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Open Access 09-05-2024 | ORIGINAL PAPER

The Relationship Between Mindfulness and Impulsivity: The Role of Meditation

Auteurs: Rotem Leshem, Or Catz, Ayelet Nave

Gepubliceerd in: Mindfulness

Abstract

Objectives

Mindfulness and impulsivity traits are considered to be important aspects of mental well-being and health. These traits are often seen as opposing concepts, yet the nature of the relationship between them is unclear, mainly because they are complex to define. The aim of this research was to investigate the relationship between impulsivity and mindfulness, taking into account the impact of mindfulness meditation experience on this connection.

Method

A total of 174 mentally and physically healthy young adults were assigned to either a non-meditation group or a meditation group based on their experience in meditation practices. Participants completed self-report scales to evaluate their impulsivity and mindfulness traits.

Results

Trait impulsivity scales and dysfunctional impulsivity were negatively correlated with trait mindfulness, while functional impulsivity was positively correlated with trait mindfulness. While meditation practice significantly predicted trait mindfulness, its moderating effect on the relationship between impulsivity and mindfulness was limited.

Conclusions

The varying relationship between impulsivity subscales and trait mindfulness, together with the relatively limited association between meditation practice and these personality traits, emphasizes the importance of considering different aspects of impulsivity and acknowledging how individual differences affect the relationship between impulsivity and mindfulness.

Preregistration

This study is not preregistered.
Opmerkingen

Publisher's Note

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Mindfulness and impulsivity can be viewed as two concepts on a continuum. At one end of the continuum is mindfulness, which includes action with thought and the ability to observe and reflect, and at the other end is impulsivity, which includes action with little thought and a certain degree of automaticity without considering the possible consequences (Terres-Barcala et al., 2022; Wittmann et al., 2015).
Although there have been studies that show mindfulness and impulsivity to be generally negatively correlated (Lattimore et al., 2011; Murphy & MacKillop, 2012; Peters et al., 2011; Rajesh et al., 2013), few studies have reported positive correlations between them (Lu & Huffman, 2017; Vinci et al., 2016; Wittmann et al., 2015). These inconclusive findings emphasize the difficulties of operationalizing both mindfulness (Alvear et al., 2022; Bergomi et al., 2013; Somaraju et al., 2023) and impulsivity and the necessity to examine the relationship between them from a multidimensional point of view and to qualify the findings according to the specific components being measured (Peters et al., 2011). This would broaden and deepen an examination of the relationship between these traits, which can vary at the subcomponent level.
One established conceptualization of impulsivity delineates it into discrete subcomponents of cognitive functioning, namely acting impulsively in the moment (motor activation), difficulty in maintaining attention (attention), and a lack of careful planning and deliberation (lack of planning) (Patton et al., 1995). This multidimensional approach to impulsivity is further supported by Dickman's work (1990, 2000), emphasizing the distinction between two types of impulsivity. The first type is dysfunctional impulsivity, which aligns with the typical definitions of the trait and encompasses maladaptive aspects characterized by hasty decision-making and reckless or rash behavior with a lack of forethought, leading to negative outcomes. The second type, functional impulsivity, is associates with adaptive aspects that drive individuals to act quickly without planning, especially in risky situations or under certain reward conditions, denoting rapid decision-making with positive consequences.
According to this definition, it is plausible that mindfulness is positively correlated with functional impulsivity, due to their shared cognitive component of rapid information processing in the “here and now” and the ability to effectively attend to the properties of the task at hand, which can be advantageous for individuals with high levels of impulsivity in specific contexts (Claes et al., 2000; Leone & Russo, 2009; Smillie & Jackson, 2006). Thus, people who focus more on what is happening in the present moment, with the past or the future not being of immediate concern to them, can be characterized in terms of either mindfulness (Dane, 2011) or impulsivity (Evenden, 1999; Gassen et al., 2019), especially functional impulsivity.
However, it is important to note that the mechanisms underlying this state of consciousness are completely different between the two traits. For instance, impulsivity, as opposed to mindfulness, is a mere focus on external events to the exclusion of internal processes, with low levels of present-focused awareness.
Following this line of reasoning, both mindfulness and impulsivity emphasize orientation to the present, reflecting a person’s emphasis (or overemphasis) on living in the here and now (Murphy & MacKillop, 2012); however, high levels of mindfulness, in contrast to impulsivity, especially the maladaptive aspect of it, lead to different outcomes. Although both relate to how prone a person is to act on impulse, they are opposites; that is, greater mindfulness reflects a decreased likelihood of acting on an impulse and greater impulsivity reflects a greater likelihood of doing so (Murphy & MacKillop, 2012). If impulsivity is defined as a swift action without conscious planning or awareness and rapid emotional reactivity, then mindfulness is the contrary. Specifically, mindfulness is often contrasted with acting on autopilot. In this regard, one aspect of mindfulness describes the non-judgmental, present-focused awareness experienced in any given moment (Bishop et al., 2004; Lau et al., 2006; Medvedev et al., 2022; Tanay & Bernstein, 2013), while impulsivity is characterized by a present focus with little awareness and forethought.
While impulsivity is considered a risk factor for involvement in negative behaviors (e.g., addictions, violence, delinquency) (Blair, 2016; Gonge et al., 2022; Han & Park, 2023; Loya et al., 2023), mindfulness stands as a protective factor that not only mitigates such behaviors but also strengthens mental well-being and encourages productive behaviors (Schindler & Pfattheicher, 2023). Recognizing this, it becomes clear that the interplay between these two can significantly influence one’s behaviors.
Consequently, the importance of enhancing mindfulness and reducing impulsivity for adjustive and controlled behaviors is reflected in the continued growth of mindfulness-based intervention programs in the general and clinical population (Koenig, 2023; Peters et al., 2011; Tran et al., 2022; Yosep et al., 2023). Mindfulness skills may reduce impulsivity in several ways, such as by enhancing awareness of internal experiences, which facilitates the monitoring and management of impulsive behaviors often characterized by a lack of reflection and thoughtful intention (Miller & Racine, 2022; Peters et al., 2011). The cultivation of mindfulness skills through meditation practice, for example, which precludes impulsive thought and behavior through the maintenance of attention focused on the present moment and the qualities of acceptance, openness, and curiosity (Carrière et al., 2022; Stratton, 2006; Tran et al., 2022), is conceptually associated with enhancing behavioral control and reducing impulsivity. However, the evidence supporting the effectiveness of meditation in reducing impulsivity remains inconclusive and limited (Fekih-Romdhane et al., 2023; Korponay et al., 2019).
Moreover, the existing literature on mindfulness meditation, particularly in non-clinical populations, is comparatively scarce when contrasted with research on clinical populations. Most studies on the effects of mindfulness meditation have focused predominantly on mental health aspects, such as depression, anxiety, and stress, as well as physical outcomes (Hyland et al., 2015). Additionally, the majority of research exploring the link between meditation and impulsivity has focused on populations with clinical impulsivity-related disorders (e.g., Mantzios & Giannou, 2014) and neuropsychological disorders such as ADHD (Krisanaprakornkit et al., 2010; Mitchell et al., 2015; Santonastaso et al., 2020). In light of the limited research on mindfulness meditation in non-clinical populations and the predominant focus on clinical populations in studies exploring the link between meditation and impulsivity, Korponay et al. (2019) undertook a comprehensive examination of the effects of an 8-week mindfulness intervention on impulsivity and its associated neurobiological factors within a population of healthy adults. The overall results showed that the mindfulness intervention did not reduce impulsivity, nor did it produce changes in the neural correlates of impulsivity, compared to active (meditation-naïve participants) or wait-list control groups. However, looking at impulsivity subscales and the duration of meditation practice revealed that long-term meditators had lower attentional impulsivity and higher motor and non-planning impulsivity scores on the Barratt Impulsiveness Scale (BIS-11) than did meditation-naïve participants.
The need to consider the subcomponents of trait impulsivity when examining its relationship to mindfulness is evident. In addition, investigating differences in the relationships between the trait-level subcomponents of impulsivity and mindfulness might contribute to a future understanding of the effects of meditation (and the resultant mindfulness trait) on impulsivity.
Two commonly used measures of trait mindfulness employed in research, the Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003) and the Freiburg Mindfulness Inventory short form (FMI; Walach et al., 2006). The MAAS was originally designed for use with individuals both familiar and unfamiliar with mindfulness practices, making it suitable for the general population (Bergomi et al., 2013; González-Blanch et al., 2022; Ruiz et al., 2016). In contrast, the FMI questionnaire necessitates a certain level of familiarity with mindfulness practices to yield meaningful results. It is essential to acknowledge that the content validity of the MAAS presents significant challenges within the realm of research, despite its robust internal and external validity (González-Blanch et al., 2022; Rau & Williams, 2016; Van Dam et al., 2010). Therefore, in the current study, the MAAS served as a measure to support the FMI, contributing to the maintenance of the internal validity of the present study.
This study aimed to (1) examine the relationship between mindfulness and impulsivity traits, (2) investigate the role of mindfulness meditation experience in this relationship, and (3) compare trait mindfulness and impulsivity levels between meditators and non-meditators. Since meditation practice strengthens and enhances cognitive functions related to mindfulness and impulsivity traits, the present examination endeavored to gain a deeper understanding of the relationship between mindfulness and impulsivity.
We predicted that trait mindfulness would be negatively correlated with trait impulsivity and dysfunctional impulsivity, as measured by BIS-11 (Patton et al., 1995) and Dickman Impulsivity Inventory (DII; Dickman, 1990), respectively. Since this was the first study to examine the relationship between DII functional impulsivity and trait mindfulness, if any connection was found between them, we expected that high functional impulsivity would be associated with high mindfulness. This association would be due to the shared cognitive component of rapid processing of information in the “here and now” leading to positive outcomes. As a part of this examination, we also investigated whether mindfulness-based meditation practice attenuates the (negative) relationship between impulsivity and mindfulness traits. Mindfulness-based meditation methods (e.g., body scan or breathing) emphasize the focus of attention on the “here and now” and are related to strengthening and improving the cognitive and emotional functions underlying the studied variables (Bamber & Schneider, 2016; Lodha & Gupta, 2022; Malinowski, 2013; Prakash, 2021). Although the relationship between meditation practice and impulsivity is unclear (Fekih-Romdhane et al., 2023; Korponay et al., 2019; Mantzios & Giannou, 2014) and still requires further investigation, the relationship between meditation practice and mindfulness is well-established and supported by empirical evidence (D’Antoni et al., 2022; Greif & Kaufman, 2021; Kabat-Zinn, 2021; Sedlmeier, 2023; Verhaeghen, 2021). Given that meditation practice is associated with the facilitation of reflective processes and enhancement of conscious processes over automatic ones (Maran et al., 2021; Schuman-Olivier et al., 2020), we predicted that mindfulness meditation would significantly moderate and mitigate the impact of impulsivity, in particular trait impulsivity and dysfunctional impulsivity on mindfulness. In addition, we predicted that individuals with meditation practice experience would be high in trait mindfulness and low in impulsivity in particular as measured by BIS-11 and DII dysfunctional scales, compared with those who do not meditate.

Method

Participants

A total of 207 adult volunteers participated in the study. To assess their prior experiences with mindfulness meditation, participants were initially queried about their meditation practices. Those who affirmed their engagement in meditation were subsequently prompted to specify the type of meditation they practiced. Then, they were asked to answer two questions examining the duration and frequency of their meditation practice. Regarding the question about the duration (“Do you currently practice meditation? If so, how long have you been practicing?”), the participants were asked to mark a box according to how many years, months, weeks, or days they had been meditating. Regarding the question dealing with the frequency (“indicate the duration and frequency”), the participants were asked to check the corresponding box according to the number of days per week and number of minutes per session. Following data collection, the participants who reported practicing meditation for less than 50 hr were not included in the study. This criterion aimed to create a clear distinction between participants who did not meditate at all and those who meditated regularly. This resulted in a total of 174 out of 207 volunteers for the current analysis, of which 128 (73.6%) were women and 46 (26.4%) men (Mage = 28.08, SD = 7.23; age range: 21–45 years). Eighty-three participants (47.7%) had an academic education, 15 (8.6%) had diploma studies, 67 (38.5%) had a high school education, and nine (5.2%) indicated that they had another type of education. The exclusion criteria included no history of neurological or psychiatric illnesses or language-related disorders, including attention deficit hyperactivity disorder.
An a priori power analysis was conducted using G*Power version 3.1.9.7 (Faul et al., 2007, 2009) to determine the minimum sample size required to test the study hypotheses. The results indicated that for correlation, the bivariate normal model, that is, the required sample size to achieve 95% power for detecting a medium effect at a significance criterion of α = 0.05, was n = 115. For linear multiple regression of a fixed model, that is, R2 deviation from zero design with four predictors, the required sample size to achieve 95% power for detecting a medium effect at a significance criterion of α = 0.05 was n = 129. For an independent samples t-test, the required sample size to achieve 95% power for detecting a medium effect at a significance criterion of α = 0.05 was n = 152. Thus, the obtained sample size of n = 174 was adequate to test the study hypotheses.

Procedure

The research was carried out using Qualtrics, a dedicated software platform for conducting academic surveys online. The recruitment process was carried out through a dedicated university system for recruiting participants for course credit and through advertising on social networks dedicated to mindfulness meditation. Participation in the study was voluntary and without financial compensation. Before filling out the questionnaires, all participants were asked to sign an informed consent form stating that their participation in the study was voluntary and that they could withdraw from the study at any time.

Measures

The Barratt Impulsiveness Scale

The BIS-11 (Patton et al., 1995) questionnaire was designed to assess the trait impulsivity. The scale consists of 30 items, each scored on a four-point Likert scale ranging from 1 (rarely/never) to 4 (almost always/always). The questionnaire consists of the following three subscales: motor impulsiveness (MI; motor, perseverance); non-planning impulsiveness (NPI; self-control, cognitive complexity); and attentional impulsiveness (AI; attention, cognitive instability). The BIS-11 provides a total score ranging from 30 to 120 that serves as a global impulsivity measure. A total score between 52 and 71 is considered within normal limits for impulsiveness. A total score of 72 or more is used to classify an individual as highly impulsive (Stanford et al., 2009). The BIS-11 has adequate reliability (α = 0.83; Stanford et al., 2009). The Hebrew version used in this study had adequate reliability (α = 0.79), similar to the reliability scores reported in previous studies (α = 0.72—0.79; Glicksohn & Nahari, 2007; Leshem, 2016; Leshem & Glicksohn, 2007; Leshem & Yefet, 2019). The omega reliability coefficient was ω = 0.78 (95% CI [0.72, 0.84]).

The Dickman Impulsivity Inventory

The DII self-report questionnaire (Dickman, 1990) was developed to measure two types of impulsivity, namely dysfunctional and functional impulsivity. The DII consists of 23 items to be answered in a true/false answer format, of which 12 items measure dysfunctional impulsivity (e.g., “I often buy things without thinking if I can really afford it financially”) and 11 items measure functional impulsivity (e.g., “Most of the time, I can put my thoughts into words very rapidly”). The dysfunctional and functional impulsivity scales have adequate reliability (α = 0.85, α = 0.74, respectively). The Hebrew versions of the dysfunctional and functional scales had adequate reliability (α = 0.80, α = 0.76, respectively), similar to the reliability scores reported in a previous study by Ben-Yaacov and Glicksohn (2020; α = 0.78, α = 0.84, respectively). The omega reliability coefficient of the dysfunctional scale was ω = 0.76 (95% CI [0.72, 0.81]), and that of the functional scale was ω = 0.77 (95% CI [0.71, 0.82]).

The Mindful Attention and Awareness Scale

The MAAS (Brown & Ryan, 2003) is a 15-item scale designed to assess the core characteristic of mindfulness, namely, a receptive state of mind in which attention, informed by sensitive awareness of what is occurring in the present, simply observes what is taking place. Response options range from 1 (almost never) to 6 (almost always) (e.g., “I find it difficult to stay focused on what is happening in the present”). A higher score indicates a greater degree of mindfulness. The questionnaire was translated into Hebrew by the researcher and then re-translated into Hebrew and compared by two independent professional translators. The translated questionnaire had adequate reliability (α = 0.85). The omega reliability coefficient was ω = 0.86 (95% CI [0.83, 0.89]).

The Freiburg Mindfulness Inventory Short Form

The FMI (Walach et al., 2006) is a 14-item scale examining mindfulness components that relate nonjudgmental present-moment observation and openness to negative experience (e.g., “I am open to the present moment”; “I am able to smile when I notice how I sometimes make life difficult”) that utilizes a Likert scale ranging from 1 (rarely) to 4 (almost always). The short version was designed to measure the core of the mindfulness construct and capture all aspects of the long form (for the 30-item full form, see Buchheld et al., 2001) with a reliability of α = 0.79 to 0.86 (Kohls et al., 2009; Pfeifer et al., 2016; Trousselard et al., 2010). The questionnaire was translated into Hebrew by the researcher and then re-translated into Hebrew and compared by two independent professional translators. The translated questionnaire had adequate Cronbach reliability (α = 0.87). The omega reliability (ω = 0.87) (95% CI [0.84, 0.90]).

Data Analyses

SPSS version 28 and R version 4.3.1 were used for statistical analysis. Six indices of predictors were calculated as follows: the BIS-11 total score; the BIS attentional, motor, and non-planning subscales scores; and the DII functional and dysfunctional scores. A dichotomous moderator variable of meditation practice was used to divide the participants into two groups based on their experience with meditation practice. For this purpose, the cumulative meditation practice duration index was calculated as follows: Number of years of practice × 52 weeks × number of sessions per week × number of minutes in each practice / 60 (Pintimalli et al., 2023).
The participants without any meditation practice were assigned to the non-meditation group (coded as 0), totaling 121 participants, and the participants with at least 50 hr of meditation practice (Mmeditation = 920 hr, SD = 1276) were assigned to the meditation group (coded as 1), totaling 53 participants. We chose a 50-hr cutoff for the meditation group to ensure a minimum level of experience and regularity in meditation practice among participants. To evaluate the outcome measure, trait mindfulness, two dependent indices were calculated from the total scores of the MAAS and the FMI.
We conducted Pearson correlations to examine correlations between scores in the mindfulness and impulsivity self-reported questionnaires. Next, to compare the association between trait mindfulness and impulsivity levels among meditators and non-meditators, hierarchical regression analyses were conducted, with the MAAS and the FMI as the outcome variables (y). Each regression equation had three steps. First, age was entered as an independent variable. Second, the BIS-11 subscales and total scores and the DII functional and dysfunctional scores were entered as independent variables (x), together with the meditation practice variable. Third, the interactions between each of the independent variables, namely BIS-11, the DII functional and dysfunctional scores, and the meditation practice variable, were entered. Each of the independent variables was entered separately into the regression model. Lastly, an independent samples t-test was performed to examine the differences between the meditation and non-meditation groups on the mindfulness and impulsivity indices.

Results

Initial Screening

Initial screening of the data was conducted to determine whether there were statistically significant differences between the two groups in age and gender distribution. For age, an independent-samples t-test revealed that the participants in the non-meditation group (M = 24.98, SD = 4.55) were significantly younger than those in the meditation group (M = 35.15, SD = 7.27; t(172) = -9.40; p < 0.001). To test whether age correlated with the study variables, a Pearson correlation coefficient analysis was performed, showing positive correlations between age and the MAAS (r = 0.22; p < 0.01) and age and the FMI (r = 0.24; p < 0.01). A chi-square test revealed a significant relationship between gender and meditation practice, (χ2(1) = 5.00; p = 0.02), with 79% of women in the no-meditation group compared to 62% women in the meditation group. To test whether there were differences between women and men on the study variables, separate independent-samples t-tests were performed, showing no significant difference (p > 0.30). Based on these results, age was included in the regression analyses.

Observed Correlations Between Impulsivity and Mindfulness

Correlations between the BIS subscales and total score and the DII dysfunctional and functional scales were examined separately for the MAAS and the FMI (Table 1). The MAAS was negatively correlated with the BIS subscales and total score as well as the DFI scale, indicating that higher levels of impulsivity correspond to lower levels of mindfulness. The FMI was negatively correlated with the BIS AI subscale and BIS total score as well as the DFI scale, suggesting a consistent pattern of association between trait mindfulness and impulsivity. In addition, the FMI was positively correlated with the FI scale, implying a potential link between trait mindfulness, cognitive processes and adaptive aspect of impulsivity.
Table 1
Means, standard deviations, and correlations
Variable
M
SD
1
2
3
4
5
6
7
8
9
1. MAAS
56.99
11.01
         
2. FMI
38.14
6.68
0.54**
        
3. BIS sum
60.93
9.67
 − 0.48**
 − 0.27**
       
4. BIS AI
17.10
4.01
 − 0.70**
 − 0.49**
0.69**
      
5. BIS MI
20.49
4.02
 − 0.28**
 − 0.04
0.80**
0.35**
     
6. BIS NPI
23.34
4.65
 − 0.15*
 − 0.10
0.80**
0.26**
0.50**
    
7. FI
14.43
2.64
0.13
0.34**
0.07
 − 0.14*
0.24**
0.07
   
8. DFI
12.12
2.23
 − 0.33**
 − 0.25**
0.57**
0.35**
0.49**
0.46**
0.15*
  
MAAS Mindful Attention and Awareness Scale; FMI Freiburg Mindfulness Inventory; BIS-11 Barratt Impulsiveness Scale; MI Motor impulsivity subscale; NPI Non-planning impulsivity; AI Attentional impulsivity; FI Functional impulsivity; DFI Dysfunctional impulsivity
* p < 0.05, ** p < 0.01

The Effects of Trait Impulsivity and Mindfulness Practice on MAAS

Hierarchical regression models were used to test whether meditation practice moderated the relationships between the BIS total score, the BIS subscales, the FI or DFI, and the MAAS. Age was entered into the regression in the first step because of the differences in age according to the meditation variable (Table 2).
Table 2
Moderation analysis of impulsivity to MAAS, as moderated by meditation practice
 
Model 1
Model 2
Model 3
Variables
B
SE B
β
B
SE B
β
B
SE B
β
Age
0.33
0.11
0.22**
0.20
0.12
0.14
0.19
0.13
0.13
BIS-11 total score
   
 − 0.61
0.07
 − 0.53***
 − 0.65
0.08
 − 0.57***
Meditation practice
   
3.83
1.95
0.16*
 − 9.62
11.62
 − 0.41
BIS total score × meditation practice
      
0.22
0.19
0.58
R2
 
0.05
  
0.33
  
0.34
 
F for change in R2
 
8.50**
  
36.53***
  
1.38
 
Age
0.33
0.11
0.22**
 − 0.03
0.11
 − 0.02
 − 0.02
0.11
 − 0.01
AI
   
 − 1.90
0.15
 − .69***
 − 1.98
0.18
 − .72***
Meditation practice
   
2.37
1.68
0.10
 − 2.64
5.81
 − 0.11
AI × meditation practice
      
0.30
0.33
0.21
R2
 
0.05
  
0.50
  
0.50
 
F for change in R2
 
8.50**
  
77.78***
  
0.81
 
Age
0.33
0.11
0.22**
0.20
0.14
0.14
0.17
0.14
0.11
MI
   
 − 0.91
0.20
 − 0.32***
 − 1.01
0.22
 − 0.36***
Meditation practice
   
3.49
2.20
0.15
 − 12.64
12.47
 − 0.53
MI × Meditation practice
      
0.79
0.60
0.71
R2
 
0.05
  
0.15
  
0.16
 
F for change in R2
 
8.50**
  
10.91***
  
1.73
 
Age
0.33
0.11
0.22**
0.31
0.14
0.20*
0.24
0.14
0.16
NPI
   
 − 0.73
0.18
 − .30***
 − 1.03
0.21
 − 0.42***
Meditation practice
   
3.55
2.23
0.15
 − 22.86
9.74
 − 0.97*
NPI × Meditation practice
      
1.10
0.40
1.20**
R2
 
0.05
  
0.14
  
0.17
 
F for change in R2
 
8.50**
  
8.86***
  
7.74**
 
Age
0.33
0.11
0.22**
0.19
0.15
0.13
0.19
0.15
0.13
FI
   
0.27
0.31
0.07
0.31
0.36
0.08
Meditation practice
   
2.71
2.31
0.11
4.86
10.61
0.20
FI × Meditation practice
      
 − 0.14
0.69
 − 0.09
R2
 
0.05
  
0.06
  
0.06
 
F for change in R2
 
8.50**
  
1.07
  
0.04
 
Age
0.33
0.11
0.22**
0.23
0.14
0.15
0.23
0.14
0.15
DFI
   
 − 1.55
0.34
 − 0.33***
 − 1.61
0.38
 − 0.34***
Meditation practice
   
1.66
2.20
0.07
 − 1.93
10.28
 − 0.08
DFI × Meditation practice
      
0.30
0.84
0.15
R2
 
0.05
  
0.16
  
0.16
 
F for change in R2
 
8.50**
  
11.36***
  
0.13
 
MAAS Mindful Attention and Awareness Scale; BIS-11 Barratt impulsiveness Scale; MI Motor impulsivity subscale; NPI Non-planning impulsivity; AI Attentional impulsivity; FI DII functional impulsivity; DFI DII dysfunctional impulsivity; Meditation practice = 0 – non-meditation group, 1 – meditation group
* p < 0.05, ** p < 0.01, *** p < 0.001
The regression models with the MAAS as the outcome measure showed that age was significant in the first step. In the second step, the BIS-11 total score, the BIS subscales, and the DFI scale score significantly predicted the MAAS; that is, a decrease in impulsivity predicted an increase in trait mindfulness. Moreover, being in the meditation group significantly predicted the MAAS only with the BIS total score but not with the other measures, showing that meditation training predicted an increase in trait mindfulness. In the third step, there was a significant interaction between the meditation group and the BIS-11 NPI subscale, indicating a significant negative correlation between the NPI subscale and the MAAS among participants in the non-meditation group (β = -0.42; p < 0.001) (Fig. 1). No significant correlation was found between the NPI subscale and the MAAS among the participants with meditation training (β = 0.03, p = 0.83). There were no other significant interactions (p > 0.30).

The Effects of Trait Impulsivity and Mindfulness Practice on FMI

Hierarchical regression models were used to test whether meditation practice moderated the relationships between the BIS total score, the BIS subscales, the FI or DFI, and the FMI. Age was entered into the regression in the first step because of the differences in age according to the meditation variable (Table 3).
Table 3
Moderation analysis of impulsivity to FMI, as moderated by meditation practice
 
Model 1
Model 2
Model 3
Variables
B
SE B
β
B
SE B
β
B
SE B
β
Age
0.22
0.07
0.24**
 − 0.02
0.08
 − 0.02
 − 0.01
0.08
 − 0.01
BIS-11 total score
   
 − 0.20
0.05
 − 0.28***
 − 0.18
0.05
 − 0.25**
Meditation practice
   
6.06
1.32
0.41***
12.46
7.84
0.85
BIS total score × meditation practice
      
 − 0.11
0.13
 − 0.45
R2
 
.06
  
0.22
  
0.22
 
F for change in R2
 
10.35**
  
17.87***
  
0.69
 
Age
0.22
0.07
0.24**
 − 0.11
0.08
 − 0.12
 − 0.11
0.08
 − 0.12
AI
   
 − 0.76
0.11
 − 0.45***
 − 0.73
0.13
 − 0.43***
Meditation practice
   
5.56
1.22
0.38***
7.30
4.21
0.50
AI × meditation practice
      
 − 0.10
0.24
 − 0.12
R2
 
0.06
  
0.33
  
0.33
 
F for change in R2
 
10.35**
  
34.69***
  
0.19
 
Age
0.22
0.07
0.24**
 − 0.01
0.09
 − 0.01
 − 0.01
0.09
 − 0.01
MI
   
 − 0.11
0.13
 − 0.06
 − 0.11
0.14
 − 0.06
Meditation practice
   
5.78
1.38
0.39***
5.91
7.84
0.40
MI × Meditation practice
      
 − 0.01
0.38
 − 0.01
R2
 
0.06
  
0.15
  
0.15
 
F for change in R2
 
10.35**
  
8.95***
  
0.00
 
Age
0.22
0.07
0.24**
0.02
0.09
.02
0.02
0.09
0.02
NPI
   
 − 0.28
0.11
 − 0.18**
 − 0.31
0.13
 − 0.21*
Meditation practice
   
6.01
1.33
.41***
2.99
6.07
0.20
NPI × Meditation practice
      
0.13
0.25
0.22
R2
 
0.06
  
0.17
  
0.17
 
F for change in R2
 
10.35**
  
12.03***
  
0.26
 
Age
0.22
0.07
0.24**
 − 0.08
0.09
 − 0.08
 − 0.08
0.09
 − 0.08
FI
   
0.74
0.18
0.30***
0.75
0.20
0.30***
Meditation practice
   
5.71
1.30
0.39***
5.88
5.99
0.40
FI × Meditation practice
      
 − 0.01
0.39
 − 0.01
R2
 
0.06
  
0.23
  
0.23
 
F for change in R2
 
10.35**
  
18.58***
  
0.00
 
Age
0.22
0.07
0.24**
 − 0.01
0.09
 − 0.01
 − 0.01
0.09
 − 0.01
DFI
   
 − 0.62
0.21
 − 0.21**
 − 0.62
0.23
 − 0.21**
Meditation practice
   
5.27
1.35
0.36***
5.18
6.30
0.35
DFI × Meditation practice
      
0.01
0.52
0.01
R2
 
0.06
  
0.19
  
0.19
 
F for change in R2
 
10.35**
  
13.49***
  
0.00
 
FMI Freiburg Mindfulness Inventory; BIS-11 Barratt Impulsiveness Scale; MI Motor impulsivity subscale; NPI Non-planning impulsivity; AI Attentional impulsivity; FI DII functional impulsivity; DFI DII dysfunctional impulsivity; Meditation practice = 0 – non-meditation practice, 1 – meditation practice
* p < 0.05, ** p < 0.01, *** p < 0.001
The regression models were significant in the first step, showing that age predicted the FMI. The second step was also significant, showing that the BIS AI subscale, the NPI subscales, and the total scores, as well as the FI and DFI scales, predicted FMI. Specifically, a decrease in the BIS AI, the NPI, and the total scores, as well as the DFI scale, predicted an increase in trait mindfulness as measured by the FMI, and an increase in the FI scale predicted an increase in trait mindfulness. Moreover, meditation practice strongly predicted an increase in trait mindfulness as measured by FMI. In the third step, none of the interactions were significant.

Differences Between the Meditation Groups in Mindfulness and Impulsivity

T-tests for independent variables between meditation and non-meditation groups on the MAAS, the FMI, and the BIS-11 subscales and the total score and the DII functional and dysfunctional impulsivity scales are shown in Table 4. Regarding mindfulness traits, higher MAAS and FMI scores were observed in the meditation group compared to the non-meditation group, suggesting that engaging in meditation practice may contribute to the cultivation of mindfulness traits. Concerning trait impulsivity, lower BIS AI scores were found in the meditation group than in the non-meditation group, indicating potentially greater attentional control among individuals practicing meditation. Conversely, higher scores on the BIS NPI subscale were found in the meditation group compared to the non-meditation group. In addition, there was a marginally higher FI score in the meditation group compared to the non-meditation group. These findings point to a possible connection between meditation practice and the cognitive aspects of impulsivity.
Table 4
Independent-samples t-tests for meditation and non-meditation groups on mindfulness and impulsivity
Variable
Meditation practice
n
M
SD
t
Cohen’s d
MAAS
No
121
55.65
10.55
t(172) =  − 2.77, p < 0.01
0.46
Yes
53
60.55
11.10
  
FMI
No
121
36.43
6.35
t(172) =  − 5.35, p < 0.001
0.88
Yes
53
42.00
6.25
  
BIS-11
  Total score
No
121
60.61
10.35
t(172) =  − 1.21, p = 0.23
0.18
Yes
53
62.28
7.41
  
  AI
No
121
17.47
3.97
t(172) = 2.30, p = 0.02
0.38
Yes
53
15.98
3.86
  
  MI
No
121
20.31
4.28
t(172) =  − 1.40, p = 0.16
0.19
Yes
53
21.04
2.56
  
  NPI
No
121
22.83
4.43
t (172) =  − 3.38, p < 0.01
0.56
Yes
53
25.26
4.21
  
DII
  FI
No
121
14.31
2.76
t(172) =  − 1.96, p > 0.05
0.32
Yes
53
15.17
2.50
  
  DI
No
121
12.37
2.44
t(172) = 1.71, p = 0.09
0.25
Yes
53
11.79
1.86
  
MAAS Mindful Attention and Awareness Scale; FMI Freiburg Mindfulness Inventory; BIS-11 Barratt Impulsiveness Scale; MI Motor impulsivity subscale; NPI Non-planning impulsivity; AI Attentional impulsivity; FI Functional impulsivity; DI Dysfunctional impulsivity

Discussion

This study aimed to examine the relationship between mindfulness and impulsivity in a normative adult population, referring to the multifactorial structure of these two traits. As part of examining the relationship between mindfulness and impulsivity, the effect of meditation practice on this relationship was tested. To this end, the participants were divided into two groups, one that included those with experience in meditation practice and one that included those without experience in meditation practice. As previously mentioned, our primary measurement for assessing the mindfulness trait was the FMI questionnaire, while the MAAS questionnaire served as a supportive measure to bolster the obtained insights. Consequently, our discussion primarily centers on the FMI results, with a concise reference to the findings related to the MAAS.
Consistent with the first prediction, the results showed that both the FMI and the MAAS were negatively correlated with the BIS-11 total score and with the DII dysfunctional impulsivity subscale, suggesting that a high level of impulsivity is associated with a low level of mindfulness. Focusing on the FMI, there was a negative correlation with the attentional impulsivity subscale and a positive correlation with the DII functional impulsivity scale. These correlations may to some extent reflect the attentional functions that underlie both mindfulness and impulsivity traits. Specifically, attentional impulsivity (i.e., an inability to focus attention or concentrate; Stanford et al., 2009) was inversely associated with mindfulness. The same was the case for dysfunctional impulsivity, emphasizing the tendency to act with little forethought (Dickman, 1990), which was inversely associated with the ability to observe an experience without reacting. These findings strengthen the argument that mindfulness and impulsivity refer to attention characteristics that form a continuum, where the tendency to mindfulness with the ability to pay conscious attention and reflectivity is at one end and the tendency to impulsivity and low attentiveness and automatic thought processes is at the other end (De Wit, 2009; Herman, 2023; Maltais et al., 2020; Murphy & MacKillop, 2012).
In addition, the FMI was positively correlated with the functional aspect of impulsivity. This is presumably because of a common component of rapid processing of cognitive information in the “here and now,” which characterizes both mindfulness (Daniel et al., 2022; Hölzel et al., 2011; Jha et al., 2010) and functional impulsivity (Brunas-Wagstaff et al., 1994; Dickman, 1990) and allows for an optimal and adaptive response. According to Brown et al. (2009), mindfulness is not deliberative in nature; it involves the simple acts of observing without scrutiny, making comparisons, or evaluating events and experiences and is thus dissimilar to “self-awareness” or reflexive consciousness in other forms (Béres, 2009; De Verlaine, 2022). Mindfulness concerns non-interference with experience, suspending the categorical judgments that typically follow every perception rather quickly and thus is not a cold, cognitive process (Kotzé & Nel, 2016; Terres-Barcala et al., 2022; Walach et al., 2006). It is plausible, therefore, that the FMI measures aspects of mindfulness, such as openness to experience and a non-judgmental and accepting attitude (e.g., “I am open to the experience of the present moment”; “When I notice an absence of mind, I gently return to the experience”), which converge with functional impulsivity (Whiteside & Lynam, 2001), resulting in a positive association between them. Specifically, attention and awareness of the present, including reactivity to these experiences, depend on various attentional factors, among them signals, especially rewards or threats, that can attract one’s attention involuntarily (Suelmann et al., 2018). Having a prepared behavioral pattern at one’s disposal that gets executed in an automatic, reflex-like manner enables quick and efficient responses. These response patterns indicate a high-level preparedness to perform a desired action, and it can be based on learned automaticity created through repeated execution of a behavior in response to a trigger. With increased repetition, the cognitive effort required to decide on a behavior or movement and to implement it diminishes, transforming the response over time from a deliberate action into an overlearned habit. Or that the automatic attentional process can be based on keeping instructions on how to deal with an arising task or challenge in mind, one can execute the appropriate behavior rapidly without having to have learned it through repeated execution (Maran et al., 2021).
This suggests that elements capable of drawing one’s attention may exist unconsciously and be present in both impulsivity and mindfulness in an adaptive manner. Also, self-report-based mindfulness scales tend to reduce mindfulness to specific qualities that may be associated with it, but which may also be attributed to other states and/or traits (such as impulsivity) and do not capture the phenomenon, such as the ability to maintain attention or to be emotionally nonreactive (Frank & Marken, 2022).
In contrast to our second prediction, no mediating effect was observed on this relationship using the FMI. It is worth noting that, in the case of the MAAS, meditation practice emerged as a weaker predictor, compared to impulsivity scales. Furthermore, there was an interaction between meditation practice and non-planning impulsivity, indicating a significant negative correlation between non-planning impulsivity and the MAAS in the non-meditation group, but this correlation was not evident in the meditation group. This finding aligns with concerns about the content validity of the MAAS and supports the argument that the assessment of attentional lapses on the MAAS, along with response bias to items related to “mindfulness absent,” may encompass aspects of experience that significantly diverge from the qualities associated with mindfulness-based practices (e.g., Grossman, 2011).
Returning to the findings regarding the FMI, the absence of a mediating role of meditation practice in the relationship between impulsivity and mindfulness traits underscores the necessity to distinguish between reflexivity and mindfulness meditation. While mindfulness meditation involves the cultivation of awareness and attention to the present moment by observing and distancing oneself from thoughts and emotional reactions (decentering) as they occur (Chambers et al., 2008; Keng et al., 2011; Krishnakumar & Robinson, 2015; Peters et al., 2011), it does not aim to improve past events or prepare for future experiences (De Verlaine, 2022). Instead, for an effective response, mindfulness practice emphasizes embracing the present moment, letting go of current situations, focusing on breathing, maintaining a still position, and making minimal concentrated efforts (De Verlaine, 2022). This aspect of mindfulness may align more closely with a reflective practice.
In contrast, reflexive practice focuses on self-transformation and the generation of knowledge that extends beyond specific situations, fostering self-monitoring awareness and the ability to be both aware and critical about ongoing reflective improvement and adjustment' (Béres, 2009; McCaw, 2023). The absence of a moderating effect of mindfulness meditation in this study may indicate that cultivating reflexive processes within mindfulness training could be beneficial in disrupting the typical thinking–feeling–acting pattern associated with trait impulsivity (Franco et al., 2016; Lattimore et al., 2011). Reflexivity, a key aspect of metacognition, entails reflecting on one's thoughts, emotions, actions, and experiences and critically analyzing them from various perspectives, leading to a deeper understanding of one's internal cognitive dynamics and behavioral tendencies (Béres, 2009; Maran et al., 2021; McCaw, 2023; Smolka & Fisher, 2024; Vu & Burton, 2020). This heightened self-awareness, combined with self-transformation and analytical thought, may empower individuals to consciously adjust their thinking strategies and behaviors to improve learning outcomes (McCaw, 2023; Smolka & Fisher, 2024).
While impulsive automated behaviors can hinder individuals from adjusting their reactions as needed, engaging in mindful reflexivity meditation has the potential to impact attention regulation and metacognition. This practice helps to overcome habituation and achieve de-automatization, thereby facilitating sustained de-centered observation during mindfulness meditation (Maran et al., 2021). This, in turn, could lead to a more significant decrease in impulsivity and foster gradual enhancement of trait mindfulness over time (Kiken et al., 2015; McCaw, 2023; Sappio et al., 2023).
Relatedly, mindfulness meditation practice emerged as the stronger predictor of higher levels of mindfulness, as assessed by the FMI, in comparison to the impulsivity scales, with the exception of attentional impulsivity. This suggests that engaging in mindfulness practice might have a more pronounced impact on individuals’ levels of mindfulness components of nonjudgmental present-moment observation as well as openness to experience, and it may be indicative that it encompasses and promotes these components. Conversely, attentional impulsivity emerged as a more potent predictor for low levels of mindfulness in comparison to the impact of meditation practice. Specifically, the distinction between the focus attention component of impulsivity (e.g., “I don’t pay attention”) and mindfulness (e.g., “When I notice an absence of mind, I gently return to the experience of the here and now”) underscores the notion that challenges in maintaining attention may indeed hinder one’s capacity for mindful awareness of the present moment (Peters et al., 2011). However, this observation prompts contemplation on whether the “letting go” of distractions and the adoption of a minimized concentrating effort, as advocated by mindfulness meditation, are less effective in enhancing this specific facet of attentional mindfulness. It also raises the question of whether incorporating reflexive processes that encourage the examination of past experiences and future outcomes in mindfulness training (McCaw, 2023) would be more efficient in addressing attentional impulsivity. Reflexivity processes that promote a metacognitive distance and self-monitoring awareness may contribute to improving attentional control, a deficiency often associated with impulsivity (Parisi et al., 2023).
Continuing this line of reasoning, it is important to consider that meditation practice may affect participants differently and that its impact may vary among individuals. Meditation does not necessarily work in the same way for everyone, and individual characteristics such as well-being, mental health, physical health conditions, lifestyle factors, and psychological traits, should be taken into account as potential sources of variability in the response to meditation (see Buric et al., 2022; Warren et al., 2023). Furthermore, our study revealed age as a predictor of increased trait mindfulness, consistent with previous research findings (Fisher et al., 2022; Hut et al., 2021; Mahlo & Windsor, 2021). This age-related enhancement in mindfulness is likely attributable to the developmental improvement of cognitive and executive functioning associated with age, factors closely linked to higher trait mindfulness (Davidson & Kaszniak, 2015; MacAulay et al., 2022). However, we observed that the influence of age on trait mindfulness diminished when impulsivity trait and mindfulness practice variables were entered in the moderation analysis. While age may initially contribute to increased trait mindfulness, its influence diminishes when considering other factors such as impulsivity trait and mindfulness practice. This suggests that age, as a predictor of increased trait mindfulness, is influenced by individual differences in impulsivity and engagement in mindfulness practices, making the relationship complex. In other words, younger individuals who practice mindfulness and have lower impulsivity may exhibit levels of trait mindfulness comparable to older individuals. This highlights the importance of adopting a multifaceted approach when studying mindfulness predictors.
Looking at the differences between individuals with and without meditation practice experience in mindfulness and impulsivity traits, our third prediction was partially supported. In accordance with the prediction, the findings showed that participants with meditation practice were higher in trait mindfulness than those without meditation practice.
This supports the notion that mindfulness meditation practice encompasses and fosters trait mindfulness (Alhawatmeh et al., 2022; Himichi et al., 2021; Karl & Fischer, 2022; Kiken et al., 2015; Thiermann & Sheate, 2022), involving sustained attention to one’s ongoing sensory, cognitive, and emotional experience, without giving in to the natural tendency to react, elaborate, or evaluate (Bishop et al., 2004; Keng et al., 2011; Papies et al., 2012).
Regarding impulsivity, however, the findings obtained were mixed, namely, significant differences were observed between the two groups on the attentional and non-planning impulsivity subscales. For attentional impulsivity, the meditation practice group had a significantly lower score than the no-meditation group. This is in line with the prevailing claim in studies, according to which people with meditation experience, compared to those with no experience, have an improved ability to concentrate and maintain attention (Chen et al., 2022; Chimiklis et al., 2018; Gill et al., 2020; Goldberg et al., 2020; Lodha & Gupta, 2022; Sleimen-Malkoun et al., 2023). These are often considered to be weak and inadequate among those with high trait impulsivity (Korponay et al., 2019). In contrast, the non-planning impulsivity score was higher in the group with meditation practice than in the group without meditation experience. This finding is supported by the study of Korponay et al. (2019), which showed that adult participants with experience in meditation practice had higher levels of non-planning impulsivity than those without experience in meditation practice. The researchers concluded that these participants resorted to meditation practice to reduce their levels of impulsivity.
Planning is a cognitive process that involves setting a predetermined course of action to achieve a goal and continuously monitoring the execution until the goal (Hayes-Roth & Hayes-Roth, 1979; Mumford et al., 2017; Unterrainer & Owen, 2006). Thus, it is possible that the participants in the current study turned to meditation precisely because of their difficulties in planning ahead and their desire to overcome the tendency to act according to immediate rewards without considering future results. That is, they would meditate as a form of psychological “self-therapy” for self-improvement (Graham & Lewis, 2021; Wittmann et al., 2015), aiming to enhance their planning abilities.
Expending on this notion, mindfulness meditation strengthens the capacity to observe and accept thoughts, feelings, and behaviors without judgment, fostering self-understanding and potentially facilitating subsequent self-transformation processes (Matey, 2024). This heightened awareness enables individuals to recognize and address automatic patterns of thought and behavior, promoting personal growth and transformation (Herman, 2023; McCaw, 2023).
This explanation requires further investigation because it relates to a specific component of impulsivity, and it is unclear why this does not apply to the other components of impulsivity. It is possible that the differences found regarding attentional impulsivity were due to the fact that this component is affected by the practice of meditation in a relatively short time, most likely because the practice of mindfulness meditation acts directly and mainly on attention and concentration (Carter et al., 2005; Ivanovski & Malhi, 2007; Norris et al., 2018).
This is in contrast to the planning and foresight component, which involves multiple cognitive steps, including determining a course of action in advance to achieve a future goal along with continuous monitoring of the execution until the goal is achieved (Hayes-Roth & Hayes-Roth, 1979; Jurado & Rosselli, 2007), and may require a longer period of meditation practice before change can be seen. In this context, the cumulative duration of experience in meditation practice in the present sample was low to moderate relative to the cumulative duration of participants defined as having much experience in meditation in other studies in the field (e.g., Berkovich-Ohana et al., 2012, 2017; Wittmann et al., 2015).
Additionally, variations in interpretation of certain items on the BIS-11 scale among individuals with meditation experience may contribute to discrepancies in findings, reflecting different mental processes at different levels of training. By recognizing subtle, habitual facets of lived experience that often elude conscious awareness, such as patterns of cognitive and emotional reactivity, meditation cultivates the ability to direct attention to the unfolding stream of experience in the present moment (McCaw, 2023).
This understanding of meditation’s impact on cognition and reactivity underscores the inherent challenges in interpreting BIS-11 scale items. Similar to non-planning impulsivity, variations were identified in functional impulsivity, which could potentially reinforce the aforementioned explanation. Although these differences did not reach statistical significance, they were very close to it (p = 0.052). This suggests a plausible connection between functional impulsivity and rapid, efficient cognitive function, which may also manifest following meditation practice. This observation aligns with the diverse interpretations of the questionnaire items and the complexities associated with the concepts of impulsivity and mindfulness. In essence, individuals with higher levels of impulsivity may respond similarly to those with elevated mindfulness on certain questionnaire items, despite having different yet meaningful understandings of them.

Limitations and Future Research

Within the examination on the relationship between mindfulness and impulsivity, considering the effect on mindfulness practice in the current study, it is important to acknowledge certain limitations and areas for future research. Although the self-report questionnaires used in this study are the most widely used method of measuring these traits and exhibit high reliability, they do have limitations in terms of construct validity and content validity for both impulsivity (Hook et al., 2021; Leshem & Glicksohn, 2007; Vasconcelos et al., 2012) and mindfulness (Alvear et al., 2022; Baer, 2019; Enkema et al., 2020; Frank & Marken, 2022; Grossman, 2008, 2011). This is particularly significant when considering the relationship between these two traits, given the shared attentional characteristics. Specifically, respondents may interpret mindfulness scale items differently, depending on their understanding of terms such as “awareness,” “noticing,” “paying attention,” “judging,” and “present moment” (Alvear et al., 2022; Choi et al., 2021; Grossman, 2008, 2011; Somaraju et al., 2023). Similarly, impulsivity scale items that reference attentional components of the “here and now” and reflection may be subject to varying interpretations (Wittmann et al., 2015). Future studies that employ diverse methods, such as diary study methodology, cognitive performance tasks, and physiological markers, can complement and strengthen the findings related to the relationship between these multidimensional traits.
Additionally, the duration of meditation practice experience plays a role in the interpretation of questionnaire items. Individuals with experience in mindfulness meditation may attribute specific meanings to terms used in the self-reports, particularly FMI, which is designed more for experienced meditators. These interpretations can significantly differ from those of individuals who have never practiced mindfulness meditation (Choi et al., 2021; Frank & Marken, 2022; Grossman, 2008; Somaraju et al., 2023). In the present study, the meditation group consisted of individuals with limited to moderate experience, and this group was smaller in size than the non-meditation group. Expanding the participant pool to include individuals with extensive meditation backgrounds in future research would enhance the validity and comprehensiveness of the findings by providing a broader range of experiences and perspectives related to meditation. This would allow for a more detailed exploration of the effects of meditation practice on mindfulness and impulsivity traits across different levels of experience and expertise.
Relatedly, our participant pool primarily consists of students and individuals who actively engage in mindfulness practices, which may limit the generalizability of our findings to populations with similar demographics and interests (Rosenkranz et al., 2019). While a more homogeneous sample, as observed in our study, aids in reducing the confounding effects of other variables, we recommend that future research endeavors explore a broader sample with inclusive criteria to enhance the generalizability of findings.
Furthermore, different mindfulness practices, such as Focused Attention meditation, Open Monitoring meditation, and mindfulness-based stress reduction share the common denominator of strengthening attentional control processes (Lutz et al., 2008; Malinowski, 2013; Prakash, 2021); however, it is possible that the effects obtained in the current study depended on the meditation method used (Behan, 2020; Bowles et al., 2022; Frank & Marken, 2022; Yordanova et al., 2021). Hence, investigating how meditation practice impacts the interplay between impulsivity and mindfulness across different mindfulness training methods (e.g., reflexive processes; Vu & Burton, 2020) could expand and advance our existing knowledge. This research bears significance not only in the realm of theory but also in practical applications, since it can provide insights for the development of tailored meditation intervention programs aimed at mitigating impulsivity and enhancing mindfulness.
In summary, the findings of this study reveal a nuanced pattern of associations between impulsivity and trait mindfulness. Specifically, trait impulsivity, as assessed by the BIS-11 specific subscale and total score, along with DII dysfunctional impulsivity, demonstrated negative correlations with trait mindfulness. In contrast, DII functional impulsivity exhibited a positive correlation with trait mindfulness, as measured by the FMI. Additionally, while meditation practice emerged as a significant predictor for trait mindfulness, its mediating effect on the relationship between impulsivity and mindfulness was limited. Notably, the attentional impulsivity subscale displayed stronger predictive power in relation to lower levels of trait mindfulness.
These results coincide with variations observed between participants with and without meditation practice in impulsivity and mindfulness. The participants who engaged in meditation practice reported higher levels of mindfulness traits. However, differences in impulsivity between the two groups were primarily evident in specific subscales that constitute the maladaptive aspects of trait impulsivity.
At the conceptual level, the diverse associations between impulsivity scales and trait mindfulness underscore the importance of recognizing the multidimensional nature of impulsivity. This emphasizes that various personality characteristics, particularly those related to attentional components, can influence the nature of the relationship between impulsivity and mindfulness as well as the ways in which meditation practice impacts this relationship. This understanding can also have clinical implications by informing tailored interventions for individuals with specific impulsivity-related disorders, such as ADHD, thereby guiding clinicians in selecting mindfulness-based approaches that best suit their clients’ needs and characteristics.

Declarations

Ethics Statement

The research study was approved by the Institutional Review Board of the Bar-Ilan University.
All participants provided a written informed consent before they participated in the study.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Use of Artificial Intelligence Statement

AI was not used in the writing of this manuscript.
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Metagegevens
Titel
The Relationship Between Mindfulness and Impulsivity: The Role of Meditation
Auteurs
Rotem Leshem
Or Catz
Ayelet Nave
Publicatiedatum
09-05-2024
Uitgeverij
Springer US
Gepubliceerd in
Mindfulness
Print ISSN: 1868-8527
Elektronisch ISSN: 1868-8535
DOI
https://doi.org/10.1007/s12671-024-02371-0