The current study examined how brief mindfulness meditation training affects impulsive behaviors and their underlying mechanisms using a randomized controlled design with smartphone-based online interventions.
Method
A total of 70 participants who were identified with low level of mindfulness participated in the study. Participants were randomly assigned to three groups: mindfulness (monitor + acceptance, n = 24), monitor-only (n = 23), and no-intervention control (n = 23), in which mindfulness and monitor-only groups were required 10 min daily for a 7-days online intervention. These groups were established based on the Monitor and Acceptance Theory. Participants completed measurements about cognitive impulsivity (measured with Stroop tasks), motoric impulsivity (measured with Go/No-go tasks), and impulsive decision-making behaviors (measured with Delay Discounting tasks) at pre-test, post-test (after 1 week mindfulness training), and follow-up (half month after the end of training).
Results
The results revealed that at the post-test, the mindfulness group showed significantly reduced reaction times on the Stroop and Go/No-Go tasks compared to the monitor group and the control group, indicating stronger cognitive and motoric impulse inhibition abilities in the mindfulness group participants. Compared to the monitor and control groups, the mindfulness group did not show significantly improved impulsive decision-making abilities at post-test. At follow-up, all the results indicated that the brief mindfulness training did not have sustained effects.
Conclusions
The current study suggests that monitor and acceptance training produced a momentarily de-automation effect on some impulsive behaviors, demonstrating enhanced cognitive and motoric impulse inhibition abilities. The study emphasizes the significance of the acceptance dimension in mindfulness training, offering valid methods and empirical evidence for mitigating impulsive behaviors through mindfulness training.
Preregistration
The current study is not preregistered.
Opmerkingen
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As the saying goes, impulsivity is the devil. Impulsive behavior can wreak havoc in real-life scenarios (McHugh & Balaratnasingam, 2018). A number of studies have linked impulsivity to a wide range of destructive behaviours, including criminal activity, violence, compulsive gambling and sexual behaviour, as well as other maladaptive behaviours (Indu et al., 2017; Liu et al., 2017; Sharma et al., 2014). The construct of impulsivity has been continually updated and refined with developments. Many researchers suggest that impulsive behavior is a multidimensional concept (Reynolds et al., 2006). It can be divided into behavioral inhibition and impulsive decision-making. The behavioral inhibition can be further divided into cognitive and motoric impulses (Caprioli et al., 2014; Winstanley et al., 2006). In this context, cognitive impulsivity refers to an individual's inability to resist extraneous and automated thoughts or memories; Motoric impulsivity refers to an individual's inability to suppress dominant or automatic behavioral responses; Impulsive decision-making refers to an individual's inability to take action without considering other possible alternatives and outcomes. Impulsive behavior is a diagnostic criterion for several mental disorders, including antisocial personality disorder, borderline personality disorder, bipolar disorder, and substance abuse and dependence (American Psychiatric Association, 2013). Among healthy populations, impulsive behavior is often associated with negative outcomes such as overspending, debt, poverty (Achtziger, 2022), lower executive functioning (Cruz et al., 2020), more aggression and substance abuse (Chamorro et al., 2012). Given the wide range of negative impacts associated with impulsive behaviors, it is necessary to conduct studies to reduce the likelihood of their occurrence.
Mindfulness meditation training is a method that requires individuals to consciously focus their attention on current internal or external experiences without judging them (Kabat-Zinn, 1990; Liu et al., 2008). Research have demonstrated the beneficial effects of mindfulness training on attentional control (Sørensen et al., 2018; Wheeler et al., 2016), emotional regulation (Baylan et al., 2018; Xu et al., 2015), and the development of social mindfulness and perspective taking (Wang et al., 2023). In clinical research, it has been proven that mindfulness training can significantly reduce insomnia (Kennett et al., 2021), addictive behaviors (Xu et al., 2016), drug and alcohol abuse (Roos et al., 2020), various types of chronic pain (Pardos-Gascón et al., 2021) and symptoms of clinical depression and anxiety (Fan et al., 2024; Johannsen et al., 2022; Ren et al., 2018). In healthy populations, a meta-analysis of 51 randomized controlled studies involving university students and postgraduates revealed that mindfulness training significantly alleviated symptoms of depression and state anxiety compared to control groups (Dawson et al., 2020). Despite the growing body of evidence supporting the efficacy of mindfulness training, existing studies primarily focus on phenomenological investigations, with limited exploration of the underlying mechanisms.
Some studies have investigated the impact of brief mindfulness meditation training on impulsive inhibition, revealing that individuals undergoing mindfulness training demonstrated enhanced impulsive inhibition compared to control groups (Allen et al., 2012; Li et al., 2019; Ron-Grajales et al., 2021; Sahdra et al., 2011; Wang et al., 2012; Zheng et al., 2023). For instance, Tang et al. (2007) devised an Integrative Body-Mind Training (IBMT) program, incorporating mindfulness and relaxation therapy elements. In the mindfulness group, after 5 days of daily 20-min IBMT sessions, participants showed significant improvements in impulsive inhibition on the Stroop task. Despite several studies supporting the positive effects of brief mindfulness training on impulsive inhibition, some studies have demonstrated the ineffectiveness of mindfulness training (Anderson et al., 2007; Heeren et al., 2009). Researchers have utilized tasks (the Stroop task and Go/No-go task) to explore the impact of brief mindfulness training on cognitive and motoric impulsive inhibition. Findings indicated that individuals in the brief mindfulness training group did not significantly differ in performance on these tasks compared to the control group (Anderson et al., 2007; Heeren et al., 2009). Additionally, limited research examined on the influence of brief mindfulness training on impulsive decision-making. Studies on individuals with mental disorders have demonstrated reduced delay discounting rates following brief mindfulness training among those with borderline personality disorder (Elices et al., 2016) and online gaming addiction (Yao et al., 2017). However, there are still some discrepancies. For example, Shead et al. (2020) found that a 7-day brief mindfulness training did not decrease delay discounting rates in healthy university students with gambling tendencies. While prior research suggests that mindfulness training affects impulsive behavior in both healthy and psychologically disordered populations, research deficience persist. Firstly, previous studies usually focused on the effects how the brief mindfulness training influences the one dimension of impulsive behavior (i.e.,Ron-Grajales et al., 2021; Shead et al., 2020; Zheng et al., 2023). No study has systematically examined the effects of brief mindfulness training on different types of impulsive behaviors at the same time; Moreover, many studies used the mindfulness-based compound training which inspired by established systemic mindfulness training but are not bound by a rigid set of standards (Davidson & Kaszniak, 2015; Diamond, 2024; Wang et al., 2012). This training cannot separate out the effective components of mindfulness training. This has resulted in confusion regarding the mechanisms by which brief mindfulness training influences impulsive behavior.
The Monitor and Acceptance Theory (MAT) proposed by Lindsay and Creswell (2016) offers a framework to elucidate the mechanisms underlying of mindfulness meditation training interventions, emphasizing monitor and acceptance as critical components. According to MAT, monitoring enhances attentional processes and intensifies present-moment experiences, while acceptance alters individuals' relationships with monitored experiences to mitigate emotional reactions. The combination of the two ultimately fosters physical and mental health benefits. The theory posits that the unique synergies of monitor and acceptance skills drive the positive outcomes seen in mindfulness research. To be specific, while monitor training alone can enhance cognitive outcomes, it may also heighten sensitivity to negative emotional information, potentially exacerbating emotional arousal and symptoms. To optimize emotional, stress, and physical health, combining monitor and acceptance training is crucial, as acceptance can mitigate adverse reactions (Creswell, 2017). Lindsay et al. (2018) validated MAT through multiple randomized controlled trials focused on the effects of mindfulness training on individual stress levels, demonstrating that the group receiving combined monitor and acceptance training experienced reductions in systolic blood pressure and salivary cortisol levels, effectively reducing individual stress levels compared to the monitor-only and control groups. Studies on reducing mind wandering (Rahl et al., 2016), panic disorder (Wang et al., 2016) and alleviating loneliness (Lindsay et al., 2019) further support the importance of combined monitor and acceptance training in mindfulness interventions.
The positive mindfulness training intervention based on the MAT that may be beneficial to reduce impulsive behavior. The Impulsive Dual-Process Theory model introduced by Leshem (2016) categorizes impulsivity into cognitive/action impulsivity and emotional impulsivity. This model suggests that impulsive behaviors may result from excessive activation of the emotional system, a deficit in cognitive control of executive functions, or a combination of both factors. Based on this speculation, it is hypothesized that the efficacy mechanism of mindfulness training on individual impulsivity may involve distinct psychological processes targeted by monitor and acceptance training during impulsivity processing, with their interaction leading to a reduction in individual impulsive behaviors (Yang & Zeng, 2023).
The emergence of smartphone technology has revolutionized the method of mindfulness interventions, shifting towards remote methods like smartphone-based online training. This transition has been driven by the convenience, accessibility, cost-effectiveness, and scalability of remote interventions compared to traditional face-to-face approaches (Creswell, 2017; Wahbeh et al., 2014). Researchers have increasingly recognized the effectiveness of remote mindfulness training across various domains. Studies have demonstrated the efficacy of remote mindfulness interventions in reducing depression, stress, and anxiety (Cavanagh et al., 2018; Walsh et al., 2019) while also enhancing positive emotions (Tkatch et al., 2017). Especially during the COVID-19 pandemic, online mindfulness training has been instrumental in supporting mental health on the general population, studies provided evidence showing significant positive impacts (Green et al., 2021; Khandelwal, 2020; Lim et al., 2020; Matiz et al., 2020; Sanilevici et al., 2021; Zhang et al., 2021).
The current study aimed to investigate the impact of remote audio mindfulness training on impulsive behavior. By elucidating the active mechanisms by which the mindfulness training affects impulsive behavior, the ultimate goal is to stimulate new evidence on how we can customize more effective positive mindfulness training in practice. The current study classified impulsive behaviors into cognitive impulsivity, motoric impulsivity, and impulsive decision-making according to the classification by Winstanley et al. (2006). Based on the MAT, the current study established three groups: a mindfulness group (including monitor and acceptance), a monitoring-only group, and a control group. We hypothesized that the mindfulness group, which received 10 min of monitor and acceptance training per day for 1 week, would exhibit less impulsive behaviors compared to the monitor-only and control groups.
Method
Participants
Given that most psychological studies have moderate to small effect sizes (Meyer et al., 2001), the appropriate number of participants was calculated using G*power (Faul et al., 2007). A medium effect size has been chosen. With an effect size of f = 0.25, a power of 1 − β = 0.95, and an alpha standard probability of .05, a power analysis for the 3 × 3 repeated measures ANOVA resulted in a total required sample size of n = 54. In a comprehensive university which is situated in the eastern coastal city of China, 374 participants were recruited through advertisements to participate in this experiment. After excluding invalid questionnaires, 364 valid questionnaires were collected, resulting in a response rate of 97.33%. Previous research suggested that individuals with higher mindfulness levels exhibit better impulsive inhibition (Moore & Malinowski, 2009; Shead et al., 2020; Short et al., 2016; Teper & Inzlicht, 2013). The current study focuses on the effects of mindfulness training on impulsive behavior, so individuals with low levels of mindfulness were specifically chosen to more accurately assess the impacts of mindfulness training. Therefore, participants scoring in the lowest 27% on the Philadelphia Mindfulness Scale were classified as low-trait mindfulness individuals and randomly assigned to the mindfulness group, monitor-only group, and control group. Seventy participants (43 females, 24 males) who met the experimental conditions and voluntarily participated were included, with ages ranging from 18 to 26 years (M = 21.68, SD = 2.43). There were 24 participants in the mindfulness group, 23 in the monitor group, and 23 in the control group. Participants had no prior experience with mindfulness or meditation, no significant events or severe emotional fluctuations in the past 2 weeks, no physical or mental illnesses, normal or corrected-to-normal vision, no color blindness, and all participants volunteered for the study. Before the experiment began, participants received and signed an informed consent form.
Procedure
Participants with low trait mindfulness were selected using the PHLMS. Those who met the research criteria were randomly assigned to one of three groups: mindfulness, monitor or control. Then the groups completed the Stroop task, Go/No-Go task, and Delay Discounting task in the laboratory, with the order of tasks being balanced. The entire task took approximately 30 min. Subsequently, participants in the mindfulness and monitor groups received 10-min audio interventions daily for seven consecutive days. The initial training session for both groups was conducted in the laboratory, where the experimenter explained the training content and instructions in detail. After ensuring that the participants had no questions, they were instructed to find a quiet and uninterrupted environment each day to carry out subsequent training using a specific mobile application. To ensure daily compliance, participants were required to log their training completion every day in the experimental groups. The control group did not undergo any training and simply waited for a week before the study continued. After 1 week, all three groups returned to the laboratory for the second assessment. They first completed the PHLMS and then the assessment tasks. After the initial assessment, participants would wait for 15 days for the final assessment. Following this waiting period, the mindfulness group, monitor group, and control group underwent the final assessment with consistent assessment tasks. Please refer to Fig. 1 which illustrates the selection process of study participants using the CONSORT diagram.
Fig. 1
CONSORT diagram showing the flow of participants through each stage of the RCT
×
Intervention
The mindfulness meditation training utilized in the current study is adapted from Williams and Penman's (2011) Mindfulness of Body and Breath. This training integrates the principles of mindfulness-based cognitive therapy to provide an economical and time-saving mindfulness training method for individuals who lack time, money, and teaching resources. Participants in the current study were randomly assigned to the mindfulness group, monitor group or control group. The mindfulness group received a 1-week training, 10 min per day, which includes monitor and acceptance. The monitor group also received a 1-week training, 10 min per day, but focused solely on monitor. The control group did not receive any training and will only wait for a week. The materials provided for the mindfulness and monitor groups are as follows:
(1)
Mindfulness Group: Participants in the mindfulness group received mindfulness training, including cultivation of monitor and acceptance. The training material is an audio clip adapted from Williams and Penman's (2011) Mindfulness of Body and Breath. The content of the audio clip includes: ① Introduction of the audio and its purpose to motivate participant training, such as "This training is derived from a widely used mindfulness training course worldwide, applied in various fields like healthcare, education, and business," "Numerous scientific research findings have shown that simply training our attention by observing our mind-body sensations can bring about many positive changes to our minds"; ② Detailed guidance on posture to help participants naturally and relaxingly engage in the experiment; ③ Monitor of bodily sensations, such as "Shift your attention to your calves. Then to the knees. Next, focus on the thighs. Use both legs as the center of conscious monitor. Now expand your attention upwards along the body. From the pelvis to the hips, to the lower back and abdomen. Then move to the trunk. Chest and back, up to the shoulders," and guide participants to accept the sensations observed, paying attention to all bodily perceptions in that area. For example, "See if you can authentically feel the original bodily sensations. Do not attempt to control any sensations or wish to change them"; ④ Shift attention to observing the breath, such as "Shift your attention to the center of your body. As you breathe in and out, observe the sensations in your abdomen. Notice the changes in this area," and accept all experiences while observing the breath, such as: "Do not try to control your breathing in any way. Let the breathing process happen naturally. During the attention to breathing, you may have many sensations, thoughts, or emotions. Please do not judge or think about them, just be aware of their presence"; ⑤ Guide trainers to re-focus on breath monitor when distracted; ⑥ Encourage trainers to maintain the training state in their daily lives.
(2)
Monitor Group: Participants in the monitor group received monitor training intervention, solely focused on cultivating monitor. The training material is an audio clip adapted from Williams and Penman's (2011) Mindfulness of Body and Breath. The content of the audio clip includes: ① Introduction of the audio and its purpose to motivate participant training; ② Posture guidance, similar to the mindfulness group; ③ Emphasis on monitor of bodily sensations only; ④ Observing the breath, but not guiding participants to accept the experiences observed; ⑤ Guide trainers to re-focus on breath monitor when distracted; ⑥ Encourage trainers to maintain the training state in their daily lives.
Measures
Philadelphia Mindfulness Scale
Mindfulness refers to a form of self-regulation of attention that requires maintaining focus on the present experience, continuous cognitive processing of current mental activity, and adopting a specific attitude toward the present experience, such as curiosity, openness, and acceptance (Kabat-Zinn, 1990; Liu et al., 2008). According to the characteristic of the brief online training in mindfulness meditation and the research objectives, the current study used the PHLMS to measure the participants’ mindfulness level (Simione & Saldarini, 2023). The current study utilized the Chinese version of the Philadelphia Mindfulness Scale (PHLMS) developed by Zeng et al. (2014). The scale was used to assess an individual's level of mindfulness and consisted of two dimensions: monitor and acceptance, each with 10 items scored on a 5-point Likert scale ranging from 1 (never) to 5 (very often). Scores for the monitoring dimension are positive, while scores for the acceptance dimension are reverse-coded. A higher total score indicates a higher level of mindfulness. Cronbach’s alpha/McDonald’s omega for the individual subscales and the total scale in the current sample were 0.74/0.73 (monitor), 0.78/0.78 (acceptance) and 0.82/0.85 (total scale). This scale had been used among the Chinese population with good reliability and validity (Liang et al., 2018).
Stroop Task
Cognitive Impulse Inhibition refers to an individual's ability to resist external or automatic thoughts or memories (Winstanley et al., 2006). The current study used the classic color-word Stroop task paradigm to examine participants' cognitive impulse inhibition in the context of cognitive conflict. In this task, participants must identify the color of words presented on a screen while ignoring the actual meaning of the words. The color of the words can be either the same as the meaning they represent (e.g., the word "green" in green color) or different (e.g., the word "yellow" in red color). The participants have to quickly select the key that corresponds to the color of the word, e.g. "red—key D", "yellow—key F", "blue—key J", "green—key K", while ignoring the interference caused by the meaning of the word. The specific procedure of this paradigm involves presenting participants with a 500 ms fixation sign ( +), followed by a 1500 ms key response stimulus, and then a 500 ms blank screen before the next trial. The formal experiment consists of a total of 96 trials, with 48 trials each for congruent conditions (where word color and word meaning match) and incongruent conditions (where word color and word meaning do not match). The measured variables in the study are accuracy and reaction time of the participants. It is generally assumed that higher error rates and longer average reaction times indicate poorer individual cognitive conflict inhibition.
Go/No-Go Task
Motor Impulse Inhibition is the ability of an individual to inhibit dominant motoric responses or automated behavioral responses (Winstanley et al., 2006). The current study used the classic experimental paradigm of the Go/No-Go task to measure individual motoric impulse inhibition ability. This task involves responding to either the number 1 or 9 displayed on the screen. Participants must respond to the presented number, with “9” being the Go stimulus and “1” being the No-Go stimulus. When the computer screen displays “9”, participants should press the “Q” key with their right index finger. However, when the computer screen displays “1”, participants should not respond. The task consisted of a total of 80 trials, comprising 60 Go stimuli and 20 No-Go stimuli, presented randomly. Each stimulus lasts for 150 ms, with an interval of 1000 ms between stimuli. The study variables include the accuracy and reaction time of the participants. A higher error rate and longer average reaction time are generally believed to indicate poorer individual motoric impulse inhibition ability.
The Delay Discounting Task
The term impulsive decision refers to individuals taking action without considering other possible choices and outcomes (Winstanley et al., 2006). The current study utilized an adapted version of the classic intertemporal choice experiment paradigm to measure individual impulsive decisions (McClure et al., 2004). The study presented participants with two options: a fixed immediate reward of £20 or a delayed reward that would increase by a specific percentage ((X'-X)/X) compared to the immediate reward, with waiting times of 7, 15, and 30 days. The delayed reward percentage ranged from 10 to 250%. Each waiting period presented a delayed reward ranging from 10 to 180% (10%, 15%, 20%, 30%, 50%, 70%, 90%, 120%, 150%, 180%), 15% to 215% (15%, 20%, 30%, 50%, 70%, 90%, 120%, 150%, 180%, 215%), and 20% to 250% (20%, 30%, 50%, 70%, 90%, 120%, 150%, 180%, 215%, 250%). The study employed an orthogonal design of delayed reward amount and delay time. The research variable was the immediate choice proportion of the participants. Generally, a higher immediate choice proportion indicates a greater tendency towards immediate gratification, reflecting more impulsive decision-making behaviors in individuals.
Experimental Instrumentation and Experimental Environment
The impulse behavior tasks were programmed using E-prime 2.0 (Psychology Software Tools, Sharpsburg, PA, USA). The experimental apparatus consisted of a Huawei MateBook 14 with a 14-inch color display with a resolution of 1024 × 768, true color, and a refresh rate of 60 Hz. Participants were positioned approximately 60 cm from the display, and all stimuli were presented at the center of the screen. All tests were performed in a soundproof room.
Data Analyses
Statistical analyses on self-report and behavioral data were conducted using IBM SPSS 28, and the figures were conducted using R 4.3.2 to show visualization of the data. To investigate how the mindfulness training (monitor and acceptance) affects impulsive behavior, the outcomes were submitted to repeated-measures ANOVAs. The between-subject factor was group (Mindfulness/Monitor/Control), and the within-subject factor time of measurement (pre-test/post-test/ half-month follow-up). The dependent variables were the following: the mindfulness level (PHLMS), the accuracy and reaction time on the Stroop task and Go/No-Go task. Based on the research by McClure et al. (2004), the current study divided the tasks into easy and difficult options. Easy options included 7 days (10–20%, 150–180%), 15 days (15–30%, 180–215%), and 30 days (20–50%, 215–250%). Difficult options included 7 days (30–120%), 15 days (50–150%), and 30 days (70–180%). A repeated-measures ANOVA was conducted on the immediate choice proportion of the Delay Discounting task with factors of 3 (group: Mindfulness/Monitor/Control) × 3 (measurement time: pre-test/post-test/half-month follow-up) × 2 (difficulty of choice: easy and difficult). Homogeneity of error variances was tested using the Mauchly test for sphericity. In case of significant results of the Mauchly test, a Greenhouse–Geisser correction was conducted. The level of significance was set as p < 0.05 (two-tailed). The level of significance is set at 5%. All presented results were corrected by Bonferroni corrections.
Results
Manipulation Check
A repeated measures ANOVA was conducted with a 3 (groups: Mindfulness/Monitor/Control) × 3 (measurement time: pre-test/post-test/half-month follow-up) design, using the PHLMS total score as the dependent variable. The results, as shown in Fig. 2 and Table 1, revealed a significant main effect of group (F(2, 67) = 35.75, p < 0.001, ηp2 = 0.52). Bonferroni post hoc tests revealed that the mindfulness group scored significantly higher than both the monitor group and the control group (p < 0.001). Additionally, there was no significant difference between the monitor group and the control group (p = 0.33); There was a significant main effect of measurement time (F(2, 134) = 11.09, p < 0.001, ηp2 = 0.14). Bonferroni post hoc tests revealed a significant increase in scores at post-test and half-month follow-up compared to pre-test scores (p < 0.001). There was no significant difference between post-test and half-month follow-up scores (p = 0.93); There was also a significant interaction between measurement time and group (F(4, 134) = 17.91, p < 0.001, ηp2 = 0.35). Simple effect analyses after bonferroni correction showed: there were no significant differences in scores among the three groups under pre-test conditions (p > 0.10); Under post-test and half-month follow-up conditions, the mindfulness group scored significantly higher than both the monitor and control groups (p < 0.001), there was no significant difference between the monitor group and the control group (p > 0.10). These results suggest that under pre-test conditions, the three groups of participants showed good homogeneity in mindfulness levels. After 1 week of mindfulness training and half a month later, the mindfulness group exhibited significantly higher mindfulness levels compared to the monitor group and the control group.
Fig. 2
Total PHLMS scores (M ± SE) between the mindfulness group, the monitor group, and the control group at different measurement times. † p < 0.08, *p < 0.05, **p < 0.01, ***p < 0.001
Table 1
The means and standard deviations (M ± SD) of the mindfulness group, monitor group, and control group on the PHLMS and the impulsive behaviors at pre-test, post-test, and half-month follow-up
Pre-test
Post-test
Follow-up
Mindfulness
Monitor
Control
Mindfulness
Monitor
Control
Mindfulness
Monitor
Control
PHLMS
53.25 ± 3.04
54.09 ± 1.00
53.91 ± 1.04
61.17 ± 5.82
53.70 ± 1.26
52.52 ± 1.81
59.08 ± 4.74
54.61 ± 2.13
53.74 ± 3.78
The accuracy of the Stroop task
.96 ± .03
.97 ± .03
.96 ± .03
.98 ± .02
.97 ± .02
.97 ± .02
.97 ± .02
.97 ± .02
.97 ± .02
The reaction time of the Stroop task (ms)
905.69 ± 102.45
955.70 ± 140.55
886.93 ± 151.78
749.72 ± 75.96
854.29 ± 143.93
828.59 ± 126.42
737.42 ± 87.59
832.82 ± 142.83
805.89 ± 130.37
The accuracy of the Go/No-Go task
.95 ± .06
.96 ± .06
.97 ± .03
.96 ± .12
.97 ± .04
.94 ± .20
.95 ± .19
.98 ± .19
.98 ± .04
The reaction time of the Go/No-Go task (ms)
250.96 ± 34.92
264.56 ± 40.17
253.36 ± 47.65
232.90 ± 31.38
268.39 ± 43.44
263.06 ± 49.01
244.20 ± 37.19
259.12 ± 48.43
258.68 ± 55.35
The immediate choice proportion of easy options
.56 ± .28
.48 ± .27
.42 ± .28
.47 ± .32
.40 ± .27
.45 ± .31
.38 ± .36
.36 ± .33
.39 ± .35
The immediate choice proportion of difficult options
.43 ± .37
.37 ± .32
.32 ± .29
.46 ± .32
.41 ± .28
.43 ± .31
.38 ± .36
.36 ± .32
.39 ± .35
×
Stroop Task Results
The repeated measures ANOVAS were conducted on the accuracy and reaction time of the Stroop task across 3 (groups: Mindfulness/Monitor/Control) × 3 (measurement times: pre-test/post-test/half-month follow-up).
With the accuracy on the Stroop task as the dependent variable, all groups had a mean of greater than 95% correct in all three time periods. The results (Table 1) showed that the main effect of group was not significant (F(2, 67) = 0.67, p = 0.52); the main effect of measurement time was significant (F(2, 134) = 7.55, p < 0.001, ηp2 = 0.10). Bonferroni post-hoc tests showed: The accuracy at post-test condition was significantly higher than the accuracy at pre-test and follow-up conditions (p < 0.001, p = 0.072); There was no significant difference between pre-test and follow-up accuracy (p = 0.24). The interaction between group and measurement time was not significant (F(4, 134) = 0.22, p = 0.93).
With the reaction time on the Stroop task as the dependent variable, the results (shown in Fig. 3 and Table 1) indicated that groups significantly differed (F(2, 67) = 3.15, p = 0.049, ηp2 = 0.09). Bonferroni post-hoc tests showed: The reaction time of the mindfulness group was significantly lower than that of the monitor group (p = 0.044). There were no significant differences between the reaction times of the control group and the mindfulness and monitor groups (p > 0.100); The main effect of measurement time was significant (F(2, 134) = 80.83, p < 0.001, ηp2 = 0.55). Bonferroni post-hoc tests showed: The reaction time was significantly higher at pre-test than at post-test and follow-up conditions (p < 0.001). There was no significant difference between reaction times at post-test and follow-up (p = 0.185); The interaction between group and measurement time was significant (F(4, 134) = 4.37, p = 0.002, ηp2 = 0.12). A simple effects analysis after bonferroni correction showed: Under pre-test condition, there were no significant differences in reaction times among the three groups (p > 0.10); Under post-test condition, the reaction time of the mindfulness group was significantly lower than that of the monitor and the control groups (p = 0.011 and p = 0.077). The difference between the reaction times of the monitor group and the control group was not significant (p > 0.100); Under follow-up conditions, the reaction time of the mindfulness group was significantly lower than that of the monitor group (p = 0.028). The reaction times of the control groups exhibited no statistically significant difference between the mindfulness and monitor groups (p > 0.100). These results indicate that compared to the monitor and control groups, the mindfulness group showed improved impulse control in the Stroop task after 1 week of mindfulness training.
Fig. 3
Reaction time on the Stroop task (M ± SE) between the mindfulness group, the monitor group, and the control group at different measurement times. † p < 0.08, *p < 0.05, **p < 0.01, ***p < 0.001
×
Go/No-Go Task Results
The repeated measures ANOVAS were conducted on the accuracy and reaction time of the Stroop task across 3 (groups: Mindfulness/Monitor/Control) × 3 (measurement times: pre-test/post-test/half-month follow-up).
With the accuracy on the Go/No-Go task as the dependent variable, all groups had a mean of greater than 95% correct in all three time periods. The results (Table 1) indicate that the main effect of group (F(2, 67) = 0.38, p = 0.68), the main effect of measurement time (F(2, 134) = 0.14, p = 0.87), and the interaction between group and measurement time (F(4, 134) = 0.51, p = 0.73) were not significant.
The results for the reaction time as the dependent variable showed that the main effect of group was not significant (F(2, 67) = 1.91, p = 0.16), nor was the main effect of measurement time (F(2, 134) = 0.16, p = 0.85). However, there was a significant interaction between group and measurement time (F(4, 134) = 2.53, p = 0.043, ηp2 = 0.07), as illustrated in Fig. 4 and Table 1. The results of the simple effect analysis after bonferroni correction indicate that, under the post-test condition, the reaction time of the mindfulness group was significantly shorter than that of the monitor group and the control group (p < 0.05). There was no significant difference between the monitor group and the control group (p > 0.10). Additionally, no significant differences were found among the three groups in the pre-test condition and the follow-up condition (p > 0.10). The results suggest that compared to the monitor and control groups, the mindfulness group showed improved impulse control in the Go/No-Go task after 1 week of mindfulness training.
Fig. 4
Reaction time on the Go/No-Go task (M ± SE) between the mindfulness group, the monitor group, and the control group at different measurement times. † p < 0.08, *p < 0.05, **p < 0.01, ***p < 0.001
×
Delay Discounting Task Results
Based on the research by McClure et al. (2004), the current study divided the tasks into easy and difficult options. Easy options included 7 days (10–20%, 150–180%), 15 days (15–30%, 180–215%), and 30 days (20–50%, 215–250%). Difficult options included 7 days (30–120%), 15 days (50–150%), and 30 days (70–180%). A repeated measures ANOVA was conducted on the immediate choice proportion of the Delay Discounting task with factors of 3 (group: Mindfulness/Monitor/Control) × 3 (measurement time: pre-test/post-test/half-month follow-up) × 2 (difficulty of choice: easy and difficult).
The results (shown in Fig. 5 and Table 1) showed that the main effect of groups was not significant (F(2, 67) = 0.231, p = 0.79); the main effect of measurement time was not significant (F(2, 134) = 0.105, p = 0.84); the main effect of difficulty of choice was significant (F(1, 67) = 37.969, p < 0.001, ηp2 = 0.36), indicating that the immediate choice proportion for difficult options was significantly lower than that for easy options. There are two significant two-way interactions, as follows: The interaction between group and measurement time was significant (F(4, 134) = 2.608, p = 0.038, ηp2 = 0.07). Simple effects analysis after bonferroni correction revealed that there was no significant difference in the immediate choice proportion between the mindfulness group, the monitor group and control group at pre-test, post-test, and follow-up conditions (p > 0.10). The interaction between measurement time and difficulty of choice was significant (F(2, 134) = 20.458, p < 0.001, ηp2 = 0.23). Simple effects analysis after bonferroni correction revealed that under easy options, the immediate choice proportion at post-test was lower than at follow-up (p < 0.001). The immediate choice proportion at the pre-test shows no significant difference between the post-test and follow-up (p > 0.10); Under difficult options, the immediate choice proportion at post-test was significantly higher than at pre-test (p = 0.017), and significantly higher than at follow-up (p = 0.003). There was no significant difference between pre-test and follow-up (p = 0.90). These results suggest that the impulse decision inhibition abilities of the mindfulness group did not significantly improve under post-test and follow-up conditions. All other interactions were non-significant.
Fig. 5
The immediate choice proportion of easy and difficult options at different measurement times for the positive mindfulness group, the monitor group, and the control group (violin plots show distributions, white dots indicate means. Rectangles show 95% confidence intervals)
×
Discussion
To investigate the impact and mechanisms of smartphone-based brief mindfulness meditation training on impulsive behaviors, the current study established a mindfulness group (monitor + acceptance), a monitor group and a control group based on the MAT. Cognitive impulsivity, motoric impulsivity and impulsive decision-making were assessed separately at pre-test, post-test and follow-up using the Stroop task, Go/No-Go task, and Delay Discounting task. Results indicated that participants receiving monitor and acceptance training exhibited increased mindfulness levels and demonstrated enhanced inhibitory control over impulsive behaviors, showing improvements in cognitive and motoric impulse inhibition capacities. However, the mindfulness (monitor + acceptance) training is ineffective for impulsive decision-making inhibition capacities.
The results of cognitive impulsive behavior found that the mindfulness group exhibited significantly shorter reaction times compared to both the monitor and control groups at the post-test. This finding is supported by previous studies in which both 6 and 8 weeks of mindfulness training significantly improved cognitive impulse inhibition in a healthy group (Allen et al., 2012; Prakash et al., 2020; Wang et al., 2012). However, Anderson et al. (2007) used a variant of the Stroop task and found that after training subjects in MBSR for 8 weeks, 2 hr per week, individuals in the brief mindfulness training group did not show significant differences in the Stroop task compared to the control group. They explained that it might be possible that the inconsistent results were due to the ceiling effect exhibited by the subjects. But the MBSR task indicated in that study was mainly designed to validate the role of the first structural component of mindfulness (monitor), and in combination with the results of the current study, another possibility is that the inconsistent results were due to the unidimensionality of the mindfulness training in the study by Anderson et al. (2007). The results of the current study show that brief mindfulness meditation training produces a de-automatization effect on cognitive impulse inhibition, which means mindfulness meditation training can effectively improve individuals' cognitive impulse inhibition.
The results of motoric impulsive behavior found that the mindfulness group exhibited significantly shorter reaction times compared to both the monitor and control groups at the post-test. Some recent studies have same findings (Ahne & Rosselli, 2024; Jensen et al., 2012; Pozuelos et al., 2019; Rahl et al., 2016). For instance, Pozuelos et al. (2019) used brain imaging techniques to found that a 3-week mindfulness training enhanced motoric inhibition in the Go/No-Go task, as evidenced by stronger N2 signals and larger ERN amplitudes in the mindfulness group. However, some studies have revealed that mindfulness training is ineffective to improve the motoric inhibition of impulsive behavior (Heeren et al., 2009; Korponay et al., 2019; Prakash et al., 2020). For instance, Heeren et al. (2009) found that an 8-week MBCT program did not significantly affect motoric inhibition as measured by the Go/Stop task. The inconsistent finding in the study by Heeren et al. (2009) may be attributed to two factors: there were the absence of a treatment control group; the MBCT program's primary focus on relapse prevention for individuals at high risk of depression relapse. Therefore, the results of the current study demonstrated that brief mindfulness meditation training produced a de-automatization effect on motoric impulse inhibition and effectively improved the subjects' motoric impulse inhibition.
The results of the accuracy on the Stroop task and the "Go/no-go" task found a null finding in the current study. The insignificant results cannot be considered as a basis for invalidating the mindfulness training. Because all participants had higher accuracy in the Stroop task and the "Go/no-go" task in the three different time periods (the means are all greater than 95%). And there was no significant difference in the results of the ANOVAs. Similar findings were reported across many studies (Rabi et al., 2020; Wang et al., 2012). For example, Wang et al. (2012) used 8 weeks of mindfulness training to intervene with healthy college students once a week for around 1.5 to 2 hr each time. It was found that the means of correctness of valid data in the Stroop task was all high (97.8% in the mindfulness group and 98.9% in the control group) and no differences were found in the analysis of variance (ANOVA). The response time results indicated that individuals in the mindfulness group had significantly lower response times on the Stroop task compared to the control group. Therefore, the insignificant results of the accuracy on the Stroop task and the "Go/no-go" task are one of auxiliary measurement indexes to improve the effectiveness in the results of the reaction time on the Stroop task and the "Go/no-go" task.
There was a surprising lack of significant findings related to impulsive decision-making. The results of the Delay Discounting task suggest that the mindfulness training in the mindfulness group couldn’t enhance individuals' ability to inhibit impulsive decision-making compared to the monitor and control groups. The mindfulness training not improved discounting rates for several possible reasons. Firstly, the mindfulness training emphasizes focusing on the present and does not specifically target tendencies to delay gratification which is central to delay discounting. The mindfulness training might actually be counterproductive to the goal of lowering rates of delay discounting which involves thinking about future consequences of behavior. Secondly, impulsivity is a multi-dimensional construct that could be impacted by mindfulness training in several ways (Shead et al., 2020). The inconsistent results observed in delay discounting tasks appears to suggest that MAT-based mindfulness training is ineffective in mitigating impulsive decision-making. However, as previously mentioned, there are numerous potential reasons for these unexpected results. Therefore, we cannot conclude that MAT is not an effective strategy for enhancing impulsive decision-making.
In the current study, the de-automation effect on cognitive and motoric impulsive behavior is facilitated by the components of monitor and acceptance. Drawing from the MAT (Lindsay & Creswell, 2016), it can be inferred that the de-automation effect of mindfulness training on impulsive behavior arises from the synergistic interplay between the two fundamental components of mindfulness: monitor and acceptance. Monitor training is designed to bolster individual attentional control and cognitive flexibility. It directs and sustains individual attention towards specific objectives while efficiently allocating attentional resources as required. Furthermore, in terms of cognitive flexibility, monitor training enhances adaptability to diverse environments and circumstances (Langer, 1989). Consequently, the enhancement of attentional capacity and cognitive flexibility enables individuals to effectively disrupt automatic information processing patterns. On the other hand, acceptance training assists individuals in cultivating a higher level of acceptance and adeptly managing their thoughts and emotions. By observing their experiences through monitor training and fostering a non-judgmental, authentic, and compassionate attitude towards themselves, individuals are encouraged to confront thoughts or behaviors associated with fear and anxiety rather than suppressing or avoiding them. This approach aids in diminishing maladaptive self-defense mechanisms and automated response (Bear, 2003). Yang and Zeng (2023) proposed that within the dual-system processing model, the monitor and acceptance dimension of mindfulness training targets distinct psychological structures involved in impulsive processing, working in tandem to mitigate impulsive behavior in individuals. This aligns with the results of the current study, which suggest that the emergence of the de-automation effect hinges on the collaborative influence of the monitor and acceptance dimensions.
Furthermore, the findings indicate that participants in the monitor group, which exclusively received monitor training, did not exhibit significant improvements in impulsive behavior. This outcome could be attributed to the possibility that solely enhancing monitoring skills may make participants more attuned to their automatic negative emotions, thoughts, or physical discomfort during the training. Prolonged Monitoring may lead individuals to continuously dwell on or even magnify these negative experiences, fostering a habitual inclination to reject perceived negativity and eliciting heightened negative emotional reactions (Lindsay & Creswell, 2019). However, another possibility is presented in the review by Simione and Saldarini (2023). They suggest that monitoring might not be a key component of the effect of mindfulness on psychological well-being. The key active component of mindfulness interventions is some form of acceptance. This possibility requires further research for validation. Notably, only individuals in the mindfulness group demonstrated an elevation in mindfulness levels post-training. These results underscore the pivotal and irreplaceable role of acceptance training in eliciting the de-automation effect, which serves to diminish impulsive behavior and elevate individual levels of mindfulness.
Expanding on the investigation, the current study has further explored the effects and sustainability of a 1-week mindfulness meditation training program delivered through smartphones. There has been offline research showing the benefits of brief mindfulness training, such as 20 min of training over three days, which can have an immediate positive effect, reducing symptoms such as fatigue, negative mood, and depression, and alleviating irritating pain (Zeidan et al., 2010). Winnebeck et al. (2017) conducted a study that showed a 7-day, 25-min-per-day training session on mindfulness was effective in reducing the level of depression in patients with acute depression in comparison to a control group. Additionally, Erisman and Roemer (2010) found that even a brief session of mindfulness training, such as a 10-min session, was effective in alleviating the negative emotions that individuals experience in response to external stimuli. Recent studies have also underscored the efficacy of online mindfulness training (Cavanagh et al., 2018; Walsh et al., 2019). The current study affirms the significant inhibitory effect of 1-week smartphone-based mindfulness training on part of impulsive behavior. However, the results also suggest that the de-automaticity concerning cognitive and motoric impulse inhibition disappeared after the 2-weeks follow-up period. This implies that the impact of brief mindfulness meditation training on impulsive behavior is immediate yet transient, emphasizing the necessity for prolonged practice to sustain positive effects. Nonetheless, brief mindfulness meditation training, yielding temporary results, remains practically significant. Moreover, the straightforward, cost-effective, and user-friendly smartphone-based mindfulness meditation training approach employed in the current study enables individuals who are hesitant to invest substantial time or resources in seeking professional guidance to seamlessly integrate mindfulness practices into their daily routines. This fosters present-moment monitoring and cultivates non-judgmental attitudes (Winnebeck et al., 2017). Thus, brief mindfulness meditation training via smartphones stands as an effective method for reducing some impulsive behavior.
Limitations and Future Research
The current study has some limitations in the participants and methods. Firstly, we must mention that we did not preregister the current study goals and hypotheses, which is best avoided in future research. Secondly, in the current study, the participants were drawn from a cohort of college students. Future studies need to further explore the effects of mindfulness training on different populations, such as adolescents who are more prone to impulsive behavior and individuals with impulse disorders. Thirdly, a recent study has identified specific cognitive detection brain networks for various types of mindfulness training modalities (Yordanova et al., 2021). This approach would allow researchers to explore how the monitor and acceptance dimensions of mindfulness training impact an individual's impulsive behavior through the lens of cognitive neuroscience.
There are several suggestions for future research and clinical applications to tailor mindfulness training for the impulsive people. Firstly, the current study suggests that the interventions for impulsive behaviors should consider the mindfulness training which combines monitor and acceptance based on the MAT. However, the study did not directly assess whether acceptance could be the only effective component of mindfulness training. To develop more effective and targeted programs, more research is needed to investigate the mechanisms of the mindfulness training. Secondly, regarding impulsive behavior, the results were mixed. This indicates a need for further investigation into the reasons for these outcomes. At the conceptual level, the varying effects of mindfulness training on impulsive behavior underscore the importance of recognizing the multidimensional nature of impulsive behaviors. This understanding could have clinical implications by enabling tailored interventions for individuals with specific impulse-related disorders (e.g., ADHD), helping clinicians choose the most suitable mindfulness-based approach for their clients' needs and characteristics. Thirdly, a follow-up study could consider employing long-term mindfulness training to monitor changes in individual impulsive behavior over an extended period. In conclusion, more multicenter, double-blind RCTs with a larger and more diverse participant pool is warranted to enhance the generalizability and external validity of the study’s findings while minimizing potential bias.
Acknowledgements
The authors are very grateful support of the participating school and program implementers and students’ time and willingness to participate in the current study.
Declarations
Ethical Approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Ningbo University.
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Use of Artificial Intelligence Statement
AI was not used.
Disclosure of Potential Conflicts of Interest
The authors declare that have no conflict of interest.
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