analysis (CFA) on the second sample. This was done to test whether the data fit the hypothesized structure of APS and to examine its measurement properties. We used several statistical indicators to assess how well our model fit the data. These included the relative Chi-Square (χ²/df), which compares the observed and expected frequencies; the comparative fit index (CFI), which measures how much better our model is than a baseline model; the root mean square error of approximation (RMSEA), which estimates how closely our model reproduces the population covariance matrix; the standardized root mean square residual (SRMR), which evaluates how well our model reproduces the sample covariance matrix; and the Tucker-Lewis index (TLI), which adjusts for model complexity. We followed Hu and Bentler’s (1999) recommendations for acceptable values of these indicators. Overall, the CFA aimed to confirm whether the proposed APS factor model adequately represents the underlying structure of academic procrastination among Iranian college students. The statistical indicators were used to determine whether the model fits the data well and to validate the measurement properties of the Academic Procrastination Scale. By following established guidelines and criteria, we aimed to ensure that our factor model is a valid representation of academic procrastination in this specific population.

Additionally, we employed the Item Response Theory (IRT) graded response model to further analyze the APS and APS-S items. This model provided valuable insights into the item characteristics and participants’ responses, allowing for a more detailed examination of individual item performance. We applied Item Response Theory (IRT) to ensure the stability of item properties and to avoid potential biases caused by variations in the sample of respondents. Specifically, we employed a specific type of IRT model known as the Graded Response Model (GRM) proposed by Samejima (1969) to estimate item parameters, including difficulty, information, and discrimination. The GRM is particularly well-suited for ordinal response data, such as the Likert scale used in the Academic Procrastination Scale (APS), as it takes into account the ordered nature of the response categories. To evaluate the item discrimination indexes, we adopted Baker’s (2001) levels of recommendation. A discrimination index measures how well an item can differentiate between individuals with different levels of the latent trait being measured (in this case, academic procrastination). The discrimination index values can range from 0 to infinity, with higher values indicating better discrimination. Based on Baker’s classification, discrimination indexes were categorized as follows: 0 means no discrimination; very low discrimination ranges from 0.01 to 0.34; low discrimination goes from 0.34 to 0.64; moderate discrimination covers from 0.65 to 1.34; high discrimination spans from 1.35 to 1.69; and anything higher than 1.70 indicates very high discrimination. By examining the item discrimination indexes, we can determine how effectively each item in the APS contributes to differentiating individuals based on their academic procrastination tendencies. Furthermore, we analyzed the Item Information Curves and the Test Information Curve. The Item Information Curves illustrate how much information each individual item contributes to the total information of the measure. A higher Item Information Curve indicates that the item provides more precise information about an individual’s level of academic procrastination. On the other hand, the Test Information Curve depicts how well the APS as a whole differentiates individuals across the entire range of the latent trait. A sharper Test Information Curve signifies that the scale effectively distinguishes individuals with varying levels of academic procrastination. In the context of Item Response Theory (IRT), “information” refers to how well an item can discriminate among individuals who have similar levels of the underlying trait being measured (represented as θ or theta). It indicates the precision with which an item can differentiate individuals with different levels of the latent trait. Higher information values imply that the item is more informative and can better distinguish individuals based on their abilities or characteristics related to the trait being measured.

On the other hand, “location” in IRT refers to where on the latent trait scale an item provides information to differentiate among individuals’ abilities. It indicates the position or level on the latent trait at which the item contributes the most information. Items with different locations are informative at distinct points on the trait scale.

In the case of the Academic Procrastination Scale (APS), the number of location parameters is four. This indicates that the APS items have four different positions on the latent trait scale where they provide information to differentiate among individuals’ academic procrastination tendencies. The number of location parameters is one less than the number of response options in the APS, as the scale uses a five-point Likert response format (ranging from 1 to 5).

By considering information and location parameters, we can gain valuable insights into how well the APS items perform in distinguishing students’ academic procrastination levels and where on the latent trait scale the items are most informative. This analysis enhances our understanding of the APS’s measurement properties and its ability to accurately assess academic procrastination tendencies among Iranian college students. By employing IRT and examining these various indices and curves, we sought to ensure that the APS items are reliable, informative, and effective in measuring academic procrastination among Iranian college students. The application of IRT provides a comprehensive evaluation of the scale’s item properties and contributes to the robustness and validity of the Academic Procrastination Scale in our study.

Addressing Ceiling and Floor Effects: To evaluate whether the Academic Procrastination Scale (APS) is subject to ceiling or floor effects, we analyzed the distribution of scores across all items. Specifically, we examined whether a substantial number of participants scored at the extreme ends of the scale. Our analysis revealed that the distribution of responses was well-dispersed, with no significant clustering at the highest or lowest possible scores. This indicates that the APS effectively captures the full spectrum of academic procrastination behaviors, minimizing the risk of ceiling or floor effects and enhancing its utility in identifying variations among students.

Discussing Distribution and Linearity of Responses: Additionally, we assessed the distribution of responses for normality and examined the linearity between the items and the latent construct of academic procrastination. Using descriptive statistics and visual inspection of histograms, we found that the responses were approximately normally distributed, which supports the use of parametric statistical techniques in our analysis. Furthermore, we conducted tests for linearity and confirmed that the items demonstrated a consistent and linear relationship with the overall academic procrastination construct. This linearity indicates that higher scores on individual items correspond to higher levels of academic procrastination, reinforcing the validity of the APS as a measure of this construct.

Overall, our analytical approach allowed us to gain a comprehensive understanding of the underlying structure of the Academic Procrastination Scale and its shortened version, as well as providing insights into the participants’ procrastination behaviors. The combination of EFA, CFA, and IRT enhanced the validity and accuracy of our findings and contributed to a more robust analysis of academic procrastination in the Iranian university context.

Results

Prior to conducting the data analysis, data screening-related issues were considered. First, multivariate normality was assessed using graphical methods, such as Q-Q plots and histograms. The distribution of APS scores was examined to ensure that the data followed a multivariate normal distribution. Next, linearity was checked by creating scatter plots to visualize the relationship between APS scores and potential confounding variables, such as age and gender. Any non-linear patterns were addressed by considering appropriate transformations or the inclusion of interaction terms in subsequent analyses. Managing missing data was handled using multiple imputation techniques, assuming the data were missing at random. The imputed datasets were combined for subsequent analyses to avoid bias and loss of statistical power. Lastly, outliers were identified through visual inspection of box plots and z-score calculations. Extreme values were carefully examined to determine their influence on the overall dataset. Outliers were either removed from the analysis or addressed through robust statistical methods, depending on their impact on the results.

We conducted an exploratory factor analysis (EFA) on the students’ responses to the APS to examine the underlying structure of the measured variables. Before performing the EFA, we checked the suitability of factor analysis by computing the relevant indexes (KMO = 0.93 and Bartlett, χ² = 5942.6, p < .001). These indexes indicate that factor analysis is appropriate for our data set. The one-dimensionality of the scale was verified by an initial solution that used the principal axis factoring method.

The factor analysis results of the Academic Procrastination Scale (APS) indicated a theoretically significant solution, explaining 51% of the total variation in the data. The item loadings for all APS items ranged from 0.53 (item 8) to 0.80 (item 11). Importantly, all item loadings exceeded the minimum acceptable threshold of 0.30, as presented in Table 1.

Table 1.

Factorial Structure of the Persian Version of the Academic Procrastination Scale (APS).

No	Item descriptions	APS	APS-S
No	Item descriptions	Factor loadings	Factor loadings
1	*I usually allocate time to review and proofread my work	0.70
2	I put off projects until the last minute	0.72	0.77
3	I have found myself waiting until the day before to start a big project	0.75
4	I know I should work on school work, but I just don’t do it	0.64	0.59
5	When working on school work, I usually get distracted by other things	0.76
6	I waste a lot of time on unimportant things	0.72
7	I get distracted by other, more fun, things when I am supposed to work on school work	0.58	0.68
8	*I concentrate on school work instead of other distractions	0.53
9	I can’t focus on school work or projects for more than an hour until I get distracted	0.70
10	My attention span for school work is very short	0.57
11	Tests are meant to be studied for just the night before	0.80
12	*I feel prepared well in advance for most tests	0.68
13	“Cramming” and last minute studying is the best way that I study for a big test	0.76
14	*I allocate time so I don’t have to “cram” at the end of the semester	0.77
15	I only study the night before exams	0.71
16	If an assignment is due at midnight, I will work on it until 11:59	0.58
17	When given an assignment, I usually put it away and forget about it until it is almost due	0.57	0.58
18	Friends usually distract me from school work	0.74
19	I find myself talking to friends or family instead of working on school work	0.48
20	On the weekends, I make plans to do homework and projects, but I get distracted and hang out with friends	0.56
21	I tend to put off things for the next day	0.61
22	I don’t spend much time studying school material until the end of the semester	0.54
23	I frequently find myself putting important deadlines off	0.47	0.60
24	If I don’t understand something, I’ll usually wait until the night before a test to figure it out	0.77
25	*I read the textbook and look over notes before coming to class and listening to a lecture or teacher	0.78
Composite reliability (CR)		0.91	0.82
McDonald’s Omega (ω)		0.90	0.85

Note. Items with * were reverse.

The internal consistency of the APS was found to be satisfactory. The McDonald’s Omega coefficient yielded a value of 0.90, while the Composite Reliability coefficient was 0.91. Both coefficients surpassed the recommended threshold of 0.70, as suggested by previous research studies (Fornell & Larcker, 1981; Gouveia & Soares, 2015; Hayes & Coutts, 2020; Kline, 2013).

These findings support the reliability and validity of the APS as a measure of academic procrastination among Iranian college students.

Confirmatory Factor Analysis

To assess the validity of the one-dimensional structure of the Academic Procrastination Scale (APS), we conducted a Confirmatory Factor Analysis (CFA). The CFA results demonstrated that the model fit was acceptable, with good fit indices: Comparative Fit Index (CFI) = 0.97, Tucker-Lewis Index (TLI) = 0.96, and Root Mean Square Error of Approximation (RMSEA) = 0.054. Furthermore, all APS items showed significant factor loadings (lambda, λ) and were found to contribute meaningfully to the latent construct of academic procrastination (λ ≠ 0; z > 1.96, p < .001). The factor loadings ranged from 0.43 (Item 16) to 0.71 (Item 8), indicating that each item significantly and positively contributed to the overall measurement of academic procrastination. Similarly, the Confirmatory Factor Analysis for the APS-S (shortened version of the APS) demonstrated a good fit to the model. The CFA yielded satisfactory fit indices: CFI = 0.98, TLI = 0.97, and RMSEA = 0.032. Additionally, all items in the APS-S showed significant factor loadings (λ ≠ 0; z > 1.96, p < .001), ranging from 0.47 (Item 7) to 0.72 (Item 23), indicating that each item effectively measured the latent construct of academic procrastination. The main results for the two versions of the APS, namely APS and APS-S, are presented in Table 2.

Table 2.

Factorial Structure, Item Information, and Location Parameters for the Persian Version of the APS (N = 813).

Item	λ APS	λ APS-S	Item response theory
Item	λ APS	λ APS-S	a	b ₁	b ₂	b ₃	b ₄
1	0.55		1.31	−1.44	−0.06	1.45	3.13
2*	0.59	0.64	1.21	−1.78	−0.32	1.64	4.15
3	0.50		1.20	−1.60	−0.18	1.46	3.12
4*	0.48	0.70	1.82	−1.22	−1.07	1.28	2.63
5	0.63		1.53	−1.35	−0.15	1.30	2.67
6	0.56		1.93	−1.16	−0.02	1.28	2.42
7*	0.54	0.47	1.53	−1.24	−0.07	1.44	3.52
8	0.71		1.57	−1.31	−0.03	1.36	3.29
9	0.67		1.63	−1.15	0.10	1.50	2.77
10	0.51		1.13	−1.33	0.13	1.80	3.67
11	0.63		0.99	−1.71	−0.15	1.76	3.48
12	0.49		1.25	−1.22	0.05	1.69	3.29
13	0.70		1.06	−1.38	−0.03	1.61	3.73
14	0.55		0.99	−1.56	−0.08	1.91	4.06
15	0.55		0.74	−1.84	−0.10	2.48	5.20
16	0.43		1.30	−1.07	0.18	1.53	2.66
17*	0.44	0.70	1.44	−1.18	0.12	1.54	2.32
18	0.55		0.75	−2.13	−0.55	2.00	4.12
19	0.49		0.92	−1.98	−0.34	1.83	4.36
20	0.55		1.33	−1.42	−0.19	1.46	3.13
21	0.45		1.67	−0.94	0.05	1.45	2.54
22	0.48		1.73	−1.05	0.04	1.33	2.17
23*	0.46	0.72	1.13	−1.56	−0.28	1.60	2.92
24	0.51		1.53	−1.29	−0.06	1.32	2.13
25	0.64		1.18	−1.58	−0.14	1.41	2.30

Note. λ = loading factors; a = discrimination; b_1–4 = difficulty. Items with * included in the shorter version.

Item Response Theory

We employed Item Response Theory (IRT) models to thoroughly examine the properties of each item in the Academic Procrastination Scale (APS) and how well they measure different levels of academic procrastination among participants. One of the key aspects we investigated was the discriminative ability of each item, which refers to the item’s capability to differentiate between individuals with varying degrees of academic procrastination. According to Baker’s (2001) classification, three items in the APS demonstrated very high discrimination values (λ > 1.70), specifically items 4, 6, and 22. These items were particularly effective in distinguishing between individuals with significantly different levels of academic procrastination. Additionally, seven items exhibited high discrimination values (λ > 1.34 and λ < 1.69), including items 5, 7, 8, 9, 17, 21, and 24. These items were also valuable in discriminating between participants with varying degrees of procrastination. Furthermore, fifteen items showed moderate discrimination values (λ > 0.65 and λ < 1.34), indicating their ability to differentiate to some extent between individuals with different levels of academic procrastination. In IRT, items are also characterized by their difficulty parameters or item thresholds, which represent the level of the latent trait (academic procrastination in this case) required to answer the items correctly. Items with lower difficulty parameters are considered “easier” and can be answered by individuals with lower levels of the trait, while items with higher difficulty parameters are considered “harder” and necessitate higher levels of the trait to be answered correctly.

To ensure the reliability of the APS, we selected items that fell within an appropriate difficulty range, commonly between −2 and 2 (Rauthmann, 2013). These items are optimal for measuring academic procrastination across the range of participants’ trait levels.

Overall, our IRT analysis provided valuable insights into the APS items’ discriminative properties and difficulty levels, enhancing our understanding of how well the scale measures academic procrastination among participants. The findings contribute to the validity and effectiveness of the APS as a reliable measure of academic procrastination tendencies in our study population. Additionally, the individuals’ trait levels, represented by the location estimates (b₁ for lower performance and b₃ for higher performance), further support the differentiation among participants based on their academic procrastination levels (Molina et al., 2020).

We further explored the Test Information Curve and Item Information Curves to gain insights into the amount of information provided by the Academic Procrastination Scale (APS) items and the overall scale. These analyses allowed us to understand the scale’s measurement precision and the extent to which individual items contribute to accurate measurements of academic procrastination. The Item Information Curves revealed that most of the APS items had satisfactory levels of information, indicating their ability to provide reliable measurements of academic procrastination across varying levels of the latent trait (theta). Specifically, Item 15 demonstrated the least informative property among all items, while Item 6 was identified as the most informative item.

The Test Information Curve, depicted in Figure 1, showed the cumulative information available from all APS items across different levels of the latent trait (theta). The top line in the figure represented the amount of information obtained when considering theta values within a range of ±3. This range indicates the degree of agreement or disagreement with academic procrastination tendencies. The bottom line in the figure indicated the level of uncertainty in the estimation. As the amount of information increases on the Test Information Curve, the error in the estimation decreases, indicating a higher precision in measuring academic procrastination. Conversely, when the information decreases, the error in measurement increases, leading to reduced precision. The best level of information for this scale was observed between theta values of −1 and 2.5, indicating that the APS works particularly well for individuals who exhibit academic procrastination tendencies within this range.

Figure 1.

Test information function of APS with standard errors.

To assess the convergent validity of the Academic Procrastination Scale (APS) and the shortened version, APS-S, we examined their relationships with scores from the Tuckman Procrastination Scale (TPS). The results revealed a strong positive correlation between the TPS scores and both the APS (correlation coefficient = 0.80) and APS-S (correlation coefficient = 0.78). This finding indicates that participants who scored higher on the TPS, reflecting a greater tendency to delay tasks, also tended to score higher on both versions of the APS, demonstrating a consistent pattern of academic procrastination.

Next, we evaluated the reliability of the APS and APS-S by employing three estimators of internal consistency. The results indicated that both versions exhibited satisfactory levels of internal consistency reliability. Specifically, the APS demonstrated strong internal consistency, with McDonald’s Omega (ω) = 0.89, Composite Reliability (CR) = 0.91, and Marginal reliability = 0.89. Similarly, the APS-S also exhibited acceptable internal consistency, with McDonald’s Omega (ω) = 0.78, Composite Reliability (CR) = 0.80, and Marginal reliability = 0.80. These findings align with the criteria proposed by Gouveia and Soares (2015) and Kline (2013), affirming the reliability of both versions of the APS for measuring academic procrastination tendencies in our study population. The robust internal consistency of the APS and APS-S suggests that the items consistently assess the underlying construct of academic procrastination and provide reliable measurements across different samples and settings.

Overall, the strong positive correlations with the TPS scores and the satisfactory internal consistency reliability indicate that the APS and APS-S are valid and dependable measures for capturing academic procrastination tendencies among participants in our study. These results enhance the credibility of the APS and APS-S as valuable tools for future research and practical applications in the field of academic procrastination research.

Discussion

Students’ lives are significantly affected by academic procrastination, which is associated with various important factors, such as reduced self-confidence, increased levels of academic stress, and dread of not succeeding. To examine academic procrastination more comprehensively, it is necessary to create and adapt technics and instruments that are based on evidence and have credibility. Instead of measuring procrastination in general, the APS is a reliable instrument that concentrates on the specific domain of academic performance (Soares et al., 2022). This paper reports on the psychometric properties of the APS, and the procedure of testing it with a group of university students from Tehran, Iran that reflects the population. The primary objectives of this research were to examine the validity and reliability of the APS in Iran. We also tested the APS-S, which is a shorter version of the APS and Tuckman’s procrastination scale was used to provide convergent validity.

We evaluated the APS’s factorial structure in two steps. First, we checked its psychometric suitability by exploratory factor analysis and found evidence for McCloskey’s (2011) proposed unifactorial structure. Secondly, confirmatory factor analysis was used to validate the one-dimensional model. We also evaluated how well the APS-S, a measure created by Yockey (2016), works as a psychological test. The measure had a good fit to the data, which means that its structure is appropriate for the Iranian context, just like it was for its original version. The measure scores of both versions of the APS were consistent over time, showing adequate reliability results (higher than .70; Kline, 2013). The IRT approach was used to evaluate the properties of each item in the test (Item information, discrimination and difficulty). They measured how much information each item provided about the examinees’ ability level, how well each item distinguished between examinees with different ability levels, and how challenging each item was for the examinees.

According to Baker (2001), the analysis of the results revealed that most of the items had a satisfactory or excellent ability to differentiate between respondents with different levels of the construct being measured. Discrimination level of two items (Items 18 and 19) were estimated below 1, However, they were at moderate level. Other analyses showed that these items had acceptable measurement qualities, even though their values were not very strong. For this reason, we decided to keep these items in the final version of the APS that we will use in Iran. The APS items show a strong ability to differentiate between people who have varying degrees (e.g., low and high) of academic procrastination. This means that the APS items can accurately identify how much someone delays or avoids their academic tasks. Moreover, the APS-S items had very strong discrimination levels, suggesting that the measure’s shorter version can distinguish well among different responses. The APS had appropriate difficulty levels that were neither too hard nor too simple (Rauthmann, 2013). This suggests that participants would not completely agree or disagree with the items, but give different answers when responding to them. People who delay their academic tasks also tend to procrastinate more in other areas of life, repeating these behaviors in other daily activities and this led us to select a more specific scale (McCloskey & Scielzo, 2015). We also examined how well the APS and APS-S scores matched with scores of a general procrastination measure (TPS).

The article will conclude with a comprehensive summary of the study’s key contributions and its significance in the broader field of academic procrastination research. The findings of this study, focusing on the psychometric properties of the Academic Procrastination Scale (APS) in an Iranian context, hold immense value for both researchers and practitioners in understanding and addressing academic procrastination.

Firstly, the study’s contribution lies in the successful validation of the APS in an Iranian sample of university students. By conducting rigorous exploratory and confirmatory factor analyses, item response theory analysis, and tests of convergent validity, the study ensures that the APS accurately captures academic procrastination behaviors specific to the Iranian cultural context. This validation serves as a reliable and valid tool for future research on academic procrastination in Iran, providing researchers with a standardized instrument to assess and compare procrastination levels among Iranian students. Moreover, the establishment of a validated APS in Iran contributes to the body of literature on cross-cultural variations in academic procrastination, shedding light on how cultural factors can influence procrastination behaviors.

Secondly, the study’s findings offer valuable insights into the underlying structure of the APS in Iran. By conducting both exploratory and confirmatory factor analyses, the study confirms the one-dimensional structure of the APS in the Iranian context. This information is crucial for researchers and practitioners, as it confirms that the APS measures a unified construct of academic procrastination in the Iranian student population. Moreover, the study’s application of item response theory analysis provides psychometric parameters at the individual level, offering a deeper understanding of how each item contributes to the overall assessment of academic procrastination. This information aids researchers and educators in identifying specific procrastination behaviors and tailoring interventions to address individual students’ needs.

Thirdly, the study’s assessment of convergent validity by comparing the APS-S scores with those from the Tuchman Procrastination Scale strengthens the APS’s validity in Iran. The positive correlations between these two scales demonstrate that the APS-S is measuring a similar construct as the widely used Tuchman Procrastination Scale. This finding further solidifies the APS’s relevance and applicability in the Iranian context and provides evidence of its validity as a measure of academic procrastination among Iranian students.

The significance of this study extends beyond its contributions to the Iranian context. The thorough validation of the APS in Iran offers a methodological model for future research on the psychometric properties of measures in other cultural contexts. The study’s comprehensive approach, involving both exploratory and confirmatory analyses, item response theory, and tests of convergent validity, serves as a blueprint for researchers interested in assessing and validating scales in different cultural settings. Researchers can draw from this study’s methodology to ensure the reliability and validity of academic procrastination measures in diverse populations, thereby advancing the understanding of procrastination behaviors globally.

Moreover, the validated APS in Iran serves as a valuable resource for the broader field of academic procrastination research. By providing researchers with a standardized measure of academic procrastination specific to the Iranian context, the study enables cross-cultural comparisons and meta-analyses. This, in turn, fosters a more comprehensive understanding of academic procrastination and its impact on students’ lives worldwide. Additionally, the APS’s applicability in Iran allows for comparative studies on academic procrastination behaviors between different cultural groups, contributing to a richer understanding of cultural variations in procrastination.

To address the sociocultural nuances relevant to academic procrastination, incorporating biopsychosocial perspectives is pertinent. This theoretical framework emphasizes the interaction of biological, psychological, and sociocultural factors, illuminating how cultural norms and gender expectations in Iran may influence procrastination behaviors. For instance, gender-specific societal pressures and expectations can manifest as academic procrastination, with potential variations in how males and females respond to academic demands and stressors. Future research could integrate biopsychosocial insights to explore these dynamics, offering a more comprehensive understanding of academic procrastination in Iranian society.

Conclusion

In conclusion, this study’s conclusion will present a synthesis of its key contributions to the field of academic procrastination research. The successful validation of the APS in an Iranian sample, along with its underlying factor structure and convergent validity, strengthens the APS’s relevance and applicability in the Iranian context. Furthermore, the study’s methodological approach provides a valuable model for researchers investigating the psychometric properties of measures in diverse cultural settings. Ultimately, the study’s findings and implications extend to the broader field of academic procrastination research, fostering cross-cultural comparisons and enhancing the understanding of procrastination behaviors on a global scale.

This study, like any other research project, has some limitations that need to be addressed. Our studies employed a sample that was not selected randomly, which limits the extent to which our results can be applied to other contexts. In our opinion, to ensure the validity and reliability of the APS and APS-S scales in various Iranian settings (e.g., Students from different universities and cities), it would be necessary to conduct more studies with larger sample sizes and using random sampling methods, if it is to be used in other universities and cities other than Tehran. Another possible area for future research would be to examine how consistent the APS and APS-S scores are over time and by creating the standard tables it can help to understand the meaning of the scores on the scale. The instruments used in this research (APS and APS-S) have higher validity when measuring the extreme cases of academic procrastination. This means that they can identify students who procrastinate a lot in their academic tasks more accurately. These scales were more dependable for identifying students who procrastinate a lot in their academic tasks. That is, they had more accuracy in detecting high levels of academic procrastination among students and One can infer from this that it is difficult to obtain accurate measurements of procrastination when it occurs at a low frequency. Another limitation of our study was self-report nature of the APS. Self-report measures may introduce bias in the responses of the participants, who might not report their actual situation due to social desirability. A way to address this issue in future studies could be to develop a scale that measure academic procrastination with indirect items and it could be implemented in a study by situational judgment test development approach.

Footnotes

ORCID iDs

Mahdi Ghorbankhani

Keyvan Salehi

Statements and Declarations

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Psychometric Properties of the Academic Procrastination Scale in an Iranian Sample