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The effects of imagery interventions in sports: a
Bianca A. Simonsmeier , Melina Androniea , Susanne Buecker & Cornelia
To cite this article: Bianca A. Simonsmeier , Melina Androniea , Susanne Buecker & Cornelia
Frank (2020): The effects of imagery interventions in sports: a meta-analysis, International Review
of Sport and Exercise Psychology, DOI: 10.1080/1750984X.2020.1780627
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The eﬀects of imagery interventions in sports: a meta-analysis
Bianca A. Simonsmeier
, Melina Androniea
, Susanne Buecker
and Cornelia Frank
Educational Psychology, University of Trier, Trier, Germany;
Department of Psychology, Ruhr-University
Bochum, Bochum, Germany;
Neurocognition and Action, University of Bielefeld, Bielefeld, Germany
Imagery interventions are an established psychological tool to
enhance performance, psychological skills, and injury
rehabilitation. Previous meta-analyses found positive eﬀects of
mental practice on performance, leaving it open whether imagery
can also enhance outcomes other than performance such as
motivational or aﬀective outcomes. We performed a meta-analysis
to extend the current understanding of the eﬀectiveness of
imagery in sports on any sport speciﬁc outcome and the
relevance of additional variables potentially moderating the eﬀect.
The overall eﬀect of imagery interventions was medium in
magnitude with d= 0.431 (95% CI [0.298, 0.563]). Imagery
interventions signiﬁcantly enhanced motor performance,
motivational outcomes, and aﬀective outcomes. Summarized
across all outcomes, imagery combined with physical practice was
more eﬀective than physical practice alone, indicating diﬀerential
eﬀects of imagery and physical practice. We found the same
pattern of result for performance outcomes. The eﬀectiveness of
imagery was positively associated with the intensity of the
imagery training. We discuss our results against previous meta-
analyses on mental practice and the background of theoretical
and practical aspects of imagery. Moreover, we lay out directions
for future research by providing a comprehensive overview of
research gaps in the literature on imagery.
Received 6 April 2020
Accepted 5 June 2020
Psychological skill; mental
practice; mental strategies;
mental stimulation; review
Imagery is one of the most popular and well-accepted sport psychological strategies to
improve performance, psychological skills, and injury rehabilitation (e.g. Cumming &
Ramsey, 2009; Cumming & Williams, 2013; Guillot & Collet, 2008). It describes
the creation and re-creation of an experience generated from memorial information, involving
quasi-sensorial, quasi-perceptual, and quasi-aﬀective characteristics, that is under the voli-
tional control of the imager, and which may occur in the absence of the real stimulus antece-
dents normally associated with the actual experience. (Morris et al., 2005, p. 19)
Sometimes, imagery and mental practice are used synonymously. The constructs are com-
parable in terms of describing a cognitive process of symbolic rehearsal. However, mental
practice does not necessarily involve imagery but can also refer to other types of mental pro-
cesses or mental preparation including self-talk or relaxation. Diﬀerent to mental practice,
© 2020 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Bianca A. Simonsmeier firstname.lastname@example.org
Supplemental data for this article can be accessed at https://doi.org/10.1080/1750984X.2020.1780627
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY
imagery is a speciﬁc mental process that can be mentally practiced (Murphy & Martin, 2002)
and that includes the creation and re-creation of an experience of any kind not limited to
motor performance. The present meta-analysis has the aim to extend the current under-
standing of the eﬀectiveness of imagery interventions by investigating the eﬀects of
diﬀerent types of imagery on various outcomes, employing comprehensive analyses regard-
ing control conditions and comparisons, and using state-of-the-art meta-analytic strategies.
Previous meta-analyses summarized existing evidence from single studies on the eﬀec-
tiveness of mental practice and indicated positive eﬀects on motor performance. Table 1
provides an overview of the main characteristics of the previous meta-analyses regarding
conceptual and methodological aspects. The two earliest published meta-analyses (Feltz &
Landers, 1983; Hinshaw, 1991) investigated the eﬀectiveness of interventions that
included both mental practice and mental preparation which is a more general term
that includes a variety of disparate strategies with the goal to enhance performance (Ber-
tollo et al., 2009; Weinberg et al., 1985). While these meta-analyses provided ﬁrst evidence
on the eﬀectiveness of mental practice on performance, conclusions about the eﬀective-
ness of mental practice as an individual strategy cannot be drawn. This limitation was
addressed in a later meta-analysis that included studies employing mental practice inter-
ventions only (Driskell et al., 1994). The analysis revealed a medium positive eﬀect of
mental practice on performance when compared to no-treatment control conditions
with d= 0.527 comprising 62 eﬀect sizes from 35 studies. Toth et al. (2020) recently per-
formed a methodological replication of the Driskell et al. (1994) study including 37
studies and 99 eﬀect sizes from the research of the past 25 years. They also found a posi-
tive eﬀect comparable in magnitude of d= 0.419 which was, however, substantially lower
when accounting for publication bias (d= 0.264). Besides demonstrating the eﬀectiveness
of mental practice to enhance performance, the two meta-analyses provide further valu-
able insights into relevant variables moderating the eﬀect leading to useful practical impli-
cations. For example, both meta-analyses highlight the relevance of the duration of the
mental practice session. Results indicated an inverse (Driskell et al., 1994) and inverse U-
shaped relationship (Toth et al., 2020), with both suggesting 20 min sessions to be most
Limitations and extensions of previous meta-analyses on mental practice
The previous meta-analyses provide valuable theoretical and practical insights on the
eﬀectiveness of mental practice on performance, but do not provide an integration of
the comprehensive existing literature on imagery training thus far. As mental practice
and imagery conceptually diﬀer (Murphy & Martin, 2002), a meta-analysis on the eﬀects
of imagery speciﬁcally is still outstanding. The present analysis aims at extending results
of previous meta-analyses in three ways: by implementing diﬀerent inclusion criteria,
including other potential moderating variables, and applying state of the art statistical
methods which will be discussed in the following.
First, all previous meta-analyses provide evidence for the eﬀectiveness of mental prac-
tice to enhance performance. It is however suggested that imagery is eﬀective to enhance
a variety of outcomes such as psychological skills and not only performance as indicated in
diﬀerent models on imagery (Cumming & Williams, 2013; Guillot & Collet, 2008; Martin
et al., 1999). This has also been considered in single studies that, for example, investigated
2B. A. SIMONSMEIER ET AL.
Table 1. Characteristics of the previous four meta-analyses on mental practice.
Explicit inclusion and
.The only criterion was
that there be a group
that was given only
mental practice and
that this group have
either pretest scores or
a control group to
which be compared
no no Comparison
(no practice control
group with same
Performance 60 (146) .48 (.67) .Task type
.One condition mental
practice alone (mental/
physical practice group
.Provide the necessary
no no N/A .Direct
unrelated tasks in
Performance 21 (44) .68 (.11) .Type of
.Reported (or allowed
the retrieval of) tests of
performance under a
comparison with a no-
no no .Fail safe N .No-contact control
group (e.g. wait-list)
group (e.g. non-
Post-post Performance 35 (62) .527 .Duration of
Toth et al.
in mental practice with
no no .Fail-safe N
.Trim and ﬁll
Performance 37 (99) 0.419
.Type of task
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 3
Table 1. Continued.
Explicit inclusion and
those engaging in NO
.An explicit No-Practice
control group with
which to compare
mental practice group
.Studies in which the
mental practice group
mentally practice the
exact same task as the
one which they were
later expected to
control (e.g. quiet
4B. A. SIMONSMEIER ET AL.
the eﬀectieness of imagery on other outcomes such as anxiety or self-conﬁdence (e.g.
Callow et al., 2001; Hale & Whitehouse, 1998; Hammond et al., 2012). It is desriable to evalu-
ate the eﬀectiveness of imagery on outcomes other than performance (Wakeﬁeld & Smith,
2012) to obtain an overall picture of the eﬀectiveness of imagery interventions in sport. As
the previous meta-analyses did not consider other outcomes than performance, the eﬀect
of imagery on other outcomes is still unclear. To estimate the overall eﬀectiveness of
imagery, we included studies independent of the outcome assessed in the present
meta-analysis. In our classiﬁcation of outcomes, we followed models on imagery
(Cumming & Williams, 2013; Guillot & Collet, 2008; Martin et al., 1999) and distinguished
between performance outcomes, outcomes on strategies and problem solving, psycho-
logical outcomes including aﬀective and motivational outcomes, rehabilitation outcomes,
and psychological skills.
Second, imagery has emerged as a distinct research ﬁeld within the domain of sport
psychology and has signiﬁcantly grown since which led to detailed theories on imagery
(e.g. Cumming & Williams, 2013; Guillot & Collet, 2008; Holmes & Collins, 2001; Martin
et al., 1999). These models include many potential moderators, which have not been con-
sidered in the previous meta-analyses. For example, the Toth et al.’s(2020) meta-analysis
included a moderator analysis considering imagery modality, namely visual, kinesthetic,
and mixed imagery, while the imagery content has not been examined. To classify diﬀer-
ences in the imagery content, ﬁve major types have been proposed (Hall et al., 1998;
Paivio, 1985). These are (1) cognitive speciﬁc (CS; i.e. images of skills), (2) cognitive
general (CG; i.e. images of strategies), (3) motivational speciﬁc (MS, i.e. images of goals),
(4) motivational general-arousal (MG-A, i.e. images of arousal and aﬀect), and (5) motiva-
tional general-mastery (MG-M, i.e. imagery of cognitions including self-conﬁdence and
mental toughness). The cognitive functions are conceptually akin to the term motor
imagery (MI), as both involve the internal representation of motor skills without any cor-
responding body movements occurring (Guillot & Collet, 2008). For the purpose of the
current meta-analysis we included any type of imagery in the analyses and systematically
investigated their eﬀectiveness, respectively.
Third, previous meta-analyses demonstrated the eﬀectiveness of mental practice com-
pared to active and passive control groups without considering diﬀerences in the active
control groups (Feltz & Landers, 1983; Hinshaw, 1991)or compared mental practice to
active control groups without any practice components (Driskell et al., 1994; Toth et al.,
2020). In the ﬁeld of imagery reasearch, most commonly active control groups receive
physical practice (e.g. Guillot et al., 2010; O & Munroe-Chandler, 2008; Shackell & Standing,
2007; Spittle & Kremer, 2010), another sport psychological intervention (e.g. Gordon et al.,
1994; Kim et al., 2017), or another intervention, not related to the sports task (e.g. Robin
et al., 2007). More speciﬁcally, imagery combined with physical practice vs. a physical prac-
tice control group is a common form of the application of imagery in research and prac-
tical settings (e.g. Brouziyne & Molinaro, 2005; Frank et al., 2014; C. Wright & Smith, 2009)
but has not been considered in the previous meta-analyses. To extend the ﬁndings of the
previous meta-analyses and to estimate the eﬀectiveness of imagery compared to
diﬀerent control groups, the current meta-analysis included any kind of control group
and systematically investigated variations in the eﬀectiveness of imagery interventions.
Fourth, previous meta-analyses used diﬀerent types of comparisons to determine the
eﬀects of mental practice potentially leading to diﬀerent magnitudes in eﬀect sizes.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 5
While the previous meta-analyses included both, pre–post and post-post comparisons
(Feltz & Landers, 1983; Hinshaw, 1991), or post-post comparisons only (Driskell et al.,
1994), the most recent meta-analysis used pre–post gains to operalize the performance
change due to the mental practice (Toth et al., 2020). Until now, no systematic analysis inves-
tigating diﬀerences in the magnitude of eﬀect sizes due to variations in the type of compari-
son exists. Such an analysis is, however, useful to provide benchmark data allowing valid
comparisons across studies and a-priori sample size calculations (Moher et al., 1994; Schwei-
zer & Furley, 2016). We therefore invesigated the eﬀects of imagery interventions taking all
possible types of comparison into account and systematically investigating possible
Fifth, while all meta-analyses used current statistical methods for their analyses when
they were published, application of modern techniques of meta-analytic aggregation
can further extend the validly and generalizability of their ﬁndings. For example, all pre-
vious meta-analyses except for the Toth et al. (2020) meta-analysis ignored the distinction
between correlated designs and independent group designs. As such, conclusions
reached from the meta-analytic results must be questioned (Dunlap et al., 1996).
Further, all previous meta-analyses combined various eﬀect sizes per study. This is proble-
matic as ignoring covariance at the study level can result in biased standard errors and
conﬁdence interval coverage proportions (e.g. Van den Noortgate et al., 2013). Lastly,
none of the previous meta-analyses performed outlier analyses and only few analyses
regarding publication bias, possibly limiting the validity of the results. Novel techniques
of meta-analysis allow the inclusion of more than one eﬀect size per study by statistically
accounting for the dependency (e.g. Hedges et al., 2010) and enabling comprehensive
outlier and publication bias analyses (e.g. Viechtbauer & Cheung, 2010). In the present
meta-analysis, we tried to extend the results found in previous meta-analyses by using
robust methods for aggregating and analyzing the available data meta-analytically.
The present meta-analysis
Imagery is one of the most researched psychological skills within the ﬁeld of sport psychol-
ogy and is widely accepted in practical settings to enhance performance. Despite the con-
tribution of previous meta-analyses on the eﬀectiveness of mental practice on
performance, the quantitative summary of the existing empirical evidence on the
eﬀects of diﬀerent types of imagery interventions and the eﬀect on various outcomes
in sports is still outstanding. Further, eﬀects of methodical aspects, for example using
diﬀerent control groups and types of comparisons to determine the eﬀectiveness of
imagery, are not well understood yet. The present study aims to add to previous meta-ana-
lyses and to ﬁll this gap in the literature on imagery interventions in sports.
We a-priori formulated the following ﬁve research questions and hypotheses:
1. Is imagery eﬀective to enhance sport related outcomes and is the eﬀect causal? We
expect to ﬁnd a positive and causal eﬀect of imagery on sports related outcomes
2. Is imagery eﬀective when compared to a passive and an active control condition?
Moreover, is physical practice combined with imagery more eﬀective than physical
practice alone? We assume that the overall eﬀect of imagery interventions compared
6B. A. SIMONSMEIER ET AL.
to diﬀerent control conditions is positive (Hypothesis 2a) and that physical practice
combined with imagery is more eﬀective than physical practice alone (Hypothesis 2b).
3. Does the magnitude of the eﬀect of imagery vary due to diﬀerent comparisons
employed? We expect to ﬁnd a higher eﬀect for pre–post comparisons compared to
eﬀects for post-post and pre–post gains comparisons (Hypothesis 3).
4. Is imagery eﬀective to enhance performance and other sport speciﬁc outcomes? We
assume an eﬀectiveness of imagery on various outcomes (Hypothesis 4) (Guillot &
Collet, 2008; Martin et al., 1999).
5. Are diﬀerent types of imagery (equally) eﬀective? We assume to ﬁnd positive eﬀects for
all diﬀerent types of imagery and to obtain no diﬀerences between them in their eﬀec-
tiveness (Hypothesis 5).
Besides these main moderators, we included many others for exploratory moderator
analyses retrieved from models on imagery frequently discussed in the literature, for
example, imagery type, imagery perspective, temporal equivalence, the athletes age, or
the athletes expertise (Cumming & Williams, 2013; Guillot & Collet, 2008; Holmes &
Collins, 2001; Martin et al., 1999).
Literature search and study selection
We searched the title, abstract, and keywords of all articles in the literature database Psy-
cINFO and PubMed in January 2018 with the following search string: ((imagery interven-
tion OR imagery training OR mental training OR mental practice) AND (sport* OR athlete*)).
We limited the results to studies with human populations that had been published in a
peer-reviewed journal in English language. We did not limit the search to publication
years. The standardized search with the respective keyword combination and restrictions
provided 290 hits in total. We also identiﬁed relevant studies via hand search by looking
through references of published meta-analyses on mental practice and reviews on
imagery (Cooley et al., 2013; Driskell et al., 1994; Feltz & Landers, 1983; Hinshaw, 1991;
Schuster et al., 2011). The hand search identiﬁed 62 additional eligible studies. Following,
the systematic search and hand search resulted in 372 relevant hits for this meta-analysis.
Figure 1 summarizes the search process in a PRISMA ﬂow chart (Moher et al., 2009). We
accounted for publication bias by using visual and statistical methods (described in the
section Statistical Analyses below) instead of including unpublished studies. The quality
of unpublished studies is hard to assess, and researchers commonly obtain only a non-
representative set of unpublished studies, which does not increase the quality of the
meta-analytic results (Ferguson & Brannick, 2012; Rothstein & Bushman, 2012).
Inclusion of studies
Inclusion of studies followed four inclusion criteria: (1) The study reported quantitative
non-confounded data on eﬀects of an imagery intervention. The eﬀect could either
pertain to within or between comparisons. Therefore, single case studies, studies with
single subject designs and qualitative studies were excluded. We did not include
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 7
studies/eﬀect sizes comparing one imagery intervention to another imagery intervention
or eﬀect sizes where the treatment group diﬀered in more than the imagery implemen-
tation compared to the control group. Studies combining imagery with other mental strat-
egies were sampled, but only for comparison with studies using pure imagery
Figure 1. Flow chart of the literature search.
8B. A. SIMONSMEIER ET AL.
interventions. Studies were also excluded if they implemented preparatory imagery before
movement execution to extend the validity of the results by combining similar interven-
tions. (2) The imagery content/outcome had to be sports speciﬁc. (3) The eﬀects of the
imagery intervention had to pertain to measures assessed before and after the interven-
tion. Studies exclusively assessing online measures during imagery were excluded. (4) The
study had to report original empirical ﬁndings (i.e. not a re-analysis of already reported
ﬁndings or a review) to avoid double coding of eﬀect sizes.
Coding of studies occurred in two steps. First, all abstracts were screened by the ﬁrst
author to evaluate relevance for the present study. The third author independently screened
a random sample of 71 studies. The absolute intercoder agreement was 96%. Disagreements
were resolved by discussion. A total of 153 abstracts were classiﬁed as eligible for further
inspection of the full texts. Second, the 153 full texts were assessed for eligibility. The
second author coded all full texts; the ﬁrst and third authors coded half of the full texts,
respectively. Overall, 55 studies were identiﬁed as relevant for the present meta-analysis.
The intercoder agreement for the inclusion and exclusion of studies based on inspection
of the full texts was 91%. The overall intercoder agreement for the coding of all moderating
variables and eﬀect sizes was 88%. Disagreements were again resolved by discussion. The
studies included in the meta-analysis are listed in the Supplemental Materials. Whenever
data were missing to compute the eﬀect sizes of interest, we requested this information
from the authors of the paper by email. When the authors did not respond, we were not
able to include the respective study in the meta-analysis.
We coded all eﬀect sizes reported in the included studies and did not limit the number of
eﬀects included from each study, because studies using several groups, outcomes, or
measurement points frequently reported several relevant comparisons. To maximize com-
parability across studies, we coded the raw data (i.e. the means and standard deviations of
the outcome measures) instead of the reported eﬀect sizes whenever possible and com-
puted a standardized eﬀect size the same way for each study, as described in the Sup-
plemental Materials. For each included eﬀect, we coded the values of the moderators.
Preparation of eﬀect sizes
For each eﬀect, we computed the eﬀect size Cohen’sdfrom the coded raw data using
syntax (for more details, see the Supplemental Materials). For 61 eﬀect sizes, raw data
was not available. Instead, we included the reported Cohen’sdvalues or the transformed
-values, t-values, or F-values. We analyzed three diﬀerent types of comparisons (pre–
post, post-post, and pre–post gains comparisons) to estimate the overall eﬀectiveness
of imagery interventions which is described in the Supplemental Material in more details.
We performed a bare bones meta-analysis and did not statistically adjust the eﬀect sizes
for study artifacts (Schmidt & Hunter, 2015), as only few studies reported the reliabilities for
the employed measures. As sensitivity analyses, we performed the meta-analysis with and
without attenuation for study artefacts and with small sample correction calculating
Hedge’sginstead of Cohen’sd. The alternative approaches did not meaningfully
change the overall eﬀect sizes and moderating eﬀects.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 9
Before aggregation of data from single studies, we identiﬁed outliers using speciﬁc outlier
diagnostics for meta-analysis (Viechtbauer & Cheung, 2010). Based on the examination of
studentized deleted residuals, DFFITS values, Cook’s distances, and COVRATIO values (for
more details see Viechtbauer & Cheung, 2010), we removed two eﬀect sizes out of one
study (Afrouzeh et al., 2015).
Most of the included studies provided multiple eﬀect sizes for the eﬀects of an imagery
intervention. Consequently, eﬀect sizes were statistically dependent. We addressed this
problem by using robust variance estimation (RVE, Hedges et al., 2010; Tanner-Smith
et al., 2016; Tanner-Smith & Tipton, 2014). Random eﬀects statistical models were used
for all analysis (Raudenbush, 2009), to address the presumed heterogeneity of eﬀects.
First, we estimated a simple RVE meta-regression model to estimate the overall eﬀect of
imagery interventions. Second, to estimate the variability in the eﬀect size due to modera-
tor variables, we estimated a mixed-eﬀects RVE meta-regression model (for more details,
see the Supplemental Material). We used the robumeta package (Fisher & Tipton, 2014)in
the R statistical environment (R Core Team, 2008) for the analyses.
Meta-analyses can be subject to publication bias, which is a higher likelihood of signiﬁ-
cant results to be published which can in turn bias the overall eﬀect size when aggregating
across studies (Hunter & Schmidt, 2004; Polanin et al., 2016; Rothstein et al., 2005). We
approached this problem by analyzing the symmetry of the distribution around the
mean through visual inspection of funnel plots and computing Egger regressions (Egger
et al., 1997; Lau et al., 2006). Further, we performed trim-and-ﬁll analyses (Duval &
Tweedie, 2000) estimating the number of missing studies that might exist and the
eﬀect that these studies might have had on the overall meta-analytic eﬀect.
A total of 55 studies reporting 401 eﬀect sizes obtained with 1438 participants were
included in the ﬁnal meta-analysis. The studies were published between 1960 and 2018
with a median publication year of 2005. The sample size varied between 5 and 106 partici-
pants with a mean of 24.36 participants. The mean age of the participants in the individual
studies ranged from 9 to 40 with an overall mean age of 22 years. A screening of imagery
ability occurred in 44% of the studies. Participants in 2 of the 55 studies had prior experi-
ence with imagery.
Most eﬀect sizes were from randomized controlled trials (62%), followed by controlled
trials (26%), and pre–post comparisons (12%). Studies included outcomes of motor learn-
ing and performance (77%), psychological skills (11%), motivational outcomes (8%),
aﬀective outcomes (3%), and strategies and problem solving (2%).
Overall eﬀectiveness of imagery interventions
Table 2 summarizes all results of the meta-analysis. The meta-analytically obtained overall
eﬀect size based on 401 eﬀect sizes from 55 studies indicated a positive, medium, and
10 B. A. SIMONSMEIER ET AL.
statistically signiﬁcant eﬀect of imagery with Cohen’sd= 0.431, 95% CI [0.298, 0.563]. The
eﬀect was also signiﬁcantly positive for randomized controlled trials, indicating a causal
eﬀect of imagery with d= 0.254 (95% CI [0.179, 0.530]). The eﬀects of imagery were
evident in both post-tests and retention tests, indicating lasting changes due to the
The eﬀectiveness of imagery was signiﬁcantly better compared to a passive control
group (no intervention, no physical practice, d= 0.508, 95% CI [0.281, 0.735]) and an
active control group without physical practice (another intervention, no physical prac-
tice, d= 0.484, 95% CI [0.069, 0.898]). Imagery combined with physical practice was
more eﬀective than physical practice alone (d= .0156, 95% CI [0.002, 0.310]). We
repeated this analysis for motor outcomes only, which revealed the same result (d=
0.231, 95% CI [0.060, 0.402]). Overall, the eﬀects of imagery were comparable to the
eﬀects of physical practice (d= 0.125, 95% CI [−0.175, 0.431]). Moderation analyses
did not indicate any diﬀerences across the diﬀerent control conditions with F(7.38) =
0.404, p= .755.
Contributing Factors to the eﬀectiveness of imagery interventions
Regarding hypothesis 3, imagery was eﬀective to enhance motor learning and perform-
ance (d= 0.468, 95% CI [0.303, 0.633)], motivational outcomes (d= 0.348, 95% CI [0.033,
0.663)], and aﬀective outcomes (d= 0.269, 95% CI [0.001, 0.537)]. There were no signiﬁ-
cant diﬀerences in the magnitude of the eﬀect depending on the diﬀerent outcomes (F
(5.89) = 1.32, p= .353). Thus, the results provide evidence for our third hypothesis, indi-
cating the eﬀectiveness of imagery interventions for performance but also psychological
The eﬀectiveness of imagery interventions varied due to the employed comparison (F
(16.90) = 7.53, p= .005). The eﬀect was largest for pre–post comparisons (d= 0.934, 95%
CI [0.571, 1.300)], followed by post-post comparisons (d= 0.570, 95% CI [0.188, 0.953)],
and pre–post gains (d= 0.260, 95% CI [0.122, 0.398)]. We performed the same analyses
holding study characteristics constant. From the set of 32 studies and 278 eﬀect sizes,
results were comparable with the largest eﬀect for pre–post comparisons (d= 0.727,
95% CI [0.548, 0.906)], followed by post-post comparisons (d= 0.339, 95% CI [0.166,
0.511)], and pre–post gains (d= 0.232, 95% CI [0.097, 0.368)]. In summary, eﬀect sizes sig-
niﬁcantly vary in magnitude due to the employed comparison, as expected in our fourth
Few studies reported their employed imagery type, leading to insuﬃcient power to deter-
mine eﬀect sizes and moderation analyses. Whenever stated in the single studies, CS
imagery was implemented most commonly, followed by MG-M imagery, MG-A imagery,
and other types of imagery. Cognitive speciﬁc imagery was eﬀective to enhance sport
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 11
Table 2. Number of studies (j), Number of eﬀect sizes (k), Eﬀect size (d), 95% Conﬁdence interval,
measure of heterogeneity τ
, and signiﬁcance of the moderator analyses.
Coding Options j k d 95% CI τ
Methodological study characteristics
Study Design *
Randomized controlled trial 30 249 0.254 [0.179, 0.530] .202 ref
Controlled trial 16 104 0.347 [0.131, 0.564] .520 ns
Pre-Post 10 48 0.934 [0.571, 1.300] .164 **
Control group ns
No intervention, no physical practice control group 17 51 0.508 [0.281, 0.735] ns
No intervention, physical practice control group 25 153 0.138 [−0.045, 0.322] ref
Another intervention, no physical practice control group 9 42 0.484 [0.069, 0.898] ns
Another intervention, physical practice control group 10 107 0.488 [0.125, 0.851] ns
Pre-post gains 33 283 0.260 [0.122, 0.298] 0.267 ref
Post-post 11 61 0.570 [0.188, 0.953] 0.336 ns
Pre-post 10 48 0.934 [0.571, 1.300] 0.164 **
Retention Test ns
Yes 8 26 0.429 [0.252, 0.572] .236 ref
No 52 368 0.441 [0.252, 0.572] .337 ns
Outcome Category ns
Motor learning and performance 48 304 0.416 [0.272, 0.559] .273 ns
Strategies and problem solving 2 6 0.032 –– –
Aﬀective 6 13 0.269 [0.001, 0.537] .161 ref
Motivational 7 30 0.351 [0.003, 0.699] .151 ns
Psychological skills 6 44 0.583 [−0.362, 1.530] 1.013 *
Imagery intervention characteristics
Imagery Type –
CS 24 194 0.304 [0.135, 0.473] .186
MG-A 2 12 0.476 ––
MG-M 3 15 0.907 ––
Other 2 16 -.0148 ––
Archery 2 7 0.005 ––
Basketball 6 33 0.524 [0.026, 1.020] .104 ns
Cricket 2 64 0.190 ––
Darts 3 10 0.309 ––
Field hockey 2 5 2.170 ––
Figure Skating 2 33 0.297 ––
Fitness 8 55 0.161 [−0.219, 0.541] .219 ref
Golf 8 64 0.557 [0.144, 0.970] .322 ns
Gymnastics 3 14 0.455 ––
Soccer 3 21 0.265 ––
Yes 23 144 0.491 [0.239, 0.742] .264 ns
No 28 244 0.445 [0.289, 0.600] .334 ref
Duration [days] cont. 53 386 ns
Duration [minutes/session] cont. 33 284 ns
Number of sessions cont. 49 374 **
Number of trials cont. 28 159 ns
Modality of instruction ns
Read aloud 5 33 .201 ––
Audio tape 7 80 0.418 [−0.116, 0.952] . 211 ref
Inner self-talk 35 252 0.501 [0.303, 0.698] .391 ns
Various 3 17 0.433 ––
Practice 20 187 0.242 [0.080, 0.403] .171 ref
Outside of practice 16 98 0.611 [0.231, 0.992] .543 ns
Visual 5 14 0.450 ––
Kinesthetic 5 76 0.232 ––
Combination 28 163 0.507 [0.296, 0.718] .277
12 B. A. SIMONSMEIER ET AL.
speciﬁc outcomes with d= 0.304 (95% CI [0.135, 0.473)]. Due to the lack of studies and
resulting limited power, we were not able to perform any statistical analyses regarding
our ﬁfth hypothesis.
Of all included moderators, the only signiﬁcant moderator was the number of sessions of
the imagery training. The eﬀectiveness was signiﬁcantly higher the more sessions the
implementation included (F(18) = 11, p= .004). None of the other moderators reached sig-
niﬁcance, demonstrating a robust eﬀect of imagery across diﬀerent age groups, imagery
speciﬁcs, and settings.
Checks for publication bias
Visual inspection of the funnel plot (see Figure 2) for the study level (i.e. the average eﬀect
size of each study) and eﬀect size level (i.e. all 401 eﬀect sizes) and Egger regressions for
random eﬀects (Egger et al., 1997) did not indicate signiﬁcant asymmetry on study level
Table 2. Continued.
Coding Options j k d 95% CI τ
Given 23 183 0.440 [0.238, 0.642] .231 ref
Individual 20 150 0.538 [0.290, 0.787] .284 ns
Timing (Temporal equivalence) –
Yes 14 81 0.568 [0.214, 0.922] .350
No 3 67 0.045 ––
Mixed 3 9 0.439 ––
Stimulus-and-response propositions ns
yes 14 66 0.696 [0.286, 1.110] .414 ns
no 32 257 0.396 [0.235, 0.558] .306 ref
Internal 28 175 0.428 [0.251, 0.605] .185 ref
External 5 42 0.205 ––
Internal and External 3 65 0.392 ––
Individual 7 48 0.479 [−0.114, 1.070] .398 ns
Age cont. 40 281 ns
Age group ns
Children and Adolescents (7-18) 15 128 0.577 [0.313, 0.840] 0.260 ns
Adults (18 and older) 39 267 0.412 [0.252, 0.572] 0.311 ref
Mixed 2 6 −0.083 –– –
Sports Expertise ns
Novice 26 204 0.268 [0.155, 0.580] 0.322 ref
Recreational 10 69 0.552 [0.299, 0.806] 0.207 ns
Competitive 10 81 0.555 [0.185, 0.926] 0.390 ns
Professional 9 31 0.390 [0.030, 0.751] 0.239 ns
Various 3 16 ––––
Previous imagery experience –
Yes 2 12 0.268 ––
No 48 296 0.449 [0.311, 0.587] 4.350
Imagery ability –
Low to moderate 2 4 0.118 ––
Moderate to High 12 64 0.928 [0.551, 1.310] .364
Note: –: insuﬃcient number of data points for the analysis; ref: reference category; ns: not signiﬁcant, *p< .05, **p< .01.
Moderators without levels were used as continuous predictors in meta-regressions; all moderators with only one study
were omitted from this table.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 13
and eﬀect size level. Trim and ﬁll (Duval & Tweedie, 2000) did not indicate any missing
studies, keeping the results of the meta-analysis unchanged. The results suggest that
our ﬁndings are unlikely distorted by publication bias.
Eﬀectiveness of imagery interventions
The main goal of the meta-analysis was to extend previous meta-analyses on mental prac-
tice by examining the overall eﬀects of imagery on sport speciﬁc outcomes, its generaliz-
ability, and identifying relevant moderating variables. We summarize the results of the
meta-analysis in ﬁve key ﬁndings. First, imagery is eﬀective to enhance not only perform-
ance but also other sport speciﬁc outcomes. Second, imagery signiﬁcantly enhances the
eﬀects of physical practice. Third, the magnitude of eﬀect sizes vary across diﬀerent
types of comparisons. Fourth, imagery eﬀects are dosage speciﬁc. Fifth, there still exist
many gaps in the literature on imagery. While the diﬀerent theories and models include
a variety of variables proposed to be relevant for successful imagery interventions, empiri-
cal evidence of the relevance of these variables is lacking.
Figure 2. Funnel plots of the inverse standard error and the eﬀect size Cohens’s d for the eﬀect size
level (left) and the study level (right).
14 B. A. SIMONSMEIER ET AL.
Key ﬁnding 1
As expected, imagery was eﬀective to enhance sport speciﬁc outcomes with an overall
eﬀect size of d= 0.431. The obtained eﬀect size summarizing various sport speciﬁc out-
comes is comparable to previous meta-analyses on mental practice focusing on perform-
ance outcomes, which found eﬀect sizes of d= 0.527 (Driskell et al., 1994) and d= 0.419
(Toth et al., 2020). It is also comparable to the eﬀects from other meta-analyses investi-
gating eﬀects of psychological interventions on sports performance, such as goal
setting (Kyllo & Landers, 1995) or self-talk interventions (Hatzigeorgiadis et al., 2011).
The eﬀect of imagery is causal rather than correlation, as the eﬀect was still present in
randomized controlled trials holding third variables constant. The imagery was signiﬁ-
cantly more eﬀective compared to a passive control group and an active control group.
Results suggest a long-term eﬀect as the eﬀectiveness was demonstrated in retention
tests. It was further evident across a variety of diﬀerent participant, intervention, and
outcome characteristics, indicating a robust eﬀect of imagery across diﬀerent settings.
Key ﬁnding 2
Imagery combined with physical practice was more eﬀective than physical practice alone,
which follows the assumption that imagery enhances the eﬀects of physical practice (e.g.
Hall et al., 1992). From a theoretical perspective, imagery and physical practice share
similar neural substrate, although corresponding neural networks are not totally overlap-
ping (e.g. Decety et al., 1994; Gerardin et al., 2000; Guillot et al., 2008). More recently, it has
been discussed that combined mental and physical practice is superior to physical practice
alone as there might be diﬀerential inﬂuences of mental practice and physical practice
(e.g. Frank et al., 2016; Guillot et al., 2013). Another explanation might be that the com-
bined practice group had more practice trials as compared to the physical practice
group. However, when analyzing the eﬀectiveness of studies with equal practice trials
(e.g. imagery plus physical practice vs. physical practice plus a ﬁller task), the eﬀect of
imagery was still positive and signiﬁcant, both on motor tasks and other tasks. Therefore,
the results of the current meta-analysis also indicate diﬀerential inﬂuences of imagery and
physical practice. Furthermore, the diﬀerential eﬀects are likely to be found for both motor
performance and other sport speciﬁc outcomes such as psychological outcomes.
Key ﬁnding 3
We demonstrate that the magnitude of eﬀect size for imagery interventions diﬀers due to
the type of comparison. Our results highlight the relevance to account for diﬀerent com-
parisons, as pre–post eﬀects signiﬁcantly diﬀer from post-post eﬀects and pre–post gains.
The last comparison is most appropriate for intervention studies that focus on learning or
improvement in speciﬁc variables as it represents the change due to an intervention (e.g.
Hake, 1998; Nissen et al., 2018; R. H. Williams & Zimmerman, 1996). Studies aiming to inves-
tigate change in speciﬁc variables due to an imagery intervention should therefore report
gain scores whenever possible. Many studies reported the relevant information for the
computation of gains scores, but did not report the eﬀect size respectively. One reason
why studies do not report gain scores might be that gain scores were once thought to
have undesirable statistical characteristics, for example, chronically low reliabilities.
Newer studies, however, show that these conclusions are based on unrealistic statistical
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 15
assumptions and that gain scores can have acceptable validities and reliabilities under
more realistic assumptions (Maris, 1998; May & Hittner, 2010; Zimmermann & Williams,
Key ﬁnding 4
Eﬀects of imagery are dosage speciﬁc. Our results suggest that the more sessions
employed, the more eﬀective the imagery intervention. This result supports the results
from previous meta-analyses and reviews, also indicating dosage speciﬁceﬀects of
mental practice (Driskell et al., 1994; Hinshaw, 1991; Toth et al., 2020) and imagery inter-
ventions (Cooley et al., 2013). The results further support expertise theory, suggesting that
the time an individual is engaged in deliberate practice activities is monotonically related
to performance enhancements (Ericsson et al., 1993). Deliberate practice is any type of
practice activity with the aim to improve performance. Imagery has been described as
one form of deliberate practice in sport (Cumming & Hall, 2002). Given that imagery is
more eﬀective the more sessions employed, our ﬁndings provide evidence for the poten-
tial of imagery as one form of deliberate practice. However, the interventions of the single
studies were designed to ﬁnd positive and high eﬀects of imagery with the majority of the
studies following best practice strategies. As such, it is still unclear whether too much
imagery may lose its eﬀects.
Key ﬁnding 5
There still exist many gaps in research on imagery, resulting in an underrepresentation of
some moderators in our analyses. While theories and models include variables considered
relevant for imagery to be successful, their eﬀect remains to be determined. On a descrip-
tive level, we found great diﬀerences in the magnitude of eﬀect size regarding, for
example, imagery type, the participants’imagery ability or skill level, the employed per-
spective, or temporal equivalence of the imagery. However, we were not able to test
these diﬀerences statistically due to a small number of studies within one category.
One reason may be the complex nature of imagery and the large amount of diﬀerences
in the implementation. In turn, it needs a great amount of studies to test diﬀerences in
the eﬀectiveness caused by the speciﬁcs of imagery and implementation systematically.
To understand the impact of characteristics of the participants, the speciﬁcs of imagery
and the implementation strategies, more empirical investigations are needed that
thoroughly test the variety of variables of models on imagery (Cumming & Williams,
2013; Guillot & Collet, 2008; Holmes & Collins, 2001).
Directions for future research
In light of the current meta-analysis, at least three suggestions for future research can be
proposed. First, speciﬁcs of imagery greatly varied across studies, resulting in few studies
within each moderator category. To fully understand the eﬀectiveness of imagery and
under which condition imagery is most eﬀective, more research is needed that tests
assumptions of current models on imagery. The summary of previous studies in our
meta-analysis gives a comprehensive overview of remaining gaps in literature. For
example, future studies could investigate the eﬀects of imagery other than cognitive
speciﬁc imagery (e.g. Martin et al., 1999; Munroe-Chandler et al., 2012)ordiﬀerences in
16 B. A. SIMONSMEIER ET AL.
the eﬀectiveness of imagery due to participant characteristics, such as imagery ability (e.g.
S. E. Williams & Cumming, 2011) and expertise (Guillot et al., 2008; Simonsmeier et al.,
2018). Further, variations in the implementation, such as temporal equivalence or
imagery perspective (e.g. Cumming & Ste-Marie, 2001; Holmes & Collins, 2001) can be con-
sidered in future studies. Replication of existing results and extension of empirical evi-
dence is necessary to test whether the results generalize to other settings and other
Second, most of the outcomes related to motor performance. Only a few studies inves-
tigated the eﬀects of imagery on psychological skills, such as imagery use (e.g. Cumming &
Ste-Marie, 2001; Munroe-Chandler et al., 2005) and imagery ability (e.g. Cumming & Ste-
Marie, 2001; D. J. Wright et al., 2015), motivational outcomes (e.g. Martin & Hall, 1995;
Ramsey et al., 2010), or aﬀective outcomes (e.g. Mellalieu et al., 2009; Ramsey et al.,
2010). Future research may extend the understanding of the eﬀectiveness of imagery
by investigating eﬀects of imagery on other outcomes than performance.
Third, the quality of future studies and meta-analyses may be enhanced. This can be
achieved by critically deciding for a speciﬁc research design, control groups, comparison,
and reporting the procedure of an intervention more precisely (e.g. Goginsky & Collins,
1996). We had to exclude 90 studies for methodological reasons or reporting issues,
such as missing data (e.g. missing means or standard deviations) or confounding variables
(e.g. combination of imagery with other mental strategies). Researchers should conscien-
tiously decide on how they report characteristics of their studies to ensure replicability. In
our case, most imagery interventions were described incomplete, resulting in fewer eﬀect
sizes that could be included in moderator analyses as compared to the amount of eﬀect
sizes included in the general analysis.
Generalizability of the ﬁndings and conclusion
The medium positive eﬀect of imagery in sport speciﬁc outcomes reported in the present
meta-analysis can be interpreted as non-confounded eﬀects of imagery, as studies were
only included when the intervention and control condition only diﬀered in the implemen-
tation of imagery (e.g. imagery compared to no intervention) and nothing else (e.g. imagery
combined with physical practice compared to no intervention). As the eﬀect of imagery was
still signiﬁcant for randomized controlled trials, possible inﬂuences of third variables can be
ruled out. The eﬀects were robust as compared to passive control groups and active control
groups implementing another intervention. Further, eﬀects of imagery were evident in both
post-tests and retention tests, indicating lasting changes due to the intervention. In our
analysis, we accounted for publication bias and the dependencies of eﬀect sizes, and had
suﬃcient coding reliability to increase the validity of our ﬁndings.
Due to the great variety in the implementation of imagery interventions, some modera-
tors were underrepresented. For example, there is little evidence on the eﬀects of imagery
for participants with low imagery ability, professional athletes, or participants with imagery
experience. Similarly, only a few studies investigated the eﬀects of imagery types other
than cognitive speciﬁc imagery. Furthermore, some speciﬁc characteristics of the
imagery implementation were considered only in a few studies, for example, variations
in timing, the perspective, or the sensory modalities included. This resulted in limited
power for some analyses.
INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 17
Overall, imagery was conﬁrmed to be an eﬀective strategy for enhancing various out-
comes in sports. Furthermore, we identiﬁed moderators that could further explain the
eﬀects of imagery, enhance our knowledge regarding the eﬀectiveness of imagery inter-
ventions, and provide directions for future research. The medium eﬀect of imagery in
sport, as determined by the present meta-analysis, encourages the promotion and use
of imagery by athletes, sport educators, coaches, and sport psychologists. The obtained
data in this meta-analysis may serve as benchmark data for future studies with varying
designs (e.g. within or between comparisons) and comparisons (e.g. post-post compari-
sons or pre–post gain comparisons) and can be used for a-priori power analyses. As
such, we hope that this meta-analysis provides new and valuable insights into the
impact of imagery on various outcomes in sports.
No potential conﬂict of interest was reported by the author(s).
Bianca A. Simonsmeier http://orcid.org/0000-0002-2269-4838
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