Mindfulness and problematic smartphone use: indirect and conditional associations via self-regulated learning and digital detox

Abstract

Previous research indicates that mindfulness is associated with lower levels of addictive behaviors, including problematic smartphone use. However, the mechanisms underlying this relationship remain insufficiently explored. Self-regulated learning has been identified as a process that may partially account for this association, while digital detox practices may be associated with stronger self-regulation. Yet, these factors have rarely been examined together within a single model of problematic smartphone use. This study aimed to investigate the mediating role of self-regulated learning and the moderating role of digital detox in the relationship between mindfulness and problematic smartphone use among 1,241 Chinese college students from Shandong Xiehe University. Participants completed the Mindful Attention Awareness Scale (MAAS), the Problematic Smartphone Use Scale (PSU), the Self-Regulation of Learning Self-Report Scale (SRL-SRS), and the Digital Detoxification Scale (DDS). The results showed that mindfulness was negatively associated with problematic smartphone use, and self-regulated learning partially mediated this association. Further analysis indicated a significant interaction between digital detox and self-regulated learning in relation to problematic smartphone use. These results are consistent with a complex pattern in which mindfulness is linked to lower problematic smartphone use partly via self-regulated learning, with digital detox associated with a stronger negative association between self-regulated learning and problematic smartphone use. Given the cross-sectional design, these findings should be interpreted as associations rather than causal effects. This study contributes to clarifying the mechanisms underlying the association between mindfulness and problematic smartphone use, highlighting the relevance of promoting self-regulated learning and digital detox strategies.

Introduction

Smartphones have become integral to university students’ daily routines, offering a wide range of academic and social functions [1]. However, excessive smartphone use—often referred to as “problematic smartphone use”—raises significant concerns, as it disrupts academic performance, social interactions, and overall well-being [2, 3]. Mindfulness has been consistently associated with lower levels of compulsive smartphone use [4, 5]. By fostering self-awareness and emotional regulation, prior work reports lower detrimental patterns of technology engagement among participants exposed to mindfulness-based programs [6].

In addition, self-regulated learning—entailing proactive management of one’s cognitive, emotional, and behavioral processes—appears to play a critical role in the relationship between mindfulness and problematic smartphone use [7, 8]. Poor self-regulation has been linked to heightened addictive behaviors, whereas mindfulness training is associated with higher self-regulatory capacities [9, 10]. Furthermore, digital detox, defined as a deliberate pause from digital device use, may buffer against excessive smartphone reliance by minimizing distractions and reinforcing self-regulation [11, 12].

Positive psychology emphasizes the role of mindfulness is associated with well-being, self-awareness, and adaptive functioning, highlighting its capacity to counteract maladaptive behaviors such as problematic smartphone use [40, 41]. Within this perspective, mindfulness is regarded as a psychological strength that fosters intentional actions and healthier patterns of technology engagement [42].

Self-regulation theory further clarifies the mechanisms that link mindfulness to problematic smartphone use. Mindfulness promotes attentional control, emotional regulation, and reflective awareness, which are central to self-regulated learning [46]. These processes enable students to plan, monitor, and evaluate their behaviors more effectively, thereby decreasing the likelihood of compulsive smartphone use.

The dual-systems model offers a complementary lens, distinguishing between reflexive systems, which drive impulsive behaviors, and reflective systems, which involve deliberate self-regulation. Problematic smartphone use often reflects an imbalance favoring the reflexive system. Mindfulness is associated with higher self-regulatory capacities and is linked to a more active reflective system, which relates to lower impulsive technology-related behaviors [40]. Collectively, these frameworks provide a coherent theoretical basis for understanding how mindfulness influences problematic smartphone use directly, how self-regulated learning may function as a mediator, and how digital detox may serve as a moderator that reinforces self-regulatory processes.

This study contributes to the existing literature in three main respects. First, it simultaneously incorporates self-regulated learning as a mediating variable and digital detox as a moderating variable within a conditional process model of problematic smartphone use, an approach that has seldom been applied in university populations. Second, it extends theoretical perspectives on positive psychology and self-regulation by examining the interrelations among these constructs in a large sample of Chinese college students. Third, it employs validated Chinese adaptations of established instruments (MAAS, PSU, SRL-SRS, DDS), thereby ensuring measurement consistency and facilitating comparison with previous research while testing the integrated model in this context. Accordingly, the study assesses whether self-regulated learning mediates the association between mindfulness and problematic smartphone use, and whether digital detox moderates this indirect relationship, to advance a more refined framework for understanding problematic smartphone use among university students.

Mindfulness and problematic smartphone use

Although smartphones provide students with diverse academic and social benefits, their excessive use raises concerns regarding negative impacts on performance and well-being. Smartphones also facilitate academic learning by providing access to online libraries, research databases, and collaboration tools, thereby enhancing students’ learning experiences [1]. However, the pervasive use of smartphones among students has raised concerns about their negative impacts, particularly when usage becomes excessive or addictive [2].

Problematic smartphone use, often classified as a non-chemical behavioral addiction, is characterized by compulsive usage patterns that interfere with daily life, social interactions, and academic performance [3]. Recent studies indicate that university students are among the most affected demographic groups, as smartphones have become essential for both social engagement and academic activities [13, 14]. While smartphones offer various benefits, such as promoting social connectivity and providing learning resources, excessive use can lead to adverse psychological, social, and physical outcomes.

Mindfulness, which is defined as the practice of maintaining present-moment awareness without judgment, has been associated with lower levels of addictive behaviors. These practices empower individuals to cultivate a more intentional and balanced relationship with technology. Mindfulness meditation, in particular, is associated with lower reactivity to digital distractions, clearer mental states, and overall well-being [15]. Techniques such as mindful breathing and body scan meditation help individuals sustain present-moment attention and reduce automatic reactivity to digital distractions [16].

Several studies emphasize the effect of mindfulness on problematic smartphone use. Research has demonstrated that mindfulness is negatively associated with problematic smartphone use [4, 5, 17, 18]. Experimental evidence also supports the effectiveness of mindfulness interventions on problematic smartphone use. For instance, a recent study investigated the effect of a brief online mindfulness-based intervention on mobile phone addiction [6]. The findings revealed that the intervention effectively reduced mobile phone addiction. These results align with previous studies demonstrating that high mindfulness plays a crucial role in reducing problematic smartphone use [19–21].

Although several studies have conceptualized mindfulness as a moderating factor that buffers the adverse effects of problematic technology use, the present study treats mindfulness as an antecedent variable. This perspective is consistent with self-regulation theory, which emphasizes the role of mindfulness in fostering attentional control, emotional regulation, and reflective awareness ( [46]– [47]). These processes are not merely protective but actively contribute to the development of self-regulation skills. In turn, enhanced self-regulation reduces susceptibility to compulsive smartphone use. On this basis, mindfulness is examined here as a predictor that shapes self-regulatory capacity and subsequent smartphone behaviors, rather than solely as a moderating influence. Therefore, based on previous research consistently supporting the theoretical perspective suggesting that higher levels of mindfulness are associated with lower levels of problematic smartphone use, we propose the following hypothesis:

H1: Mindfulness negatively correlates with problematic smartphone use.

Self-regulated learning as a mediator

Recent research has shown that mindfulness is negatively associated with problematic smartphone use among university students. This means that higher levels of mindfulness correspond with lower levels of problematic smartphone use. A key factor that might explain this relationship is self-regulated learning.

Self-regulation is generally defined as the individual’s ability to control thoughts, emotions, and behaviors in pursuit of personal goals [46]. This broader theoretical perspective provides the foundation for understanding problematic behaviors, including excessive technology use. Within this framework, self-regulated learning (SRL) can be viewed as a contextualized application of self-regulation in academic settings. SRL emphasizes students’ capacity to plan, monitor, and evaluate their learning processes [33, 34], and these skills reflect the same underlying mechanisms of self-regulation described in general theory. The use of SRL in the present study is therefore justified by the academic nature of the sample, while remaining conceptually consistent with the broader self-regulation perspective [46, 47].

Self-regulated learning refers to a student’s ability to intentionally manage their thoughts, emotions, and behaviors to achieve educational goals. It involves strategies such as planning, observing one’s actions, monitoring progress, and evaluating outcomes. The inclusion of self-regulated learning as a mediating variable is grounded in self-regulation theory, which explains how mindfulness fosters attentional control, emotional regulation, and reflective awareness—processes central to self-regulated learning [46]. Prior research has shown that mindfulness practices are associated with skills such as planning, monitoring, and self-control, while deficits in self-regulated learning are consistently linked to higher levels of problematic smartphone use. For example, mindfulness practices help students enhance their self-control, an essential part of self-regulated learning [7, 8, 22]. Furthermore, mindfulness training positively impacts students’ ability to regulate their behaviors and maintain a sense of control over their academic activities [10].

On the other hand, poor self-regulated learning has been linked to increased problematic smartphone use [9, 23, 24]. In this context, examining Self-regulated learning as a mediator provides a theoretically justified and problem-oriented approach. It helps to explain the cognitive and behavioral processes through which mindfulness may lessen problematic patterns of smartphone use among university students. Therefore, higher levels of mindfulness are related to stronger self-regulated learning skills, which subsequently reduce problematic smartphone use among students. Accordingly, we propose the following hypothesis:

H2: Self-regulated learning may mediate the relationship between mindfulness and problematic smartphone use.

Digital detox as a moderator

Digital detox refers to the deliberate practice of abstaining temporarily from the use of digital devices such as smartphones, computers, and social media platforms, aiming to improve mental health, increase productivity, and enhance concentration [11, 12, 25]. This practice can lessen digital distractions and provide students with the opportunity to strengthen their cognitive and self-regulatory resources. By limiting digital exposure, individuals are less likely to experience overstimulation and distraction, which can enhance their ability to engage in meaningful, goal-directed academic activities. In this way, digital detox provides a context in which self-regulation skills can be more effectively applied. This intentional disengagement provides individuals with the opportunity to recover from overstimulation and information overload, conditions increasingly prevalent in the contemporary technological environment. Stepping away from digital devices has been associated with reductions in stress and anxiety, thereby offering the mind a restorative break [25]. Furthermore, minimizing digital distractions enables individuals to regain cognitive control, thereby enhancing their ability to concentrate on meaningful and goal-oriented tasks.

In educational contexts, digital detox has been proposed as a moderating factor that is associated with a stronger link between self-regulated learning and problematic technology use. When students reduce their reliance on digital devices, they minimize interruptions and distractions, thereby creating an environment that supports the successful use of planning, monitoring, and control strategies inherent in self-regulated learning. Prior research supports this proposition: Li et al. [26] found that the association between self-regulation and smartphone use varied according to levels of digital detox, while Zhang and Wang [27] reported that students who regularly practiced digital detox were better able to apply self-regulated learning strategies and demonstrated lower tendencies toward problematic smartphone use.

Based on this evidence, digital detox can be conceptualized as a contextual condition that influences the effectiveness of self-regulated learning in reducing problematic smartphone use. In other words, while self-regulated learning provides the skills to control behavior, digital detox may amplify these skills by reducing environmental distractions and opportunities for overuse. On this basis, the following hypothesis is proposed:

H3: Digital detox may moderate the relationship between self-regulated learning and problematic smartphone use.

Hypothesized model and study aims

Although self-regulated learning is often considered a potential mediator of the relationship between mindfulness and reduced addictive behaviors, its role in the context of problematic smartphone use remains less established, given the extent to which this behavior is embedded in students’ daily routines. The primary purpose of this study is to examine whether self-regulated learning mediates the link between mindfulness and problematic smartphone use, and whether digital detox moderates this mediated pathway. The proposed conceptual model is shown in Fig. 1. Specifically, the study pursues three objectives: [1] to test a conditional process model in which self-regulated learning operates as a mediator and digital detox as a moderator of problematic smartphone use; [2] to analyze these associations within the perspectives of positive psychology and self-regulation in a large sample of Chinese university students; and [3] to employ validated Chinese versions of established measures (MAAS, PSU, SRL-SRS, DDS) to ensure consistency of measurement and comparability with prior research.

Fig. 1.

Hypothesized Conditional-Process Model

Method

This cross-sectional study was conducted to investigate the relationship between mindfulness and problematic smartphone use, while also exploring the potential mediating role of self-regulated learning and the moderating role of digital detox in these associations.

Participants

A total of 1,241 college students from Shandong Xiehe University, China, voluntarily participated in this study. Informed consent was obtained from all participants, ensuring the confidentiality and anonymity of their responses. The participants’ ages ranged from 18 to 22 years (M = 21.12, SD = 1.36). Participants with prior experience in mindfulness training, digital detox practices, or yoga were excluded to avoid potential confounding, as such experiences may independently influence mindfulness and self-regulation. This study followed the ethical standards set by the Academic Committee of Shandong Xiehe University, the principles of the Declaration of Helsinki (1964) and its later amendments, and comparable guidelines governing research involving human subjects. Detailed demographic characteristics of the participants are presented in Table 1.

Table 1.

Demographic characteristics of the participants

Variable	Frequency	%
Gender
Male	499	40. 2%
Female	742	59.8%
Family Income
3000–10,000 RMB	741	59.71%
10,000–20,000 RMB	314	25.30%
20,000-above RMB	186	14.99%
Grade
1st	512	41%
2nd	325	26%
3rd	287	23%
4th	117	10%
Total	1241	100%

RMB = The Chinese currency

Measurements

Mindfulness. The Chinese version of the Mindful Attention Awareness Scale (MAAS), consisting of 15 items [28], has been validated and demonstrated as a reliable instrument within Chinese contexts [29]. Participants responded to items such as “I am aware of my thoughts and feelings in the present moment”, “I notice when my attention wanders during tasks.”, “I pay attention to my experiences without judgment.” Responses were scored on a 6-point Likert scale, ranging from 1 (Almost always) to 6 (Almost never). After reverse coding, higher mean scores indicated greater mindfulness. In the present study, the scale demonstrated acceptable internal consistency, with a Cronbach’s alpha of 0.82.

Problematic smartphone use. Problematic smartphone use was assessed using the 10-item Short Smartphone Addiction Scale (S-SAS) and has been validated and demonstrated as a reliable instrument within Chinese contexts [21]. Sample items include “I feel anxious when I cannot check my smartphone.”, “I use my smartphone even when it interferes with my daily tasks.”, and “I spend more time on my smartphone than I intend.” Items were rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). In the present study, the scale demonstrated acceptable internal consistency, with a Cronbach’s alpha of 0.86.

Self-regulation of learning. The Chinese version of the Self-Regulation of Learning Self-Report Scale (SRL-SRS), consisting of 26 items [30], has been validated and demonstrated as a reliable instrument within Chinese contexts [52]. Representative items include: “I set specific goals for my learning tasks” and “I monitor my progress toward achieving my learning goals.” And “I adjust my study strategies when I encounter difficulties.” Responses were scored with a 5-point scale (1 = not at all true of me, 5 = very true of me). In the present study, the scale demonstrated acceptable internal consistency, with a Cronbach’s alpha of 0.90.

Digital detox. The Chinese version of the Digital Detoxification Scale (DDS) consists of 10 items [31]. Example items include: “I get distracted by my smartphone during study sessions.”, “Notifications from digital devices disrupt my focus on tasks.” And “I find it hard to concentrate when digital distractions are present.” Items were rated on a 5-point Likert scale, ranging from 1 (Strongly disagree) to 5 (Strongly agree). The DDS was used to assess digital detox behaviors. The items reflect both actual practices and attitudes toward limiting smartphone use, rather than intentions alone. Thus, the scale can be considered a measure of self-reported behavior combined with attitudes toward intentional disconnection [11, 12, 25]. In the present study, the scale demonstrated acceptable internal consistency, with a Cronbach’s alpha of 0.78.

Data analysis

Pearson’s correlation coefficients were calculated to examine the relationships between the study variables. Mediation analyses were conducted in SPSS using the PROCESS macro (version 3.5). The significance of the mediated effects was assessed using 95% confidence intervals generated through 5,000 bootstrap resamples, following the recommendations of Hayes [32].

Results

Correlation among study variables

The results indicate that all study variables were significantly correlated with one another. Mindfulness was negatively correlated with problematic smartphone use. Furthermore, mindfulness was positively correlated with both self-regulated learning and digital detox. See Table 2.

Table 2.

Descriptive statistics and pearson correlations among study variables (N = 1,241)

Variables	MAAS	PSU	SRL-SRS	DD
MAAS	1
PSU	− 0.41**	1
SRL-SRS	0.36**	− 0.31**	1
DD	0.40**	− 0.60**	0.50**	0.1
M_sum	9.90	4.42	7.17	8.88
SD_sum	1.80	1.62	1.40	1.20

Note. *p < .05, *p < .01. MAAS = Mindfulness; PSU = Problematic Smartphone Use; SRL-SRS = Self-Regulated Learning; DD = Digital Detox

Mediation effects

To investigate the influence of mindfulness on problematic smartphone use, the bias-corrected percentile bootstrap method was employed (Model 4 in SPSS PROCESS; 5,000 bootstrap samples; 95% confidence intervals) to test the mediating effect. Mindfulness was entered as the independent variable, problematic smartphone use as the dependent variable, and self-regulated learning as the mediating variable. Gender, age, and family income were included as covariates in all models; none reached statistical significance (all ps > 0.10), the total effect of mindfulness on problematic smartphone use was significant (β = −0.41, p < .05). The direct effect also remained significant (β = −0.29, p < .05). Further details are presented in Table 3.

Table 3.

Path analysis

Path	β	SE	t	p-value
a (MAAS → SRL-SRS)	0.36	0.02	12.86	p = .010
b (SRL-SRS → PSU)	-0.31	0.03	-10.33	p < .001
c (Total Effect)	-0.41	0.02	-14.46	p < .001
c’ (Direct Effect)	-0.29	0.02	-10.36	p < .001
Indirect Effect (a*b)	-0.11	0.04	-2.80	95% CI [-0.18, -0.05]

Note. *p < .05., MAAS = Mindfulness, PSU = Problematic Smartphone Use, SRL-SRS = Self-regulated learning and DD = Digital Detox

As shown in Table 4, mindfulness showed a positive association with self-regulated learning (Model 1), and self-regulated learning showed a negative association with problematic smartphone use (Model 2). Furthermore, the bias-corrected percentile bootstrap method revealed a significant indirect effect of mindfulness on problematic smartphone use through self-regulated learning (ab = − 0.11, SE = 0.04, 95% CI [-0.18, -0.05]), indicating that self-regulated learning partially mediates this relationship. Further details are provided in Table 4; Fig. 2.

Table 4.

Mediation effects of SRL

Predictors	Model 1 (SRL-SRS)			Model 2 (PSU)
	β	SE	t	β	SE	t
MAAS	0.36	0.02	12.86	-0.29	0.02	-10.36
SRL-SRS				0.31	0.03	-10.33

Note. *p < .05., MAAS = Mindfulness, PSU = Problematic Smartphone Use, SRL-SRS = Self-regulated learning and DD = Digital Detox

Fig. 2.

Mediation Effects of SRL

Moderation effects

The results (Table 5) indicate that both self-regulated learning and digital detox significantly predicted problematic smartphone use, such that higher levels of either corresponded to lower levels of problematic smartphone use. Moreover, digital detox moderated the relationship between self-regulated learning and problematic smartphone use, as evidenced by a negative interaction term (self-regulated learning × digital detox). This finding indicates that engaging in digital detox practices intensifies the protective effect of self-regulated learning against problematic smartphone use. Further details are presented in Fig. 3.

Table 5.

Moderation effects of SRL on PSU by DD

Predictor	β	SE	t	p-value
SRL-SRS	-0.31	0.12	-2.08	0.02
DD	-0.60	0.20	-3.00	0.00
SRL-SRS *DD	-0.12	0.03	-4.00	0.00

Note. *p < .05., SRL-SRS = Self-regulated learning and DD = Digital Detox

Fig. 3.

Moderation Of SRL-SRS On PSU By DD

Discussion

The first aim of this study was to examine the relationship between mindfulness and problematic smartphone use among a sample of 1,241 Chinese college students. The findings indicated a significant negative correlation between mindfulness and problematic smartphone use, suggesting that higher levels of mindfulness are associated with reduced problematic use. These results are consistent with previous research demonstrating a negative relationship between mindfulness and problematic smartphone use [4, 5, 17]. Moreover, the present study revealed a positive correlation between mindfulness and both self-regulated learning and digital detox. These outcomes are aligned with prior studies indicating that mindfulness positively correlates with self-regulated learning [33, 34] and digital detox [35–37].

The second aim of our study was to explore the potential mediating role of self-regulated learning in the relationship between mindfulness and problematic smartphone use. The results are consistent with the view that higher mindfulness is accompanied by higher self-regulation skills, and both are associated with lower problematic smartphone use. This finding is consistent with self-regulation theory [46], which emphasizes the role of attentional control and emotional regulation in supporting goal-directed behavior. It also supports earlier evidence that mindfulness was associated with higher self-control and lower rumination, which were in turn linked to lower levels of problematic smartphone use [38, 39]. Within the perspective of positive psychology, mindfulness may be understood as a protective personal resource that is associated with reflective awareness and accompanies adaptive digital behaviors [40, 41]. Our findings supported this hypothesis, showing that self-regulated learning partially mediated the association between mindfulness and problematic smartphone use. This indicates that although self-regulated learning plays a significant role, it does not fully account for the association between mindfulness and problematic smartphone use. Previous research has established that mindfulness is inversely related to problematic smartphone use [5, 17, 18] and that mindfulness is associated with self-regulation capabilities, which in turn are associated with lower problematic use [38, 39]. For instance, mindfulness was significantly associated with higher self-control and lower rumination, which were related to lower problematic smartphone use among college students [5]. Similarly, mindfulness and self-control partially mediated the relationship between emotion regulation and mobile phone addiction, indicating a critical pathway through which mindfulness may be related to technology use [39]. The partial mediation observed in this study suggests that other mechanisms may also be involved. Prior studies indicate that emotion regulation difficulties [42, 43] and impulsiveness [44] could account for the remaining direct association. Future research should examine these factors as potential mediators.

Theoretical frameworks from positive psychology and self-regulation theories further support these findings, suggesting that mindfulness is associated with self-regulation skills through its correlations with awareness, attentional control, and emotional regulation [40, 41]. According to the Dual Systems Model, self-regulation functions as a reflective system that is involved in regulating impulsive behaviors associated with problematic smartphone use, thereby suggesting a potential mechanism through which mindfulness may be associated with beneficial outcomes [40]. Furthermore, mindfulness-based interventions have been reported to be associated with better executive functioning and cognitive flexibility, which are important components of self-regulation [42]. Our findings align with these theoretical insights, demonstrating that higher mindfulness was associated with stronger self-regulated learning skills, which in turn showed a negative association with problematic smartphone use among university students. These findings emphasize the importance of incorporating mindfulness-based interventions in educational settings to foster healthier digital habits and promote overall well-being.

The third aim of this study was to examine whether digital detox moderates the association between self-regulated learning and problematic smartphone use. The results confirmed our hypothesis, demonstrating that the interaction term was significant, indicating that the negative association between self-regulated learning and problematic smartphone use was stronger at higher levels of digital detox, which coincides with students’ ability to translate regulatory skills into healthier digital practices. This finding aligns with the dual-systems model [40], suggesting that digital detox is associated with a reduced influence of reflexive impulses while being associated with an enhanced role of reflective, self-regulatory systems. In practical terms, digital detox may serve as an effective strategy that coincides with a greater student ability to control smartphone use and maintain focus on academic tasks. The moderating role of digital detox may be explained by its capacity to reduce external distractions, potentially enabling students to apply self-regulation strategies more effectively and thereby strengthening the negative association between SRL and PSU [45,46]. The strong negative correlation between DDS and problematic smartphone use (r = − .60) may suggest partial construct overlap, as both capture aspects of controlling digital behavior. While this indicates convergent validity, it also raises concerns about discriminant validity. Future studies should further investigate whether digital detox can be empirically distinguished from problematic smartphone use.

These findings suggest that mindfulness is not only directly associated with reduced problematic smartphone use but also indirectly related to it through self-regulated learning, with digital detox strengthening this indirect pathway. The integration of positive psychology, self-regulation theory, and the dual-systems model offers a comprehensive framework for explaining these results, highlighting the psychological and behavioral mechanisms involved. It should be noted that mindfulness may also function as a moderating variable, buffering the negative impact of problematic smartphone use on psychological well-being. Future research could compare alternative conceptualizations of mindfulness, examining whether it is primarily associated as an antecedent that is connected to self-regulation or as a moderator that is linked to buffering harmful outcomes. Such comparisons could help clarify the mechanisms through which mindfulness is related to technology-related behaviors.

The findings of this study are consistent with general self-regulation theory, which conceptualizes self-regulation as the ability to manage cognitive, emotional, and behavioral responses in line with long-term goals [46]. Although the present study employed a measure of self-regulated learning specific to academic contexts, the results can also be interpreted within this broader theoretical perspective. The negative association between mindfulness and problematic smartphone use, mediated by SRL, suggests that similar regulatory capacities may be common to both academic behaviors and broader patterns of technology use. This interpretation is aligned with previous research showing that self-regulation plays a central role in managing diverse forms of behavior, including digital habits [47]. Future research could extend these findings by incorporating broader measures of self-control or self-regulation to examine whether the same patterns of association are present beyond academic contexts.

Implications for practice

The findings of this study have implications for both theory and practice. At the theoretical level, the results clarify the associations between mindfulness, self-regulated learning, digital detox, and problematic smartphone use within an integrated framework. At the practical level, they support several evidence-based recommendations for educational contexts. Scheduling brief device-free intervals during study sessions (e.g., 20–30 min) has been linked to improved sleep quality and reduced anxiety [48]. Short mindfulness practices such as breathing or body-scan exercises (5–10 min) can be integrated into weekly classes to enhance attention and emotional regulation [50]. Student workshops on self-regulated learning strategies—including goal setting, monitoring, and strategy adjustment—can provide practical tools for academic engagement. Simple digital detox routines, such as disabling non-essential notifications, using app timers, or placing phones out of reach, may also help prevent overuse [49]. Finally, teacher training and involvement of families and the broader community can facilitate consistent implementation and support sustained healthy digital habits [51]. Together, these approaches may contribute to reducing problematic smartphone use and promoting student well-being.

Limitations and future directions

Despite its contributions, this study has several limitations. First, the reliance on self-reported measures may have introduced response biases, including social desirability. Future studies could incorporate objective indicators, such as digital usage tracking, to complement self-report data. Second, the sample was limited to students from a single university, which restricts the generalizability of the findings. Including participants from multiple institutions and diverse cultural contexts would provide broader insights. Third, using a self-regulated learning scale designed primarily for academic contexts [33,34] limits the applicability of the findings beyond academic settings. Employing more general measures of self-regulation or self-control [46,47] would allow a broader understanding of the mechanisms linking mindfulness and problematic smartphone use. Fourth, only self-regulated learning was examined as a mediator. Future research should also investigate other potential mediators, such as emotion regulation [42,43] and impulsiveness [44]. Fifth, the high correlation between DDS and problematic smartphone use raises concerns about discriminant validity; future research should employ alternative or multidimensional measures of digital detox to clarify its validity. Finally, the cross-sectional design precludes causal inference. Longitudinal and experimental designs are needed to validate the causal pathways proposed in the model.

Conclusion

This study provides evidence that mindfulness is negatively associated with problematic smartphone use among Chinese college students, indicating that higher levels of mindfulness correspond with reduced problematic smartphone use. Furthermore, mindfulness positively correlates with self-regulated learning and digital detox, which further contribute to mitigating problematic smartphone use. Self-regulated learning partially mediates this relationship, indicating that it is associated with the link between mindfulness and problematic smartphone use. Moreover, digital detox significantly moderates the association between self-regulated learning and problematic smartphone use, strengthening its protective effect. Collectively, these findings underscore the potential of mindfulness-based interventions and digital detox strategies to promote healthier digital habits through improved self-regulation and intentional technology use.

Abbreviations

MAAS

Mindful attention awareness scale

PSU

Problematic smartphone use

SRL-SRS

Self-regulation of learning self-report scale

DDS

Digital detoxification scale

RMB

Renminbi (Chinese currency)

Author contributions

Dear Prof. The Editor of The BMC Psychology Journal. I am submitting a manuscript for consideration for publication in BMC Psychology. The manuscript is entitled. “The Effect of Mindfulness on Smartphone Addiction: The Mediating Role of Self-regulation Learning and the Moderating Role of Digital Detox”. It has not been published elsewhere, and it has not been submitted simultaneously for publication elsewhere. Thank you very much for your consideration. Dr. Aamer Aldbyani *Email: aameraldbyani@sdxiehe.edu.cn, Department of General Education, Shandong Xiehe University, Jinan, China. Dr. Zhang Chuanxia Email: zhangchuanxia@sdxiehe.edu.cn. Department of General Education, Shandong Xiehe University, Jinan, China. Dr. Afnan AlhimaidiEmail: aaalhimaidi@pnu.edu.sa. Department of Psychology, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Yanwen Li yanwenli_me@163.com Department of General Education, Shandong Xiehe University, Jinan, China* Corresponding author: Dr. Aamer Aldbyani, Associate Professor at the Department of General Education, Shandong Xiehe University, No. 6277, Jiqing Road, Licheng District, Jinan City, Shandong Province, China. Email: aameraldbyani@sdxiehe.edu.cn, https://orcid.org/0000-0002-8803-1754.

Funding

The authors gratefully acknowledge the financial support provided by Shandong Xiehe University (SDXIEHE/2025) for this study.

Data availability

Upon a reasonable request, the corresponding author (Dr. Aamer Aldbyani) will provide the data supporting the study’s conclusions. For further inquiries regarding data access, please get in touch with the corresponding author at [aameraldbyani@sdxiehe.edu.cn] (mailto: aameraldbyani@sdxiehe.edu.cn) .

Declarations

Ethics approval

This study was approved by the Academic Committee of the College of Humanities, Arts, and Education at Shandong Xiehe University (2025/3-321) and conducted following the Declaration of Helsinki.

Consent to participate

All participants provided informed consent after being briefed on the study’s purpose and procedures. Participation was voluntary, and anonymity and confidentiality were assured.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.