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Mindfulness improves verbal learning and memory
through enhanced encoding
Adam Lueke
1
&Niloufar Lueke
1
#The Psychonomic Society, Inc. 2019
Abstract
Recent research has begun to demonstrate the effectiveness of mindfulness in improving certain cognitive abilities, including
verbal learning and memory. However, no research has investigated the potential mechanism by which mindfulness may improve
verbal learning and memory. We examined encoding, consolidation, and retrieval as potential mechanisms by which learning and
memory may be increased on a list learning test (Rey Auditory Verbal Learning Task; RAVLT). After dividing participants into
either a mindfulness or a control condition, in which they listened to a 10-min audio tape, results found that the mindfulness
condition significantly outperformed the control condition on every RAVLT trial. Using the Item-Specific Deficit Approach, we
discovered that this enhanced verbal learning and memory was specifically due to a significantly enhanced encoding process for
the mindfulness group, which fully mediated the relationship between the mindfulness condition and performance on the RAVLT.
There were no differences between the conditions on consolidation or retrieval. Furthermore, these improvements were not
accompanied by improvements in verbal fluency or attention. In a second study, we presented a mindfulness or control audio
before the first RAVLT delayed free-recall trial and another one before the second RAVLT delayed free-recall trial in order to
better determine the effect of mindfulness on consolidation and retrieval. The results replicated Study 1, in that neither consol-
idation nor retrieval were significantly affected by mindfulness. This research indicates that mindfulness may primarily improve
verbal learning and memory through improved encoding processes.
Keywords Mindfulness .Learning .Memory .Encoding .Ver ba l
Introduction
Mindfulness is a state of being characterized by present-
moment awareness of the unfolding of experience in a nonre-
active way. This simple practice has been shown to have a
myriad of benefits for its practitioners, despite the science of
mindfulness being a relatively new field. Much of the early
work on mindfulness focused on its ability to improve indi-
vidual well-being through its ameliorative effects on stress,
anxiety, and depression (Baer, Carmody, & Hunsinger,
2012; Ciesla, Reilly, Dickson, Emanuel, & Updegraff, 2012;
Davidson et al., 2003; Desrosiers, Vine, Klemanski, & Nolan-
Hoeksema, 2013; Lagor, Williams, Lerner, & McClure,
2013). Furthermore, mindfulness has also been shown to be
effective in improving the healing process (Davidson et al.
2003; Kabat-Zinn et al., 1998) and helping clinical popula-
tions cope with painful medical conditions (Brown & Jones,
2013). In addition to personal well-being, mindfulness has
also been demonstrated to be an effective tool in improving
interpersonal relationships (Hopthrow, Hooper, Mahmood,
Meier, & Weger, 2017; Langer, Bashner, & Chanowitz,
1985; Lueke & Gibson, 2015,2016;Parks,Birtel,&Crisp,
2014; Pratscher, Rose, Markovitz, & Bettencourt, 2017;
Ramsey & Jones, 2015). Among all of these positive benefits
from the practice of mindfulness, there is also a burgeoning
literature on the ability of this practice to enhance cognitive
ability. The focus of the current article is to indicate a partic-
ular cognitive faculty that can be improved through brief
mindfulness training –verbal learning and memory, while also
demonstrating the mechanism by which verbal learning and
memory is improved. Concurrently, we look to rule out other
potential explanations for improved learning and memory –
namely attentional processes.
*Adam Lueke
aklueke@bsu.edu
Niloufar Lueke
nassar@bsu.edu
1
Department of Psychological Science, Ball State University,
Muncie, IN 47306, USA
Memory & Cognition
https://doi.org/10.3758/s13421-019-00947-z
Author's personal copy
Recent work with mindfulness indicates that verbal learn-
ing and memory can be positively affected by mindfulness
practice. Participants assigned to a 2-week mindfulness class
demonstrated improved ability on a reading comprehension
measure, whereas control participants did not. This effect
was particularly pronounced in individuals whose mind-
wandering significantly decreased due to the mindfulness
class (Mrazek, Franklin, Phillips, Baird, & Schooler, 2013).
Other research has also indicated that mindfulness can help
reduce mind-wandering (Killingsworth & Gilbert, 2010;Rahl,
Lindsay, Pacilio, Brown, & Creswell, 2017). While it is pos-
sible that mindfulness may help to free up cognitive resources
necessary for peak verbal learning and memory performance
that would otherwise be engaged in task-unrelated thoughts,
the avenue by which mindfulness may positively impact ver-
bal learning and memory is currently uncertain.
One potential explanation for improvements observed in
verbal learning and memory could be due to increased atten-
tion, but currently the research is mixed as to whether mind-
fulness increases attentional capabilities or not (Anderson,
Lau, Segal, & Bishop, 2007; Chambers, Lo, & Allen, 2008;
Jensen, Vangkilde, Frokjaer, & Hasselbalch, 2012; Josefsson
& Broberg, 2011;Kerretal.,2011). Indeed, recent research
has found that long-term meditators were significantly better
on a measure of verbal learning and memory compared to
non-meditators, even though they found no significant differ-
ences between the two groups in terms ofattention or attention
switching (Lykins, Baer, & Gottlob, 2012). We propose that
rather than altering attention, mindfulness may improve verbal
learning and memory via its effect on the encoding process of
learning, which allows for enhanced memory for new infor-
mation over time.
List-learning and parsing out memory process
capabilities
List-learning is a common neuropsychological device that can
help measure general verbal learning and memory capabili-
ties. Typically, these tests provide participants with several
learning trials to practice a list of words, followed by an inter-
ference trial before a free-recall trial. Another longer delay is
then presented, followed by another free-recall trial, and then a
recognition trial. For example, the Rey Auditory Verbal
Learning Test (RAVLT) has participants listen to and recall
the same list of words over five consecutive trials. With rep-
etition, it is expected that participants improve across trials.
This is then followed by a single presentation and recall test of
a new list of words, which is used as interference to the pre-
vious word list. A free-recall test of the first list that the par-
ticipants had learned is then administered immediately after
the free-recall test of the interference list, and thenagain after a
delay period of approximately 20 min. Finally, a recognition
test of the word list is administered.
List-learning measures such as the RAVLT also attempt to
make distinctions in ability regarding encoding, consolidation,
and retrieval. Previous research has shown that the RAVLT
can measure encoding, consolidation, and retrieval (Vakil &
Blachstein, 1993), and there is evidence from similar list-
learning tests that immediate recall during the five learning
trials is associated with encoding, while the two delayed-
recall trials are associated with consolidation and retrieval
(Delis et al., 1991). However, the way in which these memory
processes are distinguished with these list-learning measures
may lack precision and potentially could be confounded by
other factors, and therefore may not accurately reflect the
measurement of these processes. For instance, encoding is
generally measured as the improvement in recall across learn-
ing trials in a list-learning task (Delis, Kramer, Kaplan, &
Ober, 2000). However, this improvement may simply be due
to a lack of attention during early trials that is mitigated
through repeated practice. Thus, any improvements in recall
across trials may not accurately reflect encoding capabilities.
Likewise, consolidation is usually measured by comparing
performance on the final learning trial to performance on a
delayed free-recall trial (Delis, et al., 2000). Consolidation
difficulties are said to occur when words that were recalled
on the final learning trial are not recalled on the delayed free-
recall trial, as this indicates rapid loss of previously learned
information. However, it is certainly possible that poor perfor-
mance on the delayed free-recall trial may indicate a retrieval
rather than consolidation deficit. Similarly, retrieval is typical-
ly measured bycomparing a recognition trial to a delayed free-
recall trial, with retrieval deficits said to occur when recogni-
tion is better than delayed free-recall (Delis et al., 2000).
However, recall and recognition represent different processes
(Aggleton & Brown, 2006), which may not be ideal to com-
pare in order to adequately measure retrieval capabilities.
A relatively new approach has been developed to more
accurately distinguish and isolate encoding, consolidation,
and retrieval processes with regard to list-learning measures
such as the RAVLT –the Item-Specific Deficit Approach
(ISDA). The ISDA is a psychometrically valid means of pars-
ing out these processes that otherwise would be unable to be
measured adequately. Additionally, the ISDA was developed
in order to eliminate, or at least minimize, the confounding
effects of inattention on encoding, consolidation, and retrieval,
thus allowing a process-specific measure that is not influenced
by attentional capabilities. This feature of the ISDA can help
us identify any improvement in encoding due to mindfulness
regardless of whether or not attention is also improved.
Additionally, the ISDA measures consolidation and retrieval
in a manner that better accounts for their potential overlap and
eliminates the use of recognition trials, which may include
confounding processes (Wright et al., 2009).
The ISDA must be applied to a list-learning measure that
utilizes multiple learning trials and at least two delayed free-
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recall trials. Recognition trials are not utilized with the ISDA.
The encoding index is determined by identifying the number
of items that are not correctly recited on more than half of all
learning trials. The RAVLT has five learning trials, meaning
that an encoding error would be the inability to recall a spe-
cific word on atleast three of the learning trials. By calculating
encoding as the tendency to neglect certain words across trials,
rather than by examining the improvement of performance on
successive trials, the ISDA protects against the confounding
effects of inattention on any one trial (Wright et al., 2009).
The consolidation index is calculated by identifying the
words recalled during list learning that were not recalled on
either delayed free-recall trial. This value is then divided by
the total number of words that were recalled during list learn-
ing. For example, if someone recalled 13 out of 15 words in
total over the course of the list learning trials, but two of those
13 words were not recalled on either delayed free-recall trial,
then the consolidation index would be calculated by dividing
2 by 13. This helps control for encoding differences during list
learning. The inability to recall previously learned items
across both delayed free-recall trials indicates a deficit in con-
solidation more likely than with retrieval (Wright et al., 2009).
The retrieval index is calculated by identifying the
words recalled during list learning that were inconsistent-
ly recalled across multiple delayed free-recall trials. This
value is then divided by the total number of words that
were recalled during list learning. For example, if some-
one recalled 11 of 15 words over the course of the list
learning trials, but three of those 11 words were recalled
on only one of the two delayed free-recall trials, then the
retrieval index would be calculated by dividing 3 by 11.
This helps control for encoding differences during list
learning. Since the retrieval index identifies the inconsis-
tency of recall across multiple trials, it indicates a problem
with retrieval more likely than with consolidation (Wright
et al., 2009).
Research using the RAVLT and ISDA has shown that pa-
tients with a traumatic brain injury demonstrate deficits in
encoding and consolidation in comparison with controls
(Wright & Schmitter-Edgecombe, 2011). Likewise, research
with amyotrophic lateral sclerosis patients using these same
measures indicates impairment within the encoding and con-
solidation but not retrieval stages in comparison with controls
(Christidi, Zalonis, Smyrnis, & Evdokimidis, 2012).
Additionally, the ISDA has also revealed that HIV-positive
patients indicate impaired encoding processes in comparison
with controls, whereas HIV-positive patients who did not ad-
here well to treatment also indicated deficits in retrieval pro-
cesses (Wright et al., 2011).
If verbal learning and memory performance on the RAVLT
was better for a mindfulness group in comparison with a con-
trol group, the ISDA could determine the memory process(es)
responsible for this improvement, while also controlling for
potential differences in attention. There is reason to suspect
that the encoding process is particularly affected by a mindful
state. Recent research has indicated that mindfulness reduces
inattentional blindness (Schofield, Creswell, & Denson,
2015), which implies that people who are mindful are better
able to encode information that others may simply not see or
be aware of.
Additionally, research has shown that a primary brain re-
gion responsible for the encoding of verbal information, the
left parahippocampal gyrus (Dolan & Fletcher, 1999;
Fernandez et al., 1998; Strange et al., 2002), is more active
within people with higher dispositional mindfulness (Kong,
Wang, Song, & Liu, 2016). This overlap may indicate that the
higher activity in this region among mindful individuals con-
currently facilitates the encoding of verbal information.
Relatedly, mindfulness training has been shown to increase
volume in the left hippocampus, which reduced proactive in-
terference and thus improved memory (Greenberg et al.,
2018). Proactive interference is a major impediment to
encoding, but factors such as higher working memory capac-
ity can minimize the effects of proactive interference (Kliegl,
Pastotter, & Bauml, 2015), and thus improve encoding pro-
cesses. Mindfulness (even brief experience) has been shown
to be related to greater working memory capacity (Dubert
et al., 2016; Jha et al., 2010; Mrazek et al., 2013; Quach,
Mano, & Alexander, 2016), which in turn would minimize
proactive interference and increase encoding processes.
Other research has demonstrated that interference often takes
place specifically during the encoding process (i.e., encoding
interference; Gordon, Hendrick, & Johnson, 2001,2004;
Villata, Tabor, & Franck, 2018), which implies that large
memory gains can be achieved through an intervention that
reduces encoding interference.
Other research has reported that mindfulness improves ver-
bal memory through increased Bencoding^(Bonamo,
Legerski, & Thomas, 2015); however, the results only illus-
trated improved recall of learned verbal information, not an
actual improvement in encoding. There was no measure of the
separate memory processes, including the encoding process,
so there was no evidence to suggest that encoding specifically
was responsible for the improved verbal memory. Similarly,
research with trait mindfulness has indicated that people
higher on trait mindfulness tend to have an external
Bencoding^process (Herndon, 2008), but the measure used
(Lewicki’s Internal/External encoding styles; Lewicki, 2005)
merely measured the tendency to attend to information in the
internal or external world. It was not a measure of encoding as
a learning and memory process. Our study is the first to di-
rectly measure memory processes that are potentially en-
hanced by mindfulness and that subsequently improve verbal
learning and memory.
Our central hypothesis is that participants who engage in
mindfulness will perform significantly better on a measure of
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verbal learning and memory (the RAVLT) than control partic-
ipants, and that this improvement will be due to an enhanced
encoding memory process. This encoding process should me-
diate the relationship between the mindfulness condition and
performance on the RAVLT. This relationship would desig-
nate mindfulness as a useful tool for learning new verbal in-
formation, which would aid in future recall, and not necessar-
ily in remembering previously learned verbal information.
As mindfulness is expected to work primarily on improv-
ing encoding, we would not expect increased performance on
a measure that relied on previously learned verbal informa-
tion. For this reason, we hypothesize that mindfulness partic-
ipants will not perform better than others on a measure of
verbal fluency that relies on recall of words that begin with
specified letters (thus word-knowledge stored in long-term
memory) within a limited timeframe.
Finally, we expect improvement in verbal learning and
memory without improvements in selective attention or atten-
tion switching, which would mirror the results of Lykins,
Baer, and Gottlob (2012). This would indicate that brief mind-
fulness works to improve verbal learning and memory by
specifically enhancing encoding processes, and not due to
increases in general attention abilities. To test this hypothesis,
we included the Color-Word Interference Test (CWIT; a
Stroop-like task that measures selective attention) and the
Trail Making Test (a measure of attention switching). All tasks
used in this study are commonly used and well validated neu-
ropsychological measures.
Method
Participants
The total number of participants was 94, but four participants
were excluded due to a technical error (i.e., no condition num-
ber), and another five were excluded due to having recently
completed the neuropsychological tests used in this experi-
ment. This was necessary because naïvety is crucial for mea-
sures like the RAVLT, in which participants are supposed to be
unaware of the final delayed free-recall trial. With previous
experience taking the RAVLT, participants know to rehearse
before the final delayed free-recall trial in order to increase
performance. Additionally, since the 15 target words on the
RAVLT never change, these participants had recently memo-
rized the words that they were given in this study, thus making
them easier to relearn. Therefore, our final sample was com-
prised of 85 undergraduate university students (50 females
and 35 males; 46 mindfulness condition and 39 control con-
dition) of traditional college age who were recruited from a
large Midwestern university. The final sample size was deter-
mined by a power analysis for independent samples t-tests,
with the desire to achieve a 95% probability of detecting a
large effect (d= .80), which required approximately 35 partic-
ipants per condition.
Measures
Mindful Attention Awareness Scale (MAAS; Brown &
Ryan, 2003)
The MAAS is a measure of trait mindfulness that consists of
15 items measured on a 6-point scale (1 –Almost always, to 6
–Almost never) that asks participants about how they normal-
ly go through activities in their daily lives (e.g., BIrush
through activities without being really attentive to them^).
State Mindfulness Scale (SMS; Tanay & Bernstein, 2013)
The SMS is a measure of state mindfulness that consists of 15
items on a 5-point Likert scale (0 –Not at all, to 4 –Ve ry
much) that asks participants to rate their experiences during an
audio recording immediately preceding the scale (e.g., BItried
to pay attention to pleasant and unpleasant sensations^).
Rey Auditory-Verbal Learning Test (RAVLT; Strauss, Sherman,
&Spreen,2006)
The RAVLT measures verbal learning and memory. A 15-
noun word list (List A) was read aloud to the participant, in
a fixed order and with a 1-s interval between words, for five
consecutive trials, with recall instructions repeated at the start
of each trial. Each of the five trials was followed by a free-
recall test, for which the participant was asked to repeat as
many of the words as possible, in any order. Responses were
tracked, and feedback was not provided. Upon completion of
Trial 5 free-recall, a single presentation and free-recall test of a
second (new) list of 15 words (List B; interference list; Trial 6)
was administered. Immediately after the free-recall test of List
B, and without an additional presentation of List A, a short-
delayed recall of the first list (List A; Trial 7) was assessed.
After a 20-min delay period (with no other verbal memory
tests administered during this time interval), the long-
delayed free-recall of List A (Trial 8) was assessed, again
without an additional presentation of List A. Immediatelyafter
Trial 8, a recognition test (Trial 9) was administered by pro-
viding the participant with a matrix array of 50 words contain-
ing both List A and List B words, in addition to 20 words that
were phonemically or semantically similar to those in both
lists, and requesting the identification of List A words only.
The RAVLT is a sensitive test of verbal learning and mem-
ory (see Schoenberg et al., 2006, for a review), and provides
scores for examination of immediate memory span, new ver-
bal learning, susceptibility to interference, retention of infor-
mation after a delay, and memory recognition (Magalhães &
Hamdan, 2010; Strauss et al., 2006).
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Controlled Oral Word Association Test (COWAT; FAS version:
phonemic verbal fluency; Benton, Hamsher, & Sivan, 1994)
The FAS measures verbal fluency with the spontaneous
oral generation of words that begin with a specified letter
during a prescribed timeframe, while adhering to the fol-
lowing restrictions: no proper nouns (no names of people
or places), no numbers, and no variants of the same word
(saying the same word using a different ending).
Following the abovementioned guidelines, participants
were asked to provide as many words as possible that
begin with the letters F, A, and S, for 60 s each (thus a
total of three trials were administered, one per letter).
Performance was measured by calculating the sum of all
admissible words for the three letters, minus the errors
(e.g., proper nouns, variations, repetitions, wrong words).
A recent factor-analytic study found that the FAS loaded
exclusively onto the language factor, and not the executive
functioning factor, implicating verbal fluency as primarily a
language-processing measure (Whiteside et al., 2016). Word-
knowledge (Ruff et al., 1997; Whiteside et al., 2016)aswellas
auditory attention and long-term memory, but not short-term
memory, have also been suggested to be the most important
determinants for FAS performance (Ruff et al., 1997).
Trail Making Test (TMT; Reitan & Wolfson, 1993)
The TMT is an attention-switching measure and consists of
two parts: Part A and Part B. Part A measures the speed at
which participants sequentially connect, by making pencil
lines, 25 encircled numbers that are variously spread across
a page. Part B measures the speed at which participants con-
nect 25 encircled, and variously spread, numbers and letters in
sequential, but alternating order (i.e., 1-A-2-B-3-C and so on).
For each part, participants were instructed to draw the line as
fast as they can. If errors occurred, they would be pointed out
as per standard procedure, and error-correction would subse-
quently influence the total time taken to complete each part. A
practice trial was provided prior to the administration of each
part. While the primary variables of interest were the total time
in seconds taken to complete each of the two parts, a ratio
score (Part B/Part A) was also calculated in order to control
for general processing speed when interpreting Part B
performance.
While visual search and scanning abilities as well as speed-
ed performance are required by both parts, Part B also requires
divided attention (alteration of operations), and it is sensitive
to cognitive flexibility (Strauss et al., 2006). The derived ratio
score (Part B/Part A) is thought to serve as an index of com-
plex divided attention –in other words, the B/A ratio score is
thought to be the best indicator of attentional control processes
required for rapid alternation between two tasks (e.g.,
Arbuthnott & Frank, 2000).
Color-Word Interference Test (CWIT) from the Delis-Kaplan
Executive Function System (D-KEFS; Delis, Kaplan, & Kramer,
2001)
The CWIT is a subtest from D-KEFS, and an extension of the
classic Stroop procedure (Stroop, 1935). It is comprised of
four conditions: (1) color naming, consisting of rows of col-
ored patches (red, blue, and green) on a white surface. The
participant was asked to name the colors aloud as fast and as
accurately as possible; (2) word reading, consisting of rows of
the words Bred,^Bgreen,^and Bblue^printed in black ink on a
white surface. The participant was asked to read the words
aloud as fast and as accurately as possible; (3) inhibition,
consisting of rows of the same three words as before, but this
time the words were written in an incongruent ink color. The
participant was asked to not read the words (thus inhibit the
automaticresponseofwordreading),andinsteadsayaloud
the color of the ink in which each word was printed in (e.g.,
say Bred^when the word Bgreen^is printed in red ink) as fast
and as accurately as possible; (4) inhibition/switching,
consisting of rows of the same three words, with half of the
words enclosed within boxes. The participant was asked to
switch between naming aloud the color of the ink in which
the word was printed (same as the inhibition condition), and
actually reading the word (and not naming the ink color) if the
word was enclosed within a box, as fast and as accurately as
possible. The aim of this last condition is to measure both
inhibition and switching. Performance on this test is primarily
assessed via the total completion time in seconds for each of
the four conditions. Optional measurements include error
analysis: the total number of uncorrected and self-corrected
errors per condition.
Performance on the CWIT measures selective attention
with the integration of processing speed, inhibitory control,
and cognitive set-switching/attention shifting. Color naming
(condition 1) and word reading (condition 2) are thought to
reflect baseline low-level cognitive measures that are required
for the subsequent high-level cognitive functions (e.g., inhibi-
tion and cognitive flexibility) that are assessed in inhibition
(condition 3) and inhibition/switching (condition 4). In the
inhibition condition, the participant is presented with interfer-
ence in the form of competing responses, and their ability to
inhibit a dominant and automatic response (word reading) in
order to provide an intentional one (naming the ink color) is
assessed. In the inhibition/switching condition, the participant
is required to switch back and forth between the automatic
response (reading the word, when the word is enclosed in a
box), and the intentional response (not reading the word, but
instead naming the ink color that the word is printed in); thus it
not only measures inhibition, but also cognitive flexibility or
the ability of set switching (Delis et al., 2001).
In order to obtain pure measures of inhibition and cognitive
flexibility (Delis et al., 2001; Yu et al., 2018), lower level
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factors such as basic processing speed (as captured by condi-
tions 1 and 2) were controlled for by calculating contrast
scores: inhibition (inhibition minus color-naming completion
time), inhibition/cognitive flexibility (inhibit/switching minus
color-naming completion time), and cognitive flexibility (in-
hibit/switching minus inhibit completion time).
Procedure
All participants entered the lab and first completed the MAAS
in order to assess trait mindfulness. They were then instructed
to listen to a 10-min audiotape, which was either a mindful-
ness audio tape that directed the participant to concentrate on
their breath and bodily sensations while remaining nonjudg-
mental about their experience, or a control audio tape that
described an English countryside. These audios have been
used in previous research a number of times, and the mindful-
ness audio has been shown to reliably increase mindfulness
over the control condition (Cropley, Ussher, & Charitou,
2007;Lueke&Gibson,2016). Participants alerted the exper-
imenter when the audio had finished, and then completed the
SMS.
Participants then completed the neuropsychological tests in
the same order regardless of condition. First, they completed
the CWIT, followed by the FAS, and then the RAVLT (except
for the second-delayed recall trial and the recognition test).
Participants then completed the TMTand a filler task in order
to have enough time elapse (about 20-min) before the second
part of the RAVLT was administered (the second delayed free-
recall, followed by the recognition test). The filler task was the
Wisconsin Card Sorting task, which was chosen for its length
and relianceon nonverbal processes. The order of presentation
was determined by the need to present the audio manipulation
before all subsequent neuropsychological tests. The neuropsy-
chological tests were ordered with the primary goal of achiev-
ing approximately a 20-min delay using tasks that were not
reliant on verbal activity between the first and second delayed
free-recall RAVLT trials. The TMT was administered during
the RAVLT’s delay interval since it was a nonverbal task, as
was our filler task. The CWIT and FAS were presented before
the RAVLT so as not to bury them at the end of the experi-
ment. After all tasks were completed, participants were
debriefed and left the experiment.
Results
Preliminary results
We first investigated whether our two conditions were similar
in terms of trait mindfulness before any intervention had taken
place. An independent t-test analysis on the MAAS indicated
that the mindfulness and control conditions were not signifi-
cantly different in trait mindfulness, (t<1).
Additionally, as a manipulation check we measured
state mindfulness after the intervention to ensure that our
audio intervention did increase self-reported feelings of
mindfulness. An independent t-test analysis on the SMS
indicated that the mindfulness condition (M= 49.54, SD
= 14.34) did report significantly greater state mindfulness
than the control condition (M= 41.18, SD = 10.95), t(83) =
2.98, p= .004, d= .66.
RAVLT analyses for verbal learning and memory
We first examined our hypothesis that verbal learning and
memory would be better for individuals in the mindful-
ness condition than the control condition. In order to do
this, we performed two independent samples t-tests –one
for the combined performance on the five learning trials
and one for the combined performance on the two delayed
free-recall trials. One participant did not complete the
RAVLT so was not included. A second participant had
to leave before the second delayed free-recall could be
administered so was not included in that specific analysis
or subsequent ISDA analyses. Overall, results revealed
significant support for the hypothesis that mindfulness
improves verbal learning and memory, as the mindfulness
condition (M=53.31,SD = 7.33) performed significantly
better than the control condition (M=48.51,SD =7.20)
on the learning trials, t(82) = 3.02, p< .002, d= .66, and
delayed free-recall trials, t(81) = 2.19, p< .02, d=.48
(Mindfulness: M= 22.38, SD =4.25;Control:M= 20.26,
SD = 4.54). All individual trial comparisons were also
significant, including a recognition trial (Fig. 1).
ISDA for memory processes
In order to examine what aspect of memory may have been
enhanced in the mindfulness condition, we utilized the ISDA
to analyze encoding, consolidation, and retrieval processes.
Following the instructions of Wright et al. (2009), we used
the five learning trials to calculate encoding errors, and the
two delayed free-recall trials to calculate consolidation and
retrieval. Independent t-tests were used to determine any dif-
ferences between mindfulness and control conditions for all
three memory processes. Results indicated significantly more
encoding errors for the control group (M=4.47,SD =2.30)
than for the mindfulness group (M=3.11,SD =2.18),t(81) =
2.77, p=.004,d= .61. The consolidation index was not quite
significantly different between the groups, t(81) = 1.53, p=
.07, d= .34. The retrieval process was also not significantly
different between the groups, t(81) = 1.24, p=.11,d=.27.
Both indices trended toward being better in the mindfulness
condition.
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We then conducted a mediational analysis to determine
if the improvements in verbal learning and memory in the
mindfulness condition were due to increased encoding
capabilities. Using PROCESS macro, model 4 (Hayes,
2017), we used the audio condition as our X variable,
encoding as our M variable, and the combined delayed
free-recall trials as our Y variable. We found that the
overall model for X predicting Y was significant, F(1,
81) = 4.79, p= .032, R
2
= .06, as the mindfulness condi-
tion remembered more words on the delayed free-recall
trials, b=2.11,t(81) = 2.19, p= .032. Next, we found
a significant effect of X on M, as the overall model was
significant, F(1, 81) = 7.67, p= .007, R
2
=.09,withthe
mindfulness group showing greater encoding capabilities,
b=1.36,t(81) = 2.77, p= .007. Finally, we looked at X
and M together predicting Y. The overall model was sig-
nificant, F(2, 80) = 19.83, p< .0001, R
2
= .33. The effect
of M on Y was also significant, b= 1.06, t(80) = 5.74, p<
.0001, and the effect of X on Y was no longer significant,
b=.67,t(80) = .78, p= .44. A Sobel test confirmed that
there was a significant difference between the prediction of X
on Y based on the involvement of M, Z=2.49,p=.01.
We were unable to run the consolidation and retrieval indi-
ces as part of a multi-mediational analysis along with
encoding to determine their combined effects on the delayed
free-recall trials due to the nature of how these indices are
calculated. Both the consolidation and retrieval indices exclu-
sively utilize performance on the delayed free-recall trials to
calculate ability within these processes. Thus, it would be
inappropriate and meaningless to use these indices as a
potential mediator for performance on the delayed free-recall
trials. On the other hand, the encoding index only uses perfor-
mance on the learning trials to calculate ability on this process,
thus making it appropriate to use as a mediator for perfor-
mance on the delayed free-recall trials.
General verbal fluency
We further expected that mindfulness would not improve gen-
eral verbal ability even though it improved verbal learning and
memory. The ability of mindfulness to improve encoding
should help people learn verbal information, but this should
not affect verbal information that had already been learned
previous to the intervention, which would simply need to be
retrieved. We tested this by examining any differences be-
tween the mindfulness and control conditions in terms of per-
formance on the FAS, which measures verbal fluency through
the timed recall of words thatbegin with the letters F, A, and S.
An independent samples t-test confirmed that there was no
difference between the mindfulness and control conditions in
the number of words recalled that began with those letters,
t(83) = 1.20, p= .12 (Mindfulness: M=37.89,SD =10.27;
Control: M=35.10,SD = 11.17).
Attention
We then examined the possibility that mindfulness may im-
prove attentional capabilities. It is possible that any improve-
ments in encoding were largely derived from improvements of
attention. If there are no differences, it provides support for
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 First
Delay
Second
Delay
Recognion
5
6
7
8
9
10
11
12
13
14
Mindfulness Control
RAVLT Performance
RAVLT Trial
Words Remembered
Fig. 1 Verbal learning and memory performance for both conditions on each Rey Auditory Verbal Learning Task (RAVLT) trial. All comparisons are
significant
Mem Cogn
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our hypothesis that mindfulness improves learning and mem-
ory specifically through enhanced encoding and not necessar-
ily through increased attention.
Independent samples t-tests were used in order to ex-
amine any differences with regard to two different mea-
sures of attention: the CWIT (selective attention measure)
and the TMT (attention switching measure). We examined
several different measures available within the CWIT, in-
cluding the time it took to complete each trial, and the
number of errors that were either self-corrected or uncor-
rected by the participant. Results indicated that there were
no differences between the mindfulness and control
groups in terms of the time taken to complete any of the
four CWIT trials, or the two critical trials combined (trials
3 and 4), or the combined time among all four trials (all ts
< 1). Likewise, there were no significant differences in the
number of errors of either type (self-corrected or
uncorrected) for either critical trial or the total number
of errors from both trials (all ts < 1.17). The total number
of uncaught errors from both critical trials combined was
also not significant, t(83) = 1.40, p= .08. The total num-
ber of caught errors from both critical trials combined was
not significantly different (t< 1). Additionally, we isolat-
ed more pure assessments of inhibition and cognitive flex-
ibility on the CWIT as outlined in previous research (see
Yu et al., 2018), and found no significant differences
among the three independent samples t-tests (all ts<1).
Three independent samples t-tests were performed on the
length of time to complete each of two parts on the TMT, as
well as their combined time. We also conducted a fourth in-
dependent samples t-test for the ratio between Part B over Part
A, which is thought to be a purer assessment of attention
switching (Arbuthnott & Frank, 2000). Results indicated that
none of these four comparisons indicated a significant differ-
ence (all ts < 1.21). Taken together, our results indicated that
the mindfulness condition did not affect selective attention or
attention switching. This provides support for the hypothesis
that encoding is likely enhanced without necessarily increas-
ing attention (see Table 1for all attention comparisons).
Discussion
Our results strongly supported our central hypothesis that
mindfulness improves verbal learning and memory through
the enhancement of the encoding process, which mediated
the relationship between mindfulness and recall at both de-
layed free-recall trials. Furthermore, this improved encoding
capability was not due to increases in attention, as there were
no differences in attention between the mindfulness and con-
trol groups. This means that encoding is enhanced by mind-
fulness without necessarily affecting attentional processes.
Additionally, general verbal ability was left unaffected by
brief mindfulness training, providing evidence that mindful-
ness is particularly effective for learning new verbal informa-
tion through improved encoding processes, rather than help-
ing to retrieve previously learned verbal information, or im-
proving verbal ability more generally. However, questions
remain regarding whether the mindfulness induced by the ma-
nipulation lasted until the final delayed free-recall, or even the
measure of attention switching (i.e., TMT). It is possible that
certain measures were not significant due to mindfulness hav-
ing worn off over the course of the experiment. In order to
address these questions, we conducted a second study to en-
sure that some of our null results were not due to dissipated
mindfulness.
Study 2
In Study 1, the mindfulness audio was administered before the
RAVLT learning trials. The ISDA calculates its encoding in-
dex using these learning trials, whereas the consolidation and
retrieval indices are calculated using the two delayed free-
recall trials. It is possible that the mindfulness produced by
the initial mindfulness induction improved encoding during
these learning trials but then dissipated over time and was no
longer present during one or both of the delayed free-recall
trials. Indeed, in Study 1 the consolidation and retrieval indi-
ces were not significant, but they did trend toward significance
in favor of the mindfulness condition. If this is the case, then a
mindfulness induction before the delayed free-recall trials but
after the learning trials could improve consolidation and re-
trieval while leaving encoding untouched. We would then
expect the delayed free-recall trials to be better for the mind-
fulness condition over the control, while the learning trials
would indicate no difference.
On the other hand, if mindfulness truly improves verbal
learning and memory through enhanced encoding, then with-
out a mindfulness induction before the learning trials, we
would expect no differences in verbal learning and memory
with regard to the learning trials or delayed free-recall trials,
even if participants were exposed to a mindfulness induction
before the two delayed free-recall trials. Furthermore, we
would expect no differences between conditions in terms of
their consolidation and retrieval indices, even with the audio
manipulations placed immediately before the delayed free-
recall trials. In Study 2 we made these adjustments to test for
these possibilities.
Finally, it is also possible that mindfulness wore off before
participants reached our measure of attention switching (i.e.,
TMT) in Study 1, thus leading to null results. Had mindfulness
been active during this measure, we may have found a differ-
ence. To test this, we moved the TMT closer to the mindful-
ness induction in Study 2.
Mem Cogn
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Method
Participants
Participants were 57 college students (35 females and 22
males; 31 mindfulness and 26 control) of traditional college
age who were recruited from a large Midwestern university.
The final sample size was determined by a power analysis for
independent samples t-tests, with the desire to achieve a 90%
probability of detecting a large effect (d= .80), which required
approximately 27 participants per condition.
Measures
All measures were identical to Study 1 and were administered
in the same manner except for the SMS. Instead of the SMS,
we used three questions to measure state mindfulness. Two
questions came from the SMS and were presented on a 5-point
scale (0 –Not at all, to 4 –Very much; e.g., BDuring the audio,
I felt closely connected to the present moment^), while the
other was the one-question State MAAS (Ostafin & Kassman,
2012), presented on a 12-point scale (0 –Strongly disagree, to
11 –Strongly agree; BAt this moment I feel like I will rush
through activities without being really attentive to them^).
Procedure
The procedure had a few key differences from Study 1. First,
the mindfulness and control audios were administered before
the RAVLT in Study 1, whereas Study 2 placed these audios
after the RAVLT learning trials and interference trial but be-
fore the first delayed free-recall trial. Second, in Study 2 we
added a novel second audio (which varied by condition and
were similar to the audios used in Study 1) before the second
RAVLT delayed free-recall trial, given that there were approx-
imately 20 min in between delayed free-recall trials, and there
still existed the possibility of mindfulness dissipating before
the second delayed free-recall trial. Third, to account for the
addition of the second 10-min audio and the reordering of the
RAVLT in relation to the audio trials, we eliminated the filler
task and placed the remaining tests in an order designed to
provide approximately a 20-min gap between the two RAVLT
delayed free-recall trials.
All manipulations and measures were presented in the fol-
lowing order: MAAS, RAVLT learning trials and interference
trial, first 10-min audio tape (mindfulness/control), state mind-
fulness questions, first RAVLT delayed-recall trial, CWIT,
TMT, second 10-min audio tape (mindfulness/control), state
mindfulness questions, second RAVLT delayed free-recall tri-
al and recognition trial, FAS, and demographic questions.
Results
Preliminary results
An independent samples t-test revealed no differences be-
tween the mindfulness and control groups in trait mind-
fulness before any audio manipulation, (t< 1). However,
state mindfulness was significantly higher for the mind-
fulness condition after the first audio, t(55) = 4.06, p<
.001, d= 1.06 (Mindfulness: M= 12.48, SD = 2.82;
Control: M=8.81,SD = 4.00) and the second audio
t(55) = 2.38, p= .01, d= .63 (Mindfulness: M= 12.39,
SD = 3.30; Control: M= 10.27, SD = 3.39).
RAVLT and ISDA analyses for verbal learning
and memory
We then examined whether the mindfulness and control
conditions were different on the combined performance
for all five learning trials (which were completed before
any audio manipulation), as well as the combined
Table 1 Descriptive statistics for all attention comparisons
Test Mindfulness Control
CWIT
Time (in seconds)
Time 1 26.17 (4.74) 26.92 (4.74)
Time 2 19.96 (3.78) 20.69 (4.35)
Time 3 45.58 (12.67) 45.15 (8.49)
Time 4 55.09 (11.45) 54.36 (10.75)
Total Time 146.69 (27.88) 147.13 (22.88)
Times 3 and 4 100.40 (21.21) 99.51 (16.69)
Errors
Total 4.04 (3.26) 4.77 (3.39)
Trial 3 Uncorrected .37 (1.04) .67 (1.30)
Trial 3 Corrected 1.04 (1.30) .90 (1.10)
Trial 4 Uncorrected 1.11 (1.58) 1.54 (1.93)
Trial 4 Corrected 1.52 (1.81) 1.67 (1.56)
Trials 3 and 4 Uncorrected 1.48 (1.93) 2.21 (2.82)
Trials 3 and 4 Corrected 2.57 (2.59) 2.56 (1.83)
Pure processes
Inhibition 19.33 (9.49) 18.23 (6.79)
Cognitive Flexibility 9.24 (11.51) 9.21 (9.85)
Inhibition/Cog. Flexibility 28.91 (9.52) 27.44 (9.86)
Trail-Making Test (in seconds)
Trail A 19.72 (5.60) 20.26 (8.79)
Trail B 44.26 (16.60) 48.62 (21.15)
Trails A and B 63.98 (19.25) 68.87 (27.10)
Ratio B/A 2.33 (.86) 2.56 (.88)
Note. Data are given as means and standard deviations (in parentheses)
for all non-significant tests examined with regard to selective attention
(CWIT) and attention switching (Trail-Making Test)
Mem Cogn
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performance on the two delayed free-recall trials (which
were all completed after an audio manipulation). There
were no differences with regard to the learning trials
(higher numbers means better performance), t(55) = 1.24,
p= .11 (Mindfulness: M= 47.32, SD = 7.46; Control: M=
49.77, SD = 7.44), or the delayed free-recall trials, t(55) =
1.34, p= .09 (Mindfulness: M= 19.03, SD =5.01;Control:
M= 20.69, SD = 4.22) Fig. 2. As this study predicted that
the null hypothesis would be supported for both of these
analyses, we calculated a Bayes factor for each using the
mean differences from Study 1 as an estimate of the effect
we should see if the mindfulness and control conditions are
different from each other. This mean difference was used
as the SD of a half normal (Dienes, 2014). As per Jeffrey
(1939), we interpret a Bayes factor above 3 as providing
substantial evidence for the alternative hypothesis, whereas
a Bayes factor below 1/3 providing substantial evidence
for the null hypothesis. The learning trials provided sup-
port for the null hypothesis, B
H(0, 4.80)
= .19, as did the
delayed recall trials, B
H(0, 2.12)
=.25.
To follow up with the ISDA, we examined the potential
difference between mindfulness and control conditions in
terms of their encoding, consolidation, and retrieval. The
encoding index was calculated using the five learning trials,
which were completed before any manipulation and therefore
were expected to be similar. This was the case, as there was no
significant difference between conditions, (t=1.00).Again,
we used the mean difference between conditions regarding
encoding from Study 1 as an estimate of the effect in order
to calculate a Bayes factor to determine whether or not the null
hypothesis was supported. Results indicated support for the
null hypothesis, B
H(0, 1.36)
=.23.
We then examined any potential consolidation or retrieval
benefits of mindfulness, as these indices were calculated using
the two delayed free-recall trials, each of which followed an
audio manipulation. Higher numbers on each index indicates a
greater deficit. There were no significant differences between
the mindfulness and control conditions for the consolidation
index, t(55) = 1.49, p= .07 (Mindfulness: M=.34,SD =.25;
Control: M=.25,SD = .18), or retrieval index, t(55) = 1.31, p
= .10 (Mindfulness: M=.14,SD = .11; Control: M=.17,SD =
.09). Once again, we calculated a Bayes factor with the results
from Study 1 as an estimate for the effect regarding consoli-
dation and retrieval. Results indicated some support for the
null hypothesis regarding consolidation, B
H(0, .0456)
=.43,
but no support for the null hypothesis regarding retrieval,
B
H(0, .0278)
=1.80.
General verbal fluency and attention
Similar to Study 1, we found no significant differences be-
tween the mindfulness and control conditions on our verbal
fluency measure (i.e., FAS), t< 1. Furthermore, our measure
of attention switching (i.e., TMT) also indicated no significant
differences among the four possible comparisons, (all ts < 1).
Our selective attention measure (CWIT) also found no signif-
icant differences among its comparisons, (all ts < 1). Tab. 2
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 First
Delay
Second
Delay
Recognion
5
6
7
8
9
10
11
12
13
14
Mindfulness Control
RAVLT Performance
Words Remembered
RAVLT Trial
Fig. 2 Verbal learning and memory performance for both conditions on each Rey Auditory Verbal Learning Task (RAVLT) trial in Study 2. None of the
comparisons are significant at p= .05 except Recognition
Mem Cogn
Author's personal copy
Discussion
Study 2 found further support for the idea that mindfulness
improves verbal learning and memory through enhancing the
encoding process of memory rather than the consolidation and
retrieval processes. Without mindfulness during the learning
trials, the mindfulness condition did not perform any better on
the learning trials or delayed free-recall trials, even when giv-
en a mindfulness induction before both delayed free-recall
trials. This indicates that mindfulness must be present during
the learning process in order to enhance the encoding process
and subsequently recall the new verbal information at a later
time. Alternatively, it appears as though mindfulness is not
particularly effective at improving consolidation and retrieval
processes ifinstituted after a learning phase has already ended.
Additionally, we again found no effect of mindfulness on
general verbal fluency, indicating further that mindfulness is
particularly effective at helping to learn new verbal informa-
tion, rather than giving greater access to and retrieval of pre-
viously learned verbal material. Finally, the results of Study 2
reflected those of Study 1 with regard to attention. The mind-
fulness condition did not enhance selective attention or
attention-switching capabilities. As the attention-switching
task was placed much closer to the mindfulness induction in
Study 2, this indicates the null result found in Study 1 was not
due to mindfulness wearing off by the time participants
reached that task. Instead,we found evidence that mindfulness
did not alter selective attention or attention switching in either
study.
General discussion
Participants who engaged in mindfulness for a mere 10 min
exhibited improved verbal learning and memory through en-
hanced encoding. This demonstrates that even brief periods of
mindfulness can help people improve important areas of learn-
ing with relatively little investment before the learning process
begins, such as learning vocabulary, reading comprehension,
listening comprehension, etc. Furthermore, it seems likely that
experienced meditators who generally maintain a mindful
state throughout their day would exhibit higher encoding ca-
pabilities without the need to have recently engaged in medi-
tation. In this way, long-term meditators may indicate a greater
general capacity to learn, understand, and remember verbal
information within their environment throughout the course
of the day. Indeed, long-term meditators have shown better
verbal learning and memory performance on a task similar
to the RAVLT without having recently meditated (Lykins,
Baer, & Gottlob, 2012). It is important to understand if these
long-term meditators achieve these enhanced results due to
increased encoding capabilities as well, which would be a
fruitful area for future research. If so, it would elevate mind-
fulness as an extremely important tool to actively improve
verbal learning and memory processes through enhancing
the ability to encode new information.
This elevated learning through mindfulness should be able
to improve almost anyone’s verbal learning and memory ca-
pability without the need for invasive or difficult learning
techniques that may be off-putting or time-consuming for peo-
ple to incorporate into their lives. This seems particularly use-
ful for children, as learning progresses rapidly through early
school years. A number of school subjects may benefit from
enhanced verbal learning, such as learning vocabulary, learn-
ing a new language, understanding reading assignments, re-
membering important historical events, and many more.
Recent research with children has shown some promising ear-
ly signs regarding the benefits that mindfulness can have on
academic success (Ksendzov, 2017; Lu, Huang, & Rios,
2017). Research with children and the potential for increased
learning through mindfulness should be an area of primary
importance for future research.
Table 2 Descriptive statistics for all attention comparisons in Study 2
Test Mindfulness Control
CWIT
Time (in seconds)
Time 1 26.11 (3.72) 25.89 (2.25)
Time 2 19.69 (3.19) 19.30 (3.69)
Time 3 45.56 (11.46) 46.63 (8.20)
Time 4 53.50 (12.68) 54.19 (10.06)
Total Time 144.94 (26.12) 146.36 (15.56)
Times 3 and 4 99.08 (21.62) 100.82 (15.10)
Errors
Total 3.77 (3.45) 4.20 (4.19)
Trial 3 Uncorrected .77 (2.01) .92 (1.85)
Trial 3 Corrected 1.00 (1.13) 1.16 (1.40)
Trial 4 Uncorrected 1.23 (1.91) .84 (1.21)
Trial 4 Corrected 1.03 (1.22) 1.28 (1.43)
Trials 3 and 4 Uncorrected 1.70 (2.58) 1.76 (2.60)
Trials 3 and 4 Corrected 2.07 (1.82) 2.44 (2.62)
Pure processes
Inhibition 19.45 (9.41) 20.55 (8.01)
Cognitive Flexibility 7.91 (11.23) 7.56 (10.44)
Inhibition/Cog. Flexibility 27.46 (11.32) 28.11 (10.12)
Trail-Making Test (in seconds)
Trail A 21.51 (8.78) 20.57 (5.05)
Trail B 56.81 (17.38) 59.52 (19.74)
Trails A and B 78.32 (21.20) 80.20 (22.64)
Ratio B/A 2.89 (1.18) 2.91 (.85)
Note. Data are given as means and standard deviations (in parentheses)
for all non-significant tests examined with regards to selective attention
(CWIT) and attention switching (Trail-Making Test)
Mem Cogn
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Additionally, our research demonstrated that mindfulness
increases encoding capabilities despite not improving atten-
tional capabilities, which implies that mindfulness may be a
particularly effective learning tool for people regardless of
their attentional capacity. While attention is important for
learning, and improving its capacity is valuable for the learn-
ing process, the ability of mindfulness to strengthen encoding
processes by bypassing attentional constraints can be incred-
ibly valuable in its own right. This may especially be the case
for those who struggle to pay attention, as this research implies
that mindfulness can improve verbal learning and memory
despite these difficulties. In this way, children or adults who
are vulnerable to distraction may still be able to improve their
ability to learn and recall new verbal information through
enhancing their encoding skills through mindfulness.
Perhaps this may even be true of clinical populations, such
as in people with Alzheimer’s disease whom show certain
impairments in encoding (Millet, Le Goff, Bouisson,
Dartigues, & Amieva, 2010). On the other hand, individuals
whose attentional capabilities are excellent, without much
room for improvement, may still be able to enhance their
verbal learning and memory capabilities by further improving
their encoding capacity through mindfulness. Theoretically,
this may work regardless of whether individuals show learn-
ing difficulties or not, which could potentially be another very
fertile area for future research.
While we found evidence that encoding enhancement was
not due to increases in attention, it is possible that other mea-
sures of attention may have been more likely to have been
affected by mindfulness, and therefore could have helped me-
diate the relationship between mindfulness and RAVLT per-
formance. We utilized measures of attention switching and
selective attention, but other attention measures (such as fo-
cused attention measures) could havebeen more likely to have
been enhanced by mindfulness. Future research should look at
these other attention measures as possible mediators between
mindfulness and improved verbal learning and memory.
Similarly, while we found that a brief mindfulness induc-
tion does not improve consolidation or retrieval processes, it is
possible that long-term practice may benefit these memory
processes. Taken together with our results, this would mean
that even a short mindfulness practice can help increase
encoding processes, which increases verbal learning and
memory, but long-term mindfulness practice could also
strengthen consolidation and retrieval, which would then en-
hance verbal learning and memory even more greatly. Future
research should examine whether consolidation and retrieval
processes are better in long-term meditators than controls.
Additionally, the current study demonstrated that mindful-
ness improved learning and memory in the verbal domain, but
it is possible that nonverbal learning capabilities may also
benefit from mindfulness. Future work will need to assess
whether visuo-spatial learning and memory is also enhanced
by a brief mindfulness practice. If it is the case that mindful-
ness can improve visuo-spatial learning and memory, this
would provide evidence that mindfulness can enhance general
learning capabilities, regardless of the modality in which
learning occurs. Preliminary evidence in this domain has
shown that mindfulness can enhance the recognition of visual
objects (Brown, Goodman, Ryan, & Analayo, 2016) and im-
prove visuo-spatial processing (Zeidan et al., 2010)
On the other hand, it could be that mindfulness is specifi-
cally good for verbal learning and memory, as perhaps the
enhanced encoding in this domain is produced by removing
cognitive load from the phonological loop –an essential as-
pect of working memory that holds and manipulates auditory
information (Baddeley & Hitch, 1994). Activities that engage
the phonological loop do not necessarily impede with perfor-
mance in non-verbal tasks, such as spatial tasks, while spatial
tasks also do not necessarily impede with verbal tasks. For
instance, Baddeley (1992) reported an attempt to have partic-
ipants memorize chess-piece locations, a visuo-spatial task,
while loading either the phonological loop or the visuospatial
sketchpad. Compared to a control group, memory was im-
paired when the visuo-spatial sketchpad was loaded but not
when the phonological loop was loaded (also see Burnham,
Sabia, & Langan, 2014). When people allow their thoughts to
slip away from the current task into thoughts that are unrelated
to the task, this internal verbalization (or inner speech) likely
interferes with the task that currently requires the phonological
loop, which would negatively affect cognitive performance.
Alternatively, this internal verbalization may not have any
impact on other learning capabilities as long as the task does
not heavily involve the phonological loop. It is for this reason
that mindfulness may be particularly suited to improve verbal
learning and memory but not general learning capabilities.
This hypothesis is derived from the ability of mindful-
ness to help people disengage from their thoughts, includ-
ing decreasing rumination (Kumar, Felman, & C.H.S,
2008), even after a stressful event (Key, 2010).
Similarly, low levels of trait mindfulness are related to
elevated levels of rumination (Ciesla, Reilly, Dickson,
Emanuel, & Updegraff, 2012), and higher trait and state
mindfulness have also been shown to be associated with
lower rumination (Eisenlohr-Moul, Peters, Pond, &
DeWall, 2016). Similarly, mind-wandering is a natural
phenomenon (Killingsworth & Gilbert, 2010) that can be
alleviated through mindfulness (Mrazek et al., 2013;R
ahl
et al., 2017). Mind-wandering can be thought of as a form
of cognitive load, as it negatively impacts working mem-
ory through its apparent recruitment of working memory
resources (Kam & Handy, 2014). By allowing the mind to
let go and disengage from thoughts, it perhaps reduces
cognitive load by clearing the phonological loop, thereby
providing more resources for verbal learning and memory
tasks, but not necessarily for other non-verbal learning
Mem Cogn
Author's personal copy
tasks. If this is indeed the case, then mindfulness may not
lead to any improvements in visuo-spatial learning tasks.
Future research should examine this possibility.
Tremendous resources have been exhausted in the attempt
to improve learning capabilities and enhance the ability to
remember important information. The present research dem-
onstrates strong support for mindfulness as an important, ef-
fective, and easily utilized tool for improved verbal learning
and memory through its specific enhancements of the
encoding process. These improvements likely transcend age
groups, establishing mindfulness as a valuable learning tool
that can be started during childhood and maintained and fos-
tered throughout adulthood. Furthermore, the ease of imple-
mentation and limited requirements for practicing mindful-
ness make it a method of learning enhancement that is ap-
proachable and easily able to be incorporated into daily life.
While there still needs to be much investigation within this
field, early indications are promising that the more you prac-
tice mindfulness, the more you know.
Author Notes Both authors were equally involved in the de-
velopment of this research. As such, both authors share first
authorship, and both are corresponding authors. Data are
available upon email request.
Data Availability Data are available through email request. Neither study
was pre-registered.
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