mind wandering spanish

From Distraction to Mindfulness: Latent Structure of the Spanish Mind-Wandering Deliberate and Spontaneous Scales and Their Relationship to Dispositional Mindfulness and Attentional Control

• ORIGINAL PAPER
• Open access
• Published: 13 December 2022
• Volume 14 , pages 732–745, ( 2023 )

Cite this article

You have full access to this open access article

• Luis Cásedas   ORCID: orcid.org/0000-0001-5650-6332 1 , 2 ,
• Jorge Torres-Marín   ORCID: orcid.org/0000-0001-7663-0699 1 , 3 , 4 ,
• Tao Coll-Martín   ORCID: orcid.org/0000-0002-0591-4018 1 , 3 ,
• Hugo Carretero-Dios   ORCID: orcid.org/0000-0001-8822-3791 1 , 3 &
• Juan Lupiáñez   ORCID: orcid.org/0000-0001-6157-9894 1 , 2  

2084 Accesses

2 Citations

7 Altmetric

Explore all metrics

Mind-wandering is a form of internal distraction that may occur both deliberately and spontaneously. This study aimed to provide a psychometric evaluation of the Spanish version of the Mind-Wandering Deliberate and Spontaneous (MW-D/MW-S) scales, as well as to extend prior research investigating their associations with dispositional mindfulness (Five Facets Mindfulness Questionnaire) and with the ability for attentional control of external distraction (Attentional Control Scale).

In two large samples ( n 1  = 795; n 2  = 1084), we examined latent structure, item- and dimension-level descriptive statistics, and internal consistency reliability scores of the Spanish MW-D/MW-S scales. Partial correlations were used to evaluate their associations with dispositional mindfulness and attentional control. Multiple linear regression and relative weight analyses were used to investigate whether or not, and to what extent, the facets of mindfulness could be uniquely predicted by internal and external distraction.

The Spanish MW-D/MW-S scales demonstrated a two-factor structure, high internal consistency reliability scores, and good nomological validity. Dispositional mindfulness was independently explained by internal and external distraction. MW-S was the largest (negative) predictor of the scores of the Five Facet Mindfulness Questionnaire, being this association particularly strong for the facet Acting with awareness. Conversely, MW-D was mildly associated with increased mindfulness. In addition, attentional control was found moderately negatively associated with MW-S and mildly positively associated with MW-D.

Conclusions

Our results indicate that the Spanish version of the MW-D/MW-S scales are a useful tool to assess individual differences in deliberate and spontaneous mind-wandering, shed light on the relationship between mindfulness and both internal and external distraction, and accentuate the critical role of intentionality in the study of the mind-wandering phenomena.

Similar content being viewed by others

Positive Psychology: An Introduction

More Things in Heaven and Earth: Spirit Possession, Mental Disorder, and Intentionality

Mohammed Abouelleil Rashed

Brief Resilience Scale (BRS)

Avoid common mistakes on your manuscript.

Remaining attentive without getting distracted is a challenging endeavor. As the writer and inventor Hugo Gernsback ( 1925 ) described it, “[p]erhaps the most difficult thing that a human being is called upon to face is long, concentrated thinking” (p. 214). Whether it is sustaining attention to environmental stimuli or maintaining a train of thought in a goal-directed manner, external distraction can readily disturb our focus. This is the case, for example, of the noisy construction work across the street capturing our attention when we are trying to finish an important report. However, external, sensory stimuli are not the only cause by which we can get distracted; as Gernsback ( 1925 ) went on writing, “even if supreme quiet reigns, you are your own disturber practically fifty per cent of the time” (p. 214). In fact, the detour of our attention away from a given task can also be self-generated, or caused by internal distraction. This is the case, for instance, when repetitive thoughts about an uncertain personal circumstance are the reason why we struggle to finish our report. This kind of internally generated distraction refers to the phenomenon most commonly known as self-generated though, or mind-wandering.

Various specific definitions of mind-wandering have been proposed, each of them emphasizing different aspects. One of the most stablished views of mind-wandering defines it as the cognitive process by which we engage in thoughts unrelated to the current demands of the external environment (Schooler et al., 2011 ). This ground-breaking perspective of mind-wandering has generated a wealth of empirical findings and has greatly advanced our understanding of the topic. Being focused on thought content (i.e., task-unrelated thought), however, it does not address the dynamics of the thought process occurring during mind-wandering. In this vein, a second popular account understands mind-wandering as spontaneous thought, that is, as thought that is relatively unconstrained (Christoff et al., 2016 ). Under this view, the main feature of mind-wandering lies not in its content, but in how it transitions relatively freely from one mental state to the next. Note that while these are arguably the two most influential perspectives on mind-wandering within cognitive science, broader philosophical and metatheoretical accounts have also been proposed (see, e.g., Irving, 2016 ; Metzinger, 2013 ).

Likely due to its fundamentally private nature, mind-wandering has traditionally been relatively understudied as compared to other psychological phenomena. Over the last 15 years, however, the scientific interest in understanding why and how the mind wanders has seen a striking surge. A reason why this phenomenon may have inevitably gained popularity can be found in how ubiquitous it is. Conservative estimates of its prevalence indicate that we spend around 20% of our waking time in mind-wandering (Seli et al., 2018a ); less conservative estimations suggest that we spend up to 50% engaged in it (Killingsworth & Gilbert, 2010 ). Mind-wandering can be assessed using various subjective techniques, most commonly questionnaires, probe-caught, and self-caught methods (Smallwood & Schooler, 2015 ). Interestingly, mind-wandering has been linked not only with costs (e.g., impaired reading comprehension due to attentional disengagement) but also with certain benefits in areas including future planning or creative thought (Mooneyham & Schooler, 2013 ).

While mind-wandering was originally considered a single, unitary phenomenon, in recent years it has become increasingly acknowledged that it is best characterized, rather, as a family of related yet distinct processes (Seli et al., 2018c ) . One of the earliest and most prominent categorizations of the mind-wandering phenomena highlights that it can occur both with and without intention (Seli et al., 2016b ) . Whereas the latter refers to the automatic process by which our attention shifts from the external environment to internally generated cognitions, more often related to personal current concerns of neutral or negative valence, the former alludes to the same process but happening in a voluntary fashion, more commonly in relation to positively valenced content such as fantasies or daydreams (Carriere et al., 2013 ). Providing an example of the importance of this distinction, one study investigated the role of task difficulty in the prevalence of intentional and unintentional mind-wandering using thought-probes during a cognitive-behavioral assessment (Seli et al., 2016a ) . The study found that, although overall rates of mind-wandering did not differ across conditions, participants reported more intentional mind-wandering in the easy condition, but more unintentional mind-wandering in the difficult one. Had the distinction between intentional and unintentional mind-wandering been ignored, the authors would have incorrectly concluded that there was no effect of task difficulty over the rates of task-unrelated thought.

The tendency to engage in intentional versus unintentional mind-wandering has also been studied at the individual differences level. In this vein, Carriere et al., ( 2013 ) developed the Mind-Wandering: Deliberate ( MW-D ) and Mind-Wandering: Spontaneous ( MW-S ) scales to address the role of the intentionality of mind-wandering in its relationship to fidgeting (i.e., the tendency to make spontaneous, involuntary movements). The instrument was composed by eight statements (four items per scale) reflecting the proposed two-factorial structure of mind-wandering. Although this study lacked an assessment of the dimensionality of the MW-D/MW-S scales, it provided initial evidence of their discriminant associations by showing that only MW-S was a (positive) predictor of fidgeting (indicating that the tendency to make involuntary movements is related to involuntary, but not deliberate, forms of mind-wandering). More recently, Marcusson-Clavertz and Kjell ( 2018 ) conducted a formal psychometric validation procedure of the MW-D/MW-S scales, showing that they were optimally fitted by a two-factor solution (with the best fit attained excluding the third item from the MW-S) and demonstrated a psychometrically sound behavior, including strong measurement invariance across gender and time, and good reliability of their scores (α/ω ≥ 0.81/0.82; test–retest ≥ 0.75 [2-week-interval]). This initial validation study also showed that MW-D and MW-S differed in their prediction of external outcomes: Whereas MW-D was linked to openness and experience-sampling reports of intentional mind-wandering, MW-S predicted generalized anxiety and experience-sampling reports of unintentional mind-wandering.

Subsequent psychometric research has validated the MW-D/MW-S scales for use in other languages and cultures, including Chinese (Carciofo & Jiang, 2021 ), German (Martarelli et al., 2021 ), and Italian (Chiorri & Vannucci, 2019 ). These studies successfully replicated the original two-factor structure, and provided further evidence of their nomological validity by examining correlates with a wide range of external variables. Chiorri and Vannucci ( 2019 ) found that MW-S was more strongly correlated with other self-report measures of mind-wandering, and to attentional control, than was MW-D (while both scales predicted daydreaming to a similar extent). Martarelli et al., ( 2021 ) examined the associations of the MW-D and MW-S scales to trait boredom, similarly finding that the correlation was substantially weaker for MW-D than for MW-S. Carciofo and Jiang ( 2021 ) found that MW-S showed stronger positive correlations with negative affect and attentional lapses, and stronger negative correlations with agreeableness and positive affect; on the contrary, MW-D was more strongly positively associated to openness (in line with Marcusson-Clavertz & Kjell, 2018 ). Overall, these studies made possible to disentangle deliberate and spontaneous expressions of mind-wandering at the individual differences level in various cultural contexts other than the original (i.e., reinforcing the cross-cultural validity of the scales). Note however that, to date, there is no available version of the MW-D/MW-S scales that can be administered in Spanish samples.

Classically, mind-wandering has been considered antithetical to the construct of mindfulness, which can be broadly defined as the psychological inclination to attend to present-moment experience while having an attitude of acceptance towards it (Baer, 2019 ; Bishop et al., 2004 ). The distinction between intentional and unintentional mind-wandering, however, has revealed that this relationship may be more complex. In one study, Seli et al., ( 2015 ) investigated the unique contributions of the MW-D and MW-S scales to the five facets assessed by the Five Facets Mindfulness Questionnaire (FFMQ; Baer et al., 2006 ). The study found that the two types of mind-wandering were dissociable (i.e., an effect was observed for one but not the other, or the effects were in opposite direction) in their relationship to four of the five facets, and that deliberate mind-wandering was actually positively related to two of them (Observing and Non-reactivity to inner experience). These results thus nuanced the relationship between mindfulness and mind-wandering, emphasizing again the necessity of considering intentionality when investigating the mind-wandering phenomena.

As just described, the study by Seli et al., ( 2015 ) provided the first trait-level evidence characterizing the facets of mindfulness in terms of (spontaneous and deliberate) mind-wandering, or what we have termed above as internal distraction. However, to date, no study has yet attempted to extend these findings to encompass also external distraction as part of its nomological network. In particular, there are two specific sets of questions that remain to be addressed regarding external distraction, as it relates to internal distraction and mindfulness, as described next.

First, it is as yet unclear how MW-D and MW-S associate to the vulnerability to engage in external distraction. From an individual differences perspective, external distraction can be assessed with the Attentional Control Scale (ACS; Derryberry & Reed, 2002 ), a well-stablished two-factorial measure of the capacity to sustain ( Focus ) and reorient ( Shift ) attention in a goal-directed manner in the face of external events (e.g., music or other people talking around). Prior research has found that both Focus and Shift dimensions were largely negatively correlated to MW-S, while MW-D was only slightly negatively correlated (Carriere et al., 2013 ) or unrelated to them (Chiorri & Vannucci, 2019 ). However, and importantly, these studies relied exclusively on bivariate correlational analyses, which hinders the interpretation of their results given that MW-D and MW-S are also highly correlated constructs themselves. Instead, the study of the relationships of the MW-D/MW-S scales to attentional control or any other external variable is better suited by analytical approaches that can account for their commonality, thus quantifying the amount of variance that is uniquely explained by each of them (e.g., partial correlation or multiple linear regression analyses; Seli et al., 2015 ).

Second, it is also not known whether the tendency to engage in internal distraction (as assessed by MW-D and MW-S) and external distraction (as assessed by Focus and Shift) uniquely contribute to explain individual differences in the facets of mindfulness (as assessed by the FFMQ), and to what extent. Given that internal and external distraction are also expected to be moderately overlapping processes (Carriere et al., 2013 ; Chiorri & Vannucci, 2019 ; for a latent variable approach, see also Unsworth & McMillan, 2014 ), addressing both simultaneously as predictors of mindfulness is required to disentangle the distinctive contributions of each distraction-related dimension to the latter construct. Critically, without a combined analytical approach, it is not possible to know whether the variance common to mindfulness and internal distraction (as reported by Seli et al., 2015 ) is unique, or can be accounted for by individual differences in external distraction instead.

On the basis of these considerations, we conducted the present study pursuing two intertwined aims: (1) to develop and validate the Spanish-language version of the MW-D/MW-S scales for research use with Spanish samples and (2) to replicate and extend prior findings on the relationship between the facets of mindfulness (FFMQ), internal distraction (MW-D and MW-S), and external distraction (Focus and Shift). Regarding our second aim, and more precisely, we set out to (2a) replicate the findings by Seli et al., ( 2015 ) linking internal distraction and the facets of mindfulness; (2b) provide original evidence of the relationship between internal and external distraction; and (2c) provide original evidence of the unique contributions of internal and external distraction to the facets of mindfulness. In order to address our first aim, we conducted a forward- and back-translation procedure from the original instrument and evaluated its psychometric adequacy including item- and dimension-level distributional properties, dimensionality, and internal consistency reliability. Our second aim was addressed by means of partial correlations and multiple linear regressions combined with relative weight analyses. Note that while this second part was primarily motivated by an interest to empirically characterize the structure of relationships between dispositional mindfulness, mind-wandering, and attentional control, it was also a means to provide evidence of the nomological validity of the Spanish version of the MW-D/MW-S scales.

Participants

Two independent samples of 808 and 1095 participants were collected for this study. In both cases, the subjects were invited using the institutional email lists of the University of Granada, and participated in exchange of course credits (if they were undergraduate Psychology students) or monetary compensation (if they were students from other programs or university personnel). From each sample, we removed participants identified as completion time outliers (i.e., those with ± 3 standard deviations [SD] from the group mean in completing the survey; n excluded  = 13 and n excluded  = 11, respectively). The samples were thus finally comprised by 795 (sample 1 [S1]: 72.01% female; M age  = 23.80 years, SD  = 5.54) and 1084 (sample 2 [S2]: 74.91% female; M age  = 22.80, SD  = 5.49) participants. All subjects gave informant consent prior to participation.

The development of the Spanish version of the MW-D/MW-S scales comprised (1) translation of instructions for administration and items from the original English version (Carriere et al., 2013 ) into Spanish by two of the authors (LC and JL); and (2) independent back-translation into English by a professional native English translator. Inconsistencies between both versions were assessed through discussion and iterations of translation and back-translation until consensus among authors and translator was achieved.

In regard to the administration of the measures during the study session, the procedure was virtually identical for S1 and S2. After providing informant consent, participants were presented with a battery of sociodemographic questions, followed by the MW-D/MW-S, the FFMQ, and the ACS. Measures were implemented and data were collected online using the platform LimeSurvey ( http://www.limesurvey.org ). Participants were informed that their participation was voluntary and that they could withdraw from the study at any time.

Mind-Wandering Deliberate and Spontaneous Scales

The MW-D/MW-S scales (Carriere et al., 2013 ) comprise four items each, assessing the propensity to engage in task-unrelated thought or mind-wandering voluntarily (e.g., “I allow my thoughts to wander on purpose”) and involuntarily (e.g., “I mind wander even when I’m supposed to be doing something else”), respectively. Items are rated on a 7-point Likert scale ranging from 1 (“rarely”) to 7 (“a lot”), except for the third item of the MW-D (from 1 = “not at all true” to 7 = “very true”) and the third item of the MW-S (from 1 = “almost never” to 7 = “almost always”). The original English version has been recently validated by Marcusson-Clavertz and Kjell ( 2018 ), demonstrating adequate factorial and construct validity, as well as good internal consistency reliability scores (MW-D: ranging from α  = 0.86 to α  = 0.90; MW-S: ranging from α  = 0.81 to α  = 0.82). The psychometric properties of the Spanish version of the MW-D and MW-S can be found in the “ Results ” section. The items and instructions for administration of the scales are provided in Supplementary Material S1 .

Five Facets Mindfulness Questionnaire

The FFMQ (Baer et al., 2006 ; Spanish version by Cebolla et al., 2012 ) is a 39-item instrument rated on a 5-point Likert scale ranging from 1 (“never or very rarely true”) to 5 (“very often or always true”), designed to assess five distinct domains of trait mindfulness. (1) Observing (from here on referred to as Observe ), or the tendency to attend to and noticing internal and external experiences including sensations, emotions, and thoughts (e.g., “I notice the smells and aromas of things”). (2) Describing ( Describe ), or the ability to label internal experiences, and particularly emotions, with words (e.g., “I can usually describe how I feel at the moment in considerable detail”). (3) Acting with awareness ( Actaware ), or the tendency to be grounded on present-moment experience as opposed to behaving mindlessly or in autopilot (e.g., “I do jobs or tasks automatically without being aware of what I’m doing”, reversed item). (4) Non-judging of inner experience ( Nonjudge ), or the tendency to appraise thoughts and feelings from a non-evaluative stance (e.g., “I disapprove of myself when I have irrational ideas,” reversed item). And (5) non-reactivity to inner experience ( Nonreact ), or the capacity to experience thoughts and emotions without having to reflexively respond to nor being caught up by them (e.g., “I watch my feelings without getting lost in them”). The Spanish version of the FFMQ has shown adequate factorial and external validity, as well as good internal consistency reliability scores, both in previous research (ranging from α  = 0.80 to α  = 0.91; Cebolla et al., 2012 ) and in the two samples reported herein (see the “ Results ” section).

Attentional Control Scale

The ACS (Derryberry & Reed, 2002 ; Spanish by Pacheco-Unguetti et al., 2011 ) is a 20-item questionnaire rated on a 4-point Likert scale ranging from 1 (“almost never”) to 4 (“always”). It was developed to assess two distinct attention-related factors, namely the capacity to maintain the focus of attention in the presence of distractors (Focus; e.g., “I have difficulty concentrating when there is music in the room around me,” reversed item) and the ability to efficiently switch attention between tasks or stimuli including the reorienting of attention from distractors to the primary task (Shift; e.g., “After being interrupted, I have a hard time shifting my attention back to what I was doing before,” reversed item). While originally comprised by 20 statements, subsequent psychometric research has proposed alternative, more efficient versions of the scale (12-item version in Judah et al., 2014 ; 8-item version in Carriere et al., 2013 ). For the present study, we conducted three competing confirmatory factor analyses on the ACS as translated into Spanish by Pacheco-Unguetti et al., ( 2011 ) in order to obtain the best fitting version of the Spanish version of the scale (i.e., 20 vs. 12 vs. 8 items). As detailed in Supplementary Material S2 , the best fit was attained by the 8-item version, which was therefore the one used for analyses. The 8-item ACS has shown adequate internal consistency reliability scores, both in previous research (Focus: ranging from α  = 0.77 to α  = 0.81; Shift: ranging from α  = 0.69 to α  = 0.82; Carriere et al., 2013 ) and in the two samples reported herein (see the “ Results ” section).

Data Analyses

To analyze the psychometric properties of the MW-D/MW-S scales, first descriptive statistics (i.e., mean, standard deviation, skewness, and kurtosis) and corrected item-total correlations were computed for all the items. The dimensionality of both scales was assessed by means of a set of confirmatory factor analyses (CFAs) with robust maximum likelihood estimator. The relative fit of three models was tested: (a) one-factor structure or general factor of mind-wandering (model 1); (b) two-factor structure reflecting the deliberate and spontaneous components of mind-wandering (model 2); and (c) the same two-factor structure but excluding the item 3 of the MW-S (model 3) as recommended in the validation study of the original version of the scale (Marcusson-Clavertz & Kjell, 2018 ). Model fit was assessed following Kaplan’s ( 2009 ) recommendations, with CFI ≥ 0.90, TLI ≥ 0.90, RMSEA ≤ 0.08, and SRMR ≤ 0.08 reflecting adequate fit. After corroborating the internal structure of our scales, dimension-level descriptive statistics were calculated for the MW-D/MW-S scales, as well as for all other outcome variables, along with their internal consistency reliability coefficients using both Cronbach’s alpha (α) and McDonald’s omega (ω).

Pearson’s correlations were used to assess the bivariate relationships between MW-D/MW-S, FFMQ, and ACS. Subsequently, partial correlations were conducted to assess the unique associations of MW-D and MW-S (controlling for each other) with dispositional mindfulness and attentional control. Finally, multiple linear regressions along with relative weight analyses (RWAs) were conducted to assess the unique contributions of both internal distraction (MW-D and MW-S) and external distraction (Focus and Shift) to each of the mindfulness facets. By also introducing RWA into our analytic strategy, we overcame one limitation of the regression approach, namely that it does not reliably estimate the specific variance explained by each predictor under analyses, particularly when they are intercorrelated (see Tonidandel & LeBreton, 2011 ). To account for the influence of sociodemographics, age and sex were introduced in a first step in the regression model, and internal and external distraction variables in a second step (both methods: enter). For parsimony, only the final models are reported.

All the analyses were independently conducted in both S1 and S2. To control for the type I error rate, significance level was set at α  = 0.01 and results were only interpreted as true positives when replicated in both samples. To avoid drawing conclusions upon findings without practical significance, we set the smallest effect size of interest (SESOI) at r  = 0.10, R 2  = 0.01. Note that both S1 and S2 were sensitive enough to statistically detect effect sizes equal or higher than the SESOI, given α  = 0.01. We used Mplus 8.1 software (Muthén & Muthén, 2017 ) and RStudio 2021.09.0 (RStudio Team, 2021 ) to conduct the CFA and RWA, respectively; all other analyses were conducted in Jamovi 1.6.23 (Jamovi Project, 2021 ).

Psychometric Properties of the Spanish MW-D and MW-S Scales

Item analyses.

Descriptive statistics for all the items of the Spanish MW-D/MW-S scales in S1 and S2 are provided in Supplementary Material S3 . As shown, no floor/ceiling effects in item responses were detected (5.08 ≥  M  ≥ 2.96). High between-subject variabilities also emerged ( SD  ≥ 1.65). Skewness and kurtosis indexes strongly suggested scores for all items to follow the normal distribution ( ≤|2| in all cases; Pituch & Stevens, 2015 ). Finally, the items of both scales displayed high discrimination indexes in both samples (MW-D from 0.65/0.60 [item 4] to 0.81/78 [item 2] in S1/S2; and MW-S from 0.58/0.51 [item 1] to 0.67/62 [item 4] in S1/S2). Together, these results indicate adequate item properties for Spanish-language version of the MW-D/MW-S scales.

Factor Structure

As shown in Table 1 , fit indices indicated that both two-factor structures (models 2 and 3) outperformed the one-factor solution (model 1) in terms of model fit. Mirroring the Marcusson-Clavertz and Kjell’s ( 2018 ) validation study for the English version of the instrument, the exclusion of the item 3 of the MW-S scale (model 3) outperformed the version with the full set of items (model 2). Model 3 thus appeared as the best fitting factor structure, globally yielding acceptable to good fit indices across both S1 and S2. We thus conducted the remaining analyses excluding the item 3 of the MW-S scale. All items were significant and showed high loadings in their corresponding latent factors across both samples, namely MW-D ≥ 0.69/0.65 and MW-S ≥ 0.62/0.58 in S1/S2. Latent correlation between the scores of the MW-D and MW-S only reflected a moderated overlapping (≈ 0.50), which provides further support for a two-factorial model of mind-wandering as the most interpretable solution.

Descriptive Statistics and Reliability

As shown in Table 2 (upper rows), the mean scores, standard deviations, skewness, and kurtosis of the Spanish MW-D/MW-S scales closely resemble the values originally obtained by Marcusson-Clavertz and Kjell ( 2018 ). Importantly, skewness and kurtosis coefficients indicated normal-like distribution of the scores of the MW-D and MW-D across both S1 and S2 ( ≤|2| in all cases). In terms of the internal consistency of their scores, the Spanish MW-D/MW-S scales showed convincing coefficients for research purposes (all α/ω ≥ 0.71). Note that both estimators (α and ω) largely converged in S1 and S2.

Bivariate and Partial Correlation Analyses

As can be seen in Table 2 (mid and bottom rows), the distributional properties and internal consistency reliability scores of the FFMQ facets and ACS factors were also satisfactory. Table 3 displays the structure of bivariate correlations among the three sets of constructs, for both S1 and S2. The pattern is highly similar across samples, highlighting the stability of the associations. As found in previous research (Carriere et al., 2013 ; Chiorri & Vannucci, 2019 ; Seli et al., 2015 ), MW-S was more strongly related to both dispositional mindfulness and attentional control than MW-D, as reflected by a larger number of observed correlations and stronger effect sizes. However, also in line with these studies, the MW-D and MW-S scales showed to be strongly associated to each other ( r ≈ 0.40), which hinders direct interpretation of their bivariate relationships with external variables (Seli et al., 2015 ). Thus, a series of partial correlations was conducted next.

The results of the partial correlation analyses between MW-D and MW-S, controlling for each other, and the FFMQ facets in both S1 and S2 can be found in Table 4 (left columns). As shown, the pattern of findings was similar across samples. Observe was found to be positively related to both types of mind-wandering, while the only consistent finding revealed for Describe, Actaware, and Nonjudge was their negative relationship to MW-S. In turn, Nonreact demonstrated to be positively associated with MW-D. All other contrast resulted non-significant either statistically, p  ≥ 0.01, or practically, r  < 0.10, in at least one of both samples. Nonjudge and Actaware showed medium-to-large and large (negative) correlations to MW-S, respectively; effect sizes for all other results ranged from small to medium. This pattern of findings closely replicates the seminal study by Seli et al., ( 2015 ).

Going beyond Seli et al.’s ( 2015 ) findings, we further investigated the pattern of associations between deliberate and spontaneous mind-wandering (controlling for each other) and the two factors of attentional control. The results of these set of partial correlations are also displayed in Table 4 (right columns). As can be seen, small positive associations were found between MW-D and both Focus and Shift, while small-to-medium negative associations were revealed between these and MW-S. This was indicative of a double dissociation (see also Fig.  1 ).

Partial correlations of MW-D (controlling for MW-S) and MW-S (controlling for MW-D) with Focus and Shift in sample 1 ( n  = 795) and sample 2 ( n  = 1084). MW-D, Mind-Wandering: Deliberate; MW-S, Mind-Wandering: Spontaneous. * p  < 0.01; ** p  < 0.001 (two tailed)

Regression and Relative Weight Analyses

The results of the linear regression and RWA characterizing the five facets of mindfulness in terms of internal distraction (MW-D and MW-S) and external distraction (Focus and Shift) are provided in Table 5 and Table 6 for S1 and S2, respectively. They are also displayed graphically in Fig.  2 , which depicts for each of the mindfulness facets (1) the absolute variance explained by predictor ( R 2 ), and (2) the relative variance (or percentage of the total variance explained by the full model) explained by predictor (% R 2 ). As shown, the pattern of findings obtained by using this analytic approach, too, is consistent across samples. In step 1, age and sex demonstrated to be generally unrelated to mindfulness, with two exceptions: (1) older participants self-reported higher scores on Describe; and (2) male participants tended to self-report higher scores on Nonreact. Note that both effects were small in magnitude.

Stacked area plots depicting the absolute and relative variance explained (upper and lower panels, respectively) by internal distraction (MW-D and MW-S) and external distraction (Focus and Shift) across mindfulness facets, after controlling by age and sex, in sample 1 ( n  = 795) and sample 2 ( n  = 1084). MW-D, Mind-Wandering: Deliberate; MW-S, Mind-Wandering: Spontaneous

Internal and External distraction variables were introduced in the step 2 of the regression procedure. The total variance explained by the full model ranged from R 2  = 0.079 (Describe) to R 2  = 0.460 (Actaware), indicating that internal and external distraction explained the mindfulness facets by a medium to large extent in all cases. In both samples, internal distraction was the domain most strongly predictive of Observe, Actaware, and Nonjudge, whereas external distraction was the best predictor of Describe and Nonreact. Averaged across mindfulness facets and samples, the variance explained by internal and external distraction was R 2  = 0.111 and R 2  = 0.077, respectively; as per each individual factor, MW-S was the variable with the largest predictive power, R 2  = 0.086, followed by Shift, R 2  = 0.043, Focus, R 2  = 0.034, and MW-D, R 2  = 0.025.

At the level of individual mindfulness facets, each of them followed a distinctive pattern of contributions of MW-D, MW-S, Focus, and Shift, as described next (see also Fig.  2 ; the direction and statistical significance of the relationships are provided in Tables 5 and 6 ). The facet Observe demonstrated small-to-medium positive associations with both MW-D and MW-S. Describe, on the contrary, only appeared to be consistently linked to external distraction, showing a small-to-medium positive association with Shift. Notably, Actaware was the facet most strongly related to both internal and external distraction (see the central peak in the upper panels of Fig.  2 ), demonstrating medium positive associations with Focus and Shift, and a large negative association with MW-S. Nonjudge, in turn, showed a pattern similar to the former facet but of reduced magnitude, revealing small-to-medium positive associations with Focus and Shift, and a medium negative association with MW-S. Finally, Nonreact showed positive associations in the small-to-medium range with MW-D, Focus, and Shift. All other predictors resulted non-significant either statistically, p  ≥ 0.01, or practically, R 2  < 0.01, in at least one of both samples.

Based on data from two independent samples comprising over 1800 participants, the present study aimed to evaluate the psychometric adequacy of the Spanish version of the MW-D/MW-S scales and to replicate and extend prior findings of their relationship with the facets of mindfulness and attentional control. The psychometric evaluation of the Spanish MW-D/MW-S scales indicated adequate validity and reliability. Factor analyses confirmed that the instrument is best characterized as two distinct factors reflective of deliberate and spontaneous or mind-wandering, as was initially conceived by Carriere et al., ( 2013 ). Mirroring the study formally assessing the psychometric properties of the original version of the scales (Marcusson-Clavertz & Kjell, 2018 ), the best model fit was attained excluding the third item from the MW-S scale; we thus recommend future research not include it into analyses. All remaining items showed convincing distributional properties, as did the two mind-wandering dimensions themselves. In all cases, internal consistency coefficients (α/ω) were ≥ 0.71 for MW-S and ≥ 0.86 for MW-D, which can be interpreted as evidence of high reliability, specially taking into account the concision and brevity of administration of the scales, composed by 3 and 4 items, respectively.

We successfully replicated the seminal findings relating spontaneous and deliberate mind-wandering to the five facets of mindfulness (Seli et al., 2015 ). There was only one exception, namely: whereas a negative relationship between Non-reactivity to inner experience and MW-S was reported originally, we could only reproduce this result in our second sample (but not in the first one). This seeming discrepancy, however, may not be surprising in the context of a fairly small effect size. Note that the statistical power achieved by our first sample ( n  = 795) to capture true effects of small size ( ρ  = 0.10) with a two-tailed test ( α  = 0.01) was 0.60; meaning that the probability of committing a type II error was 40% (Faul et al., 2009 ). To further explore this interpretation, we conducted a fixed-effects meta-analysis of the results across both samples ( n  = 1879), which afforded a statistical power of 0.96 in the same scenario. A small yet significant negative partial correlation between Non-reactivity to inner experience and spontaneous mind-wandering was revealed ( r  =  − 0.12, p  < 0.001; see Supplementary Material S4 for details). Considering also this result, the pattern of findings obtained with the Spanish MW-D/MW-S in the present study appears virtually interchangeable with the findings obtained by Seli et al., ( 2015 ) using the original scales.

Interestingly, our assessment of the relationships between deliberate and spontaneous mind-wandering (controlling for each other) and the two factors of attentional control revealed the existence of a double dissociation: While participants more susceptible to engage in spontaneous mind-wandering also reported higher vulnerability to external distraction, those with a higher propensity to engage in mind-wandering in a voluntary fashion reported being less vulnerable to it (regarding both Focus and Shift). This finding is suggestive of the idea of “strategic” mind-wandering, which posits that individuals are able to and benefit from modulating their level of mind-wandering to accommodate the demands of the environment (e.g., Seli et al., 2018b ). Prior research has shown that this ability differs across individuals and situations. For instance, it has been shown that participants with high versus low working memory capacity display less mind-wandering during high demanding tasks (Kane & McVay, 2012 ), while, on the contrary, tend to engage more in mind-wandering when task demands are low (Levinson et al., 2012 ). In line with these findings, our results suggest that the proclivity to voluntarily let the mind wander, presumably when the environmental demands are more permissive, may be protective in more attention-demanding situations not only against subsequent task-unrelated though (as prior studies suggest) but also against becoming distracted by external events.

The present study also revealed various key aspects of the relationship between dispositional mindfulness and internal and external distraction. While, as discussed above, both deliberate and spontaneous mind-wandering have shown predictive capacity in explaining inter-individual variability in the facets of mindfulness (Seli et al., 2015 ), our study extend these results by showing that the capacity for attentional control of external distraction independently explains the facets of mindfulness over and above the variance accounted for by the mind-wandering factors. This finding, moreover, seems relatively stable across mindfulness facets, as in four of them at least one of the two factors of attentional control significantly contributed to explain a unique proportion of variance (the only exception was Observe). Complementarily, in all but one case, both deliberate and spontaneous mind-wandering were retained as significant predictors of the mindfulness facets after including Focus and Shift in the regression model (the previously observed relationship between Describe and MW-S was entirely accounted for by external distraction). Importantly, these findings indicate that internal and external distraction are (partially) independent domains in their relationship to dispositional mindfulness, being both relevant insofar the two of them uniquely contribute to explain it.

On average, internal distraction showed greater predictive capacity than did external distraction in explaining individual differences in dispositional of mindfulness (11.1% vs 7.7% of variance). While the contribution of external distraction was evenly shared by Focus and Shift (3.4% and 4.3% of variance), the great majority of the variance explained by internal distraction was accounted for by spontaneous mind-wandering—by far the stronger predictor across mindfulness facets (8.6% of variance on average). Importantly, these results suggest that dispositional mindfulness, while also protective against external distraction, is most strongly predictive of a decreased vulnerability to engage in mind-wandering, particularly without intention (note however that for Observe, the effect was in the opposite direction). By contrast, the results also indicate that dispositional mindfulness is linked, to a lesser degree, to an increased tendency to engage in mind-wandering voluntarily (2.5% of variance).

This latter finding echoes the one discussed above about the positive link between deliberate mind-wandering and attentional control, in that both indicate that the proclivity to allow the mind to wander on purpose, presumably in low attention-demanding contexts, may be mildly linked to traits that are adaptive in nature. Interestingly, both results are in line with earlier research indicating that mind-wandering may come not only with costs but also with certain benefits (e.g., Franklin et al., 2013 ; Gable et al., 2019 ), while in addition suggest that the intentionality with which it occurs may be a critical aspect determining its adaptive value. This can be interpreted under the so-called content and context regulation hypothesis (Smallwood & Andrews-Hanna, 2013 ), which proposes that the adaptive or maladaptive nature of a given mind-wandering episode is dependent on both its thought content and the task context in which it appears. While speculative, it seems reasonable to conceive deliberate mind-wandering as characterized by being positive in content and deployed in contexts where it is not critical for performance in the primary task, maximizing its adaptive value. As will be further discussed below, future research may find fruitful to further examine the intentionality of mind-wandering under the context and content regulation framework.

A finer-grained analysis at the level of individual mindfulness facets revealed that each of them was characterized by a distinctive pattern of unique contributions of the factors of distraction. While discussing these patterns in detail is beyond the scope of the present report, there is one salient observation worth mentioning: Acting with awareness was, by a large difference, the facet of mindfulness most strongly predicted by both internal and external distraction (28.8% and 16.5% of variance, respectively). Indeed, the total variance explained for this facet was more than twice than for any of the remaining ones. Importantly, virtually all variation accounted for by internal distraction was attributable to spontaneous mind-wandering (deliberate mind-wandering did not reach significance as predictor in any of our two samples). Acting with awareness thus appeared as the most protective facet against distraction, being particularly strongly associated to a decreased vulnerability to involuntarily engage in task-unrelated thought. This finding is consistent with the theoretical characterization of dispositional mindfulness, within which Acting with awareness was originally described as “attending to one’s activities of the moment [as] contrasted with behaving mechanically while attention is focused elsewhere” (Baer et al., 2008 , p. 330). It is also consistent with recent meta-analytical evidence indicating that Acting with awareness is the only mindfulness facet reliably linked with enhanced performance across a range of cognitive-behavioral attentional tasks, most of which are presumably affected by both external and internal types of distraction (Verhaeghen, 2021 ).

All in all, the main contributions of the present study can be summarized as follows. First, we have shown that the Spanish MW-D/MW-S scales have favorable psychometric properties, including factor structure, distributional properties, and internal consistency reliability scores. We have also shown that they have adequate nomological validity, since they displayed a notably similar pattern of relationships with the facets of mindfulness as compared to the original scales, while also demonstrating satisfactory discriminant properties in relation to the factors of attentional control. Collectively, these findings suggest that the Spanish MW-D/MW-S scales constitute a promising measure to assess individual differences of intentional and unintentional mind-wandering with Spanish samples. Second, we have shown that dispositional mindfulness, as primarily driven by the facet Acting with awareness, is independently associated to both enhanced attentional control of external distractions and, more prominently, decreased vulnerability to spontaneous mind-wandering. We have also shown that deliberate mind-wandering, by contrast, is mildly associated to increased dispositional mindfulness. Deliberate mind-wandering, in addition, was also found to be mildly linked to greater attentional control, which in turn was linked to diminished spontaneous mind-wandering. Together, these findings broaden our understanding of the relationship between mindfulness and (internal and external) distraction, while continue to accentuate the critical role of intentionality in the study of the mind-wandering phenomena.

Limitations and Future Research

This study is not without limitations. First, we used convenience samples primarily composed of young, well-educated, healthy participants mostly without meditation experience, a methodological feature that precludes the generalization of our conclusions beyond this particular population. In light of this, future research must consider extending our results to other distinct, more specific populations. Relatedly, future studies may find it fruitful to examine the variables assessed here in their interaction with mindfulness meditation training. In particular, given the strong link we observed between Actaware and MW-S, future research could test whether mindfulness-based interventions explicitly targeting this particular facet are specifically efficacious in reducing maladaptive, involuntary forms of mind-wandering. Second, the model fit of the CFA, while generally good, had margin for improvement. To obtain an even clearer representation of the latent structure of mind-wandering, future studies could consider creating additional indicators specifically addressing central aspects of each type of mind-wandering, so as to more strongly demarcate its two-factorial nature.

Third, our results were entirely based on self-report measures, which place them at risk of method bias (Podsakoff et al., 2012 ) and other artifacts (Quigley et al., 2017 ). Future research must consider exploring the correlates of deliberate vs. spontaneous mind-wandering using alternative methodologies, such as cognitive-behavioral tasks tapping into distractibility processes; as for their relation to mindfulness, the breath counting task may serve as an alternative, more ecological assessment (Levinson et al., 2014 ). Finally, and as outlined above, future studies may find it fruitful to explore the intentionality of mind-wandering in light of the content-context regulation hypothesis (Smallwood & Andrews-Hanna, 2013 ). For instance, it is conceivable that the positive links of deliberate mind-wandering with mindfulness and attentional control were stronger in individuals who are especially skillful at engaging in strategic mind-wandering, and that do so about topics particularly positive or constructive (and vice versa). Future research is warranted to further explore this intriguing possibility.

Data, Materials, and Code Availability

The data and the R scripts used for analyses are provided at the Open Science Framework ( https://osf.io/ceg89/ ).

Baer, R. A. (2019). Assessment of mindfulness by self-report. Current Opinion in Psychology, 28 , 42–48. https://doi.org/10.1016/j.copsyc.2018.10.015

Article   PubMed   Google Scholar  

Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment, 13 (1), 27–45. https://doi.org/10.1177/1073191105283504

Baer, R. A., Smith, G. T., Lykins, E., Button, D., Krietemeyer, J., Sauer, S., Walsh, E., Duggan, D., & Williams, J. M. G. (2008). Construct validity of the five facet mindfulness questionnaire in meditating and nonmeditating samples. Assessment, 15 (3), 329–342. https://doi.org/10.1177/1073191107313003

Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmoda, J., Segal, Z. V., Abbey, S., Speca, M., Velting, D., & Devins, G. (2004). Mindfulness: A proposed operational definition. Clinical Psychology: Science and Practice, 11 (3), 230–241. https://doi.org/10.1093/clipsy/bph077

Article   Google Scholar  

Carciofo, R., & Jiang, P. (2021). Deliberate and spontaneous mind wandering in Chinese students: Associations with mindfulness, affect, personality, and life satisfaction. Personality and Individual Differences, 180 , 110982. https://doi.org/10.1016/j.paid.2021.110982

Carriere, J. S. A., Seli, P., & Smilek, D. (2013). Wandering in both mind and body: Individual differences in mind wandering and inattention predict fidgeting. Canadian Journal of Experimental Psychology, 67 (1), 19–31. https://doi.org/10.1037/a0031438

Cebolla, A., García-Palacios, A., Soler, J., Guillen, V., Baños, R., & Botella, C. (2012). Psychometric properties of the Spanish validation of the Five Facets of Mindfulness Questionnaire (FFMQ). The European Journal of Psychiatry, 26 (2), 118–126. https://doi.org/10.4321/S0213-61632012000200005

Chiorri, C., & Vannucci, M. (2019). Replicability of the psychometric properties of trait-levels measures of spontaneous and deliberate mind wandering. European Journal of Psychological Assessment, 35 (4), 459–468. https://doi.org/10.1027/1015-5759/a000422

Christoff, K., Irving, Z. C., Fox, K. C. R., Spreng, R. N., & Andrews-Hanna, J. R. (2016). Mind-wandering as spontaneous thought: A dynamic framework. Nature Reviews Neuroscience, 17 (11), 718–731. https://doi.org/10.1038/nrn.2016.113

Derryberry, D., & Reed, M. A. (2002). Anxiety-related attentional biases and their regulation by attentional control. Journal of Abnormal Psychology, 111 (2), 225–236. https://doi.org/10.1037/0021-843X.111.2.225

Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41 (4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

Franklin, M. S., Mrazek, M. D., Anderson, C. L., Smallwood, J., Kingstone, A., & Schooler, J. W. (2013). The silver lining of a mind in the clouds: Interesting musings are associated with positive mood while mind-wandering. Frontiers in Psychology, 4 , 583. https://doi.org/10.3389/fpsyg.2013.00583

Article   PubMed   PubMed Central   Google Scholar  

Gable, S. L., Hopper, E. A., & Schooler, J. W. (2019). When the muses strike: Creative ideas of physicists and writers routinely occur during mind wandering. Psychological Science, 30 (3), 396–404. https://doi.org/10.1177/0956797618820626

Gernsback, H. (1925). The Isolator. Science and Invention, 13 (3), 214–281.

Google Scholar  

Irving, Z. C. (2016). Mind-wandering is unguided attention: Accounting for the ‘“purposeful”’ wanderer. Philosophical Studies, 173 (2), 547–571. https://doi.org/10.1007/s11098-015-0506-1

Jamovi Project. (2021). jamovi (Version 1.6.23) [Computer software]. https://www.jamovi.org

Judah, M. R., Grant, D. M. M., Mills, A. C., & Lechner, W. V. (2014). Factor structure and validation of the attentional control scale. Cognition and Emotion, 28 (3), 433–451. https://doi.org/10.1080/02699931.2013.835254

Kane, M. J., & McVay, J. C. (2012). What mind wandering reveals about executive-control abilities and failures. Current Directions in Psychological Science, 21 (5), 348–354. https://doi.org/10.1177/0963721412454875

Kaplan, D. (2009). Structural equation modeling: Foundations and extensions (2nd ed.). SAGE Publications. https://doi.org/10.4135/9781452226576

Book   Google Scholar  

Killingsworth, M. A., & Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science, 330 (6006), 932–932. https://doi.org/10.1126/science.1192439

Levinson, D. B., Smallwood, J., & Davidson, R. J. (2012). The persistence of thought: Evidence for a role of working memory in the maintenance of task-unrelated thinking. Psychological Science, 23 (4), 375–380. https://doi.org/10.1177/0956797611431465

Levinson, D. B., Stoll, E. L., Kindy, S. D., Merry, H. L., & Davidson, R. J. (2014). A mind you can count on: Validating breath counting as a behavioral measure of mindfulness. Frontiers in Psychology, 5 , 1202. https://doi.org/10.3389/fpsyg.2014.01202

Marcusson-Clavertz, D., & Kjell, O. N. E. (2018). Psychometric properties of the spontaneous and deliberate mind wandering scales. European Journal of Psychological Assessment, 35 (6), 878–890. https://doi.org/10.1027/1015-5759/a000470

Martarelli, C. S., Bertrams, A., & Wolff, W. (2021). A personality trait-based network of boredom, spontaneous and deliberate mind-wandering. Assessment, 28 (8), 1915–1931. https://doi.org/10.1177/1073191120936336

Metzinger, T. (2013). The myth of cognitive agency: Subpersonal thinking as a cyclically recurring loss of mental autonomy. Frontiers in Psychology, 4 , 931. https://doi.org/10.3389/fpsyg.2013.00931

Mooneyham, B. W., & Schooler, J. W. (2013). The costs and benefits of mind-wandering: A review. Canadian Journal of Experimental Psychology, 67 (1), 11–18. https://doi.org/10.1037/a0031569

Muthén, L. K., & Muthén, B. O. (2017). MPlus user’s guide (8th ed.). Muthén & Muthén.

Pacheco-Unguetti, A. P., Acosta, A., Marqués, E., & Lupiáñez, J. (2011). Alterations of the attentional networks in patients with anxiety disorders. Journal of Anxiety Disorders, 25 (7), 888–895. https://doi.org/10.1016/j.janxdis.2011.04.010

Pituch, K. A., & Stevens, J. P. (2015). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM’s SPSS (6th ed.). Routledge. https://doi.org/10.4324/9781315814919

Podsakoff, P. M., Mackenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63 (1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452

Quigley, L., Wright, C. A., Dobson, K. S., & Sears, C. R. (2017). Measuring attentional control ability or beliefs? Evaluation of the factor structure and convergent validity of the attentional control scale. Journal of Psychopathology and Behavioral Assessment, 39 (4), 742–754. https://doi.org/10.1007/s10862-017-9617-7

RStudio Team. (2021). RStudio (Version 2021.09.0) [Computer software]. http://www.rstudio.com

Schooler, J. W., Smallwood, J., Christoff, K., Handy, T. C., Reichle, E. D., & Sayette, M. A. (2011). Meta-awareness, perceptual decoupling and the wandering mind. Trends in Cognitive Sciences, 15 (7), 319–326. https://doi.org/10.1016/j.tics.2011.05.006

Seli, P., Carriere, J. S. A., & Smilek, D. (2015). Not all mind wandering is created equal: Dissociating deliberate from spontaneous mind wandering. Psychological Research Psychologische Forschung, 79 (5), 750–758. https://doi.org/10.1007/s00426-014-0617-x

Seli, P., Risko, E. F., & Smilek, D. (2016a). On the necessity of distinguishing between unintentional and intentional mind wandering. Psychological Science, 27 (5), 685–691. https://doi.org/10.1177/0956797616634068

Seli, P., Risko, E. F., Smilek, D., & Schacter, D. L. (2016b). Mind-wandering with and without intention. Trends in Cognitive Sciences, 20 (8), 605–617. https://doi.org/10.1016/j.tics.2016.05.010

Seli, P., Beaty, R. E., Allan, J., Smilek, D., Oakman, J., & Schacter, D. L. (2018a). How pervasive is mind wandering, really? Consciousness and Cognition, 66 , 74–78. https://doi.org/10.1016/j.concog.2018.10.002

Seli, P., Carriere, J. S. A., Wammes, J. D., Risko, E. F., Schacter, D. L., & Smilek, D. (2018b). On the clock: Evidence for the rapid and strategic modulation of mind wandering. Psychological Science, 29 (8), 1247–1256. https://doi.org/10.1177/0956797618761039

Seli, P., Kane, M. J., Smallwood, J., Schacter, D. L., Maillet, D., Schooler, J. W., & Smilek, D. (2018c). Mind-wandering as a natural kind: A family-resemblances view. Trends in Cognitive Sciences, 22 (6), 479–490. https://doi.org/10.1016/j.tics.2018.03.010

Smallwood, J., & Andrews-Hanna, J. (2013). Not all minds that wander are lost: The importance of a balanced perspective on the mind-wandering state. Frontiers in Psychology, 4 , 441. https://doi.org/10.3389/fpsyg.2013.00441

Smallwood, J., & Schooler, J. W. (2015). The science of mind wandering: Empirically navigating the stream of consciousness. Annual Review of Psychology, 66 (5), 487–518. https://doi.org/10.1146/annurev-psych-010814-015331

Tonidandel, S., & LeBreton, J. M. (2011). Relative importance analysis: A useful supplement to regression analysis. Journal of Business and Psychology, 26 (1), 1–9. https://doi.org/10.1007/s10869-010-9204-3

Unsworth, N., & McMillan, B. D. (2014). Similarities and differences between mind-wandering and external distraction: A latent variable analysis of lapses of attention and their relation to cognitive abilities. Acta Psychologica, 150 , 14–25. https://doi.org/10.1016/j.actpsy.2014.04.001

Verhaeghen, P. (2021). Mindfulness as attention training: Meta-analyses on the links between attention performance and mindfulness interventions, long-term meditation practice, and trait mindfulness. Mindfulness, 12 , 564–581. https://doi.org/10.1007/s12671-020-01532-1

Download references

Funding for open access publishing: Universidad de Granada/CBUA LC was supported by a doctoral fellowship from “la Caixa” Foundation (ID 100010434; fellowship code LCF/BQ/DE18/11670002). JTM was supported by a postdoctoral fellowship “Margarita Salas” at the University of Granada, financed by the European Union–Next Generation EU funds. TCM was supported by a doctoral fellowship (FPU17/06169). HCD was supported by research projects grant from the Spanish Agencia Estatal de Investigación, Ministerio de Economía y Competitividad (PID2019-104239 GB-I00/SRA (State Research Agency/ https://doi.org/10.13039/501100011033 )). JL was supported by research projects grants from the Spanish Agencia Estatal de Investigación, Ministerio de Economía y Competitividad (PID2020-114790 GB-I00) and Junta de Andalucía (PY20_00693). This paper is part of the doctoral dissertation of the first author under the supervision of the last author. Funding for open access charge: Universidad de Granada / CBUA.

Author information

Authors and affiliations.

Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain

Luis Cásedas, Jorge Torres-Marín, Tao Coll-Martín, Hugo Carretero-Dios & Juan Lupiáñez

Department of Experimental Psychology, University of Granada, Granada, Spain

Luis Cásedas & Juan Lupiáñez

Department of Research Methods in Behavioral Sciences, University of Granada, Granada, Spain

Jorge Torres-Marín, Tao Coll-Martín & Hugo Carretero-Dios

Department of Social Psychology and Quantitative Psychology, Universitat de Barcelona, Barcelona, Spain

Jorge Torres-Marín

You can also search for this author in PubMed   Google Scholar

Contributions

LC: conceptualization, methodology, investigation, data curation, formal analysis, visualization, writing—most of original draft, review, and editing; JTM: conceptualization, methodology, formal analyses, writing—part of original draft, review, and editing; TCM: conceptualization, methodology, writing—review and editing; HCD: conceptualization, methodology, supervision, writing—review and editing; JL: conceptualization, methodology, supervision, project administration, funding acquisition, writing—review and editing.

Corresponding author

Correspondence to Luis Cásedas .

Ethics declarations

Ethical approval.

The study was conducted according to the ethical principles established by the 1964 Declaration of Helsinki and its later amendments, and was as part of a larger research project (PSI2017-84926-P) approved by the University of Granada Ethical Committee (536/CEIH/2018).

Informed Consent

All subjects provided informed consent.

Conflict of Interest

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 41 KB)

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cásedas, L., Torres-Marín, J., Coll-Martín, T. et al. From Distraction to Mindfulness: Latent Structure of the Spanish Mind-Wandering Deliberate and Spontaneous Scales and Their Relationship to Dispositional Mindfulness and Attentional Control. Mindfulness 14 , 732–745 (2023). https://doi.org/10.1007/s12671-022-02033-z

Download citation

Accepted : 21 November 2022

Published : 13 December 2022

Issue Date : March 2023

DOI : https://doi.org/10.1007/s12671-022-02033-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Deliberate mind-wandering
• Spontaneous mind-wandering
• Mindfulness
• Acting with awareness
• Attentional control
• Individual differences
• Find a journal
• Publish with us
• Track your research

Psychology: Research and Review

• Open access
• Published: 02 June 2017

Translation and validation of the Mind-Wandering Test for Spanish adolescents

• Carlos Salavera 1 , 2 ,
• Fernando Urcola-Pardo 3 ,
• Pablo Usán 1 , 2 &
• Laurane Jarie 1 , 2  

Psicologia: Reflexão e Crítica volume  30 , Article number:  12 ( 2017 ) Cite this article

6026 Accesses

9 Citations

1 Altmetric

Metrics details

Working memory capacity and fluent intelligence influence cognitive capacity as a predictive value of success. In line with this, one matter appears, that of mind wandering, which partly explains the variability in the results obtained from the subjects who do these tests. A recently developed measure to evaluate this phenomenon is the Mind-Wandering Questionnaire (MWQ).

The objective of this work was to translate into Spanish the MWQ for its use with adolescents and to validate it and to analyze its relation with these values: self-esteem, dispositional mindfulness, satisfaction with life, happiness, and positive and negative affects.

A sample of 543 secondary students: 270 males (49.72%) and 273 females (50.28%) were used, who completed the questionnaire, and also did tests of self-esteem, dispositional mindfulness, satisfaction with life, happiness, and positive and negative effects. The transcultural adaptation process followed these steps: translation, back translation, evaluation of translations by a panel of judges, and testing the final version.

Validity analyses were done of the construct (% explained variance = 52.1), and internal consistency was high (α = .766). The coefficients of correlation with the self-esteem, MASS, satisfaction with life, happiness, and affects scales confirmed the questionnaire’s validity, and a multiple regression analysis ( R 2  = 34.1; model F  = 24.19. p  < 0.001) was run.

Conclusions

The Spanish version of the questionnaire obtained good reliability coefficients and its factorial structure reliably replicated that obtained by the original measure. The results indicate that the Spanish version of the MWQ is a suitably valid measure to evaluate the mind-wandering phenomenon.

As human beings, we tend to be distracted by the activities we perform, which is when the mind tends to wander back to the past or to plan the future. This spontaneous tendency to produce thoughts and to freely allow our minds to wander, despite external stimuli, is considered a typical characteristic of the human mind (Smallwood and Schooler, 2006 ). Mind wandering is understood as a mental process during which attention is distracted from a task underway to focus on the contents that our minds intrinsically produce (Smallwood and Schooler, 2015 ). As it is one of the most common activities that the human mind performs, it occurs in practically all day-to-day activities, and individuals are gripped to their own mind events between 10 and 50% of the time they are awake (Kane, Brown, McVay, Silvia, Myin-Germeys & Kwapil, 2007 ; Killingsworth and Gilbert, 2010 ). Mind wandering presents wide inter-individual variability, and the mind-wandering trait appears as the personal characteristic of a tendency toward mind wandering for a given period of time (Mrazek, Smallwood, Franklin, Baird, Chin & Schooler, 2012a ).

Repetitive thoughts are considered an adaptive function of human beings. Despite the negative connotations associated with this concept, mind wandering is not itself considered a negative characteristic. Similar negative connotations are attached to common terms like cognitive failures, resting state, rumination, distraction, attentional failures, absent-mindedness, repetitiveness, and the like (Baars, 2010 ). Planning the future is one of the most beneficial results connected with mind wandering as its appearance is associated with thoughts about the future, and not with the past or present (Schooler, Smallwood, Christoff, Handy, Reichle & Sayette, 2011 ). Thoughts that focus on the future are increased by self-reflection (Smallwood and O’Connor, 2011 ) and by prioritizing personal goals (Stawarczyk, Majerus, Maj, Van der Linden and D’Argembeau, 2011 ), which is reduced by negative moods (Smallwood and O’Connor, 2011 ). Along these lines, mind wandering comes over as an adaptive advantage as it can diminish distress by predicting future events to better adapt to one’s own environment (Bar, 2009 ). Mind wandering allows information that cannot be analyzed when a stimulus emerges to be systematized because the semantic manipulation of information cannot take place while a stimulus occurs (Binder, Frost, Hammeke, Bellgowan, Rao & Cox, 1999 ), and is thus associated with effective coping (Greenwald and Harder, 1995 ) and creativity (Sio and Ormerod, 2009 ). This anticipative capacity and planning of the future allow problems to be creatively solved (Baird, Smallwood, Mrazek, Kam, Franklin & Schooler, 2012 ).

High levels of mind wandering are related with low moods (Killingsworth and Gilbert, 2010 ) and negative thinking (Smallwood, O’Connor, Sudbery, and Obonsawin, 2007 ). An increase in negative thoughts in relation to mind wandering has been associated with individual levels of depression (Marchetti, Koster and De Raedt, 2012 ). This association may be due to mind wandering which, given the spontaneous emergence of thoughts, is associated with paying more attention to one’s own thoughts, emotions, and experiences (Smallwood and Schooler, 2015 ). This marked increase in self-attention may mean being at more risk of self-assessment, which has been associated with negative emotions (Mor and Winquist, 2002 ). The appearance of repetitive thoughts is relevant for the appearance and maintenance of emotional disorders (Aldao, Nolen-Hoeksema and Schweizer, 2010 ) through brooding and worrying. Although both of these constructs are related with mind wandering, they are considered to semantically differ. Indeed, worrying is defined as expecting possible negative results in the future (Borkovec, Robinson, Pruzinsky and DePree, 1983 ), while brooding is defined as the repetitive response model that involves the constant development of distress symptoms, and of the causes and consequences of distress (Nolen-Hoeksema, Wisco and Lyubomirsky, 2008 ).

Increased mind wandering and paying more attention to one’s own thoughts, emotions, and experiences have been related with low levels of self-esteem (Mrazek, et al. 2013 ). Nevertheless, paying more attention to oneself is not necessarily considered a negative activity for self-esteem. So mindfulness is considered a construct that contrasts with mind wandering (Mrazek, Smallwood, and Schooler, 2012b ). The mindfulness construct has been defined in many forms, and all its definitions coincide in that it is a matter of paying intentionally more attention to the present time and not taking a judgemental attitude about experience (Brown and Ryan, 2003 ; Germer, 2005 ; Kabat-Zinn, 1990 ; Segal, Williams and Teasdale, 2002 ). This non-judgemental attitude makes mindfulness appear positively related with self-esteem (Kong, Wang, and Zhao, 2014 ; Rasmussen and Pidgeon, 2011 ). In turn, self-esteem is considered a predictor of satisfaction with life (Diener and Diener, 1995 ; Mäkikangas and Kinnunen, 2003 ). Hence, the aforementioned factors may be considered modulators in the relation between mind wandering and satisfaction with life.

As no valid scale exists to measure mind wandering, the usual way to assess it involves periodically interrupting individuals while they do a task, and asking them to report the extent to which their attention was related to on-task or on task-unrelated concerns (Mrazek, Smallwood, Franklin, Baird, Chin & Schooler, 2012a ). In the last few years, the Mind-Wandering Questionnaire (MWQ) was developed. It is a simple validated tool designed to directly measure mind-wandering trait levels. Its design offers good reliability and validity in both adult and adolescent populations (Mrazek, 2013 ), and has been validated to Chinese (Luo, Zhu, Ju and You, 2016 ) and Japanese (Kajimura and Nomura, 2016 ). In Spain, studies have been conducted on mind wandering by electroencephalography in relation to movement (Melinscak, Montesano and Minguez, 2014 ). However, no references about psychometric studies of the construct are available. For this reason, the objective of this work was to translate into Spanish and to validate the Mind-Wandering Questionnaire and to analyze its relation with the values of self-esteem, dispositional mindfulness, satisfaction with life, happiness, and positive and negative affects among adolescents.

For the Spanish MWQ adaptation purposes, the following phases were followed:

Translation of the original scale into Spanish by a group of expert researchers in mindfulness.

The translated scale was administered to a sample of 50 people to detect any items that did not work well, and possible difficulties in understanding because items were poorly translated or badly written. No special difficulties were found in either the items or the instrument in general.

The work with the scale centered on the analysis, translation, and validation of the MWQ. The whole study sample ( N  = 543) was recruited from four high school centres.

The objective of this research was to validate the MWQ. After finishing the translation processes (Fig.  1 ), the first step was to study the reliability of the scales. To do this, statistics were obtained as the scale was not adapted to Spanish. This analysis informed us about the value of Cronbach’s alpha coefficient of reliability. In this questionnaire, good values were obtained (α = .766), which indicates good internal consistency among the scale elements.

Diagram showing the phases followed to adapt the MWQ

Participants

The research sample comprised 543 secondary students, 270 males (49.72%) and 273 females (50.28%). Subjects voluntarily participated and gave signed informed consents. The ethical norms of the Declaration of Helsinki were respected. The study population’s mean age was 17.24 years, and their ages ranged from 16 to 18 years, with a standard deviation of 1.015.

Measurements

The Mind-Wandering Questionnaire (MWQ) (Mrazek, 2013 ), is a self-report 5-item questionnaire that evaluates the levels of the mind-wandering trait. It is a 6-point Likert-type scale that goes from 1 (almost never) to 6 (almost always). Some item examples are “I have difficulty maintaining focus on simple or repetitive work” or “I do things without paying full attention”. The total MWQ score is the sum of the five items within a 5–30 range. After obtaining permission from the author of the MWQ, it was translated. The results and its reliability/validity are described in later sections of this document.

The Mindful Attention Awareness Scale (MAAS) (Brown and Ryan, 2003 ) is a simple scale that is quickly administered and globally evaluates an individual’s dispositional capacity of being alert and aware of the present experience in his/her daily life. MAAS is a 15-item questionnaire that scores on a Likert scale from 1 (almost always) to 6 (almost never). It measures the frequency of the mindfulness state in activities of daily living without having to train subjects. Scores are obtained using the arithmetic mean of all the items, and high scores indicate a greater mindfulness state. In the present study, this scale shows high internal consistency with a Cronbach’s alpha coefficient of 0.878.

The Subjective Happiness Scale (Lyubomirsky and Lepper, 1999 ) is an overall measure of subjective happiness that evaluates a molar category of well-being as an overall psychological phenomenon by considering the definition of happiness from the respondent’s perspective. It comprises four items with Likert-type responses and is corrected by summing the points obtained and then dividing them by the total number of items. In the present study, this scale shows high internal consistency with a Cronbach’s alpha coefficient of 0.845.

The Satisfaction with Life Scale (Diener, Emmons, Larsen and Griffin, 1985 ) is a 5-item scale that evaluates satisfaction with life. The participants must indicate the extent to which they agree with each statement on a 7-point Likert scale (from 1 = I strongly disagree to 7 = I strongly agree). Scores may range from 5 to 35 points; higher scores indicate greater satisfaction with life. This scale in this study shows high internal consistency with a Cronbach’s alpha coefficient of 0.863.

Rosenberg’s Self-esteem Scale (Rosenberg, 1965 ) is self-applied and contains 10 statements of the feelings that each person feels about him/herself; five in the positive sense (items 1, 2, 4, 6, and 7) and five in the negative sense (items 3, 5, 8, 9, and 10). It is a Likert-type scale whose theoretical values fluctuate between 10 (low self-esteem) and 40 (high self-esteem). The Cronbach’s alpha obtained by this scale is 0.876.

The PANAS schedule (Watson, Clark and Tellegen, 1988 ), this being the positive and negative affect schedule (PANAS), includes 20 items, of which 10 refer to positive affects (PA) and 10 to negative affects (NA) on two Likert-type scales. They all refer to the time the scale is answered (right now), with a score from 0 (not at all emotional) to 5 (extremely emotional). This scale shows an alpha of 0.790 for PA and one of 0.874 for NA.

Data analysis

The statistical analysis was done using version 22.0 of the SPSS software package for Windows. Factorial analyses were done. By reducing data, this technique is used to explain the variability among observed variables in terms of a smaller number of non-observed variables called factors. The observed variables were modeled as linear combinations of factors, plus error expressions. The intention was to analyze the consistency of the scale factors. In this study, a combination of EFA and CFA was performed. The majority of the studies chose the use of EFA for factor analysis. Others used CFA, for specific hypothesized factor structure proposed in EFA. DeVellis ( 2003 ) suggested the combined use of EFA and CFA for more consistent results on the psychometric indices of new scales. Recently, this suggestion of considering the combined use of EFA and CFA during the evaluation of construct validity of new measures has been approved by other authors, in order to provide more consistent psychometric results (Morgado, Meireles, Neves, Amaral and Ferreira, 2017 ).

Confirmatory analyses were run with the AMOS program, v24.0, with the study sample to verify if the factorial structure of the Spanish version matched that in the original version. Following the recommendations by Batista and Coenders ( 2000 ), the maximum likelihood estimation method was used rather than the weighted least squares method given the small sample size and few variables involved. As variables were measured at the ordinal level, estimations were made with polychoric correlations matrices instead of with covariance matrices.

Construct validity

Construct validity was firstly analyzed. Although it is not a factor analysis technique, it was used to factorize the principal components analysis with varimax rotation as it can serve as an exploratory tool. After checking the validity of the factorial analysis with the following criteria: the correlations matrix had a large number of correlations (87.4%) with a value over 0.30, and a determining factor that equaled 0.001. The result of Bartlett’s sphericity test showed that the variables were not independent (Bartlett’s test = 321.43, p  < .001). The obtained Kaiser-Meyer-Olkin (KMO) test value for sampling sample adequacy was 0.788. This indicated that the correlations between pairs of variables can be explained by the other variables. All the measures of sampling adequacy (MSA) values were over .78. These values indicated that running a factorial analysis of the correlations matrix was adequate. As Table  1 shows, a factor was obtained with an eigenvalue higher than 1 by assigning the factor an item as a criterion in that which presents a factorial load over 0.40, which explained 52.1% of total variance.

Figure  2 offers the confirmatory factor analysis (CFA) result of the model generated in the exploratory study, along with the structural equations from the method that obtained the maximum likelihood. This confirmed that the model was adequate because a sustainable model was obtained, which comprised a total of one factor and five indicators (Fig.  2 ). The normalized regression coefficients were statistically significant ( p  < 0.05), with values above 0.5, which indicates that all the indicators satisfactorily saturated with the latent variable.

Estimated normalized parameters of the CFA model

The different fit indices were suitable for the model’s fit. Thus, we can state that the model proposed for the factorial scale structure is sustainable: χ 2 (5) = 18.3; p  = 0.003; χ 2 /gl = 3.7; GFI  = 0.94; AGFI  = 0.96; CFI  = 0.96; NFI  = 0.94; TLI  = 0.93; RMSEA  = 0.07. 90% CI (0.05–0.11).

Internal consistency

It allowed us to estimate the reliability of the measuring instrument with a set of items expected to measure the same construct or the theoretical dimension. The scale’s Cronbach’s alpha was higher than 0.75, so it was assumed that the items which comprised the scale measured the same construct and correlated well (Table  2 ).

Convergent validity

We also analyzed convergent validity with the other constructs analyzed in this work to test that the constructs expected to be related were indeed related (Table  3 ).

Multiple regression analysis

Finally, a multiple regression analysis was performed (Table  4 ) to analyze the possible relation between the independent variables (self-esteem, MAAS, satisfaction with life, PA, and NA) that act as predictors or explanatory variables, and another independent variable, the MWQ.

The MAAS and NA had a significant and negative effect with the MWQ as high values for these variables were associated with low MWQ values. PA had a significant direct effect with the MWQ and the high values of these affects were associated with high MWQ values.

The objective of the present study was to translate into Spanish and analyze the psychometric properties of the Mind-Wandering Questionnaire (MWQ) with adolescents. Studies into this construct conducted with adolescent populations are much scarcer than those done with adult populations. Some research works have evaluated mind wandering in adolescent samples by identifying relevant indicators (Luo, Zhu, Ju, and You, 2016 ; Mrazek et al. 2013 ). The results revealed that the Spanish version of the MWQ for adolescents evidences validity and reliability.

Regarding evidence for construct validity, a correlations analysis was firstly done with the five-scale items. The results showed some positive and significant results among them, with values above those obtained by Mrazek in 2013. These scores can be accounted for by the homogeneity that occurs in the scores of the variables that make up subjective well-being. Indeed, this situation has led several authors to consider the possible existence of some higher-order construct that covers several of what we now often consider to be synonyms, measured by different scales (e.g., subjective well-being, personal well-being, satisfaction with life, or happiness), which have shown significantly positive and generally high correlations with one another, and apparently overlap. Although these variables have clearly different characteristics, it is generally considered that their respective overall values are equally good indicators of subjective well-being. However, the observed correlations have not been high enough to be able to state that they measure identical constructs (Banati and Diers, 2016 ; Casas, Baltatescu, Bertrán, González, and Hatos, 2013 ; Diener, et al. 1999 ; Nilsen and Bacso, 2017 ). The scores obtained with the MWQ would indicate that somehow this new construct could form part of subjective well-being.

Secondly, the factorial structure of the MWQ was analyzed by a confirmatory factorial analysis. The results indicated good data fit, which corroborated the scale’s dimensional structure, and also coincided with both the initial questionnaire postulates (Mrazek et al. , 2013 ) and the factorial structure obtained in the original questionnaire version. The values obtained for scale reliability through Cronbach’s alpha were acceptable in all the items and were similar to those found in not only the original version, but also in subsequent studies conducted in different contexts (Kajimura and Nomura, 2016 ; Luo et al. 2016 ). This could be an indication of the appropriateness of using this scale with an adolescent population. To examine the scale’s concurrent validity, the structural equations model was tested, in which it was hypothesized that self-esteem, satisfaction with life, subjective happiness, positive/negative affects, and dispositional mindfulness predicted the results of the mind-wandering phenomenon. Here, gender differences were found as the results for the female participants in the MWQ scale obtained higher correlation indices with the MAAS Scale and PA, while the males’ results were higher for self-esteem and NA. This gender discrepancy in the affects themes has already been pointed out by some authors (Salavera, Usán, Antoñanzas, Teruel and Lucha, 2017 ). The multiple regression results showed that happiness, self-esteem, and satisfaction with life did not seem to influence the mind-wandering phenomenon. These three constructs have a lot to do with a person’s disposition and with the subjective evaluation of his or her well-being. So up to a point, it would be logical to understand that with a phenomenon like mind wandering, the variables that require greater awareness about the subject’s conscience state do not act as predictors, which was the case of the present research. Only PA had a significant and positive effect with the MWQ as high values for PA were associated with high MWQ values. There is an explanation for this as positive affect includes mood states and various emotions with pleasant, almost agreeable, subjective content, and with conditions or events that positively inform about how life is going (Luna, 2012 ), which falls in line with mind wandering. In the same way, dispositional mindfulness and NA predicted a negative and significant effect with the MWQ as high values for these variables were associated with low MWQ scores, which indicates that despite an increase in emotional regulation skills taking place in adolescence, an increase in negative affect states has also been detected during this life period (Larson, Moneta, Richards and Wilson, 2002 ). Thus the self-assessments that adolescents make can activate negative emotions, like fear, sadness, or rejection, which would explain why the mind-wandering process correlates inversely with negative affects.

We should, however, point out that the present study has some limitations. Firstly, the evidence found for validity and reliability must be considered provisional as our sample size, especially males, was small. Future studies should verify gender effects with a larger study sample to evaluate the relation of these constructs over the years. Secondly, it would be necessary to test the instrument’s factorial structure in different contexts. As future research lines, and like other works (Diener, Suh, Lucas and Smith, 1999 ; Hampel and Petermann, 2006 ; Mrazek, et al., 2012b ), we should make an in-depth examination of the interaction among mind wandering, psychological factors, and different life events, and continue to investigate the relation of mind wandering with different subjective well-being components (subjective happiness, self-esteem, and satisfaction with life and affects), and consider programs that promote the use of active strategies to enhance personal well-being in adolescents.

To conclude, our results revealed that the Spanish version of the MWQ for adolescents offers preliminary evidence for validity and reliability, and along the same lines as the results obtained in the original version. In addition, this questionnaire could be useful for indirect measurement of the effectiveness of interventions with mindfulness. The inverse relationship found with the MAAS questionnaire (which measures mindfulness-trait) leads us to think that it can serve as an indicator of mind-wandering moments, which will decrease as the practice of mindfulness advances. Therefore, the Spanish version for adolescents may be considered a preliminary adaptation of the original questionnaire version, and the results justify its use for evaluating the mind-wandering phenomenon in the Spanish adolescent population. The present research results encourage us to continue seeking new questions to help us define new tools and methodologies and to find some answers to make progress in building mindfulness practices in adolescents.

Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: a meta-analytic review. Clinical Psychology Review, 30 (2), 217–237. http://dx.doi.org/10.1016/j.cpr.2009.11.004 .

Article   PubMed   Google Scholar  

Baars, B. J. (2010). Spontaneous repetitive thoughts can be adaptive: postscript on “Mind Wandering”. Psychological Bulletin, 136 (2), 208–210. http://dx.doi.org/10.1037/a0018726 .

Baird, B., Smallwood, J., Mrazek, M. D., Kam, J. W., Franklin, M. S., & Schooler, J. W. (2012). Inspired by distraction: mind wandering facilitates creative incubation. Psychological Science, 23 (10), 1117–1122. http://dx.doi.org/10.1177/0956797612446024 .

Banati, P., & Diers, J. (2016). Measuring adolescent well-being: National Adolescent Assessment Cards (NAACs). In Innocenti Research Brief (p. 10). Florence: Unicef Office of Research – Innocenti.

Google Scholar  

Bar, M. (2009). The proactive brain: memory for predictions. Philosophical Transactions of the Royal Society B-Biological Sciences, 364 (1521), 1235–1243. http://dx.doi.org/10.1098/rstb.2008.0310 .

Article   PubMed Central   Google Scholar  

Batista, J. M., & Coenders, G. (2000). Modelos de Ecuaciones Estructurales (Structural Equation Modeling) . Madrid: Editorial La Muralla.

Binder, J. R., Frost, J. A., Hammeke, T. A., Bellgowan, P. S. F., Rao, S. M., & Cox, R. W. (1999). Conceptual processing during the conscious resting state: a functional MRI study. Journal of Cognitive Neuroscience, 11 (1), 80–93. http://dx.doi.org/10.1162/089892999563265 .

Borkovec, T. D., Robinson, E., Pruzinsky, T., & DePree, J. A. (1983). Preliminary exploration of worry: some characteristics and processes. Behaviour Research and Therapy, 21 (1), 9–16. http://dx.doi.org/10.1016/0005-7967(83)90121-3 .

Brown, K. W., & Ryan, R. M. (2003). The benefits of being present. Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84 (4), 822–848. http://dx.doi.org/10.1037/0022-3514.84.4.822 .

Casas, F., Baltatescu, S., Bertrán, I., González, M., & Hatos, A. (2013). School satisfaction among adolescents: testing different indicators for its measurement and its relationship with overall life satisfaction and subjective well-being in Romania and Spain. Social Indicators Research, 111 , 665–681.

Article   Google Scholar  

DeVellis, R. F. (2003). Scale development: theory and applications (2nd ed.). Newbury Park: Sage Publications.

Diener, E., & Diener, M. (1995). Cross-cultural correlates of life satisfaction and self-esteem. Journal of Personality and Social Psychology, 68 , 653–663.

Diener, E., Emmons, R.A., Larsen, R.J. & Griffin, S. (1985). The Satisfaction with Life Scale. Journal of Personality Assessment, 49 , 71–75.

Diener, E., Suh, E., Lucas, R., & Smith, H. (1999). Subjetive well-being: three decades of progress. Psychological Bulletin, 125 , 276–302.

Hampel, P. & Petermann, F. (2006). Perceived stress, coping, and adjustment in adolescents. Journal of Adolescent Health, 38 (4), 409–415. http://dx.doi.org/10.1016/j.jadohealth.2005.02.014 .

Germer, C. K. (2005). Mindfulness: what is it? What does it matter? In C. K. Germer, R. D. Siegel, & P. R. Fulton (Eds.), Mindfulness and psychotherapy (pp. 3–27). New York: The Guilford Press.

Greenwald, D. F., & Harder, D. W. (1995). Sustaining fantasies, daydreams, and psychopathology. Journal of Clinical Psychology, 51 (6), 719–726. http://dx.doi.org/10.1002/1097-4679(199511)51:6%3C719::AID-JCLP2270510602%3E3.0.CO;2-I .

Kabat-Zinn, J. (1990). Full catastrophy living. How to cope with stress, pain and illness using mindfulness meditation . New York: Piatkus.

Kajimura, S., & Nomura, M. (2016). Development of Japanese versions of the Daydream Frequency Scale and the Mind Wandering Questionnaire. Shinrigaku Kenkyu, 87 (1), 79–88. http://dx.doi.org/10.4992/jjpsy.87.14223 .

Kane, M. J., Brown, L. H., McVay, J. C., Silvia, P. J., Myin-Germeys, I., & Kwapil, T. R. (2007). For whom the mind wanders, and when: an experience-sampling study of working memory and executive control in daily life. Psychological Science, 18 (7), 614–621. http://dx.doi.org/10.1111/j.1467-9280.2007.01948.x .

Killingsworth, M. A., & Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science, 330 (6006), 932. http://dx.doi.org/10.1126/science.1192439 .

Kong, F., Wang, X., & Zhao, J. (2014). Dispositional mindfulness and life satisfaction: the role of core self-evaluations. Personality and Individual Differences, 56 , 165–169. http://dx.doi.org/10.1016/j.paid.2013.09.002 .

Larson, R. W., Moneta, G., Richards, M. H., & Wilson, S. (2002). Continuity, stability, and change in daily emotional experience across adolescence. Child Development, 73 (4), 1151–1165.

Luna, F. J. (2012). Bienestar subjetivo y satisfacción escolar en la adolescencia. Tesis doctoral . Girona: Universidad de Girona.

Luo, Y., Zhu, R., Ju, E., & You, X. (2016). Validation of the Chinese version of the Mind-Wandering Questionnaire (MWQ) and the mediating role of self-esteem in the relationship between mind-wandering and life satisfaction for adolescents. Personality and Individual Differences, 92 , 118–122. http://dx.doi.org/10.1016/j.paid.2015.12.028 .

Lyubomirsky, S. & Lepper, H. (1999). A measure of subjective happiness: preliminary reliability and construct validation. Social Indicators Research, 46 , 137–155.

Mäkikangas, A., & Kinnunen, U. (2003). Psychosocial work stressors and well-being: self-esteem and optimism as moderators in a one-year longitudinal sample. Personality and Individual Differences, 35 (3), 537–557. http://dx.doi.org/10.1016/S0191-8869(02)00217-9 .

Marchetti, I., Koster, E. H., & De Raedt, R. (2012). Mindwandering heightens the accessibility of negative relative to positive thought. Consciousness and Cognition, 21 (3), 1517–1525. http://dx.doi.org/10.1016/j.concog.2012.05.013 .

Melinscak, F., Montesano, L., & Minguez, J. (2014). Discriminating between attention and mind wandering during movement using EEG. In Proceedings of the 6th International Brain–Computer Interface Conference (pp. 0601–0604). Graz: Graz University of Technology Publishing House.

Mor, N., & Winquist, J. (2002). Self-focused attention and negative affect: a meta-analysis. Psychological Bulletin, 128 (4), 638–662. http://dx.doi.org/10.1037/0033-2909.128.4.638 .

Morgado, F. F. R., Meireles, J. F. F., Neves, C. M., Amaral, A. C. S., & Ferreira, M. E. C. (2017). Scale development: ten main limitations and recommendations to improve future research practices. Psicologia: Reflexão e Crítica, 30 (3). http://dx.doi.org/10.1186/s41155-016-0057-1

Mrazek, M. D., Phillips, D. T., Franklin, M. S., Broadway, J. M., & Schooler, J. W. (2013). Young and restless: validation of the Mind-Wandering Questionnaire (MWQ) reveals disruptive impact of mind-wandering for youth. Frontiers in Psychology, 4 , 560. http://dx.doi.org/10.3389/fpsyg.2013.00560 .

Article   PubMed   PubMed Central   Google Scholar  

Mrazek, M. D., Smallwood, J., Franklin, M. S., Baird, B., Chin, J., & Schooler, J. W. (2012a). The role of mind-wandering in measurements of general aptitude. Journal of Experimental Psychology: General, 141 , 788–798. http://dx.doi.org/10.1037/a0027968 .

Mrazek, M. D., Smallwood, J., & Schooler, J. W. (2012b). Mindfulness and mind-wandering: finding convergence through opposing constructs. Emotion, 12 (3), 442–448. http://dx.doi.org/10.1037/a0026678 .

Nilsen, E. S., & Bacso, S. A. (2017). Cognitive and behavioural predictors of adolescents’ communicative perspective-taking and social relationships. Journal of Adolescence, 56 , 52–63. http://dx.doi.org/10.1016/j.adolescence.2017.01.004 .

Nolen-Hoeksema, S., Wisco, B. E., & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science, 3 (5), 400–424. http://dx.doi.org/10.1111/j.1745-6924.2008.00088.x .

Rasmussen, M. K., & Pidgeon, A. M. (2011). The direct and indirect benefits of dispositional mindfulness on self-esteem and social anxiety. Anxiety, Stress and Coping, 24 (2), 227–233. http://dx.doi.org/10.1080/10615806.2010.515681 .

Rosenberg, M. (1965). Society and the Adolescent Self-Image. Princeton, New Jersey: Princeton University Press.

Salavera, C., Usán, P., Antoñanzas, J. L., Teruel, P., & Lucha, O. (2017). Affects and personality: a study students. Annales Medico-Psychologiques (in press). http://dx.doi.org/10.1016/j.amp.2016.06.014

Schooler, J. W., Smallwood, J., Christoff, K., Handy, T. C., Reichle, E. D., & Sayette, M. A. (2011). Meta-awareness, perceptual decoupling and the wandering mind. Trends in Cognitive Sciences, 15 (7), 319–326. http://dx.doi.org/10.1016/j.tics.2011.05.006 .

PubMed   Google Scholar  

Segal, Z. V., Williams, J. M., & Teasdale, J. D. (2002). Mindfulness-based cognitive therapy for depression: a new approach to preventing relapse . New York: The Guilford Press.

Sio, U. N., & Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135 (1), 94–120. http://dx.doi.org/10.1037/a0014212 .

Smallwood, J., & O’Connor, R. C. (2011). Imprisoned by the past: unhappy moods lead to a retrospective bias to mind wandering. Cognition & Emotion, 25 (8), 1481–1490. http://dx.doi.org/10.1080/02699931.2010.545263 .

Smallwood, J., O’Connor, R. C., Sudbery, M. V., & Obonsawin, M. (2007). Mind-wandering and dysphoria. Cognition and Emotion, 21 (4), 816–842. http://dx.doi.org/10.1080/02699930600911531 .

Smallwood, J., & Schooler, J. W. (2006). The restless mind. Psychological Bulletin, 132 (6), 946–958. http://dx.doi.org/10.1037/0033-2909.132.6.946 .

Smallwood, J., & Schooler, J. W. (2015). The science of mind wandering: empirically navigating the stream of consciousness. Annual Review of Psychology, 66 , 487–518. http://dx.doi.org/10.1146/annurev-psych-010814-015331 .

Stawarczyk, D., Majerus, S., Maj, M., Van der Linden, M., & D’Argembeau, A. (2011). Mind-wandering: phenomenology and function as assessed with a novel experience sampling method. Acta Psychologica, 136 (3), 370–381. http://dx.doi.org/10.1016/j.actpsy.2011.01.002 .

Watson, D., Clark, L.A. & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54 , 1063–1070.

Download references

Acknowledgements

To Michael Mrazek, for his guidance, indications, advice, and help to prepare this work.

To Helen Warburton, for translating this manuscript and for making suggestions and contributions.

This study was performed by Research Group OPIICS (S126) and Parasitology, self-care and environmental health (B124), University of Zaragoza (Zaragoza, Spain) and was supported by research funds provided by the Department of Science and Technology of the Government of Aragón (Spain) and the European Social Fund.

Authors’ contributions

CS, FUP, PU, and LJ contributed to the conception and design of the work. CS, FUP, PU, and LJ organized the sample collection and data preparation, performed the data collection, analysis, and interpretation. CS, FUP, PU, and LJ prepared drafts of the article. PU and LJ critically reviewed its comprehensive content. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Ethics and approval and consent to participate

Subjects voluntarily participated and gave signed informed consents. The ethical norms of the Declaration of Helsinki were respected.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Authors and affiliations.

Research Group OPIICS, University of Zaragoza, Zaragoza, Spain

Carlos Salavera, Pablo Usán & Laurane Jarie

Faculty of Education, University of Zaragoza, c/ Pedro Cerbuna, 12, 50009, Zaragoza, Spain

Faculty of Health Sciences, University of Zaragoza, c/Violante de Hungría, s/n, 50009, Zaragoza, Spain

Fernando Urcola-Pardo

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Carlos Salavera .

Mind-Wandering Scale (Mrazek, 2013 )

Cuestionario de vagabundeo de la mente.

Translation Spanish (Salavera, Urcola-Pardo, Usán and Jarie)

Me resulta difícil mantener la concentración en trabajos sencillos o repetitivos

Mientras leo, me doy cuenta de que no he estado pensando en el texto y que, por lo tanto, tengo que leerlo otra vez

Hago las cosas sin prestar total atención

Me encuentro escuchando a medias al mismo tiempo que estoy pensando en otra cosa

Me distraigo durante conferencias y presentaciones

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Salavera, C., Urcola-Pardo, F., Usán, P. et al. Translation and validation of the Mind-Wandering Test for Spanish adolescents. Psicol. Refl. Crít. 30 , 12 (2017). https://doi.org/10.1186/s41155-017-0066-8

Download citation

Received : 28 November 2016

Accepted : 10 May 2017

Published : 02 June 2017

DOI : https://doi.org/10.1186/s41155-017-0066-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Mind wandering
• Mindfulness
• Adolescents
• Instrumental study

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol
• PMC10368185

Spanish and cross-cultural validation of the mind excessively wandering scale

Alfonso morillas-romero.

1 Apploading S.L., Palma, Spain

2 Department of Psychology of the University of the Balearic Islands, Palma, Spain

Alejandro De la Torre-Luque

3 Department of Legal Medicine, Psychiatry and Pathology Department, Complutense University of Madrid, Madrid, Spain

Florence D. Mowlem

4 King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom

Philip Asherson

Associated data.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Introduction

Over the last decade, excessive spontaneous mind wandering (MW) has been consistently associated with emotional disorders. The main aims of the present study were (1) to re-examine the factor structure of the Mind Excessively Wandering Scale (MEWS); (2) to validate the Spanish version of the MEWS; and (3) to conduct a cross-cultural validation of the MEWS in Spanish and UK samples.

A forward/backward translation to Spanish was conducted. Data of 391 Spanish and 713 British non-clinical individuals were analysed.

A revised 10-item version of the MEWS (MEWS-v2.0) demonstrated to be a valid instrument to assess MW. A 2-correlated factor structure properly captured the MEWS-v2.0 variance, accounting for two specific but interrelated dimensions ( Uncontrolled thoughts and Mental Overactivity ).

The Spanish MEWS-v2.0 showed adequate internal consistency and construct validity, as well as appropriate convergent/divergent validity. Cross-cultural analyses showed that MEWS-v2.0 captured the same construct in both UK and Spanish samples. In conclusion, both Spanish and English MEWS-v2.0 demonstrated to be reliable measures to capture spontaneous MW phenomenon in non-clinical adult populations.

1. Introduction

Mind wandering (MW) can be defined as periods of time when attention and the contents of thoughts shift away from external sources and/or ongoing tasks to unrelated internal thoughts or feelings ( Smallwood and Schooler, 2015 ). Over the last decade and following a seminal review by Smallwood and Schooler (2006) , the study of MW has become a hot topic in cognitive and affective psychology research ( Callard et al., 2013 ; Christoff et al., 2016 ; Hobbiss et al., 2019 ).

Seli et al. (2015) and Carriere et al. (2013) suggested a distinction between intentional/deliberate vs. unintentional/spontaneous MW. Excessive spontaneous MW has been related to several mental health conditions including high levels of neuroticism and anxiety ( Christoff et al., 2016 ; Robison et al., 2017 ), attention-deficit/hyperactivity disorder (ADHD), and borderline personality disorder (BPD; Mowlem et al., 2016 , 2019 ; Franklin et al., 2017 ; Moukhtarian et al., 2020 ); in addition to lower levels of daily happiness ( Killingsworth and Gilbert, 2010 ; Hobbiss et al., 2019 ), reduced attention, greater interference in performance on executive-function tasks ( Smallwood et al., 2004 ; Mrazek et al., 2012 ; Mooneyham and Schooler, 2013 ), reduced dispositional mindfulness ( Deng et al., 2014 ; Marchetti et al., 2016 ), and increased depressive symptoms ( Stawarczyk et al., 2013 ; Marchetti et al., 2014 ; Ottaviani et al., 2015 ). In contrast, potentially linked to deliberate forms of MW, several studies have postulated an adaptive role of MW associated with greater creative problem-solving ( Baird et al., 2012 ; Yamaoka and Yukawa, 2020 ), adaptive future planning, and better management of personal goals ( Baird et al., 2011 ; Mooneyham and Schooler, 2013 ; Smallwood and Schooler, 2015 ).

Several self-reported rating scales have been developed that assess MW. Among these, the Mind Excessively Wandering Scale (MEWS) ( Mowlem et al., 2016 ), is one of the most representative and well-supported by research over the last years. The MEWS development was based on ADHD patient reports of MW and captures both lack of control over MW and difficulty focusing on one thought at a time, thought to be related to spontaneous MW ( Mowlem et al., 2019 ). In this sense, Carriere et al. (2013) developed two separate subscales to distinguish between deliberate and spontaneous MW as two well-differentiated constructs, posteriorly supported by the works of Seli et al. (2015) . Related to this, the MEWS showed a strong significant correlation with spontaneous MW but not deliberate MW ( Mowlem et al., 2019 ) suggesting that the MEWS may be considered a specific measure of spontaneous MW. The original MEWS scale consists of 15 items to be scored on a 4-point Likert-type scale (0 =  not at all or rarely , 1 =  some of the time , 2 =  most of the time , 3 =  nearly all of the time or constantly ), and has shown to be a reliable and valid instrument, demonstrating measurement invariance across sex, age and ADHD diagnostic status ( Mowlem et al., 2019 ).

Following the original authors report, psychometric analysis in a subsequent study showed the MEWS to have a unidimensional structure with good internal consistency and three out of four fit indices suggesting acceptable model fit ( Mowlem et al., 2019 ); specifically, the MEWS showed adequate fit based on the comparative fit index (CFI = 0.97), Tucker-Lewis Index (TLI = 0.99) and standardized root mean square residual (SRMR = 0.06). However, the root mean squared of the residuals (RMSEA) index was 0.13, with some authors suggesting that RMSEA >0.1 0 is indicative of poor fit ( Browne and Cudeck, 1993 ; MacCallum et al., 1996 ) and be related to inflated type II error rate ( Hu and Bentler, 1999 ). In other words, the higher the RMSEA, the higher the probability of erroneously rejecting a more complex structure of covariances when explaining a construct. In this sense, Nakovics et al. (2020) identified a 2-factorial scale structure solution when analyzing the psychometric properties of the German version of the MEWS. However, the authors argued that these two factors, namely “difficulties controlling own thoughts and focusing” (Factor 1) and “thought fluctuation” (Factor 2), were closely related and interdependent but not distinct facets of MW ( Nakovics et al., 2020 ). Therefore, further research is needed to compare the unidimensional structure of the MEWS and other competing more complex models with large samples.

While the MEWS has been recently adapted and validated in several languages including German ( Nakovics et al., 2020 ) and Portuguese ( Figueiredo et al., 2018 ), a Spanish version is not yet available. Further, to the best of our knowledge, no well-validated self-reported instruments to assess MW are available in the Spanish language for adult populations. Only a Spanish version of the Mind Wandering Questionnaire (MWQ, Mrazek et al., 2013 ) has been validated in an adolescent sample, replicating the original MWQ factorial structure, but not in adults ( Salavera et al., 2017 ).

The first aim of the present study was to examine the factor structure of the 12-item MEWS using an approach that considered the existence of a potential complex factor structure (hierarchical patterns of variance–covariance) and adapt the scale if required. The second aim was to develop a Spanish version of the MEWS through a backward/forward translation process for use in a Spanish non-clinical adult population to assess the factor structure of the adapted scale in an independent sample. Thirdly, to conduct a cross-sample validation of the Spanish dataset with the UK dataset, to explore the comparability of their construct validity (measurement invariance) in samples from two different cultural backgrounds, and using the different translations of the MEWS. Finally, to investigate the convergent and divergent validity of the Spanish MEWS by exploring its relationships with well-known theoretical constructs. Based on the existing literature, a positive relationship between MW and negative affect ( Robison et al., 2017 ), rumination ( Christoff et al., 2016 ), and anxious and depressive symptomatology was hypothesized ( Killingsworth and Gilbert, 2010 ; Marchetti et al., 2014 ). In contrast, a negative relationship was expected between MW, and both self-reported attentional control ( Mooneyham and Schooler, 2013 ) and dispositional mindfulness capabilities ( Mrazek et al., 2012 ).

2. Materials and methods

2.1. participants.

We used two samples from Spain and the United Kingdom. Both samples comprised adults, who voluntarily agreed to participate and signed an informed consent form. Individuals with diagnosed mental disorders were excluded, as well as those with active psychiatric treatment.

The United Kingdom sample consisted of a subsample ( n  = 1,100) extracted from the Mowlem et al. (2019) study database, who had not reported a diagnosis of ADHD ( M  = 33.9 years; SD  = 13.5; range 18–83 years; 74.2% female). The Spanish sample included 391 students and staff members from the Universitat de les Illes Balears, Universidad Complutense de Madrid, and Universidad de Granada, as well as others in the general population ( M  = 26.9 years; SD  = 11.9; range 18–70 years; 78% female). Participants were recruited via mailing, electronic, and poster advertisements, as well as through online informative talks, and were not selected on any psychological or sociodemographic characteristics.

The Spanish sample was equivalent to the UK sample in terms of sex proportion, χ 2 (1) = 2.33, p  = 0.12, Cramer’s V  = 0.03. Regarding age, participants from the Spanish sample were younger than those from the UK sample used, F (1, 1410) = 82.84, p  < 0.01, η 2 partial  = 0.055. However, age differences did not reach the level of statistical meaningfulness (i.e., medium effect size) to prevent type-I error, in large sample size studies ( Lin et al., 2013 ).

2.2. Materials and procedure

Recruitment of the Spanish sample started in the autumn of 2019, being completed half year later. Spanish versions of self-reported measures were collected through online forms. Participants signed an electronic consent form before completing the self-report measures. The Balearic Islands Research Ethics Committee (IB4093/20PI) approved all procedures. Acquisition of self-reported data from the UK used a similar approach ( Mowlem et al., 2019 ).

2.2.1. Translation and adaptation of the Spanish version of the MEWS

Prof. Philip Asherson and Dr. Florence Mowlem provided permission for the translation and adaptation of the MEWS scale ( Mowlem et al., 2016 ). A sequential forward-backward translation approach was followed to adapt the MEWS into Spanish. First, each of the 12 original English items was independently translated into Spanish by two bilingual researchers. Both researchers were familiar with cognitive-related research and clinical practice. Secondly, the proposed translations were discussed, and a consensus was reached prior to the backward translation. Spanish-adapted items were then sent to a native Spanish-English bilingual clinical psychologist to backward translate them again to English. In the third step, two independent researchers and the same bilingual native psychologist compared the item translations and carried out needed variations to ensure a proper content translation (inter-judge content review and correspondence analysis). As a result, the first version of the adapted questionnaire was tested in a pilot sample ( n  = 25) to detect potential difficulties in item comprehension (see Table 1 for final items). No specific difficulties were found in either the items or the instrument overall. After this forward-backward translation, the whole sample was recruited for complete validation analyses.

Spanish items of the MEWS.

2.2.2. Self-reported negative affect

2.2.2.1. negative affect.

The negative affect subscale of the Positive and Negative Affect Schedule (PANAS, Watson et al., 1988 ) was used. This subscale consists of 10 statements describing different negative feelings and emotional states rated on a 5-point Likert-type scale (1 = Not at all ; 5 = Very much ); measuring the extent to which each statement applies to the person’s global tendencies. Cronbach’s alpha for the Spanish sample was α = 0.881.

2.2.3. Self-reported negative emotion regulation strategies

2.2.3.1. brooding rumination.

The shortened Ruminative Response Scale (RRS; Treynor et al., 2003 ) was used. The scale is composed of 10 items and divided into two subscales: brooding and reflection. Each subscale consists of five items rated on a 4-point Likert-type scale (1 =  Totally disagree ; 4 =  Totally agree ) according to the frequency in which ruminative responses are presented when experiencing a dysphoric mood. Cronbach’s alpha for the Spanish sample was α  = 0.784.

2.2.4. Self-reported attentional and mindfulness capabilities

2.2.4.1. attentional control.

The Attentional Control Scale (ACS; Derryberry and Reed, 2002 ) was used. The scale comprises 20 items rated on a 4-point Likert-type scale (1 =  Almost never ; 4 =  Always ) measuring the ability to voluntarily manage attention. The scale can be divided into two subscales: focusing and shifting. Following Ólafsson et al. (2011) , item 9 was excluded from the overall score. Cronbach’s alpha for the Spanish sample was α  = 0.842 for the total scale; and α  = 0.814 and α  = 0.729 for focusing and shifting subscales, respectively.

2.2.4.2. Mindfulness

The Spanish version of the Five Facets of Mindfulness Questionnaire (FFMQ; Baer et al., 2006 ) was used to evaluate self-reported trait mindfulness ( Cebolla et al., 2012 ). It consists of 39 items divided into five subscales assessing different aspects of mindfulness: Observing, Describing, Acting with awareness, Non-judging of inner experience, and Non-reactivity to inner experiences. Items are rated on a Likert scale ranging from 1 ( Never or very rarely true ) to 5 ( Very often or always true ) including some items with reversed scores. Cronbach’s alpha for the Spanish sample was α  = 0.754 for Observing, α  = 0.895 for Describing, α  = 0.862 for Acting with awareness, α  = 0.879 for Non-judging, and α  = 0.781 for Non-reactivity.

2.2.5. Depressive and anxiety symptomatology

2.2.5.1. depressive symptomatology.

The Patient Health Questionnaire-9 (PHQ-9) was used. PHQ-9 is a short instrument designed to screen for depression in primary care and other medical settings ( Kroenke et al., 2001 ). Each item is scored from 0 (not at all) to 3 (nearly every day) assessing the concurrent presence of depressive symptomatology. Cronbach’s alpha for the Spanish sample was α  = 0.884.

2.2.5.2. Anxious symptomatology

The General Anxiety Disorder (GAD-7) instrument ( Spitzer et al., 2006 ) was used to evaluate concurrent anxiety symptoms. The scale has been widely used in clinical practice and research and is composed of 7 items rated from 0 (not at all) to 3 (nearly every day) assessing the concurrent presence of depressive symptomatology. Cronbach’s alpha for the Spanish sample was α  = 0.886.

2.3. Statistical analyses

All the analyses were conducted using the R software (psych, lavaan, and corrplot packages) and SPSS 21.0.0.

2.3.1. Factor structure of the MEWS in the UK dataset

Bearing in mind that the MEWS structure poorly fitted to data, as shown by the elevated close fit testing index in a previous study (RMSEA = 0.015; see Mowlem et al., 2019 ), model misspecification should not be discarded ( Fan and Shivo, 2007 ; Heene et al., 2012 ; Savalei, 2012 ). To deal with covariance structure model misspecification, hierarchical exploratory factor analysis was used. The hierarchical factor analysis allows for detecting complex structures covering common variance entirely explained by subordinate factors ( Markon, 2019 ). This analysis involves transforming an oblique factor solution into an orthogonal solution, ‘preserving the desired interpretation characteristics of the oblique solution, but also discloses the hierarchical structuring of the variables’ ( Schmid and Leiman, 1957 , p. 53). The hierarchical exploratory factor analyses were then conducted to explore a more complex (hierarchical) structure of the English version of the revised 12-item MEWS ( Mowlem et al., 2016 ) using a UK sample. This may help underlying first-order factors to be visualized.

Confirmatory factor analysis (CFA) was subsequently conducted to compare the fit of factor structures derived from the hierarchical analysis, the 1-factor structure demonstrated in previous studies ( Mowlem et al., 2016 ; Nakovics et al., 2020 ) and other hierarchical solutions using the UK sample. CFA estimates were obtained using diagonally weighted least square algorithms due to the ordinal response scale of items and data distribution skewness ( DiStefano and Morgan, 2014 ; Li, 2016 ). Standard errors of estimated parameters were calculated by bootstrapping. The following fit indices were used to assess the goodness of fit ( Hu and Bentler, 1999 ): the χ 2 test (a non-significant χ 2 is indicative of perfect fit), the root mean squared of the residuals (RMSEA <0.080 indicates satisfactory fit; RMSEA >0.080 indicates poor fit), the Comparative Fit Index (CFI) and the Tucker-Lewis Index (TLI) (for both indexes scores above 0.95 indicate satisfactory fit) ( Hu and Bentler, 1999 ), and finally, the standardized root mean square residual (SRMR) (scores >0.080 depicting poor fit data).

The hierarchical exploratory factor analysis was conducted on a random subsample comprising data from 30% of the UK sample, following the cross-validation tradition ( Knafl and Grey, 2007 ). Data from the remaining participants were used for CFA.

2.3.2. Validation of the Spanish version of the MEWS

Following translation, CFA on the Spanish translation of the MEWS in the Spanish sample was conducted to test the fit of the optimal factor structure derived from the re-analysis of the MEWS in the UK sample. We then conducted the cross-cultural comparison of factor structure under the measurement invariance (MI) approach ( Meredith and Teresi, 2006 ), which investigates whether the MEWS behaves the same way across the Spanish and UK datasets. According to MI, the fit of models with increasing parameter restrictions is compared: a configural solution (i.e., with the same structural pattern of relationships across samples), metric invariance solution (i.e., constraints on item loadings), and scalar invariance (adding constraints on item thresholds). The incremental CFI (ΔCFI) was used to evaluate measurement invariance. A ΔRMSEA ≥0.015 (in absolute value) and ΔCFI ≥0.010 would reflect significant differences between nested models ( Cheung and Rensvold, 2002 ; Chen, 2007 ).

To further evaluate the validity of the Spanish MEWS in the Spanish sample, associations between Spanish MEWS scores and PANAS, ACS, RRS, FFMQ, PHQ, and GAD questionnaires were tested as convergent and divergent validity indices using Pearson’s correlation coefficients.

3.1. Descriptive statistics of items response

Descriptive statistics for both Spanish and UK versions of the MEWS items, as well as mean comparisons among them are provided in Table 2 .

Descriptive statistics of item responses and mean comparisons between UK and Spanish samples.

t  = Mean scores comparisons between UK and Spanish samples for each MEWS item; * p  < 0.05; ** p  < 0.01.

No significant differences were found between mean scores in the two versions except for Item 5 and Item 6, although effect sizes were small to moderate ( d Cohen  = 0.38; IC95% = 0.25 to 0.50 and d Cohen  = 0.16; IC95% = 0.03 to 0.28, respectively).

3.2. Factor structure of the UK sample

As abovementioned, we split our sample into the exploratory factor analysis subsample ( n  = 370) and the confirmatory factor analysis subsample ( n  = 840). The hierarchical factor analysis conducted in the UK exploratory factor analysis sample yielded a 3-factor structure derived from the original 12-item MEWS, explaining 54% of the variance. The standardized loadings derived from this factor structure model under the oblimin rotation are displayed in Table 3 .

Standardized loadings derived from the hierarchical factor analysis on the English MEWS.

The 3-factor model explained 54% of MEWS variance.

Saturation with higher loading was considered (in bold).

Based on this analysis, we decided to remove Factor 3 due to its weakness, and slightly low reliability ( α  = 0.79), as it had only two saturated items. This involved removing item 1, and as item loading for Item 2 was higher than 0.30 this was considered saturated on factor 2. Item 3 was also removed due to a lack of theoretical consistency with the remaining items that saturated on factor 1. Based on these changes, a revised version of the MEWS (MEWS-v2.0) was adopted. This was a 10-item scale with a 2-factor structure: with Factor 1 (items 4, 7, 8, 9, 10, 11, 12) reflecting Uncontrolled Thoughts ; and Factor 2 (Items 2, 5, 6) reflecting Mental Overactivity .

We conducted the confirmatory factor analysis on the confirmatory factor analysis subsample ( n  = 840). Table 4 displays the fit indexes of the competing confirmatory factor models. Factor models are also depicted in Figure 1 .

Model fit summary of confirmatory factor solutions and reliability index for the English MEWS.

Model with a better fit in bold.

The 1-factor model came from the original structure of the 12-item MEWS. The 2-factor solution was derived from the hierarchical factor analysis in conjunction with expert guidelines (10 items). The 3-factor solution was derived from the hierarchical factor analysis (12 items).

All the χ 2 -based models were significant, p  < 0.01.

df, degrees of freedom; RMSEA, Root Mean Square Error of approximation index (scores below 0.080 depict reasonable model fit); CI 90 , confidence interval at 90%; CFI, comparative fit index; TLI, Tucker-Lewis index. Scores of 0.95 or more indicate good model fitting, for TLI and CFI. SRMR, standardized root mean square residual (scores above 0.080 depict poor fit).

Models coming from the hierarchical exploratory factor analysis, using an independent sample.

MEWS confirmatory solutions to be tested. a(1) , unidimensional 12-item model; a(2) , correlated 12-item model; a(3) , uncorrelated 12-item model; b(1) , unidimensional 10-item model; b(2) , correlated 10-item model; b(3) , uncorrelated 10-item model.

To ensure manifest variables to be equivalent between the MEWS solutions, we also tested the fit of a 10-item unidimensional model. Therefore, model testing involved comparing two-factor solutions (unifactorial solution vs. the solution derived from the hierarchical exploratory analysis) for the 12-item MEWS (unifactorial solution vs. 3-factor solution, with either correlated or uncorrelated factors), and for the 10-item MEWS (unifactorial solution vs. 2-factor solution, with either correlated or uncorrelated factors). As a result, the correlated factor models (both the 2-factor and 3-factor models with correlated factors) fitted better to data structure, according to fit indexes (i.e., RMSEA <0.080, both CFI and TLI scores >0.95, and, the SRMR <0.080). However, the 3-correlated factor solution yielded a lower Cronbach’s α for one of their factors ( α < 0.80). Besides, the 2-factor version would better reflect what the instrument measures in theoretical terms. We therefore decided to retain the 2-correlated factor model, with fit indexes: χ 2 (54) = 101.87; p < 0.01; RMSEA = 0.053, CFI = 0.998, TLI = 0.998, SRMR = 0.04. Factor reliability for the two-correlated factor solution ranged between Cronbach’s α  = 0.86 to α  = 0.92.

3.3. Cross-cultural validation of the 2-factor solution of the 10-item MEWS (MEWS-v2.0)

To test whether the Spanish MEWS-v2.0 fitted the two-correlated factor solution, a confirmatory factor analysis was conducted. Adequate fit indices were found, χ 2 (34) = 135.03, p  < 0.01; RMSEA = 0.067 ( CI 90  = 0.058, 0.076), CFI = 0.99, TLI = 0.99, SRMR = 0.06.

Regarding measurement invariance (MI) comparisons to test cross-cultural equivalence of the MEWS structure, fit indices of increasingly restricted solutions are displayed in Table 5 . These fit indices reflect an adequate fit of all the MI models. Moreover, item communalities for both UK and Spanish samples were satisfactory, being greater than 0.30 (see Table 2 ), indicating that the large variance of the item is explained by factors.

Measurement invariance model comparison to explore cross-cultural effects on MEWS structure.

The configural MI imposes the same structural pattern of relationships between both the English and Spanish MEWS responses. The metric invariance solution imposes constraints on item loadings. The scalar invariance model adds constraints on item thresholds.

MI, Measurement invariance; df, degrees of freedom; RMSEA, Root Mean Square Error of approximation index (scores below 0.080 depict reasonable model fit); CI 90 , confidence interval at 90%; CFI, comparative fit index; TLI, Tucker-Lewis index. Scores of 0.95 or more indicate good model fitting, for TLI and CFI. SRMR, standardized root mean square residual (scores above 0.080 depict poor fit).

Regarding incremental indices, although the incremental CFI might point to a lack of measurement invariance (ΔCFI ≤ −0.01, across model comparisons) this result was not endorsed by ΔRMSEA ≤0.015, suggesting no differences on the MEWS structure parameters (item loadings, intercepts, and residuals) between the English and Spanish datasets.

3.4. Convergent and divergent validity in the Spanish sample

Table 6 depicts means and standard deviations for all the self-reported variables included in this study, as well as bivariate correlations between them. The Spanish MEWS-v2.0 (both considering total score and each Factor separately) was positively and significantly associated with negative affect, rumination, and both anxious and depressive symptomatology (stronger correlation value r  = 0.647). In contrast, the MEWS-v2.0 scores were inversely correlated to attentional control and each of the FFMQ scales but the Observing one (stronger correlation value r  = −0.587). The correlation between MEWS-v2.0 subscales (i.e., Factor 1 and Factor 2) was r  = 0.599 ( p  < 0.01).

Descriptive statistics and bivariate correlations between self-reported measures in Spanish sample ( n  = 391).

M, mean; SD, Standard Deviation; MEWS_T, MEWS Total Score; MEWS_UT, MEWS Uncontrolled Thoughts Subscale; MEWS_MO, MEWS Mental Overreactivity Subscale; NA, PANAS Negative Affect Subscale; RRS_T, RRS Total Score; RRS_B, RRS Brooding Subscale; RRS_R, RRS Reflection Subscale; ACS_T, Attentional Control Scale Total; ACS_F, ACS Focusing Subscale; ACS_S, ACS Shifting Subscale; FFMQ_O, Five Facets Mindfulness Questionnaire Observing Subscale; FFMQ_D, Five Facets Mindfulness Questionnaire Describing Subscale; FFMQ_A, Five Facets Mindfulness Questionnaire Awarenness Subscale; FFMQ_NJ, Five Facets Mindfulness Questionnaire Non-Judgment Subscale; FFMQ_NR, Five Facets Mindfulness Questionnaire Non-reaction Subscale.

* p  < 0.005; ** p  < 0.000.

4. Discussion

The first aim of this study was to re-analyze the English version of the 12-item MEWS ( Mowlem et al., 2016 ) in a UK sample, to explore alternative factor structures of the instrument under hierarchical models. This led to a revised 10-item version of the scale (MEWS-v2.0). The second aim was to translate the MEWS to Spanish and assess the cross-scale validity of the translations by evaluating the factor structure of the adapted MEWS-v2.0. Further validation steps for the MEWS-v2.0 included cross-cultural comparisons of the English and Spanish datasets for measurement invariance; and convergent validity against clinical scales previously associated with MW, in the Spanish sample.

We re-evaluated the factor structure of the original 12-item MEWS in the UK sample using a hierarchical approach, given the inflated RMSEA (RMSEA >0.10) of the unidimensional MEWS ( Mowlem et al., 2019 ). Our results showed that a shorter 10-item version of the MEWS (MEWS-v2.0) with a 2-correlated factor structure, had a better fit to data than the original unidimensional structure or a 3-factor solution on the original 12-item version. More specifically, our results, therefore, suggest the existence of two factors which, given the item content, could fit the descriptive labels of Uncontrolled Thoughts (Factor 1) and Mental Overactivity (Factor 2). Although the hierarchical EFA also suggested a 3-factor solution, with satisfactory CFA fit indices, we decided to remove the factor 3 due to factor overdetermination issues and factor stability ( MacCallum et al., 1996 ; Tabachnick and Fidell, 2001 ). We come from the assumption that a factor with fewer than three items may be distinctive of a weak factor ( Costello and Osborne, 2005 ). Two items were saturated on Factor 3 (the item 1 and 2). The item 2 saturated on both Factor 2 and 3, leading to cross-loading issues. In this regard, cross-loading items (i.e., those with loading at least 0.32 on two or more factors) may affect the accuracy of factor extraction based on eigenvalue methods ( Li et al., 2020 ). We decided the item 2 to be dropped from Factor 3 and retained on Factor 2, as its loading was higher than 0.30 and it theoretically matches with the Factor 2 construct (Mental overactivity). Only one item distinctively saturated on this third factor (item 1). We, therefore, decided to drop item 1 from the scale so as to retain robust factors from the MEWS.

The MEWS-v2.0 may be used both as a unidimensional scale to assess the global tendency to engage in excessive spontaneous MW, as well as divided in two interdependent subscales of Uncontrolled thoughts and Mental Overactivity . Although highly correlated, both factors ( Uncontrolled thoughts and Mental Overactivity ) appear to reflect two theoretically separated constructs. While Mental Overactivity items’ content reflects a greater tendency to experience thoughts constantly on the go and flitting from one topic to another, Uncontrolled Thoughts reflect a person’s difficulty in voluntarily regulating these unfocused thoughts. Therefore, they appear to relate closely to concepts of attentional and cognitive control. This proposal aligns with studies suggesting that reduced attentional control may be a shared mechanism between MW and external distraction ( Unsworth et al., 2012 ). In relation to the Christoff et al. (2016) model, it is tempting to speculate that participants with a greater tendency to MW who also exhibit greater attentional control capabilities, would show more controlled forms of spontaneous thought. For example, off-task thoughts might be more deliberate and potentially more creative, reflecting a more deliberate form of MW. Further studies would benefit from explicitly exploring this hypothesis by comparing the MEWS-v2.0 subscales derived from the 2-factors structure with other scales addressing different aspects of MW; such as deliberate and spontaneous forms of MW ( Mrazek et al., 2013 ).

Although our data-driven approach generated two factors, both appeared to be highly correlated, which suggests that they are interdependent and reflect different aspects of the same higher global dimension; that is spontaneous MW. This conceptualisation seems to be in line with the results of the factorial structure of the German version of the MEWS (MEWS-G) reported by Nakovics et al. (2020) , as their explorative analyses found that both a 2-factor and 3-factor solutions explained greater variance than a unidimensional factor structure. However, they also found those models to have many cross-loadings with many items saturating in different factors at the same time; reflecting an overlap between factors consistent with a single global dimension ( Nakovics et al., 2020 ).

Regarding the new Spanish version of the 10-item MEWS-v2.0, CFA analysis showed a good fit in line with the results derived from the re-analysis of the English MEWS, with the 2-correlated factor structure fitted adequately to data. Values of Cronbach’s α reflected that internal consistency of the two-factor model was high both for the Spanish and UK 10-item versions in their respective samples. Additionally, the cross-cultural analyses showed measurement invariance, suggesting that MEWS-v2.0 is a reliable and valid instrument capturing the same constructs across both UK and Spanish samples; so that no cultural, cross-sample, or scale translation differences were observed. These findings strongly support the validity of the forward-backward translation process and the adaptation of the MEWS to a revised 10-item version.

The Spanish MEWS-v2.0 also demonstrated reliable convergent and divergent validity. Starting with convergent measures, a positive relationship was found between the self-reported tendency to excessive MW and rumination. These associations were significant when considering both total and subscale-divided MEWS-v2.0 scores. This should not be surprising given the substantial overlap between the core characteristics of both constructs. For example, both brooding rumination and spontaneous MW seem to share an unintentional nature. Furthermore, they are both associated with executive impairments since individuals with a greater tendency to MW (and/or ruminate) would exhibit greater difficulties in disengaging attentional resources from irrelevant-task stimuli, and ultimately controlling thoughts. Our results are in line with this conception, showing both MEWS-v2.0 subscales to be negatively related to the self-reported capability to voluntarily manage attentional resources.

Christoff et al. (2016) recently described that MW can be characterized by a huge variability in the content of thought, whereas brooding rumination would tend to remain fixed/restricted on a single and negatively valenced topic. Thus, they consider rumination to be a constrained form of MW in terms of content ( Christoff et al., 2016 ). However, previous studies also reported independent electrophysiological indices (heart rate variability), associated with each of them ( Ottaviani et al., 2015 ). Further complimentary studies would benefit by combining cardiac indices with experience-sampling methods when analyzing MW, considering both contents of thought and contextual variables.

A significant positive relationship between MW and anxious and depressive symptomatology, as well as with negative affect was found in the Spanish sample. This is in line with previous literature linking excessive MW to neuroticism ( Robison et al., 2017 ) and depressive symptoms ( Killingsworth and Gilbert, 2010 ; Andrews-Hanna et al., 2013 ; Hoffmann et al., 2016 ). However, the mechanism of the MW-Negative mood pathway remains unclear and needs further investigation, since the direction of any causal relationship is still not well understood ( Smallwood and O’Connor, 2011 ; Stawarczyk et al., 2013 ).

Regarding divergent validity, as expected, a significant negative association was found between attentional control and MW, with those reporting higher MW scores, reporting lower attentional control capabilities. Although, impaired task performance for measures of attentional skills has previously been reported to be related to high levels of MW ( Mooneyham and Schooler, 2013 ; Stawarczyk et al., 2014 ), evidence for this association using self-reported measures of attentional control remained unexplored in adults. Assuming an equivalence between performance-based and self-reported measures of attentional control [although this has been questioned ( Tortella-Feliu et al., 2014 )], a negative association between self-reported attentional control and MW was expected. This makes even more sense considering that reduced self-reported attentional control has been previously related to an increased tendency to ruminate ( Armstrong et al., 2011 ; Koster et al., 2011 ; Tortella-Feliu et al., 2014 ). It may be hypothesized that both MW and rumination share some underlying mechanisms, such as low attentional control, which may be at least partially responsible for their commonalities. Attentional control refers to the ability to voluntarily regulate and manage attentional allocation, including the capability to concentrate and resist distraction, to switch attention between tasks, and to flexibly control thoughts ( Derryberry and Reed, 2002 ). It is therefore plausible that participants with lower attentional control capabilities find it harder to disengage their attention from self-focused task-unrelated thoughts and redirect attentional focus to an ongoing task. In line with this, Forster and Lavie (2009 , 2014) advanced the hypothesis that MW could be a manifestation of a more general susceptibility to irrelevant distractions, whether from internal task unrelated thoughts or external distractions.

Finally, it has been proposed that there is an opposite relationship between mindfulness capabilities and MW ( Marchetti et al., 2016 ), since the ability to remain mindful at the moment (i.e., focused on an object or task) appears to be in direct opposition to the tendency for attention to wander away from the task at hand ( Mrazek et al., 2012 ). Consistent with this, our data showed that an increased tendency to MW was significantly and negatively associated with four out of five of the FFMQ subscales (Describing, Awareness, Non-judgment, and Non-reaction). The Observing subscale of the FFMQ appeared not to be associated with either the total MEWS-v2.0 score or any of the two subscales. Considering that this FFMQ subscale reflects the ability to notice or attend to internal and external experiences, such as thoughts, sensations, or emotions ( Baer et al., 2006 ), this was unexpected. However, our results are in line with those reported by Cebolla et al. (2012) who found that the Observing subscale was the only one not showing convergent and divergent validity. It is tempting to speculate that this may be linked with an unawareness MW experience, and further studies would benefit to include awareness-unawareness as key dimensions when studying MW in relation to emotional-related processes ( Schooler et al., 2011 ).

This study has some limitations. First, our main aim was to validate the scale as an instrument to evaluate individual differences in MW in the general adult population, so participants meeting the criteria for mental health disorders were excluded from this study. Furthermore, the female gender constituted the 78% and the 74.2% of the Spanish and UK sample respectively, which may affect the representativeness of the sample. In order to contribute to the generalisability of the results, future studies would benefit from a more gender-equitable sample. In relation to the Spanish version of the MEWS, future studies would benefit from analysis in clinical populations, such as ADHD, to ensure measurement invariance between general and clinical population samples. Secondly, the non-clinical UK sample analyzed in this study was selected from a broader pool of participants under the unique condition of not being diagnosed with ADHD. It may however have been that some of these may have presented with other mental health issues which have not been accounted for. Thirdly, further studies will need to explore the convergent validity of the MEWS-v2.0 and more specifically the new Spanish translation, with other scales addressing different aspects of MW such as deliberate and spontaneous forms of MW.

Several studies have already begun to include experience sampling-based measures of MW and executive/attentional performance-based measures, as a complement of self-reported instruments when exploring emotional-related factors, such as emotional instability ( Moukhtarian et al., 2020 ; Bozhilova et al., 2021 ). This multi-method approach is of special interest to better capture and understand the MW phenomenon and to contribute to the exploration of its potential relationships with basic attentional impairments. Additionally, results transferability from laboratory settings to ecological environments as related to MW seems to be a controversial issue ( Kane et al., 2017 ; Linz et al., 2021 ) and further research combining these measures is still needed.

5. Conclusion

The 10-item version of both the English and the Spanish MEWS (MEWS-v2.0) were demonstrated to be useful and valid instruments to assess MW in healthy adult populations. Two factors were identified reflecting Uncontrolled thoughts (Factor 1) and Mental Overactivity (Factor 2). The correlated two-factor structure may optimally capture the MEWS variance, accounting for two specific but interrelated dimensions of a higher dimension of spontaneous MW. The Spanish version of MEWS-v2.0 showed adequate internal consistency levels and construct validity, as well as evidence of convergent and divergent validity in line with hypothesized relationship directions between selected measures. Furthermore, the cross-cultural analyses showed that the Spanish MEWS-v2.0 was a reliable and valid instrument capturing the same construct as the English version of MEWS-v2.0. Given that excessive spontaneous MW has been previously associated with several clinical manifestations such as depression, ADHD, and related factors such as negative affect and executive impairments, it is tempting to hypothesize its role as a transdiagnostic process. However, further research is needed to contribute to our understanding of the functional consequences of MW and explore the potential role of MW as related to vulnerability to affective disorders. Additionally, MW needs to be also considered as a potential clinical treatment target, for which proper assessment tools are critical.

Data availability statement

Ethics statement.

The studies involving human participants were reviewed and approved by the Balearic Islands Research Ethics Committee (IB4093/20PI). The patients/participants provided their written informed consent to participate in this study.

Author contributions

AM-R: conceptualization, methodology, investigation, formal analysis, and original draft preparation. AT-L: formal analysis, data curation, and original draft preparation. FM and PA: reviewing, editing, and resources. All authors contributed to the article and approved the submitted version.

This work was supported by the Spanish Government through the Torres Quevedo Grant Program (PTQ2018-009836) and the Department of Psychology of the University of the Balearic Islands.

Conflict of interest

AM-R was employed by company Apploading S.L.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

• Andrews-Hanna J. R., Kaiser R. H., Turner A. E. J., Reineberg A. E., Godinez D., Dimidjian S., et al.. (2013). A penny for your thoughts: dimensions of self-generated thought content and relationships with individual differences in emotional wellbeing . Front. Psychol. 4 :900. doi: 10.3389/fpsyg.2013.00900 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Armstrong T., Zald D. H., Olatunji B. O. (2011). Attentional control in OCD and GAD: specificity and associations with core cognitive symptoms . Behav. Res. Ther. 49 , 756–762. doi: 10.1016/j.brat.2011.08.003, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baer R. A., Smith G. T., Hopkins J., Krietemeyer J., Toney L. (2006). Using self-report assessment methods to explore facets of mindfulness . Assessment 13 , 27–45. doi: 10.1177/1073191105283504, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baird B., Smallwood J., Mrazek M. D., Kam J. W. Y., Franklin M. S., Schooler J. W. (2012). Inspired by distraction: mind wandering facilitates creative incubation . Psychol. Sci. 23 , 1117–1122. doi: 10.1177/0956797612446024 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baird B., Smallwood J., Schooler J. W. (2011). Back to the future: autobiographical planning and the functionality of mind-wandering . Conscious. Cogn. 20 , 1604–1611. doi: 10.1016/j.concog.2011.08.007, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bozhilova N., Kuntsi J., Rubia K., Michelini G., Asherson P. (2021). Electrophysiological modulation of sensory and attentional processes during mind wandering in attention-deficit/hyperactivity disorder . Neuroimage 29 :102547. doi: 10.1016/j.nicl.2020.102547, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Browne M. W., Cudeck R. (1993). “ Alternative ways of assessing model fit ” in Testing structural equation models . eds. Bolle K. A., Long J. S. (Newbury Park, CA: Sage; ), 136–162. [ Google Scholar ]
• Callard F., Smallwood J., Golchert J., Margulies D. S. (2013). The era of the wandering mind? Twenty-first century research on self-generated mental activity . Front. Psychol. 4 :891. doi: 10.3389/fpsyg.2013.00891, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Carriere J. S. A., Seli P., Smilek D. (2013). Wandering in both mind and body: individual differences in mind wandering and inattention predict fidgeting . Can. J. Exp. Psychol. 67 , 19–31. doi: 10.1037/a0031438, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cebolla A., García-Palacios A., Soler J., Guillen V., Baños R., Botella C. (2012). Psychometric properties of the Spanish validation of the five facets of mindfulness questionnaire (FFMQ) . Eur. J. Psychiatry 26 , 118–126. doi: 10.4321/S0213-61632012000200005 [ CrossRef ] [ Google Scholar ]
• Chen F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance . Struct. Equ. Model. Multidiscip. J. 14 , 464–504. doi: 10.1080/10705510701301834 [ CrossRef ] [ Google Scholar ]
• Cheung G. W., Rensvold R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance . Struct. Equ. Model. Multidiscip. J. 9 , 233–255. doi: 10.1207/S15328007SEM0902_5 [ CrossRef ] [ Google Scholar ]
• Christoff K., Irving Z. C., Fox K. C. R., Nathan Spreng R., Andrews-Hanna J. R. (2016). Mind-wandering as spontaneous thought: a dynamic framework . Nat. Rev. Neurosci. 17 , 718–731. doi: 10.1038/nrn.2016.113 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Costello A. B., Osborne J. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis . Pract. Assess. Res. Eval. 10 , 1–9. doi: 10.7275/jyj1-4868 [ CrossRef ] [ Google Scholar ]
• Deng Y.-Q., Li S., Tang Y.-Y. (2014). The relationship between wandering mind, depression and mindfulness . Mindfulness 5 , 124–128. doi: 10.1007/s12671-012-0157-7 [ CrossRef ] [ Google Scholar ]
• Derryberry D., Reed M. A. (2002). Anxiety-related attentional biases and their regulation by attentional control . J. Abnorm. Psychol. 111 , 225–236. doi: 10.1037/0021-843X.111.2.225, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• DiStefano C., Morgan G. B. (2014). A comparison of diagonal weighted least squares robust estimation techniques for ordinal data . Struct. Equ. Model. Multidiscip. J. 21 , 425–438. doi: 10.1080/10705511.2014.915373 [ CrossRef ] [ Google Scholar ]
• Fan X., Shivo S. A. (2007). Sensitivity of fit indices to model misspecification and model types . Multivar. Behav. Res. 42 , 509–529. doi: 10.1080/00273170701382864 [ CrossRef ] [ Google Scholar ]
• Figueiredo T., Erthal P., Fortes D., Asherson P., Mattos P. (2018). Transcultural adaptation to Portuguese of the mind excessively wandering scale (MEWS) for evaluation of thought activity . Trends Psychiatry Psychotherapy 40 , 337–341. doi: 10.1590/2237-6089-2017-0117, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Forster S., Lavie N. (2009). Harnessing the wandering mind: the role of perceptual load . Cognition 111 , 345–355. doi: 10.1016/j.cognition.2009.02.006, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Forster S., Lavie N. (2014). Distracted by your mind? Individual differences in distractibility predict mind wandering . J. Exp. Psychol. Learn. Mem. Cogn. 40 , 251–260. doi: 10.1037/a0034108, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Franklin M. S., Mrazek M. D., Anderson C. L., Johnston C., Smallwood J., Kingstone A., et al.. (2017). Tracking distraction . J. Atten. Disord. 21 , 475–486. doi: 10.1177/1087054714543494 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Heene M., Sven Hilbert H., Freudenthaler H., Bühner M. (2012). Sensitivity of SEM fit indexes with respect to violations of uncorrelated errors . Struct. Equ. Model. Multidiscip. J. 19 , 36–50. doi: 10.1080/10705511.2012.634710 [ CrossRef ] [ Google Scholar ]
• Hobbiss M. H., Fairnie J., Jafari K., Lavie N. (2019). Attention, Mindwandering, and mood . Conscious. Cogn. 72 , 1–18. doi: 10.1016/j.concog.2019.04.007, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hoffmann F., Banzhaf C., Kanske P., Bermpohl F., Singer T. (2016). Where the depressed mind wanders: self-generated thought patterns as assessed through experience sampling as a state marker of depression . J. Affect. Disord. 198 , 127–134. doi: 10.1016/j.jad.2016.03.005, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hu L. T., Bentler P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives, structural equation modeling . Struct. Equ. Model. 6 , 1–55. doi: 10.1080/10705519909540118 [ CrossRef ] [ Google Scholar ]
• Kane M. J., Gross G. M., Chun C. A., Smeekens B. A., Meier M. E., Silvia P. J., et al.. (2017). For whom the mind wanders, and when, varies across laboratory and daily-life settings . Psychol. Sci. 28 , 1271–1289. doi: 10.1177/0956797617706086, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Killingsworth M. A., Gilbert D. T. (2010). A wandering mind is an unhappy mind . Science 330 :932. doi: 10.1126/science.1192439, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Knafl G. J., Grey M. (2007). Factor analysis model evaluation through likelihood cross-validation . Stat. Methods Med. Res. 16 , 77–102. doi: 10.1177/0962280206070649, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Koster E. H. W., De Lissnyder E., Derakshan N., De Raedt R. (2011). Understanding depressive rumination from a cognitive science perspective: the impaired disengagement hypothesis . Clin. Psychol. Rev. 31 , 138–145. doi: 10.1016/j.cpr.2010.08.005, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kroenke K., Spitzer R. L., Williams J. B. (2001). The PHQ-9: validity of a brief depression severity measure . J. Gen. Intern. Med. 16 , 606–613. doi: 10.1046/j.1525-1497.2001.016009606.x, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Li C. H. (2016). Confirmatory factor analysis with ordinal data: comparing robust maximum likelihood and diagonally weighted least squares . Behav. Res. Methods 48 , 936–949. doi: 10.3758/s13428-015-0619-7, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Li Y., Wen Z., Hau K.-T., Yuan K.-H., Peng Y. (2020). Effects of cross-loadings on determining the number of factors to retain . Struct. Equ. Model. Multidiscip. J. 27 , 841–863. doi: 10.1080/10705511.2020.1745075 [ CrossRef ] [ Google Scholar ]
• Lin M., Lucas H. C., Jr., Shmueli G. (2013). Research commentary—too big to fail: large samples and the p-value problem . Inform. Syst. Res. 24 , 906–917. doi: 10.1287/isre.2013.0480 [ CrossRef ] [ Google Scholar ]
• Linz R., Pauly R., Smallwood J., Engert V. (2021). Mind-wandering content differentially translates from lab to daily life and relates to subjective stress experience . Psychol. Res. 85 , 649–659. doi: 10.1007/s00426-019-01275-2, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• MacCallum R. C., Browne M. W., Sugawara H. M. (1996). Power analysis and determination of sample size for covariance structure modeling . Psychol. Methods 1 , 130–149. doi: 10.1037/1082-989X.1.2.130 [ CrossRef ] [ Google Scholar ]
• Marchetti I., Koster E. H. W., Klinger E., Alloy L. B. (2016). Spontaneous thought and vulnerability to mood disorders: the dark side of the wandering mind . Clin. Psychol. Sci. 4 , 835–857. doi: 10.1177/2167702615622383, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Marchetti I., Van de Putte E., Koster E. H. W. (2014). Self-generated thoughts and depression: from daydreaming to depressive symptoms . Front. Hum. Neurosci. 8 :131. doi: 10.3389/fnhum.2014.00131, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Markon K. E. (2019). Bifactor and hierarchical models: specification, inference, and interpretation . Annu. Rev. Clin. Psychol. 15 , 51–69. doi: 10.1146/annurev-clinpsy-050718-095522, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Meredith W., Teresi J. A. (2006). An essay on measurement and factorial invariance . Med. Care 44 , S69–S77. doi: 10.1097/01.mlr.0000245438.73837.89, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mooneyham B. W., Schooler J. W. (2013). The costs and benefits of mind-wandering: a review . Can. J. Exp. Psychol. 67 , 11–18. doi: 10.1037/a0031569 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Moukhtarian T. R., Reinhard I., Morillas-Romero A., Ryckaert C., Mowlem F., Bozhilova N., et al.. (2020). Wandering minds in attention-deficit/hyperactivity disorder and borderline personality disorder . Eur. Neuropsychopharmacol. 38 , 98–109. doi: 10.1016/j.euroneuro.2020.07.005, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mowlem F. D., Agnew-Blais J., Pingault J. B., Asherson P. (2019). Evaluating a scale of excessive mind wandering among males and females with and without attention-deficit/hyperactivity disorder from a population sample . Sci. Rep. 9 :3071. doi: 10.1038/s41598-019-39227-w, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mowlem F. D., Skirrow C., Reid P., Maltezos S., Nijjar S. K., Merwood A., et al.. (2016). Validation of the mind excessively wandering scale and the relationship of mind wandering to impairment in adult ADHD . J. Atten. Disord. 23 , 624–634. doi: 10.1177/1087054716651927, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mrazek M. D., Phillips D. T., Franklin M. S., Broadway J. M., Schooler J. W. (2013). Young and restless: validation of the mind-wandering questionnaire (MWQ) reveals disruptive impact of mind-wandering for youth . Front. Psychol. 4 :560. doi: 10.3389/fpsyg.2013.00560, PMID: [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mrazek M. D., Smallwood J., Schooler J. W. (2012). Mindfulness and mind-wandering: finding convergence through opposing constructs . Emotion 12 , 442–448. doi: 10.1037/a0026678, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nakovics H., Benoit D., Asherson P., Luderer M., Alm B., Vollstädt-Klein S., et al.. (2020). Validation of the German version of the mind excessively wandering scale (MEWS-G) . Fortschritte Der Neurologie Psychiatrie. 89 , 607–616. doi: 10.1055/a-1362-9743, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ólafsson R. P., Smári J., Guðmundsdóttir F., Olafsdóttir G., Harðardóttir H. L., Einarsson S. M. (2011). Self reported attentional control with the attentional control scale: factor structure and relationship with symptoms of anxiety and depression . J. Anxiety Disord. 25 , 777–782. doi: 10.1016/j.janxdis.2011.03.013, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ottaviani C., Shahabi L., Tarvainen M., Cook I., Abrams M., Shapiro D. (2015). Cognitive, behavioral, and autonomic correlates of mind wandering and perseverative cognition in major depression . Front. Neurosci. 9 :433. doi: 10.3389/fnins.2014.00433 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Robison M. K., Gath K. I., Unsworth N. (2017). The neurotic wandering mind: an individual differences investigation of neuroticism, mind-wandering, and executive control . Q. J. Exp. Psychol. 70 , 649–663. doi: 10.1080/17470218.2016.1145706, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Salavera C., Urcola-Pardo F., Usán P., Jarie L. (2017). Translation and validation of the mind-wandering test for Spanish adolescents . Psicologia 30 . doi: 10.1186/s41155-017-0066-8 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Savalei V. (2012). The relationship between root mean square error of approximation and model misspecification in confirmatory factor analysis models . Educ. Psychol. Meas. 72 , 910–932. doi: 10.1177/001316441245256 [ CrossRef ] [ Google Scholar ]
• Schmid J., Leiman J. M. (1957). The development of hierarchical factor solutions . Psychometrika 22 , 53–61. doi: 10.1007/BF02289209 [ CrossRef ] [ Google Scholar ]
• Schooler J. W., Smallwood J., Christoff K., Handy T. C., Reichle E. D., Sayette M. A. (2011). Meta-awareness, perceptual decoupling and the wandering mind . Trends Cogn. Sci. 15 , 319–326. doi: 10.1016/j.tics.2011.05.006, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Seli P., Carriere J. S. A., Smilek D. (2015). Not all mind wandering is created equal: dissociating deliberate from spontaneous mind wandering . Psychol. Res. 79 , 750–758. doi: 10.1007/s00426-014-0617-x, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Davies J. B., Heim D., Finnigan F., Sudberry M., O’Connor R., et al.. (2004). Subjective experience and the Attentional lapse: task engagement and disengagement during sustained attention . Conscious. Cogn. 13 , 657–690. doi: 10.1016/j.concog.2004.06.003, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., O’Connor R. C. (2011). Imprisoned by the past: unhappy moods lead to a retrospective bias to mind wandering . Cognit. Emot. 25 , 1481–1490. doi: 10.1080/02699931.2010.545263, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Schooler J. W. (2006). The restless mind . Psychol. Bull. 132 , 946–958. doi: 10.1037/0033-2909.132.6.946 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Schooler J. W. (2015). The science of mind wandering: empirically navigating the stream of consciousness . Annu. Rev. Psychol. 66 , 487–518. doi: 10.1146/annurev-psych-010814-015331, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Spitzer R. L., Kroenke K., Williams J. B. W., Löwe B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7 . Arch. Intern. Med. 166 , 1092–1097. doi: 10.1001/archinte.166.10.1092 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stawarczyk D., Majerus S., Catale C., D’Argembeau A. (2014). Relationships between mind-wandering and attentional control abilities in young adults and adolescents . Acta Psychol. 148 , 25–36. doi: 10.1016/j.actpsy.2014.01.007, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stawarczyk D., Majerus S., D’Argembeau A. (2013). Concern-induced negative affect is associated with the occurrence and content of mind-wandering . Conscious. Cogn. 22 , 442–448. doi: 10.1016/j.concog.2013.01.012, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tabachnick B.G., Fidell L.S. (2001). Using multivariate statistics . 4th Edition, Allyn and Bacon. Boston, MA. [ Google Scholar ]
• Tortella-Feliu M., Morillas-Romero A., Balle M., Bornas X., Llabrés J., Pacheco-Unguetti A. P. (2014). Attentional control, attentional network functioning, and emotion regulation styles . Cognit. Emot. 28 , 769–780. doi: 10.1080/02699931.2013.860889 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Treynor W., Gonzalez R., Nolen-Hoeksema S. (2003). Rumination reconsidered: a psychometric analysis . Cogn. Ther. Res. 27 , 247–259. doi: 10.1023/A:1023910315561 [ CrossRef ] [ Google Scholar ]
• Unsworth Nash., Brittany D McMillan., Gene A Brewer., Gregory J Spillers. (2012). “Everyday attention failures: an individual differences investigation” . J. Exp Psychol Learn Mem Cogn. 38 , 1765–75. doi: 10.1037/a0028075 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Watson D., Clark L. A., Tellegen A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales . J. Pers. Soc. Psychol. 54 , 1063–1070. doi: 10.1037/0022-3514.54.6.1063, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yamaoka A., Yukawa S. (2020). Does mind wandering during the thought incubation period improve creativity and worsen mood? Psychol. Rep. 123 , 1785–1800. doi: 10.1177/0033294119896039, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]

Let Your Mind Wander

Experience the benefits of daydreaming in creativity and problem solving..

Posted February 20, 2024 | Reviewed by Davia Sills

• Understanding Attention
• Find a therapist to help with ADHD
• Mind wandering is a universal human experience rooted in evolution and brain science.
• Creative thinking and problem-solving happen when people's minds wander.
• Mind wandering also allows individuals to simulate the future and script their range of responses.

Comedian Steven Wright deadpanned, “I was trying to daydream, but my mind kept wandering.” With that quip, he encapsulated the universal human experience of mind wandering .

Our minds are never idle. When not focused on doing a specific task or achieving a goal, we daydream, fantasize , ruminate, reminisce about something in the past, or worry about something in the future.

In fact, research with thought-sampling techniques has shown that an average of 47 percent of our time is spent with our mind wandering. 1 Think of it: nearly half our waking hours!

Research also suggests that mind wandering is not time wasted but a constructive mental tool supporting creativity, problem-solving, and better mood.

Creativity Benefits From Mind Wandering

Mind wandering can be negative and obsessive and present obstacles to accomplishing goals . Left to their own devices, people may gravitate toward the negative.

But that is only part of the story. Many reveries are welcome, playful, creative daydreams to be nourished. Mind wandering allows us to learn from our imagination . Consequently, mind wandering is critical to “creative incubation,” the background mental work that precedes our insightful “Aha!” moments.

In my lab, we have found that broad and unrestrained mind wandering can also promote better mood among people with mental health disorders such as anxiety and depression .

Learning Through Imagined Experience

Memory stores actual experience. It can also hold the outcome of experiences we imagine or simulated scenarios. I’ll give you an example.

While on an airplane flight once, I was reviewing a paper, and my mind drifted until it landed on the emergency door, which triggered the following simulation: What if the door suddenly opens while we are in the air?

I will need a parachute, I thought. I could probably use the airplane blanket on my lap, but I will not be able to hold on to it in the strong wind—it needs holes. I can use my pen to make the holes. And so on.

This story is far-fetched and funny, but nevertheless, I now have, from an imagined experience, a script stored in my memory that would be helpful should the unlikely event ever happen.

We do this often, and not always about possible catastrophes. By fabricating possible future experiences, we have memories that we can call on to navigate our lives and fall back on to guide our behavior in the future.

Wandering Is the Brain’s Default

One of the most meaningful developments in recent neuroscience is the serendipitous discovery of the brain network that hosts our mind wandering: substantial cortical regions clustered together in the brain’s “ default mode network .”

Wandering is what our brain does by default. So, logic dictates that if our brains dedicate so much energy to mind wandering, mind wandering should play an important role.

There is a trade-off, though. With all the benefits of creative thinking , planning, decision-making , and mood, mind wandering takes us away from the present. Evolution seems to have prioritized our ability to survive and flourish over our ability to cherish the moment.

I remember having lunch at a cafe in Tel Aviv with a visiting professor from Stanford. I greatly admire his work and his personality . At one point in our conversation, he told me he had once heard something that had completely changed him, how he thinks, and how he lives his life, and he wanted to share it with me.

I have no idea what it was. Despite his dramatic introduction, my mind drifted far away as he spoke. I was too embarrassed to tell him I hadn’t caught what he’d said once I realized what had happened. I can only imagine how odd he must have thought it was that I didn’t comment meaningfully on what he’d said but quickly changed the subject.

Happily, though, I can report that my mind had wandered to something interesting in my own life. Perverse as our mind wandering can be, at least it generally does have a purpose.

Put a Wandering Mind to Use

Most of what we do regularly involves some creation or production, from making food to fixing a leaky shower, from writing a letter to gardening. Even thinking is an act of creation. New ideas, inventions, and plans you make while your mind wanders are all products your mind created.

While we cannot direct our mind as to what to wander about, we can strive to fill the mental space of possibilities with what we would have liked to wander about, either because we seek new ideas, because it makes us feel good, or both.

Before I go on a long walk or do any other activity that is not overly demanding, I ask myself what is on my mind. If it is something like the bills I just paid or an annoying email, I try to replace it with something I’d rather spend my mind-wandering stretch on instead.

I might reread a paragraph that caught my interest recently. Or I might bring back a problem that engaged me before I gave up on it or warm up the idea of an upcoming trip so I can fine-tune the details as I simulate the future with my mind.

This post was adapted from M indwandering: How Your Constant Mental Drift Can Improve Your Mood and Boost Your Creativity by Moshe Bar, Ph.D.

1. Killingsworth, M. R., & Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science, 330(6006), 932. https://doi.org/10.1126/science.1192439

Moshe Bar, Ph.D. , is a cognitive neuroscientist and the former Director of the Cognitive Neuroscience Lab at Harvard Medical School and the Massachusetts General Hospital.

• Find a Therapist
• Find a Treatment Center
• Find a Psychiatrist
• Find a Support Group
• Find Teletherapy
• United States
• Brooklyn, NY
• Chicago, IL
• Houston, TX
• Los Angeles, CA
• New York, NY
• Portland, OR
• San Diego, CA
• San Francisco, CA
• Seattle, WA
• Washington, DC
• Asperger's
• Bipolar Disorder
• Chronic Pain
• Eating Disorders
• Passive Aggression
• Personality
• Goal Setting
• Positive Psychology
• Stopping Smoking
• Low Sexual Desire
• Relationships
• Child Development
• Therapy Center NEW
• Diagnosis Dictionary
• Types of Therapy

Understanding what emotional intelligence looks like and the steps needed to improve it could light a path to a more emotionally adept world.

• Coronavirus Disease 2019
• Affective Forecasting
• Neuroscience

• Conjugation
• Pronunciation

THE BEST SPANISH-ENGLISH DICTIONARY

Get more than a translation, written by experts, translate with confidence, spanish and english example sentences, examples for everything, regional translations, say it like a local.

Making educational experiences better for everyone.

Immersive learning for 25 languages

Marketplace for millions of educator-created resources

Fast, easy, reliable language certification

Fun educational games for kids

Comprehensive K-12 personalized learning

Trusted tutors for 300+ subjects

35,000+ worksheets, games, and lesson plans

Adaptive learning for English vocabulary