Cognition, Language, and Development
Mindfulness Meditation
Improves Visual
Short-Term Memory
Psychological Reports
2021, Vol. 124(4) 1673–1686
! The Author(s) 2020
Article reuse guidelines:
DOI: 10.1177/0033294120926670
Molly A. Youngs, Samuel E. Lee, and
Michael O. Mireku
School of Psychology, University of Lincoln, Lincoln, UK
Dinkar Sharma
School of Psychology, University of Kent, Canterbury, UK
Robin S. S. Kramer
School of Psychology, University of Lincoln, Lincoln, UK
Research into the effects of mindfulness meditation on behavioral outcomes has
received much interest in recent years, with benefits for both short-term memory
and working memory identified. However, little research has considered the potential effects of brief mindfulness meditation interventions or the nature of any benefits
for visual short-term memory. Here, we investigate the effect of a single, 8-minute
mindfulness meditation intervention, presented via audio recording, on a short-term
memory task for faces. In comparison with two control groups (listening to an
audiobook or simply passing the time however they wished), our mindfulness meditation participants showed greater increases in visual short-term memory capacity
from pre- to post-intervention. In addition, only mindfulness meditation resulted in
significant increases in performance. In conclusion, a single, brief mindfulness meditation intervention led to improvements in visual short-term memory capacity for
faces, with important implications regarding the minimum intervention necessary to
produce measurable changes in short-term memory tasks.
Corresponding Author:
Robin S. S. Kramer, School of Psychology, University of Lincoln, Lincoln LN6 7TS, UK.
Email: remarknibor@gmail.com
Psychological Reports 124(4)
Mindfulness, meditation, visual short-term memory, faces, intervention
Working memory (WM) is a multicomponent system, bringing together shortterm memory (STM) and attention (Cowan, 2016), and has a limited capacity,
varying between individuals (Ortells et al., 2016). Having a particularly low or
high capacity can affect people in many different ways, impacting daily life
(Richmond et al., 2015).
Low WM capacity has been linked to inattentive behavior, which can
increase the difficulty of everyday tasks and activities requiring sustained attention (Kofler et al., 2017; Zhang et al., 2018), while STM capacity may, for
example, explain individual differences in learning (Frensch & Miner, 1994),
mathematical performance (Swanson & Kim, 2007), and reading comprehension (Haarmann et al., 2003). Specific courses designed to improve WM have
been implemented using different techniques and with varying levels of success
(Klingberg et al., 2002; for a review, see Morrison & Chein, 2011). Methods
targeting the improvement of STM specifically have included rehearsal
(Broadley et al., 1994), visual imagery (de la Iglesia et al., 2005), creating stories
from the information to be remembered (McNamara & Scott, 2001), and grouping of the items into conceptual categories (Carr & Schneider, 1991).
One promising avenue for improvement has been the introduction of mindfulness meditation (MM), gaining popularity in recent years and triggering substantial research (Keng et al., 2011). Mindfulness-based interventions have
become common, owing to their affordability, ease of learning, and growing
evidential support for benefits in mental health and cognitive function (Davis &
Hayes, 2011). The term MM can describe several practices and states, with the
main goal of reaching a state of awareness that maintains attention in the present moment (e.g., on changing sensory and mental states) while avoiding the
intrusion of outside factors (Baltar & Filgueiras, 2018).
Chambers et al. (2008) assessed individuals after they had attended a 10-day
MM camp, finding that WM capacity (specifically, backward digit memory
span) had improved. Indeed, several studies have recently demonstrated similar
improvements on various measures of WM, including the adaptive n-back task
and operation span, although no improvements in STM (e.g., forward digit
span) were found (e.g., Mrazek et al., 2013; Zeidan et al., 2010). In contrast,
Lykins et al. (2012) found no improvements in WM (letter-number sequencing;
Wechsler, 1997) while identifying group differences (experienced meditators
vs. controls) in measures of STM (both short delay free and cued recall;
Delis et al., 1987).
Youngs et al.
While studies appear to have demonstrated relationships between MM and
improved WM and STM capacities, the length of the MM intervention involved
has been variable, ranging from one to eight weeks. Shorter intervention periods
are generally preferred to longer ones due to their ease and convenience (BergenCico et al., 2013). However, there are some cases in which brief
interventions have been shown to be marginally less effective than longer ones
(Basso et al., 2019). In terms of implementation, there is a clear demand for
research surrounding the effectiveness of MM in even shorter sessions, such as
a single sitting (Chiesa et al., 2011). It is also worth noting that the motivation
to practice MM can decrease over time and across sessions (Hafenbrack &
Vohs, 2018). As such, the main aim of our study was to investigate whether a
single, brief session of MM could lead to a measurable improvement in
STM capacity.
There are many ways to study the impact of MM on STM capacity, and the
specific task used to quantify STM can vary. With previous research involving
STM capacity focusing on verbal paradigms (e.g., Lykins et al., 2012), the
effects of MM on visual STM have yet to be investigated, which is perhaps
surprising since this can be assessed reliably and is critical for the online use
of visual information. One method of testing visual STM is through a delayed
nonmatching-to-sample paradigm, where participants are tasked with distinguishing between previously seen items and a novel item (e.g., using faces—
Crook & Larrabee, 1992). As such, identification of the novel item requires
that previously seen items are maintained in STM.
There are many explanations as to why MM improves memory, with the
most widely accepted explanation being through a reduction of anxiety. For
instance, Eysenck et al. (2007) suggested that the attentional control aspect of
the central executive is impaired by anxiety. Specifically, the inhibition function
of the central executive can no longer effectively redirect attention away
from task irrelevant stimuli. This, in turn, means that people find difficulty in
completing tasks that require sustained attention as they become distracted.
A link between attentional control and memory has been established as
a result of this, due to the completion of memory tasks requiring effective attentional control in order to maintain attention to goal-relevant information
(Shipstead et al., 2014).
Researchers have suggested that attention and memory processes are closely
related forms of cognitive control, with both likely to be influenced by MM (Jha
et al., 2010). Furthermore, both short- and long-term memory are largely dependent on present-moment direction of attention (Cowan, 1997). Therefore, in line
with previous work (Lykins et al., 2012), it is important to determine whether
MM can improve performance on STM tasks. In the current study, we utilize a
single, brief MM intervention, lasting only a few minutes. In addition, we focus
on visual STM specifically, given the lack of previous research investigating this
particular domain.
Psychological Reports 124(4)
A total of 90 undergraduate students (age range, 18–25 years; 61 women; 83 selfreported as White) participated in exchange for course credits. Data from one
additional participant were excluded due to a failure to complete all the tasks.
Sample size (N ¼ 30 per group) was chosen to be comparable with previous
research in this area (for a systematic review, see Chiesa et al., 2011).
The university’s research ethics committee approved the experiment presented here, which was carried out in accordance with the provisions of the
World Medical Association Declaration of Helsinki. Participants provided written informed consent before taking part and were given both a written and
verbal debriefing upon completion.
Participants completed two measures of mindfulness during everyday life. The
Mindfulness Attention Awareness Scale (MAAS; Brown & Ryan, 2003) consists
of 15 items that are rated on a 6-point Likert-type scale from 1 (almost always)
to 6 (almost never), where the mean rating across all items represents the final
score, with higher scores reflecting greater mindfulness. The Five-Factor
Mindfulness Questionnaire (FFMQ; Baer et al., 2006) consists of 39 items
that are rated on a 5-point Likert-type scale from 1 (never or very rarely true)
to 5 (very often or always true). Mean ratings (after reverse scoring specific
items) are calculated for each of five facets: observing, describing, acting with
awareness, nonjudging of inner experience, and nonreactivity to inner experience. Again, higher scores reflect greater mindfulness.
Given that the FFMQ is derived from a factor analysis of several questionnaires including the MAAS, we would predict at least some correlation between
participants’ scores on these instruments. However, since such relationships are
far from perfect (Baer et al., 2006) and both measures remain popular, we
decided to include both questionnaires in the current study.
In the listening task, participants in the audiobook group listened to the
beginning of “The Hobbit” (Tolkien, 2005). Those in the meditation group
listened to a “mindfulness of body and breath” exercise (Williams & Penman,
2011) designed to focus their attention on the movement of the breath in the
body. We selected an audiobook for comparison since it requires a similar
amount of attention and concentration to the meditation task, although the
focus of attention in the two tasks was necessarily, and importantly, different.
Both of these audio segments have featured in previous research (e.g., Kramer
et al., 2013). Finally, for the control group, participants were simply asked to sit
quietly and fill their time however they wished. (In the majority of cases, this
Youngs et al.
involved the use of personal smartphones.) The audio recordings were presented
using closed-back headphones.
For the face memory task, 450 images of White faces (225 women) were
downloaded from an online database (www.facity.com), which contained
around 2000 high-quality photographs of faces, taken front-on and with neutral
expressions, hair pulled back, and minimal make-up. We selected only faces with
no jewellery and who were aged approximately 18 to 40 (year of birth was
available in the majority of cases). Images were already cropped below the
hairline, and we additionally cropped them just below the chin, and close to
the sides of the faces, using Adobe Photoshop CS software.
Participants were tested individually in a quiet laboratory room, first completing
both questionnaires, along with demographic information. Following this, participants performed a face memory task adapted from previous work (Crook &
Larrabee, 1992), presented on a desktop computer using custom MATLAB
software. On each trial, a single facial photograph was initially displayed
onscreen, which the participant was instructed to select with the mouse. Next,
this face and a second face appeared onscreen, and the participant was required
to select the new face. If the correct response was given, this process would
continue, each time introducing a new face, until a maximum of 45 faces were
displayed (see Figure 1). Within each trial, all faces were of the same sex. Trials
terminated when an incorrect response was given, and the number of correct
responses was recorded. Importantly, after every response, the new display of
faces was randomized with respect to spatial position onscreen, meaning that
participants could not use location information to inform their decisions.
Participants completed five trials in the first session, with the sex of faces alternating across trials. No face appeared in more than one trial.
Upon completion, participants were randomly allocated to one of three
groups. Those in the audiobook (11 men and 19 women) and meditation (12
men and 18 women) groups then listened to an 8-minute audio recording with
instructions to follow along as best they could and to inform the experimenter
when it finished. Those in the meditation group were presented with a breathing
exercise, while those in the audiobook group listened to a neutral recording.
Participants in the control group (6 men and 24 women) were instructed to fill
their time however they wished and were given 8 minutes for this task. In all
cases, the experimenter remained in the room but did not interact with the
participant. The assignment of participants to groups was randomized.
After the listening/control task, participants completed the face memory task
again (second session). The procedure was identical to earlier although only face
images that had not appeared in the first session were presented.
Psychological Reports 124(4)
Figure 1. Illustration depicting the face memory task. In this example trial, the participant
responds correctly to the first three displays. (Images not to scale.)
Preliminary analyses
Participants’ scores on the MAAS and FFMQ were calculated, and the associations between these measures are summarized in Table 1. As expected, we
found some significant overlap between the two questionnaires as well as
among the five facets of the FFMQ. Most notably, we found a large positive
relationship between scores on the MAAS and the “acting with awareness” facet
of the FFMQ.
In addition, we compared participants across the three groups. We found no
group differences in FFMQ Describing scores, FFMQ Nonjudging scores, and
FFMQ Nonreactivity scores (in all cases, F < 2.64, p > .077, g2p < 0.06).
However, we found a significant difference in MAAS scores, F(2, 87) ¼ 4.28,

corrected here and below)
p ¼ .017, g2p ¼ 0.09, with post hoc tests (Dunn-Sidák
revealing that participants in the control group (M ¼ 3.82, SD ¼ 0.61) showed
higher scores than those in the audiobook group (M ¼ 3.38, SD ¼ 0.63;
p ¼ .021). No other comparisons were significant (both ps > .087). Groups also
differed in FFMQ Observing scores, F(2, 87) ¼ 4.15, p ¼ .019, g2p ¼ 0.09, with
participants in the meditation group (M ¼ 3.31, SD ¼ 0.54) showing higher
scores than those in the control group (M ¼ 2.83, SD ¼ 0.72; p ¼ .017). No
other comparisons were significant (both ps > .200). Finally, group differences
were also found in FFMQ Acting with Awareness scores, F(2, 87) ¼ 4.44,
Youngs et al.
Table 1. Correlations between questionnaire measures.
2. FFMQ: Observing
3. FFMQ: Describing
4. FFMQ: Acting with awareness
5. FFMQ: Nonjudging
6. FFMQ: Nonreactivity





Note: MAAS: Mindful Attention Awareness Scale; FFMQ: Five-Factor Mindfulness Questionnaire.
*p < .05. **p < .01. ***p < .001.
p ¼ .015, g2p ¼ 0.09, with participants in the control group (M ¼ 3.26, SD ¼ 0.55)
showing higher scores than those in the audiobook group (M ¼ 2.82, SD ¼ 0.62;
p ¼ .011). No other comparisons were significant (both ps > .302).
In two of these results, group differences suggested higher baseline mindfulness in the control than in the audiobook participants, which had no bearing on
the hypothesized benefit of our mindfulness task over the other two groups.
However, we also found that participants in the meditation group scored
higher on baseline FFMQ Observing in comparison with control participants
prior to any listening task. Perhaps reassuringly, this difference comprised only
0.48 on a 1 to 5 scale, and we found no difference between the meditation and
audiobook groups. As such, we could be confident that any benefit for the MM
group during the listening task was not the result of baseline differences between
the three groups. In addition, we included these scores as covariates in our
analyses (see below).
Improvements in face memory
For each participant, we calculated the mean score across the five trials of the
memory task for each session separately. We then calculated the difference
between sessions (second minus first), providing us with a measure of the
improvement due to the listening (or control) task. The difference scores were
then analyzed as follows.
Initial consideration of the difference scores revealed nine data points (meditation group–1; audiobook group–4; control group–4) that were classified as
outliers (identified using boxplots produced with IBM’s SPSS Statistics software
v25), defined as values further than 1.5 times the interquartile range from the
nearer edge of that range. It is worth noting that four of these outliers showed
extreme negative difference scores while the remaining five demonstrated
extreme positive differences, suggesting no particular pattern of performance
Psychological Reports 124(4)
across this subsample. As a result of identifying these outliers, we decided to
carry out two types of analyses on our data.
Parametric analysis: One-way ANOVA
Since both the group means and variances are sensitive to outliers, their presence
violates the assumptions of an analysis of variance (ANOVA) by reducing the
validity of the results. We therefore excluded the above-mentioned nine data
points and then carried out a one-way (Group: control, audiobook, meditation)
between-subjects ANOVA. We found a main effect of group, F(2, 78) ¼ 9.83,

p < .001, g2p ¼ 0.20, with post hoc tests (again, Dunn-Sidák
corrected) revealing
larger difference scores for participants in the meditation group (M ¼ 2.08,
SD ¼ 2.41) in comparison with those in the audiobook group (M ¼ –0.18,
SD ¼ 1.79; p < .001) and the control group (M ¼ 0.18, SD ¼ 1.82; p ¼ .003).
These latter two groups did not differ from each other (p ¼ .887; see Figure 2).
In addition, we compared mean improvement scores to a value of zero for
each group separately. For the meditation group, we found a nonzero improvement, t(28) ¼ 4.63, p < .001, Cohen’s d ¼ 0.86. In contrast, improvements did not
differ from zero for both the audiobook group, t(25) ¼ 0.53, p ¼ .603, Cohen’s
d ¼ 0.10, and control group, t(25) ¼ 0.52, p ¼ .609, Cohen’s d ¼ 0.10.
Our preliminary analyses revealed significant differences between participants
across our three groups with regard to three of their questionnaire scores:
MAAS, FFMQ Observing, and FFMQ Acting with Awareness. As such, we
repeated the above analysis while including these three scores as covariates.
Again, we found a main effect of group, F(2, 75) ¼ 10.66, p < .001, g2p ¼ 0.22,

with post hoc tests (again, Dunn-Sidák
corrected) revealing larger difference
scores for participants in the meditation group in comparison with those in
the audiobook group (p < .001) and the control group (p ¼ .001). These latter
two groups did not differ from each other (p ¼ .998).
Nonparametric analysis: Kruskal–Wallis test
We also carried out a nonparametric equivalent of the above analysis, allowing
us to include all data points since ranked data are far less sensitive to outliers.
The Kruskal–Wallis test found a significant difference between groups, H(2) ¼
7.74, p ¼ .022.1 Follow-up comparisons using Mann–Whitney tests2 showed
larger difference ranks for participants in the meditation group in comparison
with those in the audiobook group, U ¼ 285.50, z ¼ 2.43, p ¼ .015, r ¼ 0.31. In
addition, those in the meditation group also showed higher difference ranks
than those in the control group, U ¼ 294.50, z ¼ 2.30, p ¼ .020, r ¼ 0.30. These
latter two groups did not differ from each other, U ¼ 406.50, z ¼ 0.64, p ¼ .525,
r ¼ 0.08.
Youngs et al.
Figure 2. Mean improvement scores for the three groups. Error bars represent 95%
confidence intervals.
The goal of this research was to investigate whether a single, brief MM intervention could improve STM capacity. Our results demonstrated a significant
improvement in visual STM for our MM group. In contrast, those who listened
to an audiobook or filled their time however they wished failed to show an
improvement. The increase in performance on the face memory task as a
result of MM extends previous research demonstrating that MM can improve
various components of STM (Lykins et al., 2012).
That an 8-minute MM intervention was effective is an important result,
building upon earlier research showing that MM sessions as brief as 10 minutes
Psychological Reports 124(4)
can improve attentional control and reduce psychological stress (Norris et al.,
2018), two aspects considered important in WM performance (Kane et al., 2001;
Schoofs et al., 2008). Our results are also consistent with research showing that
time spent on a MM task may not be correlated with the strength of subsequent
improvements, suggesting that the majority of MM benefits may occur early on
in one’s practice (Carmody & Baer, 2009).
One explanation as to why MM might improve STM capacity is that during
task performance, part of STM is occupied by task-irrelevant information. MM
could then improve (relevant) STM capacity by reducing this information, freeing
up cognitive resources to be put to work on the task at hand. Previous research
has shown that anxiety can inhibit central executive processes (Berggren et al.,
2016; Park et al., 2016), and with MM reducing anxiety (Hoge et al., 2014), this
could provide a potential mechanism through which MM can improve STM. In
addition, MM encourages the acceptance, rather than avoidance, of thoughts and
emotions as they pass through awareness. Evidence suggests that MM improves
the acceptance of emotional states, resulting in greater executive control (Teper &
Inzlicht, 2013; for a review, see Malinowski, 2013). Again, this may be why our
MM participants showed increases in visual STM in the current experiment.
However, we acknowledge that the specific mechanism through which MM
affects STM has yet to be identified.
Here, for practical reasons, we presented an audio recording for our MM
intervention rather than a face-to-face session. Along similar lines, recent evidence has suggested that participants can benefit from completing their own
MM practices via the use of a smartphone application (Walsh et al., 2019),
representing the possibility that a greater proportion of the population might
benefit from access to MM through solo practice. If further research supports
this idea, more people might be willing to incorporate MM into their daily
routines if additional costs and time constraints, typically associated with organized classes and sessions, are not required.
To conclude, this study demonstrates that a single, brief MM intervention
improves performance on a STM task. Our focus on visual STM, as well as the
use of only minimal MM with our participants, represents important extensions
to the literature with regard to measurable effects that MM has on behavioral
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Youngs et al.
Robin S. S. Kramer
1. Monte Carlo estimate of significance based on 10,000 samples.
2. Significance values calculated using exact methods.
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Psychological Reports 124(4)
Author Biographies
Molly A. Youngs is a masters student in the School of Psychology at the University
of Lincoln.
Samuel E. Lee was an undergraduate student at the University of Lincoln and
now works in rehabilitation, using dialectical behavioural therapy and mindfulness meditation.
Michael O. Mireku is a senior lecturer in the School of Psychology at the
University of Lincoln.
Dinkar Sharma is a reader in the School of Psychology at the University of
Robin S. S. Kramer is a lecturer in the School of Psychology at the University of
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