Procrastination, defined as the voluntary delay of intended tasks despite expecting negative consequences, is a pervasive self-regulation difficulty among university students (Steel, 2007; Khan et al., 2024). Nursing students, who must juggle demanding theoretical coursework and time-sensitive clinical responsibilities, are considered an at-risk group for maladaptive time management behaviors.

Recent empirical evidence indicates that the prevalence of procrastination among nursing students ranges from moderate to high. In a large multi-institutional study in Türkiye, 62.4% of nursing students demonstrated moderate levels of academic procrastination, and poor time management was a significant predictor (Çingöl and Karakaş, 2023). A study conducted in India similarly reported that 68% of nursing students exhibited moderate procrastination, with heavy academic workload and avoidance behaviors noted as contributing factors (Yousuf et al., 2024). In Indonesia, Khotimah et al. (2022) found a strong negative correlation between time management ability and academic procrastination among nursing students, strengthening the behavioral relevance of this pattern.

From a behavioral-health perspective, procrastination has broader implications beyond academic performance. The Procrastination–Health Model (Tice and Baumeister, 1997; Sirois et al., 2003; Sirois and Pychyl, 2013) posits two mechanisms linking procrastination to poorer well-being:

Empirical evidence supports these pathways. For example, Sirois (2023) demonstrated that chronic procrastination leads to poorer health outcomes by elevating stress levels and diminishing engagement in self-care behaviors. Likewise, Johansson et al. (2023) found that higher levels of procrastination correlate with poorer self-rated health and more frequent physical complaints.

In educational contexts, procrastination is understood as a failure of self-regulation, particularly in time management. Research demonstrates that well-structured time management interventions can reduce academic procrastination and improve students’ academic performance (Zhao et al., 2021). However, the effectiveness of such interventions depends on the pedagogical quality and structure of instruction.

In the post-pandemic higher education context, instructional delivery methods have diversified, with increasing interest in online and hybrid formats. Emerging evidence suggests that learning effectiveness and student engagement may be comparable across instructional modalities, highlighting the need for theory-driven and scalable educational interventions (So et al., 2025).

Slavin’s Effective Teaching Model (1984) offers a strong pedagogical framework that highlights the central role of instructional quality, the suitability of instruction to learners’ needs, motivational support, and active use of learning time. These elements closely align with the cognitive and behavioral skills essential to effective time management.

Given the high prevalence of procrastination among nursing students and the documented impact on well-being and academic success, there is a clear need for theory-driven, evidence-based time management interventions within nursing education. This study, therefore, aimed to evaluate the effectiveness of a structured time management training program—grounded in Slavin’s Effective Teaching Model and informed by the Procrastination–Health Model—in improving time use and reducing procrastination behaviors among nursing students.

By integrating an educational model with a behavioral-health model, this study contributes to nursing science through a dual-theoretical perspective on self-regulation and professional preparedness.

Although the change in the total score of the General Procrastination Tendency Scale was not statistically significant, the slight reduction in mean values may indicate an early cognitive shift rather than an immediate behavioral change. In contrast, a statistically significant increase was observed in the Effective Use of Time subscale, suggesting a meaningful improvement in students’ planning, prioritization, and scheduling behaviors. Additionally, a significant decrease in Academic Procrastination Scale scores was found following the intervention, indicating a reduction in academic procrastination behaviors. These findings suggest that the Slavin model–based time management training was effective in enhancing time management skills and reducing academic procrastination, even though broader procrastination tendencies may require longer-term interventions to demonstrate substantial change.

As shown in Figures 1, 2, the largest proportion of participants were aged 22 years and over (40.3%), followed by those aged 21 years (33.9%) and 20 years and under (25.8%). In terms of gender distribution, the majority of participants were female (71.0%), while males accounted for 29.0% of the sample.

As shown in Figure 3, 66.1% of the participants reported that a single day was generally insufficient to complete their tasks, while 72.6% stated that they enjoyed their daily routines. Despite this, a large proportion of students reported not using structured planning tools, with 75.8% indicating that they did not use an agenda and 64.5% reporting that they did not utilize online applications to organize their daily activities. In contrast, 67.7% of the participants reported mentally planning the following day, and the same proportion indicated having a mental plan regarding their future. Overall, these findings suggest that while nursing students tend to rely on cognitive and informal planning strategies, the use of formal time-management tools remains limited, underscoring the need for structured time-management training within nursing education programs.

As presented in Table 3, the pre-test mean score of the General Procrastination Tendency Scale was 50.53 ± 12.51, while the post-test mean score slightly decreased to 50.00 ± 8.03. Similarly, the mean score of the Procrastination subscale decreased from 26.21 ± 12.38 at pre-test to 23.65 ± 7.71 at post-test. In contrast, the Effective Use of Time subdimension showed an increase in mean scores, rising from 24.32 ± 6.64 before the intervention to 26.35 ± 4.36 after the intervention. Notably, the Academic Procrastination Scale mean score demonstrated a substantial decrease from 54.11 ± 13.10 at pre-test to 44.88 ± 10.40 at post-test, indicating a reduction in academic procrastination following the intervention.

As shown in Table 4, no statistically significant differences were observed between pre-test and post-test scores for the total score of the General Procrastination Tendency Scale (Z = −0.15, p = 0.877) or for its Procrastination subscale (Z = −1.46, p = 0.142). These findings suggest that general procrastination tendencies remained relatively stable over the course of the intervention.

In contrast, a statistically significant improvement was observed in the Effective Use of Time subscale, with post-test scores higher than pre-test scores (Z = −2.29, p = 0.022). The corresponding effect size indicated a small-to-moderate magnitude of change (r = 0.29), suggesting a meaningful, albeit modest, improvement in students’ time-management behaviors following the training.

Additionally, scores on the Academic Procrastination Scale showed a statistically significant decrease after the intervention (Z = −3.78, p < 0.001). The associated effect size was in the medium-to-large range (r = 0.48), indicating a notable reduction in academic procrastination. Taken together, these results suggest that while broader procrastination tendencies may be relatively resistant to short-term change, the intervention was associated with meaningful improvements in context-specific academic procrastination and functional time use.

The present study demonstrated that a time-management training program grounded in Slavin’s Effective Teaching Model was associated with a significant reduction in nursing students’ academic procrastination and a significant improvement in their effective use of time. These findings suggest that students became more capable of planning, prioritizing, and structuring their academic responsibilities—skills consistently linked to academic performance and self-regulated learning in nursing education (Çingöl and Karakaş, 2023; Zhao et al., 2021). The results align with earlier evidence, including Britton and Tesser’s (1991) foundational work, indicating that structured, theory-informed instruction in planning and scheduling can strengthen students’ time-management behaviors and academic engagement. In line with more recent studies, our findings also suggest that self-regulation interventions embedded within a coherent pedagogical framework may be particularly effective in addressing context-specific academic procrastination (Khotimah et al., 2022; Suárez Perdomo and Ruiz Alfonso, 2024). Importantly, higher scores on the Effective Use of Time subdimension indicate more effective time-management behaviors; therefore, the observed post-test increase reflects an improvement in students’ functional planning and scheduling skills rather than an increase in procrastination.

Despite these improvements, no statistically significant changes were observed in the total score of the General Procrastination Tendency Scale or its Procrastination subdimension. This finding suggests that deeply ingrained procrastination tendencies may be less responsive to short-term, skills-focused interventions and may instead require longer-term or multi-component approaches to change. This interpretation is consistent with previous research characterizing general procrastination as a relatively stable, trait-like pattern that is resistant to brief educational programs (Sirois, 2023; Johansson et al., 2023). From the perspective of the Procrastination–Health Model (Tice and Baumeister, 1997; Sirois, 2023; Sirois and Pychyl, 2013), the present findings may reflect a distinction between early cognitive and motivational shifts triggered by the intervention and the slower translation of these changes into broader, habitual behavior. Accordingly, the observed reduction in academic procrastination may represent an initial stage of change, whereas the stability of general procrastination scores suggests that sustained practice, reinforcement, or extended intervention duration may be necessary for more pervasive behavioral change to occur.

Following clarification of the Academic Procrastination Scale scoring, the observed decrease in APS scores indicates a meaningful reduction in academic procrastination after the intervention. This improvement can be directly linked to the active components of the training program, particularly the structured planning exercises and the time-blocking workshop, which encouraged students to allocate study time more deliberately and engage with academic tasks in a timely manner. Within Slavin’s QAIT framework, these components primarily address the “Time” dimension by increasing engaged learning time and the “Appropriateness” dimension by aligning strategies with students’ academic demands and skill levels. Additionally, goal-setting, feedback, and self-monitoring activities likely contributed through the “Incentive” component by enhancing motivation and sustained task engagement, while the structured and interactive delivery of content supported instructional “Quality.” Together, these elements provide a coherent pedagogical explanation for the observed reduction in academic procrastination.

Several elements of Slavin’s Effective Teaching Model (1984) likely contributed to the effectiveness of the intervention. High-quality instruction—including clear examples, planning templates, and structured learning tasks—may have enhanced comprehension and supported skill acquisition, consistent with recent work on instructional quality in nursing education (Slavin, 1984). Instructional appropriateness, tailored to the unique academic and clinical demands of nursing students, likely promoted engagement and self-regulation (Çingöl and Karakaş, 2023). Likewise, the incentive component, reinforced through motivational feedback and explicit links between time management and future professional roles, may have strengthened students’ intrinsic motivation, paralleling evidence that motivational processes shape procrastination behaviors (Eren and Coşkun, 2016). Active learning strategies, including time-blocking workshops and weekly planning exercises, also appear to have facilitated the translation of instruction into practice, as reflected by improvements in the Effective Use of Time subscale. Taken together, these mechanisms support the notion that Slavin’s instructional framework can enhance academic self-regulation among nursing students.

From an educational perspective, the findings underscore the value of integrating structured time-management training into nursing curricula. Given the intensity of both academic and clinical demands in nursing education, supporting students in developing effective time-use habits early in their training may be critical for academic success and professional preparedness (Zhao et al., 2021). While the current intervention demonstrated positive effects on academic procrastination and functional time use, future programs may benefit from incorporating additional components such as cognitive–behavioral strategies, stress-management techniques, and self-efficacy enhancement to more comprehensively address the behavioral and motivational dimensions of procrastination (Rabin et al., 2011; Salguero-Pazos and Reyes-de-Cózar, 2023). Moreover, longitudinal research is needed to examine whether these improvements are sustained over time and to explore potential moderating factors, such as individual characteristics and demographic variables, that may influence the effectiveness of the intervention. Although a separate manipulation check was not conducted, the Effective Use of Time subdimension served as a meaningful indicator of participants’ engagement with the intervention, as it directly captures the planning and scheduling behaviors targeted by the training. Improvements observed in this subdimension therefore suggest that participants actively applied the strategies introduced during the program, providing indirect support for the effectiveness of the intervention (Sirois et al., 2003).

Beyond the observed outcomes within a face-to-face instructional format, the present findings also point to broader implications for scalability and instructional delivery. Recent multi-year evidence from higher education indicates that learning effectiveness, student participation, and satisfaction may be largely comparable across online and face-to-face instruction. In a large pre–post analysis spanning five academic years, So et al. (2025) reported similar levels of enrollment, attendance, and satisfaction across 118 face-to-face and 110 online courses, supporting the equivalence of instructional modalities and highlighting the potential of hybrid delivery models.

In this context, the theory-driven time-management training evaluated in the present study appears well suited for adaptation to online or hybrid formats without compromising core educational outcomes. Consistent with QAIT principles, such adaptations could maintain instructional quality, appropriateness, incentive, and engaged learning time while expanding access and reach. Future implementations may also benefit from aligning outcome monitoring with participation indicators emphasized by So et al. (2025), including enrollment, attendance, completion, and satisfaction.

Because the study was conducted within a single nursing program, the findings should be interpreted in relation to this specific educational context. Differences in instructional delivery and clinical training across institutions may influence the applicability of the results, underscoring the need for replication in diverse academic settings.

This study has several limitations that should be considered when interpreting its findings. First, the use of a single-group quasi-experimental design limits causal inference, as the absence of a control or comparison group makes it difficult to rule out alternative explanations such as maturation, testing effects, or regression to the mean. Second, the sample consisted of volunteer nursing students from a single institution, which may restrict the generalizability of the findings to nursing students in other educational settings with different curricular structures, instructional approaches, or clinical training models. Although nursing programs in Türkiye share nationally defined core requirements, institutional differences may influence students’ time-management behaviors and their responses to intervention.

Another important limitation is the exclusive reliance on self-report measures. While self-report instruments are useful for capturing perceived changes in time management and procrastination, they may be influenced by response bias, including social desirability or increased self-awareness following the intervention, and may not fully reflect actual behavioral change. In addition, the relatively short duration of the intervention and the absence of short-term or long-term follow-up assessments limit conclusions regarding the sustainability of the observed improvements. Without follow-up data, it remains unclear whether reductions in academic procrastination and improvements in time use represent enduring behavioral change or short-term post-intervention effects. Future research would benefit from randomized controlled designs, multi-site sampling, extended follow-up periods, and the inclusion of objective behavioral indicators—such as digital time-use records or task-completion logs—to provide a more comprehensive understanding of the long-term effects of time-management interventions on academic self-regulation.

This study shows that clear, well-structured, and theory-informed instruction can help nursing students strengthen their time-management behaviors and reduce academic procrastination. Although general procrastination tendencies remained unchanged, the improvements observed in academic behaviors suggest that meaningful change is possible when students receive guidance that supports engagement, clarity, and purposeful practice.

Going forward, nursing programs may benefit from integrating time-management training more intentionally across both classroom and clinical settings, allowing students to apply these skills in real learning environments. Faculty development focused on effective instruction and supportive feedback can further enhance students’ self-regulation. Because deeper procrastination patterns often relate to stress and coping, offering mentoring, digital planning tools, and well-being resources may help sustain long-term behavioral change. By fostering a supportive and responsive educational environment, nursing schools can better equip students for the complex demands of academic work and the realities of professional nursing practice.