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Langer's theory of mindfulness proposes that a mindful person seeks out and produces novelty, is attentive to context, and is flexible in thought and behavior. In three independent studies, the factor structure of the Langer Mindfulness/Mindlessness Scale was examined. Confirmatory factor analysis failed to replicate the four-factor model and a subsequent exploratory factor analysis revealed the presence of a two-factor (mindfulness and mindlessness) solution. Study 2 demonstrated that the two factors assessed discrete constructs and were not merely products of acquiescence. Support was also found for a nine-item, one-factor model comprised solely of mindfulness items. On comparing models, Study 3 suggested the superiority of the one-factor mindfulness model. Finally, a preliminary investigation of the concurrent validity of the revised nine-item Langer Mindfulness/Mindlessness Scale is presented. The current article offers researchers a revised version of a mindfulness measure derived from a cognitive perspective.
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DOI: 10.1177/1073191110386342
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Emily A. P. Haigh, Michael T. Moore, Todd B. Kashdan and David M. Fresco
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Examination of the Factor Structure and Concurrent Validity of the Langer Mindfulness/Mindlessness
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DOI: 10.1177/1073191110386342
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Mindfulness is perhaps most widely regarded as a secular-
ized adaptation of Eastern Buddhist tradition. As a
construct, mindfulness is commonly defined as moment-to-
moment awareness without judgment (Thera, 1962) or
“paying attention in a particular way: on purpose, in the
present moment, and nonjudgmentally” (Kabat-Zinn, 1994,
p. 4). Growing interest in mindfulness as a way to enhance
medical and psychological theories and treatment has led to
several attempts to operationalize and measure mindfulness
based on an Eastern Buddhistic perspective. The measures
include the Freiburg Mindfulness Inventory (FMI 30-item;
Buchheld, Grossman, & Walach, 2001; FMI 14-item;
Walach, Buchheld, Buttenmüller, Kleinknecht, & Schmidt,
2006), the Mindfulness Attention and Awareness Scale
(MAAS; Brown & Ryan, 2003), the Kentucky Inventory of
Mindfulness Skills (KIMS; Baer, Smith, & Allen, 2004),
the Toronto Mindfulness Scale (TMS state version; Lau
et al., 2006; TMS trait version; Davis, Lau, & Cairns, 2009),
the Five Facet Mindfulness Questionnaire (FFMQ; Baer,
Smith, Hopkins, Krietemeyer, & Toney, 2006), the Cogni-
tive and Affective Mindfulness Scale–Revised (CAMS-R;
Feldman, Hayes, Kumar, Greeson, & Laurenceau, 2007),
the Southampton Mindfulness Questionnaire (SMQ;
Chadwick et al., 2008), and the Philadelphia Mindfulness
Questionnaire (PMQ; Cardaciotto, Herbert, Forman, Moitra,
& Farrow, 2008).
Although there is likely considerable overlap among the
aforementioned measures because of their shared Eastern
lineage, each measure is somewhat unique in terms of how
mindfulness is conceptualized and which dimensions are
emphasized. The MAAS, a unidimensional scale, purports
to measure attention and awareness to present moment
experiences. Similarly, the CAMS, FMI, and SMQ are all
single-factor scales; however, they aim to capture other
dimensions of mindfulness such as acceptance/nonjudgment,
openness to negative experiences, and letting go. Several
scales have been developed to measure components of
mindfulness as separable factors. The PMQ was designed to
assess present-moment awareness and acceptance as two
distinct factors. Both the state and trait versions of the TMS
were designed to reflect a two-component model of mind-
fulness (Bishop et al., 2004) and are composed of two
factors: curiosity and decentering. The four-factor KIMS
386342ASMnt18110.1177/1073
191110386342Haigh et al.Assessment
© The Author(s) 2011
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1Kent State University, Kent, OH, USA
2University of Pennsylvania, Philadelphia, PA, USA
3George Mason University, Fairfax, VA, USA
Corresponding Author:
Emily A. P. Haigh, Psychopathology Research Unit, Department of
Psychiatry, University of Pennsylvania, 3535 Market Street, Room 2056,
Philadelphia, PA 19104, USA
Email: ehaigh@mail.med.upenn.edu
Examination of the Factor Structure and
Concurrent Validity of the Langer
Mindfulness/Mindlessness Scale
Emily A. P. Haigh1,2, Michael T. Moore1, Todd B. Kashdan3,
and David M. Fresco1
Abstract
Langer’s theory of mindfulness proposes that a mindful person seeks out and produces novelty, is attentive to context, and
is flexible in thought and behavior. In three independent studies, the factor structure of the Langer Mindfulness/Mindlessness
Scale was examined. Confirmatory factor analysis failed to replicate the four-factor model and a subsequent exploratory
factor analysis revealed the presence of a two-factor (mindfulness and mindlessness) solution. Study 2 demonstrated that
the two factors assessed discrete constructs and were not merely products of acquiescence. Support was also found
for a nine-item, one-factor model comprised solely of mindfulness items. On comparing models, Study 3 suggested the
superiority of the one-factor mindfulness model. Finally, a preliminary investigation of the concurrent validity of the revised
nine-item Langer Mindfulness/Mindlessness Scale is presented. The current article offers researchers a revised version of a
mindfulness measure derived from a cognitive perspective.
Keywords
mindfulness, Ellen Langer, factor structure, self-report, concurrent validity
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12 Assessment 18(1)
(Observe, Describe, Act with Awareness, and Accept without
Judgment) is largely based the mindfulness skills taught in
Dialectical Behavior Therapy (Linehan, 1993). The five-
factor FFMQ (Nonreactivity, Observing, Acting with
Awareness, Describing, and Nonjudging) was derived from
112 pooled items from the MAAS, FMI, KIMS, CAMS-R,
and SMQ.
Mindfulness from a purely Western psychological per-
spective has a relatively young history as a construct pio-
neered by Ellen Langer (1989). Langer’s conceptualization
of mindfulness, which was conceived entirely within a cog-
nitive information-processing framework, is defined
[A]s a general style or mode of functioning through
which the individual actively engages in reconstruct-
ing the environment through creating new categories
or distinctions, thus directing attention to new con-
textual cures that may be consciously controlled or
manipulated as appropriate. (Langer, 1989, p. 4)
This definition reflects four interrelated components that
characterize Langer’s (1989) conceptualization of mindful-
ness (a) novelty seeking (b) engagement (c) novelty pro-
ducing, and (d) flexibility.
Novelty Seeking and Engagement are components of
Langer’s conceptualization of mindfulness that refer to
one’s orientation to their environment (Bodner & Langer,
2001). Novelty Seeking involves the tendency to have an
open and curious orientation to one’s environment. Novelty
Seeking is facilitated by and contributes to Engagement or
an individual’s propensity to interact and actively attend
to changes in the environment. Novelty Producing and
Flexibility are components of mindfulness that refer to how
one operates in one’s environment (Bodner & Langer,
2001). An individual with a propensity toward Novelty
Producing actively creates new categories rather than rely-
ing on previously constructed categories and distinctions
(Langer, 1989). Flexibility refers to a mindful person’s
ability to view his or her experiences from multiple per-
spectives and to use feedback from the environment to make
any necessary adaptations to his or her behavior.
Langer’s conceptualization of mindfulness grew out of
her work examining mindlessness, described as follows:
“When in a mindless state, an individual operates much like
a robot; thoughts, emotions, and behaviors (hereafter just
behaviors) are determined by ‘programmed’ routines based
on distinctions and associations learned in the past” (Bodner
& Langer, 2001, p. 1). Langer theorizes that mindlessness is
often a consequence of premature cognitive commitments
or the tendency to apply previously formed mindsets to cur-
rent situations, which lock individuals into a repetitive
unelaborated approach to daily life. Langer states that the
most significant effect of mindlessness is the role it plays in
stunting our creativity and overall potential. “Mindlessness,
as it diminishes our self-image, narrows our choices, and
weds us to single-minded attitudes, has a lot to do with this
wasted potential.” (Langer, 1989, p. 55).
Despite Langer’s acknowledgment that both Eastern and
Western conceptualizations of mindfulness appear to share
“strikingly similar” qualities, she wrote that, “not being
fully trained in Eastern thought, I leave it to others to tease
out the similarities and differences between the two con-
cepts of mindfulness” (Langer, 1989, p. 79). The degree to
which Langer’s conceptualization of mindfulness maps
onto Eastern conceptualizations of mindfulness remains an
empirical question; the answer to which relies on our ability
to measure Langer’s mindfulness construct.
Langer’s Mindfulness/Mindlessness Scale
Over the past 25 years, tenants of Langer’s theory of mind-
fulness have been examined by employing novel research
paradigms designed to elicit mindful processing. More
recently, Langer developed the Mindfulness/Mindlessness
scale (MMS; Bodner & Langer, 2001), a rationally derived,
21-item 4-factor (Novelty Seeking, Engagement, Flexibility,
and Novelty Producing), self-report questionnaire. Bodner
and Langer (2001) examined the factor structure of the
MMS in a pooled sample of 952 undergraduate students and
community members. An initial confirmatory factor analy-
sis (CFA) confirmed that all items related positively to a
single factor (Cronbach’s α = .28-.69). The authors reported
two fit indices, the goodness-of-fit index (GFI = .95) and the
root mean square of approximation (RMSEA = .07), indicat-
ing adequate fit of a single factor to the data. Next, a CFA
was conducted to examine whether the four-factor theoreti-
cal model fit the data, which resulted in the following fit
indices: GFI = .97 and RMSEA = .057. Finally, the results
of a second-order single-factor CFA provided further evi-
dence of a single dominant factor underlying the 21 items
and 4 indicator domains (GFI = .998, RMSEA = .031).
Cronbach’s alpha for the pooled covariance matrix for the
single factor was .85. The Cronbach’s alpha for the
Flexibility, Novelty Producing, Engagement, and Novelty
Seeking scales were .54, .83, .63, and .74, respectively
(Bodner & Langer, 2001).
In the same study, Bodner and Langer (2001) demon-
strated construct validity through concurrent associations
with theoretically related constructs. Specifically, the MMS
was shown to correlate positively with the ability to view
situations from multiple perspectives, liberal thinking style,
openness to experience, need for cognition, and general
cognitive ability. Last, the MMS showed a negative correla-
tion with the need for structure.
Although Bodner and Langer (2001) presented data sug-
gesting a good fit between the model and the data, two of
the four indicator scales, flexibility and engagement, dem-
onstrated inadequate internal consistency of .54 and .63,
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Haigh et al. 13
respectively. In addition, we are aware of only one study
that provided convergent validity by demonstrating that the
MMS was associated with the MAAS, an eastern measure
of mindfulness (Brown &Ryan, 2003). Bodner and Langer
(2001) acknowledged that additional validation was war-
ranted; however, to our knowledge, the MMS has not been
the focus of any additional psychometric studies.
The primary aim of this set of studies was to provide psy-
chometric validation for the MMS (Bodner & Langer, 2001)
given its importance as the only measure developed to reflect
a Western cognitive theory of mindfulness. Study 1 sought
to validate the factor structure of the MMS by providing evi-
dence for a robust and replicable factor structure in an inde-
pendent sample. Study 2, sought to address the issues with
the factor structure evaluated in Study 1 by examining two
revised models in a new sample. Study 3, sought to establish
the stability and overall superiority of one of the two remain-
ing revised MMS models in two new samples.
The secondary aim of this set of studies was to examine
the convergent and discriminant validity of the MMS.
Insofar as research has shown associations between Eastern
conceptualizations of mindfulness and select clinically ori-
ented variables, Study 2 and 3 sought to examine the MMS
in relation to affect, depression, anxiety, worry, and rumi-
native brooding, curiosity, and emotion regulation (Baer
et al., 2004; Brown & Ryan, 2003; Hayes & Feldman,
2004). Predictions regarding how the MMS is expected to
relate to the selected constructs are discussed in more detail
in the introduction sections of Studies 2 and 3.
Study 1
Given the initial validation of the factor structure of the
MMS (Bodner & Langer, 2001), the primary goal of the
Study 1 was to validate this structure in an independent
sample. It was hypothesized that the factor structure of the
MMS would be replicated in the current sample.
Method
As part of a larger research study, university undergradu-
ates (N = 582; 401 women; 181 men; mean age = 19.06
years, SD = 3.5) were recruited from general psychology
classes to participate in a questionnaire session to fulfill a
class requirement. The sample was 89.1% Caucasian, 4.3%
African American, 0.7% Asian American, 0.8% Hispanic,
1.7% other, and 3.6% missing. Each participant provided
demographic information and completed the MMS (Bodner &
Langer, 2001).
Measures
Mindfulness. The MMS (Bodner & Langer, 2001) is a
21-item, 4-factor (Novelty Seeking, Novelty Producing,
Engagement, and Flexibility) self-report questionnaire that
assesses an individual’s tendency to be mindful. Mindfulness
is assessed using a 7-point Likert-type scale, ranging from
1 = strongly disagree to 7 = strongly disagree with 8 reverse-
scored items. The MMS is scored such that higher total scores
correspond with an increased propensity to be mindful. Cron-
bach’s alpha for the MMS total score was .81 whereas
Cronbach’s alpha for the flexibility, novelty producing,
engagement, and novelty seeking scales were .47, 63, .52,
and .65 respectively. Item-level means and standard devia-
tions for the MMS for each sample are presented in Table 1.
Data Analysis
Examination of the data set revealed that 91.72% of the par-
ticipants’ responses had no missing data points. To permit
inclusion of data from all participants in the CFA proce-
dures, missing values were imputed using an expectation-
maximization (EM) imputation algorithm. EM imputation
has been found to yield better estimates of missing data
points than many other commonly used procedures (e.g.,
mean imputation, regression imputation; Bentler, 2004),
leading to more accurate standard errors. EM imputation
was also used in Studies 2 and 3 where 85.52% to 91.87% of
the participants’ responses had no missing data points.
The results of the initial CFA analyses are presented in
Table 2. Mardia’s statistic (average value of 89.22 in the
model being tested) indicated significant violations of the
assumptions of normally distributed data in structural equa-
tion modeling (Satorra & Bentler, 1994) as was the case with
all of the models examined in Studies 2 and 3. Therefore, all
structural models were refit using robust variances to obtain
Satorra–Bentler scaled fit indices, which are corrected fit
indices used to more accurately calculate the significance of
a model employing nonnormal data (Satorra & Bentler,
1994). Chi-square is the most widely used summary statistic
for examining the adequacy of a structural equation model,
however, it is likely to overestimate the lack of fit, especially
when the sample size is large (Bollen, 1989). In response to
problems interpreting chi-square, Hu and Bentler (1999)
highlight various fit indices that have been developed to
complement the chi-square statistic to demonstrate converg-
ing evidence that the model fits the data well. For the
Comparative Fit Index (CFI; Bentler, 1990), values between
the ranges of .90 and .95 are considered acceptable and
greater than .95 are considered indicative of good fit (Hu &
Bentler, 1999). In addition, RMSEA values “close to 0.06”
(Hu & Bentler, 1999, p. 1) and standardized root mean
squared residual (SRMR) values “close to 0.08” (Hu &
Bentler, 1999, p. 1) are considered to reflect adequate model
fit. When reporting RMSEA, the common convention is to
report the 90% confidence interval (CI), or the values
between which 90% of all estimates of the RMSEA are
likely to fall. The final fit index considered in the current
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14 Assessment 18(1)
study is the CMIN/df statistic, a modification of the χ2 statis-
tic intended to reduce the tendency for χ2 to be conflated
by large sample sizes (Bollen, 1989). The CMIN/df is
calculated simply by dividing χ2 by the degrees of freedom
for the overall model. Values of CMIN/df less than 3 to 4 are
considered to reflect a good fit of the model to the data.
Table 2. Goodness-of-Fit Indices of Models for the Mindfulness/Mindlessness Scale (Study 1, Sample 1, N = 582; Study 2, Sample 2, N = 457)
Model χ2df CMIN/df CFI SRMR RMSEA 90% CI on RMSEA
Study 1, Sample 1
Mindfulness/Mindlessness Scale 948.70*** 183 5.18 .64 .12 .085 0.08-0.09
Study 2, Sample 2
Mindfulness/Mindlessness Scale two-factor 260.80*** 103 2.53 .90 .06 .06 0.05-0.07
Mindfulness/Mindlessness Scale two-factor
(with post hoc modifications)
107.41*** 63 1.70 .96 .04 .04 0.03-0.05
Difference between two-factor models 153.39*** 40
Methods model two-factors 238.95*** 99 2.41 .91 .05 .06 0.05-0.07
Methods model two-factors (with post hoc
modifications)
102.79*** 60 1.71 .96 .04 .04 0.03-0.05
Methods model one-factor 288.13*** 64 4.5 .81 .09 .09 0.08-0.10
Mindfulness/Mindlessness Scale one-factor 55.65*** 26 2.14 .97 .04 .05 0.03-0.07
Difference between two-factor model and
one-factor model
51.76*** 37
Note: CMIN/df = final fit index; CFI = comparative fit index; SRMR = standardized root mean squared residual; RMSEA = root mean square error of
approximation; CI = confidence interval. All values are rounded to two decimal places. Values >.90 for the CFI indicate a reasonable fit, whereas those >.95
suggests a good fit. Values <.05 for the RMSEA indicate a good fit, and values between .05 and .08 for the RMSEA indicate a reasonable fit. Values .08
for the SRMR indicate a good fit (Hu & Bentler, 1999).
*p < .01. **p < .05.
Table 1. Mindfulness/Mindlessness Scale (MMS) Means and Standard Deviations
Mean (SD)
Item Study 1, Sample 1 Study 2, Sample 1 Study 3, Sample 1 Time 1 Study 3, Sample 1 Time 2 Study 3, Sample 2
MMS 1 5.23 (1.37) 5.04 (1.36) 5.26 (1.26) 5.37 (1.36) 5.14 (1.38)
MMS 2a3.60 (1.54) 4.10 (1.35) 3.60 (1.52) 3.48 (1.61) 3.38 (1.50)
MMS 3 5.11 (1.42) 5.12 (1.16) 5.0 9 (1.43) 5.27 (1.17) 4.91 (1.43)
MMS 4 4.89 (1.42) 4.89 (1.23) 4.63 (1.32) 4.83 (1.32) 4.81 (1.35)
MMS 5a2.99 (1.48) 4.66 (1.33) 2.43 (1.47) 2.42 (1.37) 2.69 (1.52)
MMS 6 4.05 (1.43) 4.27 (1.23) 4.26 (1.34) 4.49 (1.41) 4.47 (1.34)
MMS 7a3.76 (1.46) 4.16 (1.30) 3.5 (1.49) 3.64 (1.47) 3.81 (1.47)
MMS 8a2.79 (1.53) 4.72 (1.34) 2.37 (1.41) 2.64 (1.43) 2.56 (1.48)
MMS 9a2.48 (1.45) 4.78 (1.47) 2.29 (1.54) 2.36 (1.36) 2.42 (1.49)
MMS 10 5.28 (1.45) 4.91 (1.43) 5.06 (1.51) 5.17 (1.64) 5.20 (1.57)
MMS 11 5.48 (1.29) 4.93 (1.23) 5.47 (1.22) 5.31 (1.40) 5.44 (1.32)
MMS 12 5.07 (1.22) 4.8813 (1.14) 5.08 (1.26) 5.13 (1.33) 4.85 (1.36)
MMS 13 5.68 (1.16) 5.2677 (1.23) 5.40 (1.17) 5.48 (1.29) 5.58 (1.25)
MMS 14 5.06 (1.27) 4.9361 (1.29) 4.88 (1.34) 5.01 (1.20) 4.96 (1.28)
MMS 15a2.63 (1.41) 4.6498 (1.36) 2.30 (1.27) 2.37 (1.24) 2.49 (1.35)
MMS 16 4.77 (1.54) 4.6791 (1.40) 4.78 (1.68) 4.89 (1.52) 4.70 (1.74)
MMS 17 4.76 (1.45) 4.7070 (1.33) 5.43 (1.42) 5.45 (1.27) 4.97 (1.57)
MMS 18 4.58 (1.39) 4.5771 (1.21) 4.43 (1.38) 4.76 (1.33) 4.55 (1.38)
MMS 19a3.01 (1.41) 4.4746 (1.30) 2.57 (1.25) 2.60 (1.23) 2.60 (1.36)
MMS 20 4.77 (1.58) 4.8190 (1.37) 5.05 (1.49) 5.21 (1.33) 5.06 (1.48)
MMS 21a2.84 (1.49) 4.6762 (1.40) 2.86 (1.50) 2.63 (1.47) 2.65 (1.51)
a These items should be reverse scored.
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Haigh et al. 15
Results
The four-factor model proposed by Bodner and Langer (2001)
yielded a significant chi-square statistic, χ2(183) = 948.70,
p = .000, which was indicative of poor fit. Based on addi-
tional cut off guidelines suggested by Hu and Bentler
(1999), the original four-factor model demonstrated a poor
fit to the data, χ2(183) = 948.70, p = .000; CMIN/df = 5.18;
CFI = .64; SRMR = .12; RMSEA = .09; 90% CI on
RMSEA = .08-.09). An attempt was made to improve the
fit of the original four-factor model via the use of modifica-
tion indices supplemented by relevant theory (e.g., items
deemed particularly representative of the underlying con-
struct would not be deleted). However, it became clear that
simple, theory-guided alterations of this model would be
insufficient to adequately improve model fit. As a result, an
exploratory factor analysis (EFA) using maximum likeli-
hood estimation with oblique rotation1 was performed.
Examination of the scree plot and eigenvalues suggested
the presence of two underlying factors. A second EFA was
therefore conducted, with the additional constraint that only
two factors be extracted. Individual items were considered
to load on a factor if the factor loading exceeded .40 and
if the difference in factor loadings between factors was
greater than .20 (Gorsuch, 1983). Factor loadings for all
items are shown in Table 3. Factor 1, with an eigenvalue
4.83 representing 23% of the variance, consisted of 11
positively worded items and was labeled Mindfulness.
Inspection of the content of the items comprising the
Mindfulness factor indicated that it adequately represented
the various facets of Bodner and Langer’s concept of mind-
fulness: engagement with the world, flexibility, and seek-
ing out and creating novel experiences. Factor 2, with an
eigenvalue of 2.25 representing 10.72% of the variance,
consisted of five reverse-worded items and was labeled
Mindlessness. Inspection of the content of the items com-
prising the Mindlessness factor indicated that it represented
a lack of awareness of the world and avoidance of novelty,
mapping well onto Bodner and Langer’s concept of mind-
lessness. The remaining five items from the original pool of
21 items were dropped from further analysis because they
either failed to load on either factor or loaded equally on
both factors.
Discussion
Study 1 sought to replicate the Bodner and Langer’s (2001)
four-factor model of the MMS. The present findings failed
Table 3. Mindfulness/Mindlessness Scale (MMS) Item-Factor and Factor-Scale Loadings for Study 1, Sample 1
Study 1, Sample 1
Item Factor 1 Factor 2
Factor 1 (Mindfulness)
MMS 14: I try to think of new ways of doing things. .67 .03
MMS 18: I find it easy to create new and effective ideas. .64 .00
MMS 3: I am always open to new ways of doing things. .59 .08
MMS 13: I am very curious. .57 .01
MMS 10: I am very creative. .57 .02
MMS 20: I like to figure out how things work. .57 .03
MMS 17: I like to be challenged intellectually. .56 .08
MMS 1: I like to investigate things. .54 .07
MMS 4: I “get involved” in almost everything I do. .47 .04
MMS 12: I attend to the “big picture. .47 .02
MMS 16: I have an open mind about everything, even things that challenge my core beliefs. .44 .14
Factor 2 (Mindlessness)
MMS 15: I am rarely aware of changes. (R) .09 .69
MMS 19: I am rarely alert to new developments. (R) .02 .60
MMS 8: I seldom notice what other people are up to. (R) .14 .57
MMS 9: I avoid thought provoking conversations. (R) .13 .50
MMS 21: I am not an original thinker. (R) .22 .42
Items that do not load on either factor
MMS 2: I generate few novel ideas. .02 .26
MMS 5: I do not actively seek to learn new things. .22 .24
MMS 6: I make many novel contributions. .30 .11
MMS 7: I stay with the old tried and true ways of doing things. .16 .11
MMS 11: I can behave in many different ways for a given situation. .39 .02
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16 Assessment 18(1)
to replicate the initial four-factor model. Subsequent EFAs
suggest a two-factor model comprised of an 11-item mind-
fulness factor and five reverse-scored items reflecting a
mindlessness factor.2
Study 2
In the second study, two competing models of the factor
structure for the MMS were evaluated in a new sample.
CFAs were conducted to examine the fit of a two-factor
model comprised of a mindfulness factor and a mindless-
ness factor versus a one-factor model comprised of posi-
tively worded mindfulness items.
A secondary aim of the current study was to examine the
relationships between the MMS and self-report measures of
depression and anxiety symptoms, worry, and ruminative
brooding.
We hypothesized that that the MMS mindfulness factor
would be negatively associated with depression and anxiety
whereas the mindlessness factor would be positively associ-
ated with measures of depression and anxiety.
Ruminative brooding refers to the tendency to repeti-
tively focus on a negative event or stimulus, and negatively
affects the onset, severity, and duration of depressive symp-
toms (Nolen-Hoeksema, 1998). Langer’s characterization
of mindlessness as an inflexible reliance on previously
defined ways of thinking is likely overlaps with the ten-
dency to engage in repetitive negative thinking. In contrast,
a ruminative response style appears to be unlike Langer’s
definition of mindfulness, which involves the act of creat-
ing new categories and perceiving situations from more
than one perspective. Thus it is hypothesized that rumination
would be negatively related to mindfulness and positively
associated with mindlessness.
Worry is conceptualized to be a relatively uncontrollable
cascade of negative thoughts that usually occurs when an
uncertain issue has one or more possible negative outcomes
(Borkovec, Robinson, Pruzinsky, & DePree, 1983). A major
aspect of Langer’s conceptualization of mindfulness is a
present-tense orientation to the environment, which likely
precludes an anxious focus on the future. Therefore, it is
hypothesized that worry would be positively related to
mindlessness and unrelated to mindfulness.
Method
Participants. As part of a larger research study, a second
sample of university undergraduates (N = 457; 273 female;
182 male; 2 missing; mean age = 22.99 years, SD = 9.86)
were recruited from general psychology classes to partici-
pate in a questionnaire session to fulfill a class requirement.
The sample was 83.8% Caucasian, 11.8% African American,
0.4% Asian American, 0.4% Hispanic, 3.1% Other, and
0.4% missing. Each participant provided demographic
information and completed the MMS as well as concurrent
validity measures assessing depression and anxiety symp-
toms, worry, and depressive rumination.
Measures
Mindfulness. Participants completed the MMS (Bodner &
Langer, 2001) that was used in Study 1. In this sample,
Cronbach’s alpha for the MMS total score was .86 whereas
Cronbach’s alpha for the flexibility, novelty producing,
engagement, and novelty seeking scales were .51, .63, .60,
and .73, respectively.
Depression and anxiety symptoms. The Mood and Anxiety
Symptom Questionnaire–Short Form (MASQ-SF; Watson
& Clark, 1991) is a 62-item measure assessing symptoms
that commonly occur in the mood and anxiety disorders.
The MASQ-SF is composed of four subscales; however,
only the two subscales shown to differentiate between
symptoms of depression (anhedonic depression subscale:
AD) and anxiety (anxious arousal subscale: AA) were
included in the analyses. The AA subscale is composed of
17 items assessing anxiety-specific symptoms of somatic
tension and hyperarousal (e.g., “Startled easily”; “Was
trembling or shaking”). The AD subscale consists of 22
items assessing symptoms relatively specific to depression,
such as loss of pleasure in usual activities, disinterest, low
energy (e.g., “Felt like nothing was very enjoyable”) and
reverse-keyed items assessing positive emotional experi-
ences (e.g., “Felt cheerful”). Items are rated by how often
symptoms were experienced in the past week on a Likert-
type scale ranging from 1 (not at all) to 5 (extremely). The
MASQ–short form has demonstrated high levels of internal
consistency for each of the subscales in student samples (all
αs .78), a community sample (all αs .78), and one patient
sample (all αs .86; Watson et al., 1995). In this sample,
Cronbach’s alphas for the AA and AD subscales were .88
and .90, respectively.
The Beck Depression Inventory–II (BDI-II; Beck, Steer,
& Brown, 1996) is a 21-item self-report measure that
assesses the affective, cognitive, behavioral, and somatic
symptoms of depression as well as motivational components
and suicidal wishes. Items reflect a 2-week time period and
are rated on a 4-point scale. The BDI-II has demonstrated
good internal consistency (α = .91; Beck, Steer, Ball, &
Ranieri, 1996) and high test–retest reliability over a 1-week
period (r = .93; Beck, Steer, & Brown 1996). Cronbach’s
alpha for the BDI-II total score was .9 in the current
sample.
Worry. The Penn State Worry Questionnaire (PSWQ;
Meyer, Miller, Metzger, & Borkovec, 1990) contains 16
items rated on a 1 to 5 scale and assesses the extent to which
worry is excessive, uncontrollable, and pervasive (e.g., “My
worries overwhelm me”; “I worry all the time”). The items
are rated on a Likert-type scale, 1 being not at all typical of
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Haigh et al. 17
me, 5 being very typical of me. The PSWQ has demonstrated
good internal consistency = .93) and test–retest reliability
over periods as long as 8 to 10 weeks in a college under-
graduate population (Meyer et al., 1990). Cronbach’s alpha
for the current sample was .93.
Depressive rumination. The Response Styles Question-
naire (RSQ; Nolen-Hoeksema, 1991) is a self-report
questionnaire that assesses the individuals’ tendencies to
ruminate in response to their symptoms of negative emo-
tion. Only 25 items from the Ruminative Response Scale of
the RSQ were administered. Values range from 1 (almost
never) to 4 (almost always). The Ruminative Response
Scale consists of two factors (brooding and pondering);
however, only the brooding subscale (i.e., “Go away by
yourself and think about why you feel this way”) was ana-
lyzed in the current sample. Cronbach’s alpha for the RSQ
brooding subscale was .87.
Data Analysis
Since EFA in Study 1 suggested that a two-factor solution
fit the data, follow-up CFAs were conducted in the current
study. The first CFA examined the fit of a correlated two-
factor model with distinct mindfulness and mindlessness
first-order factors. The second analysis examined a two-
factor methods model and last, an alternative one-factor
mindfulness model was also tested.
A series of zero-order correlations and tests of dependent
correlations were computed to evaluate the relationships
between the mindfulness and mindlessness factors, anxiety,
depression, worry, and ruminative brooding.
Results
The two-factor model yielded the following fit indices:
χ2(103) = 260.80, p < .001; CMIN/df = 2.53; CFI = .90;
SRMR = .06; RMSEA = .06; 90% CI on RMSEA = .05-.07.
Both factors were significantly correlated with one another
(r = .40, p < .05). Factor loading for all items are presented
in Table 4.
Post hoc model modifications were performed in an
attempt to improve model fit. The error terms of two
items (Item 17, “I like being challenged intellectually”
and Item 20, “I like to figure out how things work”) were
allowed to correlate. This modification was made both
because of the overlapping nature of the item content and
based on recommendations to improve model fit given by
the LeGrange multiplier test. In addition, three items
(Item 16, “I have an open mind about everything, even
things that challenge my core beliefs,” Item 18, “I find it
easy to create new and effective ideas,” and Item 21,
“I am not an original thinker”) were dropped from the
model as they contributed poorly to model fit as evidenced
by the Lagrange multiplier test. Results indicated that these
items cross-loaded on both factors and so were dropped to
ensure that each item was a pure indicator of only one latent
variable.
The modified two-factor model yielded the following fit
indices: χ2(63) = 107.41, p < .001; CMIN/df = 1.70; CFI = .96;
SRMR = .04; RMSEA = .04; 90% CI on RMSEA = .08-.05
(see Table 3 for a list of factor loadings for all retained
items). Again, both factors were significantly correlated with
one another (r = .38, p < .05).
Table 4. Mindfulness/Mindlessness Scale (MMS) Item-Factor and Factor-Scale Loadings for Study 2, Sample 1
Study 2, Sample 1
Item
Two-Factor
Mindful/ Mindless
Two-Factor
Methods
One-Factor
Methods
One-Factor
Mindful
Factor 1 (Mindfulness)
MMS 1: I like to investigate things. .58 .58 .58 .58
MMS 3: I am always open to new ways of doing things. .69 .69 .68 .70
MMS 4: I “get involved” in almost everything I do. .60 .60 .60 .60
MMS 10: I am very creative. .51 .52 .51 .51
MMS 12: I attend to the “big picture. .59 .59 .58 .59
MMS 13: I am very curious. .66 .66 .66 .66
MMS 14: I try to think of new ways of doing things. .61 .62 .61 .61
MMS 17: I like to be challenged intellectually. .63 .64 .63 .63
MMS 20: I like to figure out how things work. .52 .53 .51 .53
Factor 2 (Mindlessness)
MMS 15: I am rarely aware of changes. (R) .58 .21 .27 N/A
MMS 19: I am rarely alert to new developments. (R) .57 .14 .21 N/A
MMS 8: I seldom notice what other people are up to. (R) .64 .24 .30 N/A
MMS 9: I avoid thought provoking conversations. (R) .69 .31 .37 N/A
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18 Assessment 18(1)
Finally, an alternative one-factor model, containing only
positively worded mindfulness items, was estimated. The
one-factor mindfulness model yielded the following fit
indices: χ2 [26] = 55.65, p < .001; CMIN/df = 2.14; CFI = .97;
SRMR = .04; RMSEA = .05; 90% CI on RMSEA = .03-.07.
Reliability. The internal consistency was estimated for the
mindfulness factor and the mindlessness factor. Cronbach’s
alpha for the nine-item mindfulness factor and the four-item
mindlessness factor was .83 and .72, respectively.
Relationship of mindfulness to depression and anxiety symp-
toms. As shown in Table 5, the mindfulness and mindless-
ness factors were inconsistently related to measures of mood
and repetitive thought. The mindfulness factor was signifi-
cantly and negatively correlated with anhedonic depression
as measured by the MASQ-AD; however, unrelated to
depression as measured by the BDI-II. Similarly, the mind-
lessness factor was unrelated to depression as measured by
the BDI-II; however, significantly and positively correlated
with both depression and anxiety as measured by the MASQ-
AD and MASQ-AA. A test of the dependent correlations
revealed that the mindlessness factor was significantly more
related to anxiety as measured by the MASQ-AA than the
mindfulness factor, although this finding falls below Cohen’s
(1988) conventions for a small effect size.
Relationship of mindfulness to ruminative brooding and worry.
With regard to negative repetitive thought, the mindlessness
factor was significantly correlated with ruminative brooding
and unrelated to worry, as shown in Table 5. The mindful-
ness factor was unrelated to worry or ruminative brooding.
There were no significant differences between the mindful-
ness factor and the mindlessness factor in their relationships
with ruminative brooding and worry.
Discussion
The primary goal of Study 2 was to compare two compet-
ing models underlying the mindfulness/mindlessness scale.
The initial mindfulness/mindlessness two-factor model
failed to fit the data; however, with post hoc modifications,
based on statistical diagnostics and relevant theory, the
model fit the data well. Finally, a CFA of an alternative
one-factor model comprising positively worded mindful-
ness items was conducted. The model fit the data well and
had comparable fit to the two-factor mindfulness/mind-
lessness model. To determine which model is superior,
past research suggests examining both the chi-square dif-
ference test and the CFI for nested models (Cheung &
Rensvold, 2002). The chi-square difference test indicated
a significant difference between the two-factor model and
one-factor model, Δχ2(37) = 51.76, p < .000. Examination
of the CFI index for each model suggests that the one-
factor model (CFI = .97) is superior to the two-factor
model (CFI = .96).
The secondary goal of Study 2 was to determine conver-
gent validity by examining the relationship of the mindful-
ness and mindlessness factors to depression, anxiety, worry,
and ruminative brooding. Mixed support was found for the
predicted relationships between mindfulness, mindlessness,
and mood. Neither the mindfulness nor mindlessness fac-
tors were correlated with depression as measured by the
BDI-II. However, the mindfulness was significantly nega-
tively related to anhedonic depression, whereas the oppo-
site pattern of association was found for the mindlessness
factor. Similarly, mindlessness was significantly related to
anxiety whereas the mindfulness factor was unrelated to
anxiety. The mindlessness factor was also significantly more
related to anxiety than the mindfulness factor, although
this finding falls below Cohen’s conventions for a small
effect size. With respect to negative repetitive thought, the
mindlessness factor was significantly and positively associ-
ated with ruminative brooding. Mindfulness was unrelated
to ruminative brooding and mindfulness factor was not
related to worry. Finally, there were no significant differ-
ences between the mindfulness factor and the mindlessness
factor in their relationships with ruminative brooding and
worry.
Table 5. Sample Means, Standard Deviations, Zero-Order Correlations, and Tests of Dependent Correlations Comparing
Mindfulness and Mindlessness Factors to Symptom Measures and Measures of Negative Thinking in Study 2
Difference a
Versus b
Variable Mean (SD) Mindfulness Factor Mindlessness Factor t(432) d
BDI 9.94 (7.91) .07 .07 0 0
MASQ-AA 25.05 (8.03) .03 .14** 1.80** .17
MASQ-AD 55.76 (10.37) .23** .17** 1.02 .10
RSQ-Brooding 9.97 (3.41) .09 .11* .35 .03
PSWQ 49.15 (12.74) .05 .07 .32 .03
Note: BDI = Beck Depression Inventory; MASQ-AA = Mood and Anxiety Symptom Questionnaire–Anxious Arousal Subscale; MASQ-AD = Mood and
Anxiety Symptom Questionnaire–Anhedonic Depression Subscale; RSQ-Brooding = Ruminative Response Scale–Brooding Subscale; PSWQ = Penn
State Worry Questionnaire. N = 435 for BDI and MASQ.
*p < .05. **p < .01.
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Haigh et al. 19
Study 3
In Study 3, the fit of a two-factor and a one-factor model
were compared in two additional samples to confirm the
stability of these models. In addition, the current study
sought to examine the relationship of the final model to
symptom measures, emotion regulation, and openness to
experience to provide supplemental validity to the model.
Various lines of research have demonstrated that the strat-
egies we employ to regulate our emotions have great impli-
cations for mental health. Gross and John (2003) have
examined two emotion regulation strategies, cognitive
reappraisal and suppression. Cognitive reappraisal occurs
before one’s emotions have become fully activated and
involves reframing emotional events to change the emo-
tional impact of the situation. Expressive suppression
involves restraining emotional behavior that is currently
underway. Greater use of reappraisal is associated with
more positive and less negative emotions whereas the
inverse is true for suppression (Gross & John, 2003). The
executions of these emotion regulation strategies are theo-
rized to occur automatically without much conscious delib-
eration or awareness. It is likely that individuals with a
greater propensity to be mindful are more likely to use
reappraisal to disengage from negative thinking patterns.
In contrast, mindlessness is likely to be associated with
suppression insofar as suppression reflects a divide
between what one is feeling and what one actually expresses.
As such, it was hypothesized that the propensity to be
mindful as conceptualized by Langer (1989) would be posi-
tively related to reappraisal and negatively related to the
suppression.
The Curiosity and Exploration Inventory (CEI; Kashdan,
Rose, & Fincham, 2004) was developed to assess two sepa-
rate components of curiosity. The first component, explora-
tion, refers to the propensity to actively orient and pursue
novel and challenging experiences. The second component,
absorption, refers to one’s engagement and investigative
manipulation of these novel and challenging experiences.
This construct is of relevance to the current study as Langer
(1989, 1997) includes openness to experience in her model
of mindfulness. Insofar as curiosity and mindfulness share
overlapping properties, it was hypothesized that mindful-
ness would be related to the exploration and absorption sub-
scales of the CEI.
Finally, we sought to evaluate the stability of the final
model by investigating whether the model possessed struc-
tural invariance at two time points, 3 months apart. The tra-
ditional, test–retest correlation is useful for identifying mean
change in a variable over time. In the context of a latent vari-
able framework, a correlation would not be able to detect if
the relationships between the indicators that compose a fac-
tor, change over time. It is for this reason that we have sup-
plemented the traditional test–retest indicator of temporal
stability with a latent variable modeling approach that is
consistent with the analytical approach used throughout the
manuscript.
Method
Participants. Participants were undergraduate psychology
students at a large, public, Mid-Atlantic university. Students
received research credit for participation. In Sample 1, stu-
dents completed both an initial and 3-month follow-up sur-
vey. There were 148 students at Time 1 (T1) and 145 of
them completed the 3-month follow-up survey at Time 2
(T2). The T2 sample was composed of 109 women and 36
men. The majority were Caucasian (69%), with the remain-
ing defining themselves as Hispanic/ Hispanic American
(6.3%), Asian/Asian American (5.6%), Middle Eastern
(5.6%), African American (3.5%), Mixed or Other (7.7%),
and 2.1% indicating “not applicable” or providing no
response. The mean age was 23.18 (SD = 6.08).
In Sample 2, we recruited 306 undergraduate students
(201 women, 105 men) enrolled in psychology courses at a
medium-sized, public, Mid-Western university. Students
received research credit for completing an initial survey.
The majority of participants were Caucasian (94%), with a
mean age of 21.16 years (SD = 2.78).
Procedure. In Samples 1 and 2, participants completed a
confidential Internet-based survey (no personally identify-
ing information). In Sample 1, students also received an
email approximately 3 months after completing the initial
survey at T1 with a web link to complete the follow-up sur-
vey at T2.
Measures
Mindfulness. Participants completed the MMS (Bodner &
Langer, 2001) that was used in Studies 1 and 2. For Sample 1,
Cronbach’s alpha for the MMS total score was .84 whereas
Cronbach’s alphas for the flexibility, novelty producing,
engagement, and novelty seeking scales were .45, 77, .46,
and .66, respectively. For Sample 2, Cronbach’s alpha for
the MMS total score was .83 while Cronbach’s alpha for
the flexibility, novelty producing, engagement, and novelty
seeking scales were .53, 72, .56, and .70, respectively.
Affect. The Positive and Negative Affect Schedule
(PANAS; Watson, Clark, & Tellegen, 1988) is a 20-item
questionnaire that assesses two orthogonal dimensions of
mood: positive and negative affect. Respondents indicate
the extent to which they have felt different feelings and
emotions during the past few weeks using a 5-point Likert-
type scale (ranging from very slightly or not at all to
extremely). This measure has adequate internal consistency;
coefficients alpha for the two scales are as follows: positive
affect = .87; negative affect = .87. Both scales have shown
evidence of internal and external validity as well (Watson
et al., 1988). Cronbach’s alphas for the positive and nega-
tive affect scales were .78 and .77, respectively.
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20 Assessment 18(1)
Curiosity. The CEI (Kashdan et al., 2004) measures curi-
osity, conceptualized as a positive emotional–motivational
system of cognitions that identifies, seeks out, and regulates
novel and challenging opportunities. The scale was designed
to assess the exploration or appetitive motivation and
absorption theorized to reflect flow-like engagement, both
components of curiosity. Studies have shown the explora-
tion and absorption subscales have alpha coefficients that
range from .72 to .80 (Kashdan et al., 2004). In Study 3,
Sample 1, Cronbach’s alphas for total score and the explo-
ration and absorption scales were .67, .72 and .64, respec-
tively. A similar degree of internal consistency was found
for the CEI in Study 3, Sample 2. Cronbach’s alphas for the
total score and the exploration and absorption scales were
75, 70, and .63, respectively.
Emotion regulation. The Emotion Regulation Question-
naire (ERQ; Gross & John, 2003) is a 10-item self-report
questionnaire that assesses individual differences in the
habitual use of two emotion regulation strategies: cognitive
reappraisal and expressive suppression. The ERQ demon-
strated adequate test–retest reliability (.69) for both sub-
scales across 3 months and demonstrated good internal
consistency for cognitive reappraisal = .79) and expres-
sion suppression (α = 0.73; Gross & John, 2003). In the
current sample (Study 3, Sample 1) Cronbach’s alpha for
the reappraisal subscale was .84 and for the suppression
subscale was .74.
Data Analysis
CFA was conducted with the two competing mindfulness
models in Sample 1 (both T1 and T2) and Sample 2.
Bivariate correlations were conducted to examine the rela-
tionship between the final model and measures of affect,
emotion regulation, and openness to experience. Finally,
multigroup CFA (MGCFA) was used in Sample 1 to deter-
mine if the final model represented the data equally well at
both T1 and at T2. We sought to evaluate if the loadings of
the various items composing the mindfulness factor were
equal across time points and possessed what is known as
structural invariance (Bollen, 1989).
Finally a series of zero-order correlations and tests of
dependent correlations were computed to evaluate the rela-
tionships between the mindfulness and mindlessness factors,
positive/negative affect, curiosity, and emotion regulation.
Results
In Sample 1—T1, the one-factor mindfulness model fit the
data well, χ2(26) = 28.38, p < .001; CMIN/df = 1.09; CFI = .99;
SRMR = .05; RMSEA = .03; 90% CI on RMSEA = .00-.07.
Factor loadings for all items are shown in Table 6. The two-
factor mindfulness model also fit the data well, χ2(63) = 70.85,
p < .001; CMIN/df = 1.12; CFI = .97; SRMR = .07;
RMSEA = .03; 90% CI on RMSEA = .00-.06. Similar to the
results from Study 2, both factors were significantly correlated
with one another (r = .55, p < .05). The change in CFI index
suggests that there was a significant difference between the
models (ΔCFI = .022) indicating that the one-factor model fit
the data significantly better than the two-factor model.
In Sample 1—T2, the one-factor mindfulness model
yielded the following fit indices: χ2(26) = 27.25, p < .001;
CMIN/df = 1.05; CFI =1.0; SRMR = .05; RMSEA = .02;
90% CI on RMSEA = .00-.07. In comparison, the two-
factor mindfulness model yielded the following fit indices:
χ2(63) = 104.10, p < .001; CMIN/df = 1.65; CFI = .91;
SRMR = .08; RMSEA = .07; 90% CI on RMSEA = .05-.09.
Similar to the results from T1, both factors were signifi-
cantly correlated with one another (r = .57, p < .05). The
change in CFI index suggested that there was a significant
Table 6. Goodness-of-Fit Indices of Models for the Mindfulness/Mindlessness Scale for Study 3, Sample 1, Time 1 (T1) and Time 2
(T2) and Sample 2
Model χ2df CMIN/df CFI ΔCFI SRMR RMSEA
Study 3–Sample 1
T1 MMS 1-Factor (N = 143) 28.38 26 1.09 .99 .05 .03
T1 MMS 2-Factor (N = 143) 70.85 63 1.12 .97 .02 .07 .03
T2 MMS 1-Factor (N = 140) 27.25 26 1.05 1.0 .05 .02
T2 MMS 2-Factor (N = 140) 104.10 63 1.65 .90 .10 .08 .07
Study 3–Sample 2
MMS 1-Factor (N = 286) 48.34 26 1.86 .93 .05 .06
MMS 2-Factor (N = 286) 106.38 63 1.69 .92 .01 .07 .05
Note: CMIN/df = final fit index; CFI = comparative fit index; SRMR = standardized root mean squared residual; RMSEA = root mean square error of
approximation; CI = confidence interval. Values >.90 for the CFI indicate a reasonable fit, whereas those >.95 suggests a good fit. Values <.05 for the
RMSEA indicate a good fit, and values between .05 and .08 for the RMSEA indicate a reasonable fit. Values .08 for the SRMR indicate a good fit
(Hu & Bentler, 1999). Values less than 3 to 4 for CMIN indicates a good fit. Values >.01 for ΔCFI indicate a significant difference between the two
nested models.
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Haigh et al. 21
difference between the models (ΔCFI = .083) indicating
that the one-factor model fit the data significantly better
than the two-factor model.
In Sample 2, the one-factor mindfulness/mindlessness
model yielded the following fit indices: χ2(26) = 48.34,
p < .001; CMIN/df = 1.86; CFI = .93; SRMR = .05;
RMSEA = .06; 90% CI on RMSEA = .03-.08. Factor loadings
for all items for each CFA are shown in Table 7.
In comparison, the two-factor mindfulness/mindlessness
model yielded the following fit indices: χ2(63) = 106.38,
p < .001; CMIN/df = 1.69; CFI = .92; SRMR = .07;
RMSEA = .05; 90% CI on RMSEA = .03-.07. Consistent
with prior findings, both factors were significantly corre-
lated with one another (r = .20, p < .05).The change in CFI
index suggested that there was a small but significant differ-
ence between the models (ΔCFI = .011) indicating that the
one-factor model fit the data significantly better than the
two-factor model.
Reliability. The internal consistency was estimated for
the one-factor mindfulness model in both samples. Cronbach’s
alphas for the nine-item mindfulness factor in Sample 1–T1
and T2 were .76 and .85, respectively. In Sample 2,
Cronbach’s alpha for the nine-item mindfulness factor
was .79.
Concurrent validity. The previous analyses suggest that a
one-factor mindfulness model fit the data better than the
two-factor model and should be adopted to reflect a version
of the Langer Mindfulness scale replicable factor structure.
The current set of analyses sought to examine the relation-
ship of the one-factor mindfulness model to affect, openness,
and emotion regulation. To maximize the interpretability of
the results, the relationship of the mindlessness factor to
affect, openness, and emotion regulation was also examined.
These conceptually relevant measures were collected
concurrently to the MMS. See Table 8 for descriptive
statistics.
Relationship of Mindfulness and Mindlessness to
Affect. As shown in Table 9, the mindfulness and mindless-
ness factors were not consistently related to affect. The
mindfulness factor was positively correlated with positive
affect at T1 and T2. The mindfulness factor unrelated to
negative affect at T1; however, negatively related to nega-
tive affect at T2. The mindlessness factor was negatively
correlated with positive affect at T1 and T2. The mindless-
ness factor was unrelated to negative affect at T1; however,
it was positively correlated with negative affect at T2.
Relationship of Mindfulness and Mindlessness to
Emotion Regulation and Curiosity. As predicted, the
mindfulness factor was positively correlated with reap-
praisal; however, in contrast with predictions, the mind-
fulness factor unrelated to suppression (see Table 9).
Mindlessness was not consistently related to reappraisal
and suppression at T1 and T2. At T1, but not at T2, mind-
lessness was positively correlated with suppression. At T1,
mindlessness was negatively correlated with reappraisal;
however, it was unrelated to reappraisal at T2.
Relationship of Mindfulness and Mindlessness to
Curiosity. In line with predictions, the mindfulness factor
was positively correlated with curiosity total score, and the
exploration and absorption subscales at all time points.
Similarly, the mindlessness factor was negatively corre-
lated with the curiosity total score and the exploration sub-
scale; however, contrary to predictions, the mindlessness
factor was unrelated to the absorption subscale.
Table 7. Mindfulness/Mindlessness Scale (MMS) Item-Factor and Factor-Scale Loadings for Study 3
Sample 1, Time 1 Sample 1, Time 2 Sample 2
Item Two-Factor One-Factor Two-Factor One-Factor Two-Factor One-Factor
Factor 1 (Mindfulness)
MMS 1: I like to investigate things. .65 .65 .78 .80 .64 .64
MMS 3: I am always open to new ways of doing things. .35 .35 .65 .65 .43 .43
MMS 4: I “get involved” in almost everything I do. .50 .51 .67 .66 .43 .44
MMS 10: I am very creative. .55 .56 .43 .44 .55 .55
MMS 12: I attend to the “big picture. .19 .21 .63 .62 .46 .46
MMS 13: I am very curious. .66 .67 .64 .63 .56 .56
MMS 14: I try to think of new ways of doing things. .77 .77 .66 .64 .72 .73
MMS 17: I like to be challenged intellectually. .52 .49 .61 .61 .50 .50
MMS 20: I like to figure out how things work. .46 .47 .58 .57 .58 .57
Factor 2 (Mindlessness)
MMS 15: I am rarely aware of changes. (R) .57 .74 .81
MMS 19: I am rarely alert to new developments. (R) .63 .76 .69
MMS 8: I seldom notice what other people are up to. (R) .40 .55 .57
MMS 9: I avoid thought provoking conversations. (R) .43 .44 .38
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22 Assessment 18(1)
Structural Invariance. MGCFA was used to determine if
the one-factor model represented the data well in Sample 1
at T1 and at T2. We sought to evaluate if the loadings of the
various items composing the mindfulness factor were equal
across time points and possessed what is known as struc-
tural invariance (Bollen, 1989). Testing structural invariance
involves first estimating a model where all factor loadings
are constrained to be equal across the two groups being
compared (in this case, T1 and T2). This model is then com-
pared with one or more alternative models where the factor
loading(s) of each item is unconstrained and allowed to be
freely estimated. Differences in goodness of fit between the
constrained and the unconstrained models indicate a lack of
structural invariance, or that the item-factor loadings are
unequal across groups. Cheung and Rensvold (2002) sug-
gest that a difference in CFI (ΔCFI) greater than .01 is
indicative of an item not loading equally between groups.
Seven of nine values of ΔCFI fell below this cut-off, indi-
cating that the unifactorial mindfulness model fit both T1
and T2 equally well. Two of the nine values (Item 12,
“I attend to the ‘big picture’”; and Item 14, “I try to think of
new ways of doing things”) fell below this cut-off in our
MGCFA of time, indicating that these items did not fit both
T1 and T2 equally well. Item 12 had a factor loading of .206
Table 8. Sample Means (Standard Deviations) and Zero-Order Correlations Comparing the Mindfulness and Mindlessness Factors to
Measures of Affect, Openness to Experience, and Emotion Regulation for Study 3
Mean (SD)
Variable Sample 1, Time 1 Sample 1, Time 2 Sample 2
PANAS
Positive affect 3.25 (0.58) 3.29 (0.61)
Negative affect 2.30 (0.61) 2.16 (0.59)
CEI
Total score 32.62 (6.05) 33.72 (6.28) 32.23 (6.73)
Exploration subscale 20.03 (4.08) 20.77 (4.14) 19.38 (4.21)
Absorption subscale 13.14 (3.08) 13.96 (3.07) 13.75 (3.42)
ERQ
Reappraisal subscale 27.52 (7.00) 28.03 (7.20)
Suppression subscale 12.74 (4.89) 12.73 (5.14)
Note: PANAS = Positive and Negative Affect Schedule (Time 1, N = 145; Time 2, N = 145); CEI = Curiosity and Exploration Inventory (Time 1, N = 143;
Time 2, N = 142; Sample 2, N = 292); ERQ = Emotion Regulation Questionnaire (Time 1, N = 145; Time 2, N = 143. One-Factor Mindfulness Model
(Time 1, N = 143; Time 2, N = 135; Sample 2, N = 271).
Table 9. Zero-Order Correlations Comparing the Mindfulness and Mindlessness Factors to Measures of Affect, Openness to
Experience, and Emotion Regulation for Study 3
Sample 1, Time 1 Sample 1, Time 2 Sample 2
Variable
Mindfulness
Factor
Mindlessness
Factor
Mindfulness
Factor
Mindlessness
Factor
Mindfulness
Factor
Mindlessness
Factor
PANAS
Positive affect .36*** .29** .36*** .22**
Negative affect .01 .09 .19* .24**
CEI
Total .59*** .27** .76*** .32*** .63*** .22***
Exploration .58*** .31*** .77*** .36*** .60*** .25***
Absorption .44*** .10 .63*** .15 .55*** .11
ERQ
Reappraisal .32*** .12 .33*** .26**
Suppression .12 .24** .01 .15
Note: PANAS = Positive and Negative Affect Schedule (Time 1, N = 145; Time 2, N = 145); CEI = Curiosity and Exploration Inventory (Time 1, N = 143;
Time 2, N = 142; Sample 2, N = 292); ERQ = Emotion Regulation Questionnaire (Time 1, N = 145; Time 2, N = 143).
*p < .05. **p < .01. ***p < .001.
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Haigh et al. 23
at T1 and .621 at T2 indicating that Item 12 was more
representative of the underlying construct at T2. Item 12
had an average factor loading of .60 in three of the four cur-
rent studies. Item 14 had a factor loading of .768 at T1 and
.644 at T2 indicating that Item 4 was more representative of
the underlying construct at T1. Given that the data suggest
that Items 12 and 14 are problematic, additional CFAs were
conducted to examine the impact of removing these items
on model fit. In Sample 1–T1, a CFA without Items 12 and
14 decreased model fit. Given that factor loadings are noto-
riously variable, it is possible that the two aberrant results
are due to small sample sizes (Tabachnick & Fidell, 1996).
Discussion
The first aim of Study 3 was to compare the two-factor
and one-factor mindfulness models in two new samples.
Replication of these models indicated that the one-factor
mindfulness model revealed a superior fit to the data as
compared with the two-factor model. The second aim of
Study 3 was to establish concurrent validity for the superior
model. To maximize the interpretability of the results, we
also examined concurrent validity for the mindlessness fac-
tor. The mindfulness and mindlessness factors demonstrated
inconsistent relationships with negative affect. The mind-
fulness and mindlessness factors were positively and nega-
tively associated with positive affect respectively.
As expected, the mindfulness factor was positively asso-
ciated with curiosity, as represented by the exploration and
absorption subscales of the CEI (Kashdan et al., 2004) and
emotion regulation as measured by the reappraisal subscale
of the ERQ (Gross & John, 2003). However, in contrast
with predictions, the mindfulness factor was unrelated to
suppression. The mindlessness factor was negatively cor-
related with curiosity and exploration, however unrelated to
absorption subscale of the CEI. Furthermore, mindlessness
was not consistently related to reappraisal and suppression.
The mindlessness factor exhibited a more inconsistent pat-
tern of external correlations than the mindfulness factor.
These results provide further justification for a one-factor
model of mindfulness.
The final aim of Study 3 was to examine whether the one-
factor mindfulness model fit the data equally well across
time. Seven of the nine items comprising the mindfulness
scale demonstrated structural invariance.
General Discussion
Langer’s conceptualization of mindfulness refers to a
flexible cognitive state, which emerges from drawing novel
distinctions about situations (Carson & Langer, 2006). The
current set of studies sought to evaluate the factor structure
of the MMS, a self-report measure developed to capture
Langer’s theoretical model of mindfulness. Results failed
to replicate the proposed four-factor structure of the MMS.
A series of structural equation models in three independent
studies yielded a one-factor model of Langer’s theoretical
conceptualization of mindfulness that sampled from each
of the four original MMS subscales (novelty seeking, nov-
elty producing, engagement, and flexibility). The revised
MMS reflects a global measure of mindfulness rather than
a multifactorial scale as originally suggested by Bodner and
Langer (2001). Further scale construction is needed to
establish items that discretely assess Langer’s mindfulness
theory in a multi-faceted manner.
In addition to providing psychometric support for a
monofactorial mindfulness scale, the current studies offered
modest evidence for convergent validity. While the major-
ity of the affect-laden variables (i.e., positive/negative affect,
depression, anxiety, ruminative brooding, and worry) were
unrelated or inconsistently related to the MMS, the mind-
fulness factor was strongly related to a measure of curiosity.
This association serves as encouraging evidence of conver-
gent validity as Kashdan et al’s curiosity construct and
Langer’s conceptualization of mindfulness share overlap-
ping attributes. Specifically, Kashdan et al.’s curiosity con-
struct emphasizes a cognitive system that identifies, seeks
out, and regulates novel and challenging opportunities,
which is similar to Langer’s novelty seeking and novelty
producing components of mindfulness. Furthermore, the
results suggest that the CEI’s absorption subscale, which
refers to flow-like engagement, overlaps with Langer’s
conceptualization of engagement. These findings raise an
important question: In what way are these constructs differ-
ent from one another? Future research would benefit from
examining whether the MMS has incremental validity over
the CEI in predicting other variables.
Analyses examining convergent validity revealed that the
MMS was positively associated with reappraisal, an emotion
regulation strategy that refers to capacity to reframe emo-
tional events in order to change the emotional impact of the
situation. However, contrary to predictions, the mindfulness
factor was unrelated to suppression or the capacity to restrain
emotional behavior that is currently underway. Results indi-
cated that Langer’s conceptualization of mindfulness is gen-
erally related to affect; however, unrelated to symptoms of
depression and anxiety. This finding represents a departure
from Eastern conceptualizations of mindfulness, which have
shown stronger associations with psychological symptoms
and affect (Baer et al., 2006; Brown & Ryan, 2003). One
possible interpretation is that this differential pattern of asso-
ciations might reflect meaningful differences between
Eastern and Western conceptualizations of mindfulness.
Limitations
Although the present set of studies employed four relatively
large sample sizes, there are some notable limitations. First,
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24 Assessment 18(1)
all samples were composed of largely Caucasian college
students, which limit generalizability to other populations
and thus, necessitates replication in ethnically diverse
clinical and community samples. Second, unfortunately the
current study did not examine whether the revised version
of the MMS has similar relationships with constructs that
were shown to relate to the original scale. Third, the current
studies did not examine incremental validity to determine
how the MMS functions relative to other mindfulness
measures. Validation is an ongoing process and additional
research on the MMS is warranted.
Future Directions
Future research should be directed at examining the rela-
tionship of the MMS within the family of measures pur-
porting to measure mindfulness. Researchers have attempted
to develop an operational definition of mindfulness as con-
ceptualized by secularized adaptations of Eastern Buddhist
traditions (Bishop et al., 2004; Brown & Ryan, 2003;
Brown, Ryan, & Creswell, 2007). Brown and Ryan (2003)
defined mindfulness as a receptive attention to and aware-
ness of present events and experience. Bishop et al. (2004)
have proposed a two-component model of mindfulness that
emphasizes self-regulation of attention on immediate expe-
riences that is characterized by openness, curiosity, and
acceptance. Bishop et al. (2004) suggest that Langer’s con-
ceptualization of mindfulness differs from their conceptual-
ization in that,
Langer’s mindfulness involves the active construc-
tion of new categories and meanings when one pays
attention to the stimulus properties of primarily exter-
nal situations, while our own definition emphasizes
the inhibition of such elaborative processes as one
pays attention to primarily internal stimuli (thoughts,
feelings and sensations). (p. 6)
Indeed Langer’s conceptualization of mindfulness empha-
sizes cognitive processes operating on cues from the exter-
nal environment; however Brown and Ryan (2004) have
argued that mindfulness should not be bound to meditation
by the definitions’ emphasis on consciousness of internal
stimuli. Rather, Brown and Ryan (2004) have suggested
that mindfulness is an inherent aspect of the human condi-
tion that can be enhanced by training (i.e., meditation).
Although Langer’s theory of mindfulness clearly differs in
focus from secularized adaptations of Eastern Buddhist tra-
ditions, future research is needed to determined whether the
difference in emphasis reflect separate constructs or differ-
ent aspects of the same construct.
It is likely that researchers will gain greater insight into
the nature of mindfulness by studying how the various con-
ceptualizations of mindfulness relate to one another. To this
end, the revised version of the MMS may serve an important
function as the only measure developed to examine indi-
vidual differences in mindfulness from a Western scientific
or cognitive perspective.
Declaration of Conflicting Interests
The authors declared no conflicts of interest with respect to the
authorship and/or publication of this article.
Funding
The authors received no financial support for the research and/or
authorship of this article.
Notes
1. An oblique rotation was used because Bodner and Langer’s
(2001) conceptualization of mindfulness and mindlessness
operationalize them as opposing sides of a single dipole. As
a result, one would predict them to be negatively correlated.
However, identical results were obtained with a varimax rota-
tion. These results are available from the authors by request.
2. A key question unanswered by Study 1, is whether the two-
factor model reflects two constructs that have substantive and
distinct meaning or whether the mindlessness construct repre-
sents a methods factor or an artifact of response style. To exam-
ine whether the two factors of the Mindfulness/Mindlessness
Scale (MMS) reflected two distinct constructs or a mindfulness
factor and methods factor, we conducted a confirmatory factor
analysis (CFA) in a new sample. The methods factor was theo-
rized to represent participants responding in a fixed style to the
reverse-scored items. CFAs were conducted to examine the fit
of a two-factor model composed of a mindfulness factor and a
methods factor, where all items retained in the initial explor-
atory factor analysis model of Study 1 were allowed to load on
a mindfulness factor and reverse-scored items were allowed
to cross-load on a second, methods factor. The CFA for the
methods factor model yielded the following fit indices: χ2(99,
N = 457) = 238.95, p < .001; final fit index, CMIN/df = 2.41;
comparative fit index (CFI) = .91; standardized root mean
squared residual (SRMR) = .05; root mean square error of
approximation (RMSEA) = .06; 90% confidence interval on
RMSEA = .05-.07. The results of all method factor CFA analyses
are presented in Table 2. The same post hoc model modifications
that were applied to the two-factor mindfulness/mindlessness
model (see Study 2) were performed on this model (correlating
the error terms of Items 17 and 20 and deleting Items 16, 18,
and 21) in an attempt to develop a better fitting model. The
post hoc model modifications yielded the following fit indices:
χ2(60, N = 457) = 102.79, p < .001; CMIN/df = 1.71; CFI = .96;
SRMR = .04; RMSEA = .04; 90% CI on RMSEA = .03-.05.
Interestingly, the reverse-scored items loaded poorly on the
mindfulness factor.
There are two possible interpretations that may account for
a methods factor model with good fit, despite the fact that the
methods factor items have poor loadings on the main factor.
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Haigh et al. 25
One interpretation is that the introduction of the latent methods
factor resulted in a reduction in the loadings of the methods
factor items on the main factor. The other explanation is that
the items truly measure a construct that is distinct from the
main factor.
To determine whether the loadings on the mindfulness factor
were attenuated due to the introduction of the method factor,
a one-factor CFA, which included all of the scale items, was
conducted. The model converged after seven iterations and
yielded the following fit indices: χ2(64) = 288.13, p < .001;
CMIN = 4.50; CFI = .81; SRMR = .09; RMSEA = .09; 90%
CI on RMSEA = .08-.10. This model failed to fit the data well
suggesting that the low item loadings on the mindfulness factor
were not due to the introduction of the methods factor. Rather,
they represent a unique construct, possibly a mindlessness con-
struct, which is distinct from the mindfulness factor.
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